A novel ensemble decision tree-based CHi-squared Automatic Interaction Detection (CHAID) and multivariate logistic regression models in landslide susceptibility mapping

Landslides

Volumn 11, Issue 6, 2014, Pages 1063-1078

  Althuwaynee, Omar F ^a   Pradhan, Biswajeet ^a   Park, Hyuck Jin ^b   Lee, Jung Hyun ^b  

^a UNIVERSITY PUTRA MALAYSIA   (Malaysia)

^b Sejong University   (South Korea)

Author keywords

CHAID.LR; Decision tree; Ensemble modeling; GIS; Landslide; Remote sensing; South Korea

Indexed keywords

CATCHMENTS; DATA MINING; DECISION TREES; DRAIN CURRENT; GEOGRAPHIC INFORMATION SYSTEMS; LANDSLIDES; MAPPING; REMOTE SENSING; SOILS; TEXTURES; TREES (MATHEMATICS);

AUTOMATIC INTERACTION DETECTION; CHAID.LR; CLASSIFICATION AND REGRESSION TREE; EFFICIENCY AND RELIABILITY; ENSEMBLE MODELING; LANDSLIDE SUSCEPTIBILITY MAPPING; MULTIVARIATE LOGISTIC REGRESSIONS; SOUTH KOREA;

LOGISTIC REGRESSION;

DATA MINING; DATA SET; DECISION ANALYSIS; ENSEMBLE FORECASTING; GEOMORPHOLOGICAL MAPPING; GIS; LANDSLIDE; MULTIVARIATE ANALYSIS; NEW RECORD; REGRESSION ANALYSIS; REMOTE SENSING;

SOUTH KOREA;

EID: 84911812068     PISSN: 1612510X     EISSN: 16125118     Source Type: Journal    
DOI: 10.1007/s10346-014-0466-0     Document Type: Article

References (67)

