**Meet the editors**

Associate Professor Dr Rustam B. Rustamov is an independent expert in space science and technology. He is the former Acting Director General of the Azerbaijan National Aerospace Agency. Rustam B. Rustamov has mainly specialized in space instrumentation, remote sensing, and GIS technology. He graduated with a PhD from the Russian Physical-Technical Institute (S. Peters-

burg) and was invited to work for the European Space Agency with the United Nations Program on Space Applications at the European Space Research and Technology Center, The Netherlands. Rustam B. Rustamov has been appointed to the United Nations Office for Outer Space Affairs Action Team (member, Austria), United Nations Economical and Social Commission for Asia and the Pacific (national focal point, Thailand), the International Astronautical Federation (Federation's contact, France), and the Recent Advances in Space Technologies International Conference Program Committee (member, Turkey). He is the author of nine books published in Europe and the United States, and more than 70 scientific papers.

Dr Saida E. Salahova is currently the head of company management processes for an engineering company. She attained her PhD with an emphasis on remote sensing, from the Institute for Space Research and Natural Resources at the Azerbaijan National Aerospace Agency. Dr. Saida S. Salahova's scientific and research interests have centered around remote sensing methods and data

processing, GIS technology application, natural disaster studies, and risk assessments, environmental monitoring, and impact evaluation. She has participated in several international events organized and conducted by the United Nations Office for Outer Space Affairs (UN OOSA) in co-operation with appropriate host countries. Dr. Saida S. Salahova is responsible, as the Group Chair, for the activities of the UN OOSA Disaster Management Working Group. The International Astronautical Federation (IAF) considered her contribution to the work of the IAF and named her the IAF 2009 Youth Program Grantee. She has published five books and is the author of a number of scientific papers.

### Contents

#### **Preface** XI


#### **Part 2 Approaches of Earth Observation Monitoring 61**


X Contents


Chapter 10 **Current Advances in Uncertainty Estimation of Earth Observation Products of Water Quality 229**  Mhd. Suhyb Salama

### Preface

Space science and technology applications are the key instruments in modern information and industrial society. Natural resources study, environmental monitoring, communication and TV reporting around the world, satellite navigation systems (GPS), and precise climate and weather analyses, all depend on space science and technology achievements.

There is no doubt that over the past 50 years, space observations of the Earth have accelerated the cross-disciplinary collection, analysis, interpretation, and, ultimately our understanding of the dynamic processes that govern the planet. Taking into account this momentum, we can assume that the next decades will bring more significant and remarkable discoveries, as well as the capability to predict Earth processes and reduce the impact of negative consequences in order to protect human lives and property.

Using space science and technology achievements and providing full and open access to international audiences capitalizes on the investment in satellite technology and creates a more interdisciplinary and integrated Earth science community. International data sharing and collaboration on satellite missions lessens the burden on individual nations to maintain Earth observational capacities.

Satellite Earth observations often reveal known phenomena and processes to be more complex than previously understood. Recently, a wide array of cases related to Earth study have become clearer thanks to space science and technology applications. This brings forth the indisputable benefits of multiple synergistic observations including orbital, suborbital, and in-situ measurements.

The valuable benefits of satellite observations of Earth are successfully realized only when the essential infrastructure, such as appropriate space data, models, computing facilities like software, ground networks, successful integration of both space and ground data, and trained personnel are in place. The scientific advances resulting from Earth observations from space illustrate the successful synergy between science and technology.

Innovative space technologies help us to monitor environmental protection agreements, forecast the impact of climate change, and deal with natural disaster.

#### XII Preface

Using a number of satellites for the daily synoptic global view of Earth, has revolutionized Earth studies greatly, and ushered in a new era of multidisciplinary Earth study sciences with an emphasis on dynamics at all accessible spatial and temporal scales, even in remote areas. This new capability plays a critically important role in helping society manage planetary-scale resources and environmental challenges.

There is no doubt that one of the most important and controversial uses of satellites today is that of the study and investigation of the Earth's surface environment. Many satellites study features on the ground, the behavior of the oceans, or the characteristics of the Earth's upper atmosphere. Satellites that observe the Earth to collect scientific data are usually referred to as "Earth observation satellites." Sometimes the interpretation of their data has been controversial because the interpretation is difficult and people have used the data to call for substantial changes in human behavior.

Today a huge of area of space technology is demonstrating evidence that it can be used as an excellent instrument in Earth observation applications. It is based on data collection using the satellite as well as other available platforms for remote sensing data..

Observations from space provide global and consistent measurements of the Earth at daily intervals or better; measurements which are not available by any other means. We use a sophisticated array of instruments, operating at all wavelengths of the electromagnetic spectrum, that can penetrate the atmosphere, including visible light, and ultraviolet, infrared and, microwave radiation.

Remote sensing data collection uses a wide range of electromagnetic energy which is emitting, transmitting, or reflecting from the Earth surface. Appropriate detection systems need to be implemented for further data processing.

The application of space technologies has been proven to play a key role in sustainable development, at national, regional, and global levels. Earth observation technologies and techniques are considered to be of great importance and to have great impact. Today, radar remote sensing is one of the new and modern Earth observation technologies with promising results and a promising future. It is an established technique for precise assessment of land surface movements, and generating high quality digital elevation models (DEM) from spaceborne and airborne data. Modern space technology technique is able to produce DEM with the precision of just tens of meters and its movement map results have sub-centimeter precision. The technique has many applications in the context of Earth sciences such as in topographic mapping, environmental modeling, rainfall-runoff studies, landslide hazard zonation, and seismic source modeling.

Space technology has been found to be a successful application for studying climate change, as it can compare dynamic processes using current and past data.

This book presents different aspects of Earth observation studies with the exploration and application of space science and technological achievements.

X Preface

challenges.

in human behavior.

data..

Using a number of satellites for the daily synoptic global view of Earth, has revolutionized Earth studies greatly, and ushered in a new era of multidisciplinary Earth study sciences with an emphasis on dynamics at all accessible spatial and temporal scales, even in remote areas. This new capability plays a critically important role in helping society manage planetary-scale resources and environmental

There is no doubt that one of the most important and controversial uses of satellites today is that of the study and investigation of the Earth's surface environment. Many satellites study features on the ground, the behavior of the oceans, or the characteristics of the Earth's upper atmosphere. Satellites that observe the Earth to collect scientific data are usually referred to as "Earth observation satellites." Sometimes the interpretation of their data has been controversial because the interpretation is difficult and people have used the data to call for substantial changes

Today a huge of area of space technology is demonstrating evidence that it can be used as an excellent instrument in Earth observation applications. It is based on data collection using the satellite as well as other available platforms for remote sensing

Observations from space provide global and consistent measurements of the Earth at daily intervals or better; measurements which are not available by any other means. We use a sophisticated array of instruments, operating at all wavelengths of the electromagnetic spectrum, that can penetrate the atmosphere, including visible light,

Remote sensing data collection uses a wide range of electromagnetic energy which is emitting, transmitting, or reflecting from the Earth surface. Appropriate detection

The application of space technologies has been proven to play a key role in sustainable development, at national, regional, and global levels. Earth observation technologies and techniques are considered to be of great importance and to have great impact. Today, radar remote sensing is one of the new and modern Earth observation technologies with promising results and a promising future. It is an established technique for precise assessment of land surface movements, and generating high quality digital elevation models (DEM) from spaceborne and airborne data. Modern space technology technique is able to produce DEM with the precision of just tens of meters and its movement map results have sub-centimeter precision. The technique has many applications in the context of Earth sciences such as in topographic mapping, environmental modeling, rainfall-runoff studies, landslide hazard zonation,

Space technology has been found to be a successful application for studying climate

change, as it can compare dynamic processes using current and past data.

and ultraviolet, infrared and, microwave radiation.

and seismic source modeling.

systems need to be implemented for further data processing.

**Dr. Rustam B. Rustamov** 

Institute of Physics, Azerbaijan National Academy of Sciences, Baku, Azerbaijan

> **Dr. Saida E. Salahova**  ENCOTEC –Engineering & Consulting Technologies, Baku, Azerbaijan

## **Part 1**

## **Earth Observation – Capability and Advances**

### **Earth Observation – Space Technology**

Rustam B. Rustamov, Saida E. Salahova, Maral H. Zeynalova and Sabina N. Hasanova *Institute of Physics, Azerbaijan National Academy of Sciences, ENCOTEC –Engineering & Consulting Technologies, Institute of Botany, Azerbaijan National Academy of Sciences, Architecture and Construction University/ENCOTEC LLC, Baku, Azerbaijan* 

#### **1. Introduction**

For monitoring of the Earth thousands of satellites have been sent into space on missions to collect data related different spheres of the Earth investigations and studies. Today, the ability to forecast weather, climate, and natural hazards, environmental monitoring and ecological issues depend critically on these satellite-based observations. Based on this data it is possible to gather satellite images frequently enough to create the model of the changing planet, improving the understanding of Earth's dynamic processes and helping society to manage limited resources and environmental challenges. Earth observations from space open and makes requirement to address scientific and societal challenges of the future.

Space technologies play the significant role in the sustainable development in national, regional and global level. Modern and advances of the Earth observation techniques are taking a great importance amongst existing traditional technologies. Radar remote sensing is one of the new Earth observation technologies with promising results and future. Interferometric SAR (InSAR) is a sophisticated radar remote sensing technique for combining synthetic aperture radar (SAR) complex images to form interferogram and utilizing its phase contribution to land topography, surface movement and target velocity. Presently considerable applications of InSAR technique are developed. It is an established technique for precise assessment of land surface movements and generating high quality digital elevation models (DEM) from spaceborne and airborne data. InSAR is able to produce DEM with the precision of a couple of ten meters whereas its movement map results have sub-centimeter precision. The technique has many applications in the context of Earth sciences such as in topographic mapping, environmental modeling, rainfall-runoff studies, landslide hazard zonation, and seismic source modeling.

Making observations of the land, sea and air from space allow scientists to develop and improve their models of the Earth. Space instruments provide continuous global measurements of the Earth for many years at a time. Currently this includes to consider following issues:


#### **2. Earth observation systems**

It is necessary to emphasize that one of the most important and controversial uses of satellites today is that of monitoring the Earth's environment. Many satellites study features on the ground, the behavior of the oceans, or the characteristics of the atmosphere. Satellites that observe the Earth to collect scientific data are usually referred to as "Earth observation satellites." Sometimes the interpretation of their data has been controversial because the interpretation is difficult and people have used the data to call for substantial changes in human behavior.

One of the popular satellite for Earth observation the Envisat is an advanced polar-orbiting Earth-observation satellite that provides measurements of the atmosphere, ocean, land and ice. It was launched in March 2002 on an Ariane 5 rocket into an 800km polar orbit by the European Space Agency (ESA). Originally was planned for five years, the life of Envisat has been extended till 2013.

It is necessary to mention that the satellite also helps scientists access data for analyzing long-term climatic changes.

The recent advances and developments in information and communication technologies, education and health care, agriculture and agro-food processing, geo-strategic initiatives, infrastructure and energy and critical technologies and strategic industries have been realized in light of the space technologies. Earth observation techniques which apply optical and thermal spectra of the electromagnetic wavelengths have so far developed considerably. Although there is done a lot in this area beforehand, a long way is still ahead. The background of using microwaves for remote sensing goes far the decades ago while it was remaining in the experimental domain and exploratory status for years. It is only in the recent couple of decades that radar remote sensing techniques have been commercialized and used widely. Radar remote sensing is actually accounted for as a new earth observation technology with promising results and future. Its potentials and capacities by itself and being a strong complementary tool for optical and thermal remote sensing are undeniable currently.

i. Radar and SAR techniques for remote sensing

Obviously, the use of radar systems opens a wide opportunity to reduce an obstacles existing in the traditionally used technologies. For the time being it became very interesting

Expertise in obtaining information on the surface and atmosphere using remote sensing

Expertise in and provision of facilities for generating archiving and distributing

Expertise in and facilities for characterizing spectral properties of environmental

Expertise in the technology and practice of remote sensing at mm and sub-mm

It is necessary to emphasize that one of the most important and controversial uses of satellites today is that of monitoring the Earth's environment. Many satellites study features on the ground, the behavior of the oceans, or the characteristics of the atmosphere. Satellites that observe the Earth to collect scientific data are usually referred to as "Earth observation satellites." Sometimes the interpretation of their data has been controversial because the interpretation is difficult and people have used the data to call for substantial changes in

One of the popular satellite for Earth observation the Envisat is an advanced polar-orbiting Earth-observation satellite that provides measurements of the atmosphere, ocean, land and ice. It was launched in March 2002 on an Ariane 5 rocket into an 800km polar orbit by the European Space Agency (ESA). Originally was planned for five years, the life of Envisat has

It is necessary to mention that the satellite also helps scientists access data for analyzing

The recent advances and developments in information and communication technologies, education and health care, agriculture and agro-food processing, geo-strategic initiatives, infrastructure and energy and critical technologies and strategic industries have been realized in light of the space technologies. Earth observation techniques which apply optical and thermal spectra of the electromagnetic wavelengths have so far developed considerably. Although there is done a lot in this area beforehand, a long way is still ahead. The background of using microwaves for remote sensing goes far the decades ago while it was remaining in the experimental domain and exploratory status for years. It is only in the recent couple of decades that radar remote sensing techniques have been commercialized and used widely. Radar remote sensing is actually accounted for as a new earth observation technology with promising results and future. Its potentials and capacities by itself and being a strong

complementary tool for optical and thermal remote sensing are undeniable currently.

Obviously, the use of radar systems opens a wide opportunity to reduce an obstacles existing in the traditionally used technologies. For the time being it became very interesting

i. Radar and SAR techniques for remote sensing

methods;

components;

wavelengths;

human behavior.

been extended till 2013.

long-term climatic changes.

environmental data;

**2. Earth observation systems** 

Expertise in modeling environmental phenomena;

Expertise in and facilities for atmospheric research using radars;

Developing e-science applications in environmental research.

Carrying out a program of research in aspects of environmental science;

and important explorations and examining a new radar technologies, their unique possibilities to comply the needs and answering the questions that the classic optical and thermal remote sensing techniques have been unable or difficult to tackle has grown the expectation that radar technologies can take place due to a more flexibility in bridging the gaps for sustainable development for which the optical and thermal remote sensing is an important tool while the latter techniques show shortage in some cases and areas.

Currently, radar remote sensing that is mainly developed on the Synthetic Aperture Radar (SAR) technique represents its values and potentials increasingly. Radar is a useful tool for land and planetary surface mapping. It is a good mean for obtaining a general idea of the geological setting of the area before proceeding for field work. Time, incidence angle, resolutions and coverage area all play important role at the outcome.

ii. InSAR techniques

SAR interferometry (InSAR), Differential InSAR (DInSAR), Persistent Scatterer (PSInSAR) is the a new achieved techniques in radar remote sensing systems. By using InSAR technique very precise digital elevation models (DEM) can be produced which privilege is high precision in comparison to the traditionally used methods. DEM refers to the process of demonstrating terrain elevation characteristics in 3-D space, but very often it specifically means the raster or regular grid of spot heights. DEM is the simplest form of digital representation of topography, while digital surface model (DSM) describes the visible surface of the Earth.

Considerable applications of InSAR have been developed leaving it an established technique for high-quality DEM generation from spaceborne and airborne data and that it has advantages over other methods for the large-area DEM generation. It is capable of producing DEMs with the precision of a couple of ten meters while its movement map results have sub-centimeter precision over time spans of days to years. Terrestrial use of InSAR for DEM generation was first reported in 1974. It is used for different means particularly in geo-hazards and disasters like earthquakes, volcanoes, landslides and land subsidence.

#### **2.1 Earth observation satellites**

The first satellite to be used for Earth observation purposes was Explorer VII, launched in October 1959. This satellite was equipped with an infrared sensor designed to measure the amount of heat reflected by the Earth. This measurement, referred to as the "radiation budget," is a key to understanding global environmental trends, for it represents the difference between the amount of incoming energy from the sun and the outgoing thermal and reflected energy from the Earth. But it was not until the launch of the Earth Radiation Budget Satellite (ERBS) in 1984 by the National Aeronautics and Space Administration (NASA) that more authoritative readings of this important figure were obtained. Many Earth observation satellites like ERBS use specialized sensors that operate in non-visible wavelengths like the infrared, allowing them to gather data on many different types of atmospheric and ground phenomena.

The most important early Earth observation satellites were members of the Nimbus series. NASA launched eight Nimbus satellites between 1964 and 1978, with only one failing to reach orbit. Although they started out as part of the weather satellite program, the Nimbus satellites were not weather satellites, but carried a number of instruments for measuring the temperature and humidity of the atmosphere. This was a major advance, for earlier weather satellites like Tiros (Television Infrared Observation Satellite) had only been capable of taking visible light photographs of clouds and could not provide the kinds of traditional weather measurements that meteorologists normally used. Eventually many of the instruments demonstrated on Nimbus, named "sounders," were incorporated into later weather satellites. Atmospheric sounders are now common on many meteorological satellites, as well as on scientific satellites and even planetary space probes (Belew & Stuhlinger, 1973) , (Covault, 1991).

In July 1972, NASA launched the Earth Resources Technology Satellite (ERTS-1) into orbit. ERTS-1 used advanced instruments to view the Earth's surface in several infrared wavelengths. These sensors enabled scientists to assess vegetation growth, monitor the spread of cities, and make many other measurements of how the Earth's surface was changing. ERTS was so successful that it was followed by two more satellites named Landsat. By the early 1980s, with the launch of Landsat 4, the satellites became an "operational" system rather than an experimental one and their data was heavily used around the world by farmers, urban planners, geologists and environmentalists. Landsat and similar satellites are often referred to as "remote sensing satellites," a term that is usually used to refer to satellites that focus on the ground rather than the oceans or atmosphere.

In the mid 1970s NASA also conducted numerous observation experiments aboard the Skylab space station. Skylab was equipped with handheld as well as fixed cameras using special film. It also had an array of other instruments. Data the crews obtained during their three visits to Skylab was used to refine the instruments on other satellites, such as Landsat. Skylab also demonstrated the value of other observations, such as tracking icebergs and the breakup of sea ice (Skylab, 1977) .

In 1978 NASA launched SeaSat, an ocean observation satellite with a synthetic aperture radar, or SAR. SAR works by taking several radar images from different positions and combining them to produce a more detailed single image. SeaSat's radar produced detailed images of the surface of the ocean, providing valuable data on waves and the interaction of the ocean's surface with the winds. Although SeaSat's mission ended prematurely due to a malfunction, it demonstrated the immense value of space-based SARs.

Approximately around the same time the United States was experimenting with SeaSat, the Soviet Union launched a similar series of satellites known as Okean. Later, during the late 1980s, the Soviet Union orbited several large radar satellites. These spacecraft, launched aboard Proton rockets, produced radar maps of the Earth's surface and were also used to measure waves on the oceans' surface. In 1991 the Soviet Union launched Almaz-1, which was another of this series of satellites but the first that the Soviet government openly acknowledged. Although they announced that this was a civilian Earth observation satellite and sought international customers, many experts speculated about the military uses of these satellites and their role in searching for objects such as submarines, which can create waves on the ocean surface when traveling at high speed at shallow depths. Because such data has military uses, SAR technology has always been sensitive. Although the Soviets

reach orbit. Although they started out as part of the weather satellite program, the Nimbus satellites were not weather satellites, but carried a number of instruments for measuring the temperature and humidity of the atmosphere. This was a major advance, for earlier weather satellites like Tiros (Television Infrared Observation Satellite) had only been capable of taking visible light photographs of clouds and could not provide the kinds of traditional weather measurements that meteorologists normally used. Eventually many of the instruments demonstrated on Nimbus, named "sounders," were incorporated into later weather satellites. Atmospheric sounders are now common on many meteorological satellites, as well as on scientific satellites and even planetary space probes (Belew &

In July 1972, NASA launched the Earth Resources Technology Satellite (ERTS-1) into orbit. ERTS-1 used advanced instruments to view the Earth's surface in several infrared wavelengths. These sensors enabled scientists to assess vegetation growth, monitor the spread of cities, and make many other measurements of how the Earth's surface was changing. ERTS was so successful that it was followed by two more satellites named Landsat. By the early 1980s, with the launch of Landsat 4, the satellites became an "operational" system rather than an experimental one and their data was heavily used around the world by farmers, urban planners, geologists and environmentalists. Landsat and similar satellites are often referred to as "remote sensing satellites," a term that is usually used to refer to satellites that focus on the ground rather than the oceans or

In the mid 1970s NASA also conducted numerous observation experiments aboard the Skylab space station. Skylab was equipped with handheld as well as fixed cameras using special film. It also had an array of other instruments. Data the crews obtained during their three visits to Skylab was used to refine the instruments on other satellites, such as Landsat. Skylab also demonstrated the value of other observations, such as tracking icebergs and the

In 1978 NASA launched SeaSat, an ocean observation satellite with a synthetic aperture radar, or SAR. SAR works by taking several radar images from different positions and combining them to produce a more detailed single image. SeaSat's radar produced detailed images of the surface of the ocean, providing valuable data on waves and the interaction of the ocean's surface with the winds. Although SeaSat's mission ended prematurely due to a

Approximately around the same time the United States was experimenting with SeaSat, the Soviet Union launched a similar series of satellites known as Okean. Later, during the late 1980s, the Soviet Union orbited several large radar satellites. These spacecraft, launched aboard Proton rockets, produced radar maps of the Earth's surface and were also used to measure waves on the oceans' surface. In 1991 the Soviet Union launched Almaz-1, which was another of this series of satellites but the first that the Soviet government openly acknowledged. Although they announced that this was a civilian Earth observation satellite and sought international customers, many experts speculated about the military uses of these satellites and their role in searching for objects such as submarines, which can create waves on the ocean surface when traveling at high speed at shallow depths. Because such data has military uses, SAR technology has always been sensitive. Although the Soviets

malfunction, it demonstrated the immense value of space-based SARs.

