deforestation-model

Utilizing machine learning to examine deforestation rates in the undeveloped region of Paraguay's Chaco

Modeling vulnerability of ruffed lemurs to climate change and deforestation

Detect deforestation from satellite imagery using U-Net + Google Earth Engine. Deployed with Flask & Docker on Hugging Face Spaces.

Transformer-based app to detect deforestation in the Brazilian Amazon using Sentinel-2 imagery (F1: 0.9886, IoU: 0.9572)

Deep Learning Based Multi-Source Data Fusion to Map Deforested Areas

regression model for deforestation monitoring using satellite images

deforestation monitoring using satellite images

A simple factor-cluster analysis on global deforestation patterns based on FAO data.

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.