Abstract
The aim of this study is to produce a landslide susceptibility map in Mogods and Hedil using the fuzzy logic method. To increase the objectivity of the approach, the fuzzy membership was calculated using the frequency ratio (FR). Nine factors were considered for landslide control, including slope, aspect, plan curvature, profil curvature, distance from faults, distance from rivers, land use, precipitation, and lithology. The frequency ratio was used to calculate the fuzziness of each factor, and these results were then applied to the fuzzy operators to produce the landslide susceptibility map. The selection of the susceptibility map closest to reality was based on the spatial distribution of landslides in each susceptibility class of each fuzzy operator and on the application of the receiver operating curve (ROC). The results of the area under curve (AUC) analysis show that the GAMMA operator (0.90) provided the most accurate prediction of the landslide susceptibility map, as indicated by the prediction accuracy of the model (0.766). The study area was classified into four classes using Jenks natural fracture classification method: low susceptibility zone, moderate susceptibility zone, high susceptibility zone, and very high susceptibility zone. The use of the fuzzy GAMMA operator for landslide susceptibility map** gave a very satisfactory result with a reliability rate of 76.6%.
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs12518-023-00544-5/MediaObjects/12518_2023_544_Fig1_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs12518-023-00544-5/MediaObjects/12518_2023_544_Fig2_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs12518-023-00544-5/MediaObjects/12518_2023_544_Fig3_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs12518-023-00544-5/MediaObjects/12518_2023_544_Fig4_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs12518-023-00544-5/MediaObjects/12518_2023_544_Fig5_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs12518-023-00544-5/MediaObjects/12518_2023_544_Fig6_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs12518-023-00544-5/MediaObjects/12518_2023_544_Fig7_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs12518-023-00544-5/MediaObjects/12518_2023_544_Fig8_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs12518-023-00544-5/MediaObjects/12518_2023_544_Fig9_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs12518-023-00544-5/MediaObjects/12518_2023_544_Fig10_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs12518-023-00544-5/MediaObjects/12518_2023_544_Fig11_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs12518-023-00544-5/MediaObjects/12518_2023_544_Fig12_HTML.png)
Similar content being viewed by others
Data availability
The data presented in this study are available on request from the corresponding author.
References
Abdi A, Bouamrane A, Karech T et al (2021) Landslide susceptibility map** using GIS-based fuzzy logic and the analytical hierarchical processes approach: a case study in Constantine (North-East Algeria). Geotech Geol Eng 39:5675–5691. https://doi.org/10.1007/s10706-021-01855-3
Abdul Rahaman S, Aruchamy S (2017) Geoinformatics based landslide vulnerable zonation map** using analytical hierarchy process (AHP), a study of Kallar river sub watershed, Kallar watershed, Bhavani basin, Tamil Nadu. Model Earth Syst Environ 3:41
Akgun A, Sezer EA, Nefeslioglu HA, Gokceoglu C, Pradhan B (2012) An easy-to-use MATLAB program (MamLand) for the assessment of landslide susceptibility using a Mamdani fuzzy algorithm. Comput Geosci 38(1):23–34
Ayalew L, Yamagishi H (2005) The application of GIS-based logistic regression for landslide susceptibility map** in the Kakuda-Yahiko Mountains, Central Japan. Geomorphology 65:15–31
Ben Ayed N (1986) Evolution Tectonique de l’Avant-Pays de la Chaîne Alpine de Tunisie du Début du Mésozoïque à l’Actuel Thèse d’Etat; Université de Paris Sud—Centre d’Orsay: Gif-sur-Yvette, France, 1986
Benn JL (2005) Landslide events on the West Coast, South Island, 1867–2002. NZ Geogr 61:3–13. https://doi.org/10.1111/j.1745-7939.2005.00001.x
Bonham-Carter G (1994) Geographic information systems for geoscientists: modelling with GIS. Pergamon press, p 416
Carranza EJM, Hale M (2001) Geologically constrained fuzzy map** of gold mineralization potential, Baguio District, Philippines. Nat Resour Res 10(2):125–136
Carrara A (1983) Multivariate models for landslide hazard evaluation. Math Geol 15:403–426
Champati Ray PK, Dimri S, Lakhera RC et al (2007) Fuzzy-based method for landslide hazard assessment in active seismic zone of Himalaya. Landslides 4:101–111. https://doi.org/10.1007/s10346-006-0068-6
Chen RF, Chang KJ, Angelier J, Chan YC, Deffontaines B, Lee CT, Ming-Lang L (2006) Topographical changes revealed by high-resolution airborne LiDAR data: the 1999 Tsaoling landslide induced by the Chi-Chi earthquake. Eng Geol 88(3–4):160–172
Cheng Q, Agterberg FP (1999) Fuzzy weights of evidence method and its application in mineral potential map**. Nat Resour Res 8:27–35
Chung CF, Fabbri AG (2001) Prediction model for landslide hazard using a Fuzzy set Approach. In: M. Marchetti and V. Rivas (eds) Geomorphology and environmental impact assessment. Balkema, Rotterdam, pp. 31–47.