Stuhlinger, 1973) , (Covault, 1991).

breakup of sea ice (Skylab, 1977) .

atmosphere.

attracted the attention of western military officials, they found no commercial customers for their satellite (SeaWifs projects)**.** 

During the 1980s, and 1990s NASA, along with German and Italian participants, conducted several Space Shuttle missions carrying a large SAR in the Shuttle's payload bay. This radar, called SIR (for Shuttle Imaging Radar) produced topographical maps of much of the Earth's surface. The radar equipment was modified several times to collect more accurate data during the latter missions. In February 2000, NASA flew another mission called SRTM, for Shuttle Radar Topography Mission (SRTM), with Italian and German participation. This time NASA used a modified version of the radar capable of obtaining much more precise altitude data. Three-dimensional electronic maps produced from the SRTM data are highly accurate and can be used in aviation to guide aircraft and missiles, even over rough terrain like mountain ranges. In 1991 and again in 1995, the European Space Agency launched the ERS-1 and ERS-2 (European Remote Sensing) satellites. Both were equipped with SARs and were highly successful **[1].** 

In 1988 astronaut Dr. Sally Ride led a committee to evaluate America's future in space (Ride, 1987). One of her suggestions was that NASA focus more attention on environmental monitoring in response to increasing scientific discussion of global climate change, a program the agency called Mission to Planet Earth. As a result, NASA started the Earth Observing System (EOS). At the turn of the century, a number of EOS satellites were launched, most importantly Terra and Aqua, to be followed by Aqua's sister-satellite Aura. Terra, as its name implies, is focused upon monitoring the Earth's surface. It is equipped with instruments like MOPITT, the Measurements of Pollution in the Troposphere, and MISR, the Multi-Angle Imaging Spectroradiometer. Aqua has instruments such as microwave, infrared, and humidity sounders. These provide information on clouds, precipitation, snow, sea ice, and sea surface temperature.

In 1992, an Ariane 42P rocket launched a spacecraft named Topex/Poseidon. A joint French space agency (CNES-Centre National d'Etudes Spatiales) and NASA spacecraft, it was equipped with a radar altimeter to allow it to measure ocean topography, or surface features. Data gathered from Topex/Poseidon over years of operation have allowed scientists to accurately map ocean circulation, a key factor in understanding both global weather and climate change. In particular, Topex/Poseidon has been able to track the phenomenon known as El Niсo, a warming of the ocean surface off the western coast of South America that occurs every four to twelve years. El Niсo affects weather patterns in various parts of the world as well as fish and plankton populations. Another spacecraft, called SeaStar and carrying the Sea-viewing Wide Field-of-view Sensor, or SeaWiFs, was launched in 1997 to study biological organisms in the oceans such as algae and phytoplankton (microscopic marine plants).

In 2002, the European Space Agency launched a large environmental monitoring satellite named Envisat, aboard an Ariane 5 rocket. Envisat, the successor to ERS-1 and 2, is designed to take simultaneous readings of various atmospheric and terrestrial features and contribute to understanding of global change. The data from satellites like Envisat is used to develop complex computer models of how the Earth's environment works and how human activities, like burning down forests or operating automobiles, affects the environment.

For successful Earth observation issues sustainable development can be defined as maintaining a delicate balance between the human need to improve lifestyles and feeling of well-being on one hand, and preserving natural resources and ecosystems, on which we and future generations depend (Parviz, 2010).

In general the seven dimensions including spiritual, human, social, cultural, political, economic and ecological can be considered for the sustainable development where the main components are economy, society and environment. Approaching sustainable development requires establishing a continuous balance between three latter components. An effectiveness of the space technology applications on the environmental, economical and social issues are quite apparent. The recent developments in information and communication technologies, education and health care, agriculture and agro-food processing, geo-strategic initiatives, infrastructure and energy, and critical technologies and strategic industries, construction, engineering and engineering management have been realized in light of the space technologies. Earth observation techniques are considered of great importance amongst these technologies. Earth observation techniques which apply optical and thermal spectra of the electromagnetic wavelengths have so far developed considerably. Although there is done a lot in this area beforehand, a long way is still ahead. The background of using microwaves for remote sensing goes far the decades ago while it was remaining in the experimental domain and exploratory status for years. It is only in the recent couple of decades that radar remote sensing techniques have been commercialized and used widely. Radar remote sensing is actually accounted for as a new earth observation technology with promising results and future. Its potentials and capacities by itself and being a strong complementary tool for optical and thermal remote sensing are undeniable currently.

#### **2.2 Application of radar remote sensing and SAR techniques**

As it was previously indicated InSAR is a sophisticated processing of radar data for combining synthetic aperture radar (SAR) single look complex (SLC) images to form interferogram and utilizing its phase contribution to generate DEM, surface deformation and movement maps and target velocity. The interferogram contains phase difference of two images to which the imaging geometry, topography, surface displacement, atmospheric change and noise are the contributing factors.

Satellite-based InSAR began in the 1980s using Seasat data, although the technique's potential was expanded in the 1990s with launch of ERS-1 (1991), JERS-1 (1992), Radarsat-1 and ERS-2 (1995). They provided the stable well-defined orbits and short baselines necessary for InSAR. The 11-day NASA STS-99 mission in February 2000 used two SAR antennas with 60-m separation to collect data for the Shuttle Radar Topography Mission (SRTM). As a successor to ERS, in 2002 ESA launched the Advanced SAR (ASAR) aboard Envisat. Majority of InSAR systems has utilized the C-band sensors, but recent missions like ALOS PALSAR and TerraSAR-X are using L- and X-band. ERS and Radarsat use the frequency of 5.375GHz for instance. Numerous InSAR processing packages are also used commonly. IMAGINE-InSAR, EarthView-InSAR, ROI-PAC, DORIS, SAR-e2, Gamma, SARscape, Pulsar, IDIOT and DIAPASON are common for interferometry and DEM generation.

It is obvious that digital elevation model (DEM) is important for surveying and other applications in engineering. Its accuracy is paramount; for some applications high accuracy does not matter but for some others it does. Numerous DEM generation techniques with different accuracies for various means are used. DEMs can be generated through different methods which are classified in three groups that are DEM generation by:


8 Earth Observation

For successful Earth observation issues sustainable development can be defined as maintaining a delicate balance between the human need to improve lifestyles and feeling of well-being on one hand, and preserving natural resources and ecosystems, on which we and

In general the seven dimensions including spiritual, human, social, cultural, political, economic and ecological can be considered for the sustainable development where the main components are economy, society and environment. Approaching sustainable development requires establishing a continuous balance between three latter components. An effectiveness of the space technology applications on the environmental, economical and social issues are quite apparent. The recent developments in information and communication technologies, education and health care, agriculture and agro-food processing, geo-strategic initiatives, infrastructure and energy, and critical technologies and strategic industries, construction, engineering and engineering management have been realized in light of the space technologies. Earth observation techniques are considered of great importance amongst these technologies. Earth observation techniques which apply optical and thermal spectra of the electromagnetic wavelengths have so far developed considerably. Although there is done a lot in this area beforehand, a long way is still ahead. The background of using microwaves for remote sensing goes far the decades ago while it was remaining in the experimental domain and exploratory status for years. It is only in the recent couple of decades that radar remote sensing techniques have been commercialized and used widely. Radar remote sensing is actually accounted for as a new earth observation technology with promising results and future. Its potentials and capacities by itself and being a strong complementary tool for optical

As it was previously indicated InSAR is a sophisticated processing of radar data for combining synthetic aperture radar (SAR) single look complex (SLC) images to form interferogram and utilizing its phase contribution to generate DEM, surface deformation and movement maps and target velocity. The interferogram contains phase difference of two images to which the imaging geometry, topography, surface displacement, atmospheric

Satellite-based InSAR began in the 1980s using Seasat data, although the technique's potential was expanded in the 1990s with launch of ERS-1 (1991), JERS-1 (1992), Radarsat-1 and ERS-2 (1995). They provided the stable well-defined orbits and short baselines necessary for InSAR. The 11-day NASA STS-99 mission in February 2000 used two SAR antennas with 60-m separation to collect data for the Shuttle Radar Topography Mission (SRTM). As a successor to ERS, in 2002 ESA launched the Advanced SAR (ASAR) aboard Envisat. Majority of InSAR systems has utilized the C-band sensors, but recent missions like ALOS PALSAR and TerraSAR-X are using L- and X-band. ERS and Radarsat use the frequency of 5.375GHz for instance. Numerous InSAR processing packages are also used commonly. IMAGINE-InSAR, EarthView-InSAR, ROI-PAC, DORIS, SAR-e2, Gamma, SARscape, Pulsar, IDIOT and DIAPASON are common for interferometry and DEM

It is obvious that digital elevation model (DEM) is important for surveying and other applications in engineering. Its accuracy is paramount; for some applications high accuracy

future generations depend (Parviz, 2010).

and thermal remote sensing are undeniable currently.

change and noise are the contributing factors.

generation.

**2.2 Application of radar remote sensing and SAR techniques** 

In DEM generation by geodesic measurements, the planimetric coordinates and height values of each point of the feature are summed point-by-point and using the acquired data the topographic maps are generated with contour lines. The 1:25000-scale topographic maps are common example. The method uses contour-grid transfer to turn the vector data from the maps into digital data. For DEM generation by photogrammetry, the photographs are taken from an aircraft or spacecraft and evaluated as stereo-pairs and consequently 3-D height information is obtained.

DEM generation by remote sensing can be made in some ways, including stereo-pairs, laser scanning (LIDAR) and InSAR. There are three types of InSAR technique that is single-pass, double-pass and three-pass. In double-pass InSAR, a single SAR instrument passes over the same area two times while through the differences between these observations, height can be extracted. In three-pass interferometry (or DInSAR) the obtained interferogram of a double-pass InSAR for the commonly tandem image pairs is subtracted from the third image with wider temporal baseline respective to the two other images. In single-pass InSAR, space-craft has two SAR instrument aboard which acquire data for same area from different view angles at the same time. With single-pass, third dimension can be extracted and the phase difference between the first and second radar imaging instruments give the height value of the point of interest with some mathematical method. SRTM used the singlepass interferometry technique in C- and X-band. Earth's height model generated by InSAR-SRTM with 90-m horizontal resolution is available while the DEM with 4-to-4.5-m relative accuracy is also available for restricted areas around the world.

InSAR ability to generate topographic and displacement maps in wide applications like earthquakes, mining, landslide, volcanoes has been proven. Although other facilities like GPS, total stations, laser altimeters are also used, comparison between InSAR and these tools reveals its reliability. Laser altimeters can generate high resolution DEM and low resolution displacement maps in contrary to InSAR with the spatial resolution of 25m. However, most laser altimeters record narrow swaths. Therefore, for constructing a DEM by laser altimeter, more overlapping images are required. Displacement map precision obtained by terrestrial surveying using GPS and total stations is similar or better than InSAR. GPS generally provides better estimation of horizontal displacement and with permanent benchmarks slow deformations is monitored for years without being concerned about surface de-correlation. The most important advantage of InSAR over GPS and total stations are wide continuous coverage with no need for fieldwork. Therefore, wide and continuous coverage, high precision, cost effectiveness and feasibility of recording data in all weather conditions are its main privileges. However, it is important that the InSAR displacement result is in the line-ofthe-sight direction and to decompose this vector to parallel and normal components the terrestrial data or extra interferograms with different imaging geometry are required. It is shown that DEM generated by photogrammetric method is more accurate than the others. It has approximately 5.5m accuracy for open and 6.5m for forest areas. SRTM X-band DSM is 4m less accurate for open and 4.5m less accurate for forest areas.

Data availability and atmospheric effects limit using InSAR, however processing of its data is challenging. For each selected image pair, several processing steps have to be performed. One of the current challenges is to bring the techniques to a level where DEM generation can be performed on an operational basis. This is important not only for commercial exploitation of InSAR data, but also for many government and scientific applications. Multi pass interferometry is affected by the atmospheric effects. Spatial and temporal changes due to the 20% of relative humidity produce an error of 10cm in deformation. Moreover, for the image pairs with inappropriate baseline the error introduced to the topographic maps is almost 100m. In topographic mapping this error can be reduced by choosing interferometric pairs with relatively long baselines, while in the displacement case the solution is to average independent interferograms.

**InSAR DEM advantages:** Distinction between SAR imaging and the optical systems are more profound than the ability of SAR to operate in conditions that would cause optical instruments to fail. There are basic differences in the physical principles dominating the two approaches. Optical sensors record the intensity of radiation beamed from the sun and reflected from the features. The intensity of the detected light characterizes each element of the resulting image or pixel. SAR antenna illuminates its target with coherent radiation. Since the crests and troughs of the emitted electromagnetic wave follow a regular sinusoidal pattern, both the intensity and the phase of returned waves can be measured.

InSAR has some similarities to stereo-optical imaging in that two images of the common area, viewed from different angles, are appropriately combined to extract the topographic information. The main difference between interferometry and stereo imaging is the way to obtain topography from stereo-optical images. Distance information is inherent in SAR data that enables the automatic generation of topography through interferometry. In other words DEMs can be generated by SAR interferometry with greater automation and less errors than optical techniques. Moreover, using DInSAR surface deformations can be measured accurately.

Different DEM generation methods of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) stereoscopy, ERS tandem InSAR, and SRTM-InSAR are used. Both the ERS-InSAR and SRTM DEMs are free of weather conditions, but ASTER DEM quality may be affected by cloud coverage in some local areas. InSAR has the potential of providing DEMs with 1-10cm accuracy, which can be improved to millimeter level by DInSAR. Its developments are rapid however it is our requirements that say which one is better for use.

#### **2.2.1 Earth observation for river flood issues**

Rivers of Azerbaijan can be divided into the three main groups regarding their water flow specifications:


has approximately 5.5m accuracy for open and 6.5m for forest areas. SRTM X-band DSM is 4m

Data availability and atmospheric effects limit using InSAR, however processing of its data is challenging. For each selected image pair, several processing steps have to be performed. One of the current challenges is to bring the techniques to a level where DEM generation can be performed on an operational basis. This is important not only for commercial exploitation of InSAR data, but also for many government and scientific applications. Multi pass interferometry is affected by the atmospheric effects. Spatial and temporal changes due to the 20% of relative humidity produce an error of 10cm in deformation. Moreover, for the image pairs with inappropriate baseline the error introduced to the topographic maps is almost 100m. In topographic mapping this error can be reduced by choosing interferometric pairs with relatively long baselines, while in the displacement case the solution is to average

**InSAR DEM advantages:** Distinction between SAR imaging and the optical systems are more profound than the ability of SAR to operate in conditions that would cause optical instruments to fail. There are basic differences in the physical principles dominating the two approaches. Optical sensors record the intensity of radiation beamed from the sun and reflected from the features. The intensity of the detected light characterizes each element of the resulting image or pixel. SAR antenna illuminates its target with coherent radiation. Since the crests and troughs of the emitted electromagnetic wave follow a regular sinusoidal

InSAR has some similarities to stereo-optical imaging in that two images of the common area, viewed from different angles, are appropriately combined to extract the topographic information. The main difference between interferometry and stereo imaging is the way to obtain topography from stereo-optical images. Distance information is inherent in SAR data that enables the automatic generation of topography through interferometry. In other words DEMs can be generated by SAR interferometry with greater automation and less errors than optical techniques. Moreover, using DInSAR surface deformations can be measured

Different DEM generation methods of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) stereoscopy, ERS tandem InSAR, and SRTM-InSAR are used. Both the ERS-InSAR and SRTM DEMs are free of weather conditions, but ASTER DEM quality may be affected by cloud coverage in some local areas. InSAR has the potential of providing DEMs with 1-10cm accuracy, which can be improved to millimeter level by DInSAR. Its developments are rapid however it is our requirements that say which one is

Rivers of Azerbaijan can be divided into the three main groups regarding their water flow

2. Seasonal rivers that flow only during the melting of snow in spring;

3. Episodic rivers that flow in episodes after a downpour of rain of flash flood.

pattern, both the intensity and the phase of returned waves can be measured.

less accurate for open and 4.5m less accurate for forest areas.

independent interferograms.

accurately.

better for use.

specifications:

1. Perennial rivers;

**2.2.1 Earth observation for river flood issues** 

These three groups differ from each other for the volume of underwater supply to their streams. Perennial rivers are fed by a constantly flowing baseflow (groundwater). Seasonal rivers are fed by an elevated water table during the rainy period, while episodic rivers are not at all dependent on base flow.

Like in all other countries, rivers have different feeding sources in Azerbaijan. Most rivers are fed by snow, rainfalls and ground waters. Snow is the predominant feeding source for the rivers of the Major Caucasus, while ground waters contribute the most to water supply of rivers in the Minor Caucasus. The Kur and Araz rivers pass Azerbaijan in their lower and middle courses.

The Kura river is the largest river of Azerbaijan. It stretches for 1,515 kilometers and covers an area of 188 thousand sq. km. The Kura originates from the Hel River in Turkey, passes through Azerbaijan and flows into the Caspian Sea in south-eastern part of the country. The Araz River covers an area of 86 thousand sq. km until its junction with the Kura River. It originates from the Bingol mountains in Turkey at the altitude of 3300 meters. On the whole, the Araz River forms Azerbaijan's border with Turkey and Iran. It passes through Azerbaijan in its lower 80 kilometers and joins the Kura River near Sabirabad. These two rivers belong to the group of rivers, flowing at full under the influence of snow and rainfalls in spring and rainfalls in autumn.

Weather produces the greatest impact on the river flow in Azerbaijan. Intensive rise in temperature causes melting of snow at heights of over 1500. The melting of snow further intensifies after heavy rainfalls of April and May. Snow melts more intensively in the high altitudes (over 2500-3000 meters) from early April through May until June. The melting process influences river flow even in summer time. Thus, melted snow water, absorbed by soil, emerges on the surface and raises water level in rivers. Low river basins (except for those of the Talysh region) are less influenced by the precipitation in spring and summer periods. Winter and autumn rainfalls account for the most part of precipitations in the Talysh region. Rivers are less full of water in summer in Azerbaijan. Heavy rainfalls that may from time to time occur in July and August, lead to floods, causing agricultural damages. Severe floods have been registered in the rivers of southwestern slopes of Major Caucasus Zengezur part. Rivers of the Major and Minor Caucasus mainly flow in hot seasons, while rivers of the Talysh regions flow in colder seasons of year. Rivers, flowing in hot seasons account for most part of all rivers (60-80%).

Such seasonal flows are difficult for industrial use. On the whole, rivers of the Azerbaijan Republic are divided into two groups, according to their water regime:


Flood rivers are the Lenkoran rivers and episodic rivers of Gobustan. Other rivers are included into the first group of rivers.

Complex topography and other natural factors cause a non-standard flow across the country. The flow increases with altitudes and reaches its top at a certain height (2800, on the north-eastern slope of the Major Caucasus, 2000-2200-on its southern slope and 2200- 2400 on the Minor Caucasus). The flow starts to decline from above the indicated height. Due to the orographic specifications of the Talysh mountains, the flow is inconsistent with the average height. It decreases with the increase of altitude in the Talysh mountains, while in Peshteser and Burovar mountains it rises with the altitude.

The full-flowing rivers of the Azerbaijan Republic mainly flow on the southern slope of the Minor Caucasus. The average flow of such rivers exceeds 45 l-cm. The flow falls to 5 l-cm till the Alazan-Ayrichay lowland. The flow module of rivers of the north-eastern slope of the Major Caucasus 18 l-cm. The increase of flow with the increase of altitude is relatively uniform in this part of the Major Caucasus. The intensive increase in the module of flow is registered on the area between the Yah mountain chains and the Major Caucasus mountains. (upper Qusar, Qudyal and other rivers.). The Average annual module of flow is from swings hesitates from 10 to 20 l-cm.