1. Akgün A (2012) A comparison of landslide susceptibility maps produced by logistic regression, multi-criteria decision, and likelihood ratio methods: a case study at İzmir, Turkey. Landslides 9:93–106
2. Akgün A, Turk N (2013) An assessment of conditioning parameter selection efficiency on medium scale erosion susceptibility mapping by gis and remote sensing methodologies: an example from Northwest Turkey, EGU General Assembly Conference Abstracts, pp 7457
3. Akgun A, Sezer EA, Nefeslioglu HA, Gokceoglu C, Pradhan B (2012) An easy-to-use MATLAB program (MamLand) for the assessment of landslide susceptibility using a Mamdani fuzzy algorithm. Comput Geosci 38(1):23–34
4. Althuwaynee OF, Pradhan B, Lee S (2012a) Application of an evidential belief function model in landslide susceptibility mapping. Comput Geosci:44 120-135
5. Althuwaynee OF, Pradhan B, Mahmud AR, Yusoff ZM (2012b) Prediction of slope failures using bivariate statistical based index of entropy model, Humanities, Science and Engineering (CHUSER), 2012 IEEE Colloquium on. IEEE, pp 362–367
6. Althuwaynee OF, Pradhan B, Park H-J, Lee JH (2014) A novel ensemble bivariate statistical evidential belief function with knowledge-based analytical hierarchy process and multivariate statistical logistic regression for landslide susceptibility mapping. Catena 114:21–36
7. Ayalew L, Yamagishi H (2005) The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan. Geomorphology 65:15–31
8. 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
9. 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 99:18–25
10. Baker S, Cousins RD (1984) Clarification of the use of CHI-square and likelihood functions in fits to histograms. Nucl Inst Methods Phys Res 221:437–442
11. Beven K, Kirkby M (1979) A physically based, variable contributing area model of basin hydrology/Un modèle à base physique de zone d’appel variable de l’hydrologie du bassin versant. Hydrol Sci J 24:43–69
12. Bozkir AS, Sezer EA (2011) Predicting food demand in food courts by decision tree approaches. Procedia Comput Sci 3:759–763
13. Bui DT, Pradhan B, Lofman O, Revhaug I, Dick ØB (2013) Regional prediction of landslide hazard using probability analysis of intense rainfall in the Hoa Binh province, Vietnam. Nat Hazards 66:707–730
14. Bui DT, Ho TC, Revhaug I, Pradhan B, Nguyen DB (2014) landslide susceptibility mapping along the National Road 32 of Vietnam using GIS-based J48 decision tree classifier and its ensembles, cartography from pole to pole. Springer, pp 303–317
15. Crozier MJ (1999) Prediction of rainfall-triggered landslides: a test of the Antecedent Water Status Model. Earth Surf Process Landf 24:825–833
16. Dai F, Lee C (2002) Landslide characteristics and slope instability modeling using GIS, Lantau Island, Hong Kong. Geomorphology 42:213–228
17. Demyanyk Y, Hasan I (2010) Financial crises and bank failures: a review of prediction methods. Omega 38:315–324
18. Domínguez-Cuesta MJ, Jiménez-Sánchez M, Berrezueta E (2007) Landslides in the Central Coalfield (Cantabrian Mountains, NW Spain): geomorphological features, conditioning factors and methodological implications in susceptibility assessment. Geomorphology 89:358–369
19. Guzzetti F, Reichenbach P, Ardizzone F, Cardinali M, Galli M (2006) Estimating the quality of landslide susceptibility models. Geomorphology 81:166–184
20. Hosmer DW, Lemeshow S (2000) Applied logistic regression. Wiley-Interscience
21. Jakob M, Hungr O (2005) Debris-flow hazards and related phenomena. Springer
22. Jenness E (2011) An ArcGis extention for analyzing raster elevation dataset. Jenness Enterprises, Flagstaff, AZ 86004 USA
23. Jeong G-C, Kim K-S, Choo C-O, Kim J-T, Kim M-I (2011) Characteristics of landslides induced by a debris flow at different geology with emphasis on clay mineralogy in South Korea. Nat Hazards 59:347–365
24. Kass GV (1980) An exploratory technique for investigating large quantities of categorical data. Appl Stat 29:119–127
25. Lange K (2002) Mathematical and statistical methods for genetic analysis. Springer Verlag
26. Lee S (2004) Application of likelihood ratio and logistic regression models to landslide susceptibility mapping using GIS. Environ Manag 34:223–232
27. Lee S, Min K (2001) Statistical analysis of landslide susceptibility at Yongin, Korea. Environ Geol 40:1095–1113
28. Lee S, Oh H-J (2012) Ensemble-based landslide susceptibility maps in Jinbu area, Korea, Terrigenous Mass Movements. Springer, pp 193-220
29. Lee S, Hwang J, Park I (2013) Application of data-driven evidential belief functions to landslide susceptibility mapping in Jinbu, Korea. Catena 100:15–30
30. Magidson J (1993) SPSS for Windows CHAID reléase 6.0. SPSS Incorporated
31. Menard S (2000) Coefficients of determination for multiple logistic regression analysis. Am Stat 54:17–24
32. Naftulin IS, Rebrova OY (2010) Application of C&RT, CHAID, C4. 5 and WizWhy algorithms for stroke type diagnosis, Artificial Intelligence and Soft Computing. Springer, pp 651–656
33. Nefeslioglu H, Gokceoglu C, Sonmez H (2008) An assessment on the use of logistic regression and artificial neural networks with different sampling strategies for the preparation of landslide susceptibility maps. Eng Geol 97:171–191
34. Nefeslioglu H, Sezer E, Gokceoglu C, Bozkir A, Duman T (2010) Assessment of landslide susceptibility by decision trees in the metropolitan area of Istanbul, Turkey. Math Probl Eng 2010:15
35. Nisbet R, Elder IV J, Miner G (2009) Handbook of statistical analysis and data mining applications. Academic
36. Ohlmacher GC, Davis JC (2003) Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansas, USA. Eng Geol 69:331–343
37. Pal M, Mather PM (2003) An assessment of the effectiveness of decision tree methods for land cover classification. Remote Sens Environ 86:554–565
