The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
Spatial prediction models for landslide hazards: review, comparison and evaluation
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Abstract. The predictive power of logistic regression, support vector machines and bootstrap-aggregated classification trees (bagging, double-bagging) is compared using misclassification error rates on independent test data sets. Based on a resampling approach that takes into account spatial autocorrelation, error rates for predicting "present" and "future" landslides are estimated within and outside the training area. In a case study from the Ecuadorian Andes, logistic regression with stepwise backward variable selection yields lowest error rates and demonstrates the best generalization capabilities. The evaluation outside the training area reveals that tree-based methods tend to overfit the data.
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Cited by
A review of statistically-based landslide susceptibility models
Reichenbach, P., Rossi, M., Malamud, B. D., Mihir, M., & Guzzetti, F. (2018) · Earth-Science Reviews · doi:10.1016/j.earscirev.2018.03.001 · Cited by 2,347
Tien Bui, D., Tuan, T. A., Klempe, H., Pradhan, B., & Revhaug, I. (2016) · Landslides · doi:10.1007/s10346-015-0557-6 · Cited by 1,253
Youssef, A. M., Pourghasemi, H. R., Pourtaghi, Z. S., & Al-Katheeri, M. M. (2016) · Landslides · doi:10.1007/s10346-015-0614-1 · Cited by 770
Landslide susceptibility assessment using SVM machine learning algorithm
Marjanović, M., Kovačević, M., Bajat, B., & Voženílek, V. (2011) · Engineering Geology · doi:10.1016/j.enggeo.2011.09.006 · Cited by 622
Meyer, H., Reudenbach, C., Wöllauer, S., & Nauss, T. (2019) · Ecological Modelling · doi:10.1016/j.ecolmodel.2019.108815 · Cited by 509
Metadata
- Authors
- Brenning, A.
- Venue
- Natural Hazards and Earth System Sciences
- Publisher
- Copernicus GmbH
- Published
- 2005-11-07
- Volume
- 5
- Issue
- 6
- Pages
- 853-862
- ISSN
- 1561-8633 (ISSN-L)
- 1684-9981
- OpenAlex
- W2122447387
- Cited by
- 676
- References
- 31
- FWCI
- 28.03
- Type
- journal article
- Language
- en
- Open access
- gold
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