Chung CJF, Fabbri AG (2003) Validation of spatial prediction models for landslide hazard map**. Nat Hazards 30(3):451–472
Crampon N (1971) Etude géologique de la bordure des Mogods, du pays de Bizerte et du Nord des Hédils (Tunisie septentrionale). Thèse Nancy, p 522
Dahal RK, Hasegawa S, Nonomura A, Yamanaka M (2009) GIS-based landslide susceptibility map** for the 2006 Leyte landslide using generalized linear model. Landslides 6(1):17–26
Davies TR (2007) Potential for rock avalanche hazard at Franz Josef glacier village, Westland. Confidential report to west coast regional council. Natural Hazards Research Centre Dept of Geological Sciences University of Canterbury, New Zealand, p14.
Devkota KC, Regmi AD, Pourghasemi HR et al (2013) Landslide susceptibility map** 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 65:135–165. https://doi.org/10.1007/s11069-012-0347-6
Dhianaufal D, Kristyanto THW, Indra TL, Syahputra R (2018) Fuzzy logic method for landslide susceptibility map** in volcanic sediment area in Western Bogor. AIP Conf Proc 1:020190. https://doi.org/10.1063/1.5064187
El Aroui O (2016) Géomorphologie des mouvements de terrain en Kroumirie septentrionale Tunisie. Faculté des lettres des arts et des humanités de la Manouba
Emberger L (1955) Une classification biogéographique des climats. Rec Trav Lab Bot Géol Zool Fac Sc De Montpellier 7:3–43
Ercanoglu M, Gokceoglu C (2002) Assessment of landslide susceptibility for a landslide-prone area (north of Yenice, NW Turkey) by fuzzy approach. Environ Geol 41(6):720–730
Fatemi Aghda SM, Bagheri V, Razifard M (2018) Landslide susceptibility map** using fuzzy logic system and its influences on mainlines in Lashgarak Region, Tehran. Iran Geotech Geol Eng 36:915–937. https://doi.org/10.1007/s10706-017-0365-y
Fressard M (2013) Les glissements de terrain du Pays d’Auge continental (Normandie, France). Caractérisation, 22 cartographie, analyse spatiale et modélisation, Ph.D. Thesis of the University of Caen Basse-Normandie
Gupta RP, Sarkar S, Kanungo DP, Patra AK (2008) Landslide hazard zonation in Darjeeling Himalayas using logistic regression model. Landslides 5(4):489–506
Highland LM, Bobrowsky P, Kempthorne D, Myers Mark D (2008) The landslide handbook—A guide to understanding landslides: Reston, Virginia, U.S. Geological Survey Circular 1325, p 129
Ilanloo M (2011) A comparative study of fuzzy logic approach for landslide susceptibility map** using GIS: An experience of Karaj dam basin in Iran. Procedia Soc Behav Sci 19:668–676. https://doi.org/10.1016/j.sbspro.2011.05.184
Iovine G (2008) Mud-flow and lava-flow susceptibility and hazard map** through numerical modelling, GIS techniques, historical and geo-environmental analyses. In: Proceedings of the iEMSs 4th biennial meeting, international congress on environmental modelling ANS software: integrating sciences and information technology for environmental assessment and decision making (iEMSs2008), vol 3, pp 1447–1460
Jeanine K (2006) Le glissement de terrain. Informatique Et Sci 22:9–16
Jordan C, O’Connor E, Marchant A, Northmore A, Greenbaum D, McDonald A, Kovacik M, Ahmed R (2000) Rapid landslide susceptibility map** using RS and GIS modelling. In Proceedings of 14th International Conference on Applied Geologic Remote Sensing. Las Vegas, NV, pp 113–120
Kanungo DP, Arora MK, Sarkar S, Gupta RP (2006) A comparative study of conventional, ANN black box, fuzzy and combined neural and fuzzy weighting methods for landslide susceptibility zonation in Darjeeling Himalayas. Eng Geol 85(3–4):347–366
Karray MR (1977) L’extrémité nord-est de la dorsale tunisienne. Recherches géomorphologiques. Thèse 3ème cycle, Université Tunis, p 174. http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=12798891
Karray MR (2010) Sahel et Kairouanais septentrionaux et leurs abords montagneux (Tunisie orientale): étude géomorphologique. Thèse de Doctorat d‘état, Univ. Tunis I, 2 volumes, p 736
