**7. Application of GIS in product generation with satellite observations**

As climatic variability and climate change will shortly throw huge challenges to agricultural productivity and agricultural production in the country, the days are not very far that farmers of the country will need personalised services on their farm management. Here, remotesensing/satellite information will play a great role when the country does not have an ideal network of weather observatories, or if at all there will be more observatories, it will take more number of years and the management of weather observatories will also be a herculean task for a country like India. Satellite offers a unique source of information for many agricultural applications. Recent advances in satellite technology in terms of high-resolution, multi-spectral bands provide useful information for agricultural operations. The integrated use of satellite data and conventional meteorological observations are found to be very useful to extract information relevant to agriculture in India. Agricultural meteorology is one of the fields of hydrometeorology for which satellite data are very important. Agrometeorological parameters are very variable in time and space. Ground observations do not provide end users with the required spatial and temporal resolution. **Figure 10** shows the current Indian Geostationary Meteorological Satellite. Information about large areas can only be obtained by remote-sensing. The flow of data from new satellites such as Meteosat-8, Terra, and so on is much more informative which opens new areas for agrometeorological applications. Satellite remotesensing technology is increasingly gaining recognition as an important source of operational agrometeorological services. The regular and national-scale agrometeorological monitoring of the physiological processes and growth indicators require the retrieval of basic land surface variables using spatial observations. The challenge for research therefore is to develop new systems extracting this information from remotely sensed data, giving to the final user's nearreal-time information. Satellite-based agrometeorological products and the interpretation of

**Figure 10.** Current Indian geostationary meteorological satellites.

data, crop data and soil data. Preparation of agromet advisories (crop and location specific) for different agro-climatic zones (a total of 127) in the country addressing to intra-

• Accuracy check: the accuracy of the individual map will be assessed in terms of topol-

• Map projection: all collected maps will be brought into a standard projection system as

• Mosaicking and edge matching: the individual map with a desired accuracy will be processed further for edge matching and mosaicking to prepare seamless datasets.

• Data attribution: each feature of the digitised map will be linked with its attribute data.

**Figure 9** depicts an example of an interactive Web-GIS portal for operational agrometeorology.

As climatic variability and climate change will shortly throw huge challenges to agricultural productivity and agricultural production in the country, the days are not very far that farmers of the country will need personalised services on their farm management. Here, remotesensing/satellite information will play a great role when the country does not have an ideal network of weather observatories, or if at all there will be more observatories, it will take more number of years and the management of weather observatories will also be a herculean task for a country like India. Satellite offers a unique source of information for many agricultural applications. Recent advances in satellite technology in terms of high-resolution, multi-spectral bands provide useful information for agricultural operations. The integrated use of satellite data and conventional meteorological observations are found to be very useful to extract information relevant to agriculture in India. Agricultural meteorology is one of the fields of hydrometeorology for which satellite data are very important. Agrometeorological parameters are very variable in time and space. Ground observations do not provide end users with the required spatial and temporal resolution. **Figure 10** shows the current Indian Geostationary Meteorological Satellite. Information about large areas can only be obtained by remote-sensing. The flow of data from new satellites such as Meteosat-8, Terra, and so on is much more informative which opens new areas for agrometeorological applications. Satellite remotesensing technology is increasingly gaining recognition as an important source of operational agrometeorological services. The regular and national-scale agrometeorological monitoring of the physiological processes and growth indicators require the retrieval of basic land surface variables using spatial observations. The challenge for research therefore is to develop new systems extracting this information from remotely sensed data, giving to the final user's nearreal-time information. Satellite-based agrometeorological products and the interpretation of

**7. Application of GIS in product generation with satellite** 

zonal variability at the district level (about 640).

ogy, digitisation error and attribution.

**e.** Data collection and organising

204 Multi-purposeful Application of Geospatial Data

per the SRS.

**observations**

the same in terms of crop and soil moisture status will help the experts to frame the advisories in a better way and ultimately improve the quality of the advisories. In order to extend the support of the ongoing operational AAS, the generation of satellite products for the generation of location-specific agromet advisories is required to meet the end-user requirement.

