Landslide detection and susceptibility mapping in the Sagimakri area, Korea using KOMPSAT-1 and weight of evidence technique

Environmental Earth Sciences

Volumn 70, Issue 7, 2013, Pages 3197-3215

  Lee, Saro ^a  

^a Korea Institute of Geosceince and Mineral Resources   (South Korea)

Author keywords

Conditional independence; GIS; Korea; Landslide susceptibility; Weight of evidence

Indexed keywords

CONDITIONAL INDEPENDENCES; KOREA; KOREA MULTI-PURPOSE SATELLITES; LANDSLIDE SUSCEPTIBILITY; LANDSLIDE SUSCEPTIBILITY MAPPING; SUSCEPTIBILITY MAPPING; WEIGHT OF EVIDENCES; WEIGHTS OF EVIDENCES;

GEOGRAPHIC INFORMATION SYSTEMS;

LANDSLIDES;

DATABASE; DETECTION METHOD; FIELD SURVEY; GEOLOGICAL MAPPING; GIS; LANDSLIDE; MAP; NUMERICAL MODEL; SATELLITE DATA; SATELLITE IMAGERY;

KANGWON; KOREA; SAGIMAKRI; SOUTH KOREA;

EID: 84888030629     PISSN: 18666280     EISSN: 18666299     Source Type: Journal    
DOI: 10.1007/s12665-013-2385-0     Document Type: Article

References (90)

