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A GIS-based comparative study of frequency ratio, statistical index and weights-of-evidence models in landslide susceptibility mapping

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Abstract

The aim of this study is to generate reliable susceptibility maps using frequency ratio (FR), statistical index (SI), and weights-of-evidence (WoE) models based on geographic information system (GIS) for the Qianyang County of Baoji City, China. At first, landslide locations were identified by earlier reports, aerial photographs, and field surveys, and a total of 81 landslides were mapped from various sources. Then, the landslide inventory was randomly split into a training dataset 70 % (56 landslides) for training the models, and the remaining 30 % (25 landslides) was used for validation purpose. In this case study, 13 landslide-conditioning factors were exploited to detect the most susceptible areas. These factors are slope angle, slope aspect, curvature, plan curvature, profile curvature, altitude, distance to faults, distance to rivers, distance to roads, Sediment Transport Index (STI), Stream Power Index (SPI), Topographic Wetness Index (TWI), and lithology. Subsequently, landslide-susceptible areas were mapped using the FR, SI, and WoE models based on landslide-conditioning factors. Finally, the accuracy of the landslide susceptibility maps produced from the three models was verified by using areas under the curve (AUC). The AUC plot estimation results showed that the susceptibility map using FR model has the highest training accuracy of 83.62 %, followed by the SI model (83.45 %), and the WoE model (82.51 %). Similarly, the AUC plot showed that the prediction accuracy of the three models was 79.40 % for FR model, 79.35 % for SI model, and 78.53 % for WoE model, respectively. According to the validation results of the AUC evaluation, the map produced by FR model exhibits the most satisfactory properties.

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References

  • Akgun A (2012) A comparison of landslide susceptibility maps produced by logistic regression, multi-criteria decision, and likelihood ratio methods: a case study at Izmir, Turkey. Landslides 9:93–106

    Article  Google Scholar 

  • Akgun A, Turk N (2010) Landslide susceptibility mapping for Ayvalik (Western Turkey) 379 and its vicinity by multicriteria decision analysis. Environ Earth Sci 61(3):595–611

    Article  Google Scholar 

  • Akgun A, Kincal C, Pradhan B (2012a) Application of remote sensing data and GIS for landslide risk assessment as an environmental threat to Izmir city (West Turkey). Environ Monit Assess 184:5453–5470

    Article  Google Scholar 

  • Akgun A, Sezer EA, Nefeslioglu HA, Gokceoglu C, Pradhan B (2012b) An easy-to-use MATLAB program (MamLand) for the assessment of landslide susceptibility using a Mamdani fuzzy algorithm. Comput Geosci 38(1):23–34

    Article  Google Scholar 

  • Aleotti P, Chowdhury R (1999) Landslide hazard assessment: summary review and new perspectives. Bull Eng Geol Environ 58(1):21–44

    Article  Google Scholar 

  • Baeza C, Corominas J (2001) Assessment of shallow landslide susceptibility by means of multivariate statistical techniques. Earth Surf Process Landf 26:1251–1263

    Article  Google Scholar 

  • Bathrellos GD, Kalivas DP, Skilodimou HD (2009) GIS-based landslide susceptibility mapping models applied to natural and urban planning in Trikala, Central Greece. Estud Geol 65(1):49–65

    Article  Google Scholar 

  • Bathrellos GD, Gaki-Papanastassiou K, Skilodimou HD, Papanastassiou D, Chousianitis KG (2012) Potential suitability for urban planning and industry development by using natural hazard maps and geological—geomorphological parameters. Environ Earth Sci 66(2):537–548

    Article  Google Scholar 

  • Bathrellos GD, Gaki-Papanastassiou K, Skilodimou HD, Skianis GA, Chousianitis KG (2013) Assessment of rural community and agricultural development using geomorphological—geological factors and GIS in the Trikala prefecture (Central Greece). Stoch Env Res Risk A 27(2):573–588

    Article  Google Scholar 

  • Bourenane H, Bouhadad Y, Guettouche MS, Braham M (2015) GIS-based landslide susceptibility zonation using bivariate statistical and expert approaches in the city of Constantine (Northeast Algeria). Bull Eng Geol Environ 74(2):337–355

    Article  Google Scholar 

  • Bui DT, 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

    Article  Google Scholar 

  • C.H. of China geological environment information sit (CIGEM) (2014) http://www.cigem.gov.cn/