The flow of rivers, originating in the slopes of the Yah mountains, differs from that of the rivers, flowing from the Major Caucasus. The flow increases intensively and reaches from 6 to 18 l-cm at a height of 1000-2000 meters, due to high level of precipitation. The flow gradually decreases till the Caspian Sea shore down to 0.5 l-cm. the flow decreases beginning from the north-west of till south east of the seaside lowland and reaches zero level on the Apsheron peninsula. Compared with the Major Caucasus, the flow in the Minor Caucasus is more complicated, due to its orographic complexity and differing location of mountain chains. The highest flow has been registered in the rivers flowing from the slopes of Gamish and Qapidjic mountains (over 28 l-cm).

In the Karabakh plateau precipitation is absorbed by soil rocks, thus turning the region into the arid area, while in some places it bursts onto the surface thus increasing the water level in the rivers. That is typical of the upper Terter, Hekeri and other regions as under water provides 70-80% of water to them. The flow fluctuates from 0.8 to 22 l-cm in south east of the Minor Caucasus (rivers, originating in the Caucasus mountains) and from 0.5 to 10 l-cm in the Nakhchivan Autonomous Republic. The flow gradually decreases to the level even lower than 0.5 l-cm on the plains on the side of Araz. In the Talish region the flow increases in the direction from the north to south and from the west to east. The flow reaches its peak (over 25 l-cm ) in Tengerud and Astara river basins in the central part of the region, while it reaches its minimum north of the Vilesh river, as well as in the Lenkeran and Vilesh rivers. Gobustan, Nakhchevan and Kura-Araz plains account for the lesser part of water system in Azerbaijan.

Rivers of Azerbaijan carry large quantity of sediment, the result of erosion in the river basins. The rivers in Azerbaijan are the most polluted rivers in the world. Their average annual pollution rate changes from 0.07 to 9 kg-1 cubic mete per region. It reaches its top on the north slope of Major Caucasus and minimum-on the Karabakh plateau. The surface erosion is intensive in the north slope of the Major Caucasus(100-6800 t/sq/km) , and it becomes weaker on the Karabakh plateau (5-10 t/sq.km). The surface erosion in the rivers of the Major Caucasus (0.53 mm) is by 13 higher from that of the Minor Caucasus (0.03 mm per year) and Talish mountains (0.04 mm per year).

The hydrological system of the Azerbaijan Republic contains 10.3 billion cubic meters of water reserves. These water reserves together with those, entering Azerbaijan from neighbor countries (20.6 billion cubic meters) make up 30.9 billion cubic meters. Each square meters of the country receives 90 thousand cubic meters of reserves, while the annual per capita volume of water reserves total 1270 cubic meters. The basin of the river Kura accounts from

the average height. It decreases with the increase of altitude in the Talysh mountains, while

The full-flowing rivers of the Azerbaijan Republic mainly flow on the southern slope of the Minor Caucasus. The average flow of such rivers exceeds 45 l-cm. The flow falls to 5 l-cm till the Alazan-Ayrichay lowland. The flow module of rivers of the north-eastern slope of the Major Caucasus 18 l-cm. The increase of flow with the increase of altitude is relatively uniform in this part of the Major Caucasus. The intensive increase in the module of flow is registered on the area between the Yah mountain chains and the Major Caucasus mountains. (upper Qusar, Qudyal and other rivers.). The Average annual module of flow is

The flow of rivers, originating in the slopes of the Yah mountains, differs from that of the rivers, flowing from the Major Caucasus. The flow increases intensively and reaches from 6 to 18 l-cm at a height of 1000-2000 meters, due to high level of precipitation. The flow gradually decreases till the Caspian Sea shore down to 0.5 l-cm. the flow decreases beginning from the north-west of till south east of the seaside lowland and reaches zero level on the Apsheron peninsula. Compared with the Major Caucasus, the flow in the Minor Caucasus is more complicated, due to its orographic complexity and differing location of mountain chains. The highest flow has been registered in the rivers flowing from the slopes

In the Karabakh plateau precipitation is absorbed by soil rocks, thus turning the region into the arid area, while in some places it bursts onto the surface thus increasing the water level in the rivers. That is typical of the upper Terter, Hekeri and other regions as under water provides 70-80% of water to them. The flow fluctuates from 0.8 to 22 l-cm in south east of the Minor Caucasus (rivers, originating in the Caucasus mountains) and from 0.5 to 10 l-cm in the Nakhchivan Autonomous Republic. The flow gradually decreases to the level even lower than 0.5 l-cm on the plains on the side of Araz. In the Talish region the flow increases in the direction from the north to south and from the west to east. The flow reaches its peak (over 25 l-cm ) in Tengerud and Astara river basins in the central part of the region, while it reaches its minimum north of the Vilesh river, as well as in the Lenkeran and Vilesh rivers. Gobustan, Nakhchevan and Kura-Araz plains account for the lesser part of water system in

Rivers of Azerbaijan carry large quantity of sediment, the result of erosion in the river basins. The rivers in Azerbaijan are the most polluted rivers in the world. Their average annual pollution rate changes from 0.07 to 9 kg-1 cubic mete per region. It reaches its top on the north slope of Major Caucasus and minimum-on the Karabakh plateau. The surface erosion is intensive in the north slope of the Major Caucasus(100-6800 t/sq/km) , and it becomes weaker on the Karabakh plateau (5-10 t/sq.km). The surface erosion in the rivers of the Major Caucasus (0.53 mm) is by 13 higher from that of the Minor Caucasus (0.03 mm per

The hydrological system of the Azerbaijan Republic contains 10.3 billion cubic meters of water reserves. These water reserves together with those, entering Azerbaijan from neighbor countries (20.6 billion cubic meters) make up 30.9 billion cubic meters. Each square meters of the country receives 90 thousand cubic meters of reserves, while the annual per capita volume of water reserves total 1270 cubic meters. The basin of the river Kura accounts from

in Peshteser and Burovar mountains it rises with the altitude.

from swings hesitates from 10 to 20 l-cm.

of Gamish and Qapidjic mountains (over 28 l-cm).

year) and Talish mountains (0.04 mm per year).

Azerbaijan.

most part of the water reserves. The nonunifomal distribution of water reserves across the region and around the year hammers the utilization of these reserves and as a result of that the reserves are not able to meet constantly growing demands for fresh water. The situation requires the regulation of water flow. 60 water reservoirs of the country with the capacity of over 1 million cubic meters account for 21 billion cubic meters of water reserves. Most part of these reserves are used in different spheres (irrigation, water supply, industry, fishery, etc). The establishment of water reservoirs of the Middle Kura plays the important role to meeting demands for water. Currently, serious measures are undertaken to preserve pure water reserves and to prevent their polluting with communal and industrial wastes.

The Canals of the Azerbaijan Republic are the main source of irrigation. The canals used for the said purpose extend to 47058.8 kilometers., with canals, used by several farms, accounting for 8580.3 kilometers and those, used only by one farm-for 38478.5 kilometers. The amount of 11 billion cubic meters of water is used in irrigation each year. Irrigated area of Azerbaijan totals 1.4 million hectares.

#### **3. Space technology in disaster monitoring, mitigation and preparedness**

#### **3.1 Natural disaster in global change**

One of the main impacts of the global changes is the natural disaster. Natural disaster can be playing a significant indicator for the foregoing issue. Natural disaster is increasingly of global concern and its impact and actions in one region can have an impact on disaster in another and vice versa. This compounded by increasing vulnerabilities related to climate change, climate variability as well as other contributions like changing demographic, technological and socio-economic conditions, environmental degradations etc.

There is a highly need for international acknowledgement that efforts to reduce disaster risks which must be systematically integrated into policies, plans and programmes for comprehensive approach of global change and endorsed through bilateral, regional and international cooperation, including partnership.

The importance of promoting of natural disaster impacts reduce efforts on the international and regional levels as well as the national and local levels has been recognized in the past few years in a number valuable and significant multilateral frameworks and declarations.

The following main areas can be covers the challenges of objectives of the natural disaster as a key element of the global changes:


Foregoing items can be discussed as a items for further developments. Given the close linkages between disaster risk factors and environmental and natural resource management issues, a huge potential exists for the exploitation of existing resources and established practices aiming at greater disaster reduction. The need for carefully drawn up forest, vegetation, soil, water and land management measures is increasingly recognized and such investigations are being effectively employed to learn the global change.

While countries valued the increased availability of advanced technologies, some were disappointed that their technical capabilities or data were insufficient to make more effective use of them. However, take advantage of space technology and its advance methodology applications for earth observation are being developed and will be executed through global and regional strategically partnerships. The United Nations Office for Outer Space Affairs and the action team of the Committee on the Peaceful Uses of Outer Space are proceeded to implement an integrated global system for the management of natural disaster. A global multilateral imitative, involving both developed and developing countries, including for the countries of the former Soviet Union and Southern European countries with the transit economy has developed a framework document for a 10-years plan to implement a Global Earth Observation Systems. One of the its objectives is the global observation of earth for the aim of global change, reduction of losses from natural disasters and improved understanding, assessment and prediction of weather and climate system variables.

The value of methodology and advanced technology for global change is widely recognized. Their use has increased as the tools have improved, costs have decreased and local access has increased. Methodology and techniques related to the remote sensing, geographical information systems, space-based observations, computer modeling and prediction and information and communication technologies have proved very useful, especially in earth observation systems, mapping, monitoring, territorial or local assessments and early warning activities in case of the natural disaster occurs.

The use of advance methodology and associated data sets in global observation suggests possibility for synergy and shared approaches with global change management. With decreasing costs, those tools have become much more readily available as routine capacities and more useful at local scales in many countries.

States and regional and international organizations should support and encourage the capacities of regional mechanisms and organizations to develop regional plans, policies and common practices, as appropriate, in support of networking coordination, exchange of information and experience, scientific monitoring of earth observation outcomes and institutional capacity development and to deal with natural disaster.

In view of the particular vulnerabilities and insufficient capacities of least developed countries to respond to and recover from natural disasters, support is needed by the least developed countries as a matter of priority, in executing substantive programmes and relevant institutional mechanism for the implementation of the framework of action, including through financial and technical assistance for and capacity building in natural disaster as an effective and sustainable means to prevent and respond to natural disaster.

There is a highly need of the establishing standards for the systematic collection and archiving of comprehensive national records pertaining to the many related aspects of earth observation. In the meantime evaluating country-wide assessments of earth observation and conducting natural disaster assessments, incorporating technical dimensions would be a significant contribution for this issue.

There is an important to assume that earth observation is a national and local priority with strong institutional bases for implementation. It has to be executed key activities within the national institutions and legislative framework as resources – assess existing human

While countries valued the increased availability of advanced technologies, some were disappointed that their technical capabilities or data were insufficient to make more effective use of them. However, take advantage of space technology and its advance methodology applications for earth observation are being developed and will be executed through global and regional strategically partnerships. The United Nations Office for Outer Space Affairs and the action team of the Committee on the Peaceful Uses of Outer Space are proceeded to implement an integrated global system for the management of natural disaster. A global multilateral imitative, involving both developed and developing countries, including for the countries of the former Soviet Union and Southern European countries with the transit economy has developed a framework document for a 10-years plan to implement a Global Earth Observation Systems. One of the its objectives is the global observation of earth for the aim of global change, reduction of losses from natural disasters and improved understanding, assessment and prediction of weather and climate system

The value of methodology and advanced technology for global change is widely recognized. Their use has increased as the tools have improved, costs have decreased and local access has increased. Methodology and techniques related to the remote sensing, geographical information systems, space-based observations, computer modeling and prediction and information and communication technologies have proved very useful, especially in earth observation systems, mapping, monitoring, territorial or local assessments and early

The use of advance methodology and associated data sets in global observation suggests possibility for synergy and shared approaches with global change management. With decreasing costs, those tools have become much more readily available as routine capacities

States and regional and international organizations should support and encourage the capacities of regional mechanisms and organizations to develop regional plans, policies and common practices, as appropriate, in support of networking coordination, exchange of information and experience, scientific monitoring of earth observation outcomes and

In view of the particular vulnerabilities and insufficient capacities of least developed countries to respond to and recover from natural disasters, support is needed by the least developed countries as a matter of priority, in executing substantive programmes and relevant institutional mechanism for the implementation of the framework of action, including through financial and technical assistance for and capacity building in natural disaster as an effective and sustainable means to prevent and respond to natural disaster.

There is a highly need of the establishing standards for the systematic collection and archiving of comprehensive national records pertaining to the many related aspects of earth observation. In the meantime evaluating country-wide assessments of earth observation and conducting natural disaster assessments, incorporating technical dimensions would be a

There is an important to assume that earth observation is a national and local priority with strong institutional bases for implementation. It has to be executed key activities within the national institutions and legislative framework as resources – assess existing human

warning activities in case of the natural disaster occurs.

institutional capacity development and to deal with natural disaster.

and more useful at local scales in many countries.

significant contribution for this issue.

variables.

resource capacities, community participation – promote community participation through the adaptation of specific policies, the promotion of networking, strategic management of volunteer resources.

Global Earth observation is a voluntary partnership of governments and international organizations. It provides a framework within which these partners can develop new projects and coordinate their strategies, integrate research activities, share results for common interest and investments.

Remote sensing one of the key instrument of the Earth observation provides an important source of data for environmental monitoring and natural disaster mapping and in fact several satellites can service a map the terrain with one meter resolution.

Natural disaster monitoring with integration of space technology can be focused for following significant:


The use of remote sensing and development of GIS will increase the access of the developing world to global change data and harness global Earth observation efforts in support of global environmental challenges for natural disaster issues.

The ability to model potential flood inundation areas and map actual extent of inundation, timing, and intensity under different environmental conditions is central to understanding the dynamics between vegetation, soils, geomorphology, and land productivity in a floodplain. In many regions, the lack of hydrologic and spatial data, constrains the accurate delimitation of flood inundation zones. In spite of these factors, different techniques involving GIS and remote sensing could be used for rapid general zonations of areas susceptible to flooding to reduce costly monitoring infrastructure. This study showed the ability of a DEM-based surface and a wetness layer derived from a Landsat ETM image to identify potential areas to flood inundation in the Kura River Basin, Salyan districts of Azerbaijan. The analyses involved tests in relation to a map of flooded areas derived from soils and geomorphology maps. The statistical tests showed that there is a significant relationship between potential inundation areas derived from a DEM-based surface and satellite image-based dataset with potential inundation areas derived from existent cartographic information on soils and geomorphology. However, the relationships were weak. This analysis showed that the integration of ancillary geomorphologic and soils data, simple DEM-based surfaces, and satellite images maybe a useful first approach to characterize flood inundation areas.

#### **3.2 Methods**

The use and application of space technology in a huge case in particularly for the case of river flood reduction is a more suitable means due to the covering a large areas, high accuracy, availability of application in the unacceptability areas etc (Finkl,2000). Moreover, according to the created and developed database there is an advantage to be very sensitive to any available change occurred in the investigated sites.

The benefit analysis of disaster risk reduction involves a number of particular challenges, including:


For carrying out of the goals undertaken within the framework of the project execution the following methods have been used:

 The use of ALOS space imagery to be created the land use / land cover basic map for the investigated area using urban, agriculture, garden, scrub, open area, river, stream, canal, road, railroad basic classes;

The use of Landsat ETM space imagery to be detected potential flood inundation areas within the Kura River watershed in the Salyan district of Azerbaijan using a tasseled cap transformation;

The derive 1 m Digital Elevation Model (DEM) from contour lines and elevation points of the investigated area to be generated a deterministic model of potential inundated areas for the region using the DEM and a convex-areas surface;

 The evaluate the sensitivity of each approach to be characterized the flood inundations through statistical tests involving comparison of flooding areas extracted from an inventory of soils and a geomorphology maps.

Investigated area description: The geographical area of interest is the Kura River basin in Saylan district of Azerbaijan (Figure 1). The area comprises approximately 24 km2. The Kura watershed is one of Azerbaijan's most important agricultural production areas. During the last 10 years, it was affected by 5 excessive floods, causing a lot of damage to people and goods. The one of major source of Azerbaijan freshwater is the Kura River. The mean discharge of 1,144 m3 sec-1 for the Kura River is the highest among the main rivers in the Azerbaijan, representing 39% of the total discharge from this lowland region. Mean precipitation in the Kura River drainage system is 885 mm year-1, which may range from less than 400 to more 1,800 mm during any one year.

#### **3.3 Satellite data processing**

ALOS imagery was acquired 10 June 2007 (Figure 2). The image was georeferenced to UTM zone 39 North, WGS84 using a first degree polynomial rectification algorithm with 30 ground control points (GCPs) extracted from a digitized topographic map at the scale of 1:100 000. The root mean square (RMS) error was equal to 0.5 pixel (5 m).

according to the created and developed database there is an advantage to be very sensitive

The benefit analysis of disaster risk reduction involves a number of particular challenges,

 Little related information may be available on the frequency and intensity of the hazard event, particularly in a developing country context, implying uncertainty about the

 Many of the benefits of any disaster risk reduction measures, whether undertaken in the context of a disaster risk reduction project or as part of another type of development project, are related to the direct and indirect losses that will not ensue should the related hazard event occur over the life of the project, rather than streams of positive

For carrying out of the goals undertaken within the framework of the project execution the

 The use of ALOS space imagery to be created the land use / land cover basic map for the investigated area using urban, agriculture, garden, scrub, open area, river, stream,

The use of Landsat ETM space imagery to be detected potential flood inundation areas within the Kura River watershed in the Salyan district of Azerbaijan using a tasseled cap

The derive 1 m Digital Elevation Model (DEM) from contour lines and elevation points of the investigated area to be generated a deterministic model of potential inundated areas for

 The evaluate the sensitivity of each approach to be characterized the flood inundations through statistical tests involving comparison of flooding areas extracted from an

Investigated area description: The geographical area of interest is the Kura River basin in Saylan district of Azerbaijan (Figure 1). The area comprises approximately 24 km2. The Kura watershed is one of Azerbaijan's most important agricultural production areas. During the last 10 years, it was affected by 5 excessive floods, causing a lot of damage to people and goods. The one of major source of Azerbaijan freshwater is the Kura River. The mean discharge of 1,144 m3 sec-1 for the Kura River is the highest among the main rivers in the Azerbaijan, representing 39% of the total discharge from this lowland region. Mean precipitation in the Kura River drainage system is 885 mm year-1, which may range from

ALOS imagery was acquired 10 June 2007 (Figure 2). The image was georeferenced to UTM zone 39 North, WGS84 using a first degree polynomial rectification algorithm with 30 ground control points (GCPs) extracted from a digitized topographic map at the scale of

1:100 000. The root mean square (RMS) error was equal to 0.5 pixel (5 m).

benefits that will take place, as would be the case for other investments.

to any available change occurred in the investigated sites.

including:

level of risk.

transformation;

following methods have been used:

canal, road, railroad basic classes;

the region using the DEM and a convex-areas surface;

inventory of soils and a geomorphology maps.

less than 400 to more 1,800 mm during any one year.

**3.3 Satellite data processing** 

Fig. 1. 1:100 000 topographic map of the study area.

Fig. 2. ALOS imagery of the selected area.

**Generation of a Digital Elevation Model:** The digital elevation model (DEM) was generated from digitized contour lines and elevation points from topographic map (Figure 3). The digitized lines in shapefile format were converted to points in ArcGIS 9.2 using the "Feature to Point" transformation tools. The points were interpolated using the IDW – inverse distance weighting method.

Fig. 3. The flowchart of Digital Elevation Model Generation procedure.

**Inverse distance weighting method:** Inverse distance weighting is a simple interpolation method, in which a neighborhood around the interpolated point is identified and a weighted average is taken of the observation values within this neighborhood. The weights are a decreasing function of distance. Generally, one can define the mathematical form of the weighting function and the size of the neighborhood expressed as a radius or a number of points.

The simplest weighting function (w) is the inverse power:

$$w(d) = \frac{1}{d^n}$$

with *n* 0 . The value of power can be specified depending upon data characteristics. The most common choice is *n* 2 .

The neighborhood size determines how many points are included in the inverse distance weighting. The neighborhood size can be specified in terms of its radius, the number of points, or a combination of the two. If a radius is specified, the user also can specify an override in terms of a minimum and/or maximum number of points. Invoking the override option will expand or contract the circle as needed. If the user specifies the number of points, an override of a minimum and/or maximum radius can be included. It also is possible to specify an average radius based upon a specified number of points. Again, there is an override to expand or contract the neighborhood to include a minimum and/or maximum number of points. For example, given the following distribution of points with a known value Z:

**Generation of a Digital Elevation Model:** The digital elevation model (DEM) was generated from digitized contour lines and elevation points from topographic map (Figure 3). The digitized lines in shapefile format were converted to points in ArcGIS 9.2 using the "Feature to Point" transformation tools. The points were interpolated using the

> Elevation points

**IDW**  Inverse Distance Weighting **DEM**  1 m

Fig. 3. The flowchart of Digital Elevation Model Generation procedure.

