**8.4. Development and validation of crop water requirement satisfaction index (WRSI)**

Stage-wise crop water requirement satisfaction index is a function of potential, actual ET and crop age. This determines the level and persistence of water stress. The development of WRSI from available ET products from MODIS/INSAT or other sources is made for *rabi* crops such as wheat, mustard, potato and *rabi* rice. The validation is being carried out based on Eddy covariance, ISRO-AMS and scintillometer data available in India.

Hyper-spectral data using spectroradiometer in field and remote-sensing approach in reflectance for many continuous narrow wavelength bands in visible–near infrared (VNIR) and short-wave infrared (SWIR) region of electromagnetic spectrum are used for the detection and growth of Alternaria and aphid infestation in mustard crop within a year. Different spectral indices like NDVI, RVI, AI, SIPI, and so on are calculated for the identification of Alternaria

Multi-purposeful Application of Geospatial Data http://dx.doi.org/10.5772/intechopen.74217 213

Under the observed and projected climate change along with the climatic variability, productivity and production of major crops in India are expected to reduce substantially. Besides, weather and climate extremes during the last one and half decades damaged standing crops extensively. Under these scenarios, operational agrometeorological services play a great role. National Meteorological & Hydrological Services in collaboration is another organisation providing services to the marginal and small farmers at present at the district level and shortly at

Among others, the generation and use of different agromet information and products are important initiatives to deliver crop- and location-specific agromet advisories to the farmers in the country. Here, GIS has an important role to play. Agrometeorological products are derived parameters from meteorological/agrometeorological or other interdisciplinary information. At present, under the GKMS project, extensive data on crop, weather and satellite data are being used to prepare the advisories at different temporal and spatial levels. In view of that, geospatial technology is being used in generating a number of products using ground-based data as well as the satellite data. To provide these services on a pan India mode, station-wise point data are not enough to generate the required products at a desired level. At present, geospatial technology is used to convert discreet data into continuous data. Using interpolation technique, the data are converted to spatial spread. These data cover each and every district of India at a high-resolution scale which can be used for the betterment of agroadvisory. An interactive Web-GIS-based spatial decision support system is being developed to cater to various requirements of IMD in the field of agriculture, hydrology, weather forecasting, pest and disease forecasting. With the launching of a series of geostationary satellite, at present, vast information and products are available in India. The challenge for research is to develop new systems extracting this information from remotely sensed data, giving to the final user's near-real-time information. Satellite-based agrometeorological products and the interpretation of 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 enduser requirement. Under the operational Agromet Advisory Services, using GIS, a number of products like NDVI, VCI and PET (potential evapotranspiration) are being used to capture stress condition of crops for providing appropriate advisories. Besides, the generation of a number of information and products is in the pipeline. It is expected that with the ground data, satellite information and products and with the geospatial technology, more appropriate high-resolution and crop-specific agromet advisories will be provided in the near future

infection and aphid infestation or stress on crop using remote-sensing.

the sub-district level for increasing the crop production.

**9. Conclusion**