Besides, the remote-sensing technology helps to provide information for monitoring the pest and disease, drought and flood conditions along with the remedies to the farming community before the situation turns into a disaster affecting the crop yield and productivity. The potential zone for agriculture activities can be identified by studying the climatic variability, and localised services may be provided to the farmers to increase productivity. The yield productivity can be estimated using the remote-sensing technology where information can be further used for the crop insurance services. Remote-sensing methods can be integrated with crop growth models and statistical models to estimate better result in a spatial format. The great challenges would be to the meteorologists/agrometeorologists and space scientists to develop bias-free meteorological/agrometeorological information at its proper application at a local scale to further increase agricultural production to the huge population of the country in the coming years. In order to provide high-resolution information at a ground level, it is almost mandatory to use the remote-sensing data into the GIS hub under the advanced operational Agromet Advisory Services. At present, utilising the information of geostationary and polar satellite, a number of information like soil moisture index, land surface temperature (LST), Normalised Difference of Vegetation index and vegetative condition (VCI) are used to generate a number of information particularly when the plants are in stress conditions.

All information produced by the satellite is elaborated for the extraction of the desired information. There are many methods, algorithms and procedures to derive fundamental data for agrometeorological application from remote-sensing. Among the existing indices, the most extensively used are the land surface temperature (LST) which is a good indicator of climatic and microclimatic conditions prevailing close to the surface, as well as the frost or the moisture in the soil.

In developing countries, GIS use can be promoted through the transfer of technologies and information from the developed ones. This requires generalisation of the knowledge and studies carried out elsewhere. Moreover, frequently in developing countries, data used for the production of the informative layers are often unreliable or even lacking. Besides, the models used in these systems are the results of studies and projects, realised at different scales. Implementation of a GIS requires a great effort to collect and organise the available information on the territory. This important activity requires a period of validation for the operational use of the system. In any case, many projects have started to implement GIS in a number of different environmental and economic systems, mainly using information derived from remote-sensing to complete the direct observations. The common advantage is the definition of the state of the art and a first study of the particular problems, with the suggestion of innovative specific solutions. At this level, the products often are already used for practical applications, and the operators find it sufficiently powerful and reliable.

digital agro-climatic characterisation. A large scope of advanced research exists to explore the INSAT data, to develop advanced algorithm, to improve the accuracy of scheduled product and develop new products. The Imager data would be able to provide satellite meteorological (sat met) products such as rainfall, land surface temperature (LST), land surface albedo, incident solar radiation, cloudiness, upper troposphere humidity (UTH) and outgoing long-wave radiation (OLR). The occurrence and progress of fire, fog and smoke can also be monitored by INSAT 3D data. IMD and SAC have jointly started the incorporation of satellite-based agrometeorological component, particularly NDVI composite image, developed from INSAT 3A CCD image for generating information on crop vigour and agricultural progress. This information along with the rainfall data are being used in stress monitoring and track the crop growth from sowing to harvesting of the major crops in the country. Besides, some studies on crop stress detection through the estimation of evapotranspiration using satellite data have also been attempted in the past along with pest-disease studies based on weather and satellite data. It is planned for the effective usage of satellite observations, particularly Indian satellites, to improve the initial conditions of Numerical Weather Prediction (NWP). The Research and Development (R & D) activity for the optimal use of the satellite data is being carried out,

Multi-purposeful Application of Geospatial Data http://dx.doi.org/10.5772/intechopen.74217 207

**Figure 11.** NOAA/AVHRR NDVI composite and difference.

The data collected and the different information layers are organised in a database, and all the information about the territory is integrated in a GIS. Each layer is composed of different archives (numeric data, text and images), which were preliminarily controlled and evaluated. The archives are completed with graphical representations of the main data trends and synthetic information, obtained by means of spreadsheet and statistical software. The most important information is extracted to describe the territory and then combined for understanding the possible relationships between the different factors. The representation of these data can be made for discrete or continuous values, to obtain thematic maps or territorial representation of the spatially distributed parameters. Satellite data are for agricultural monitoring as monitoring land condition and also for within-season forecasting.

