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Detecting and predicting land use and land cover change in the cross-sanaga-bioko coastal forest region for sustainable forest management

This study assesses forest, agriculture and built-up areas change in the Cross-Sanaka-Bioko (CSB) region from 2000 to 2021, aiming to provide reliable data for sustainable forest management practices. This analysis will be accomplished with the aid of GIS tools (Google Earth Engine and ArcGIS Pro) a...

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Main Author: Njume, Epie Wesner
Other Authors: Hull, Simon
Format: Thesis
Language:English
English
Published: School of Architecture, Planning and Geomatics 2025
Subjects:
sustainable development
LULC
correlation analysis
change detection
descriptive statistics
machine learning
land cover forecasting
air pollution
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Internet

http://hdl.handle.net/11427/41137

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