Landslide Hazard Zonation using Logistic Regression Model: The Case of Shafe and Baso Catchments, Gamo Highland, Southern Ethiopia

AGS (Australian Geomechanics Society) (2000) Landslide risk management concepts and guidelines. Australian Ge-omechanics Society, Sub- Committee on Landslide Risk Management. AustralianGeome 35:49–92 Althuwaynee OF, Pradhan B, Mahmud AR, Yusoff ZM (2012) Prediction of slope failures using bivariate statistical based index of entropy model. IEEE Colloquium Human Sci Eng (CHUSER). https://doi.org/10.1109/chuser.2012.6504340 Bewick V, Cheek L, Ball J (2003) Statistics review 7: correlation and regression. Crit Care 7:451. https://doi.org/10.1186/cc2401 Bewick V, Cheek L, Ball J (2005) Statistics review 14: Logistic regression. Critical Care (london, England) 9(1):112–118. https://doi.org/10.1186/cc3045 Bourenane H, Guettouche M, Bouhadad Y, Braham M (2016) Landslide hazard mapping in the Constantine city, Northeast Algeria using frequency ratio, weighting factor, logistic regression, weights of evidence, and analytical hierarchy process methods. Arabian J Geosci 9(2):1–24 Bradley AP (1997) The use of the area under the ROC curve in the evaluation of machine learning algorithms. Pattern Recogn 30(7):1145–1159. https://doi.org/10.1016/s0031-3203(96)00142-2 Chen J, King E, Deek R, Wei Z, Yu Y, Grill D, Ballman K (2018) An omnibus test for differential distribution analysis of microbiome sequencing data. Bioinformatics 34(4):643–651 Chen Z, Wang J (2007) Landslide hazard mapping using logistic regression model in Mackenzie Valley. Canada Nat Hazards 42(1):75–89. https://doi.org/10.1007/s11069-006-9061-6 Cheng S, Wang YS, Chen FY (2012) Geohazard risk assessment method based on logistic regression model. Adv Mater Res 588–589:1934–1937 Chung C-JF, Fabbri AG (2012) Systematic procedures of landslide hazard mapping for risk assessment using spatial prediction models. Landslide Hazard Risk. https://doi.org/10.1002/9780470012659.ch4 Corominas J, Moya J (2008) A review of assessing landslide frequency for hazard zoning purposes. Eng Geol 102(3–4):193–213. https://doi.org/10.1016/j.enggeo.2008.03.018 Corominas J, van Westen C, Frattini P et al (2014) Recommendations for the quantitative analysis of landslide risk. Bull Eng Geol Environ. https://doi.org/10.1007/s10064-013-0538-8 Dahal BK, Dahal RK (2017) Landslide hazard map: tool for optimization of low-cost mitigation. Geoenviron Disasters. https://doi.org/10.1186/s40677-017-0071-3 Dahal RK, Hasegawa S, Nonomura A, Yamanaka M, Masuda T, Nishino K (2007) GIS-based weights-of-evidence modelling of rainfall-induced landslides in small catchments for landslide susceptibility mapping. Environ Geol 54(2):311–324. https://doi.org/10.1007/s00254-007-0818-3 Dai F, Lee C, Ngai Y (2002) Landslide risk assessment and management: an overview. Eng Geol 64(1):65–87. https://doi.org/10.1016/s0013-7952(01)00093-x Davies T (2015) Landslide hazards, risks, and disasters. Landslide Hazards Risks Disasters. https://doi.org/10.1016/b978-0-12-396452-6.00001-x Devkota KC, Regmi AD, Pourghasemi HR et al (2013) Landslide susceptibility mapping using certainty factor, index of entropy and logistic regression models in GIS and their comparison at Mugling-Narayanghat road section in Nepal Himalaya. Nat Hazards 65(1):135–165. https://doi.org/10.1007/s11069-012-0347-6 Đurić U, Marjanović M, Radić Z, Abolmasov B (2019) Machine learning based landslide assessment of the Belgrade metropolitan area: pixel resolution effects and a cross-scaling concept. Eng Geol 256:23–38. https://doi.org/10.1016/j.enggeo.2019.05.007 Fawcett T (2005) An introduction to ROC analysis. Pattern Recogn Lett 27(8):861–874. https://doi.org/10.1016/j.patrec.2005.10.010 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, on