Use of geospatial data and fuzzy algebraic operators to landslide-hazard mapping
By Biswajeet Pradhan, Saro Lee, Manfred F. Buchroithner. 2009
Geospatial data base creation for landslide-hazard mapping is often an almost inhibitive activity. This has been the reason that for quite some time landslide-hazard analysis was modeled on the basis of spatially related factors. This paper presents the use of fuzzy logic to landslide-hazard analysis in the Penang Island, Malaysia, using remote sensing data and a geographic information system (GIS). To achieve the goal, a data-derived model (frequency ratio) and a knowledge-derived model (fuzzy operator) were combined for landslide-hazard analysis. Landslide locations within the study areas were identified by interpreting aerial photographs, satellite images and field surveys. The nine factors that influence landslide occurrence were extracted from the database and the frequency ratio coefficient for each factor was computed. Using the factors and the identified landslide, the fuzzy membership values were calculated. Then fuzzy algebraic operators were applied to the fuzzy membership values for landslide-hazard mapping. Finally, the produced map was verified by comparing with existing landslide locations for calculating prediction accuracy. Among the fuzzy operators, in the case in which the gamma operator (λ = 0.8) showed the best accuracy (80%) while the case in which the fuzzy or operator was applied showed the worst accuracy (56%).
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- Hamid Reza Pourghasemi
- A. G. Jirandeh
- Chong Xu
- Candan Gokceoglu
- Binh Thai Pham
- Wei Chen
- Biswajeet Pradhan
- D. Tien Bui
Citations in the corpus
- An easy-to-use MATLAB program (MamLand) for the assessment of landslide susceptibility using a Mamdani fuzzy algorithm (2012, unknown): “…et al., 2004; Lee et al., 2004; Ercanoglu, 2005; Lui et al., 2006; Kanungo et al., 2006; Melchiorre et al., 2008; Nefeslioglu et al., 2008b, 2010; Pradhan et al., 2009, 2010; Caniani et al., 2008; Yilmaz, 2009; Bedarnik et al., 2010; Pradhan, 2010; Sezer et al., 2011), and the combination of…”
- Landslide susceptibility assessment and factor effect analysis: backpropagation artificial neural networks and their comparison with frequency ratio and bivariate logistic regression modelling (2010, methodology): “…studies adopted fuzzy logic and artificial neural network models (Ercanoglu and Gokceoglu, 2002; Neaupane and Achet, 2004; Arora et al., 2004; Lee, 2007; Lee et al., 2003a,b, 2004; Gomez and Kavzoglu, 2005; Pradhan and Lee, 2007, 2009a, 2009b, 2009c; Pradhan et al., 2009; Youssef et al., 2009).”
- Landslide susceptibility mapping using support vector machine and GIS at the Golestan Province, Iran (2013, background): “…fuzzy logic (Ercanoglu and Gokceoglu 2004; Muthu et al. 2008; Pradhan and Buchroithner 2010; Pradhan and Pirasteh 2010; Pradhan 2010a, b, 2011a, b; Pradhan et al. 2009; Akgun et al. 2011b; Pourghasemi et al. 2012c), artificial neural network models (Lee et al. 2004; Gomez and Kavzoglu 2005;…”