[1]Taking Panzhihua City as an Example.Evaluation of Landslide Susceptibility Based on MaxEnt Model[J].Research of Soil and Water Conservation,2021,28(02):224-229.
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Evaluation of Landslide Susceptibility Based on MaxEnt Model
Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume:
28
Number of periods:
2021 02
Page number:
224-229
Column:
Public date:
2021-02-06
- Title:
- Evaluation of Landslide Susceptibility Based on MaxEnt Model
- Keywords:
- maximum entropy(maxEnt)model; ArcGIS; landslide; susceptibility; Panzhihua City
- CLC:
- P642.22
- DOI:
- -
- Abstract:
- In order to objectively evaluate the contribution of landslide impact factors and build landslide prediction model, Panzhihua City, which has more landslide disasters, was selected as the research area in this study. Six factors including elevation, slope, slope direction, land use, normalized difference vegetation index(NDVI)and population density were selected as evaluation indexes for landslide susceptibility in this paper. Based on the maximum entropy(maxEnt)model and ArcGIS spatial analysis module, the landslide susceptibility in the study area was predicted and analyzed quantitatively. The results show that the applicability of the maxEnt model based on the object unit in the study area for landslide susceptibility is rated as excellence(AUC=0.96), and the Kappa coefficient is 0.86; the AUC value is the most stable and accurate, and the model prediction has the highest credibility when 75% of the data sets are randomly selected to train the model, and the remaining 25% are used to verify the model; The high-prone and high-prone areas in the study area account for 2.57% and 0.80% of the total area, respectively, which mainly distribute in the densely populated eastern and western areas, along the main roads of Jinsha River, Yalong River, Banguan River, Anning River and Panzhihua City; among the influencing factors of landslide susceptibility, vegetation cover and slope are the most important geographical environment factors that determine the spatial distribution pattern of landslide susceptibility in this study area.
- References:
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Last Update:
2021-02-10