Under GKMS project in India, a joint initiative has been taken up by the Indian Space Research Organisation (ISRO), Indian Council of Agricultural Research (ICAR), India Meteorological Department, National Centre for Medium Range Weather Forecasting (NCMRWF), Noida, Mahalanobis National Crop Forecasting Centre (MNCFC), New Delhi, under DAC (Department Agriculture and Cooperation) to prepare a roadmap for using satellite-based information to augment services to farmers. The ISRO centres include Space Applications Centre, Ahmedabad, National Remote Sensing Centre, Hyderabad, ISRO HQ, Bangalore, Indian Institute of Remote Sensing, Dehradun, and ICAR. With the launching of INSAT 3D, it is expected that Agromet Advisory Services would be further strengthened by providing customised information to the farmer at smaller areas.

A number of studies are being made with the geostationary satellite launched in India, that is, INSAT 3D. INSAT 3D has two kinds of payloads 'Imager' and 'Sounder'. The 'Imager' has six bands consisting of broad visible (VIS), short-wave infrared (SWIR), middle infrared (MIR), water vapour (WV) and two split-thermal infrared (TIR) bands. The optical (VIS, SWIR, MIR) and thermal bands (TIR) from 'Imager' are able to capture reflective and emissive signatures in cloudless skies at half-hourly interval with a single snapshot over the entire country and South-East Asian continent. The combination of all these products from 3D, improved weather forecasts, vegetation index product from INSAT 3A CCD and in situ data are valuable ingredients to generate real-time value-added information for enhanced operational agromet advisory services in the country. The long-term datasets from INSAT suite will be able to aid in digital agro-climatic characterisation. A large scope of advanced research exists to explore the INSAT data, to develop advanced algorithm, to improve the accuracy of scheduled product and develop new products. The Imager data would be able to provide satellite meteorological (sat met) products such as rainfall, land surface temperature (LST), land surface albedo, incident solar radiation, cloudiness, upper troposphere humidity (UTH) and outgoing long-wave radiation (OLR). The occurrence and progress of fire, fog and smoke can also be monitored by INSAT 3D data. IMD and SAC have jointly started the incorporation of satellite-based agrometeorological component, particularly NDVI composite image, developed from INSAT 3A CCD image for generating information on crop vigour and agricultural progress. This information along with the rainfall data are being used in stress monitoring and track the crop growth from sowing to harvesting of the major crops in the country. Besides, some studies on crop stress detection through the estimation of evapotranspiration using satellite data have also been attempted in the past along with pest-disease studies based on weather and satellite data.

It is planned for the effective usage of satellite observations, particularly Indian satellites, to improve the initial conditions of Numerical Weather Prediction (NWP). The Research and Development (R & D) activity for the optimal use of the satellite data is being carried out,

**Figure 11.** NOAA/AVHRR NDVI composite and difference.

In developing countries, GIS use can be promoted through the transfer of technologies and information from the developed ones. This requires generalisation of the knowledge and studies carried out elsewhere. Moreover, frequently in developing countries, data used for the production of the informative layers are often unreliable or even lacking. Besides, the models used in these systems are the results of studies and projects, realised at different scales. Implementation of a GIS requires a great effort to collect and organise the available information on the territory. This important activity requires a period of validation for the operational use of the system. In any case, many projects have started to implement GIS in a number of different environmental and economic systems, mainly using information derived from remote-sensing to complete the direct observations. The common advantage is the definition of the state of the art and a first study of the particular problems, with the suggestion of innovative specific solutions. At this level, the products often are already used for practical

The data collected and the different information layers are organised in a database, and all the information about the territory is integrated in a GIS. Each layer is composed of different archives (numeric data, text and images), which were preliminarily controlled and evaluated. The archives are completed with graphical representations of the main data trends and synthetic information, obtained by means of spreadsheet and statistical software. The most important information is extracted to describe the territory and then combined for understanding the possible relationships between the different factors. The representation of these data can be made for discrete or continuous values, to obtain thematic maps or territorial representation of the spatially distributed parameters. Satellite data are for agricultural moni-