Polylines to points

The simplest weighting function (w) is the inverse power:

**Inverse distance weighting method:** Inverse distance weighting is a simple interpolation method, in which a neighborhood around the interpolated point is identified and a weighted average is taken of the observation values within this neighborhood. The weights are a decreasing function of distance. Generally, one can define the mathematical form of the weighting function and the size of the neighborhood expressed as a radius or a number of

> <sup>1</sup> *<sup>n</sup> w d d*

with *n* 0 . The value of power can be specified depending upon data characteristics. The

The neighborhood size determines how many points are included in the inverse distance weighting. The neighborhood size can be specified in terms of its radius, the number of points, or a combination of the two. If a radius is specified, the user also can specify an override in terms of a minimum and/or maximum number of points. Invoking the override option will expand or contract the circle as needed. If the user specifies the number of points, an override of a minimum and/or maximum radius can be included. It also is possible to specify an average radius based upon a specified number of points. Again, there is an override to expand or contract the neighborhood to include a minimum and/or maximum number of points. For example, given the following distribution of points with a

IDW – inverse distance weighting method.

Contour Lines: Intervals: 2m

Map 1:100 000

Elevation Points 1 : 100 000

points.

most common choice is *n* 2 .

known value Z:

and we want to interpolate a grid surface based on the spatial distribution of the points and their values,

then, using IDW we would assign a value to particular cell based on a number of neighbors and their distance to this cell,

$$D = \frac{\left(\mathbf{1}/d\_1^n\right)V\_1 + \left(\mathbf{1}/d\_2^n\right)V\_2 + \left(\mathbf{1}/d\_4^n\right)V\_4 + \left(\mathbf{1}/d\_5^n\right)V\_5 + \left(\mathbf{1}/d\_6^n\right)V\_6 + \left(\mathbf{1}/d\_7^n\right)V\_7 + \left(\mathbf{1}/d\_8^n\right)V\_8}{\left(\mathbf{1}/d\_1^n\right) + \left(\mathbf{1}/d\_2^n\right) + \left(\mathbf{1}/d\_4^n\right) + \left(\mathbf{1}/d\_5^n\right) + \left(\mathbf{1}/d\_6^n\right) + \left(\mathbf{1}/d\_7^n\right)}}$$

Which can be generalized as

$$D = \frac{\sum\_{i=1}^{n} \left(1/d\_i^{\pi}\right) V\_i}{\sum\_{i=1}^{n} \left(1/d\_i^{\pi}\right)}$$

where D is the interpolated value, di is the distance from the cell to a point with a known value, and Vi is the value of a particular point.

In this study, IDW with a second order power was used to interpolate the elevation values because of the coarse detail of the original data and the general objectives of the research. IDW is a fast and simple interpolation method, which can be used when the values of points are spatially auto correlated, like in the case of elevation points. Other interpolation methods such as Kriging, could be used when higher accuracy is required.

Fig. 4. Digital Elevation Model of the selected area with high points and isolines.

**Identification of potential flood inundation areas:** A convex surface was obtained with the formula:

#### Filled DEM – mean filled DEM

Where values < 0 where identified as convex zones (Figure 5). The mean DEM was calculated using standard GIS neighborhood operations. The areas selected as potential flooding areas where those that were convex and fall within an elevation range between -26 m and – 21 m, which is approximately the elevation range corresponding to the lower alluvial plain which is generally affected when severe flooding occurs.

*i i*

*d V*

1

*<sup>n</sup> <sup>n</sup>*

1

*i*

 

*D*

methods such as Kriging, could be used when higher accuracy is required.

Fig. 4. Digital Elevation Model of the selected area with high points and isolines.

alluvial plain which is generally affected when severe flooding occurs.

**Identification of potential flood inundation areas:** A convex surface was obtained with the

Filled DEM – mean filled DEM Where values < 0 where identified as convex zones (Figure 5). The mean DEM was calculated using standard GIS neighborhood operations. The areas selected as potential flooding areas where those that were convex and fall within an elevation range between -26 m and – 21 m, which is approximately the elevation range corresponding to the lower

1

where D is the interpolated value, di is the distance from the cell to a point with a known

In this study, IDW with a second order power was used to interpolate the elevation values because of the coarse detail of the original data and the general objectives of the research. IDW is a fast and simple interpolation method, which can be used when the values of points are spatially auto correlated, like in the case of elevation points. Other interpolation

*i*

*d*

1

*<sup>n</sup> <sup>n</sup> i*

Which can be generalized as

formula:

value, and Vi is the value of a particular point.

Fig. 5. Determination of convex areas based on the difference between the DEM and a mean DEM.

**Potential flood inundation areas mapping:** The study and identification of the potentially flood inundation areas in advance is a useful and important aspect of the natural disaster impact reduction.

For this reason the areas potentially flood inundation with a high probability of flooding has been developed and mapped. In this measurements and calculations the staring point has been undertaken as -26m.

The result reflects the potential flood inundation areas based on the height data supposed being as -22m. The result of data calculation and processing from DEM (Figure 4) has been demonstrated in a Figure 6. RF indicated zones reflect potentially flood inundation areas in case of the river level will be increased up to 4m.

This methodology can be successfully applied for potentially flood inundation areas after implementation of geodetic measurements related to the river level for acceptance of the high accuracy data.

**Field trip measurements:** The main aim of conducted field trips was identification of the inundation areas of the Kura river selected for investigation. One of the needs of this approach was defined due to the luck of the appropriate space data related to the seasonal date with a reach of flood impact of the area.

For the foregoing mentioned reason two field trips have been conducted for the selected area of investigation Salyan district of Azerbaijan. Those trips were implemented in summer season due to the heavy snow melting and autumn season due to the reach of raining when the river flood is more impacted among the all Kura river basin.

Field trips implementations have been scheduled and developed from the stage of the selection more sensitive areas of inundation in place. After those actions the counter of the river has been marked using the sticks installed among the river counter. Coordinates of the counters have been measured using GPS.

Fig. 6. Forecasting of the potentially flood inundation areas.

Based on those measurements all points of counters were installed on topographical map with further bounded of the space image.

The same actions have been applied for the seasons both summer and autumn. The results received from those measurements allow to compare the seasonal river level depends of the weather impacts. At the time it is the way to identify the expected inundation areas.

Based on those results as well as existed database for the river level change there is approach of study and identification of the dynamic change of the Kura river level. It is advantages of development of GIS technology which can be play a significant place on river flood problem solution especially valuable and extremely important instrument for local authority decision makers.

#### **4. Conclusion**

In this chapter have been reflected aspects of the use of space science and technology achievements in Earth observation systems. Furthermore it is described currently advances of space technology systems for Earth observation.

One of the main targets of this chapter is to develop of an advance tool for monitoring, data collection, data processing, review and report on progress and challenges in the implementation of disaster risk reduction and recovery actions undertaken at the national level. An advance tool has been undertaken of the use and application of modern

Based on those measurements all points of counters were installed on topographical map

The same actions have been applied for the seasons both summer and autumn. The results received from those measurements allow to compare the seasonal river level depends of the

Based on those results as well as existed database for the river level change there is approach of study and identification of the dynamic change of the Kura river level. It is advantages of development of GIS technology which can be play a significant place on river flood problem solution especially valuable and extremely important instrument for local

In this chapter have been reflected aspects of the use of space science and technology achievements in Earth observation systems. Furthermore it is described currently advances

One of the main targets of this chapter is to develop of an advance tool for monitoring, data collection, data processing, review and report on progress and challenges in the implementation of disaster risk reduction and recovery actions undertaken at the national level. An advance tool has been undertaken of the use and application of modern

weather impacts. At the time it is the way to identify the expected inundation areas.

Fig. 6. Forecasting of the potentially flood inundation areas.

with further bounded of the space image.

of space technology systems for Earth observation.

authority decision makers.

**4. Conclusion** 

achievements of space science and technology for the natural disaster events particularly the river flood.

Furthermore, the other target of project is to be undertaken to assist the local authorities to build up useful database in disaster risk reduction in particularly for the selected area with a more sensitively part of country in point of view the river flood in Azerbaijan. In the meantime the next issue was to demonstrate a contribution of the possibility and advantage of use of remote sensing methods and GIS technology based on space image data collection and data processing for application of similarity problem solving.

It was a highly desirable to create a favorable conditions and mechanisms to be able to develop the strengthened coordination and interaction for appropriate partners at the national level and facilitate explanation of the present status of the selected area and prioritization of strategic areas needed to be considered for purpose of natural disaster risk reduction.

Azerbaijan is the country of the Commonwealth of Independent States (CIS) with the transit economies. The Millennium Development with the eight Goals and Hyogo Framework Actions with three strategic goals and five priorities for actions have been related to the CIS countries.

The river flood is not a reason of damage impact of property and human life. The consequences are a huge as the eventually tracking with malaria, drinking water problem etc. The same problems with appropriate impact of scale occurs in case of Kura river when happens river flood. All this indicated accepts have to be undertaken for further successful management in order to be able to reduce the effect of natural disaster on river flood. An appropriate sufficient with high accuracy database has to be developed for local authorities for decision making.

The other very significant problem is the intended to be undertaken of diversion of the Kura river bed which plans to be started to construct in the upcoming period which will reduce of river flood impact for saving human life and properties.

#### **5. References**


"Sea-viewing Wide Field-of-view Sensor (SeaWiFS)". *NASA Facts on Line.* FS-97 (03)-004- GSFC.http://www.gsfc.nasa.gov/gsfc/service/gallery/fact\_sheets/earthsci/seaw ifs.htm

*Skylab Explores the Earth.* (1977). Washington, DC: NASA SP-380.

### **Nanosatellites: The Tool for Earth Observation and Near Earth Environment Monitoring**

Marius Trusculescu1, Mugurel Balan1, Claudiu Dragasanu2, Alexandru Pandele1 and Marius-Ioan Piso2

> *1Institute for Space Sciences 2Romanian Space Agency Romania*

#### **1. Introduction**

24 Earth Observation

"Sea-viewing Wide Field-of-view Sensor (SeaWiFS)". *NASA Facts on Line.* FS-97 (03)-004-

*Skylab Explores the Earth.* (1977). Washington, DC: NASA SP-380.

ifs.htm

GSFC.http://www.gsfc.nasa.gov/gsfc/service/gallery/fact\_sheets/earthsci/seaw

Large satellites continue to be affordable only to big national projects or extremely wealthy organizations. As such, emerging countries and small organizations are adopting smaller spacecrafts as means to their space exploration endeavours by forcing the miniaturization age to the space industry. In this chapter we evaluate the possibilities of using nanosatellites with the aim of achieving the best return of scientific output.

Adopted almost exclusively by small organization with limited budgets (universities, private firms or research institutes), nanosatellites have as their main requirement the maintaining off the overall costs at minimum. Unlike the traditional space missions, the nanosatellites use commercial off the shelf components - COTS - in order to decrease costs and fast track the design. This was identified as a liability since the space industry generally requires extensive qualification campaigns for flight hardware. But this is also a strong point since satellites can be designed, built, launched and operated in a fraction of the time required for conventional spacecrafts and at costs orders of magnitude lower.

The small scale counter parts of the traditional space missions represent the tool for Earth observation and near Earth space monitoring in the new age of space explorations. Almost 10 years ago the beginning of this new age became clear with the introduction of the CubeSat standard.

Generally, the nanosatellite term designates satellites in the 1 – 10 kg mass range. However, the most representative for this class is the CubeSat which restricts developers to a volume of approximately 10 x 10 x 10 cm3 (Cal Poly SLO, 2009). Recently there have been developments of sub-nano (pico class) spacecrafts weighing several hundred grams, or even smaller to femtosats – the so called satellites on a chip. However, their characteristics are yet unknown as they are only in the early design phase at present.

Although there are many representative of the nano class, the standardization of the launcher interface and the deployer (P-POD) has helped the CubeSat to receive general acceptance as the de facto standard. Previous experience with small satellites existed before the CubeSats, but their introduction marks the moment when a critical mass of developers begun working on similar designs using similar components. The simultaneous introduction of the P-POD also brought a standardized interface to various rockets. As such it became easier for the developers to address launching organizations for a group of small satellites.

As nanosatellite developers, we propose the adoption of these types of spacecrafts to support Earth observation, space environment monitoring and space qualification efforts at minimal costs.

#### **1.1 Typical characteristics of nanosatellites**

The definition of the satellite classes is not very rigid. Contrary to general perception, the exterior dimensions are not defining the nanosatellite. Typically, when speaking of a nano class spacecraft we refer to a sub 10 kg satellite. Consequently, the mass restriction is also a size restriction limiting the exterior dimensions to tens of centimetres. The only standard that imposes restrictions on dimensions is the CubeSat – a cube with a 100 mm edge length permitting small protuberances up to 6.5 mm on each side. The standard also limits the mass of the spacecraft at 1.33 kg – recently upgraded from 1 kg. A deviation from the initial standard allows the use of the space equivalent for two or three CubeSats (or even halves) for a single satellite extending the maximum length at more than 200/300 mm but maintaining the other two dimensions unchanged. These variations from the standard are named double or triple CubeSats to differentiate them from the single cube models. It is worth mentioning that even if the standard permits it, there have been no double CubeSats launched but only single or triple units.

The main characteristic of the nanosatellite are given by their size, which is in the order of tens of centimetres. All the other subsystems need to be scaled down to accommodate the design requirements. There are two approaches in designing a spacecraft of the nano class: either start from the payload and scale the satellite to that payload (traditional method very unusual for small satellites) or scale the payload to the overall dimensions and try to accommodate the other subsystems. The later is the new method that involves setting a design for the payload and revisiting it if after adding the rest of the subsystems the overall restrictions are not met. This might require going into many iterations for the design of the payload and the subsystems.

#### **1.1.1 Electrical power**

The accessible power on board a satellite depends on the total surface area available for solar cells. Using the formula in equation (1) we can compute the maximum power one square side can generate. The first term is the solar constant (the power from the Sun light available on Earth's orbit on a dm2), the second term is the surface area exposed to the Sun light, while the third term is the conversion coefficient between light and electricity.

$$P\_{slde}^{max}[W] = 13.68 \left[\frac{W}{dm^2}\right] \cdot S\_{slde}[dm^2] \cdot \frac{\mathcal{C}[\%]}{100} \tag{1}$$

For the 10 kg satellite a gross estimation of the size is a cube with the edge length of 200 mm. If we presume that no deployable solar panels are used, the total surface available for photovoltaic cells is 4 dm2 for each of the 6 sides. Considering the solar constant at 13.68 W/dm2, and the average conversion coefficient 25%, the total power available when not in eclipse must be lower than 18 W. This value does not take into account Earth's albedo.

The single unit CubeSat is situated at the lower limit of the nano scale according to the definition, so the available surface and electric power is even lower. Repeating the previous calculations for a 10 cm cube gives a value of 4.5 W for the maximum instantaneous power available without deployable solar panels. Just like with the previous estimate we assume no variation of the conversion coefficient associated with the increase of the temperature on the photovoltaic cells and we presumed the satellite in an orientation corresponding to the maximum surface area directly exposed to the Sun. Orbit averages for the power will be significantly lower than the computed values if we take into account the time the satellite spends on eclipse – typically 30% of the orbit period. Deployable solar panels have been included in launched CubeSats, especially for triple units, but for single unit as well (Nakaya et al., 2003; Genbrugge et al., 2009).

#### **1.1.2 Orbit**

26 Earth Observation

also brought a standardized interface to various rockets. As such it became easier for the

As nanosatellite developers, we propose the adoption of these types of spacecrafts to support Earth observation, space environment monitoring and space qualification efforts at

The definition of the satellite classes is not very rigid. Contrary to general perception, the exterior dimensions are not defining the nanosatellite. Typically, when speaking of a nano class spacecraft we refer to a sub 10 kg satellite. Consequently, the mass restriction is also a size restriction limiting the exterior dimensions to tens of centimetres. The only standard that imposes restrictions on dimensions is the CubeSat – a cube with a 100 mm edge length permitting small protuberances up to 6.5 mm on each side. The standard also limits the mass of the spacecraft at 1.33 kg – recently upgraded from 1 kg. A deviation from the initial standard allows the use of the space equivalent for two or three CubeSats (or even halves) for a single satellite extending the maximum length at more than 200/300 mm but maintaining the other two dimensions unchanged. These variations from the standard are named double or triple CubeSats to differentiate them from the single cube models. It is worth mentioning that even if the standard permits it, there have been no double CubeSats

The main characteristic of the nanosatellite are given by their size, which is in the order of tens of centimetres. All the other subsystems need to be scaled down to accommodate the design requirements. There are two approaches in designing a spacecraft of the nano class: either start from the payload and scale the satellite to that payload (traditional method very unusual for small satellites) or scale the payload to the overall dimensions and try to accommodate the other subsystems. The later is the new method that involves setting a design for the payload and revisiting it if after adding the rest of the subsystems the overall restrictions are not met. This might require going into many iterations for the design of the

The accessible power on board a satellite depends on the total surface area available for solar cells. Using the formula in equation (1) we can compute the maximum power one square side can generate. The first term is the solar constant (the power from the Sun light available on Earth's orbit on a dm2), the second term is the surface area exposed to the Sun

����∙�����[���] <sup>∙</sup>

For the 10 kg satellite a gross estimation of the size is a cube with the edge length of 200 mm. If we presume that no deployable solar panels are used, the total surface available for photovoltaic cells is 4 dm2 for each of the 6 sides. Considering the solar constant at 13.68 W/dm2, and the average conversion coefficient 25%, the total power available when not in eclipse must be lower than 18 W. This value does not take into account Earth's albedo.

�[�]

<sup>100</sup> (1)

light, while the third term is the conversion coefficient between light and electricity.

���[�] � 1���� � �

developers to address launching organizations for a group of small satellites.

**1.1 Typical characteristics of nanosatellites** 

launched but only single or triple units.

payload and the subsystems.

�����

**1.1.1 Electrical power** 

minimal costs.

Due the average power being on the order of watts or tens of watts the nanosatellites are constrained on accessible orbits as well. The limited power available for the transceivers restricts the range between the ground station and the spacecraft. Consequently, nanosatellites are launched on low Earth orbits (LEO). The typical orbit is circular at almost 90o inclination and its altitude is near 700 km. The second, less encountered orbit class is also circular but at 300 – 350 km and its inclination much lower – Genesat-1 and satellites launched from the ISS or the Shuttle. These orbits are at the lower limit of the trapped radiation belts and although the particle fluxes are higher than at sea level they are inferior to those on higher altitude orbits. This is the main reason that COTS components are feasible to be used on board nanosatellites.

9 CubeSat class satellites will be launched on a non characteristic orbit on board the VEGA maiden flight. The orbit has changed several times but the current values for the perigee and the apogee are 300 km and 1450 km with the inclination at 69.5o. The higher altitude of the apogee takes the satellites inside the proton belt. The satellites launched on this mission would further evaluate the possibility of using COTS at high radiation fluxes.

The orbit of the nanosatellite also impacts the communication between the ground station and the spacecraft. For the orbits we previously mentioned a full period is approximately 90 minutes and each day there are between 3 and 5 windows of communications when the satellite is in range of the spacecraft and 3-10 minutes on each interval. These values are averages for a location at 45o latitude. There is daily re-visitation for satellites on LEO and this fits well into the objective of using nanosatellites for Earth observation applications.

#### **1.2 Currently available technologies**

Being in development for over a decade, different technologies have been adopted by the nanosatellite designers and advances have been made for increasing the capability of these spacecrafts. We are now at a time when the efforts are starting to show results and inmission demonstrations of these technologies are beginning.

#### **1.2.1 Processing power**

A second important restriction imposed by the energy available on board is the processing power that can be feasibly accommodated on small satellites. Hence the on board computers typically found on nanosatellites launched in the past decade are microcontrollers functioning at frequencies of several MHz. The reason is not the lack of advanced processors that could be integrated, but the need to limit the functioning periods for them as they drain the batteries rapidly. The proposed solution is to use a mixed approach: low power microcontrollers for general functions and high power processor for demanding tasks like attitude determination and control systems (AOCS) or data processing in payload units. This method has already been applied by the integration of units functioning at hundreds of MHz on board nanosatellites already launched or being scheduled for launch.

Launched in 2008, the Japanese nanosatellite Cute-1.7 + APD II used the main boards of two commercial off the shelf (COTS) personal device assistant (PDA) running at 400 MHz as the main components of the on board computer and data handling system (OBDH) (Ashida et al., 2008). Scheduled for launch on the VEGA maiden flight, the Goliat CubeSat integrates a dual core 600 MHz digital signal processor (DSP) for on board image compression (Balan et al., 2008).

Fig. 1. Hitachi NPD-20JWL PDA on board Cute 1.7 + APDII (left) and the DSP board on board Goliat (right).

The trend of adapting commercial portable devices like PDAs and smartphones for use on board nanosatellites fits the general guidelines of low cost design through the use of COTS subsystems. Additionally, mass produced mobile devices are benefiting from extensive research in miniaturization and reduction of power consumption, levels that can't be achieved with the limited budgets of a small satellite research project. Therefore the orientation of nanosatellites developers toward using smartphone processor boards as part of theirs satellite's OBDH system is natural.

