**2. Remote sensing and coastal environmental sensitivity for oil spill**

#### **2.1 Remote sensing**

310 Remote Sensing – Applications

coastal zone is placed in the context of the tropical humid regions, in a low-lying area with active processes of erosion, sedimentation and neotectonics. Also, it is marked by a great hydrologic influence; in a meso- to macrotidal area (Souza Filho, 2005). It is a high-density drainage network, in which the Amazon River discharges a volume of water of 6.3 trillion

Such environmental characteristics are responsible for the development of an extensive mud plain and mangrove area which is located in three States (Amapá, Pará and Maranhão), is approximately 8,386 km² wide, and contains 80% of all mangroves in Brazil (Herz, 1991). Where macrotides are present, the area of a flooded mangrove may extend for up to 30 km inland, and the estuaries themselves as much as 80 km (Souza Filho, 2005) (Figure 1). These extensive mud and mangroves plains are considered to be one of the most sensitive areas to oil spills. Also, these mangroves are along national and international ships routes. Transportation and storage are mainly responsible for oil spills in Amazonian coastal zone, since there is no expressive exploration. In 2001, in the state of Pará, approximately 1900

Fig. 1. Amazonian coastal zone in radar SRTM representation (source: modified from Souza

In this sense, researches from Federal University of Pará have been working on several projects since 2001 aiming to study the Amazonian coastline and the impact of oil spills on

Filho et al., 2005a)

m³/year and of sediment estimated at 1.2 billion tons/year (Meade et al., 1985).

tons of oil sank near the Port of Vila do Conde (Berredo et al., 2001).

Remote sensing tools are essential for the construction of maps. These tools help in the precise delimitation of coastlines and specific landforms. The selection of appropriate remote sensing data and applicable digital image processing techniques involves a compromise between costs and mapping capabilities, including coverage area, and spatial resolution (Green, 2000).

For risk maps, remote sensing are fundamental. Risk appears in a broader context in humans transform of the natural into a cultural environment, with the aim of improving living conditions and serving human wants and needs (Turner et al., 1990). There are several sources of hazards to the environment and to society, some of them originated in human activities (Smith & Petley, 2008).

Oil spills are an example of this technological risk. Information and detection about oil spills can be collected through remote sensing tools for prevention planning, as well as river/ocean pollution monitoring and restoration. Some reviews of the use of remote sensing and oil spills including Brekke & Solberg (2005) and Fingas & Brown (2000).

<sup>1</sup> PETROBRAS is the large oil company in Brazil

Remote Sensing and Environmental Sensitivity for Oil Spill in the Amazon, Brazil 313

Over-pass Frequency (days)

planning and monitoring SAR RADARSAT-1 8-100 24 days 45-500km

15-120 16 days 183-

Spot-3 10-20 26 days 60x60km

Cbers-2 20 26 days 113 km

Cbers-2 80-160 26 days 120 km

Cbers-2 260 5 days 890 km

Table 1. Characteristics of some existing sensors for oil spill management applications.

As

As required -

Airplane Altitude

Dependent

Dependent

Airplane 10-50 As required 60-80km Detect and identify the

Imagery

185km

/100km

area Application

spills and coastal environments – Strategic

polluter, the extent and type of oil spill and the cleaning necessity; Environmental mapping – Strategic and tactical planning

Detect oil spill if the weather conditions are good; can discriminate false positives; identify and mapping environments – Strategic and tactical planning

Detect oil spill if the weather conditions are good; identify and mapping environments – Strategic and tactical planning

Detect oil spill if the weather conditions are good; capable to detect thermal surface differentiations - Strategic and tactical planning

Detect oil spill if the weather conditions are good; monitoring; identify and mapping environments – Strategic planning

environmental documentation. The infrared sensor for measure the thickness of oil slicks – Operational planning

required - Oil spill and coastal

176 days 100km Identify large offshore

Spatial resolution (m)

ERS-2 30 3, 35 and

SAR Airplane 1-10 As required -

Landsat 5 Landsat 6 Landsat 7

Sensors Platform

Spaceborne

Airbone

Spaceborne

IRMSS Cbers-1;

WFI Cbers-1;

Airbone

camera Airplane Altitude

Video camera

Still

CCD Cbers-1;

