A comparative study of ensemble learning algorithms for the classification of landslide activity using vegetation anomalies indicator (VAI): a case study of Kundasang, Sabah

A comparative study of ensemble learning algorithms for the classification of landslide activity using vegetation anomalies indicator (VAI): a case study of Kundasang, Sabah

Abstract Landslide activity classification is crucial for disaster risk management and mitigation. This study explores the effectiveness of ensemble learning algorithms in classifying landslide activities using Vegetation Anomalies Indicator (VAI) within Kundasang, Sabah, Malaysia. Seven groups of V...

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Bibliographic Details
Main Authors: Mohd Radhie Mohd Salleh, Muhammad Zulkarnain Abdul Rahman, Zamri Ismail, Mohd Faisal Abdul Khanan, Radzuan Sa’ari, Ahmad Razali Yusoff
Format: Article
Language:English
Published: Springer 2025-06-01
Series:Discover Geoscience
Subjects:
Landslide
GIS
Remote sensing
Machine learning
Vegetation
Online Access:https://doi.org/10.1007/s44288-025-00171-0
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https://doi.org/10.1007/s44288-025-00171-0

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