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- Vol. 3 Issue 3
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Hydro sheds Detection In Sentinel-2A Images in GIS: A Deep Learning Approach
Authors
1Associate Professor, Dept. of Computer Applications, Coimbatore Institute of Technology, Tamilnadu, India. 2Assistant Professor, Dept. of Computer Applications, Coimbatore Institute of Technology, Tamilnadu, India. 345 Students, Dept. of Computer Applications, Coimbatore Institute of Technology, Tamilnadu, India.
Article Information
- DOI
- No DOI
- Published In
- Volume 3, Issue 3 (2022)
- Published Online
- May-June 2022
- Pages
- 444-451
- Article Type
- Research Article
- Check for updates
- No DOI available for cross-reference
Abstract
View PDFAbstract: 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.
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