iremozcann/Land-Cover-Prediction-Using-Machine-Learning
Land Cover Prediction from Satellite Imagery Using Machine Learning Techniques
This project helps environmental scientists and GIS specialists predict land cover types in specific geographic areas. It takes raw satellite imagery, specifically Sentinel-2 data, and generates detailed land cover maps for previously unmapped regions. The tool is designed for anyone needing to create up-to-date land cover classifications using machine learning.
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Use this if you need to generate land cover maps for unseen satellite imagery using a limited set of training samples, for tasks like environmental monitoring or urban planning.
Not ideal if you require real-time land cover analysis for dynamic events or if your primary data source is not Sentinel-2 satellite imagery.
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Last pushed
Apr 25, 2023
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