Application of GIS based data driven evidential belief function model to predict groundwater potential zonation

Journal of Hydrology

Volumn 513, Issue , 2014, Pages 283-300

  Nampak, Haleh ^a   Pradhan, Biswajeet ^a   Manap, Mohammad Abd ^b  

^a UNIVERSITY PUTRA MALAYSIA   (Malaysia)

^b Minerals and Geoscience Department   (Malaysia)

Author keywords

Evidential belief function (EBF); GIS; Groundwater potential; Logistic regression (LR); Malaysia; Remote sensing

Indexed keywords

DIGITAL STORAGE; FORECASTING; GEOGRAPHIC INFORMATION SYSTEMS; LITHOLOGY; MAPS; PRODUCTIVITY; REGRESSION ANALYSIS; REMOTE SENSING; SATELLITE IMAGERY; STATISTICAL TESTS; UNCERTAINTY ANALYSIS; WELL TESTING;

BELIEF FUNCTION; DEMPSTER-SHAFER THEORY OF EVIDENCE; GROUNDWATER POTENTIALS; LOGISTIC REGRESSION MODELING; LOGISTIC REGRESSIONS; MALAYSIA; NORMALIZED DIFFERENCE VEGETATION INDEX; TOPOGRAPHIC WETNESS INDEX;

GROUNDWATER;

BOREHOLE; DATA SET; GIS; GROUNDWATER; HYDROGEOLOGY; NDVI; NUMERICAL MODEL; SATELLITE DATA; SATELLITE IMAGERY; ZONATION;

LANGAT BASIN; MALAYSIA; WEST MALAYSIA;

EID: 84898908992     PISSN: 00221694     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jhydrol.2014.02.053     Document Type: Article

References (65)

