Landslide susceptibility mapping using geographically-weighted principal component analysis

Geomorphology

Volumn 226, Issue , 2014, Pages 15-24

  Faraji Sabokbar, Hassanali ^a   Shadman Roodposhti, Majid ^a   Tazik, Esmaeil ^a  

^a UNIVERSITY OF TEHRAN   (Iran)

Author keywords

Fuzzy gamma operator; Geographically weighted principal component analysis (GWPCA); Iran; Landslide susceptibility mapping (LSM)

Indexed keywords

EROSION; FUZZY MATHEMATICS; GEOLOGICAL MAPPING; HAZARD ASSESSMENT; LANDSLIDE; LEAST SQUARES METHOD; MASS MOVEMENT; MULTIVARIATE ANALYSIS; PRINCIPAL COMPONENT ANALYSIS; SLOPE FAILURE; EFFICIENCY MEASUREMENT; EROSION RATE; GIS; INVENTORY; MAPPING; RISK ASSESSMENT; SLOPE DYNAMICS; SPATIAL DATA;

IRAN;

EID: 84905674962     PISSN: 0169555X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.geomorph.2014.07.026     Document Type: Article

References (65)

1. Akgun A., Sezer E.A., Nefeslioglu H.A., Gokceoglu C., Pradhan B. An easy-to-use MATLAB program (MamLand) for the assessment of landslide susceptibility using a Mamdani fuzzy algorithm. Comput. Geosci. 2012, 38:23-34.
2. Althuwaynee O.F., Pradhan B., Lee S. Application of an evidential belief function model in landslide susceptibility mapping. Comput. Geosci. 2012, 44:120-135.
3. Ayalew L., Yamagishi H. The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan. Geomorphology 2005, 65:15-31.
4. Bai S.B., Wang J., Lu G.N., Kanevski M., Pozdnoukhov A. GIS-based landslide susceptibility mapping with validation and comparison of spatial prediction models at the basin scale. 33rd IGC, Oslo 2008, August 6-14th 2008.
5. Bai S.B., Wang J., Lu G.N., Kanevski M., Pozdnoukhov A. GIS-based landslide susceptibility mapping with comparisons of results from machine learning methods process versus logistic regression in Bailongjiang River Basin, China. European Geosciences Union General Assembly 2008 Vienna, Austria 2008, 13-18.
6. Ballabio C., Sterlacchini S. Support vector machines for landslide susceptibility mapping: the Staffora River Basin case study, Italy. Math. Geosci. 2012, 44:47-70.
7. Bathrellos G.D., Kalivas D.P., Skilodimou H.D. Landslide susceptibility mapping models, applied to natural and urban planning, using G.I.S. J. Estud. Geol. 2009, 65:49-65.
8. Birch C.P.D., Oom S.P., Beecham J.A. Rectangular and hexagonal grids used for observation, experiment and simulation in ecology. Ecol. Model. 2007, 206:347-359.
9. Bishop C.M. Neural Networks for Pattern Recognition 1995, Clarendon Press, Oxford.
10. Bishop C.M. Pattern Recognition and Machine Learning (Information Science and Statistics) 2007, Springer, New York.
11. Carr D.B., Olsen A.R., White D. Hexagon mosaic maps for display of univariate and bivariate geographical data. Cartogr. Geogr. Inf. Syst. 1992, 19:28-236.
12. Carrara A. Multivariate models for landslide hazard evaluation. Math. Geol. 1983, 15:403-426.
13. Carrara A., Cardinali M., Detti R., Guzzetti F., Pasqui V., Reichenbach P. GIS techniques and statistical models in evaluating landslide hazard. Earth Surf. Process. Landf. 1991, 16:427-445.
14. Chirici G., Barbati A., Corona P., Marchetti M., Travaglini D., Maselli F., Bertini R. Non-parametric and parametric methods using satellite images for estimating growing stock volume in alpine and Mediterranean forest ecosystems. Remote Sens. Environ. 2008, 112:2686-2700.
15. Cho S., Lambert D.M., Kim S.G., Jung S. Extreme coefficients in geographically weighted regression and their effects on mapping. GISci. Remote Sens. 2009, 46:273-288.
16. Conoscenti C., Maggio C.D., Rotigliano E. GIS-analysis to assess landslide susceptibility in fluvial basins of NW Sicily (Italy). Geomorphology 2007, 94:325-339.
17. Dai F.C., Lee C.F. Landslide characteristics and slope instability modeling using GIS; Lantau Island, Hong Kong. Geomorphology 2002, 42:213-228.
18. Dai F.C., Lee C.F., Li J., Xu Z.W. Assessment of landslide susceptibility on the natural terrain of Lantau Island, Hong Kong. Environ. Geol. 2001, 43:381-391.
