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Review

Mapping debris flow susceptibility based on watershed unit and grid cell unit: a comparison study

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Pages 1648-1666 | Received 31 May 2018, Accepted 25 Mar 2019, Published online: 24 Jun 2019

Reference

  • Alvioli M, Marchesini I, Reichenbach P, Rossi M, Ardizzone F, Fiorucci F, Guzzetti F. 2016. Automatic delineation of geomorphological slope units with r.slopeunits v1.0 and their optimization for landslide susceptibility modeling. Geosci Model Dev. 9:3975–3991.
  • 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(1–2):15–31.
  • Blais-Stevens A, Behnia P. 2016. Debris flow susceptibility mapping using a qualitative heuristic method and Flow-R along the Yukon Alaska Highway Corridor, Canada. Nat Hazards Earth Syst Sci. 16(2):449–462.
  • Bregoli F, Medina V, Chevalier G, Hürlimann M, Bateman A. 2015. Debris-flow susceptibility assessment at regional scale: validation on an alpine environment. Landslides. 12(3):437–454.
  • Cama M, Conoscenti C, Lombardo L, Rotigliano E. 2016. Exploring relationships between grid cell size and accuracy for debris-flow susceptibility models: a test in the Giampilieri catchment (Sicily, Italy). Environ Earth Sci. 75 (3), 1–21.
  • Camilo DC, Lombardo L, Mai PM, Dou J, Huser R. 2017. Handling high predictor dimensionality in slope-unit-based landslide susceptibility models through LASSO-penalized Generalized Linear Model. Environ Model Soft. 97:145–156.
  • Cao C, Xu P, Wang Y, Chen J, Zheng L, Niu C. 2016. Flash flood hazard susceptibility mapping using frequency ratio and statistical index methods in Coalmine subsidence areas. Sustainability. 8(9), 948.
  • Chang M, Tang C, Zhang D-D, Ma G-C. 2014. Debris flow susceptibility assessment using a probabilistic approach: a case study in the Longchi area, Sichuan province, China. J Mt Sci. 11(4):1001–1014.
  • Chang TC, Chao RJ. 2006. Application of back-propagation networks in debris flow prediction. Eng Geol. 85(3/4):270–280.
  • Chevalier GG, Medina V, Hürlimann M, Bateman A. 2013. Debris-flow susceptibility analysis using fluvio-morphological parameters and data mining: application to the Central-Eastern Pyrenees. Nat Hazards. 67(2):213–238.
  • Dieu TB, Lofman O, Revhaug I, Dick O. 2011. Landslide susceptibility analysis in the Hoa Binh province of Vietnam using statistical index and logistic regression. Nat Hazards. 59:1413–1444.
  • Elkadiri R, Sultan M, Youssef AM, Elbayoumi T, Chase R, Bulkhi AB, Al-Katheeri MM. 2014. A remote sensing-based approach for debris-flow susceptibility assessment using artificial neural networks and logistic regression modeling. IEEE J Sel Top Appl Earth Observ Remote Sensing. 7(12):4818–4835.
  • Erener A, Düzgün H. 2012. Landslide susceptibility assessment: What are the effects of mapping unit and mapping method? Environ Earth Sci. 66(3):859–877.
  • Faria Lima Lopes LDC, Prado Bacellar LDA, Amorim Castro P. 2016. Assessment of the debris-flow susceptibility in tropical mountains using clast distribution patterns. Geomorphology. 275:16–25.
  • Feizizadeh B, Blaschke T. 2013. GIS-multicriteria decision analysis for landslide susceptibility mapping: comparing three methods for the Urmia lake basin, Iran. Nat Hazards. 65(3):2105–2128.
  • Gf B-C. 1994. Geographic information systems for geoscientists-modeling with GIS.Pergamon Press, Oxford,p 398.
  • Giannecchini R, Naldini D, Avanzi GDA, Puccinelli A. 2007. Modelling of the initiation of rainfall-induced debris flows in the Cardoso basin (Apuan Alps, Italy). Quater Int. 171-72:108–117.
  • Greco R, Sorriso-Valvo M, Catalano E. 2007. Logistic Regression analysis in the evaluation of mass movements susceptibility: The Aspromonte case study, Calabria, Italy. Eng Geol. 89(1-2):47–66.
  • Guo-Liang D, Zhang Y-S, Iqbal J, Yang Z-h, Yao X. 2017. Landslide susceptibility mapping using an integrated model of information value method and logistic regression in the Bailongjiang watershed, Gansu Province, China. J Mt Sci. 14:249–268.
  • Guzzetti F, Reichenbach P, Ardizzone F, Cardinali M, Galli M. 2006. Estimating the quality of landslide susceptibility models. Geomorphology. 81(1–2):166–184.
  • Hong H, Pradhan B, Xu C, Tien Bui D. 2015. Spatial prediction of landslide hazard at the Yihuang area (China) using two-class kernel logistic regression, alternating decision tree and support vector machines. CATENA. 133:266–281.
  • Horton P, Jaboyedoff M, Rudaz B, Zimmermann M. 2013. Flow-R, a model for susceptibility mapping of debris flows and other gravitational hazards at a regional scale. Nat Hazards Earth Syst Sci. 13(4):869–885.
  • Jadda M, Shafri HZM, Mansor SB. 2011. PFR model and GiT for landslide susceptibility mapping: a case study from Central Alborz, Iran. Nat Hazards. 57(2):395–412.
