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Land subsidence susceptibility mapping at Kinta Valley (Malaysia) using the evidential belief function model in GIS


Citation

Pradhan, Biswajeet and Abokharima, Mohammed Hasan and Jebur, Mustafa Neamah and Tehrany, Mahyat Shafapour (2014) Land subsidence susceptibility mapping at Kinta Valley (Malaysia) using the evidential belief function model in GIS. Natural Hazards, 73 (2). pp. 1019-1042. ISSN 0921-030X; ESSN: 1573-0840

Abstract

Land subsidence is one of the frequent geological hazards worldwide. Urban areas and agricultural industries are the entities most affected by the consequences of land subsidence. The main objective of this study was to estimate the land subsidence (sinkhole) hazards at the Kinta Valley of Perak, Malaysia, using geographic information system and remote sensing techniques. To start, land subsidence locations were observed by surveying measurements using GPS and using the tabular data, which were produced as coordinates of each sinkhole incident. Various land subsidence conditioning factors were used such as altitude, slope, aspect, lithology, distance from the fault, distance from the river, normalized difference vegetation index, soil type, stream power index, topographic wetness index, and land use/cover. In this article, a data-driven technique of an evidential belief function (EBF), which is in the category of multivariate statistical analysis, was used to map the land subsidence-prone areas. The frequency ratio (FR) was performed as an efficient bivariate statistical analysis method in order compare it with the acquired results from the EBF analysis. The probability maps were acquired and the results of the analysis validated by the area under the (ROC) curve using the testing land subsidence locations. The results indicated that the FR model could produce a 71.16 % prediction rate, while the EBF showed better prediction accuracy with a rate of 73.63 %. Furthermore, the success rate was measured and accuracies of 75.30 and 79.45 % achieved for FR and EBF, respectively. These results can produce an understanding of the nature of land subsidence as well as promulgate public awareness of such geo-hazards to decrease human and economic losses.


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Additional Metadata

Item Type: Article
Divisions: Faculty of Engineering
DOI Number: https://doi.org/10.1007/s11069-014-1128-1
Publisher: Springer
Keywords: Land subsidence; Frequency ratio model; Evidential belief function; Remote sensing; GIS; Kinta Valley; Malaysia
Depositing User: Nurul Ainie Mokhtar
Date Deposited: 10 Dec 2015 06:59
Last Modified: 10 Dec 2015 06:59
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1007/s11069-014-1128-1
URI: http://psasir.upm.edu.my/id/eprint/34347
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