A systematic review of GIS-based landslide Hazard Mapping on Determinant Factors from International Databases

2020 ◽  
Author(s):  
Sevar Neamat ◽  
Hazhir Karimi
Keyword(s):  
Systematic Review ◽  
Landslide Hazard ◽  
Hazard Mapping ◽  
Determinant Factors ◽  
Landslide Hazard Mapping

Research on Non-Landslide Selection Method for Landslide Hazard Mapping

2021 ◽  
Author(s):  
Xia Li ◽  
Jiulong Cheng ◽  
Dehao Yu ◽  
Yangchun Han
Keyword(s):  
Prediction Accuracy ◽  
Prediction Models ◽  
Selection Method ◽  
Landslide Hazard ◽  
River Channel ◽  
Information Value ◽  
Hazard Mapping ◽  
Landslide Prediction ◽  
Conditioning Factors ◽  
Landslide Hazard Mapping

Abstract Most landslide prediction models need to select non-landslides. At present, non-landslides mainly use subjective inference or random selection method, which makes it easy to select non-landslides in high-risk areas. To solve this problem and improve the accuracy of landslide prediction, the method of selecting non-landslide by Information value (IV) is proposed in this study. Firstly, 230 historical landslides and 10 landslide conditioning factors are extracted and interpreted by using Remote Sensing (RS) image, Geographic Information System (GIS) and field survey. Secondly, random, buffer, river channel or slope, and IV methods are used to obtain non-landslides, and the obtained non-landslides are applied to the popular SVM model for landslide hazard mapping (LHM) in western area of Tumen City. The landslide hazard map based on the river channel or slope method is seriously inconsistent with the actual situation of study area, Therefore, the three methods of random, buffer, and IV are verified and compared by accuracy, receiver operating characteristic (ROC) curve and the area under curves (AUC). The results show that the landslide prediction accuracy of the three methods is more than 80%, and the prediction accuracy is high, but the IV is higher. In addition, IV can identify the very high hazard regions with smaller area. Therefore, it is more reasonable to use IV to select non-landslides, and IV method is more practical in landslide prevention and engineering construction. The research results may be useful to provide basic information of landslide hazard for decision makers and planners.

scholarly journals Remote sensing and GIS technology in landslide hazard mapping in the Colombian Andes

Episodes ◽  
1992 ◽  
Vol 15 (1) ◽  
pp. 32-35 ◽  
Author(s):  
E. Leroi ◽  
O. Rouzeau ◽  
J. -Y. Scanvic ◽  
C.C. Weber ◽  
G. Vargas C.
Keyword(s):  
Remote Sensing ◽  
Remote Sensing And Gis ◽  
Landslide Hazard ◽  
Hazard Mapping ◽  
Gis Technology ◽  
Colombian Andes ◽  
Landslide Hazard Mapping

Preliminary landslide hazard mapping along a hill road in western Nepal

2021 ◽  
pp. 1253-1258
Author(s):  
B.P. Mainalee ◽  
H. Fujimura ◽  
N. Morishima
Keyword(s):  
Landslide Hazard ◽  
Hazard Mapping ◽  
Landslide Hazard Mapping

Landslide-hazard mapping through multi-technique activity assessment: an example from the Betic Cordillera (southern Spain)

Landslides ◽  
2017 ◽  
Vol 14 (6) ◽  
pp. 1975-1991 ◽  
Author(s):  
J. D. Jiménez-Perálvarez ◽  
R. El Hamdouni ◽  
J. A. Palenzuela ◽  
C. Irigaray ◽  
J. Chacón
Keyword(s):  
Landslide Hazard ◽  
Betic Cordillera ◽  
Southern Spain ◽  
Hazard Mapping ◽  
Activity Assessment ◽  
Landslide Hazard Mapping

The 2010 Yushu earthquake triggered landslide hazard mapping using GIS and weight of evidence modeling

2012 ◽  
Vol 66 (6) ◽  
pp. 1603-1616 ◽  
Author(s):  
Chong Xu ◽  
Xiwei Xu ◽  
Yuan Hsi Lee ◽  
Xibin Tan ◽  
Guihua Yu ◽  
...  
Keyword(s):  
Landslide Hazard ◽  
Weight Of Evidence ◽  
Hazard Mapping ◽  
Yushu Earthquake ◽  
Landslide Hazard Mapping

scholarly journals Landslide hazard mapping considering rainfall probability in Inje, Korea

2014 ◽  
Vol 7 (1) ◽  
pp. 424-446 ◽  
Author(s):  
M.J. Lee ◽  
I. Park ◽  
J.S. Won ◽  
S. Lee
Keyword(s):  
Landslide Hazard ◽  
Hazard Mapping ◽  
Landslide Hazard Mapping
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