This is the LPB-RAP model repository providing model stage 01 & 02 published in Holler et al., 2024a & b.
-
Updated
Jan 6, 2025 - Python
#
lulcc
Here are 3 public repositories matching this topic...
This is a first attempt to employ supervised classification algorithms to Land Use and Land Cover Classification of satellite images. Authors: Naidelyn Espinoza, Eylin Sánchez y Jose Luis Cabrera
random-forest support-vector-machine geography multilayer-perceptron-network classification-model lulcc
-
Updated
Nov 21, 2022 - Jupyter Notebook
This project deals with the spatial development of protected areas in East Africa, specifically, it is based on the Mount Elgon region in Uganda, and, in the future, Kenya. It focuses predominantly on forest cover change as a biodiversity indicator and monitors forest cover development via landsat data development using a winnter-takes-all approach
-
Updated
Jun 9, 2023 - Python
Improve this page
Add a description, image, and links to the lulcc topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the lulcc topic, visit your repo's landing page and select "manage topics."