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Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansas, USA

Engineering Geology

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,
DOI: 10.1016/S0013-7952(03)00069-3

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Abstract

Landslides in the hilly terrain along the Kansas and Missouri rivers in northeastern Kansas have caused millions of dollars in property damage during the last decade. To address this problem, a statistical method called multiple logistic regression has been used to create a landslide-hazard map for Atchison, Kansas, and surrounding areas. Data included digitized geology, slopes, and landslides, manipulated using ArcView GIS. Logistic regression relates predictor variables to the occurrence or nonoccurrence of landslides within geographic cells and uses the relationship to produce a map showing the probability of future landslides, given local slopes and geologic units. Results indicated that slope is the most important variable for estimating landslide hazard in the study area. Geologic units consisting mostly of shale, siltstone, and sandstone were most susceptible to landslides. Soil type and aspect ratio were considered but excluded from the final analysis because these variables did not significantly add to the predictive power of the logistic regression. Soil types were highly correlated with the geologic units, and no significant relationships existed between landslides and slope aspect. ?? 2003 Elsevier Science B.V. All rights reserved.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansas, USA
Series title:
Engineering Geology
DOI:
10.1016/S0013-7952(03)00069-3
Volume
69
Issue:
3-4
Year Published:
2003
Language:
English
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
Larger Work Title:
Engineering Geology
First page:
331
Last page:
343
Number of Pages:
13