The most popular mobile platforms of the moment, iPhone and Android, have proven flight experience at the edge of the atmosphere, on board weather balloons at altitudes higher than 30 km. Taking the idea a step further, a team of researchers in UK plans on building and launching a triple unit CubeSat that will fly a complete smartphone (Surrey Satellite Technology Ltd, 2011). The smartphone will be the payload and the demonstration of its orbit functioning is intended. Part of the test also implies switching off the main microcontroller of the satellite and passing all the OBDH functions to the smartphone.

Besides costs and power optimization there are other benefits of adapting the processors of mobile devices to satellites: better development tools for software with better version

control, usability of the same code among several devices facilitating the upgrade of the hardware with minimal software changes, a single low voltage power supply (typically 3.3 V) and a single data interface, numerous integrated peripherals (magnetometers, accelerometers, gyroscopes, temperature sensors). These benefits also come with the loss of some of the customization as there is little possibility to intervene on the hardware (sensor calibration, removing unnecessary modules) and some parts of the software. The number of additional interfaces is also limited and typically a single serial connection exists: Bluetooth. Additionally, USB host mode connection is being proposed as standard for smartphones running the next release of Android OS (version 3.1).

As part of our research, we propose the use of the on board data connections – mainly Wi-Fi, but GPRS or 3G also – as communication platforms for nanosatellites flying in close or dispersed orbital formations. If Wi-Fi devices allow ad-hoc networking, the use of the mobile phone data connections will necessitate the existence of a cell node managing the network.

#### **1.2.2 Attitude and orbit control systems**

28 Earth Observation

typically found on nanosatellites launched in the past decade are microcontrollers functioning at frequencies of several MHz. The reason is not the lack of advanced processors that could be integrated, but the need to limit the functioning periods for them as they drain the batteries rapidly. The proposed solution is to use a mixed approach: low power microcontrollers for general functions and high power processor for demanding tasks like attitude determination and control systems (AOCS) or data processing in payload units. This method has already been applied by the integration of units functioning at hundreds of

Launched in 2008, the Japanese nanosatellite Cute-1.7 + APD II used the main boards of two commercial off the shelf (COTS) personal device assistant (PDA) running at 400 MHz as the main components of the on board computer and data handling system (OBDH) (Ashida et al., 2008). Scheduled for launch on the VEGA maiden flight, the Goliat CubeSat integrates a dual core 600 MHz digital signal processor (DSP) for on board image compression (Balan et

Fig. 1. Hitachi NPD-20JWL PDA on board Cute 1.7 + APDII (left) and the DSP board on

The trend of adapting commercial portable devices like PDAs and smartphones for use on board nanosatellites fits the general guidelines of low cost design through the use of COTS subsystems. Additionally, mass produced mobile devices are benefiting from extensive research in miniaturization and reduction of power consumption, levels that can't be achieved with the limited budgets of a small satellite research project. Therefore the orientation of nanosatellites developers toward using smartphone processor boards as part

The most popular mobile platforms of the moment, iPhone and Android, have proven flight experience at the edge of the atmosphere, on board weather balloons at altitudes higher than 30 km. Taking the idea a step further, a team of researchers in UK plans on building and launching a triple unit CubeSat that will fly a complete smartphone (Surrey Satellite Technology Ltd, 2011). The smartphone will be the payload and the demonstration of its orbit functioning is intended. Part of the test also implies switching off the main microcontroller of the satellite and passing all the OBDH functions to the smartphone.

Besides costs and power optimization there are other benefits of adapting the processors of mobile devices to satellites: better development tools for software with better version

MHz on board nanosatellites already launched or being scheduled for launch.

al., 2008).

board Goliat (right).

of theirs satellite's OBDH system is natural.

Most advanced applications require precise determination of the orbit and the attitude of the satellite. Others also need capabilities to change the orientation and some even the position of the satellite. This is the technology field where most nanosatellite research is focused. Miniaturized attitude determination sensors existed at the time nanosatellites started being launched and various sensors were rapidly integrated: Sun sensors, magnetometers, Earth horizon sensors, star trackers.

Beside early attempts at using permanent magnets or magneto-torquers to stabilize the satellite or change its orientation, recent developments have been made at integrating reaction/momentum/inertial wheels on board even the CubeSats – see Fig. 2 (Balan et al, 2008; Bozovic et al, 2008). The CanX-2 was developed and launch for testing some of the critical components of the AOCS system required in the formation flying demonstration mission of CanX-4 and CanX-5. As such, the triple unit CubeSat included a complex attitude determination system based on multiple sun sensors and a magnetometer. It also integrated a single reaction wheel for evaluation purposes together with a propulsion system evaluation unit. The team reported successful operation for all the AOCS subsystems evaluated (Sarda et al., 2010).

Fig. 2. Motors and reaction wheels on the mechanical structure of Goliat (left), motor and the inertial wheel assembly for the SwissCube (right).

For nanosatellites bigger than single unit CubeSats, different commercial solutions have emerged recently. One such example is the MAI-x00 series which offer complete attitude determination and control for small satellites in packages from half a CubeSat to 1 CubeSat (Maryland Aerospace Inc., 2011). Position actuator products are not as advanced for small satellite, and either cold gas or micro thrusters are considered. A different approach is the use of aerodynamic breaking in close orbital formation scenarios. For two or even more CubeSats launched from the same deployer, the initial velocities are the same. Any change in the orientation results in a change of the surface area normal to the trajectory and in a change of the aerodynamic drag. Such a solution will work only in preventing the spacecraft separation and it actuates only in the direction of the orbit. Any difference in the velocities of the two spacecrafts for the other two axes would render the method unusable (Balan et al., 2009).

After a decade of nanosatellites missions the technologies have evolved enabling the exploitation of the new class of spacecrafts for more complex applications. As the subsystems available have evolved, sufficient flight data has been gathered for essential components and their reliability is guaranteed.

#### **2. Earth observation and near Earth environment monitoring**

The objectives of small spacecrafts were initially only educational while science and Earth observation were just viewed as secondary goals. However the nanosatellites' missions have quickly begun to evolve to more complex science with increased demand for reliability. From the industry perspective, nanosatellites now represent an easy access to space for simple instruments or for test bed applications. Among the instruments best suited are the sensors for monitoring the radiation environment on LEO, the magnetic field and some of the upper atmosphere phenomena. The inclusion of digital cameras on board nanosatellites did not have Earth observation objectives at first. Initially the imaging experiments were included for their public outreach potential.

The Earth observation potential of nanosatellites is still disregarded since optic instruments are considered too large for integration on nanosatellites. However as the exploitation potential of the new class of spacecrafts was revealed, the idea of Earth observation even on CubeSats starts to gain more general acceptance with every new launch. A camera having one of the highest focal lengths mounted on a CubeSat is part of the Goliat mission. Its integration proved very difficult as the optical lens and sensor assembly occupy almost half of the interior of the spacecraft.

One of the advantages of LEO is the proximity to the surface and to the upper atmosphere. Earth Observation doesn't target only the monitoring of the land or water masses, but also the monitoring of phenomena in the atmosphere. Small focal distance cameras are ideal at imaging the movement of large cloud formations (like with tropical storms or large scale meteorological manifestations). Also, we mentioned earlier the re-visitation interval of approximately 12 hours which is important for events with high dynamicity. These time intervals can be further decreased if several nanosatellites (a constellation) are deployed on the same orbit in successive launches. The satellites cover the same area at time intervals several hours apart with the actual timing depending on the number of spacecrafts launched.

For nanosatellites bigger than single unit CubeSats, different commercial solutions have emerged recently. One such example is the MAI-x00 series which offer complete attitude determination and control for small satellites in packages from half a CubeSat to 1 CubeSat (Maryland Aerospace Inc., 2011). Position actuator products are not as advanced for small satellite, and either cold gas or micro thrusters are considered. A different approach is the use of aerodynamic breaking in close orbital formation scenarios. For two or even more CubeSats launched from the same deployer, the initial velocities are the same. Any change in the orientation results in a change of the surface area normal to the trajectory and in a change of the aerodynamic drag. Such a solution will work only in preventing the spacecraft separation and it actuates only in the direction of the orbit. Any difference in the velocities of the two spacecrafts for the other two axes would render the method unusable (Balan et

After a decade of nanosatellites missions the technologies have evolved enabling the exploitation of the new class of spacecrafts for more complex applications. As the subsystems available have evolved, sufficient flight data has been gathered for essential

The objectives of small spacecrafts were initially only educational while science and Earth observation were just viewed as secondary goals. However the nanosatellites' missions have quickly begun to evolve to more complex science with increased demand for reliability. From the industry perspective, nanosatellites now represent an easy access to space for simple instruments or for test bed applications. Among the instruments best suited are the sensors for monitoring the radiation environment on LEO, the magnetic field and some of the upper atmosphere phenomena. The inclusion of digital cameras on board nanosatellites did not have Earth observation objectives at first. Initially the imaging experiments were

The Earth observation potential of nanosatellites is still disregarded since optic instruments are considered too large for integration on nanosatellites. However as the exploitation potential of the new class of spacecrafts was revealed, the idea of Earth observation even on CubeSats starts to gain more general acceptance with every new launch. A camera having one of the highest focal lengths mounted on a CubeSat is part of the Goliat mission. Its integration proved very difficult as the optical lens and sensor assembly occupy almost half

One of the advantages of LEO is the proximity to the surface and to the upper atmosphere. Earth Observation doesn't target only the monitoring of the land or water masses, but also the monitoring of phenomena in the atmosphere. Small focal distance cameras are ideal at imaging the movement of large cloud formations (like with tropical storms or large scale meteorological manifestations). Also, we mentioned earlier the re-visitation interval of approximately 12 hours which is important for events with high dynamicity. These time intervals can be further decreased if several nanosatellites (a constellation) are deployed on the same orbit in successive launches. The satellites cover the same area at time intervals several hours apart with the actual timing depending on the number of spacecrafts

**2. Earth observation and near Earth environment monitoring** 

al., 2009).

components and their reliability is guaranteed.

included for their public outreach potential.

of the interior of the spacecraft.

launched.

A special application for low resolution image acquisition that could be implemented on nanosatellites involves multi-spectral imaging on board satellites flying in a close orbital formation. An identically built satellite is to be repeated and the optical systems will be the same among all the members of the orbital formation. Unlike the large spacecrafts, the imaging sensors on each satellite can be single-spectral, and the wavelength for the maximum sensitivity is the one that differs. For redundancy multiple spacecrafts will monitor each spectral band and the image acquisition will be commanded to all satellites. Multi-band images can be reconstructed either on ground or on the network on orbit. However, for each band a single image will be sent to the ground station, resulted from the fusion of all the images taken by satellites with the same spectral band sensitivity – see Fig. 3 (Balan et al., 2009).

Fig. 3. Formation flying scenario with distributed sensors, in flight data processing and single data stream communications.

One of the key application of nanosatellites is as support in disaster management efforts. In these situations low re-visitation periods are required to monitor major floods, fires or other large scale natural disasters. For these types of conditions, rapid information delivery is more important than resolution as there is an immediate need to roughly identify the areas already affected and the ones most exposed to danger. Nanosatellites can therefore be used in conjunction with large spacecrafts to identify precisely the locations where higher resolution images are required and request the specific areas to be monitored.

Several approaches have been proposed to address the problem of the size of the optical systems. Among them, worth mentioning are the use of complex deployable lens mounts and the use of multiple sensors. A nanosatellite that successfully demonstrated deployable optics is the 8 kg, 19 cm x 19 cm x 30 cm PRISM nanosatellite developed by the Intelligent Space Systems Laboratory (ISSL) of University of Tokyo (Komatsu & Nakasuka, 2009).

The advantage of nanosatellites is their reduced costs. If multiple identical such spacecraft are to be built, the costs are decreased even more. As such, it is natural to consider multiple satellites scenarios in which the imaging of the same area, or adjacent sectors would result in a representation of higher resolution. The solution is not complete if the image processing is set to be conducted on ground as all the raw data from the sensors must be forwarded to the ground station. This situation is not feasible for nanosatellites as there is a limited data rate caused by the limited power. Therefore the use of on board processing for all the data acquired by the distributed sensors is a necessity. As resources are limited on nanosatellites, the ideal method for implementing complex data processing is by using the hardware on each of the spacecrafts and dividing tasks among processors based on their availability, like in grid computing. This complex image processing method was not yet implemented on launched satellites. The main issue is with scaling down the data fusion algorithms so they can be implemented on the limited hardware resource on board nanosatellites.

Precise Earth observation requires the use of key technologies identified in the previous section. The most obvious among the requirements is the need to determine the position and orientation of the satellite with the accuracy needed by the application – approximately 10% of the ground target size. The same resolution is required when controlling the orientation actuators. Once the image has been stored on board, the data must be sent to the ground station. The reported data rate in nanosatellite to ground station communications has increased in the last couple of years with the use of S-band transceivers and the utilization of the experience acquired during the operations of the first spacecrafts. Given the limited emission power, the data throughput can be increased if directive antennas shall be developed for use on the nanosatellites. Furthermore, even if the data rate is not increased, the amount of data transferred to the ground station can be increased by optimizing the radio communications windows. At present, with midlatitude ground stations, the communications windows are less than 10% of the orbital period. A second ground station could increase the percentage, but either the separation among ground stations must be of hundreds to thousands kilometres, or each ground station must target a different satellite and different data streams are to be transferred. Single ground stations that can have greater communication windows must be situated in the Polar Regions if the polar orbits remain the custom for nanosatellites. An alternative is represented by the ground station networks currently being proposed – GENSO – but these are tailored for educational purposes and need to be adapted to the different needs of the commercial applications.

It is expected that the time from design to delivery for a nanosatellite missions to further decrease, and the mission costs to continue to go down together with it, due to the rapidly increase in the nanosatellites subsystems and components market.

#### **3. Multiple satellites mission for Space Situational Awareness (SSA)**

The multi satellite missions are best suited for small spacecrafts due to the small costs and rapid production associated with them. We present distributed measurements as a new way to better and faster understand complex phenomena by using simultaneous data gathering in the target environment. A group of nanosatellites (constellations or formations) is the most cost-effective way to implement this approach in space. Furthermore, distributed data collection can be correlated with distributed processing to enable single data stream transmissions between the spacecrafts in orbit and the ground station as opposed to the multiple streams associated with independent multiple satellites. This solution better

would result in a representation of higher resolution. The solution is not complete if the image processing is set to be conducted on ground as all the raw data from the sensors must be forwarded to the ground station. This situation is not feasible for nanosatellites as there is a limited data rate caused by the limited power. Therefore the use of on board processing for all the data acquired by the distributed sensors is a necessity. As resources are limited on nanosatellites, the ideal method for implementing complex data processing is by using the hardware on each of the spacecrafts and dividing tasks among processors based on their availability, like in grid computing. This complex image processing method was not yet implemented on launched satellites. The main issue is with scaling down the data fusion algorithms so they can be implemented on the limited hardware resource on

Precise Earth observation requires the use of key technologies identified in the previous section. The most obvious among the requirements is the need to determine the position and orientation of the satellite with the accuracy needed by the application – approximately 10% of the ground target size. The same resolution is required when controlling the orientation actuators. Once the image has been stored on board, the data must be sent to the ground station. The reported data rate in nanosatellite to ground station communications has increased in the last couple of years with the use of S-band transceivers and the utilization of the experience acquired during the operations of the first spacecrafts. Given the limited emission power, the data throughput can be increased if directive antennas shall be developed for use on the nanosatellites. Furthermore, even if the data rate is not increased, the amount of data transferred to the ground station can be increased by optimizing the radio communications windows. At present, with midlatitude ground stations, the communications windows are less than 10% of the orbital period. A second ground station could increase the percentage, but either the separation among ground stations must be of hundreds to thousands kilometres, or each ground station must target a different satellite and different data streams are to be transferred. Single ground stations that can have greater communication windows must be situated in the Polar Regions if the polar orbits remain the custom for nanosatellites. An alternative is represented by the ground station networks currently being proposed – GENSO – but these are tailored for educational purposes and need to be adapted to the different needs

It is expected that the time from design to delivery for a nanosatellite missions to further decrease, and the mission costs to continue to go down together with it, due to the rapidly

The multi satellite missions are best suited for small spacecrafts due to the small costs and rapid production associated with them. We present distributed measurements as a new way to better and faster understand complex phenomena by using simultaneous data gathering in the target environment. A group of nanosatellites (constellations or formations) is the most cost-effective way to implement this approach in space. Furthermore, distributed data collection can be correlated with distributed processing to enable single data stream transmissions between the spacecrafts in orbit and the ground station as opposed to the multiple streams associated with independent multiple satellites. This solution better

**3. Multiple satellites mission for Space Situational Awareness (SSA)** 

increase in the nanosatellites subsystems and components market.

board nanosatellites.

of the commercial applications.

addresses the issues of limited data rate in small satellites communications caused by the low available power and not using directive antennas. Unlike with imaging applications, the amount of data from multiple instruments in a close orbital formation can easily be transmitted from a single satellite even if measurements from each sensor are included. Raw signals from every event will however have the same impact as images on the size of data to be transmitted, but in the case of unusual results, the actual values recorded can be sent in multiple transmissions without impacting the stream of on board processed data.

The potential of small satellites, nanosatellites and CubeSats especially, to contribute valuable data necessary to the modelling and the prediction of the space environment in the context of the SSA has recently begun being recognized and the need to aggregate all the data from recent small satellites launches is identified (Holm et al, 2009). Extrapolating on this trend we consider there is a further need for a unified data collection structure with multiple points of acquisition and multiple similar – identical or complementary – sets of sensors. Nanosatellites are the perfect propositions for demonstrating the benefits of this type of missions due to the reduced mission costs and their rapid development.

One of the main directions in the field of near Earth space monitoring is the research and development of spacecrafts built for multi-satellite missions. Space weather's influence on our daily life increases constantly with the miniaturization as devices become more sensible to outside interferences. Within the context of a new maximum in the solar activity, the perturbations of space supported services are becoming more frequent so we base our mission proposition on the need to investigate this domain. Multiple spacecrafts missions, in either constellation or formation configurations, will serve as points of observations for the evolution of the complex environment of nuclear particles in conjunction with the dynamic magnetic field of the planet.

Based on the experience in developing the radiation detection experiment on board Goliat, we proposed the further investigation of the nuclear particles in LEO and the magnetic field, in order to identify correlations between local variations of the two. Observations on the dynamics of the phenomena are possible by using the distributed sensors and the short revisitation intervals. All spacecrafts are to be identical from the hardware point of view. The minimal requirements for the radiation sensors are the need for differentiation based on particle type and the capability of measuring the energy of each event so as to obtain the representation of the radiation spectrum at each satellite. Precise magnetic field measurements require caution in separating the interferences generated by the spacecraft's own subsystems. This is why magnetometers need to be mounted as far from the satellite as possible, usually at the end of a deployable boom. Each spacecraft needs also to integrate precise attitude determination for both position and orientation of the magnetometer's axes with respect to the Earth.

Space weather monitor nanosatellites can be launched in solitary missions as demonstrators, but greater value can be added by launching several in a close orbital formation. In the first months of their mission, they will synchronize data collection between them and the data transmissions to the ground station are centralized through a single point of contact – one member of the formation. As the atmospheric drag starts affecting each satellite differently, their relative velocities change and the distances among satellites will increase. The formation transforms into a constellation and the phenomena recorded are no longer local, but become global.

The same approach can be applied to multiple applications in the context of SSA. The mixed configuration mission can theoretically fulfil both roles: being launched as a close orbital formation and, once the fuel has run out, gradually migrating to a dispersed formation and then becoming a constellation. The simplest demonstration would require launching three identical single unit CubeSats from the same PPOD and then test the formation flying capabilities on board these three spacecrafts. Such a mission can serve as a test bed for larger nanosatellites. During the demonstration various hardware and, equally important, software can be tested to facilitate future missions.

#### **4. Case study: Goliat, building a CubeSat for Earth observation & near Earth environment monitoring**

The authors of this chapter worked at developing Romania's first CubeSat class satellite - Goliat. Among its goals an important part is the demonstration of Earth observation and near Earth environment monitoring capabilities on board nanosatellites.

#### **4.1 Goliat platform subsystems**

Goliat is a single unit CubeSat developed by a Romanian consortium led by the Romanian Space Agency. The project was directed toward students at two universities in Bucharest that were tasked at designing and building the satellite in order to have them educated in the work practices of the space industry. The project involved not only building the satellite, but also setting up a ground station infrastructure at two locations near two major cities in Romania: Bucharest and Cluj-Napoca.

Fig. 4. Goliat Flight Model.

The satellite was selected to be launched on Vega's inaugural flight on an elliptical orbit having the perigee at 300 km and the apogee at 1450 km. The satellite's life on this orbit is between 1 and 3 years due to rapid altitude decay caused by atmospheric drag.

#### **4.1.1 Mechanical structure**

Goliat was built in accordance with the CubeSat specification as a single unit satellite. The skeletonized version of Pumpkin's mechanical structure is the basis of Goliat's design. The +Z side of the satellite was full metal and not skeletonized as optics mounting and several other components required a harder fixture. The structure is made out of aluminium alloys with the rails hard anodized.

