Global Forest Watch: An online, global, near-real time forest monitoring tool
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Updated
Aug 21, 2024 - JavaScript
Global Forest Watch: An online, global, near-real time forest monitoring tool
📦🐍 Python package to model and forecast the risk of deforestation
Remote Sensing Tools for Forest Monitoring
Label satellite images from the Amazon basin, in order to better track and understand causes of deforestation.
This repository presents the product of my master's thesis, which uses UNet to map deforestation using Sentinel-2 Level 2A images.
Code repository for the paper: Silva Junior et al. Benchmark maps of 33 years of secondary forest age for Brazil. Scientific Data (2020). https://doi.org/10.1038/s41597-020-00600-4
Multimodal SuperCon: Classifier for Drivers of Deforestation in Indonesia
Dashboard of Covid-19 and Deforestation-Rainfall
The Python module for the Georgia Canopy Analysis 2009 project sponsored by the Georgia Forestry Commission
Ribeiro, J.W., Siqueira, T., Brejão, G.L., & Zipkin E.F. 2018. Effects of agriculture and topography on tropical amphibian species and communities. Ecological Applications. 28: 1554-1564.
Utilizing machine learning to examine deforestation rates in the undeveloped region of Paraguay's Chaco
GreenX is a project motivated to create social awareness against deforestation & climate change.
Modeling vulnerability of ruffed lemurs to climate change and deforestation
🌍 📝 Modelling and forecasting deforestation in the tropics
[ISPRS 23] Deforestation Detection in the Amazon with Sentinel-1 SAR Image Time Series
This is a computer vision model that detects if forest areas experienced deforestation. It takes in a satellite image of a forest region to categorize if the region experienced deforestation or hasn't experienced deforestation. This project was created within the AI4ALL Ignite Program SP24.
Reproducible approach to detect deforestation in near real time by NDVI computation of satellite imagery.
Docker images for the Fauno tool
code repo for "Performance evaluation for forecasting modeling with spatiotemporal structures in data"
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