GIS-based landslide susceptibility model considering effective contributing area for drainage time

References

• Aleotti P, Chowdhury R. 1999. Landslide hazard assessment: summary review and new perspectives. Bull Eng Geol Environ. 58:21–44.10.1007/s100640050066
   Google Scholar
• Ali G, Birkel C, Tetzlaff D, Soulsby C, McDonnell JJ, Tarolli P. 2014. A comparison of wetness indices for the prediction of observed connected saturated areas under contrasting conditions. Earth Surf Processes Landforms. 39:399–413.10.1002/esp.3506
   Web of Science ®Google Scholar
• Baeza C, Corominas J. 2001. Assessment of shallow landslide susceptibility by means of multivariate statistical techniques. Earth surf proc land. 26:1251–1263.
   Web of Science ®Google Scholar
• Barling RD, Moore ID, Grayson RB. 1994. A quasi-dynamic wetness index for characterizing the spatial distribution of zones of surface saturation and soil water content. Water Resour Res. 30:1029–1044.10.1029/93WR03346
   Web of Science ®Google Scholar
• Borga M, Dalla Fontana G, Cazorzi F. 2002. Analysis of topographic and climatic control on rainfall-triggered shallow landsliding using a quasi-dynamic wetness index. J Hydrol. 268:56–71.10.1016/S0022-1694(02)00118-X
   Web of Science ®Google Scholar
• Brocca L, Ponziani F, Moramarco T, Melone F, Berni N, Wagner W. 2012. Improving landslide forecasting using ASCAT-derived soil moisture data: a case study of the Torgiovannetto landslide in central Italy. Remote Sens. 4:1232–1244.10.3390/rs4051232
   Web of Science ®Google Scholar
• Carrara A, Cardinali M, Detti R, Guzzetti F, Pasqui V, Reichenbach P. 1991. GIS techniques and statistical models in evaluating landslide hazard. Earth Surf Processes Landforms. 16:427–445.10.1002/(ISSN)1096-9837
   Web of Science ®Google Scholar
• Chauhan S, Sharma M, Arora MK. 2010. Landslide susceptibility zonation of the Chamoli region, Garhwal Himalayas, using logistic regression model. Landslides. 7:411–423.10.1007/s10346-010-0202-3
   Web of Science ®Google Scholar
• Chirico GB, Grayson RB, Western AW. 2003. On the computation of the quasi-dynamic wetness index with multiple-flow-direction algorithms. Water Resour Res. 39:1115–1122.
   Web of Science ®Google Scholar
• Convertino M, Troccoli A, Catani F. 2013. Detecting fingerprints of landslide drivers: a MaxEnt model. J Geophys Res Earth Surf. 118:1367–1386.
   Web of Science ®Google Scholar
• Cooke RU, Doornkamp J. 1990. Geomorphology in environment management: a new introduction. Oxford: Oxford University Press.
   Google Scholar
• Dai FC, Lee CF. 2002. Landslide characteristics and slope instability modeling using GIS, Lantau Island, Hong Kong. Geomorphology. 42:213–228.