1. Abdallah C, Chorowicz J, Bou kheir R, Khawlie M (2005) Detecting major terrain parameters relating to mass movements' occurrence using GIS, remote sensing and statistical correlations, case study Lebanon. Remote Sens Environ 99: 448-461.
2. Akgun A, Türk N (2010) Landslide susceptibility mapping for Ayvalik (Western Turkey) and its vicinity by multicriteria decision analysis. Environ Earth Sci 61: 595-611.
3. Baeza C, Lantada N, Moya J (2010) Validation and evaluation of two multivariate statistical models for predictive shallow landslide susceptibility mapping of the Eastern Pyrenees (Spain). Environ Earth Sci 61: 507-523.
4. Bai SB, Wang J, Lü GN, Zhou PG, Hou SS, Xu SN (2010) GIS-based logistic regression for landslide susceptibility mapping of the Zhongxian segment in the Three Gorges area, China. Geomorphology 115: 23-31.
5. 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: 139-149.
6. Bonham-Carter GF (1994) Geographic information systems for geoscientists, modeling with GIS. Pergamon, Oxford.
7. Bonham-Carter GF, Agterberg FP, Wright DF (1989) Weights of evidence modeling: a new approach to mapping mineral potential. In: Agterberg FP, Bonham-Carter GF (Eds) Statistical applications in the earth sciences: geological survey Canada paper 89-9, pp 171-183.
8. Borgogno Mondino E, Giardino M, Perotti L (2009) A neural network method for analysis of hyperspectral imagery with application to the Cassas landslide (Susa Valley, NW-Italy). Geomorphology 110: 20-27.
9. Brabb EE (1984) Innovative Approaches to Landslide Hazard and Risk Mapping. Proc Fourth Int Symp Landslides Can Geotech Soc, Toronto, Canada 1: 307-324.
10. Carranza EJM, Hale M (2000) Geologically constrained probabilistic mapping of gold potential, Baguio district, Philippines. Nat Resour Res 9: 237-253.
11. Chang KT, Chiang SH (2009) An integrated model for predicting rainfall-induced landslides. Geomorphology 105: 366-373.
12. Chauhan S, Sharma M, Arora M (2010) Landslide susceptibility zonation of the Chamoli region, Garhwal Himalayas, using logistic regression model. Landslides 7: 411-423.
13. Chen CH, KE CC, Wang CL (2009a) A back-propagation network for the assessment of susceptibility to rock slope failure in the eastern portion of the Southern Cross-Island Highway in Taiwan. Environ Geol 57: 723-733.
14. Chen YR, Ni PN, Chen JW, Hsieh SC (2009b) The application of remote sensing technology to the interpretation of land use for rainfall-induced landslides based on genetic algorithms and artificial neural networks. IEEE J Sel Top Applied Earth Observ Rem Sens 2: 87-95.
15. Choi J, Oh HJ, Won JS, Lee S (2010) Validation of an artificial neural network model for landslide susceptibility mapping. Environ Earth Sci 60: 473-483.
16. Chung CJF, Fabbri AG (1999) Probabilistic prediction models for landslide hazard mapping. Photogramm Eng Rem S 65: 1389-1399.
17. Dahal R, Hasegawa S, Nonomura A, Yamanaka M, Masuda T, Nishino K (2008) GIS-based weights-of-evidence modelling of rainfall-induced landslides in small catchments for landslide susceptibility mapping. Environ Geol 54: 311-324.
18. Das I, Sahoo S, van Westen C, Stein A, Hack R (2010) Landslide susceptibility assessment using logistic regression and its comparison with a rock mass classification system, along a road section in the northern Himalayas (India). Geomorphology 114: 627-637.
19. Dominguez-Cuesta M, Jimenez-Sánchez M, Colubi A, González-Rodríguez G (2010) Modelling shallow landslide susceptibility: a new approach in logistic regression by using favourability assessment. Int J Earth Sci 99: 661-674.
20. Dong JJ, Lee CT, Tung YH, Liu CN, Lin KP, Lee JF (2009) The role of the sediment budget in understanding debris flow susceptibility. Earth Surf Proc Land 34: 1612-1624.
21. Ercanoglu M, Temiz FA (2011) Application of logistic regression and fuzzy operators to landslide susceptibility assessment in Azdavay (Kastamonu, Turkey). Environ Earth Sci 64: 949-964.
22. Erener A, Düzgün HSB (2012) Landslide susceptibility assessment: what are the effects of mapping unit and mapping method? Environ Earth Sci 66: 859-877.
23. Falaschi F, Giacomelli F, Federici P, Puccinelli A, D'amato Avanzi G, Pochini A, Ribolini A (2009) Logistic regression versus artificial neural networks: landslide susceptibility evaluation in a sample area of the Serchio River valley, Italy. Nat Hazards 50: 551-569.
24. Gao J, Maro J (2010) Topographic controls on evolution of shallow landslides in pastoral Wairarapa, New Zealand, 1979-2003. Geomorphology 114: 373-381.
25. Gorsevski PV, Jankowski P (2010) An optimized solution of multi-criteria evaluation an analysis of landslide susceptibility using fuzzy sets and Kalman filter. Com Geo 36: 1005-1020.
26. Guzzetti F, Reichenbach P, Cardinali M, Galli M, Ardizzone F (2005) Probabilistic landslide hazard assessment at the basin scale. Geomorphology 72: 272-299.
27. He YR, Fu WJ (2009) Application of fuzzy support vector machine to landslide risk assessment. J Nat Disasters 18: 107-112.
28. Hong Y, Adler RF, Huffman G (2007) An experimental global prediction system for Rainfall-Triggered landslides using satellite remote sensing and geospatial datasets. IEEE T Geosci Remote 45: 1671-1680.
