AI-Powered Environmental Monitoring System for detecting deforestation, poaching, and environmental hazards
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Updated
Jul 6, 2026 - Python
AI-Powered Environmental Monitoring System for detecting deforestation, poaching, and environmental hazards
Deep learning pipeline for detecting deforestation using Sentinel satellite imagery and ResNet.
Fourier Domain Adaptation + Evidential Deep Learning for source-free cross-domain deforestation detection in the Brazilian Amazon using Landsat-8 satellite imagery. ConvNeXt encoder (9.5M params) with per-pixel uncertainty estimation. PyTorch implementation.
Trains a CNN on EuroSAT satellite imagery for land-cover classification (93.6% test accuracy), then applies it to real GeoTIFF scenes across two time points to automatically flag Forest → non-forest transitions as candidate deforestation events.
A computer vision pipeline that analyzes satellite imagery to detect deforestation. It processes live or archived feeds, compares them against reference data, and alerts the user when changes in forest cover are identified. Built to support real-time environmental monitoring and conservation efforts.
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