#### **4.1.2 OBDH**

34 Earth Observation

formation transforms into a constellation and the phenomena recorded are no longer local,

The same approach can be applied to multiple applications in the context of SSA. The mixed configuration mission can theoretically fulfil both roles: being launched as a close orbital formation and, once the fuel has run out, gradually migrating to a dispersed formation and then becoming a constellation. The simplest demonstration would require launching three identical single unit CubeSats from the same PPOD and then test the formation flying capabilities on board these three spacecrafts. Such a mission can serve as a test bed for larger nanosatellites. During the demonstration various hardware and, equally important,

**4. Case study: Goliat, building a CubeSat for Earth observation & near Earth** 

The authors of this chapter worked at developing Romania's first CubeSat class satellite - Goliat. Among its goals an important part is the demonstration of Earth observation and

Goliat is a single unit CubeSat developed by a Romanian consortium led by the Romanian Space Agency. The project was directed toward students at two universities in Bucharest that were tasked at designing and building the satellite in order to have them educated in the work practices of the space industry. The project involved not only building the satellite, but also setting up a ground station infrastructure at two locations near two major cities in

near Earth environment monitoring capabilities on board nanosatellites.

but become global.

**environment monitoring** 

**4.1 Goliat platform subsystems** 

Romania: Bucharest and Cluj-Napoca.

Fig. 4. Goliat Flight Model.

software can be tested to facilitate future missions.

Two MSP430F1612 microcontrollers are the backbone of the satellite. One of the onboard computer (OBC) units was acquired from Pumpkin, while the other one was a custom solution built on an internal design. The two processors are running at 7.2 MHz and communicate with each other via a serial peripheral interface (SPI). The OBC board also includes a SD card interfaced on SPI as well. Other subsystems are also communicating using the SPI link: the camera processor board and the control unit of the UHF radio. Additionally each microcontroller connects on a serial interface to various components: camera processor board, 2.4 GHz transceiver, magnetometers, GPS. Data from two experiments (radiation measurement and micro-meteoroid impact instrument) and from the housekeeping sensors is collected at the microcontrollers on the built-in ADC channels. An independent microcontroller unit was implemented on the electronic power supply (EPS) board to manage this subsystem.

#### **4.1.3 Radio communications**

Goliat has two data links for radio communications. The primary data link unit uses a 1 W commercial transceiver operating in the 2.4 GHz band. This unit is controlled and it is directly interfaced to one of the MSP430 microprocessors. It is scheduled to operate only when in range of the ground station and its main purpose is to transmit data from the experiments and to receive commands from the operators in the control room.

The secondary transceiver is a beacon operating in the 70 cm radio amateur UHF band. It is built from a portable radio-amateur transceiver and a custom built AFSK modem controlled by a third MSP430F1612 microcontroller. This radio module is meant only at transmitting but receiving capabilities have been added to act as back-up for the main radio unit. The data transmission on this link will be continuous on the entire orbit and both Morse code and AFSK packets with housekeeping data will be transmitted. This unit is controlled by a different OBC than the 2.4 GHz transceiver so full redundancy is available on the spacecraft.

#### **4.1.4 Electronic power supply**

The EPS subsystem features the power generation, energy storage and voltage conditioning functions of the satellite. The first component of the subsystem is made up by the solar panels. 18 photovoltaic cells measuring 41 mm x 42.2 mm and having an efficiency of approximately 25% are distributed on the 6 sides of the satellite. Three sides contain 4 cells each while three sides contain only two cells each. The estimated average power from the solar panels is a little over 2 W. The cells are grouped so the voltage reaching the main EPS board is 4 V.

Due to the noise sensitive nature of one of the on board experiments, the main requirement of the EPS design was that no switching power supply should be present on the satellite's supply lines. This imposes the use of LDO regulators which are highly ineffective. More so, the need of a 5 V supply line, coupled with the less than 5 V output voltage of the solar panels, requires the use of a battery pack with the nominal voltage above 5 V. Li-Ion batteries were selected due to having the highest energy density per mass. The ping-pong architecture of the EPS uses two Li-Ion battery packs with their nominal voltage at 7.2 V. A battery pack always supplies the satellite, while the other is charging from a step-up converter that has the voltage from the solar panels as its input.

#### **4.1.5 ADCS**

For the determination of Goliat's position there are two independent methods. First uses a commercial GPS receiver while the second one involves sending the orbital parameters as a \*.tle file (two line elements) and then calculate the position using an orbit propagator implemented on one of the microcontrollers. For orientation the satellite uses a triple axis magnetometer and an IGRF implementation on the same microcontroller to compare the data for the actual position and determine the orientation of the satellite with respect to the Earth.

Goliat is meant to demonstrate a simple reaction wheel system for changing the orientation of CubeSats. Due to the mission constraints only two wheels were able to be included in the satellite design. The attitude control system is made of two high precision reaction wheels mounted on top of two micro-motors and the assemblies are attached to the aluminium structure in the centre of two perpendicular sides of the satellite.

#### **4.2 Payload**

The payload of Goliat consists of three independent experiments for near Earth environment monitoring and Earth observation.

The first of them is named SAMIS and it is a micro-meteoroid detection instrument that uses a thin film piezo-element to measure the energy of the impact between the satellite and the micrometer sized particles on LEO. The measurement of the flux of particles encountered by the satellite will take place continuously after the commissioning of the spacecraft.

Dose-N is the second on board experiment and it targets the measurement of the total ionizing dose on Goliat's orbit. The experiment's added value increases with the new Vega orbit since the satellite's trajectory is no longer circular and a range of altitudes in the radiation environment is to be mapped. If the 700 km altitude orbit was at the lower limit at the trapped proton belt, the elliptical orbit enters the region and exposes the satellite's

panels. 18 photovoltaic cells measuring 41 mm x 42.2 mm and having an efficiency of approximately 25% are distributed on the 6 sides of the satellite. Three sides contain 4 cells each while three sides contain only two cells each. The estimated average power from the solar panels is a little over 2 W. The cells are grouped so the voltage reaching the main EPS

Due to the noise sensitive nature of one of the on board experiments, the main requirement of the EPS design was that no switching power supply should be present on the satellite's supply lines. This imposes the use of LDO regulators which are highly ineffective. More so, the need of a 5 V supply line, coupled with the less than 5 V output voltage of the solar panels, requires the use of a battery pack with the nominal voltage above 5 V. Li-Ion batteries were selected due to having the highest energy density per mass. The ping-pong architecture of the EPS uses two Li-Ion battery packs with their nominal voltage at 7.2 V. A battery pack always supplies the satellite, while the other is charging from a step-up

For the determination of Goliat's position there are two independent methods. First uses a commercial GPS receiver while the second one involves sending the orbital parameters as a \*.tle file (two line elements) and then calculate the position using an orbit propagator implemented on one of the microcontrollers. For orientation the satellite uses a triple axis magnetometer and an IGRF implementation on the same microcontroller to compare the data for the actual position and determine the orientation of the satellite with respect to the

Goliat is meant to demonstrate a simple reaction wheel system for changing the orientation of CubeSats. Due to the mission constraints only two wheels were able to be included in the satellite design. The attitude control system is made of two high precision reaction wheels mounted on top of two micro-motors and the assemblies are attached to the aluminium

The payload of Goliat consists of three independent experiments for near Earth environment

The first of them is named SAMIS and it is a micro-meteoroid detection instrument that uses a thin film piezo-element to measure the energy of the impact between the satellite and the micrometer sized particles on LEO. The measurement of the flux of particles encountered by the satellite will take place continuously after the commissioning of the

Dose-N is the second on board experiment and it targets the measurement of the total ionizing dose on Goliat's orbit. The experiment's added value increases with the new Vega orbit since the satellite's trajectory is no longer circular and a range of altitudes in the radiation environment is to be mapped. If the 700 km altitude orbit was at the lower limit at the trapped proton belt, the elliptical orbit enters the region and exposes the satellite's

converter that has the voltage from the solar panels as its input.

structure in the centre of two perpendicular sides of the satellite.

board is 4 V.

**4.1.5 ADCS** 

Earth.

**4.2 Payload** 

spacecraft.

monitoring and Earth observation.

components to higher radiation fluxes. The radiation detection instrument uses a scintillating material that generates visible radiation when interacting with nuclear particles. The light is detected by a photodiode that has its maximum sensitivity at the same wave length as the photons emitted by the scintillators (430 nm). The signal from the photodiode is integrated and the amplitude of the output signal measured by the microcontrollers as the total energy deposited in the integration time frame. Measurements will be taken at equally distanced positions along the trajectory of the spacecraft and dose measurements will be correlated with resets and other errors in the functioning of the satellite.

The third and the last of the experiments on board Goliat is a narrow angle camera (NAC). The sensor of the camera consists of a 2048 x 1536 matrix of pixels, the highest resolution fitted on a single unit CubeSat. The pixel size is 3.2 µm x 3.2 µm. For the electronics of the experiment a commercial solution with the sensor board stacked on top the processor board was used. The processor board features a Blackfin ADSP-BF561 dual core DSP running at 600 MHz. A µClinux operating system is installed on the microcontroller and software written in C/C++ can be compiled on the device. A dual interface, serial and SPI, is used to communicate with the other microcontrollers on the satellite and with the SD card. The power consumption for the two stacked boards is typically at 1 W and does not exceed 2.25 W according to the manufacturer.

For a typical nanosatellite orbit – circular at 700 km altitude – the expected equivalent area in a 3 mega pixel image is a 50 x 70 km region. The expected pixel resolution is tens of meters, enabling the identification of geographical features and even of large constructions at the ground. The elliptical orbit for the Vega launch will make possible testing the camera

at various altitudes in the 300 to 1450 km range. For the project a special lens mount was designed and built at PRO Optica in Bucharest. The optics had to be accommodated inside the satellite and compliance with the CubeSat standard was desired. The optics had to meet the restrictions of accommodating the other subsystems while maximizing the focal length. A 6o field of view was achieved at a 57 mm focal length.

The main objective of the Goliat satellite is to demonstrate the potential of nanosatellites to execute complex experiments at low costs. An auxiliary objective was the development of a flight proven satellite platform that could be adapted for future application oriented space missions.

Fig. 6. The narrow angle camera on board Goliat: processor board (red), sensor board (blue), optics (yellow).

### **5. Conclusions**

Nanosatellites are definitely the most rapid changing sector of the space industry in the last decade. Their development has taken many by surprise and their momentum is just starting to grow now that technologies essential for better exploiting their potential are becoming available. We are expecting their growth to continue due to the further reduction in costs and the decrease of the development cycle associated with the trend of standardizing the bus of the spacecraft.

At first missing, technologies like small scale AOCS systems, OBDH modules, and even low power, high data rate transceivers have rapidly evolved driven by their requirement in building complex subsystems. It is now cheap to build more than one satellite and satellites are becoming smarter when connecting them in a network. Furthermore, the applications proposed for the new types of spacecrafts and missions promise to revolutionize space operations with the outside of the box thinking associated with doing things at a smaller scale.

Space is finally becoming accessible to projects with limited budgets, through nanosatellites, the new tools for near Earth explorations.

#### **6. References**

38 Earth Observation

at various altitudes in the 300 to 1450 km range. For the project a special lens mount was designed and built at PRO Optica in Bucharest. The optics had to be accommodated inside the satellite and compliance with the CubeSat standard was desired. The optics had to meet the restrictions of accommodating the other subsystems while maximizing the focal length.

The main objective of the Goliat satellite is to demonstrate the potential of nanosatellites to execute complex experiments at low costs. An auxiliary objective was the development of a flight proven satellite platform that could be adapted for future application oriented space

Fig. 6. The narrow angle camera on board Goliat: processor board (red), sensor board (blue),

Nanosatellites are definitely the most rapid changing sector of the space industry in the last decade. Their development has taken many by surprise and their momentum is just starting to grow now that technologies essential for better exploiting their potential are becoming available. We are expecting their growth to continue due to the further reduction in costs and the decrease of the development cycle associated with the trend of standardizing the

At first missing, technologies like small scale AOCS systems, OBDH modules, and even low power, high data rate transceivers have rapidly evolved driven by their requirement in

A 6o field of view was achieved at a 57 mm focal length.

missions.

optics (yellow).

**5. Conclusions** 

bus of the spacecraft.


*Proceedings of the 21st International Communications Satellite Systems Conference*, AIAA 2003-2388, Yokohama, Japan, 2003


### **Clarification of SAR Data Processing Systems and Data Availability to Support InSAR Applications in Thailand**

Ussanai Nithirochananont and Anuphao Aobpaet *Geo-Informatics and Space Technology Development Agency, Thailand* 

#### **1. Introduction**

40 Earth Observation

Sarda, K; Grant, C; Eagleson, S.; Kekez, D.D; Zee, R.E. (2010). Canadian Advance Nanospace

Surrey Satellite Technology Ltd. SSTL STRaND smartphone nanosatellite, Accessed on

*Services (4S)*, , Funchal, Madeira, Portugal, May 31 – June 4 2010

2003-2388, Yokohama, Japan, 2003

science/science-missions/strand-nanosatellite

*Proceedings of the 21st International Communications Satellite Systems Conference*, AIAA

Experiment 2 Orbit Operations: Two Years of Pushing the Nanosatellite Performance Envelope, *Proceedings of the Symposium on Small Satellite Systems and* 

28.08.2011, Available from: http://www.sstl.co.uk/divisions/earth-observation-

The Geo-Informatics and Space Technology Development Agency (GISTDA) was established since 2000, and it is the major organization in Thailand that responsible for geoinformatics and all space technology development activities under ministry of science and technology. Currently, GISTDA acquired data from Earth Observation Satellites such as THEOS, LANDSAT-5, RADARSAT-1 and -2, etc. by using remote sensing systems which extensively to be used in the past and tremendously useful from now on for acquiring the satellite data. Consequently, the recognition on the development of this technology and operation acceptant are very beneficial. Moreover, the users are necessary to understand the data processing procedures, as for their applications which depend on the satellite imageries and data processing quality. This article describes and discusses mainly about the data processing and production systems of SAR sensor, including the application example on Bangkok land subsidence using InSAR.

GISTDA has archives of many European, Canadian and Japanese SAR images of Thailand that are instantly available to InSAR applications in Thailand. With our capability to acquire the data direct down-link using 9- and 13-meter antennas, it provides the potential of times series SAR data available for the environmental change detection using InSAR techniques.

In Thailand, the land deformations are not a new phenomenon for major cities and some specific zone whose location lay on the tectonic plate. The applications such as land subsidence, flash flood induced land slide, coastal erosion and fault monitoring are subjected to the country apprehension. However, the irregular deformation patterns put severe demands to the traditional geodetic techniques such as levelling survey, GNSS etc. with respect to the number of stations and the time interval between consecutive measuring sessions. Therefore, to overcome the limitations, InSAR (Interferometric Synthetic Aperture Radar) techniques provide a high spatial resolution and accuracy at the sub-centimetre level. InSAR has all weather, day and night, capability, and the sampling rate of current spaceborne systems is improving, 45 days (ALOS-PALSAR), 24 days (RADARSAT-1 and RADARSAT-2) to 11 days (TerraSAR-X), which is satisfactorily high to the monitoring of land deformations.

For SAR data, the production requests were submitted through a Product Generation System (PGS) interface for RADARSAT-1, RADARSAT-2 and APEX CMDR via Vexcel control processor system for ALOS-PALSAR at the ground receiving station facility. The necessarily data employed in most research for deformation is required to be in single look complex (SLC) products in CEOS format where generally each of them consists of five files containing various descriptive records. Each image pixel is represented by complex I and Q numbers to maintain the amplitude and phase information which makes it suitable for interferometric processing. Therefore, the clarification such as the processing algorithm, system configuration, data available to support applications will be provided to certify the potential of using SAR data in Thailand. Finally, a case study on using InSAR techniques for land subsidence monitoring in Bangkok and its vicinity area will show that the successful cooperation between data provider and the user will lead to conquer the best practice.

#### **2. Brief background of satellite remote sensing in Thailand**

Historically, Thailand Satellite Remote Sensing Program of the National Research Council of Thailand (NRCT) was established on September 14, 1971 (NRCT, 2000) with the main reason of participating in NASA Earth Resources Technology Satellite (ERTS) Program. The program was promoted to become the Remote Sensing Division under NRCT in 1979, and internationally known as the Thailand Remote Sensing Center (TRSC). Subsequently, in late 1981, the ground receiving station was set up to acquire Landsat-MSS data, and it was capable of receiving and processing data from major remote sensing satellites throughout consistent upgrading of the facilities. In 1982, Thailand Ground Receiving Station was set up as first of its kind in Southeast Asia with the available satellite data such as LANDSAT, SPOT, NOAA, ERS and MOS at that time.

On June 27, 2000, the Cabinet was approved the establishment of Geo-Informatics and Space Technology Development Agency (GISTDA) as the self-governing public organization for conducting technological research, development and applications of satellite remote sensing and GIS, related space technologies for providing relevant services to Thai and international community. Basically, GISTDA is the merging of the TRSC and the IGIS section of Information Center of MOST. Therefore, GISTDA is the national main organization implementation of remote sensing, GIS, and satellite development programs for Thailand. Due to the main mission, Thailand Earth Observation Center (TEOC) has become the common name of TRSC since then.

One of the big movement of space activity in Thailand has been recorded on October 1, 2008, that Thailand Earth Observation Satellite (THEOS) was successfully launched by Dnepr launcher from Yasny, Russian Federation. THEOS is the first operational earth observation satellite of Thailand. The THEOS program was developed by GISTDA, EADS Astrium, the prime contractor, initiated work on the satellite in 2004. Nowadays, GISTDA is developing a worldwide network of distributors to allow the users to use and access to all GISTDA products which is able primarily to access via web-site www.gistda.or.th.

On the other hand, Synthetic Aperture Radar (SAR) satellite systems formerly in function at TEOC include European Remote Sensing Satellite 1 (ERS-1) from the European Space Agency's (ESA) which was launched by July 1991, and the Japanese Earth Resources satellite (JERS-1), launched in February 1992. The ERS-1 sensor operated in the C-band frequency

For SAR data, the production requests were submitted through a Product Generation System (PGS) interface for RADARSAT-1, RADARSAT-2 and APEX CMDR via Vexcel control processor system for ALOS-PALSAR at the ground receiving station facility. The necessarily data employed in most research for deformation is required to be in single look complex (SLC) products in CEOS format where generally each of them consists of five files containing various descriptive records. Each image pixel is represented by complex I and Q numbers to maintain the amplitude and phase information which makes it suitable for interferometric processing. Therefore, the clarification such as the processing algorithm, system configuration, data available to support applications will be provided to certify the potential of using SAR data in Thailand. Finally, a case study on using InSAR techniques for land subsidence monitoring in Bangkok and its vicinity area will show that the successful cooperation between data provider and the user will lead to conquer the best practice.

Historically, Thailand Satellite Remote Sensing Program of the National Research Council of Thailand (NRCT) was established on September 14, 1971 (NRCT, 2000) with the main reason of participating in NASA Earth Resources Technology Satellite (ERTS) Program. The program was promoted to become the Remote Sensing Division under NRCT in 1979, and internationally known as the Thailand Remote Sensing Center (TRSC). Subsequently, in late 1981, the ground receiving station was set up to acquire Landsat-MSS data, and it was capable of receiving and processing data from major remote sensing satellites throughout consistent upgrading of the facilities. In 1982, Thailand Ground Receiving Station was set up as first of its kind in Southeast Asia with the available satellite data such as LANDSAT,

On June 27, 2000, the Cabinet was approved the establishment of Geo-Informatics and Space Technology Development Agency (GISTDA) as the self-governing public organization for conducting technological research, development and applications of satellite remote sensing and GIS, related space technologies for providing relevant services to Thai and international community. Basically, GISTDA is the merging of the TRSC and the IGIS section of Information Center of MOST. Therefore, GISTDA is the national main organization implementation of remote sensing, GIS, and satellite development programs for Thailand. Due to the main mission, Thailand Earth Observation Center (TEOC) has

One of the big movement of space activity in Thailand has been recorded on October 1, 2008, that Thailand Earth Observation Satellite (THEOS) was successfully launched by Dnepr launcher from Yasny, Russian Federation. THEOS is the first operational earth observation satellite of Thailand. The THEOS program was developed by GISTDA, EADS Astrium, the prime contractor, initiated work on the satellite in 2004. Nowadays, GISTDA is developing a worldwide network of distributors to allow the users to use and access to all GISTDA

On the other hand, Synthetic Aperture Radar (SAR) satellite systems formerly in function at TEOC include European Remote Sensing Satellite 1 (ERS-1) from the European Space Agency's (ESA) which was launched by July 1991, and the Japanese Earth Resources satellite (JERS-1), launched in February 1992. The ERS-1 sensor operated in the C-band frequency

products which is able primarily to access via web-site www.gistda.or.th.