29. Intarawichian N, Dasananda S (2011) Frequency ratio model based landslide susceptibility mapping in lower Mae Chaem watershed, Northern Thailand. Environ Earth Sci 64: 2271-2285.
30. Kanungo D, Arora M, Gupta R, Sarkar S (2008) Landslide risk assessment using concepts of danger pixels and fuzzy set theory in Darjeeling Himalayas. Landslides 5: 407-416.
31. Kanungo DP, Arora MK, Sarkar S, Gupta RP (2009) A fuzzy set based approach for integration of thematic maps for landslide susceptibility zonation. Georisk 3: 30-43.
32. Kawabata D, Bandibas J (2009) Landslide susceptibility mapping using geological data, a DEM from ASTER images and an Artificial Neural Network (ANN). Geomorphology 113: 97-109.
33. Kincal C, Akgun A, Koca M (2009) Landslide susceptibility assessment in the İzmir (West Anatolia, Turkey) city center and its near vicinity by the logistic regression method. Environ Earth Sci 59: 745-756.
34. Korea Forest Research Institute (1997) Forest map, 1: 25, 000.
35. Korea Institute of Geoscience and Mineral Resources (2001) Geological map, 1: 250, 000.
36. Lee S (2005) Application of logistic regression model and its validation for landslide susceptibility mapping using GIS and remote sensing data. Int J Remote Sens 26: 1477-1491.
37. Lee S (2007a) Application and verification of fuzzy algebraic operators to landslide susceptibility mapping. Environ Geol 52: 615-623.
38. Lee S (2007b) Landslide susceptibility mapping using an artificial neural network in the Gangneung area, Korea. Int J Remote Sens 28: 4763-4783.
39. Lee S, Choi J (2004) Landslide susceptibility mapping Using GIS and the weight-of-evidence model. Int J Geogr Inf Sci 18: 789-814.
40. Lee S, Lee MJ (2006) Detecting landslide location using KOMPSAT 1 and its application to landslide-susceptibility mapping at the Gangneung area, Korea. Adv Space Res 38: 2261-2271.
41. Lee S, Ryu JH, Lee MJ, Won JS (2006) The application of artificial neural networks to landslide susceptibility mapping at Janghung, Korea. Math Geol 38: 199-220.
42. Lee S, Ryu JH, Kim IS (2007) Landslide susceptibility analysis and its verification using likelihood ratio, logistic regression, and artificial neural network models: case study of Youngin, Korea. Landslides 4: 327-338.
43. Legorreta Paulin G, Bursik M (2009) Logisnet: a tool for multimethod, multiple soil layers slope stability analysis. Com Geo 35: 1007-1016.
44. Lepore C, Kamal SA, Shanahan P, Bras RL (2012) Rainfall-induced landslide susceptibility zonation of Puerto Rico. Environ Earth Sci 66: 1667-1681.
45. Liu CN, Dong JJ, Peng YF, Huang HF (2009) Effects of strong ground motion on the susceptibility of gully type debris flows. Eng Geol 104: 241-253.
46. Lyon JG, Yuan D, Lunetta RS, Elvidge CD (1998) A change detection experiment using vegetation indices. Photogramm Rem Sens 64: 143-150.
47. Mathew J, Jha VK, Rawat GS (2007) Application of binary logistic regression analysis and its validation for landslide susceptibility mapping in part of Garhwal Himalaya, India. Int J Remote Sens 28: 2257-2275.
48. Melchiorre C, Matteucci M, Azzoni A, Zanchi A (2008) Artificial neural networks and cluster analysis in landslide susceptibility zonation. Geomorphology 94: 379-400.
49. Metternicht G, Hurnl L, Gogu R (2005) Remote sensing of landslides: an analysis of the potential contribution to geo-spatial systems for hazard assessment in mountainous environments. Remote Sens Environ 98: 284-303.
50. Miles SB, Keefer DK (2009) Evaluation of CAMEL-comprehensive areal model of earthquake-induced landslides. Eng Geol 104: 1-15.
51. Muthu K, Petrou M, Tarantino C, Blonda P (2008) Landslide possibility mapping using fuzzy approaches. IEEE T Geosci Remote 46: 1253-1265.
52. National Geographic Information Institute (2005) Topography map, 1: 5, 000.
53. National Institute of Agricultural Science and Technology (1983) Detailed soil map, 1: 25, 000.
54. Neuhäuser B, Terhorst B (2007) Landslide susceptibility assessment using "weights-of-evidence" applied to a study area at the Jurassic Escarpment (Sw-Germany). Geomorphology 86: 12-24.
55. Oh HJ, Lee S (2010) Cross-validation of logistic regression model for landslide susceptibility mapping at Geneoung areas, Korea. Disaster Advances 3: 44-55.
56. Oh HJ, Lee S (2011a) Landslide susceptibility mapping on Panaon Island, Philippines using a geographic information system. Environ Earth Sci 62: 935-951.
57. Oh HJ, Lee S (2011b) Cross-application used to validate landslide susceptibility maps using a probabilistic model from Korea. Environ Earth Sci 64: 395-409.
58. Oh HJ, Pradhan B (2011) Application of a neuro-fuzzy model to landslide-susceptibility mapping for shallow landslides in a tropical hilly area. Com Geo 37: 1264-1276.
59. Oh HJ, Lee S, Soedradjat GM (2010) Quantitative landslide susceptibility mapping at Pemalang area, Indonesia. Environ Earth Sci 60: 1317-1328.
60. Ozdemir A (2009) Landslide susceptibility mapping of vicinity of Yaka Landslide (Gelendost, Turkey) using conditional probability approach in GIS. Environ Geol 57: 1675-1686.
61. Park NW (2010) Application of Dempster-Shafer theory of evidence to GIS-based landslide susceptibility analysis. Environ Earth Sci 62: 367-376.
62. Poudyal CP, Chang C, Oh HJ, Lee S (2010) Landslide susceptibility maps comparing frequency ratio and artificial neural networks: a case study from the Nepal Himalaya. Environ Earth Sci 61: 1049-1064.
