Keywords
susceptibility mapping, landslides, gaussian mixture model
Start Date
1-7-2008 12:00 AM
Abstract
In this paper we present the approach for the analysis and modeling of landslide data using the Gaussian Mixture Model. We model the probability density of the landslide events in the high-dimensional space of parameters, conventionally used for predicting the landslide susceptibility. This work describes the application of the method for the area of Bailongjiang River, in northwest China. The available information includes the digital elevation model of the region, geological map and different GIS layers including land cover data obtained from satellite imagery. The landslides were observed with aerial imagery and documented during the field studies.
Landslide Data Analysis with Gaussian Mixture Model
In this paper we present the approach for the analysis and modeling of landslide data using the Gaussian Mixture Model. We model the probability density of the landslide events in the high-dimensional space of parameters, conventionally used for predicting the landslide susceptibility. This work describes the application of the method for the area of Bailongjiang River, in northwest China. The available information includes the digital elevation model of the region, geological map and different GIS layers including land cover data obtained from satellite imagery. The landslides were observed with aerial imagery and documented during the field studies.
