susceptibility

sinkhole

From AHP to GWR in Sinkhole Susceptibility Modeling with Advanced GIS Methods

Introduction Rosdi et al. (2017) made significant strides in understanding sinkhole susceptibility in Kuala Lumpur and Ampang Jaya by combining Geographic Information Systems (GIS) with the Analytical Hierarchical Process (AHP). Their work laid a solid foundation for assessing sinkhole risk, but there remains an opportunity to refine and enhance these models using more advanced spatial analysis techniques. One promising approach is Geographically Weighted Regression (GWR), which has the potential to improve both the accuracy and granularity of sinkhole susceptibility assessments. This article examines how incorporating GWR, along with other advanced GIS methodologies, could lead to more precise and insightful analyses […]

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Sinkhole Risk Mapping with GIS and AHP: Kuala Lumpur and Ampang Jaya Case Study

Understanding Sinkhole Susceptibility in Kuala Lumpur and Ampang Jaya: A GIS and AHP-Based Approach

Introduction Sinkholes are a significant geohazard, particularly in urban areas like Kuala Lumpur and Ampang Jaya, where the increasing number of incidents has raised concerns over public safety and urban infrastructure. Since 1968, the Klang Valley region has witnessed a growing frequency of sinkholes, posing serious threats to human lives, assets, and structures, particularly in Malaysia’s bustling capital. To address this issue, Rosdi et al. (2017) conducted a study that employed Geographic Information Systems (GIS) integrated with the Analytical Hierarchical Process (AHP) to develop a Sinkhole Hazard Model (SHM). This article discusses the findings of this study, the methods used,

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