Sinkhole Susceptibility Hazard Zones Using GIS Framework and Heuristic Method

  • Mohd Asri Hakim Mohd Rosdi
  • Zulkiflee Abd LatifEmail author
  • Ainon Nisa Othman
  • Nasyairi Mat Nasir
Conference paper
Part of the Advances in Science, Technology & Innovation book series (ASTI)


Sinkhole is not named new marvel in this nation, particularly encompass Klang Valley, Malaysia. Since 1968, the expanding quantities of sinkhole occurrence have been reported in Kuala Lumpur and surrounded areas. As the outcomes, it represents a genuine danger for human lives, resources and structure especially in the capital city of Malaysia. Therefore, a Sinkhole Hazard Model (SHM) was created with incorporation of GIS system by applying Analytical Hierarchical Process (AHP) procedure in order to created sinkhole susceptibility map for the specific territory. Five successive criteria for principle criteria each classified by five sub-classes were chosen for this study which is Lithology (LT), Groundwater Level Decline (WLD), Soil Type (ST), Land Use (LU) and Proximity to Groundwater Wells (PG). An arrangement of relative weights were allotted to each instigating factor and registered through pairwise correlation framework got from expert judgment. Lithology and Groundwater Level Decline has been distinguished gives the highest effect to the sinkhole phenomenon. A sinkhole susceptibility risk zones was grouped into five inclined territories which is very low, low, moderate, high and very high zones. The outcomes acquired were approved with 33 past sinkhole inventory data. This assessment demonstrates that the model shows 61 and 15% of the sinkhole events fall inside high and very high zones respectively. In light of this result, it unmistakably shows that AHP approach is helpful to foresee catastrophic event, for example, sinkhole hazard.


GIS Analytical hierarchical process heuristic method Sinkhole Susceptibility hazard zones 


  1. 1.
    Dom, N.C., Latif, Z.A., Ahmad, A.H., Ismail, R., Pradhan, B.: Manifestation of GIS tools for spatial pattern distribution analysis of dengue fever epidemic in the city of Subang Jaya, Malaysia. Environ. Asia 5(2), 82–92 (2012)Google Scholar
  2. 2.
    Idris, R., Latif, Z.A.: GIS multi-criteria for power plant site selection. In: Proceedings—2012 IEEE Control and System Graduate Research Colloquium, ICSGRC 2012, July, pp. 203–206 (2012)Google Scholar
  3. 3.
    Latif, Z.A., Zaki, N.A.M., Salleh, S.A.: GIS-based estimation of rooftop solar photovoltaic potential using LiDAR. In: Proceedings—2012 IEEE 8th International Colloquium on Signal Processing and Its Applications, CSPA 2012, Mar, pp. 388–392 (2012)Google Scholar
  4. 4.
    Meng, T. S.: Karstic Features of Kuala Lumpur Limestone. Geol. Soc. Malays. Bull. 46, 447– 453 (2005)Google Scholar
  5. 5.
    Othman, A.N., Naim, W.M., Noraini, S.: GIS based multi-criteria decision making for landslide hazard zonation. J. Soc. Behav. Sci. 595–602 (2012)Google Scholar
  6. 6.
    Rosdi, M.A.H.M., Othman, A.N., Zubir, M.A.M., Latif, Z.A., Yusoff, Z.M.: Sinkhole susceptibility hazard zones using GIS and analytical hierarchical process (AHP)—a case study of Kuala Lumpur and Ampang Jaya. In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences—ISPRS Archives, 42(4W5), pp. 145–151 (2017)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Mohd Asri Hakim Mohd Rosdi
    • 1
  • Zulkiflee Abd Latif
    • 1
    Email author
  • Ainon Nisa Othman
    • 1
  • Nasyairi Mat Nasir
    • 2
  1. 1.Applied Remote Sensing and Geospatial Research Group, Faculty of Architecture, Planning and Surveying, Centre of Studies for Surveying Science and GeomaticsUniversiti Teknologi MARAShah AlamMalaysia
  2. 2.Faculty of Architecture, Planning and Surveying, Centre of Studies for Quantity SurveyingUniversiti Teknologi MARAShah AlamMalaysia

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