38. Pourghasemi HR, Mohammadi M, Pradhan B (2012a) Landslide susceptibility mapping using index of entropy and conditional probability models at Safarood Basin, Iran. Catena 97:71–84. doi:10.1016/j.catena.2012.05.005
39. Pourghasemi HR, Pradhan B, Gokceoglu C (2012b) Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran. Nat Hazards 63:965–996
40. Pourghasemi HR, Jirandeh AG, Pradhan B, Xu C, Gokceoglu C (2013a) Landslide susceptibility mapping using support vector machine and GIS at the Golestan Province, Iran. J Earth Syst Sci 122:1–21
41. Pourghasemi HR, Moradi HR, Fatemi Aghda SM, Gokceoglu C, Pradhan B (2013b) GIS-based landslide susceptibility mapping with probabilistic likelihood ratio and spatial multi criteria evaluation models (North of Tehran, Iran). Arab J Geosci. doi:10.1007/s12517-012-0825-x (Article online first available)
42. Pourghasemi H, Pradhan B, Gokceoglu C, Moezzi KD (2013c) A comparative assessment of prediction capabilities of Dempster–Shafer and weights-of-evidence models in landslide susceptibility mapping using GIS. Geomatics Nat Hazards Risk 4:93–118
43. Pradhan B (2010) Landslide susceptibility mapping of a catchment area using frequency ratio, fuzzy logic and multivariate logistic regression approaches. J Indian Soc Remote Sens 38:301–320
44. Pradhan B (2013) A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzy models in landslide susceptibility mapping using GIS. Comput Geosci 51:350–365
45. Pradhan B, Lee S (2010) Landslide susceptibility assessment and factor effect analysis: backpropagation artificial neural networks and their comparison with frequency ratio and bivariate logistic regression modelling. Environ Model Softw 25:747–759
46. Pradhan B, Lee S, Buchroithner MF (2010a) Remote sensing and GIS-based landslide susceptibility analysis and its cross-validation in three test areas using a frequency ratio model. Photogrammetrie, Fernerkundung, Geoinformation 2010:17–32
47. Pradhan B, Oh JJ, Buchroithner MF (2010b) Weight-of-evidence model applied to landslide susceptibility mapping in a tropical hilly area. Geomatics Nat Hazards Risk 1(3):199–223. doi:10.1080/19475705.2010.498151
48. Pradhan B, Youssef AM, Varathrajoo R (2010c) Approaches for delineating landslide hazard areas using different training sites in an advanced artificial neural network model. Geospatial Inf Sci 13(2):93–102
49. Pradhan B, Mansor S, Pirasteh S, Buchroithner MF (2011) Landslide hazard and risk analyses at a landslide prone catchment area using statistical based geospatial model. Int J Remote Sens 32(14):4075–4087
50. Quinlan JR (1993) C4. 5: programs for machine learning. Kaufmann
51. Rygielski C, Wang J-C, Yen DC (2002) Data mining techniques for customer relationship management. Technol Soc 24:483–502
52. Saito H, Nakayama D, Matsuyama H (2009) Comparison of landslide susceptibility based on a decision-tree model and actual landslide occurrence: the Akaishi Mountains, Japan. Geomorphology 109:108–121
53. Sassa K, Canuti P (2008) Landslides-disaster risk reduction. Springer
54. Schmidt K, Roering J, Stock J, Dietrich W, Montgomery D, Schaub T (2001) The variability of root cohesion as an influence on shallow landslide susceptibility in the Oregon Coast Range. Can Geotech J 38:995–1024
55. Sezer EA, Pradhan B, Gokceoglu C (2011) Erratum: Erratum to: manifestation of an adaptive neuro-fuzzy model on landslide susceptibility mapping: Klang valley, Malaysia [Expert Systems with Applications 38 (2011) 8208-8219]. Expert Syst Appl Int J 40:2360
56. SPSS (1998) Answer tree 2.0: user’s guide. SPSS Chicago
57. StatisticsSolutions (2012) CHAID. Statistics Solutions, 2627 McCormick Drive Suite 102, Clearwater, FL 33759
58. Tehrany MS, Pradhan B, Jebur MN (2013) Spatial prediction of flood susceptible areas using rule based decision tree (DT) and ensemble bivariate and multivariate statistical models. J Hydrol 504:69–79. doi:10.1016/j.jhydrol.2013.09.034
59. Terratech (1994) Inventory of forest landslide occurrence in the kamloops forest region, Terratech Western profile consultants LTD
60. Tien Bui D, Pradhan B, Lofman O, Revhaug I, Dick OB (2011) Landslide susceptibility mapping at Hoa Binh province (Vietnam) using an adaptive neuro fuzzy inference system and GIS. Comput Geosci 45:199–211. doi:10.1016/j.cageo.2011.10.031
61. Tien Bui D, Pradhan B, Lofman O, Revhaug I, Dick OB (2012a) Landslide susceptibility assessment in the Hoa Binh province of Vietnam: a comparison of the Levenberg–Marquardt and Bayesian regularized neural networks. Geomorphology 171:12–29
62. Tien Bui D, Pradhan B, Lofman O, Revhaug I, Dick OB (2012b) Spatial prediction of landslide hazards in Hoa Binh province (Vietnam): a comparative assessment of the efficacy of evidential belief functions and fuzzy logic models. Catena 96:28–40
63. Tien Bui D, Pradhan B, Lofman O, Revhaug I (2012c) Landslide susceptibility assessment in Vietnam using support vector machines, decision tree and naïve Bayes models. Mathematical Problems in Engineering, 1–26 (http://www.hindawi.com/journals/mpe/aip/974638/)
64. Van Den Eeckhaut M, Hervás J, Jaedicke C, Malet JP, Montanarella L, Nadim F (2012) Statistical modelling of Europe-wide landslide susceptibility using limited landslide inventory data. Landslides 9:357–369
65. Xu C, Xu X, Dai F, Xiao J, Tan X, Yuan R (2012) Landslide hazard mapping using GIS and weight of evidence model in Qingshui River watershed of 2008 Wenchuan earthquake struck region. J Earth Sci 23:97–120
66. Yeon Y-K, Han J-G, Ryu KH (2010) Landslide susceptibility mapping in Injae, Korea, using a decision tree. Eng Geol 116:274–283
67. Zare M, Pourghasemi HR, Vafakhah M, Pradhan B (2012) Landslide susceptibility mapping at VazWatershed (Iran) using an artificial neural network model: a comparison between multilayer perceptron (MLP) and radial basic function (RBF) algorithms. Arab J Geosci 5:1–16