Comparative study of multiple algorithms classification for land use and land cover change detection and its impact on local climate of Mardan District, Pakistan

Comparative study of multiple algorithms classification for land use and land cover change detection and its impact on local climate of Mardan District, Pakistan

Land use and land cover (LULC) changes significantly impact global climate change, resource management, and sustainability. This study aims to evaluate the performance of various machine learning classifiers, including Support Vector Machine (SVM), Random Forest Algorithm (RFA), K-Nearest Neighbor (...

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Bibliographic Details
Main Authors: Farnaz, Narissara Nuthammachot, Muhammad Zeeshan Ali
Format: Article
Language:English
Published: Elsevier 2025-04-01
Series:Environmental Challenges
Subjects:
Land use/land cover change
Classification algorithms
Sentinel-2 imagery
Urban growth
Climate impact
Mardan District
Online Access:http://www.sciencedirect.com/science/article/pii/S266701002400235X
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