Alharbi, T.; El-Sorogy, A.S. Landslide Prediction in Mountainous Terrain Using Remote Sensing and GIS: A Case Study of Al-Hada Road, Makkah Province, Saudi Arabia. Water2023, 15, 3771.
Alharbi, T.; El-Sorogy, A.S. Landslide Prediction in Mountainous Terrain Using Remote Sensing and GIS: A Case Study of Al-Hada Road, Makkah Province, Saudi Arabia. Water 2023, 15, 3771.
Alharbi, T.; El-Sorogy, A.S. Landslide Prediction in Mountainous Terrain Using Remote Sensing and GIS: A Case Study of Al-Hada Road, Makkah Province, Saudi Arabia. Water2023, 15, 3771.
Alharbi, T.; El-Sorogy, A.S. Landslide Prediction in Mountainous Terrain Using Remote Sensing and GIS: A Case Study of Al-Hada Road, Makkah Province, Saudi Arabia. Water 2023, 15, 3771.
Abstract
In Saudi Arabia’s mountainous regions, debris flow is a natural hazard that poses a threat to in-frastructure and human lives. To assess the potential zones of landslide in the Al-Hada Road ar-ea, a study was conducted using Geographic Information System (GIS) analysis and remote sensing (RS) data. The study took into account various factors that could affect landslide, such as drainage density, elevation, slope, precipitation, land use, geology, soil, and aspect. The study also included a field trip to identify 11 previous landslide events that were influenced by high-density drainage and slope. The study utilized weighted overlay analysis in a GIS environment to create a map indicating the potential landslide zones in the area. According to the analysis, low-risk areas cover 35,354,062.5 square meters, medium-risk areas cover 60,646,250 square meters, and high-risk zones cover an area of 8,633,281 square meters. This result was verified using the locations of previous landslide events. The study’s findings can help planners and decision-makers identify and prioritize areas for mitigation and prevention measures. Additionally, the study contributes to understanding landslide hazards in arid and semi-arid regions.
Keywords
remote sensing; Geographic Information System; weighted overlay analysis; Saudi Arabia; landslide
Subject
Environmental and Earth Sciences, Remote Sensing
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
