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

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

**Figure 13.** Estimation of soil moisture using SMOS.

Agency) and (Indian Geostationary satellite) INSAT 3A CCD NDVI (1 km) data). In order to provide large-area updates, the weekly mean of AMSR-2 surface soil moisture (SSM) and the weekly composite of INSAT Normalised Difference Vegetation Index (NDVI) are used. The geospatial integration of these two was carried out after putting desired thresholds. It is known that the optimum surface soil moistures of 0.1–0.15 m<sup>3</sup> m−3 maintained at least for a week or 2 weeks are ideal at the start of the growing seasons if soil temperature and other meteorological conditions are conducive. Spectral emergence is evident when NDVI crosses 0.3. In *kharif* season, the weekly accumulated rainfall and their thresholds determine sowing. These thresholds vary from crop to crop and according to different agro-climatic settings. Using this information, the current week and the previous week SSM were applied a threshold of 0.1–0.15 and the current week NDVI was applied a threshold of 0.3 to extract the area suitable for sowing. Further thresholds were applied to determine the already sown area. The maps in **Figure 14** show the sown area and area conducive for sowing. The corresponding weekly rainfall maps also show the area with normal or excess rainfall in two consecutive weeks that are probably sown or conducive for sowing.

condition, can act as promising maps for prediction areas suitable for sowing. The technique to generate this map has been prepared and the satellite data used can be made available freely. Thus, this methodology to generate sowing suitability maps can be made operational and can be

Multi-purposeful Application of Geospatial Data http://dx.doi.org/10.5772/intechopen.74217 211

Response to abiotic stresses and quality of advice to farmers depends on the crop type and crop growth stages. The crop age or phenological stages depend on spectral emergence date/ sowing date and subsequent ambient temperature and sunshine hours expressed through thermal and helio-thermal units. The length of the growing season is determined from spec-

Temporal profiles of vegetation index from satellite remote-sensing observations are modelled to trace back spectral emergence date. Early detection could be possible if high temporal vegetation index with a resolution varying from 200 to 1000 m depends on the crop type and coverage. The potential crop mask is an essential input to this. This work is being attempted for six major crops for which the potential crop masks are expected to be available. Superimposition of extended-range or medium-range weather forecasts with spectral emergence dates would provide crop age if agro-climatic zone-wise thermal thresholds are known.

shared with different AMFUs by providing state-level sowing suitability maps.

**8.3. Development of methodology for forecasting spatial crop age/phenology**

tral emergence date and the date of physiological maturity.

**Figure 14.** Sowing suitability map.

Presently, the satellite and modelled rainfall maps are the source used for the prediction of area suitable for sowing. The abovementioned maps, which use the soil moisture condition and vegetation

**Figure 14.** Sowing suitability map.

Agency) and (Indian Geostationary satellite) INSAT 3A CCD NDVI (1 km) data). In order to provide large-area updates, the weekly mean of AMSR-2 surface soil moisture (SSM) and the weekly composite of INSAT Normalised Difference Vegetation Index (NDVI) are used. The geospatial integration of these two was carried out after putting desired thresholds. It is known that the optimum surface soil moistures of 0.1–0.15 m<sup>3</sup> m−3 maintained at least for a week or 2 weeks are ideal at the start of the growing seasons if soil temperature and other meteorological conditions are conducive. Spectral emergence is evident when NDVI crosses 0.3. In *kharif* season, the weekly accumulated rainfall and their thresholds determine sowing. These thresholds vary from crop to crop and according to different agro-climatic settings. Using this information, the current week and the previous week SSM were applied a threshold of 0.1–0.15 and the current week NDVI was applied a threshold of 0.3 to extract the area suitable for sowing. Further thresholds were applied to determine the already sown area. The maps in **Figure 14** show the sown area and area conducive for sowing. The corresponding weekly rainfall maps also show the area with normal or excess rainfall in two consecutive

Presently, the satellite and modelled rainfall maps are the source used for the prediction of area suitable for sowing. The abovementioned maps, which use the soil moisture condition and vegetation

weeks that are probably sown or conducive for sowing.

**Figure 13.** Estimation of soil moisture using SMOS.

210 Multi-purposeful Application of Geospatial Data

condition, can act as promising maps for prediction areas suitable for sowing. The technique to generate this map has been prepared and the satellite data used can be made available freely. Thus, this methodology to generate sowing suitability maps can be made operational and can be shared with different AMFUs by providing state-level sowing suitability maps.
