NDLI: Mapping landslide susceptibility with frequency ratio, statistical index, and weights of evidence models: a case study in northern Iran

Content Provider	Springer Nature Link
Author	Razavizadeh, Samaneh Solaimani, Karim Massironi, Matteo Kavian, Ataollah
Copyright Year	2017
Abstract	The main objective of this study is to investigate potential application of frequency ratio (FR), weights of evidence (WoE), and statistical index (SI) models for landslide susceptibility mapping in a part of Mazandaran Province, Iran. First, a landslide inventory map was constructed from various sources. The landslide inventory map was then randomly divided in a ratio of 70/30 for training and validation of the models, respectively. Second, 13 landslide conditioning factors including slope degree, slope aspect, altitude, plan curvature, stream power index, topographic wetness index, sediment transport index, topographic roughness index, lithology, distance from streams, faults, roads, and land use type were prepared, and the relationships between these factors and the landslide inventory map were extracted by using the mentioned models. Subsequently, the multi-class weighted factors were used to generate landslide susceptibility maps. Finally, the susceptibility maps were verified and compared using several methods including receiver operating characteristic curve with the areas under the curve (AUC), landslide density, and spatially agreed area analyses. The success rate curve showed that the AUC for FR, WoE, and SI models was 81.51, 79.43, and 81.27, respectively. The prediction rate curve demonstrated that the AUC achieved by the three models was 80.44, 77.94, and 79.55, respectively. Although the sensitivity analysis using the FR model revealed that the modeling process was sensitive to input factors, the accuracy results suggest that the three models used in this study can be effective approaches for landslide susceptibility mapping in Mazandaran Province, and the resultant susceptibility maps are trustworthy for hazard mitigation strategies.
Starting Page	1
Ending Page	16
Page Count	16
File Format	PDF
ISSN	18666280
Journal	Environmental Earth Sciences
Volume Number	76
Issue Number	14
e-ISSN	18666299
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2017-07-24
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Susceptibility modeling Geographic information systems (GISs) Bivariate statistics Mazandaran Province Geology Hydrology/Water Resources Geochemistry Environmental Science and Engineering Terrestrial Pollution Biogeosciences
Content Type	Text
Resource Type	Article
Subject	Global and Planetary Change Earth-Surface Processes Soil Science Environmental Chemistry Pollution Geology Water Science and Technology

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