1. Akgun A. A comparison of landslide susceptibility maps produced by logistic regression, multi-criteria decision, and likelihood ratio methods: a case study at İzmir, Turkey. Landslides 2012, 9(1):93-106.
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. Althuwaynee O.F., Pradhan B., Park H.J., Lee J.H. A novel ensemble bivariate statistical evidential belief function with knowledge-based analytical hierarchy process and multivariate statistical logistic regression for landslide susceptibility mapping. Catena 2014, 114:21-36.
4. 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.
5. Ayazi M.H., Pirasteh S., Arvin A.K.P., Pradhan B., Nikouravan B., Mansor S. Disasters and risk reduction in groundwater: Zagros Mountain Southwest Iran using geoinformatics techniques. Disaster Adv. 2010, 3(1):51-57.
6. Banks D., Robins N.S., Robins N. An Introduction to Groundwater in Crystalline Bedrock 2002, Norges Geologiske Undersokelse.
7. Beven K.J., Kirkby M.J. 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. 1979, 24(1):43-69.
8. Bringemeier, 2006. Groundwater exploration adjacent to the Kuala Lumpur International Airport/Malaysia-challenges and chances of exploring a fractured rock aquifer, http://www.coffey.com/.
9. Bui D.T., Pradhan B., Lofman O., Revhaug I., Dick O.B. 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 2012, 96:28-40.
10. Bui D.T., Pradhan B., Revhaug I., Nguyen D.B., Pham H.V., Bui Q.N. A novel hybrid evidential belief function-based fuzzy logic model in spatial prediction of rainfall-induced shallow landslides in the Lang Son city area (Vietnam). Geomatics, Nat. Hazard Risk 2013, 1-30. (article online first available). 10.1080/19475705.2013.843206.
11. Carranza E.J.M., Castro O.T. Predicting lahar-inundation zones: case study in West Mount Pinatubo, Philippines. Nat. Hazards 2006, 37(3):331-372.
12. Carranza E.J.M., Hale M. Evidential belief functions for data-driven geologically constrained mapping of gold potential, Baguio district, Philippines. Ore. Geol. Rev. 2003, 22(1):117-132.
13. Carranza E.J.M., Woldai T., Chikambwe E.M. Application of data-driven evidential belief functions to prospectivity mapping for aquamarine-bearing pegmatites, Lundazi district, Zambia. Nat. Resour. Res. 2005, 14(1):47-63.
14. Chang-Jo F., Fabbri A.G. Validation of spatial prediction models for landslide hazard mapping. Nat. Hazards 2003, 30(3):451-472.
15. Charon, J.E., 1974. Hydrogeological applications of ERTS satellite imagery. In: Proc UN/FAO Regional Seminar on Remote Sensing of Earth Resources and Environment, Cairo. Commonwealth Science Council, pp. 439-456.
16. Chenini I., Mammou A.B. Groundwater recharge study in arid region: an approach using GIS techniques and numerical modelling. Comput. Geosci. 2010, 36(6):801-817.
17. Chenini I., Mammou A.B., Moufida E.M. Groundwater recharge zone mapping using GIS-based multi-criteria analysis: a case study in Central Tunisia (Maknassy Basin). Water Resour. Manage 2010, 24(5):921-939.
18. Chowdhury A., Jha M.K., Chowdary V.M., Mal B.C. Integrated remote sensing and GIS-based approach for assessing groundwater potential in West Medinipur district, West Bengal, India. Int. J. Remote Sens. 2009, 30(1):231-250.
19. Corsini A., Cervi F., Ronchetti F. Weight of evidence and artificial neural networks for potential groundwater spring mapping: an application to the Mt. Modino area (Northern Apennines, Italy). Geomorphology 2009, 111(1):79-87.
20. Dar I.A., Sankar K., Dar M.A. Remote sensing technology and geographic information system modeling: an integrated approach towards the mapping of groundwater potential zones in Hardrock terrain, Mamundiyar basin. J. Hydrol. 2010, 394:285-295.
21. Dempster A. Upper and lower probabilities induced by a multivalued mapping. Classic Works of the Dempster-Shafer Theory of Belief Functions 2008, 57-72. Springer, Berlin, Heidelberg, (Chapter 3). R. Yager, L. Liu, A.P. Dempster, G. Shafer (Eds.).
22. Fitts C.R. Groundwater Science 2002, Academic Press.
23. Ganapuram S., Kumar G.T., Krishna I.V., Kahya E., Demirel M.C. Mapping of groundwater potential zones in the Musi basin using remote sensing data and GIS. Adv. Eng. Software 2009, 40(7):506-518.
24. Ghayoumian J., MohseniSaravi M., Feiznia S., Nouri B., Malekian A. Application of GIS techniques to determine areas most suitable for artificial groundwater recharge in a coastal aquifer in southern Iran. J. Asian Earth Sci. 2007, 30(2):364-374.
25. Gupta M., Srivastava P.K. Integrating GIS and remote sensing for identification of groundwater potential zones in the hilly terrain of Pavagarh, Gujarat, India. Water Int. 2010, 35(2):233-245.
26. Hosmer D.W., Lemeshow S. Applied Logistic Regression 2000, Jhon Wiley & Sons Inc., NewYork. second ed.
27. Hutchison, C.S., Tan, D.N.K., 2009. Geology of Peninsular Malaysia, University of Malaya.
28. Jha M.K., Chowdhury A., Chowdary V.M., Peiffer S. Groundwater management and development by integrated remote sensing and geographic information systems: prospects and constraints. Water Resour. Manage 2007, 21(2):427-467.
29. Juahir H., Zain S.M., Aris A.Z., Yusof M.K., Samah M.A.A., Mokhtar M. Hydrological trend analysis due to land use changes at Langat River Basin. Environ. Asia 2010, 3(2010):20-31.
30. Kavzoglu T., Sahin E.K., Colkesen I. Landslide susceptibility mapping using GIS-based multi-criteria decision analysis, support vector machines, and logistic regression. Landslides 2013, 1-15.
31. Krishnamurthy J., Kumar N.V., Jayaraman V., Manivel M. An approach to demarcate groundwater potential zones through remote sensing and a geographic information system. Int. J. Remote Sens. 1996, 17(10):1867-1884.
32. Lee S. Application of logistic regression model and its validation for landslide susceptibility mapping using GIS and remote sensing data. Int. J. Remote Sens. 2005, 26:1477-1491.
33. Lee S., Kim Y.S., Oh H.J. Application of a weights-of-evidence method and GIS to regional groundwater productivity potential mapping. J. Environ. Manage. 2012, 96(1):91-105.