19. Donati L., Turrini M.C. An objective method to rank the importance of the factors predisposing to landslides with the GIS methodology: application to an area of the Apennines (Valnerina; Perugia, Italy). Eng. Geol. 2002, 63:277-289.
20. Ercanoglu M., Gokceoglu C. Use of fuzzy relations to produce landslide susceptibility map of a landslide prone area (West Black Sea Region, Turkey). Eng. Geol. 2004, 75:229-250.
21. Fawcett T. An introduction to ROC analysis. Pattern Recogn. Lett. 2006, 27:861-874.
22. Feizizadeh B., Blaschke T. Landslide risk assessment based on GIS multi-criteria evaluation: a case study in Bostan-Abad County, Iran. J. Earth Sci. Eng. 2011, 1:66-71.
23. Fotheringham A.S., Brunsdon C., Charlton M. Geographically Weighted Regression: The Analysis of Spatially Varying Relationships 2002, John Wiley & Sons, Chichester.
24. Goetz J.N., Guthrie R.H., Brenning A. Integrating physical and empirical landslide susceptibility models using generalized additive models. Geomorphology 2011, 129:376-386.
25. Guzzetti F., Reichenbah P., Ardizzone F., Cardinali M., Galli M. Estimating the quality of landslide susceptibility models. Geomorphology 2006, 81:166-184.
26. Guzzetti F., Peruccacci S., Rossi M., Stark C.P. Rainfall thresholds for the initiation of landslides in central and southern Europe. Meteorog. Atmos. Phys. 2007, 98:239-267.
27. Guzzetti F., Mondini A.C., Cardinali M., Fiorucci F., Santangelo M., Chang K.T. Landslide inventory maps: new tools for and old problem. Earth Sci. Rev. 2012, 112:42-66.
28. Hong Y., Hiura H., Shino K., Sassa K., Suemine A., Fukuoka H., Wang G. The influence of intense rainfall on the activity of large-scale crystalline schist landslides in Shikoku Island, Japan. Landslides 2005, 2:97-105.
29. Hyndman J.R., Koehler A.B. Another look at measures of forecast accuracy. Int. J. Forecast. 2006, 22:679-688.
30. Jiang B., Yao X., Wheeler D.C. Visualizing and diagnosing coefficients from geographically weighted regression models. Geospatial Analysis and Modelling of Urban Structure and Dynamics 2010, 415-436. Springer, Netherlands. D.Z. Sui, W. Tietze, P. Claval, Y. Gradus, S.O. Park, H. Wusten (Eds.).
31. Kanungo D.P., Arora M.K., Sarkar S., Gupta R.P. A comparative study of conventional, ANN black box, fuzzy and combined neural and fuzzy weighting procedures for landslide susceptibility zonation in Darjeeling Himalayas. Eng. Geol. 2006, 85:347-366.
32. Kayastha P., Dhital M., De Smedt F. Landslide susceptibility mapping using the weight of evidence method in the Tinau watershed, Nepal. Nat. Hazards 2012, 63:479-498.
33. Komac M. A landslide susceptibility model using the analytical hierarchy process method and multivariate statistics in perialpine Slovenia. Geomorphology 2006, 74:17-28.
34. Lee S., Min K. Statistical analysis of landslide susceptibility at Yongin, Korea. Environ. Geol. 2001, 40:1095-1113.
35. Li C., Zhang S., Zhang H., Pang L., Lam K., Hui C., Zhang S. Using the K-nearest neighbor algorithm for the classification of lymph node metastasis in gastric cancer. Comput. Math. Methods Med. 2012, 10.1155/2012/876545.
36. Lloyd C.D. Analysing population characteristics using geographically weighted principal components analysis: a case study of Northern Ireland in 2001. Comput. Environ. Urban. Syst. 2010, 34:389-399.
37. Marjanovic M., Kovaevic M., Bajat B., Vozenilek V. Landslide susceptibility assessment using SVM machine learning algorithm. Eng. Geol. 2011, 123:225-234.
38. McKean J., Roering J. Objective landslide detection and surface morphology mapping using high-resolution airborne laser altimetry. Geomorphology 2004, 57:331-351.
39. McNeil B.E., Martell R.E., Read J.M. GIS and biogeochemical models for examining the legacy of forest disturbance in the Adirondack Park, NY, USA. Ecol. Model. 2006, 195:281-295.
40. MNR, Ministry of Natural Resources, Golestan Province Landslide Event Report 2010, (Golestan, Iran).
41. Mohammady M., Pourghasemi H.R., Pradhan B. Landslide susceptibility mapping at Golestan Province, Iran: a comparison between frequency ratio, Dempster-Shafer, and weights-of-evidence models. J. Asian Earth Sci. 2012, 61:221-236.