behalf of the JTC-1 Joint Technical Committee on Landslides and Engineered Slopes. Eng Geol 102:85–98 Gariano SL, Petrucci O, Rianna G, Santini M, Guzzetti F (2018) Impacts of past and future land changes on landslides in southern Italy. Region Environ Change 18(2):437–449 Guthrie RH (2002) The effects of logging on frequency and distribution of landslides in three watersheds on Vancouver Island. Br Columbia Geomo 43(3–4):273–292 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. Central Italy Geomo 31(1–4):181–216 Guzzetti F, Reichenbach P, Ardizzone F, Cardinali M, Galli M (2006) Estimating the quality of landslide susceptibility models. Geomo 81(1–2):166–184. https://doi.org/10.1016/j.geomorph.2006.04.007 Guzzetti F, Reichenbach P, Cardinali M, Galli M, Ardizzone F (2005) Probabilistic landslide hazard assessment at the basin scale. Geomo 72(1–4):272–299. https://doi.org/10.1016/j.geomorph.2005.06.002 Hina S, Kawasaki A, Qasim M (2014) Landslide Susceptibility Analysis Using GIS and Logistic Regression Model A Case Study In Malang, Indonesia. Asian J Environ and Disas Manag (AJEDM) - Focusing on Pro-Active Risk Reduction in Asia 06(02):117–129. https://doi.org/10.3850/s1793924014000323 Hong H, Xu C, Bui DT (2015) Landslide susceptibility assessment at the Xiushui Area (China) using frequency ratio model. Procedia Earth Planet Sci 15:513–517. https://doi.org/10.1016/j.proeps.2015.08.065 Hosmer DW, Lemeshow S (2000). Appl Logist Regress. https://doi.org/10.1002/0471722146 Hosmer DW, Lemeshow S (2005) Logistic regression, conditional. Encyclop Biostat. https://doi.org/10.1002/0470011815.b2a10030 Kayastha P, Dhital MR, De Smedt F (2012) Evaluation of the consistency of landslide susceptibility mapping: a case study from the Kankai watershed in east Nepal. Landslides 10(6):785–799 Krzanowski WJ, Hand DJ (2009). ROC Curves for Contin Data. https://doi.org/10.1201/9781439800225 Lee C-T (2014) Multi-stage statistical landslide hazard analysis: rain-induced landslides. Landslide Sci Safer Geoenviron. https://doi.org/10.1007/978-3-319-04996-0_45 Lee S (2005) Application of logistic regression model and its validation for landslide susceptibility mapping using GIS and remote sensing data. Int J Rem Sens 26(7):1477–1491 Lee S, Pradhan B (2006) Landslide hazard mapping at Selangor, Malaysia using frequency ratio and logistic regression models. Landslides 4(1):33–41. https://doi.org/10.1007/s10346-006-0047-y Mandal S, Maiti R (2014) Application of analytical hierarchy process (AHP) and frequency ratio (FR) model in assessing landslide susceptibility and risk. Semi-Quant Approa Landslide Assess Predict. https://doi.org/10.1007/978-981-287-146-6_7 Mandal S, Mandal K (2018) Modeling and mapping landslide susceptibility zones using GIS based multivariate binary logistic regression (LR) model in the Rorachu river basin of eastern Sikkim Himalaya. India Model Earth Syst Environ 4(1):69–88. https://doi.org/10.1007/s40808-018-0426-0 Mathew J, Jha VK, Rawat GS (2007) Application of binary logistic regression analysis and its validation for landslide susceptibility mapping in part of Garhwal Himalaya. India Int J Rem Sens 28(10):2257–2275. https://doi.org/10.1080/01431160600928583 Mathew J, Jha VK, Rawat GS (2008) Landslide susceptibility zonation mapping and its validation in part of Garhwal Lesser Himalaya, India, using binary logistic regression analysis and receiver operating characteristic curve method. Landslides 6(1):17–26. https://doi.org/10.1007/s10346-008-0138-z Medwedeff WG, Clark MK, Zekkos D, West AJ (2020) Characteristic landslide distributions: an investigation of landscape controls on landslide size. Earth Planet Sci Lett 539:116203 Meten M, Bhandary NP, Yatabe R (2015) GIS-based frequency ratio and logistic