   Web of Science ®Google Scholar
• Elith J, Phillips SJ, Hastie T, Dudík M, Chee YE, Yates CJ. 2011. A statistical explanation of MaxEnt for ecologists. Diver Distrib. 17:43–57.10.1111/ddi.2010.17.issue-1
   Web of Science ®Google Scholar
• Ercanoglu M, Gokceoglu C. 2004. Use of fuzzy relations to produce landslide susceptibility map of a landslide prone area (West Black Sea Region, Turkey). Eng Geol. 75:229–250.10.1016/j.enggeo.2004.06.001
   Web of Science ®Google Scholar
• Fell R, Corominas J, Bonnard C, Cascini L, Leroi E, Savage WZ. 2008. Guidelines for landslide susceptibility, hazard and risk zoning for land-use planning. Eng Geol. 102:99–111.10.1016/j.enggeo.2008.03.014
   Web of Science ®Google Scholar
• Frattini P, Crosta G, Sosio R. 2009. Approaches for defining thresholds and return periods for rainfall-triggered shallow landslides. Hydrol Processes. 23:1444–1460.10.1002/hyp.v23:10
   Web of Science ®Google Scholar
• Gao H, Wood EF, Jackson TJ, Drusch M, Bindlish R. 2006. Using TRMM/TMI to retrieve surface soil moisture over the southern United States from 1998 to 2002. J Hydrometeorol. 7:23–38.10.1175/JHM473.1
   Web of Science ®Google Scholar
• Gökceoglu C, Aksoy H. 1996. Landslide susceptibility mapping of the slopes in the residual soils of the Mengen region (Turkey) by deterministic stability analyses and image processing techniques. Eng Geol. 44:147–161.10.1016/S0013-7952(97)81260-4
   Web of Science ®Google Scholar
• Grabs T, Seibert J, Bishop K, Laudon H. 2009. Modeling spatial patterns of saturated areas: A comparison of the topographic wetness index and a dynamic distributed model. J Hydrol. 373:15–23.10.1016/j.jhydrol.2009.03.031
   Web of Science ®Google Scholar
• Gritzner ML, Marcus WA, Aspinall R, Custer SG. 2001. Assessing landslide potential using GIS, soil wetness modeling and topographic attributes, Payette River, Idaho. Geomorphology. 37:149–165.10.1016/S0169-555X(00)00068-4
   Web of Science ®Google Scholar
• Guzzetti F, Carrara A, Cardinali M, Reichenbach P. 1999. Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study. Geomorphology. 31:181–216.10.1016/S0169-555X(99)00078-1
   Web of Science ®Google Scholar
• Hanley JA, McNeil BJ. 1982. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology. 143:29–36.10.1148/radiology.143.1.7063747
   PubMed Web of Science ®Google Scholar
• Hutchinson JN. 1989. General report: morphological and geotechnical parameters of landslides in relation to geology and hydrogeology: Proc 5th International Symposium on Landslides, Lausanne, 10–15 July, 1988, V1, P3–35. Publ Rotterdam: AA Balkema, 1988. In International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts (Vol. 26, No. 2, p. 88), Pergamon.
   Google Scholar
• Iida T. 1984. A hydrological method of estimation of the topographic effect on the saturated throughflow. Trans Jpn Geomorphol Union. 5:1–12.
   Google Scholar
• Jadda M, et al. 2009. Landslide susceptibility evaluation and factor effect analysis using probabilistic-frequency ratio model. Eur J Sci Res. 33:654–668.
   Google Scholar
• Jaynes ET. 1957. Information theory and statistical mechanics. Phys Rev. 106:620–630.10.1103/PhysRev.106.620
   Web of Science ®Google Scholar
• Jenks GF. 1967. The data model concept in statistical mapping. International Yearbook of Cartography. 7:186–190.
   Google Scholar
• Kayastha P. 2015. Landslide susceptibility mapping and factor effect analysis using frequency ratio in a catchment scale: a case study from Garuwa sub-basin. Arabian J Geosci. 8:8601–8613.10.1007/s12517-015-1831-6
   Web of Science ®Google Scholar
• Kayastha P, Dhital MR, De Smedt F. 2013. Evaluation of the consistency of landslide susceptibility mapping: a case study from the Kankai watershed in east Nepal. Landslides. 10:785–799.10.1007/s10346-012-0361-5
   Web of Science ®Google Scholar
• Kıncal C, Akgun A, Koca MY. 2009. Landslide susceptibility assessment in the Izmir (West Anatolia, Turkey) city center and its near vicinity by the logistic regression method. Environ Earth Sci. 59:745–756.10.1007/s12665-009-0070-0
   Web of Science ®Google Scholar
• Kirkby MJ, Chorley RJ. 1967. Throughflow, overland flow and erosion. Hydrol Sci J. 12:5–21.
   Google Scholar
• Korean Geotechnical Society. 2011. Research contract report: addition and complement causes survey of Mt. Woomyeon Landslide. Seoul: Koran Geotechnical Society; 268p.
