LNSOTOM/fvc_composition
Mapping Fractional Vegetation Cover (FVC) components by introducing a CNN-based deep learning approach for UAS imagery
This project helps ecologists, land managers, and environmental scientists analyze drone-captured RGB and multispectral imagery to map different types of vegetation cover. It takes raw drone images as input and produces detailed maps that classify vegetation into categories like grasses, shrubs, or trees, providing a clear picture of the landscape's composition. It's designed for professionals who need to quantify vegetation for environmental monitoring or ecological studies.
Use this if you need to accurately identify and map fractional vegetation cover using drone imagery, especially in semi-arid environments.
Not ideal if you are looking for a simple, out-of-the-box solution without any technical setup or if your primary data source isn't drone-based imagery.
Stars
7
Forks
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Language
Python
License
GPL-3.0
Category
Last pushed
Mar 13, 2026
Commits (30d)
0
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