  • C.H. of China Meteorological Administration(CMA) (2014) http://cdc.cma.gov.cn/cdc_en/home.dd

  • Catani F, Lagomarsino S, Segoni S, Tofani V (2013) Landslide susceptibility estimation by random forests technique: sensitivity and scaling issues. Nat Hazards Earth Syst Sci 13:2815–2831

    Article  Google Scholar 

  • Cevik E, Topal T (2003) GIS-based landslide susceptibility mapping for a problematic segment of the natural gas pipeline, Hendek (Turkey). Environ Geol 44:949–962

    Article  Google Scholar 

  • Chung CJF, Fabbri AG (2003) Validation of spatial prediction models for landslide hazard mapping. Nat Hazards 30(3):451–472

    Article  Google Scholar 

  • Clerici A, Perego S, Tellini C, Vescovi P (2002) A procedure for landslide susceptibility zonation by the conditional analysis method. Geomorphology 48:349–364

    Article  Google Scholar 

  • Clerici A, Perego S, Tellini C, Vescovi P (2006) A GIS-based automated procedure for landslide susceptibility mapping by the conditional analysis method: the Baganza valley case study (Italian Northern Apennines). Environ Geol 50:941–961

    Article  Google Scholar 

  • Conforti M, Aucelli PP, Robustelli G, Scarciglia F (2011) Geomorphology and GIS analysis for mapping gully erosion susceptibility in the Turbolo stream catchment (Northern Calabria, Italy). Nat Hazards 56(3):881–898

    Article  Google Scholar 

  • Dahal RK, Hasegawa S, Nonomura A, Yamanaka M, Masuda T, Nishino K (2008) GIS-based weights-of-evidence modelling of rainfall-induced landslides in small catchments for landslide susceptibility mapping. Environ Geol 54(2):311–324

    Article  Google Scholar 

  • Demir G, Aytekin M, Akgun A (2015) Landslide susceptibility mapping by frequency ratio and logistic regression methods: an example from Niksar-Resadiye (Tokat, Turkey). Arab J Geosci 8(3):1801–1812

    Article  Google Scholar 

  • Devkota KC, Regmi AD, Pourghasemi HR, Yoshida K, Pradhan B, Ryu IC, Dhital MR, Althuwaynee OF (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

    Article  Google Scholar 

  • Donati L, Turrini MC (2002) 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 63:277–289

    Article  Google Scholar 

  • Ercanoglu M, Gokceoglu C, van Asch TWJ (2004) Landslide susceptibility zoning north of Yenice (NW Turkey) by multivariate statistical techniques. Nat Hazards 32:1–23

    Article  Google Scholar 

  • Fell R, Corominas J, Bonnard C, Cascini L, Leroi E, Savage W (2008) Guidelines for landslide susceptibility, hazard and risk zoning for land use planning. Eng Geol 102:85–98

    Article  Google Scholar 

  • Grozavu A, Plescan S, Patriche CV, Margarint MC, Rosca B (2013) Landslide Susceptibility Assessment: GIS Application to a Complex Mountainous Environment. The Carpathians: Integrating Nature and Society Towards Sustainability. Environ Sci Eng, pp 31–44

  • Guettouche MS (2013) Modeling and risk assessment of landslides using fuzzy logic. Application on the slopes of the Algerian tell (Algeria). Arab J Geosci 6:3163–3173

    Article  Google Scholar 

  • Jaupaj O, Lateltin O, Lamaj M (2014). Landslide Susceptibility of Kavaja, Albania. In Landslide Science for a Safer Geoenvironment pp. 351–356

  • Jibson WR, Edwin LH, John AM (2000) A method for producing digital probabilistic seismic landslide hazard maps. Eng Geol 58:271–289

    Article  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, East Nepal. Arab J Geosci. doi:10.1007/s12517-015-1831-6

    Google Scholar 

  • Kayastha P, Dhital MR, De Smedt F (2013) Application of analytical hierarchy process (AHP) for landslidesusceptibility mapping: a case study from the Tinau watershed, west Nepal. Comput Geosci 52:398–408

    Article  Google Scholar 

  • Kouli M, Loupasakis C, Soupios P, Rozos D, Vallianatos F (2014) Landslide susceptibility mapping by comparing the WLC and WofE multi-criteria methods in the West Crete Island, Greece. Environ Earth Sci 72(12):5197–5219