regression modelling for landslide susceptibility mapping of Debre Sina area in central Ethiopia. J Mountain Sci 12(6):1355–1372 Midi H, Sarkar SK, Rana S (2010) Collinearity diagnostics of binary logistic regression model. J Interdiscip Math 13(3):253–267. https://doi.org/10.1080/09720502.2010.10700699 Mirnazari M, Javad J, Ahmad A et al (2014) Using frequency ratio method for spatial landslide prediction. Res J Appl Sci Eng Technol 7(15):3174–3180. https://doi.org/10.19026/rjaset.7.658 Nattino G, Pennell ML, Lemeshow S (2020) Rejoinder to “Assessing the goodness of fit of logistic regression models in large samples: A modification of the Hosmer-Lemeshow test.” Biometrics 76(2):575–577 Nefeslioglu HA, Duman TY, Durmaz S (2008) Landslide susceptibility mapping for a part of tectonic Kelkit Valley (Eastern Black Sea region of Turkey). Geomo 94(3–4):401–418 Nolasco-Javier D, Kumar L (2020) Landslide susceptibility assessment using binary logistic regression in Northern Philippines. ICL Contrib Landslide Disaster Risk Reduct. https://doi.org/10.1007/978-3-030-60227-7_20 Oštir K, Veljanovski T, Podobnikar T, Stančič Z (2003) Application of satellite remote sensing in natural hazard management: the Mount Mangart landslide case study. Int J Rem Sens 24(20):3983–4002 Othman AA, Gloaguen R, Andreani L, Rahnama M (2018) Improving landslide susceptibility mapping using morphometric features in the Mawat area, Kurdistan Region, NE Iraq: comparison of different statistical models. Geomo 319:147–160 Ozdemir A, Altural T (2013) A comparative study of frequency ratio, weights of evidence and logistic regression methods for landslide susceptibility mapping: Sultan Mountains, SW Turkey. J Asian Earth Sci 64:180–197 Paul P, Pennell ML, Lemeshow S (2013) Standardizing the power of the Hosmer-Lemeshow goodness of fit test in large data sets. Stat Med 32(1):67–80 Peng C-YJ, So T-SH (2002) Logistic regression analysis and reporting: a primer. Underst Stat. https://doi.org/10.1207/s15328031us0101_04 Pourghasemi HR, Pradhan B, Gokceoglu C, Mohammadi M, Moradi HR (2012) Application of weights-of-evidence and certainty factor models and their comparison in landslide susceptibility mapping at Haraz watershed. Iran Arab J Geosci 6(7):2351–2365. https://doi.org/10.1007/s12517-012-0532-7 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. https://doi.org/10.1016/j.cageo.2012.08.023 Pradhan B, Lee S (2009) Delineation of landslide hazard areas on Penang Island, Malaysia, by using frequency ratio, logistic regression, and artificial neural network models. Environ Earth Sci 60(5):1037–1054 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 Software 25(6):747–759. https://doi.org/10.1016/j.envsoft.2009.10.016 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 Rem Sens 32(14):4075–4087 Raghuvanshi TK, Negassa L, Kala PM (2015) GIS based Grid overlay method versus modeling approach—A comparative study for landslide hazard zonation (LHZ) in Meta Robi District of West Showa Zone in Ethiopia. Egypt J Rem Sens Space Sci 18(2):235–250 Rasyid AR, Bhandary N P, Yatabe R (2016) Performance of frequency ratio and logistic regression model in creating GIS based landslides susceptibility map at Lompobattang Mountain, Indonesia. Geoenviron Disasters. https://doi.org/10.1186/s40677-016-0053-x Reichenbach P, Rossi M, Malamud BD, Mihir M, Guzzetti F (2018) A review of statistically-based landslide susceptibility models. Earth-Sci Revi 180:60–91. https://doi.org/10.1016/j.earscirev.2018.03.001 Reid L, Page M (2003) Magnitude and frequency of landsliding in a large New Zealand catchment. Geomo 49(1–2):71–88. https://doi.org/10.1016/s0169-555x(02)00164-2 Remondo J, Bonachea J, Cendrero A (2005) A statistical approach to landslide risk modelling at basin scale: from