   Google Scholar
• Korean Society of Civil Engineering. 2012. Research contract report: causes survey and restoration work of Mt. Woomyeon Landslide. Seoul: Korean Society of Civil Engineers; 435p.
   Google Scholar
• Lakhankar T, Ghedira H, Khanbilvardi R. 2006. Soil moisture retrieval from RADARSAT data: a Neuro-Fuzzy approach. Geoscience and remote sensing symposium, 2006. IGARSS 2006. IEEE international conference. IEEE; p. 2328–2331.
   Google Scholar
• Lee S, Pradhan B. 2006. Probabilistic landslide hazards and risk mapping on Penang Island. J Earth Syst Sci. 115:661–672.10.1007/s12040-006-0004-0
   Web of Science ®Google Scholar
• Lumb P. 1975. Slope failures in Hong Kong. Q J Eng Geol Hydrogeol. 8:31–65.10.1144/GSL.QJEG.1975.008.01.02
   Google Scholar
• Mahalingam R, Olsen MJ, O’Banion MS. 2016. Evaluation of landslide susceptibility mapping techniques using lidar-derived conditioning factors (Oregon case study). Geomat Nat Haz Risk. 7:1884–1907.
   Web of Science ®Google Scholar
• Mandal S, Maiti R. 2015. Impact assessment of hydrologic attributes and slope instability. In: Mandal S, Maiti R, editors. Semi-quantitative approaches for landslide assessment and prediction. Singapore: Springer; p. 95–121.10.1007/978-981-287-146-6
   Google Scholar
• Montgomery DR, Dietrich WE. 1994. A physically based model for the topographic control on shallow landsliding. Water Resour Res. 30:1153–1171.10.1029/93WR02979
   Web of Science ®Google Scholar
• O’Callaghan JF, Mark DM. 1984. The extraction of drainage networks from digital elevation data. Comput Vision Graphics Image Process. 28:323–344.10.1016/S0734-189X(84)80011-0
   Google Scholar
• O’Loughlin EM. 1986. Prediction of surface saturation zones in natural catchments by topographic analysis. Water Resour Res. 22:794–804.10.1029/WR022i005p00794
   Web of Science ®Google Scholar
• Oh HJ, Pradhan B. 2011. Application of a neuro-fuzzy model to landslide-susceptibility mapping for shallow landslides in a tropical hilly area. Comput Geosci. 37:1264–1276.10.1016/j.cageo.2010.10.012
   Web of Science ®Google Scholar
• Park NW. 2015. Using maximum entropy modeling for landslide susceptibility mapping with multiple geoenvironmental data sets. Environ Earth Sci. 73:937–949.10.1007/s12665-014-3442-z
   Web of Science ®Google Scholar
• Park DW, Nikhil NV, Lee SR. 2013. Landslide and debris flow susceptibility zonation using TRIGRS for the 2011 Seoul landslide event. Nat Hazards Earth Syst Sci. 13:2833–2849.10.5194/nhess-13-2833-2013
   Web of Science ®Google Scholar
• Penna D, Borga M, Aronica GT, Brigandì G, Tarolli P. 2014. The influence of grid resolution on the prediction of natural and road-related shallow landslides. Hydrol Earth Syst Sci. 18:2127–2139.10.5194/hess-18-2127-2014
   Web of Science ®Google Scholar
• Phillips SJ, Dudík M. 2008. Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation. Ecography. 31:161–175.10.1111/j.0906-7590.2008.5203.x
   Web of Science ®Google Scholar
• Phillips SJ, Anderson RP, Schapire RE. 2006. Maximum entropy modeling of species geographic distributions. Ecol Model. 190:231–259.10.1016/j.ecolmodel.2005.03.026
   Web of Science ®Google Scholar
• Pradhan AMS, Kang HS, Lee S, Kim YT. 2016. Spatial model integration for shallow landslide susceptibility and its runout using a GIS-based approach in Yongin, Korea. Geocarto Int. 32:420–441.
