Validation of Logistic Regression Models for Landslide Susceptibility Maps
Details
Serval ID
serval:BIB_36AB4801F007
Type
Inproceedings: an article in a conference proceedings.
Collection
Publications
Institution
Title
Validation of Logistic Regression Models for Landslide Susceptibility Maps
Title of the conference
Proceedings of the 2009 World congress on Computer Science and Information Engineering
Publisher
IEEE Computer Society
ISBN
978-0-7695-3507-4
Publication state
Published
Issued date
2009
Peer-reviewed
Oui
Editor
Burgin M., Chowdhury M.H., Ham C.H., Ludwig S., Su W., Yenduri S.
Volume
2
Pages
355-358
Language
english
Abstract
A wide range of numerical models and tools have been developed over
the last decades to support the decision making process in environmental
applications, ranging from physical models to a variety of statistically-based
methods. In this study, a landslide susceptibility map of a part
of Three Gorges Reservoir region of China was produced, employing
binary logistic regression analyses. 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 and documented during the field studies.
The validation analysis is exploited to investigate the quality of
mapping.
the last decades to support the decision making process in environmental
applications, ranging from physical models to a variety of statistically-based
methods. In this study, a landslide susceptibility map of a part
of Three Gorges Reservoir region of China was produced, employing
binary logistic regression analyses. 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 and documented during the field studies.
The validation analysis is exploited to investigate the quality of
mapping.
Create date
25/11/2013 17:18
Last modification date
20/08/2019 13:24