landslide susceptibility to quantitative risk assessment. Landslides 2(4):321–328 Roy J, Saha S (2019) Landslide susceptibility mapping using knowledge driven statistical models in Darjeeling District, West Bengal, India. Geoenviron Disasters. https://doi.org/10.1186/s40677-019-0126-8 Shano L, Raghuvanshi TK, Meten M (2020) Landslide susceptibility evaluation and hazard zonation techniques—a review. Geoenviron Disas. https://doi.org/10.1186/s40677-020-00152-0 Shano L, Raghuvanshi TK, Meten M (2021) Landslide susceptibility mapping using frequency ratio model: the case of Gamo highland, South Ethiopia. Arabian J Geosci. https://doi.org/10.1007/s12517-021-06995-7 Sun X, Chen J, Bao Y, Han X, Zhan J, Peng W (2018) Landslide susceptibility mapping using logistic regression analysis along the Jinsha River and Its Tributaries Close to Derong and Deqin County, Southwestern China. ISPRS Int J Geo-Information. https://doi.org/10.3390/ijgi7110438 Talaei R (2014) Landslide susceptibility zonation mapping using logistic regression and its validation in Hashtchin Region, northwest of Iran. J Geol Soc India 84(1):68–86. https://doi.org/10.1007/s12594-014-0111-5 Tanyaş H, Allstadt KE, van Westen CJ (2018a) An updated method for estimating landslide-event magnitude. Earth Surf Proc Land 43(9):1836–1847 Tanyaş H, Westen CJ, Allstadt KE, Jibson RW (2018b) Factors controlling landslide frequency–area distributions. Earth Surf Proc Land 44(4):900–917. https://doi.org/10.1002/esp.4543 Tebbens SF (2020) Landslide scaling: a review. Earth Space Sci. https://doi.org/10.1029/2019ea000662 Thennavan E, Pattukandan Ganapathy G (2020) Evaluation of landslide hazard and its impacts on hilly environment of the Nilgiris District - a geospatial approach. Geoenviron Disasters. https://doi.org/10.1186/s40677-019-0139-3 Tien Bui D, Tuan TA, Klempe H, Pradhan B, Revhaug I (2015) Spatial prediction models for shallow landslide hazards: a comparative assessment of the efficacy of support vector machines, artificial neural networks, kernel logistic regression, and logistic model tree. Landslides 13(2):361–378 Tiranti D, Cremonini R (eds) (2019) Landslide hazard in a changing environment. Front Res Top. https://doi.org/10.3389/978-2-88945-793-9 Valenzuela P, Domínguez-Cuesta MJ, Mora García MA, Jiménez-Sánchez M (2017) A spatio-temporal landslide inventory for the NW of Spain: BAPA database. Geomo 293:11–23 Van Westen CJ, Castellanos E, Kuriakose SL (2008) Spatial data for landslide susceptibility, hazard, and vulnerability assessment: an overview. Eng Geol 102:112–131 Van Westen CJ, Lulie Getahun F (2003) Analyzing the evolution of the Tessina landslide using aerial photographs and digital elevation models. Geomo 54(1–2):77–89 Van Westen CJ, van Asch TWJ, Soeters R (2006) Landslide hazard and risk zonation—why is it still so difficult? Bull Eng Geol Environ 65(2):167–184. https://doi.org/10.1007/s10064-005-0023-0 Varnes D, IAEG (1984) Landslide hazard zonation: a review of principles and practice. U N Sci Cult Organ, Paris, pp 1–6 Wang J, Peng X (2009) GIS-based landslide hazard zonation model and its application. Procedia Earth Planet Sci 1(1):1198–1204. https://doi.org/10.1016/j.proeps.2009.09.184 Wubalem A, Meten M (2020) Landslide susceptibility mapping using information value and logistic regression models in Goncha Siso Eneses area, northwestern Ethiopia. SN Appl Sci. https://doi.org/10.1007/s42452-020-2563-0 Zhou C, Lee C, Li J, Xu Z (2002) On the spatial relationship between landslides and causative factors on Lantau Island. Hong Kong Geomo 43(3–4):197–207. https://doi.org/10.1016/s0169-555x(01)00130-1 Zumpano V, Pisano L, Malek Ž et al (2018) Economic losses for rural land value due to landslides. Front Earth Sci. https://doi.org/10.3389/feart.2018.00097