HRV Spot-2

SAR

SLAR

MSS,TM, ETM, ETM +

RADAR

OPTICAL

For a coastal environment, remote sensors can provide information about the physical characteristics of the shoreline, coastal ecosystems dynamics, water quality, and land use/occupation. This information could be mapped at different scales generating cartographic products using all types of sensors and specific digital image processing (Jensen, 1996). Sensors can provide timely and valuable information about oil spills, including the location and extent, thickness distribution, and oil type in order to estimate environmental damage, take appropriate response activities, and to assist in clean-up operations for oil spill contingency planning (Grüner, 1991).

The most common sensors utilized to detect oil spills and to map coastal environments are: optical (visible, infrared sensors and ultraviolet sensors) or radar. Both types of sensor may be acquired at terrestrial, sub-orbital or orbital levels. At terrestrial level, both still and video cameras are commonly used. At the sub-orbital level (or airborne remote sensing), airplanes is the most commonly utilized platform. At the orbital level, satellites are usually used as a platform for sensors. Satellite differs from airborne remote sensing due to timing and frequency of the data collection, the demand of good climate conditions and the time required for processing the dataset (Jha et al., 2008). Aiming to compare sensors, a brief description is given in Table 1.

#### **2.1.1 Optical**

Optical sensors can be composed by three bands in the electromagnetic spectrum. These sensors are usually composed by multispectral bands in visible and infrared intervals from the electromagnetic spectrum. In the visible region (350 to 750 nm), oil has a higher surface reflectance than water, but also shows limited nonspecific absorption tendencies (Jha et al., 2008). Instruments such as cameras, films and spectrometers are optical techniques for remote sensing with the benefit of low cost. Normally, visible sensors cannot operate at night as they depend on the reflectance of sunlight, but, in the case of oil spills they can be used to create environmental and logistic maps of the coast to subsidize field trips and first risk management decisions. The infrared sensors are at the 0,7-14 μm intervals in the electromagnetic spectrum. Solar radiation is partially absorbed and emitted as thermal energy by oil. This is thermal energy concentrated in the thermal infrared region with a distinct spectral signature; water has a higher emissivity (Salisbury et al., 1993). Infrared sensors can provide information about the relative thickness of oil slicks, but these sensors are unable to detect emulsions of oil in water when oil is diluted to 70% water (Fingas & Brown, 1997). Infrared is reasonably inexpensive, but has limitations related to false positive results generated by weeds and shorelines (Fingas & Brown, 2000).

Ultraviolet sensor scanners capture ultraviolet radiation (0,003 – 0,38 μm) reflected by the sea surface for detecting oil spills. Oil is more reflective than water in the ultraviolet region. Limitations of this sensor are related to undetected information greater than 10 microns and false images produced by such hindrances as wind slicks, sun glints, and biogenic material (Grüner, 1991).

#### **2.1.2 Radar**

Radar is an active sensor (not dependent on electromagnetic radiation from the sun) and operates in a radio wave region (1m – 104m). Radar sensors can have two principal

For a coastal environment, remote sensors can provide information about the physical characteristics of the shoreline, coastal ecosystems dynamics, water quality, and land use/occupation. This information could be mapped at different scales generating cartographic products using all types of sensors and specific digital image processing (Jensen, 1996). Sensors can provide timely and valuable information about oil spills, including the location and extent, thickness distribution, and oil type in order to estimate environmental damage, take appropriate response activities, and to assist in clean-up

The most common sensors utilized to detect oil spills and to map coastal environments are: optical (visible, infrared sensors and ultraviolet sensors) or radar. Both types of sensor may be acquired at terrestrial, sub-orbital or orbital levels. At terrestrial level, both still and video cameras are commonly used. At the sub-orbital level (or airborne remote sensing), airplanes is the most commonly utilized platform. At the orbital level, satellites are usually used as a platform for sensors. Satellite differs from airborne remote sensing due to timing and frequency of the data collection, the demand of good climate conditions and the time required for processing the dataset (Jha et al., 2008). Aiming to compare sensors, a brief

