Python framework for automated water quality and environmental risk monitoring in urban watersheds using Google Earth Engine and Sentinel-2.
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Updated
Sep 3, 2025 - Python
Python framework for automated water quality and environmental risk monitoring in urban watersheds using Google Earth Engine and Sentinel-2.
Data analysis and object detection to assess Hurricane Maria's impact using NDVI analysis and YOLO modeling for disaster relief planning.
We are using Sentinel-2 satellite imagery and a specialized U-Net deep learning model to detect changes in landscapes before and after flood events. Using the OMBRIA dataset, the model reliably identifies flooded areas to support disaster management and response efforts.
Extension to read from Earth Observation data archives
An analysis of seasonal NDVI changes using the imagery from Sentinel-2 mission. Includes plots and stats for insights into vegetation health.
SatDataRetriever is a versatile Python-based tool designed to simplify the process of downloading satellite data from various sources, including the Copernicus program’s Sentinel-2 imagery.
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