Forest cover restoration analysis using remote sensing and machine learning in central Malawi

Forest cover restoration analysis using remote sensing and machine learning in central Malawi

Forests play a crucial role in maintaining ecological balance and supporting human well-being, yet they are increasingly threatened by anthropogenic pressures. Over the past two decades (2000–2020), Malawi has experienced a 21 % decline in forest cover, necessitating urgent and effective restoration...

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Bibliographic Details
Main Authors: Jabulani Nyengere, Precious Masuku, Sylvester Chikabvumbwa, Weston Mwase, Msaiwale Kathewera, Allena Laura Njala, Wilson Tchongwe, Isaac Tchuwa, Tiwonge I Mzumara, Chikondi Chisenga, Wilfred Kadewa, Emmanuel Chinkaka, Harineck Tholo
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:Trees, Forests and People
Subjects:
Forest restoration
Remote sensing
Machine learning
Support vector machine (SVM)
Vegetation recovery
Online Access:http://www.sciencedirect.com/science/article/pii/S2666719325000998
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