Abstract

                                aCrop identification and acreage estimation were challenging for remotesensing scientists, especially when cropping season coincides withmonsoon due to cloud coverage in optical data. Synthetic Aperture Radar(SAR) data hasproved to be an alternative for overcoming the issue ofcloudsduring the crop growth period and aid in crop identification. Cropidentification has already reached the stage of operational services usingthe SAR data, while the crop condition assessment is still developing due tovariations in crop scattering mechanisms. Automated algorithms arepromising tools for capturing the wide variation in spatial and temporaldata scattering properties.The importance of automation in GIS is evidentin recent years from global research.Tracking of growth stages of a crophas quantum applications in yield forecast and formulating marketingstrategies.To quantify the crop condition during the crop growth period, anautomated tool to capture various stages of the crop, its conditions, anddocumentation was developed using the preprocessed SAR images derivedfrom a fully automated processing chain module available with MAPscapesoftware. The outputs of temporal Band Sequential (BSQ) images and Startof Season (SOS) for the analysis crop from MAPscape software were usedas input for the automation tool to extract crop conditions viz., failedsowing, crop failure, and a good crop. The backscatter signaturesdeveloped from ground truth data for various crop conditions were used tovalidate the product.

Key words : SAR data;Crop condition;NDVI profile;Automated tool