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Abstract: Hydro sheds detection in Sentinel-2A images in GIS is to detect the presence of water in the Earth’s surface from geospatial satellite images of Sentinel-2 by Deep learning models. Analyzing and making decisions from the collected satellite images is to be done by blending remote sensing techniques, Geographic Information System (GIS) techniques with Machine Learning and Deep Learning models. The proposed system uses the satellite data and Open Street to train a spatial convolutional neural network to predict water occurrences in satellite images. Models like convolution 2D, activation function, max pooling, flatten to train the dataset, the geospatial data to predict the water flow. The proposed system is a Deep learning technique to geospatial analysis and remote sensing.