63. Prabu S, Ramakrishnan S (2009) Combined use of socio economic analysis, remote sensing and GIS data for landslide hazard mapping using ANN. J Indian Soc Rem Sens 37: 409-421.
64. Pradhan B (2010) Remote sensing and GIS-based landslide hazard analysis and cross validation using multivariate logistic regression model on three test areas in Malaysia. Adv Space Res 45: 1244-1256.
65. Pradhan B (2011) Use of GIS-based fuzzy logic relations and its cross application to produce landslide susceptibility maps in three test areas in Malaysia. Environ Earth Sci 63: 329-349.
66. Pradhan B, Buchroithner MF (2010) Comparison and validation of landslide susceptibility maps using an artificial neural network model for three test areas in Malaysia. Environ Eng Geosci 16: 107-126.
67. Pradhan B, Lee S (2007) Utilization of optical remote sensing data and GIS tools for regional landslide hazard analysis using an artificial neural network model. Earth Sci Front 14: 143-151.
68. Pradhan B, Lee S (2009) Landslide risk analysis using artificial neural network model focussing on different training sites. Int J Physic Sci 4: 01-015.
69. Pradhan B, Lee S (2010) Regional landslide susceptibility analysis using back-propagation neural network model at Cameron Highland, Malaysia. Landslides 7: 13-30.
70. Pradhan B, Lee S, Mansor S, Buchroithner M, Jamaluddin N, Khujaimah Z (2008) Utilization of optical remote sensing data and geographic information system tools for regional landslide hazard analysis by using binomial logistic regression model. J App Rem Sens 2: 023542.
71. Pradhan B, Lee S, Buchroithner MF (2010) A GIS-based back-propagation neural network model and its cross-application and validation for landslide susceptibility analyses. Comput Environ Urban 34: 216-235.
72. Qi S, Xu Q, Lan H, Zhang B, Liu J (2010) Spatial distribution analysis of landslides triggered by 2008. 5. 12 Wenchuan Earthquake. China. Eng Geol 116: 95-108.
73. Rapolla A, Paoletti V, Secomandi M (2010) Seismically-induced landslide susceptibility evaluation: application of a new procedure to the island of Ischia, Campania Region, Southern Italy. Eng Geol 114: 10-25.
74. Regmi NR, Giardino JR, Vitek JD (2010) Modeling susceptibility to landslides using the weight of evidence approach: western Colorado, USA. Geomorphology 115: 172-187.
75. Shafri HZM, Zahidi IM, Bakar SA (2010) Development of landslide susceptibility map utilizing remote sensing and Geographic Information Systems (GIS). Disaster Prev Manag 19: 59-69.
76. Singh A (1989) Digital change detection techniques using remotely-sensed data. Int J Remote Sens 10: 989-1003.
77. Sterlacchini S, Ballabio C, Blahut J, Masetti M, Sorichetta A (2011) Spatial Agreement of Predicted Patterns in Landslide Susceptibility Maps. Geomorphology 125: 51-61.
78. Suh J, Choi Y, Roh TD, Lee HJ, Park HD (2011) National-scale assessment of landslide susceptibility to rank the vulnerability to failure of rock-cut slopes along expressways in Korea. Environ Earth Sci 63: 619-632.
79. Tangestani MH (2009) A comparative study of Dempster-Shafer and fuzzy models for landslide susceptibility mapping using a GIS: an experience from Zagros Mountains, SW Iran. J Asian Earth Sci 35: 66-73.
80. Thiery Y, Malet JP, Sterlacchini S, Puissant A, Maquaire O (2007) Landslide susceptibility assessment by bivariate methods at large scales: application to a complex mountainous environment. Geomorphology 92: 38-59.
81. Vahidnia MH, Alesheikh AA, Alimohammadi A, Hosseinali F (2009) Landslide hazard zonation using quantitative methods in GIS. Int J Civil Eng 7: 176-189.
82. van Westen CJ, Rengers N, Soeters R (2003) Use of geomorphological information in indirect landslide susceptibility assessment. Nat Hazards 30: 399-419.
83. Wang WD, Guo J, Fang LG, Chang XS (2012) A subjective and objective integrated weighting method for landslides susceptibility mapping based on GIS. Environ Earth Sci 65: 1705-1714.
84. Winterkorn HF, Fang HY (1991) Soil technology and engineering properties of soils. In: Foundation engineering handbook, 2nd edn. van Nostrand Reinhold, New York, pp 88-143.
85. Wu CH, Chen SC (2009) Determining landslide susceptibility in Central Taiwan from rainfall and six site factors using the analytical hierarchy process method. Geomorphology 112: 190-204.
86. Yalcin A, Reis S, Aydinoglu AC, Yomralioglu T (2011) A GIS-based comparative study of frequency ratio, analytical hierarchy process, bivariate statistics and logistics regression methods for landslide susceptibility mapping in Trabzon, NE Turkey. Catena 85: 274-287.
87. Yilmaz I (2009a) A case study from Koyulhisar (Sivas-Turkey) for landslide susceptibility mapping by artificial neural networks. Bull Eng Geol Environ 68: 297-306.
88. Yilmaz I (2009b) Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: a case study from Kat landslides (Tokat-Turkey). Com Geo 35: 1125-1138.
89. Yilmaz I (2010) The effect of the sampling strategies on the landslide susceptibility mapping by conditional probability and artificial neural networks. Environ Earth Sci 60: 505-519.
90. Yilmaz C, Topal T, Suzen ML (2011) GIS-based landslide susceptibility mapping using bivariate statistical analysis in Devrek (Zonguldak-Turkey). Environ Earth Sci. doi: 10. 1007/s12665-011-1196-4.