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A Regional Level Preliminary Landslide Susceptibility Study of the Upper Indus River Basin
European Journal of Remote Sensing
  • Muhammad Farooq Ahmed
  • J. David Rogers, Missouri University of Science and Technology
  • Elamin H. Ismail

The major goal of this research was to explore low cost means by which large tracts of mountainous terrain (~75000 km2) can be screened for landslide-related hazards. For upper Indus watershed study, landslide susceptibility index maps were generated by coupling two main indicators groups: 1) environmental risk factors, which mainly contain slope angle, slope aspect, elevation, lithology maps; and 2) the causative factors, which include seismicity and rainfall. GIS based expert driven weighted overlay and fuzzy logic techniques were adopted to generate susceptibility maps for this preliminary landslide hazard study. The results obtained from this study were validated with landslide inventory mapping and other landslide historic data scattered throughout the upper Indus watershed. This kind of regional level landslide susceptibility mapping can play a vital role in identifying those areas where more detailed assessments of landslide hazards should be undertaken.

Geosciences and Geological and Petroleum Engineering
Keywords and Phrases
  • GIS,
  • Indus River,
  • Remote Sensing,
  • Geographic Information Systems,
  • Hazards,
  • Lithology,
  • Maps,
  • Watersheds,
  • Environmental Risk Factor,
  • Fuzzy Logic Techniques,
  • Indus River,
  • Landslide Inventories,
  • Landslide Susceptibility Mapping,
  • Fuzzy Mathematics,
  • Mountain Region,
  • River Basin,
  • Slope Angle,
  • Indus Basin
Geographic Coverage
Document Type
Article - Journal
Document Version
File Type
© 2014 Associazione Italiana di Telerilevamento, All rights reserved.
Publication Date
Publication Date
01 Jun 2014
Citation Information
Muhammad Farooq Ahmed, J. David Rogers and Elamin H. Ismail. "A Regional Level Preliminary Landslide Susceptibility Study of the Upper Indus River Basin" European Journal of Remote Sensing Vol. 47 Iss. 1 (2014) p. 343 - 373 ISSN: 1129-8596
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