Cropping pattern has undergone dramatic changes worldwide due to the effects of climate changes and human management activities. Cropping pattern is an major factor contributing to crop yield and food security at local, regional and national scales, and is a critical input data variable for many global climate, land surface, and crop models. Hence for creating annual cropping intensity maps at huge scales, MODIS images have difficulty with mixed land cover types within a pixel. Hence to generate cropping pattern maps over large spatial domains at high spatial resolution by Sentinel-2 time series image data for January 2019 using the Arc GIS software. In this pilot study, we report cropping pattern maps for January 2019 at spatial resolution over selected areas of Rahuri Tahsil. In this we compare area of selected village by using normalized different vegetation index (NDVI) and by Supervised classification. In normalized different vegetation index (NDVI) classification Kharif crop has highest area and in Supervised classification Soybean has highest area.

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