Under GKMS project in India, a joint initiative has been taken up by the Indian Space Research Organisation (ISRO), Indian Council of Agricultural Research (ICAR), India Meteorological Department, National Centre for Medium Range Weather Forecasting (NCMRWF), Noida, Mahalanobis National Crop Forecasting Centre (MNCFC), New Delhi, under DAC (Department Agriculture and Cooperation) to prepare a roadmap for using satellite-based information to augment services to farmers. The ISRO centres include Space Applications Centre, Ahmedabad, National Remote Sensing Centre, Hyderabad, ISRO HQ, Bangalore, Indian Institute of Remote Sensing, Dehradun, and ICAR. With the launching of INSAT 3D, it is expected that Agromet Advisory Services would be further strengthened by providing

A number of studies are being made with the geostationary satellite launched in India, that is, INSAT 3D. INSAT 3D has two kinds of payloads 'Imager' and 'Sounder'. The 'Imager' has six bands consisting of broad visible (VIS), short-wave infrared (SWIR), middle infrared (MIR), water vapour (WV) and two split-thermal infrared (TIR) bands. The optical (VIS, SWIR, MIR) and thermal bands (TIR) from 'Imager' are able to capture reflective and emissive signatures in cloudless skies at half-hourly interval with a single snapshot over the entire country and South-East Asian continent. The combination of all these products from 3D, improved weather forecasts, vegetation index product from INSAT 3A CCD and in situ data are valuable ingredients to generate real-time value-added information for enhanced operational agromet advisory services in the country. The long-term datasets from INSAT suite will be able to aid in

applications, and the operators find it sufficiently powerful and reliable.

206 Multi-purposeful Application of Geospatial Data

toring as monitoring land condition and also for within-season forecasting.

customised information to the farmer at smaller areas.

and subsequently, improved assimilation system for the optimal use of the satellite is implemented. The implementation plans are given as follows:

SMN data at 4 km is derived from no noise NDVI (Normalised Difference Vegetation index). Gridded weekly global vegetation indices (SMN, VCI, TCI and VHI) are derived from NOAA VHRR satellites. These datasets can be used to estimate the vigour and stress on vegetation, start of growing season and its phonological phages. Weekly NDVI products and composite

Multi-purposeful Application of Geospatial Data http://dx.doi.org/10.5772/intechopen.74217 209

In order to provide large-area updates by using finer-scale low-repeat RS data and products over land, data from IRS, OCM, AWiFS, MODIS and RISAT-1 are being created weekly composite of vegetation indices, snow cover and snow/water fraction. Surface insolation and land surface temperature (LST) from INSAT 3D are being operationalised in India. Besides, efforts are being made to operationalise products of land surface albedo and reference evapotranspiration at IMDPS, New Delhi. The generation of potential crop maps for rice (*kharif, rabi*), wheat, mustard, cotton, potato, sugarcane, jute and *rabi* sorghum at 100–200 m spatial resolution all over India coverage for all the above crops once in a season is in process including advanced operational agromet products such as actual evapotranspiration, aridity index and water requirement satisfaction index (WRSI). These products are made available subjected to the success of other core agromet products to be generated from INSAT 3D. Different remote-

maps are being operationally generated for the Indian region (**Figures 11** and **12**).

sensing products for agrometeorology are depicted in **Figure 12**.

**Agromet advisory services**

**sensors on board SMOS**

of 25 m.

**8. Other projects on use of satellite information in operational** 

**8.1. Determination of soil moisture over India using space-borne passive microwave** 

Sensor Microwave Imager/Sounder) by NASA for (LST) using Beam 4.9 software.

**8.2. Optimum sowing suitability for** *kharif* **(June and July),** *rabi* **(November and December) seasons and general agricultural health based on edaphic factors**

Soil moisture is being estimated for three states, Uttar Pradesh, Madhya Pradesh and Gujarat (**Figure 13**), by the satellite products, namely SMOS (soil moisture and salinity) launched by European Space Agency (ESA), MODIS (NDVI and LST from Terra/Aqua) and SSMIS (Special

Satellite data-based fusion approach to develop soil moisture monitoring system in India: Methodology has been developed for the estimation of soil moisture using SAR data from PALSAR (phase array L-band synthetic aperture radar) and NDVI from MODIS using NEST and POLSAR-PRO software. On experimental mode, soil moisture maps have been generated in Moga, Hissar, Roorkee, Saharanpur, Meerut, Dhanbad and Moradabad with the resolution