34. Lee S., Hwang J., Park I. Application of data-driven evidential belief functions to landslide susceptibility mapping in Jinbu, Korea. Catena 2013, 100:15-30.
35. Madrucci V., Taioli F., Cesar de Araujo C. Groundwater favourability map using GIS multi criteria data analysis on crystalline terrain, Sao Paulo State, Brazil. J. Hydrol. 2008, 357:153-173.
36. Magesh N.S., Chandrasekar N., Soundranayagam J.P. Delineation of groundwater potential zones in Theni district, Tamil Nadu, using remote sensing. GIS and MIF techniques. Geosci. Frontiers 2012, 3(2):189-196.
37. Manap M.A., Nampak H., Pradhan B., Lee S., Sulaiman W.N.A., Ramli M.F. Application of probabilistic-based frequency ratio model in groundwater potential mapping using remote sensing data and GIS. Arab. J. Geosci. 2012, 1-14. 10.1007/s12517-012-0795-z.
38. Manap M.A., Sulaiman W.N.A., Ramli M.F., Pradhan B., Surip N. A knowledge-driven GIS modeling technique for groundwater potential mapping at the Upper Langat Basin, Malaysia. Arab. J. Geosci. 2013, 6(5):1621-1637. 10.1007/s12517-011-0469-2.
39. 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.
40. Moon W.M. Integration of geophysical and geological data using evidential belief function. IEEE Trans. Geosci. Remote Sens. 1990, 28(4):711-720.
41. Moore I.D., Grayson R.B., Ladson A.R. Digital terrain modelling: a review of hydrological, geomorphological, and biological applications. Hydrol. Proc. 1991, 5(1):3-30.
42. Mukherjee S. Targetting saline aquifer by remote sensing and geophysical methods in a part of Hamirpur-Kanpur, India. Hydrol. J. 1996, 19:1867-1884.
43. Murthy K.S.R., Mamo A.G. Multi-criteria decision evaluation in groundwater zones identification in Moyale-Teltele sub-basin, South Ethiopia. Int. J. Remote Sens. 2009, 30(11):2729-2740.
44. Nag, A., Ghosh, S., Biswas, S., Sarkar, D., Sarkar, P.P., 2012. An image steganography technique using X-box mapping. In: Advances in Engineering, Science and Management (ICAESM), 2012 International Conference on pp. 709-713. IEEE.
45. Neshat A., Pradhan B., Pirasteh S., Shafri H.Z.M. Estimating groundwater vulnerability to pollution using a modified DRASTIC model in the Kerman agricultural area, Iran. Environ. Earth Sci. 2013, 1-13. 10.1007/s12665-013-2690-7.
46. Oh H.J., Kim Y.S., Choi J.K., Park E., Lee S. GIS mapping of regional probabilistic groundwater potential in the area of Pohang City, Korea. J. Hydrol. 2011, 399(3):158-172.
47. Ozdemir A. Using a binary logistic regression method and GIS for evaluating and mapping the groundwater spring potential in the Sultan Mountains (Aksehir, Turkey). J. Hydrol. 2011, 405(1):123-136.
48. Park N.W. Application of Dempster-Shafer theory of evidence to GIS-based landslide susceptibility analysis. Environ. Earth Sci. 2011, 62(2):367-376.
49. Pradhan B. Groundwater potential zonation for basaltic watersheds using satellite remote sensing data and GIS techniques. Cent. Eur. J. Geosci. 2009, 1(1):120-129.
50. 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. 2013, 51:350-365. 10.1016/j.cageo.2012.08.023.
51. Pradhan B., Abokharima M.H., Jebur M.N., Tehrany M.S. Land subsidence susceptibility mapping at Kinta Valley (Malaysia) using the evidential belief function model in GIS. Nat. Hazards 2014, 1-24. 10.1007/s11069-014-1128-1.
52. Pradhan B., Oh H.J., Buchroithner M. Weights-of-evidence model applied to landslide susceptibility mapping in a tropical hilly area. Geomat. Nat. Haz. Risk 2010, 1(3):199-223.
53. Pradhan B., Lee S. Regional landslide susceptibility analysis using back-propagation neural network model at Cameron Highland, Malaysia. Landslides 2010, 7(1):13-30.
54. Prasad R.K., Mondal N.C., Banerjee P., Nandakumar M.V., Singh V.S. Deciphering potential groundwater zone in hard rock through the application of GIS. Environ. Geol. 2008, 55(3):467-475.
55. Sander P., Chesley M.M., Minor T.B. Groundwater assessment using remote sensing and GIS in a rural groundwater project in Ghana: lessons learned. Hydrogeol. J. 1996, 4(3):40-49.
56. Saraf A.K., Choudhury P.R. Integrated remote sensing and GIS for groundwater exploration and identification of artificial recharge sites. Int. J. Remote Sens. 1998, 19(10):1825-1841.
57. Shafer G. A Mathematical Theory of Evidence 1976, vol. 1. Princeton University Press, Princeton.
58. Shahid S., Nath S.K., Kamal A.S.M.M. GIS integration of remote sensing and topographic data using fuzzy logic for ground water assessment in Midnapur District, India. Geocarto Int. 2002, 17(3):69-74.
59. Singh, A.K., Prakash, S.R., 2002. An integrated approach of remote sensing, geophysics and GIS to evaluation of groundwater potentiality of Ojhala sub-watershed, Mirjapur district, UP, India. In: Asian Conference on GIS, GPS, Aerial Photography and Remote Sensing, Bangkok-Thailand.
60. Suratman S. IWRM: Managing the Groundwater Component 2004, Paper presented at Malaysia Water Forum, Kuala Lumpur, Malaysia.
61. Tehrany M.S., Pradhan B., Jebur M.N. Spatial prediction of flood susceptible areas using rule based decision tree (DT) and a novel ensemble bivariate and multivariate statistical models in GIS. J. Hydrol. 2013, 504:69-79.
62. Tehrany M.S., Pradhan B., Jebur M.N. Flood susceptibility mapping using a novel ensemble weights-of-evidence and support vector machine models in GIS. J. Hydrol. 2014, 512:332-343. 10.1016/j.jhydrol.2014.03.008.
63. Thakur G.S., Raghuwanshi R.S. Perspect and assessment of groundwater resources using remote sensing techniques in and around Choral river basin, Indore and Khargone districts, MP. J. Indian Soc. Remote Sens. 2008, 36(2):217-225.
64. Umar Z., Pradhan B., Ahmad A., Jebur M.N., Tehrany M.S. Earthquake induced landslide susceptibility mapping using an integrated ensemble frequency ratio and logistic regression models in West Sumatera Province, Indonesia. Catena 2014, 118:124-135. 10.1016/j.catena.2014.02.005.
65. Yin E.H. Geologic map of Selangor, Sheet 94 (Kuala Lumpur). Scale 1976, 1:63360.