42. Moradi M., Bazyar M.H., Mohammadi Z. GIS-based landslide susceptibility mapping by AHP method, a case study, Dena City, Iran. J. Basic Appl. Sci. Res. 2012, 2:6715-6723.
43. Nandi A., Shakoor A. A GIS-based landslide susceptibility evaluation using bivariate and multivariate statistical analyses. Eng. Geol. 2009, 110:11-20.
44. Neuhausev B., Damm B., Terhorst B. GIS based assessment of landslide susceptibility on the basis of weights of evidence model. Landslides 2012, 9:511-528.
45. Ohlmacher G.C., Davis J.C. Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansas, USA. Eng. Geol. 2003, 69:331-343.
46. Ozdemir A. Landslide susceptibility mapping using Bayesian approach in the Sultan Mountains (Akşehir, Turkey). Nat. Hazards 2011, 59:1573-1607.
47. Pourghasemi H.R. Landslide Hazard Assessment Using Fuzzy Logic (Case Study: A Part of Haraz Watershed) 2008, 92. M.Sc. Thesis, Tarbiat Modarres University International Campus, Iran.
48. Pourghasemi H.R., Biswajeet P., Gokceoglu C., Deylami Moezzi K. Landslide susceptibility mapping using a spatial multi criteria evaluation model at Haraz Watershed, Iran. Terrigenous Mass Movements 2012, 10.1007/978-3-642-25495-6_2.
49. Pradhan B. 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. 2012, 51:350-365.
50. Pradhan B., Chaudhari A., Adinarayana J., Buchroithner M.F. Soil erosion assessment and its correlation with landslide events using remote sensing data and GIS: a case study at Penang Island, Malaysia. Environ. Monit. Assess. 2012, 184:715-727.
51. Ray N., Burgman M.A. Subjective uncertainties in habitat suitability maps. Ecol. Model. 2006, 195:172-186.
52. Rosenfeld A. Connectivity in digital pictures. J. ACM 1970, 17:146-160.
53. Sandham W., Leggett M. Geophysical Applications of Artificial Neural Networks and Fuzzy Logic 2003, Kluwer Academic Publishers, Dordrecht.
54. Schicker R., Moon V. Comparison of bivariate and multivariate statistical approaches in landslide susceptibility mapping at a regional scale. Geomorphology 2012, 161-162:40-57.
55. Shadman M., Rahimi S., Jafar Beglou M. PROMETHEE II and fuzzy AHP: an enhanced GIS-based landslide susceptibility mapping. Nat. Hazards 2014, 73:77-95.
56. Thiery Y., Malet J.P., Sterlacchini S., Puissant A., Maquaire O. Landslide susceptibility assessment by bivariate methods at large scales: application to a complex mountainous environment. Geomorphology 2007, 92:38-59.
57. Vahidnia M.H., Alesheikh A.A., Alimohammadi A., Hosseinali F. A GIS-based neuro-fuzzy procedure for integrating knowledge and data in landslide susceptibility mapping. Comput. Geosci. 2010, 36:1101-1114.
58. Wheeler D.C. Diagnostic tools and a remedial method for collinearity in geographically weighted regression. Environ. Plan. A 2007, 39:2464-2481.
59. Wheeler D.C. Simultaneous coefficient penalization and model selection in geographically weighted regression: the geographically weighted lasso. Environ. Plan. A 2009, 41:722-742.
60. Wheeler D.C., Páez A. Geographically weighted regression. Handbook of Applied Spatial Analysis: Software Tools, Methods and Applications 2010, 461-486. Springer, Berlin and Heidelberg. M.M. Fischer, A. Getis (Eds.).
61. Wheeler D., Tiefelsdorf M. Multi-collinearity and correlation among local regression coefficients in geographically weighted regression. J. Geogr. Syst. 2005, 7:161-187.
62. Xu C., Xu X., Dai F., Saraf A.K. Comparison of different models for susceptibility mapping of earthquake triggered landslides related with the 2008 Wenchuan earthquake in China. Comput. Geosci. 2012, 46:317-329.
63. Yalçin A. GIS-based landslide susceptibility mapping using analytical hierarchy process and bivariate statistics in Ardesen (Turkey): comparisons of results and confirmations. Catena 2008, 72:1-12.
64. Yang L., Jin R. Distance metric learning: a comprehensive survey. Tech. Rep 2006, Department of Computer Science and Engineering, Michigan State University.
65. Yapo P.O., Gupta H.V., Sorooshian S. Automatic calibration of conceptual rainfall-runoff models: sensitivity to calibration data. J. Hydrol. 1996, 181:23-48.