Activities on the use of satellite data have been initiated in collaboration with different organisations (Space Applications Centre, ISRO), to strengthen the Agromet Advisory Services (AAS). One important activity, that is, sowing suitability of crops during *kharif* season, has been started using the satellite data (AMSR-2 (Advanced Microwave Scanning Radiometer sensor), soil moisture content (SMC at 10 km available from Japan Aerospace Exploration


The data from suite of INSAT satellites are being received and processed on real-time basis through an operational chain known as INSAT Meteorological Data Processing System (IMDPS), New Delhi, as well as mirror site in IMDPS, SAC, Ahmedabad. The images and digital products at different time scales (half-an-hour to daily) from IMDPS on real-time basis have great potential for use in the preparation of advisories for Agrometeorological Services on an operational basis and ensuring the availability of data on a requirement basis.

There are specific requirements to derive some specialised products such as surface insolation, LST, albedo and reference evapotranspiration from INSAT 3D 'Imager'. It is proposed to develop algorithms of all these products and will be implemented at IMDPS, New Delhi, for generation of these products on an operational basis. Validated global 7-day composite of

**Figure 12.** Different remote-sensing products.

SMN data at 4 km is derived from no noise NDVI (Normalised Difference Vegetation index). Gridded weekly global vegetation indices (SMN, VCI, TCI and VHI) are derived from NOAA VHRR satellites. These datasets can be used to estimate the vigour and stress on vegetation, start of growing season and its phonological phages. Weekly NDVI products and composite maps are being operationally generated for the Indian region (**Figures 11** and **12**).

and subsequently, improved assimilation system for the optimal use of the satellite is imple-

• Operationalise the assimilation of SAPHIR and INSAT-3D radiances in the Multi-Model

• Assimilation system to assimilate different land surface products such as soil moisture,

• Development of RAPID system (www.rapid.gov.in). This system is a geoportal for satellite meteorology and forecasts with different Web-GIS facilities. This system should be modified and adapted for agrometeorological applications and agro-advisory purposes so that

The data from suite of INSAT satellites are being received and processed on real-time basis through an operational chain known as INSAT Meteorological Data Processing System (IMDPS), New Delhi, as well as mirror site in IMDPS, SAC, Ahmedabad. The images and digital products at different time scales (half-an-hour to daily) from IMDPS on real-time basis have great potential for use in the preparation of advisories for Agrometeorological Services

There are specific requirements to derive some specialised products such as surface insolation, LST, albedo and reference evapotranspiration from INSAT 3D 'Imager'. It is proposed to develop algorithms of all these products and will be implemented at IMDPS, New Delhi, for generation of these products on an operational basis. Validated global 7-day composite of

on an operational basis and ensuring the availability of data on a requirement basis.

mented. The implementation plans are given as follows:

208 Multi-purposeful Application of Geospatial Data

**Figure 12.** Different remote-sensing products.

Ensemble (MME) for improvement of weather forecast.

vegetation and snow fraction, land surface temperature and albedo.

any official engaged in Agromet Services can utilise this facility.

In order to provide large-area updates by using finer-scale low-repeat RS data and products over land, data from IRS, OCM, AWiFS, MODIS and RISAT-1 are being created weekly composite of vegetation indices, snow cover and snow/water fraction. Surface insolation and land surface temperature (LST) from INSAT 3D are being operationalised in India. Besides, efforts are being made to operationalise products of land surface albedo and reference evapotranspiration at IMDPS, New Delhi. The generation of potential crop maps for rice (*kharif, rabi*), wheat, mustard, cotton, potato, sugarcane, jute and *rabi* sorghum at 100–200 m spatial resolution all over India coverage for all the above crops once in a season is in process including advanced operational agromet products such as actual evapotranspiration, aridity index and water requirement satisfaction index (WRSI). These products are made available subjected to the success of other core agromet products to be generated from INSAT 3D. Different remotesensing products for agrometeorology are depicted in **Figure 12**.
