Forecasting and validation of landslide susceptibility using an integration of frequency ratio and neuro-fuzzy models: a case study of Seorak mountain area in Korea

详细信息    查看全文

• 作者：Moung-Jin Lee ; Inhye Park ; Saro Lee
• 关键词：Integration ; Frequency ratio ; Adaptive neuro ; fuzzy inference system (ANFIS) ; Landslide ; GIS Korea
• 刊名：Environmental Earth Sciences
• 出版年：2015
• 出版时间：July 2015
• 年：2015
• 卷：74
• 期：1
• 页码：413-429
• 全文大小：3,601 KB
• 参考文献：Althuwaynee OF, Pradhan B, Lee S (2012) Application of an evidential belief function model in landslide susceptibility mapping. Comput Geosci 44:120-35View Article
  Bai S, Lü G, Wang J, Zhou P, Ding L (2011) GIS-based rare events logistic regression for landslide-susceptibility mapping of Lianyungang, China. Environ Earth Sci 62(1):139-49View Article
  Bai S, Wang J, Zhang Z, Cheng C (2012) Combined landslide susceptibility mapping after Wenchuan earthquake at the Zhouqu segment in the Bailongjiang Basin, China. Catena 99:18-5View Article
  Bateni SM, Borghei SM, Jeng DS (2007) Neural network and neuro-fuzzy assessments for scour depth around bridge piers. Eng Appl Artif Intel 20(3):401-14View Article
  Beven KJ, Kirkby MJ (1979) Physically based, variable contributing area model of basin hydrology. Hydrolog Sci J 24:43-9
  Cohen J (1960) A coefficient of agreement for nominal scales. Educ Psychol Meas 20:37-6View Article
  Cowen J (1993) A proposed method for calculating the LS factor for use with the USLE in a grid-based environment: Proceedings of the thirteenth annual ESRI user conference, p 65-4
  Dai FC, Lee CF (2002) Landslide characteristics and slope instability modeling using GIS, Lantau Island, Hong Kong. Geomorphology 42:213-28View Article
  Desmet P, Grovers G (1996) A GIS procedure for automatically calculating the USLE LS factor on topographically complex landscape units. J Soil Water Conserv 51(5):427-33
  Devkota KC, Regmi AD, Pourghasemi HR, Yoshida K, Pradhan B, Ryu IC, Dhital MR, Althuwaynee OF (2013) Landslide susceptibility mapping using certainty factor, index of entropy and logistic regression models in GIS and their comparison at Mugling–Narayanghat road section in Nepal Himalaya. Nat Hazard 65(1):135-65View Article
  Dhakal AS, Sidle RC (2003) Long-term modeling of landslides for different forest management practices. Earth Surf Proc Land 28:853-68View Article
  Dixon B (2005) Applicability of neuro-fuzzy techniques in predicting ground-water vulnerability: a GIS-based sensitivity analysis. J Hydrol 309(1-):17-8View Article
  Edeso JM, Merino A, González MJ, Marauri P (1999) Soil erosion under different harvesting managements in steep forest lands from northern Spain. Land Degrad Dev 10:79-8View Article
  Feizizadeh B, Blaschke T, Nazmfar H (2012) GIS-based ordered weighted averaging and Dempster-Shafer methods for landslide susceptibility mapping in the Urmia Lake Basin, Iran. Int J Digit Earth. doi:10.-080/-7538947.-012.-49950
  Güler I, übeyli ED (2005) Adaptive neuro-fuzzy inference system for classification of EEG signals using wavelet coefficients. J Neurosci Meth 148:113-21View Article
  Hickey R (1994) Design and simulation of smelter reclamation strategies using an environmental decisions support system. Doctoral Dissertation. Department of Geography, University of Idaho
  Hickey R (2000) Slope Angle and Slope Length Solutions for GIS. J Cartogr 29(1):1-View Article
  Jang JSR (1993) ANFIS: adaptive-network-based fuzzy inference system. IEEE T Syst Man Cyb 23(3):665-85View Article
  Jang JSR, Sun CT (1995) Neuro-fuzzy modeling and control. P IEEE 83(3):378-06
  Landis JR, Koch GG (1977) The measurement of observer agreement for categorical data. Biometrics 33:159-74View Article
  Lee S (2007) Comparison of landslide susceptibility maps generated through multiple logistic regression for three test areas in Korea. Earth Surf Proc Land 32(14):2133-214View Article
  Lee S, Dan NT (2005) Probabilistic landslide susceptibility mapping in the Lai Chau province of Vietnam: focus on the relationship between tectonic fractures and landslides. Environ Geol 48(6):778-87View Article
  Lee S, Min K (2001) Statistical analysis of landslide susceptibility at Yongin, Korea. Environ Geol 40:1095-113View Article
  Lee S, Sambath T (2006) Landslide susceptibility mapping in the Damrei Romel area, Cambodia using frequency ratio and logistic regression models. Environ Geol 50:847-55View Article
  Lee MJ, Choi JW, Oh HJ, Won JS, Park I, Lee S (2012) Ensemble-based landslide susceptibility maps in Jinbu area, Korea. Environ Earth Sci 67(1):23-7View Article
  Lee S, Hwang J, Park I (2013) Application of data-driven evidential belief functions to landslide susceptibility mapping in Jinbu, Korea. Catena 100:15-0View Article
  Lepore C, Kamal SA, Shanahan P, Bras RL (2012) Rainfall-induced landslide susceptibility zonation of Puerto Rico. Environ Earth Sci 66(6):1667-681View Article
  Li Y, Chen G, Tang C, Zhou G, Zheng L (2012) Rainfall and earthquake-induced landslide susceptibility assessment using GIS and Artificial Neural Network. Nat Hazard Earth Syst Sci 12(8):2719-729View Article
  Mitasova H, Hofierka J, Zlocha M, Iverson L (1996) Modelling topographic potential for erosion and deposition using GIS. Int J GIS 10(5):629-41
  Moore ID, Grayson RB, Ladson AR (1991) Digital terrain modelling: a review of hydrolo
• 作者单位：Moung-Jin Lee (1)
  Inhye Park (2)
  Saro Lee (3) (4)
  
