A remote sensing and GIS-based methodology for the delineation and characterization of rainfed rice environments

Abstract

Abstract Accurate information on the extent and characteristics of rainfed rice-growing environments is lacking because of the high degree of temporal variability and spatial heterogeneity of the ecosystem/subecosystem-differentiating parameters. Although the repeated classification and mapping capture the temporal variability, the information generated reflects post facto conditions and the same geographical area gets classified under different ecozones over years; hence, the delineated ecosystems/subecosystems seem to be transitional. This limits the utility of such an enormous effort. To overcome these problems, this study developed a remote sensing and GIS-based methodology which captures the temporal variability as well as spatial heterogeneity of the ecozone-differentiating parameters and their effect on vegetation (crop) conditions, and prepared criteria for accurate delineation and characterization of rainfed rice ecosystems/subecosystems. The results showed vegetation condition to be a comprehensive reflection of the crop-growing situations and the vegetation index as an excellent criterion for ecosystem/subecosystem classification when combined with the existing classification criteria. These methods have been successfully applied in pilot areas and show greater promise for applicability in similar situations, as well as in other environments with some modifications.