**2. Brief background of satellite remote sensing in Thailand** 

SPOT, NOAA, ERS and MOS at that time.

become the common name of TRSC since then.

(approx. 5.6 cm wavelength) and JERS-1 operated in the L-band frequency (approx. 23 cm wavelength). Both sensors have a nominal spatial resolution of approximately 30 m. The ERS-1 satellite, with a projected lifespan of three years, was followed by an ERS-2 satellite to continue SAR data acquisition into the late 1990s.

The operations of SAR data at that time has been applied to several major applications such as land-use and land-cover information mapping, coastal monitoring, crop monitoring, etc. The mission record of SAR data had been started with ERS-1 in March 1993 after almost 2 year launched, and the contract had been expired in September 1995. In parallel, JERS-1 SAR ground system had been functioned from October 1993 until October 1998, respectively. Before the coming of RADARSAT-1 (Canadian Space Agency) in July 2000, TEOC had set up the new contract with ESA again for acquiring SAR data from ERS-2 mission which records from August 1996 to October 1999. Currently, the RADARSAT-1 (2000-present), RADARSAT-2 (2010-present) and ALOS-PALSAR (2007-2011) have been the main SAR satellite acquisition of TEOC. However, please note that, JAXA announced that ALOS satellite has been completed its operation due to power generation anomaly since May 12, 2011.

TEOC plays an important role in the area of remote sensing technology in the country and also in the Asian region. The center has some collaborative activities with several international agencies including NASA, JAXA, ESA, CSA, etc. TEOC is located at Ladkrabang district, Bangkok, which is about 4 kilometers from Suwanaphum International airport. It has radius coverage of 2,500 km, covering 17 countries such as Malaysia, Singapore, Philippines, Indonesia, Brunei, Myanmar, Laos, Vietnam, Cambodia, Thailand, Bangladesh, India, Nepal, Sri Lanka, Phutan, Taiwan, and South China and Hong Kong (see figure 1).

### **3. Fundamentals of synthetic aperture radar**

Synthetic Aperture Radar (SAR) is a powerful active coherent imaging system that operates in the microwave frequency band. The system could be placed onboard an airbourne or a spacebourne plarform. It provides capabilities of working in daylight-independent and allweather condition, and penetrating cloud cover. These capabilities allow SAR an attractive instrument for many applications i.e. change detection, disaster management and environmental monitoring. New applications increase as new technologies are developed.

SAR system imaging the Earth's surface by transmitting pulses and collecting echoes reflected from an illuminated area. To perform this, the transmitter generates pulses of electromagnetic energy at the regular time interval and sends to the antenna. Then the antenna radiates the energy from the transmitter in a directional beam. Each pulse travels at the speed of light to the target area. The returning echo energy are also picked up by the same antenna and passed to the receiver. By measuring the time delay between the transmitted pulses and the reflected return pulse or echo, SAR system is able to determine the distance of the target.

To construct an image, time delay of the received echo must be precisely measured in two orthogonal dimensions. One dimension is parallel to the antenna beam while another is orthogonal to the antenna beam. In the first dimension, parallel to the antenna beam, the SAR system places the received echo at the correct distance from the platform's sensor,

Fig. 1. TEOC Area Coverage for direct downlink.

along the x-axis of the image. The x-dimension is referred as range direction, or cross-track. For the second dimension, orthogonal to the antenna beam, the received echoes are placed in the y-axis of the image, according to the current position of the platform's sensor. The ydimension is called azimuth direction, or along-track.

The basic geometry of imaging SAR is shown in figure 2. As illustrated, a platform, which could be an airplane or a satellite, travelling along the flight track with velocity V at altitude H. It carries a SAR antenna that illuminates the Earth's surface with pulse of electromagnetic energy. SAR antenna is typically rectangular with dimensions of length L and width W. The antenna is oriented parallel to the flight track and looking sideward to the area on the ground. The distance from the flight track to the target is denoted as range direction and direction along the flight track is referred as the azimuth direction. An area on the ground covered by the consecutive pulses is called swath. Antenna beam footprint is an area on the ground reflected by the pulse. is defined as the incident angle or look angle.

In fact the SAR system images an area on the ground but for simplicity, a single point on the ground is considered. This point is known as a point target. The data received from the SAR system are referred as raw data. The data are then demodulated to in-phase-quadraturephase (I-Q) baseband data. The demodulated SAR signal, *s*, received from a point target can be modeled as (Cumming & Wong, 2005)

along the x-axis of the image. The x-dimension is referred as range direction, or cross-track. For the second dimension, orthogonal to the antenna beam, the received echoes are placed in the y-axis of the image, according to the current position of the platform's sensor. The y-

The basic geometry of imaging SAR is shown in figure 2. As illustrated, a platform, which could be an airplane or a satellite, travelling along the flight track with velocity V at altitude H. It carries a SAR antenna that illuminates the Earth's surface with pulse of electromagnetic energy. SAR antenna is typically rectangular with dimensions of length L and width W. The antenna is oriented parallel to the flight track and looking sideward to the area on the ground. The distance from the flight track to the target is denoted as range direction and direction along the flight track is referred as the azimuth direction. An area on the ground covered by the consecutive pulses is called swath. Antenna beam footprint is an area on the

In fact the SAR system images an area on the ground but for simplicity, a single point on the ground is considered. This point is known as a point target. The data received from the SAR system are referred as raw data. The data are then demodulated to in-phase-quadraturephase (I-Q) baseband data. The demodulated SAR signal, *s*, received from a point target

is defined as the incident angle or look angle.

Fig. 1. TEOC Area Coverage for direct downlink.

dimension is called azimuth direction, or along-track.

ground reflected by the pulse.

can be modeled as (Cumming & Wong, 2005)

Fig. 2. Basic geometry of imaging SAR.

$$\begin{split} s(\tau,\eta) = A\alpha\_r[\tau - 2R(\eta) / c] \alpha\_a(\eta - \eta\_c) \\ \times \exp(-j4\pi f\_0 R(\eta) / c) \times \exp(j\pi K\_r(\tau - 2R(\eta) / c)^2) \end{split} \tag{1}$$

where *A* = an arbitrary complex constant = range time = azimuth time *<sup>c</sup>* = beam center offset time ( ) *r* = range envelope ( ) *a* = azimuth envelope <sup>0</sup>*f* = radar center frequency *Kr* = range chirp FM rate *R*( ) = instantaneous slant range.

The raw data is not an image due to the point targets are spread out in range and azimuth direction. It will be compressed in two dimensions by SAR data processor, to produce the image. The purpose of SAR processing is to convert the raw data into an interpretable image. Several algorithms have been developed and each algorithm has its advantages in either imaging quality or computation efficient. In the following section two SAR image processing techniques will be briefly introduced: the range–Doppler and the sprectral analysis.

There are three SAR satellites acquiring data at the TEOC: RADARSAT-1, RADARSAT-2 and ALOS. RADARSAT-1 is Canadian first commercial Earth observation satellite launched on November 1995. It employs a SAR sensor operating in the C-band frequency (5.3 GHz). The RADARSAT-1 SAR sensor has two right-looking operational modes, Single Beam mode and ScanSAR mode. The modes of observation offer the real-time swath width ranging from a narrow high-resolution beam of 50-km, Fine beam in Single Beam mode, to a full 500-km swath in ScanSAR mode.

The Next-generation SAR satellite, RADARSAT-2, follow-on RADARSAT-1, was launched on December 2007. All RADARSAT-1 operational modes maintain in RADARSAT-2. The major extended capabilities are a new observation beam, ultra-fine with 3-meter resolution, a fully polarimetric imaging and ability to look either left or right side of satellite track. More details on the RADARSAT-1 and RADARSAT-2 satellites are provided by (Ahmed et al., 1990; Thompson et al., 2001).

The Advanced Land Observing Satellite (ALOS) is Japan's research earth observation satellite operated by JAXA. It was launched on January 2006. The ALOS carries three remote-sensing instruments onboard: (i) the Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM), the Advanced Visible and Near Infrared Radiometer type 2 (AVNIR-2) and the Phase Array type L-band Synthetic Aperture Radar (PALSAR). PRISM and AVNIR-2 are optical sensors while PALSAR is a microwave sensor. In this paper , we mainly focuses on the data processing system for PALSAR data only.

The PALSAR is L-band synthetic aperture radar operating in the microwave L-band frequency (1270 MHz). It was designed to achieve cloud-free, all-weather and day-and-night collecting high-resolution land observations data on a global scale. PALSAR has three imaging modes: single-polarimetric stripmap mode, ScanSAR mode, and multi-polarimetric mode. More information on the ALOS satellite can be found in (Japan Aerospace Exploration Agency [JAXA], 2008).

#### **4. SAR processing algorithms**

SAR processing algorithm is a processing tool used for transforming unfocused raw SAR signal data into a complex image data. Each processing algorithm is suitable for different SAR data types. For continuous SAR data such as data from the stripmap in SAR imaging mode, the most common algorithm is the Range-Doppler (RD) algorithm, but the burst data such as data from the scanning SAR imaging mode, the Spectral Analysis (SPECAN) algorithm, is best suitable.

The Range-Doppler algorithm is the most common algorithm used in most SAR processor. The algorithm was developed since SEASAT program. This algorithm has simplicity of onedimensional operations and archive block processing efficiency by using frequency domain operations in both range and azimuth. These two directions processing can be independently performed by using range cell migration correction (RCMC) between the two one-dimensional operations.

Computation of the RD algorithm is divided into two processing steps: range compression and azimuth compression. The unfocused raw SAR data compression in each direction is first taking the fast Fourier transform (FFT), and then multiplied in frequency domain by the

There are three SAR satellites acquiring data at the TEOC: RADARSAT-1, RADARSAT-2 and ALOS. RADARSAT-1 is Canadian first commercial Earth observation satellite launched on November 1995. It employs a SAR sensor operating in the C-band frequency (5.3 GHz). The RADARSAT-1 SAR sensor has two right-looking operational modes, Single Beam mode and ScanSAR mode. The modes of observation offer the real-time swath width ranging from a narrow high-resolution beam of 50-km, Fine beam in Single Beam mode, to a full 500-km

The Next-generation SAR satellite, RADARSAT-2, follow-on RADARSAT-1, was launched on December 2007. All RADARSAT-1 operational modes maintain in RADARSAT-2. The major extended capabilities are a new observation beam, ultra-fine with 3-meter resolution, a fully polarimetric imaging and ability to look either left or right side of satellite track. More details on the RADARSAT-1 and RADARSAT-2 satellites are provided by (Ahmed et

The Advanced Land Observing Satellite (ALOS) is Japan's research earth observation satellite operated by JAXA. It was launched on January 2006. The ALOS carries three remote-sensing instruments onboard: (i) the Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM), the Advanced Visible and Near Infrared Radiometer type 2 (AVNIR-2) and the Phase Array type L-band Synthetic Aperture Radar (PALSAR). PRISM and AVNIR-2 are optical sensors while PALSAR is a microwave sensor. In this paper , we

The PALSAR is L-band synthetic aperture radar operating in the microwave L-band frequency (1270 MHz). It was designed to achieve cloud-free, all-weather and day-and-night collecting high-resolution land observations data on a global scale. PALSAR has three imaging modes: single-polarimetric stripmap mode, ScanSAR mode, and multi-polarimetric mode. More information on the ALOS satellite can be found in (Japan Aerospace

SAR processing algorithm is a processing tool used for transforming unfocused raw SAR signal data into a complex image data. Each processing algorithm is suitable for different SAR data types. For continuous SAR data such as data from the stripmap in SAR imaging mode, the most common algorithm is the Range-Doppler (RD) algorithm, but the burst data such as data from the scanning SAR imaging mode, the Spectral Analysis (SPECAN)

The Range-Doppler algorithm is the most common algorithm used in most SAR processor. The algorithm was developed since SEASAT program. This algorithm has simplicity of onedimensional operations and archive block processing efficiency by using frequency domain operations in both range and azimuth. These two directions processing can be independently performed by using range cell migration correction (RCMC) between the two

Computation of the RD algorithm is divided into two processing steps: range compression and azimuth compression. The unfocused raw SAR data compression in each direction is first taking the fast Fourier transform (FFT), and then multiplied in frequency domain by the

mainly focuses on the data processing system for PALSAR data only.

swath in ScanSAR mode.

al., 1990; Thompson et al., 2001).

Exploration Agency [JAXA], 2008).

**4. SAR processing algorithms** 

algorithm, is best suitable.

one-dimensional operations.

reference function and finally taking the inverse fast Fourier transform (IFFT). For azimuth compression the RCMC is applied after the azimuth FFT. The most important modification of this algorithm called secondary range compression (SRC) has been added to handle data with a moderate amount of squint.

The SPECAN algorithm was developed to produce a quick-look image for real-time SAR processing. It is the most efficient processing algorithm for ScanSAR data. The key property is computing efficiency which makes the algorithm require less memory than the RD algorithm does but may suffer from some image quality effects. The compression in range direction is the same as in the RD algorithm but different in the azimuth compression.

After range compression, the RCMC is applied before the azimuth compression. The RCMC is efficiency performed a linear correction only. The compression in azimuth direction performs deramping and FFT. Then there are two possible optional way, mutli-looking and phase compensation. The multilook processing is to be performed as the RD algorithm while the phase compensation replaces when single-look processing is to be performed. Reference [4] provides more details of these algorithms.

#### **5. SAR data processing systems**

SAR data processing system (SDPS) is used to transform unprocessed raw SAR data or signal data into georeferenced and geocoded image data. The TEOC has two SDPS: the RADARSAT SDPS for data from RADARSAT-1 and RADARSAT-2 SAR sensors and ALOS SDPS for data from ALOS PALSAR sensor. The RADARSAT SDPS is a sub-system of the Product Generation System (PGS) developed by MDA. ALOS SDPS is a sub-system of the ALOS Data Reception and Processing (ALOSRP) system developed by JAXA. The PGS and ALOSRP also have a capability to process data from optical sensor satellite such as LANDSAT TM for the PGS or ALOS AVNIR-2 for the ALOSRP.

#### **5.1 RADARSAT SAR data processing system**

The RADARSAT SAR data processing system is a sub-system of the Product Generation System used to transform RADARSAT-1 and RADARSAT-2 raw SAR data into the georeferenced and geocoded image data. This system is a hybrid computer system between UNIX and Windows platform. An advantage of this system is combining power, scalability and reliability of the UNIX with the ease of operation of the Windows. The physical architecture diagram of the RADARSAT SDPS is illustrated in figure 3.

In figure 3, the multi-CPU UNIX server is the SGI Origin 350 executes the core processing software of the RADARSAT SDPS. Its processors are based on Microprocessor without Interlocked Pipeline Stages (MIPS) architecture so that they can take advantage of the multiprocessor environment to parallelize the processing operations to provide efficient, scalable, and accurate data product generation. The Archive Management System (AMS) is a component to manage the archived data in Framed Raw Expanded Data (FRED) format. It tracks and retrieves a large volume of archived data in online, near-line and offline locations. The Windows terminals are Windows operating system HP Workstation used to control and monitor the processing.

Fig. 3. RADARSAT SDPS Physical Architecture.

The RADARSAT SDPS is driven by a graphical user interface called Human Machine Interface (HMI) on the Windows terminal. The HMI provides the operator with full control over the product generation process via operator control panel. The product generation process is initiated by creating a work order. Work orders can be reviewed and edited via a work order editor panel. Multiple work orders executes in parallel, which each operator can customize to display only information of interest.

For image quality assessment, the HMI also provides the image viewer to perform visual quality assessment on an image. Image viewer tools includes map overlays, measuring distances, displaying average image intensity, displaying Doppler centroid plots and displaying product coverage. Map overlays turn on the overlays in the image to see various map features. Measuring distance allows operator to measure distance between any two points in the image. Average image intensity displays the image intensity in both range and azimuth direction. Doppler centroid plots display SAR Doppler centroid estimation results graphically. Product coverage used to check the product coverage against the expected product boundaries.

The RADARSAT SDPS software can be divided into four processing modules: Data Ingest module, SAR Processor module, Geocoded module and Product Formatting module. The logical architecture diagram of RADARSAT SDPS software is illustrated in figure 4.

The Data Ingest module is responsible for retrieving archived data in FRED format and transferring as signal data to the SAR processor module. The archived data sources could be (i) Magnetic Tape Device Storage (MTDS), (ii) Direct Archive System (DAS) or (iii) Robotic Tape Library (RTL). The MTDS is the offline storage, currently uses super digital linear tape (SDLT), the DAS is an online storage stores downlink data from RADARSAT satellites in the redundant array of independent disks (RAID), and RTL is the near-line storage using the automatic tape archive.

The SAR Processor module is used to focus the raw SAR data into single-look and multilook image data. It consists of two major software-based SAR processors: the Single-Beam

Gigabit Ethernet

The RADARSAT SDPS is driven by a graphical user interface called Human Machine Interface (HMI) on the Windows terminal. The HMI provides the operator with full control over the product generation process via operator control panel. The product generation process is initiated by creating a work order. Work orders can be reviewed and edited via a work order editor panel. Multiple work orders executes in parallel, which each operator can

For image quality assessment, the HMI also provides the image viewer to perform visual quality assessment on an image. Image viewer tools includes map overlays, measuring distances, displaying average image intensity, displaying Doppler centroid plots and displaying product coverage. Map overlays turn on the overlays in the image to see various map features. Measuring distance allows operator to measure distance between any two points in the image. Average image intensity displays the image intensity in both range and azimuth direction. Doppler centroid plots display SAR Doppler centroid estimation results graphically. Product coverage used to check the product coverage against the expected

The RADARSAT SDPS software can be divided into four processing modules: Data Ingest module, SAR Processor module, Geocoded module and Product Formatting module. The

The Data Ingest module is responsible for retrieving archived data in FRED format and transferring as signal data to the SAR processor module. The archived data sources could be (i) Magnetic Tape Device Storage (MTDS), (ii) Direct Archive System (DAS) or (iii) Robotic Tape Library (RTL). The MTDS is the offline storage, currently uses super digital linear tape (SDLT), the DAS is an online storage stores downlink data from RADARSAT satellites in the redundant array of independent disks (RAID), and RTL is the near-line storage using the

The SAR Processor module is used to focus the raw SAR data into single-look and multilook image data. It consists of two major software-based SAR processors: the Single-Beam

logical architecture diagram of RADARSAT SDPS software is illustrated in figure 4.

Windows Terminal

Windows Terminal

AMS

Windows Terminal

> Multi - CPU UNIX Server

Fig. 3. RADARSAT SDPS Physical Architecture.

customize to display only information of interest.

product boundaries.

automatic tape archive.

Fig. 4. RADARSAT SDPS Logical Architecture.

processor and the ScanSAR processor. The Single-Beam processor employs the Range-Doppler algorithm as a processing algorithm and suitable for processing Single Beam mode data while the ScanSAR processor employs the SPECAN algorithm as a processing algorithm and suitable for processing ScanSAR mode data. The processed data are georefernced image data stored on disk to be transferred to the Product Formatting module or the Geocoded module.

The Geocoded module is an optional module performs prior to the Product Formatting module. This module supports both systematic and precision geocoding. The digital elevation model (DEM) is employed to produces the systematic geocoded data. The ground truth sources in the form of ground control points (GCP) are used to refine a satellite acquisition model for the precision geocoded data. The output of the Geocoded module is geocoded image data stored on disk to be transferred to the Product Formatting module.

The Product Formatting module receives processed image data from the SAR processor module and the Geocoded module, formats the data, according to the MDA's data product specifications and then writes to output media. The data product format may be CEOS or GeoTIFF. Available output media of the data product can be in the form of disk, CD, DVD or electronics delivery i.e. FTP. The data product can be also archived back to the AMS.

Available data products generated from the RADARSAT SDPS are five georeferenced data products and two geocoded data products. There are single-look complex (SLC), SAR georeferenced fine resolution (SGF), SAR georeferenced extra-fine resolution (SGX), ScanSAR narrow (SCN), ScanSAR wide (SCW), SAR systematic geocoded (SSG) and SAR precision geocoded (SPG).

The throughput of the RADARSAT SDPS generates one standard georeferenced or systematic geocoded data product within twenty minutes. For the eight operation hours, minimum standard thirty SSG data products can be generated. The efficient resources sharing and parallel processing architecture of the system enabling up to twelve work orders can be processed at the same time.

#### **5.2 ALOS SAR data processing system**

The ALOS SAR data processing system is a sub-system of the ALOS Data Reception and Processing system used to transform ALOS raw PALSAR data into the standard data products and higher level data products. The ALOS SDPS consists of processing cluster servers, higher level processing servers, a product generation server, an archive server and a workstation terminal. All servers are Linux-based Dell server with Xeon processor. The physical architecture diagram of the ALOS SDPS is illustrated in figure 5.

In figure 5, the processing cluster servers and the higher level processing servers are multiple processors, multiple users and multiple work-order environments, so it can provide high capacity and excellent performance of the system. The data archive server is used to collect and maintain data received directly from ALOS satellite, and received as level 0 from JAXA, as well as higher level data products. All archived data are stored on the automatic tape archive in Sky Telemetry Format (STF). A workstation terminal is used for controlling and monitoring processing of data product via a product generation server. The throughput of the ALOS SDPS for each product and each sensor is at least ten scenes per eight working hours.

