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Prediction of slope failures using bivariate statistical based index of entropy model

The main objective of this research is to evaluate the spatial prediction of potential slope failures in Kuala Lumpur and surrounding areas using an index of entropy based statistical model. Based on potential information of entropy method (IoE), subjective weights were calculated for fourteen lands...

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Main Authors: Althuwaynee, Omar F., Pradhan, Biswajeet, Mahmud, Ahmad Rodzi, Md Yusoff, Zainuddin
Format: Conference or Workshop Item
Language:English
Published: IEEE 2012
Online Access:http://psasir.upm.edu.my/id/eprint/40597/1/Prediction%20of%20slope%20failures%20using%20bivariate%20statistical%20based%20index%20of%20entropy%20model.pdf
http://psasir.upm.edu.my/id/eprint/40597/
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spelling my.upm.eprints.405972018-10-23T06:33:33Z http://psasir.upm.edu.my/id/eprint/40597/ Prediction of slope failures using bivariate statistical based index of entropy model Althuwaynee, Omar F. Pradhan, Biswajeet Mahmud, Ahmad Rodzi Md Yusoff, Zainuddin The main objective of this research is to evaluate the spatial prediction of potential slope failures in Kuala Lumpur and surrounding areas using an index of entropy based statistical model. Based on potential information of entropy method (IoE), subjective weights were calculated for fourteen landslide conditioning factors used in this study such as, (slope, aspect, curvature, altitude, surface roughness, lithology, distance from faults, NDVI (normalized difference vegetation index), land cover, distance from drainage, distance from road, SPI (stream power index), soil type and precipitation). A landslide inventory map of the study area was produced using previous reports and aerial photographs interpretation aided with extensive field survey and total of 220 main scarps were identified. Out of this, 153 (70%) landslide locations were used to build the IoE model, while remaining 66 (30%) landslide locations were used for validation purpose. For validation, the area under the curve (AUC) was used to quantify the predictive performance of the employed IoE model. The validation results show that the prediction accuracy of the model is 0.80 (80%) and the success rate equals to 0.81 (81%) that consider fine indicator of the reliability of bivariate model based IoE model employed in this study. IEEE 2012 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/40597/1/Prediction%20of%20slope%20failures%20using%20bivariate%20statistical%20based%20index%20of%20entropy%20model.pdf Althuwaynee, Omar F. and Pradhan, Biswajeet and Mahmud, Ahmad Rodzi and Md Yusoff, Zainuddin (2012) Prediction of slope failures using bivariate statistical based index of entropy model. In: 2012 IEEE Colloquium on Humanities, Science & Engineering Research (CHUSER 2012), 3-4 Dec. 2012, Kota Kinabalu, Sabah. (pp. 362-367). 10.1109/CHUSER.2012.6504340
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description The main objective of this research is to evaluate the spatial prediction of potential slope failures in Kuala Lumpur and surrounding areas using an index of entropy based statistical model. Based on potential information of entropy method (IoE), subjective weights were calculated for fourteen landslide conditioning factors used in this study such as, (slope, aspect, curvature, altitude, surface roughness, lithology, distance from faults, NDVI (normalized difference vegetation index), land cover, distance from drainage, distance from road, SPI (stream power index), soil type and precipitation). A landslide inventory map of the study area was produced using previous reports and aerial photographs interpretation aided with extensive field survey and total of 220 main scarps were identified. Out of this, 153 (70%) landslide locations were used to build the IoE model, while remaining 66 (30%) landslide locations were used for validation purpose. For validation, the area under the curve (AUC) was used to quantify the predictive performance of the employed IoE model. The validation results show that the prediction accuracy of the model is 0.80 (80%) and the success rate equals to 0.81 (81%) that consider fine indicator of the reliability of bivariate model based IoE model employed in this study.
format Conference or Workshop Item
author Althuwaynee, Omar F.
Pradhan, Biswajeet
Mahmud, Ahmad Rodzi
Md Yusoff, Zainuddin
spellingShingle Althuwaynee, Omar F.
Pradhan, Biswajeet
Mahmud, Ahmad Rodzi
Md Yusoff, Zainuddin
Prediction of slope failures using bivariate statistical based index of entropy model
author_facet Althuwaynee, Omar F.
Pradhan, Biswajeet
Mahmud, Ahmad Rodzi
Md Yusoff, Zainuddin
author_sort Althuwaynee, Omar F.
title Prediction of slope failures using bivariate statistical based index of entropy model
title_short Prediction of slope failures using bivariate statistical based index of entropy model
title_full Prediction of slope failures using bivariate statistical based index of entropy model
title_fullStr Prediction of slope failures using bivariate statistical based index of entropy model
title_full_unstemmed Prediction of slope failures using bivariate statistical based index of entropy model
title_sort prediction of slope failures using bivariate statistical based index of entropy model
publisher IEEE
publishDate 2012
url http://psasir.upm.edu.my/id/eprint/40597/1/Prediction%20of%20slope%20failures%20using%20bivariate%20statistical%20based%20index%20of%20entropy%20model.pdf
http://psasir.upm.edu.my/id/eprint/40597/
_version_ 1643832761687998464
score 13.211869

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