Spatial Prediction of Rainfall-Induced Landslides Using Aggregating One-Dependence Estimators Classifier

Clicks: 273
ID: 260681
2018
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #7 of 26 articles by views in journal of the indian society of remote sensing

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
In this study, the spatial prediction of rainfall-induced landslides at the Pauri Gahwal area, Uttarakhand, India has been done using Aggregating One-Dependence Estimators (AODE) classifier which has not been applied earlier for landslide problems. Historical landslide locations have been collated with a set of influencing factors for landslide spatial analysis. The performance of the AODE model has been assessed using statistical analyzing methods and receiver operating characteristic curve technique. The predictive capability of the AODE model has also been compared with other popular landslide models namely Support Vector Machines (SVM), Radial Basis Function Neural Network (ANN-RBF), Logistic Regression (LR), and Naïve Bayes (NB). The result of analysis illustrates that the AODE model has highest predictability, followed by the SVM model, the ANN-RBF model, the LR model, and the NB model, respectively. Thus AODE is a promising method for the development of better landslide susceptibility map for proper landslide hazard management.
Reference Key
pham2018journalspatial Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Binh Thai Pham;Indra Prakash;Abolfazl Jaafari;Dieu Tien Bui;Binh Thai Pham;Indra Prakash;Abolfazl Jaafari;Dieu Tien Bui;
Journal journal of the indian society of remote sensing
Year 2018
DOI
doi:10.1007/s12524-018-0791-1
URL
https://dx.doi.org/10.1007/s12524-018-0791-1
Keywords
earth sciences remote sensing/photogrammetry general

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.