DocumentCode :
3444243
Title :
GIS-based rainfall-triggered landslide warning and forecasting model of Shenzhen
Author :
Gege Jiang ; Yuan Tian ; Chenchao Xiao
Author_Institution :
Inst. of Remote Sensing & Geogr. Inf. Syst., Peking Univ., Beijing, China
fYear :
2013
fDate :
20-22 June 2013
Firstpage :
1
Lastpage :
5
Abstract :
Landslide warning and forecasting is essential to landslide risk management. This paper establishes a GIS-based landslide warning and forecasting model of Shenzhen where rainfall-trigged landslides have caused great property and life loss. Based on the high-resolution observation data of rainfall and landslide occurrences in Shenzhen, Kriging interpolation model is applied to derive the regional rainfall data prior to the occurrence of landslides. The binary logistic model is then trained by the forward stepwise method, in which the precipitation of the first, second and fourth day prior to the occurrences of landslide are selected as significant explanatory factors. Then, the confusion matrix and AUC/ROC are calculated to verify the model. Finally the critical precipitation of landslide warning and forecasting of Shenzhen is determined. This paper may provide concrete support for landslide risk management work in Shenzhen and helpful reference for related studies.
Keywords :
data handling; geographic information systems; interpolation; matrix algebra; risk management; GIS based rainfall triggered landslide warning; Shenzhen Kriging interpolation model; Shenzhen forecasting model; binary logistic model; confusion matrix; landslide risk management; observation data; Data models; Forecasting; Interpolation; Logistics; Predictive models; Rain; Terrain factors; GIS; binary logistic regression; critical precipitation; landslide; warning and forecasting model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoinformatics (GEOINFORMATICS), 2013 21st International Conference on
Conference_Location :
Kaifeng
ISSN :
2161-024X
Type :
conf
DOI :
10.1109/Geoinformatics.2013.6626026
Filename :
6626026
Link To Document :
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