    Article  Google Scholar 

  • Kundu S, Saha AK, Sharma DC, Pant CC (2013) Remote sensing and GIS based landslide susceptibility assessment using binary logistic regression model: a case study in the Ganeshganga watershed, Himalayas. J Indian Soc Remote Sens 41(3):697–709

    Article  Google Scholar 

  • Lee S, Choi U (2003) Development of GIS-based geological hazard information system and its application for landslide analysis in Korea. Geosci J 7:243–252

    Article  Google Scholar 

  • Lee S, Min K (2001) Statistical analysis of landslide susceptibility at Youngin, Korea. Environ Geol 40:1095–1113

    Article  Google Scholar 

  • Lee S, Talib JA (2005) Probabilistic landslide susceptibility and factor effect analysis. Environ Geol 47:982–990

    Article  Google Scholar 

  • Lee S, Choi J, Min K (2004a) Probabilistic landslide hazard mapping using GIS and remote sensing data at Boeun, Korea. Int J Remote Sens 25:2037–2052

    Article  Google Scholar 

  • Lee S, Ryu JH, Won JS, Park HJ (2004b) Determination and application of the weights for landslide susceptibility mapping using an artificial neural network. Eng Geol 71:289–302

    Article  Google Scholar 

  • Liu C, Li W, Wu H, Lu P, Sang K, Sun W, Chen W, Hong Y, Li R (2013) Susceptibility evaluation and mapping of China’s landslides based on multi-source data. Nat Hazards 69(3):1477–1495

    Article  Google Scholar 

  • Luzi L, Pergalani F, Terlien MTJ (2000) Slope vulnerability to earthquakes at subregional scale, using probabilistic techniques and geographic information systems. Eng Geol 58:313–336

    Article  Google Scholar 

  • Marjanović M, Kovačević M, Bajat B, Voženílek V (2011) Landslide susceptibility assessment using SVM machine learning algorithm. Eng Geol 123:225–234

    Article  Google Scholar 

  • Mihaela C, Martin B, Marta CJ, Marius V (2011) Landslide susceptibility assessment using the bivariate statistical analysis and the index of entropy in the Sibiciu Basin (Romania). Environ Earth Sci 63:397–406

    Article  Google Scholar 

  • Nefeslioglu HA, Duman TY, Durmaz S (2008) Landslide susceptibility mapping for a part of tectonic Kelkit Valley (Eastern Black Sea region of turkey). Geomorphology 94(3):401–418

    Article  Google Scholar 

  • Oh HJ, Lee S (2011) Landslide susceptibility mapping on Panaon Island, Philippines using a geographic information system. Environ Earth Sci 62(5):935–951

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Pareek N, Sharma ML, Arora MK (2010) Impact of seismic factors on landslide susceptibility zonation: a case study in part of Indian Himalayas. Landslides 7(2):191–201

    Article  Google Scholar 

  • Pareek N, Sharma ML, Arora MK, Pal S (2013) Inclusion of earthquake strong ground motion in a geographic information system-based landslide susceptibility zonation in Garhwal Himalayas. Nat Hazards 65(1):739–765

    Article  Google Scholar 

  • Parise M, Jibson WR (2000) A seismic landslide susceptibility rating of geologic units based on analysis of characteristics of landslides triggered by the 17 January, 1994 Northridge, California earthquake. Eng Geol 58:251–270

    Article  Google Scholar 

  • 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 68:1443–1464

    Article  Google Scholar 

  • Poudyal CP, Chang C, Oh HJ, Lee S (2010) Landslide susceptibility maps comparing frequency ratio and artificial neural networks: a case study from the Nepal Himalaya. Environ Earth Sci 61(5):1049–1064

    Article  Google Scholar 

  • Pourghasemi HR, Pradhan B, Gokceoglu C (2012) Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran. Nat Hazards 63:965–996

    Article  Google Scholar 

  • Pourghasemi HR, Jirandeh AG, Pradhan B, Xu C, Gokceoglu C (2013a) Landslide susceptibility mapping using support vector machine and GIS at the Golestan province, Iran. J Earth Syst Sci 122(2):349–369

    Article  Google Scholar 

  • Pourghasemi HR, Moradi HR, Fatemi Aghda SM (2013b) Landslide susceptibility mapping by binary logistic regression, analytical hierarchy process, and statistical index models and assessment of their performances. Nat Hazards 69:749–779

    Article  Google Scholar 

  • Pourghasemi HR, Pradhan B, Gokceoglu C, Deylami Moezzi K (2013c) A comparative assessment of prediction capabilities of Dempster-Shafer and weights-of-evidence models in landslide susceptibility mapping using GIS. Geomat, Nat Hazards Risk 4(2):93–118

