sdesena/above-ground-biomass-machine-learning
End-to-end geospatial data science workflow for predicting Above Ground Biomass density (t/ha)
This project helps environmental managers and conservationists estimate the density of above-ground biomass (t/ha) across large areas without costly field surveys. It takes satellite imagery and elevation data as input and produces accurate, detailed maps of biomass density. It's designed for professionals involved in ecosystem understanding, resource management, and conservation.
Use this if you need to map above-ground biomass density over large geographical regions accurately and cost-effectively, relying on remote sensing and machine learning.
Not ideal if you require hyper-localized, extremely precise biomass measurements for very small plots where direct field measurement is feasible and preferred.
Stars
8
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Language
Jupyter Notebook
License
GPL-3.0
Category
Last pushed
Oct 22, 2025
Commits (30d)
0
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