Integrating Multi-Variable Driving Factors to Improve Land Use & Land Cover Classification Accuracy using Machine Learning Approaches: A Case Study from Lombok Island

Integrating Multi-Variable Driving Factors to Improve Land Use & Land Cover Classification Accuracy using Machine Learning Approaches: A Case Study from Lombok Island

Accurate classification of land cover is essential for effective land management and environmental monitoring. This study aimed to enhance land cover classification for Lombok Island using advanced machine learning algorithms. The models employed include Random Forest, Gradient Boosting, Decision T...

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Bibliographic Details
Main Authors: Miftahul Irsyadi Purnama, Hüseyin Oğuz Çoban
Format: Article
Language:English
Published: Bogor Agricultural University 2025-05-01
Series:Jurnal Manajemen Hutan Tropika
Subjects:
land cover classification
machine learning
Random Forest
Lombok Island
Online Access:https://journal.ipb.ac.id/index.php/jmht/article/view/58686
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