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FASAL (R&D): FORECASTING AGRICULTURAL OUTPUT USING
                  SPACE, AGRO-METEOROLOGY & LAND BASED OBSERVATIONS



               Objectives

                     •  Techniques  development  for  Cotton,  Sugarcane  and  Sorghum  crop
                        discrimination

                     •  To be carried out for Cotton, Sugarcane and kharif sorghum, crop discrimination

                     •  Area and production forecast using multi-temporal AWiFS& RISAT data
                     •  Involving field validation techniques with crop cutting experiments and condition

                        assessment
               Data Used


                     •  In-season multi-temporal AWiFS, LISS-III, LISS-IV and RISAT data
                     •  Near real time Ground Truth information

               Methodology

                       For estimation of sugarcane acreage, early growth stage from March to May will
               be detected using multi-date AWiFS data. Few synchronous AWiFS data will be taken in

               sample locations to precisely know the signature extension from high to low resolution

               data in case of sugarcane fields which are widely spaced during early growth stage. The
               signature of ratoon and freshly planted fields at different stages of growth will be mapped

               and will be compared with GT data to know their variability at signature levels. GT will be
               collected in May and digital analysis will be carried out in May-June.



                       Multi-date AWiFS data classification using ISODATA clustering technique will be
               followed. A stratified sampling scheme using digital approach with the current classified

               data will be implemented. This will help in increasing the accuracy of sample segment
               location and their stratification, thus improving the coefficient of variation.


                       Multi-date  data  of  July  to  November  period  will  be  used  for  cotton  analysis.

               Methodology consists of registration of multi-date dataset, generation of NDVI images,
               development of master temporal profiles and thereby discrimination of cotton from other





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                                                                                                      MRSAC,Nagpur ©®
                                                                                                      MRSAC,Nagpur ©®
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