ANALYSIS OF THE WATER SCARCITY USING THE TIME-SERIES RAINFALL AND SATELLITE DATASET

The rainfall is the primary key driver of an ecosystem, and it is responsible for sustaining life on the planet. Conversely, the rain deficiency creates a severe problem in the region, like shortage of water for domestic, industrial and agricultural sectors. Furthermore, the region's land cover affects severely due to the barren's increment, fallow land, and decrement of the vegetation cover. To estimate and analyze the affected area using a manual survey is a very complex and tedious task. Therefore, meteorological and satellite imagery data provides a solution for effectively assessing Land Use Land Cover (LULC). In the present research study, the historical rainfall data of the past 39 years and Sentinel 2 satellite data of the year 2016 and 2019 of the Vaijapur tehsil were used for the analysis. The Standard Precipitation Index (SPI) algorithm was applied to the historical rainfall dataset to investigate the meteorological drought. Furthermore, the ground truth points were used for the generation of training and testing pixel for classification using Random Forest (RF). The overall accuracy was obtained 92% and kappa 0.9 in 2016 and 88.69% OA and 0.85 Kappa in 2019.