12 December 2006 Remote sensing and GIS-based landslide risk assessment using a linguistic rule-based fuzzy approach
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Abstract
It is well known that natural disasters such as earthquakes, landslides, floods, etc. cause enormous damage to lives and property. The assessment of risk as a potential for adverse consequences, loss, harm to human population due to the occurrence of natural disasters, particularly the landslides in Himalayan region therefore becomes imperative. Landslide risk assessment (LRA) techniques can be applied at different stages in the decision-making process, starting from developmental planning on a regional scale to a particular site evaluation at local scale. The LRA depends on the probability of landslide hazard and the vulnerability of risk elements. The landslide probability depends on both the preparatory (i.e., inherent ground characteristics) and triggering (i.e., earthquake and rainfall) factors. Vulnerability may be defined as the level of potential damage, or degree of loss, of risk elements subjected to landslide occurrences. The assessment of vulnerability is somewhat subjective and on a regional scale it is largely based on the importance of risk elements in human society. Hence, the appropriate vulnerability factor may be assessed systematically by expert judgment. In the present study, a linguistic rule based fuzzy approach is developed and implemented to prepare the landslide risk assessment (LRA) of Darjeeling Himalayas. The LRA has been considered as a function of landslide potential (LP) and resource damage potential (RDP), which have been characterized by the landslide susceptibility zonation (LSZ) map and the resource map (i.e., land use land cover map including the road network) of the area respectively. Fuzzy membership values representing LP and RDP have been assigned to different categories of LSZ and resource maps based on the criteria developed on a linguistic scale. Landslide risk assessment matrix (LRAM) has been generated as a function of the fuzzy membership values, which reflects the relative risk values for different combinations of landslide potential and resource damage potential. These landslide risk values have been classified into six different zones namely, no risk, very low risk (VLR), low risk (LR), moderate risk (MR), high risk (HR) and very high risk (VHR) to ultimately prepare LRA map of the area. Based on this map, a risk management action plan may be suggested to avoid the possible risk to the resources available in the area.
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Debi Prasanna Kanungo, Manoj Kumar Arora, Shantanu Sarkar, Ravi Prakash Gupta, "Remote sensing and GIS-based landslide risk assessment using a linguistic rule-based fuzzy approach", Proc. SPIE 6412, Disaster Forewarning Diagnostic Methods and Management, 64120P (12 December 2006); doi: 10.1117/12.693951; https://doi.org/10.1117/12.693951
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KEYWORDS
Landslide (networking)

Roads

Lawrencium

Geographic information systems

Agriculture

Raster graphics

Earthquakes

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