    Article  Google Scholar 

  • Pourghasemi HR, Pradhan B, Gokceoglu C, Mohammadi M, Moradi HR (2013d) Application of weights-of-evidence and certainty factor models and their comparison in landslide susceptibility mapping at Haraz watershed, Iran. Arab J Geosci 6:2351–2365

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Pradhan B, Lee S (2010) Landslide susceptibility assessment and factor effect analysis: back-propagation artificial neural networks and their comparison with frequency ratio and bivariate logistic regression modeling. Environ Model Softw 25(6):747–759

    Article  Google Scholar 

  • Pradhan B, Youssef AM (2010) Manifestation of remote sensing data and GIS on landslide hazard analysis using spatial-based statistical models. Arab J Geosci 3(3):319–326

    Article  Google Scholar 

  • Pradhan B, Singh RP, Buchroithner MF (2006) Estimation of stress and its use in evaluation of landslide prone regions using remote sensing data. Adv Space Res 37:698–709

    Article  Google Scholar 

  • Pradhan B, Mansor S, Pirasteh S, Buchroithner M (2011) Landslide hazard and risk analyses at a landslide prone catchment area using statistical based geospatial model. Int J Remote Sens 32(14):4075–4087

    Article  Google Scholar 

  • Regmi AD, Devkota KC, Yoshida K, Pradhan B, Pourghasemi HR, Kumamoto T, Akgun A (2014) Application of frequency ratio, statistical index, and weights-of-evidence models and their comparison in landslide susceptibility mapping in Central Nepal Himalaya. Arab J Geosci 7(2):725–742

    Article  Google Scholar 

  • Rozos D, Bathrellos GD, Skilodimou HD (2011) Comparison of the implementation of rock engineering system (RES) and analytic hierarchy process (AHP) methods, based on landslide susceptibility maps, compiled in GIS environment. A case study from the Eastern Achaia County of Peloponnesus, Greece. Environ Earth Sci 63(1):49–63

    Article  Google Scholar 

  • Saha AK, Gupta RP, Sarkar I, Arora MK, Csaplovics E (2005) An approach for GIS-based statistical landslide susceptibility zonation with a case study in the Himalayas. Landslides 2:61–69

    Article  Google Scholar 

  • Sharma LP, Patel N, Ghose MK, Debnath P (2013) Synergistic application of fuzzy logic and geo-informatics for landslide vulnerability zonation—a case study in Sikkim Himalayas, India. Appl Geomat 5:271–284

    Article  Google Scholar 

  • Sujatha ER, Kumaravel P, Rajamanickam GV (2014) Assessing landslide susceptibility using Bayesian probability-based weight of evidence model. Bull Eng Geol Environ 73(1):147–161

    Article  Google Scholar 

  • Tay LT, Lateh H, Hossain MK, Kamil, AA (2014) Landslide Hazard Mapping Using a Poisson Distribution: A Case Study in Penang Island, Malaysia. In: Landslide Science for a Safer Geoenvironment (pp. 521–525). Springer International Publishing

  • Tunusluoglu MC, Gokceoglu C, Nefeslioglu HA, Sonmez H (2007) Extraction of potential debris source areas by logistic regression technique: a case study from Barla, Besparmak and Kapi mountains (NW Taurids, Turkey). Environ Geol 54:9–22

    Article  Google Scholar 

  • Van Westen CJ, Rengers N, Soeters R (2003) Use of geomorphological information in indirect landslide susceptibility assessment. Nat Hazards 30(3):399–419

    Article  Google Scholar 

  • Van Westen CJ, Van Asch TW, Soeters R (2006) Landslide hazard and risk zonation—why is it still so difficult? Bull Eng Geol Environ 65(2):167–184

    Article  Google Scholar 

  • Vijith H, Madhu G (2008) Estimating potential landslide sites of anupland sub-atershed in Western Ghat’s of Kerala (India) through frequency ratio and GIS. Environ Geol 55:1397–1405

    Article  Google Scholar 

  • Xu C, Dai FC, Xu X, Lee YH (2012a) GIS-based support vector machine modeling of earthquake-triggered landslide susceptibility in the Jianjiang River watershed, China. Geomorphology 145–146:70–80

