In:
Advanced Materials Research, Trans Tech Publications, Ltd., Vol. 594-597 ( 2012-11), p. 2406-2409
Kurzfassung:
Traditional regression analysis methods such as Ordinary Least Squares (OLS) are usually used to explore data relations, but they cannot reflect the spatial non-stationarity of the data. Geographically Weighted Regression (GWR) is an effective tool for dealing with this situation, whereas there has not any related studies about using GWR to analyze the landslide surface deformation. This paper tries to base on a typical reservoir-type landslide in Three Gorges Reservoir area of Yangtze River, China, and uses monitoring data, to build OLS and GWR model between landslide surface displacements and trigger factors by ArcGIS. Analysis showed that the GWR model has greater R 2 and smaller Akaike information criterion (AIC) value, and the residuals spatial autocorrelation degree can be significantly reduced then the OLS model, what means the GWR model can capture the spatial non-stationarity of independent variables and is more reliable in analysis of landslide surface deformation.
Materialart:
Online-Ressource
ISSN:
1662-8985
DOI:
10.4028/www.scientific.net/AMR.594-597
DOI:
10.4028/www.scientific.net/AMR.594-597.2406
Sprache:
Unbekannt
Verlag:
Trans Tech Publications, Ltd.
Publikationsdatum:
2012
ZDB Id:
2265002-7
