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Bulletin of Engineering Geology and the Environment

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09.03.2018 | Original Paper

A comparative assessment of information value, frequency ratio and analytical hierarchy process models for landslide susceptibility mapping of a Himalayan watershed, India

verfasst von: Swati Sharma, A. K. Mahajan

Erschienen in: Bulletin of Engineering Geology and the Environment | Ausgabe 4/2019

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Abstract

This research work presents a comparative performance of geographic information system (GIS)-based statistical models for landslide susceptibility mapping (LSM) of the Himalayan watershed in India. A total of 190 landslide locations covering an area of 14.63 km² were identified in the watershed, using high-resolution linear imaging self-scanning (LISS IV) data. The causative factors used for LSM of the study area are slope, aspect, lithology, curvature, lineament density, land cover and drainage buffer. The spatial database has been prepared using remote sensing data along with ancillary data like geological maps. LSMs were prepared using information value (InV), frequency ratio (FR) and analytical hierarchy process (AHP) models. The validation results using the prediction rate curve technique show 89.61%, 87.12% and 88.26% area under curve values for FR, AHP and InV models, respectively. Therefore, the frequency ratio (FR) model could be used for LSM in other parts of this hilly terrain.

Vorheriger Artikel Cooperative monitoring and numerical investigation on the stability of the south slope of the Fushun west open-pit mine

Nächster Artikel A method for quick assessment of earthquake-triggered landslide hazards: a case study of the Mw6.1 2014 Ludian, China earthquake

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Titel: A comparative assessment of information value, frequency ratio and analytical hierarchy process models for landslide susceptibility mapping of a Himalayan watershed, India
verfasst von: Swati Sharma
A. K. Mahajan
Publikationsdatum: 09.03.2018
Verlag: Springer Berlin Heidelberg
Erschienen in: Bulletin of Engineering Geology and the Environment / Ausgabe 4/2019
Print ISSN: 1435-9529
Elektronische ISSN: 1435-9537
DOI: https://doi.org/10.1007/s10064-018-1259-9

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