    Article  Google Scholar 

  • Xu C, Xu XW, Dai FC, Saraf AK (2012b) Comparison of different models for susceptibility mapping of earthquake triggered landslides related with the 2008 Wenchuan earthquake in China. Comput Geosci 46:317–329

    Article  Google Scholar 

  • Yilmaz I (2009a) A case study from Koyulhisar (Sivas-Turkey) for landslide susceptibility mapping by artificial neural networks. Bull Eng Geol Environ 68(3):297–306

    Article  Google Scholar 

  • Yilmaz I (2009b) Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: a case study from Kat landslides (Tokat-Turkey). Comput Geosci 35(6):1125–1138

    Article  Google Scholar 

  • Yilmaz I (2010a) The effect of the sampling strategies on the landslide susceptibility mapping by conditional probability (CP) and artificial neural network (ANN). Environ Earth Sci 60:505–519

    Article  Google Scholar 

  • Yilmaz I (2010b) Comparison of landslide susceptibility mapping methodologies for Koyulhisar, Turkey: conditional probability, logistic regression, artificial neural networks, and support vector machine. Environ Earth Sci 61:821–836

    Article  Google Scholar 

  • Yilmaz C, Topal T, Suzen ML (2012) GIS-based landslide susceptibility mapping using bivariate statistical analysis in Devrek (Zonguldak-Turkey). Environ Earth Sci 65:2161–2178

    Article  Google Scholar 

  • Youssef AM, Pradhan B, Gaber AFD, Buchroithner MF (2009) Geomorphological hazard analysis along the Egyptian Red Sea coast between Safaga and Quseir. Nat Hazards Earth Syst Sci 9:751–766

    Article  Google Scholar 

  • Youssef AM, Pradhan B, Sabtan AA, El-Harbi HM (2012) Coupling of remote sensing data aided with fieldinvestigations for geological hazards assessment in Jazan area, Kingdom of Saudi Arabia. Environ Earth Sci 65(1):119–130

    Article  Google Scholar 

  • Youssef AM, Pradhan B, Al-Harthi SG (2014a) Assessment of rock slope stability and structurally controlled failures along Samma escarpment road, Asir Region (Saudi Arabia). Arab J Geosci. doi:10.1007/s12517-014-1719-x

    Google Scholar 

  • Youssef AM, Pradhan B, Sefry SA, Abu Abdullah MM (2014b) Use of geological and geomorphological parameters in potential suitability assessment for urban planning development at Wadi Al-Asla basin, Jeddah, Kingdom of Saudi Arabia. Arab J Geosci. doi:10.1007/s12517-014-1663-9

    Google Scholar 

  • Youssef AM, Pradhan B, Al-Kathery M, Bathrellos GD, Skilodimou HD (2015a) Assessment of rockfall hazard at Al-Noor Mountain, Makkah city (Saudi Arabia) using spatio-temporal remote sensing data and field investigation. J Afr Earth Sci 101:309–321

    Article  Google Scholar 

  • Youssef AM, Pradhan B, Jebur MN, El-Harbi HM (2015b) Landslide susceptibility mapping using ensemble bivariate and multivariate statistical models in Fayfa area, Saudi Arabia. Environ Earth Sci 73(7):3745–3761

    Article  Google Scholar 

  • Zhou CH, Lee CF, Li J, Xu ZW (2002) On the spatial relationship between landslides and causative factors on Lantau Island, Hong Kong. Geomorphology 43:197–207

    Article  Google Scholar 

Download references

Acknowledgments

The authors are thankful to two anonymous reviewers for their valuable comments which were very useful in bringing the manuscript into its present form.

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Authors and Affiliations

  1. School of Geology and Environment, Xi’an University of Science and Technology, Xi’an, 710054, China

    Wei Chen & Xueyang Sun

  2. School of Resources and Earth Science, China University of Mining and Technology, Xuzhou, 221116, China

    Huichan Chai & Qiqing Wang

  3. College of Architecture and Civil Engineering, Xi’an University of Science and Technology, Xi’an, 710054, China

    Xiao Ding

  4. Jiangxi Provincial Meteorological Observatory, Jiangxi Meteorological Bureau, Nanchang, 330046, China

    Haoyuan Hong

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  1. Wei Chen
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Chen, W., Chai, H., Sun, X. et al. A GIS-based comparative study of frequency ratio, statistical index and weights-of-evidence models in landslide susceptibility mapping. Arab J Geosci 9, 204 (2016). https://doi.org/10.1007/s12517-015-2150-7

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