Optical sensors can be composed by three bands in the electromagnetic spectrum. These sensors are usually composed by multispectral bands in visible and infrared intervals from the electromagnetic spectrum. In the visible region (350 to 750 nm), oil has a higher surface reflectance than water, but also shows limited nonspecific absorption tendencies (Jha et al., 2008). Instruments such as cameras, films and spectrometers are optical techniques for remote sensing with the benefit of low cost. Normally, visible sensors cannot operate at night as they depend on the reflectance of sunlight, but, in the case of oil spills they can be used to create environmental and logistic maps of the coast to subsidize field trips and first risk management decisions. The infrared sensors are at the 0,7-14 μm intervals in the electromagnetic spectrum. Solar radiation is partially absorbed and emitted as thermal energy by oil. This is thermal energy concentrated in the thermal infrared region with a distinct spectral signature; water has a higher emissivity (Salisbury et al., 1993). Infrared sensors can provide information about the relative thickness of oil slicks, but these sensors are unable to detect emulsions of oil in water when oil is diluted to 70% water (Fingas & Brown, 1997). Infrared is reasonably inexpensive, but has limitations related to false positive

Ultraviolet sensor scanners capture ultraviolet radiation (0,003 – 0,38 μm) reflected by the sea surface for detecting oil spills. Oil is more reflective than water in the ultraviolet region. Limitations of this sensor are related to undetected information greater than 10 microns and false images produced by such hindrances as wind slicks, sun glints, and biogenic material

Radar is an active sensor (not dependent on electromagnetic radiation from the sun) and operates in a radio wave region (1m – 104m). Radar sensors can have two principal

operations for oil spill contingency planning (Grüner, 1991).

results generated by weeds and shorelines (Fingas & Brown, 2000).

description is given in Table 1.

**2.1.1 Optical** 

(Grüner, 1991).

**2.1.2 Radar** 


Table 1. Characteristics of some existing sensors for oil spill management applications.

Remote Sensing and Environmental Sensitivity for Oil Spill in the Amazon, Brazil 315

from 1 (low) to 10 (high). This Vulnerability Index became the standard for coastal management, planning and research about the effects of oil spills on different types of coastline. Over time, this index evolved and was modified, leading eventually to the

The ESI should be represented cartographically as maps in different scales for different goals. The first ESI map was produced in 1979, in response to the advance toward the coast of oil resulting from the blowout of the IXTOC 1 oil-well in the Gulf of Mexico. In the 1980s, ARPEL produced an innovative ESI atlas for the whole coast of the United States, including Alaska and the Great Lakes, to be used for the planning of contingency measures in response to oil spills (NOAA, 2002). From this moment on, ESI maps have been an integral component of response and contingency planning for oil spills, looking for the protection of life, the reduction of environmental impacts, and facilitation of the response efforts. These atlases were integrated by color printed maps on a two dimensional representation of a

After the 1990's, NOAA (2002) standardized output formats and symbols for ESI maps construction. The basic necessary information is 1) shoreline classification; 2) biological resources; 3) human-use resources. The shoreline classification scheme is based on an understanding of the physical and biological characteristics of the shoreline environment. Relationships among physical processes, exposure to wave and tidal energy, slope, substrate type (i.e. grain size, mobility, penetration and/or burial, and mobility), and associated biota produce specific geomorphic/ecologic shoreline types. Shoreline classification helps to identify oil spill origin and impacts and the best cleanup methods for a specific shoreline type. The sensitivity ranking was developed for the estuarine settings and is slightly modified for lakes and rivers. The human use resources relate to specific, valuable specific areas because of their use, such as beaches, parks and protected marine areas, water intakes, fisheries, tourism, economic sectors, and archaeological sites. The biological resources include the study and maps of oil-sensitive biological and

**3. Remote sensing and coastal environmental sensitivity in Brazil** 

Brazil has an expansive coastline through the equatorial region to the subtropical latitude of the south hemisphere. The length is approximately 8.500 km with 17 of the 26 states of the country lying on the coast of the Atlantic Ocean. The Brazilian coast is defined by the National Plan for Coastal Management (law 7661/1988), as the geographic space where there are air, sea and land interacts, which includes renewable and non-renewable resources

