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GIS-Based Logistic Regression for Landslide Susceptibility Analysis in Western Washington State
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Author(s): Lucas A. Dailey (Geography Department, Texas State University, San Marcos, TX, USA)and Sven Fuhrmann (Department of Geography and Geoinformation Science, George Mason University, Fairfax, VA, USA)
Copyright: 2017
Volume: 8
Issue: 2
Pages: 19
Source title:
International Journal of Applied Geospatial Research (IJAGR)
Editor(s)-in-Chief: Donald Patrick Albert (Sam Houston State University, USA)and Samuel Adu-Prah (Sam Houston State University, USA)
DOI: 10.4018/IJAGR.2017040101
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Abstract
The Oso landslide, one of the most recent disasters, occurred on March 22nd, 2014 in western Washington State. It caused significant property damage and killed over 40 people. As a result, a renewed interest has emerged for creating more accurate landslide susceptibility maps for this region. Research addressing landslide susceptibility within the north Puget Sound region of western Washington is lacking; therefore, this study develops a probabilistic GIS-based landslide susceptibility model for the north Puget Sound region. Multivariate logistic regression was utilized to create a landslide susceptibility map of Whatcom, Skagit, Snohomish, and King Counties. To predict probable areas of landslide occurrence, a landslide inventory map was prepared and fourteen topographic, geologic, environmental, and climatic predictor variables were considered. This research aims to assist in restructuring western Washington's landslide policies, and could serve as the first step in producing more accurate landslide susceptibility maps for the region.
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