Midlands State University Library

Landslide susceptibility mapping using frequency ratio, analytic hierarchy process, logistic regression, and artificial neural network methods at the Inje area, Korea (Record no. 161870)

MARC details
000 -LEADER
fixed length control field 01959nam a22002777a 4500
003 - CONTROL NUMBER IDENTIFIER
control field ZW-GwMSU
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20230424114652.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 230424b |||||||| |||| 00| 0 eng d
040 ## - CATALOGING SOURCE
Original cataloging agency MSU
Transcribing agency MSU
Description conventions rda
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name PARK, Soyoung
245 ## - TITLE STATEMENT
Title Landslide susceptibility mapping using frequency ratio, analytic hierarchy process, logistic regression, and artificial neural network methods at the Inje area, Korea
264 ## - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Verlag
Name of producer, publisher, distributor, manufacturer Springer
Date of production, publication, distribution, manufacture, or copyright notice 2013
336 ## - CONTENT TYPE
Source rdacontent
Content type term text
Content type code txt
337 ## - MEDIA TYPE
Source rdamedia
Media type term unmediated
Media type code n
338 ## - CARRIER TYPE
Source rdacarrier
Carrier type term volume
Carrier type code nc
440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE
Title Environmental earth sciences
Volume/sequential designation Volume , number ,
520 ## - SUMMARY, ETC.
Summary, etc. Every year, the Republic of Korea experiences numerous landslides, resulting in property damage and casualties. This study compared the abilities of frequency ratio (FR), analytic hierarchy process (AHP), logistic regression (LR), and artificial neural network (ANN) models to produce landslide susceptibility index (LSI) maps for use in predicting possible landslide occurrence and limiting damage. The areas under the relative operating characteristic (ROC) curves for the FR, AHP, LR, and ANN LSI maps were 0.794, 0.789, 0.794, and 0.806, respectively. Thus, the LSI maps developed by all the models had similar accuracy. A cross-tabulation analysis of landslide occurrence against non-occurrence areas showed generally similar overall accuracies of 65.27, 64.35, 65.51, and 68.47 % for the FR, AHP, LR, and ANN models, respectively. A correlation analysis between the models demonstrated that the LR and ANN models had the highest correlation (0.829), whereas the FR and AHP models had the lowest correlation (0.619).
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element frequency ratio (FR)
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Analytic hierarchy process (AHP)
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element logistic regression (LR)
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name CHOI, Chuluong
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name KIM, Byungwoo
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name KIM, Jinsoo
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/s12665-012-1842-5
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Library of Congress Classification
Koha item type Journal Article
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Serial Enumeration / chronology Total Checkouts Full call number Date last seen Price effective from Koha item type Public note
    Library of Congress Classification     Main Library Main Library - Special Collections 24/04/2023 Vol.68 , No.5 (Marc 2013)   GE105 ENV 24/04/2023 24/04/2023 Journal Article For In House Use Only