LANDSLIDE SUSCEPTIBILITY ANALYSIS USING REMOTE SENSING AND GIS: A CASE STUDY IN HULU LANGAT, SELANGOR, MALAYSIA

Authors

  • Muhammad Naim Edi Syams Department of Urban and Regional Planning, INTERNATIONAL ISLAMIC UNIVERSITY MALAYSIA
  • Illyani Ibrahim Department of Urban and Regional Planning, INTERNATIONAL ISLAMIC UNIVERSITY MALAYSIA
  • Ngahzaifa Abd Latif Centre for Artificial Intelligence & Data Science, UNIVERSITI MALAYSIA PAHANG AL-SULTAN ABDULLAH
  • M Zainora Asmawi Department of Urban and Regional Planning, INTERNATIONAL ISLAMIC UNIVERSITY MALAYSIA
  • Siti Aekbal Salleh Institute for Biodiversity and Sustainable Development, UNIVERSITI TEKNOLOGI MARA

DOI:

https://doi.org/10.21837/pm.v23i35.1676

Keywords:

landslide, susceptibility, remote sensing

Abstract

Landslides pose significant hazards globally, especially in expanding populations in unstable areas. This study uses geospatial analysis for landslide susceptibility in Hulu Langat, Selangor, Malaysia. The primary objectives are to understand landslide factors, analyse susceptibility, and recommend mitigation strategies. The methodology involves the Analytic Hierarchy Process (AHP) evaluating nine parameters: elevation, slope terrain, slope aspect, lithology, soil types, distance from rivers, land cover, precipitation, and distance from faults. Key findings show lower elevations, specific soils, acid intrusive lithology, and proximity to rivers and faults are particularly susceptible to landslides. Findings show that Landslide Concern Zone (LCZ) are mainly dispersed along the vicinity of Sungai Langat and Sungai Semenyih. The study emphasizes tailored mitigation, proactive land-use planning, and integration of disaster management with urban planning to enhance resilience and inform policy.

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References

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Published

2025-02-05

How to Cite

Edi Syams, M. N., Ibrahim, I., Abd Latif, N., Asmawi, M. Z., & Salleh, S. A. (2025). LANDSLIDE SUSCEPTIBILITY ANALYSIS USING REMOTE SENSING AND GIS: A CASE STUDY IN HULU LANGAT, SELANGOR, MALAYSIA. PLANNING MALAYSIA, 23(35). https://doi.org/10.21837/pm.v23i35.1676

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