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ISPRS Int. J. Geo-Inf. 2017, 6(4), 103; doi:10.3390/ijgi6040103

Validation of Spatial Prediction Models for Landslide Susceptibility Mapping by Considering Structural Similarity

1,2,* , 1,2,* and 1,2
1
Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
*
Authors to whom correspondence should be addressed.
Received: 5 January 2017 / Revised: 7 March 2017 / Accepted: 22 March 2017 / Published: 30 March 2017
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Abstract

In this paper, we propose a methodology for validating landslide susceptibility results in the Pinggu district (Beijing, China). A landslide inventory including 169 landslides was prepared, and eight factors correlated to landslides (lithology, tectonic faults, topographic elevation, slope gradient, aspect, slope curvature, land use, and road network) were processed, integrating two techniques, namely the frequency ratio (FR) and the certainty factor (CF), in a geographic information system (GIS) environment. The area under the curve (success rate curve and prediction curve) analysis was used to evaluate model compatibility and predictability. Validation results indicated that the values of the area under the curve for the FR model and the CF model were 0.769 and 0.768, respectively. Considering spatial correlation, an alternative complementary method for validating landslide susceptibility maps was introduced. The spatially approximate maps could be discriminated from their matrices which carry structural information, and the structural similarity index (SSI) was then proposed to quantify the similarity. As a specific example, the SSI value of the FR (74.15%) scored higher than that of the CF model (69.36%), demonstrating its promise in validating different landslide susceptibility maps. These results show that the FR model outperforms the CF model in producing a landslide susceptibility map in the study area. View Full-Text
Keywords: geographic information system (GIS); landslide; frequency ratio; certainty factor; validation; structural similarity index geographic information system (GIS); landslide; frequency ratio; certainty factor; validation; structural similarity index
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Deng, X.; Li, L.; Tan, Y. Validation of Spatial Prediction Models for Landslide Susceptibility Mapping by Considering Structural Similarity. ISPRS Int. J. Geo-Inf. 2017, 6, 103.

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