  • Jia N, Mitani Y, Xie M, Djamaluddin I. 2012. Shallow landslide hazard assessment using a three-dimensional deterministic model in a mountainous area. Comput Geotech. 45:1–10.
  • Jiang W, Rao P, Cao R, Tang Z, Chen K. 2017. Comparative evaluation of geological disaster susceptibility using multi-regression methods and spatial accuracy validation. J Geogr Sci. 27(4):439–462.
  • Kappes MS, Malet JP, Remaitre A, Horton P, Jaboyedoff M, Bell R. 2011. Assessment of debris-flow susceptibility at medium-scale in the Barcelonnette Basin, France. Nat Hazards Earth Syst Sci. 11(2):627–641.
  • Kritikos T, Davies T. 2015. Assessment of rainfall-generated shallow landslide/debris-flow susceptibility and runout using a GIS-based approach: application to western Southern Alps of New Zealand. Landslides. 12(6):1051–1075.
  • Lee S, Pradhan B. 2007. Landslide hazard mapping at Selangor, Malaysia using frequency ratio and logistic regression models. Landslides. 4(1):33–41.
  • Lee S, Ryu J-H, Kim I-S. 2007. Landslide susceptibility analysis and its verification using likelihood ratio, logistic regression, and artificial neural network models: case study of Youngin, Korea. Landslides. 4(4):327–338.
  • Lee S, Talib JA. 2005. Probabilistic landslide susceptibility and factor effect analysis. Environ Geol. 47(7):982–990.
  • Li Y, Wang H, Chen J, Shang Y. 2017. Debris Flow Susceptibility Assessment in the Wudongde Dam Area, China Based on Rock Engineering System and Fuzzy C-Means Algorithm. WATER. 9(9), 669.
  • Lin PS, Lin JY, Hung JC, Yang MD. 2002. Assessing debris-flow hazard in a watershed in Taiwan. Eng Geol. 66(3-4):295–313.
  • Lombardo L, Opitz T, Huser R. 2018. Point process-based modeling of multiple debris flow landslides using INLA: an application to the 2009 Messina disaster. Stoch Environ Res Risk Assess. 32(7):2179–2198.
  • Oh H-J, 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.
  • Palamakumbure D, Flentje P, Stirling D. 2015. Consideration of optimal pixel resolution in deriving landslide susceptibility zoning within the Sydney Basin, New South Wales, Australia. Comput Geosci. 82:13–22.
  • Park S, Choi C, Kim B, Kim J. 2013. Landslide susceptibility mapping using frequency ratio, analytic hierarchy process, logistic regression, and artificial neural network methods at the Inje area, Korea. Environ Earth Sci. 68(5):1443–1464.
  • Pastorello R, Michelini T, d’Agostino V. 2017. On the criteria to create a susceptibility map to debris flow at a regional scale using Flow-R (vol 14, pg 621, 2017). J Mt Sci. 14(5):1008–1008.
  • Regmi AD, Yoshida K, Pourghasemi HR, Dhital MR, Pradhan B. 2014. Landslide susceptibility mapping along Bhalubang - Shiwapur area of mid-Western Nepal using frequency ratio and conditional probability models. J Mt Sci. 11(5):1266–1285.
  • Rotigliano E, Cappadonia C, Conoscenti C, Costanzo D, Agnesi V. 2012. Slope units-based flow susceptibility model: using validation tests to select controlling factors. Nat Hazards. 61(1):143–153.
  • Rozos D, Skilodimou HD, Loupasakis C, Bathrellos GD. 2013. Application of the revised universal soil loss equation model on landslide prevention. An example from N. Euboea (Evia) Island, Greece. Environ Earth Sci. 70(7):3255–3266.
  • Shi M, Chen J, Song Y, Zhang W, Song S, Zhang X. 2016. Assessing debris flow susceptibility in Heshigten Banner, Inner Mongolia, China, using principal component analysis and an improved fuzzy C-means algorithm. Bull Eng Geol Environ. 75(3):909–922.
  • Van Den Eeckhaut M, Reichenbach P, Guzzetti F, Rossi M, Poesen J. 2009. Combined landslide inventory and susceptibility assessment based on different mapping units: an example from the Flemish Ardennes, Belgium. Nat Hazards Earth Syst Sci. 9(2):507–521.
  • Wang Q, Li W, Yan S, Wu Y, Pei Y. 2016. GIS based frequency ratio and index of entropy models to landslide susceptibility mapping (Daguan, China). Environ Earth Sci. 75:780.
  • Wang F, Xu P, Wang C, Wang N, Jiang N. 2017. Application of a GIS-Based Slope Unit Method for Landslide Susceptibility Mapping along the Longzi River, Southeastern Tibetan Plateau, China. ISPRS Int J Geo-Inform. 6(6), 172.
  • Xu W, Yu W, Jing S, Zhang G, Huang J. 2013. Debris flow susceptibility assessment by GIS and information value model in a large-scale region, Sichuan Province (China). Nat Hazards. 65(3):1379–1392.
  • 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):1–12.
  • Zezere JL, Pereira S, Melo R, Oliveira SC, Garcia R. 2017. Mapping landslide susceptibility using data-driven methods. Sci Total Environ. 589:250–267.
  • Zhang Z, Yang F, Chen H, Wu Y, Li T, Li W, Wang Q, Liu P. 2016. GIS-based landslide susceptibility analysis using frequency ratio and evidential belief function models. Environ Earth Sci. 75(11):948.