google-deepmind/forest_typology
Datasets to protect Earth's forests and biodiversity
This project provides detailed maps and datasets to help environmental organizations and researchers better understand global forest cover. It takes satellite imagery and other geographical data to produce classifications of different forest types, highlighting areas critical for biodiversity and carbon storage. The primary users are conservationists, environmental scientists, and land-use planners focused on forest protection and climate change mitigation.
106 stars.
Use this if you need to identify and differentiate natural forests, or recognize planted forests and specific tree species to support conservation or land management efforts.
Not ideal if you are looking for real-time forest change detection or detailed local-scale ecological surveys beyond forest typology.
Stars
106
Forks
15
Language
Jupyter Notebook
License
Apache-2.0
Category
Last pushed
Dec 29, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/google-deepmind/forest_typology"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
jasonmanesis/Satellite-Imagery-Datasets-Containing-Ships
This repository provides a comprehensive list of radar and optical satellite datasets curated...
blutjens/awesome-forests
🌳 A curated list of ground-truth forest datasets for the machine learning and forestry community.
vipulchaturvedi/treesense-imaging
Deep Learning based web application to automate tree enumeration in forest areas using satellite imagery.
mratsim/Amazon-Forest-Computer-Vision
Amazon Forest Computer Vision: Satellite Image tagging code using PyTorch / Keras with lots of...
dymaxionlabs/burned-area-detection
Detection of burned areas using deep learning from satellite images