Fig. 5. ALOS SDPS Physical Architecture.

Available data products generated from the RADARSAT SDPS are five georeferenced data products and two geocoded data products. There are single-look complex (SLC), SAR georeferenced fine resolution (SGF), SAR georeferenced extra-fine resolution (SGX), ScanSAR narrow (SCN), ScanSAR wide (SCW), SAR systematic geocoded (SSG) and SAR

The throughput of the RADARSAT SDPS generates one standard georeferenced or systematic geocoded data product within twenty minutes. For the eight operation hours, minimum standard thirty SSG data products can be generated. The efficient resources sharing and parallel processing architecture of the system enabling up to twelve work

The ALOS SAR data processing system is a sub-system of the ALOS Data Reception and Processing system used to transform ALOS raw PALSAR data into the standard data products and higher level data products. The ALOS SDPS consists of processing cluster servers, higher level processing servers, a product generation server, an archive server and a workstation terminal. All servers are Linux-based Dell server with Xeon processor. The

In figure 5, the processing cluster servers and the higher level processing servers are multiple processors, multiple users and multiple work-order environments, so it can provide high capacity and excellent performance of the system. The data archive server is used to collect and maintain data received directly from ALOS satellite, and received as level 0 from JAXA, as well as higher level data products. All archived data are stored on the automatic tape archive in Sky Telemetry Format (STF). A workstation terminal is used for controlling and monitoring processing of data product via a product generation server. The throughput of the ALOS SDPS for each product and each sensor is at least ten scenes per

> Higher Level Processing Servers

Archive Server

Gigabit Ethernet

Workstation Terminal

physical architecture diagram of the ALOS SDPS is illustrated in figure 5.

Processing Cluster Servers

> Product Generation Server

Fig. 5. ALOS SDPS Physical Architecture.

precision geocoded (SPG).

eight working hours.

orders can be processed at the same time.

**5.2 ALOS SAR data processing system** 

The ALOS SDPS software can be divided into four processing modules: Data Ingest module, PALSAR Processor module, Higher Level Processor module and Product Formatting module. The logical architecture diagram of the ALOS SDPS is illustrated in figure 6.

Fig. 6. ALOS SDPS Logical Architecture.

The Data Ingest module is used for retrieving archived data or level 0 data in STF format from the Robotic Tape Library (RTL). There are two possible archived data sources: (i) direct receiving ALOS PALSAR data received at the TEOC (Wide Area Observation Mode or WB1 only) and (ii) imported data from JAXA stored on DTF-2 and LTO-4. The archived data is then transferred to the PALSAR Processor module.

The PALSAR Processor module used to focus on the raw SAR data into standard image data and intermediate image data. It consists of two major software-based SAR processors: the Single Beam processor and the ScanSAR processor. The Single Beam processor employs the Range-Doppler algorithm with squint imaging mode (RDA-SIM) as a processing algorithm. It is suitable for processing Single Beam mode data. The ScanSAR processor employs SPECAN algorithm with chirp transform and secondary range compression (SPECAN-SRC) as a processing algorithm. It is suitable for processing Scanning SAR mode data.

When the STF archived data arrives at the PALSAR Processor module, the sky telemetry data and corresponding parameter are extracted and formatted into CEOS format. Then the formatted data are processed with Doppler parameter file by either of two SAR processors depending on the input data type. The processed data are stored on disk. The RDA-SIM processor can produce the standard SLC image data (L1.1), and level 1.5 (L1.5) image data referred to georeferenced and geocoded images. The data product is CEOS format with the available output media on CD, DVD or electronics delivery i.e. FTP.

#### **6. SAR image quality characteristics**

The image quality characteristic consists of a large variety of different parameters. The basic image quality parameters for general users are range resolution, azimuth resolution, peak side lobe ratio, integrated side lobe ratio and absolute location error. The specifications of these parameters are defined by the satellite operating agency and each satellite differently. The specifications of the image quality characteristics for RADARSAT-1 SLC Wide beam mode data products and ALOS level 1.1 Fine beam mode data products are summarized in table 1 and table 2. (MacDonald, Dettwiler and Associates [MDA], 2000; Earth Remote Sensing Data Analysis Center [ERSDAC], 2009) provide a full set of image quality characteristics for RADARSAT-1 and ALOS data products respectively.


Table 1. RADARSAT-1 SLC wide beam data products image quality characteristics.


Table 2. ALOS level 1.1 fine beam data products image quality characteristics.

Impulse response function is a two-dimensional signal appearing in a processed image as a result of the compression of returned energy from a point target. The width of the impulse response function at a power level 3 dB below the peak of the function is defined to be the impulse response width (IRW). The IRW is commonly referred to as the resolution, and its values are given separately for the two dimensions of the image. The IRW in the range direction is defined as the range resolution (RR), and the IRW in the azimuth direction is defined as azimuth resolution (AR). The azimuth resolution is constant within each beam.

A side lobe of the impulse response function is any local maximum other than those within the contour around the peak, which passes through points 3 dB below the main lobe peak. Side lobes are measured relatively to the main lobe peak. The peak side lobe ratio (PSLR) is defined to be the ratio of the maximum side lobe level and the main lobe level. The integrated side lobe ratio (ISLR) is defined to be the ratio of the integrated energy in the side lobe region of the two dimensional (range and azimuth) impulse response function relative to the integrated energy in the main lobe region. The absolute location error (ALE) is specified as the distance along the ground between the actual geographical location of a point within a processed image and the location as determined from the data product. It may be separated in two direction, range absolute location error (RALE) and azimuth absolute location error (AALE).

### **7. SAR interferometry**

52 Earth Observation

When the STF archived data arrives at the PALSAR Processor module, the sky telemetry data and corresponding parameter are extracted and formatted into CEOS format. Then the formatted data are processed with Doppler parameter file by either of two SAR processors depending on the input data type. The processed data are stored on disk. The RDA-SIM processor can produce the standard SLC image data (L1.1), and level 1.5 (L1.5) image data referred to georeferenced and geocoded images. The data product is CEOS format with the

The image quality characteristic consists of a large variety of different parameters. The basic image quality parameters for general users are range resolution, azimuth resolution, peak side lobe ratio, integrated side lobe ratio and absolute location error. The specifications of these parameters are defined by the satellite operating agency and each satellite differently. The specifications of the image quality characteristics for RADARSAT-1 SLC Wide beam mode data products and ALOS level 1.1 Fine beam mode data products are summarized in table 1 and table 2. (MacDonald, Dettwiler and Associates [MDA], 2000; Earth Remote Sensing Data Analysis Center [ERSDAC], 2009) provide a full set of image quality

**Parameter Specification** 

**Parameter Specification** 

available output media on CD, DVD or electronics delivery i.e. FTP.

characteristics for RADARSAT-1 and ALOS data products respectively.

Range Resolution (RR) 15.7 m Azimuth Resolution (AR) 8.9 m Peak Side Lobe Ratio (PSLR) < -20.0 dB Integrated Side Lobe Ratio (ISLR) -11.2 dB Absolute Location Error (ALE) < 750 m

Table 1. RADARSAT-1 SLC wide beam data products image quality characteristics.

Range Resolution (RR) 16.0 m – 17.1 m

Azimuth Resolution (AR) 5.8 m Peak Side Lobe Ratio (PSLR) < -20.0 dB Integrated Side Lobe Ratio (ISLR) < -15.0 dB Absolute Location Error (ALE) < 750 m

Table 2. ALOS level 1.1 fine beam data products image quality characteristics.

**6. SAR image quality characteristics** 

A more recent geodetic measurement technique is interferometric synthetic aperture radar (InSAR) which based on the combination of two radar images. It's earliest the measurement for allowing us to retrieve a Digital Elevation Model, and it has been developed to measure the large-scale surface deformation monitoring or so call Differential InSAR (D-InSAR). The principle of D-InSAR is to first obtain two interferograms of a study area, and then make a differential between for the detection of deformation information. Then, the topographic phase will be removed, and leave just only deformation phase. However, there are several limitations essentially due to temporal and geometric decorrelation. These limitations are well addressed in the time series InSAR techniques, which will be introduced in the following.

#### **7.1 Permanent scatterer InSAR (PSI)**

First algorithms of Permanent Scatterer technique were developed by (Ferretti et al., 2000, 2001). Similar processing strategies have been developed by (Crosetto et al., 2003; Lyons et al., 2003; Werner et al., 2003; Kampes, 2005). This method has been very successful for InSAR analysis of radar scenes containing large numbers of man-made structures. The numbers of differential interferograms are generated with respect to a single master (see figure 7). Pixels are selected based on its amplitude stability along the whole set of images, but the stable scatterers with low amplitude may not be detected.

In contrast, StaMPS (Hooper et al., 2007) algorithm uses spatial correlation of phase measurements, so it is applicable in areas undergoing non-steady deformation with no prior knowledge of the variation in deformation rate. PS pixels are defined by phase stability, so PS candidates are selected on the basis of their phase characteristics. It takes advantage of pixels dominated by a single scatterer to reduce the influence of atmosphere and decorrelation. Then, the phase is corrected for non-spatially correlated errors and "unwrapped" using a statistical-cost approach (Hooper, 2010). After phase unwrapping, spatially-correlated DEM error is estimated from the correlation of phase with perpendicular baseline. The phase is the re-unwrapped with the DEM error subtracted, to improve unwrapping accuracy for larger baselines. Atmospheric artefacts are estimated by high-pass temporal filtering and low-pass spatial filtering. Finally, we can subtract this signal from the estimate value of phase and leave just deformation phase while spatial uncorrelated error terms can be modeled as noise.

Fig. 7. Interferograms for PS using single master with no spectral filtering.

#### **7.2 Small baseline subset (SBAS)**

54 Earth Observation

PS candidates are selected on the basis of their phase characteristics. It takes advantage of pixels dominated by a single scatterer to reduce the influence of atmosphere and decorrelation. Then, the phase is corrected for non-spatially correlated errors and "unwrapped" using a statistical-cost approach (Hooper, 2010). After phase unwrapping, spatially-correlated DEM error is estimated from the correlation of phase with perpendicular baseline. The phase is the re-unwrapped with the DEM error subtracted, to improve unwrapping accuracy for larger baselines. Atmospheric artefacts are estimated by high-pass temporal filtering and low-pass spatial filtering. Finally, we can subtract this signal from the estimate value of phase and leave just deformation phase while spatial

uncorrelated error terms can be modeled as noise.

Fig. 7. Interferograms for PS using single master with no spectral filtering.

The Small Baseline Subset (SBAS) proposed by (Berardino et al., 2001, 2002) that the data pairs involved in the generation of the interferograms are carefully selected in order to minimize the spatial baseline. Thus, the mitigation of the decorrelation phenomenon and topography errors will be reduced. The SBAS method was initially exploited the investigation of large scale deformations by calculating the time sequence deformation and estimating DEM error and the atmospheric artifact in a similar way as PS. Noise is then further reduced by multilooking and applying range and azimuth filters (Just et al., 1994) with the aim of unwrapping them spatially. SB methods (Hooper, 2008) on the other hand seek to minimize the separation in time, in space and Doppler frequency of acquisition pairs to maximize the correlation of the interferograms formed. Slow-varying filtered phase (SFP) pixels are identified among the candidate pixels the same way as for PS pixels. For each pixel in the topographically corrected interferograms, its phase can be considered to the wrapped sum of five terms as (Hooper, 2008)

$$
\phi\_{\text{int}, \mathbf{x}, i} = \phi\_{\text{def}\_{\text{'}}, \mathbf{x}, i} + \phi\_{\text{top}, \mathbf{x}, i} + \phi\_{\text{attm}, \mathbf{x}, i} + \phi\_{\text{orb}, \mathbf{x}, i} + \phi\_{\text{n}, \mathbf{x}, i} \tag{2}
$$

where *def* , , *x i* is the deformation phase in the satellite line-of-sight (LOS) direction, *top*, , *x i* is the topographic phase caused by uncertainty in the DEM, *atm x i* , , is the atmospheric phase delay, *orb x i* , , is orbital phase error, and *nxi* , , is the noise term.

Fig. 8. Interferograms for SBAS using multiple masters with spectral filtering.

All phases error can be subtracted, and leave just deformation phase as the same algorithm used for PSI. Note that different sets of pixels are selected based on different sets of interferograms (single master with no spectral filtering vs. multiple masters with spectral filtering (see figure 8).

#### **8. Application of SAR interferometry in Thailand**

#### **8.1 Land subsidence in Bangkok, Thailand**

Land subsidence in Bangkok is caused primarily by groundwater over-pumping for the past decade. Monitoring has been carried out by levelling survey technique. The technique cannot provide many benchmarks due to the cost and the difficulty to maintain the overall benchmarks. The locations of the benchmarks are also limited by the urban development to access any area that should be considered. On the other hand, InSAR technology has become more interested since it is overcome the limitation of levelling survey technique, and it has been firstly applied by (Kuehn et al., 2004) during the time spanning February 1996 to October 1996. They reported the maximum subsidence rate -30 mm per year in the southeast and southwest alongside Chao Phraya River. However, with only 4 images and the short time span, it was difficult to estimate the deformation reliably due to decorrelation noise and variable atmospheric phase delay. Nevertheless, the maximum subsidence rates for this area agreed with the levelling survey.

Later on, (Worawattanamateekul, 2006) applied PSI technique using ERS1 and ERS2 data (16 and 10 interferograms) for the time period of 1992-2000. However, the limited number of interferograms made it difficult to achieve reliable results from PSI analysis, as indicated by the accuracy of -6 to -8 mm per year reported by the study. (Aobpaet et al., 2008) applied L-Band ALOS-PALSAR to evaluate the potential and possibility of land subsidence detection using the DInSAR technique. The subsidence map derived from ALOS PALSAR L-band between November 25, 2007 and April 11, 2008 for Bangkok revealed the spatial extent of the deformations and subsidence estimates. However, the subsidence might not reflect longterm subsidence rates because of the short temporal base line and the seasonal cycle of surface movement. (Aobpaet et al., 2009) showed the potential of time series analysis by detecting more than 200,000 pixels that could be used as monitoring points. The results showed a maximum subsidence rate of around -15 mm per year in eastern central Bangkok. However, the study area is preliminary study on sub-scene basis for the processing approach in order to reduce analyzing time and modifying parameters.

The latest study has been successes on apply InSAR time series algorithms, the Persistent Scatterer and Small Baseline, to remotely detect subsidence in Bangkok (Aobpaet et al., 2011). The data set is composed of 19 images acquired in fine beam mode by the RADARSAT-1 satellite (see figure 9a). More or less 300,000 pixels were successfully detected as monitoring points in the analysis, a two order of magnitude greater than the number of ground monitoring points (see figure 10). The average pixel density in the study area is 120 PS per km2 with over 150 PS per km2 in the urbanized areas. The subsidence velocities fall mostly between 0 to -24 mm per year (see figure 9b). Finally, the validation of the results against levelling surveys has been performed and found agreement at one standard deviation in 87% of cases. They concluded that InSAR time series analysis shows strong potential as an alternative tool for monitoring land subsidence in Bangkok.

All phases error can be subtracted, and leave just deformation phase as the same algorithm used for PSI. Note that different sets of pixels are selected based on different sets of interferograms (single master with no spectral filtering vs. multiple masters with spectral

Land subsidence in Bangkok is caused primarily by groundwater over-pumping for the past decade. Monitoring has been carried out by levelling survey technique. The technique cannot provide many benchmarks due to the cost and the difficulty to maintain the overall benchmarks. The locations of the benchmarks are also limited by the urban development to access any area that should be considered. On the other hand, InSAR technology has become more interested since it is overcome the limitation of levelling survey technique, and it has been firstly applied by (Kuehn et al., 2004) during the time spanning February 1996 to October 1996. They reported the maximum subsidence rate -30 mm per year in the southeast and southwest alongside Chao Phraya River. However, with only 4 images and the short time span, it was difficult to estimate the deformation reliably due to decorrelation noise and variable atmospheric phase delay. Nevertheless, the maximum subsidence rates for this

Later on, (Worawattanamateekul, 2006) applied PSI technique using ERS1 and ERS2 data (16 and 10 interferograms) for the time period of 1992-2000. However, the limited number of interferograms made it difficult to achieve reliable results from PSI analysis, as indicated by the accuracy of -6 to -8 mm per year reported by the study. (Aobpaet et al., 2008) applied L-Band ALOS-PALSAR to evaluate the potential and possibility of land subsidence detection using the DInSAR technique. The subsidence map derived from ALOS PALSAR L-band between November 25, 2007 and April 11, 2008 for Bangkok revealed the spatial extent of the deformations and subsidence estimates. However, the subsidence might not reflect longterm subsidence rates because of the short temporal base line and the seasonal cycle of surface movement. (Aobpaet et al., 2009) showed the potential of time series analysis by detecting more than 200,000 pixels that could be used as monitoring points. The results showed a maximum subsidence rate of around -15 mm per year in eastern central Bangkok. However, the study area is preliminary study on sub-scene basis for the processing

The latest study has been successes on apply InSAR time series algorithms, the Persistent Scatterer and Small Baseline, to remotely detect subsidence in Bangkok (Aobpaet et al., 2011). The data set is composed of 19 images acquired in fine beam mode by the RADARSAT-1 satellite (see figure 9a). More or less 300,000 pixels were successfully detected as monitoring points in the analysis, a two order of magnitude greater than the number of ground monitoring points (see figure 10). The average pixel density in the study area is 120 PS per km2 with over 150 PS per km2 in the urbanized areas. The subsidence velocities fall mostly between 0 to -24 mm per year (see figure 9b). Finally, the validation of the results against levelling surveys has been performed and found agreement at one standard deviation in 87% of cases. They concluded that InSAR time series analysis shows strong

approach in order to reduce analyzing time and modifying parameters.

potential as an alternative tool for monitoring land subsidence in Bangkok.

filtering (see figure 8).

**8. Application of SAR interferometry in Thailand** 

**8.1 Land subsidence in Bangkok, Thailand** 

area agreed with the levelling survey.

(a)

Fig. 9. (a) The study area of Bangkok has been presented using RADARSAT-1 data in Fine beam mode with the coverage area 2,500 km2. (b) The subsidence rate from InSAR indicated that the maximum subsidence rate is -24 mm per year relative to all pixels in the whole scene with respect to the reference benchmark represented by black star.

Fig. 10. The south-east Chao Phraya river estuary area which many permanent structures can serve as monitoring points which represent the subsidence rate in mm per year.

#### **9. Conclusion**

The establishment of the GISTDA and the long history of Thailand Earth Observation Center are the significants development and contribution to remote sensing activities in Thailand. From that time, Thailand has become one of the most successful countries for the space technology development program especially in remote sensing applications such as flood monitoring, fire monitoring, rice crop monitoring, disaster management, etc. Thus, the capability of direct acquisition in real-time data from SAR satellites such as RADARSAT-1 and RADARSAT-2 make the user who interested in InSAR can set up the plan to acquiring the data from current SAR satellite in time series analysis. Moreover, TEOC was the ALOS sub node, so the large ALOS data archive is still very attractive for the users' intent to study the past disaster or relate applications that may helpful for the prediction model creation.

Finally, the fully operational of TEOC can provide the customers and the users with rapid real-time satellite data for various applications to meet the country's requirement. The application of land subsidence in Bangkok reveals the potential of InSAR time series analysis, but the knowledge how to get the data is much challenged since the large amount of data is required. With the clarification of TEOC systems for especially SAR user, we believe that TEOC will be able to serve as a complimentary component to the development of remote sensing technology and space activities in Thailand and international.

### **10. References**

58 Earth Observation

Fig. 10. The south-east Chao Phraya river estuary area which many permanent structures can serve as monitoring points which represent the subsidence rate in mm per year.

The establishment of the GISTDA and the long history of Thailand Earth Observation Center are the significants development and contribution to remote sensing activities in Thailand. From that time, Thailand has become one of the most successful countries for the space technology development program especially in remote sensing applications such as flood monitoring, fire monitoring, rice crop monitoring, disaster management, etc. Thus, the capability of direct acquisition in real-time data from SAR satellites such as RADARSAT-1 and RADARSAT-2 make the user who interested in InSAR can set up the plan to acquiring the data from current SAR satellite in time series analysis. Moreover, TEOC was the ALOS sub node, so the large ALOS data archive is still very attractive for the users' intent to study the past disaster or relate applications that may helpful for the prediction model creation.

Finally, the fully operational of TEOC can provide the customers and the users with rapid real-time satellite data for various applications to meet the country's requirement. The application of land subsidence in Bangkok reveals the potential of InSAR time series analysis, but the knowledge how to get the data is much challenged since the large amount

**9. Conclusion** 


www.eorc.jaxa.jp/ALOS/en/doc/fdata/ALOS\_HB\_RevC\_EN.pdf

