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Akib Javed
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China

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Review
Published: 29 November 2019 in ISPRS International Journal of Geo-Information
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Digital elevation models (DEMs) are considered an imperative tool for many 3D visualization applications; however, for applications related to topography, they are exploited mostly as a basic source of information. In the study of landslide susceptibility mapping, parameters or landslide conditioning factors are deduced from the information related to DEMs, especially elevation. In this paper conditioning factors related with topography are analyzed and the impact of resolution and accuracy of DEMs on these factors is discussed. Previously conducted research on landslide susceptibility mapping using these factors or parameters through exploiting different methods or models in the last two decades is reviewed, and modern trends in this field are presented in a tabulated form. Two factors or parameters are proposed for inclusion in landslide inventory list as a conditioning factor and a risk assessment parameter for future studies.

ACS Style

Nayyer Saleem; Enamul Huq; Nana Yaw Danquah Twumasi; Akib Javed; Asif Sajjad. Parameters Derived from and/or Used with Digital Elevation Models (DEMs) for Landslide Susceptibility Mapping and Landslide Risk Assessment: A Review. ISPRS International Journal of Geo-Information 2019, 8, 545 .

AMA Style

Nayyer Saleem, Enamul Huq, Nana Yaw Danquah Twumasi, Akib Javed, Asif Sajjad. Parameters Derived from and/or Used with Digital Elevation Models (DEMs) for Landslide Susceptibility Mapping and Landslide Risk Assessment: A Review. ISPRS International Journal of Geo-Information. 2019; 8 (12):545.

Chicago/Turabian Style

Nayyer Saleem; Enamul Huq; Nana Yaw Danquah Twumasi; Akib Javed; Asif Sajjad. 2019. "Parameters Derived from and/or Used with Digital Elevation Models (DEMs) for Landslide Susceptibility Mapping and Landslide Risk Assessment: A Review." ISPRS International Journal of Geo-Information 8, no. 12: 545.