A diversity of coastal environments and population densities are found along the Brazilian coast. Population is higher in state capitals than in the other coastal municipalities. Environments vary from very productive, such as mangroves, to rocky and artificial manmade structures. Man-made structures, such as ports are established along the entire

Ports are high-risk areas, and oil spill monitoring is clearly important there. In 2000, two large oil spills occurred at Baía de Guanabara (Rio de Janeiro) and Paraná, both resulting from pipeline ruptures. After these accidents, fundamental changes have been made to

development of the Environmental Sensitivity Index (ESI).

three-dimensional world and high production costs.

ecological resources.

along a maritime and terrestrial border.

coastline of Brazil (Figure 2).

instruments: Side-Looking Airborne Radar (SLAR) and Synthetic Aperture Radar (SAR). Radar is a very powerful and useful sensor for searching large areas, observing oceans at night, and capturing images during cloudy weather conditions. The presence of an oil spill can be detected without thickness estimation or oil type recognition. In the radar image, the leak appears as a dark area in contrast to the bright image of the ocean because radar waves are reflected by capillary waves on the ocean (Brown et al., 2003). For a coastal environment, mapping SAR is already considered to be a powerful tool for geomorphologic mapping, providing relevant information about the emergence and submergence of the coast (Souza Filho et al., 2009a).

SLAR is an old technology predominantly used for airborne remote sensing (Fingas & Brown, 2000). Airborne surveillance is limited by high costs and is less efficient for wide area observation due to its limited coverage. SAR has greater spatial range and resolution than the SLAR because it uses the forward motion of the aircraft to synthesize a very long antenna, thereby achieving very good spatial resolution, at the expense of sophisticated electronic processing (Mastin et al., 1994). SAR can be used to provide an initial warning because aircrafts are more suitable to identify the polluter, the extent, and the type of spill.

For large scale oil spill detection, satellite platforms, including ERS-1 and -2, Radarsat, and JERS-1, are commonly used for large scales oil spills (Fingas & Brown, 2005). Radar satellites, including ERS-1 and -2, Radarsat, and JERS-1, have been useful for mapping known large offshore spills (Biegert et al., 1997). On the other hand, optical satellite imagery does not offer much potential for oil spill detection (Fingas & Brown, 2000). However, to map coastal environments, geomorphology and its sensitivity, multi-sensor data fusion such as optical and radar has proved to be a successful tool (Souza Filho et al., 2009b).

#### **2.2 Coastal environmental sensitivity to oil spills**

The inter-relationships involving natural resources and human societies have led to a concentration of human activities, services and survival strategies in the coastal environment (Viles & Spencer, 1995; Muehe & Neves, 1995; Pernetta & Elder, 1992). The unique natural geodynamics, the highly productive and extremely diverse biological systems extending from coastal lands to deep water regions (Malthus & Mumby, 2003), the growing land use changes and the pressure on natural resources (MEA, 2005) transform the coastal zone into a conflict area. Oil exploration, transportation and storage have increased the technological risk in this zone.

Areas neighboring major ports (environmental and human populated) may be affected by oil transportation, tank cleaning and oil storage procedures in a port area (Noernberg & Lana, 2002). One of the initial concerns about oil spills result in a necessity for the construction of maps that indicate which type of environment and human resources will be affected. In the mid 1970s, scientists from the National Oceanic and Atmospheric Administration (NOAA) and the American Coast Guard of the United States began to study and classify the sensitivity of coastal environments to oil spill.

This classification was based, initially, on the vulnerability index to oil spills proposed by Gundlach & Hayes (1978). Coastal area is segmented considering environmental and geomorphologic characteristics and then classified using the Vulnerability Index, scaled

instruments: Side-Looking Airborne Radar (SLAR) and Synthetic Aperture Radar (SAR). Radar is a very powerful and useful sensor for searching large areas, observing oceans at night, and capturing images during cloudy weather conditions. The presence of an oil spill can be detected without thickness estimation or oil type recognition. In the radar image, the leak appears as a dark area in contrast to the bright image of the ocean because radar waves are reflected by capillary waves on the ocean (Brown et al., 2003). For a coastal environment, mapping SAR is already considered to be a powerful tool for geomorphologic mapping, providing relevant information about the emergence and submergence of the coast (Souza