  1. Korea Environment Institute, 10F, Bidg. B, 370 Sicheong-daero, Sejong, 339-007, Republic of Korea
  2. Department of Geoinformatics, University of Seoul, Siripdae-gil 13, Dongdaemun-gu, Seoul, 130-743, Republic of Korea
  3. Geological Research Division, Korea Institute of Geoscience and Mineral Resources (KIGAM), 124, Gwahang-no, Yuseong-gu, Daejeon, 305-350, Republic of Korea
  4. Korea University of Science and Technology, 217 Gajeong-ro Yuseong-gu, Daejeon, 305-350, Republic of Korea
  
• 刊物类别：Earth and Environmental Science
• 刊物主题：None Assigned
• 出版者：Springer Berlin Heidelberg
• ISSN：1866-6299

文摘

Landslides susceptibility maps were constructed in Seorak mountain area, Korea, using an integration of frequency ratio and adaptive neuro-fuzzy inference system (ANFIS) in geographical information system (GIS) environment. Landslide occurrence areas were detected in the study by interpreting aerial photographs and field survey data. Landslide locations were randomly selected in a 50/50 ratio for training and validation of the models, respectively. Topography, geology, soil, and forest databases were also constructed. Maps relevant to landslide occurrence were assembled in a spatial database. Using the constructed spatial database, 17 landslide-related factors were extracted. The adaptive ANFIS model with different types of membership functions (MFs) was then applied for landslide susceptibility mapping in the study area. Two landslide susceptibility maps were prepared using the different MFs. The frequency ratio model was also applied to the landslide susceptibility mapping for comparing with the probabilistic ANFIS model. Finally, the resulting landslide susceptibility maps were validated using the landslide locations which were not used for training the ANFIS. The validation results showed 75.57?% accuracy using the generalized bell-shaped MF model, 74.94?% accuracy using the Sigmoidal 2 MF model and 73.07?% accuracy using frequency ratio model. These accuracy results show that an ANFIS can be an effective tool in landslide susceptibility mapping.