Volume XLII-3/W4
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W4, 579-582, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-W4-579-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W4, 579-582, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-W4-579-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  06 Mar 2018

06 Mar 2018

ANALYSIS OF THE TEMPORAL AND SPATIAL CONTROLLING FACTORS IN AFFECTING THE ACCURACY OF LANDSLIDE PREDICTING MODEL AT TAIWAN

T.-T. Yu1, Y.-S. Cheng1, W.-F. Peng2, and P.-L. Lee1 T.-T. Yu et al.
  • 1Deptarment of Resources Engineering, National Cheng Kung University, Tainan, Taiwan
  • 2Geoinformatics Research Center, National Cheng Kung University, Tainan, Taiwan

Keywords: controlling factor, LSM, AUC, model

Abstract. Most of the landslides are triggered by rainfall, earthquake or the joint effect from both. Landslide inventory map by GIS via remote sensing offer the spatial distribution of it across certain external event. The landslide model thus been trained to link the occurrence and non-occurrence of individual mass wasting on top of proposing factors/layers. Chosen factors with various calculated weighting values becomes as the base of predicting the region and condition for future landslide called as Landslide Susceptibility Mapping (LSM). It is found that the temporal factor has less AUC values than spatial factors at Taiwan, after examining the 20 years catalog and thousand cases of landslide island wide. Different resolution of DEM and NDVI from satellite image, hyper spectrum and LiDAR are utilized to resolve the degree of impact of it. The require accuracy and resolution of base map is directly link to the accuracy and also minimum mapping size of catalog, and the non-linear relationship of external factors still cannot be well predicted by the training model. To achieve better accuracy of LSM the temporal and non-linearity properties should be addressed, especially under the influence of global warming.