   Web of Science ®Google Scholar
• Pradhan AMS, Kim YT. 2015. Relative effect method of landslide susceptibility zonation in weathered granite soil: a case study in Deokjeok-ri Creek, South Korea. Nat Hazard. 72:1189–1217.
   Web of Science ®Google Scholar
• Pradhan AMS, Kim YT. 2016. Spatial data analysis and application of evidential belief functions to shallow landslide susceptibility mapping at Mt. Umyeon, Seoul, Korea. Bull Eng Geol Environ. doi:10.1007/s10064-016-0919-x
   Web of Science ®Google Scholar
• Ray RL, Jacobs JM. 2007. Relationships among remotely sensed soil moisture, precipitation and landslide events. Nat Hazards. 43:211–222.10.1007/s11069-006-9095-9
   Web of Science ®Google Scholar
• Reneau SL, Dietrich WE. 1987. The importance of hollows in debris flow studies; examples from Marin County, California. Rev Eng Geol. 7:165–180.10.1130/REG7
   Google Scholar
• Skilling J. 1988. The axioms of maximum entropy. In: Erickson GJ, Smith CR, editors. Maximum-entropy and bayesian methods in science and engineering. Dordrecht: Springer; p. 173–187.
   Google Scholar
• Soeters R, van Westen CJ. 1996. Slope instability recognition, analysis and zonation. Landslides, investigation and mitigation. Trans Res Board Nat Res Counc., Special Report. 247:129–177.
   Google Scholar
• Swets JA. 1988. Measuring the accuracy of diagnostic systems. Science. 240:1285–1293.10.1126/science.3287615
   PubMed Web of Science ®Google Scholar
• Tarolli P, Borga M, Chang KT, Chiang SH. 2011. Modeling shallow landsliding susceptibility by incorporating heavy rainfall statistical properties. Geomorphology. 133:199–211.10.1016/j.geomorph.2011.02.033
   Web of Science ®Google Scholar
• Tarolli P, Tarboton DG. 2006. A new method for determination of most likely landslide initiation points and the evaluation of digital terrain model scale in terrain stability mapping. Hydrol Earth Syst Sci. 10:663–677.10.5194/hess-10-663-2006
   Web of Science ®Google Scholar
• Van Westen CJ. 2000. The modelling of landslide hazards using GIS. Surv Geophys. 21:241–255.10.1023/A:1006794127521
   Web of Science ®Google Scholar
• Van Westen CJ. 2004. Geo-information tools for landslide risk assessment: an overview of recent developments. In: Lacerda WA, Ehrlich M, Fontoura SAB, Sayao ASF, editors. Proceedings 9th international symposium on landslides. Balkema; p. 39–56.
   Google Scholar
• Varnes DJ. 1984. Landslide hazard zonation: a review of principles and practice (No 3). Paris: UNESCO.
   Google Scholar
• Vasu NN, Lee SR. 2016. A hybrid feature selection algorithm integrating an extreme learning machine for landslide susceptibility modeling of Mt. Woomyeon. Geomorphology. 263:50–70.10.1016/j.geomorph.2016.03.023
   Web of Science ®Google Scholar
• Westen CJ, Terlien MJT. 1996. An approach towards deterministic landslide hazard analysis in GIS. A Case study from Manizales (Colombia). Earth Surf Processes Landforms. 21:853–868.10.1002/(ISSN)1096-9837
   Web of Science ®Google Scholar
• Yalcin A. 2008. GIS-based landslide susceptibility mapping using analytical hierarchy process and bivariate statistics in Ardesen (Turkey): Comparisons of results and confirmations. Catena. 72:1–12.10.1016/j.catena.2007.01.003
   Web of Science ®Google Scholar
• Yalcin A, Bulut F. 2007. Landslide susceptibility mapping using GIS and digital photogrammetric techniques: a case study from Ardesen (NE-Turkey). Nat Hazard. 41:201–226.10.1007/s11069-006-9030-0
   Web of Science ®Google Scholar