SLAR is an old technology predominantly used for airborne remote sensing (Fingas & Brown, 2000). Airborne surveillance is limited by high costs and is less efficient for wide area observation due to its limited coverage. SAR has greater spatial range and resolution than the SLAR because it uses the forward motion of the aircraft to synthesize a very long antenna, thereby achieving very good spatial resolution, at the expense of sophisticated electronic processing (Mastin et al., 1994). SAR can be used to provide an initial warning because aircrafts are more suitable to identify the polluter, the extent, and the type of

For large scale oil spill detection, satellite platforms, including ERS-1 and -2, Radarsat, and JERS-1, are commonly used for large scales oil spills (Fingas & Brown, 2005). Radar satellites, including ERS-1 and -2, Radarsat, and JERS-1, have been useful for mapping known large offshore spills (Biegert et al., 1997). On the other hand, optical satellite imagery does not offer much potential for oil spill detection (Fingas & Brown, 2000). However, to map coastal environments, geomorphology and its sensitivity, multi-sensor data fusion such

The inter-relationships involving natural resources and human societies have led to a concentration of human activities, services and survival strategies in the coastal environment (Viles & Spencer, 1995; Muehe & Neves, 1995; Pernetta & Elder, 1992). The unique natural geodynamics, the highly productive and extremely diverse biological systems extending from coastal lands to deep water regions (Malthus & Mumby, 2003), the growing land use changes and the pressure on natural resources (MEA, 2005) transform the coastal zone into a conflict area. Oil exploration, transportation and storage have increased

Areas neighboring major ports (environmental and human populated) may be affected by oil transportation, tank cleaning and oil storage procedures in a port area (Noernberg & Lana, 2002). One of the initial concerns about oil spills result in a necessity for the construction of maps that indicate which type of environment and human resources will be affected. In the mid 1970s, scientists from the National Oceanic and Atmospheric Administration (NOAA) and the American Coast Guard of the United States began to study

This classification was based, initially, on the vulnerability index to oil spills proposed by Gundlach & Hayes (1978). Coastal area is segmented considering environmental and geomorphologic characteristics and then classified using the Vulnerability Index, scaled

as optical and radar has proved to be a successful tool (Souza Filho et al., 2009b).

**2.2 Coastal environmental sensitivity to oil spills** 

and classify the sensitivity of coastal environments to oil spill.

the technological risk in this zone.

Filho et al., 2009a).

spill.

from 1 (low) to 10 (high). This Vulnerability Index became the standard for coastal management, planning and research about the effects of oil spills on different types of coastline. Over time, this index evolved and was modified, leading eventually to the development of the Environmental Sensitivity Index (ESI).

The ESI should be represented cartographically as maps in different scales for different goals. The first ESI map was produced in 1979, in response to the advance toward the coast of oil resulting from the blowout of the IXTOC 1 oil-well in the Gulf of Mexico. In the 1980s, ARPEL produced an innovative ESI atlas for the whole coast of the United States, including Alaska and the Great Lakes, to be used for the planning of contingency measures in response to oil spills (NOAA, 2002). From this moment on, ESI maps have been an integral component of response and contingency planning for oil spills, looking for the protection of life, the reduction of environmental impacts, and facilitation of the response efforts. These atlases were integrated by color printed maps on a two dimensional representation of a three-dimensional world and high production costs.

After the 1990's, NOAA (2002) standardized output formats and symbols for ESI maps construction. The basic necessary information is 1) shoreline classification; 2) biological resources; 3) human-use resources. The shoreline classification scheme is based on an understanding of the physical and biological characteristics of the shoreline environment. Relationships among physical processes, exposure to wave and tidal energy, slope, substrate type (i.e. grain size, mobility, penetration and/or burial, and mobility), and associated biota produce specific geomorphic/ecologic shoreline types. Shoreline classification helps to identify oil spill origin and impacts and the best cleanup methods for a specific shoreline type. The sensitivity ranking was developed for the estuarine settings and is slightly modified for lakes and rivers. The human use resources relate to specific, valuable specific areas because of their use, such as beaches, parks and protected marine areas, water intakes, fisheries, tourism, economic sectors, and archaeological sites. The biological resources include the study and maps of oil-sensitive biological and ecological resources.