Kavzoglu T, Sahin EK, Colkesen I (2014) Landslide susceptibility map** using GIS-based multi-criteria decision analysis, support vector machines, and logistic regression. Landslides 11:425–439. https://doi.org/10.1007/s10346-013-0391-7
Klai A, Haddad R, Bouzid MK et al (2020) Landslide susceptibility map** by fuzzy gamma operator and GIS, a case study of a section of the national road n°11 linking Mateur to Béja (Nortshern Tunisia). Arab J Geosci 13:58. https://doi.org/10.1007/s12517-019-5029-1
Kujawski H (1969) Contribution à l’étude géologique de la région des Hedhil et du Béjaoua oriental. Ann Miner Géol Tunis (24):281
Lee S, Talib JA (2005) Probabilistic landslide susceptibility and factor effect analysis. Environ Geol 47:982–990. https://doi.org/10.1007/s00254-005-1228-z
Lee S, Ryu JH, Won JS, Park HJ (2004) Determination and application of the weights 422 for landslide susceptibility map** using an artificial neural network. Eng Geol 71:289–302
Lee S, Ryu JH, Kim IS (2007) Landslide susceptibility analysis and its verification using likelihood ratio, logistic regression, and artificial neural network models: case study of Youngin, Korea. Landslides 4:327–338. https://doi.org/10.1007/s10346-007-0088-x
Mandal B, Mandal S (2016) Assessment of mountain slope instability in the Lish River basin of Eastern Darjeeling Himalaya using frequency ratio model (FRM). Model Earth Syst Environ 2:121
Marthelot P (1957) L’érosion dans la montagne Kroumirie. Revue De Géographie Alpine, No 45:273–287
Marthelot P (1959) Note sur un décollement de versant dans la vallée des Atatfa (Kroumirie). Actes du 84" congr. Nat. Suc . Sav., Dijon 1959. Section de Geographic: 61–65.
Menggenang P, Samanta S (2017) Modelling and map** of landslide hazard using remote sensing and GIS techniques. Model Earth Syst Environ 3(3):1113–1122
Metz CE (1978) Basic principles of ROC analysis. Semin Nucl Med 8:283–298. https://doi.org/10.1016/S0001-2998(78)80014-2
Metz CE, Pan X (1999) Proper binormal ROC curves: theory and maximum-likelihood estimation. J Math Psychol 43(1):1–33. https://doi.org/10.1006/jmps.1998.1218
Miossec A (1977) Observations morphologiques, sur le bassin de l’Oued Sejenane (Tunisie Septentrionale). Méditerranée 29:55–72
Miossec A (1979) Paysages et problèmes morphologiques de la région d’Hédil (Tunisie sptentrionale). Rev Tunisienne Géogr 4:57–97
Neelakantan R, Yuvaraj S (2013) Relative effect-based landslide hazard zonation map** in parts of Nilgiris, Tamil Nadu, South India. Arab J Geosci 6(11):4207–4213
Pourghasemi HR, Pradhan B, Gokceoglu C (2012) Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility map** at Haraz watershed, Iran. Nat Hazards 63:965–996. https://doi.org/10.1007/s11069-012-0217-2
Pradhan B (2010) Application of an advanced fuzzy logic model for landslide susceptibility analysis. Int J Comput Intell Syst 3(3):370–381. https://doi.org/10.2991/ijcis.2010.3.3.12
Pradhan B (2011) Manifestation of an advanced fuzzy logic model coupled with geoinformation techniques to landslide susceptibilityEnviron Ecol. Stat 18(3):471–493
Pradhan B (2011) Use of GIS-based fuzzy logic relations and its cross application to produce landslide susceptibility maps in three test areas in Malaysia. Environ Earth Sci 63(2):329–349
Pradhan B (2013) A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzy models in landslide susceptibility map** using GIS. Comput Geosci 51:350–365. https://doi.org/10.1016/j.cageo.2012.08.023
Pradhan B, Lee S (2009) Landslide risk analysis using artificial neural network model focussing on different training sites. Int J Phys Sci 4(1):1–15. https://doi.org/10.5897/IJPS.9000343
Pradhan B, Lee S, Buchroithner M (2017) A GIS-based back-propagation neural network model and its cross-application and validation for landslide susceptibility analyses. Comput Geosci 100:193–211
Rostami Z, Al-modaresi S, Fathizad H et al (2016) Landslide susceptibility map** by using fuzzy logic: a case study of Cham-gardalan catchment, Ilam. Iran Arab J Geosci 9:685. https://doi.org/10.1007/s12517-016-2720-3
Rouvier H (1973) Nappes de charriage en Tunise septentrionales : preuves et conséquences paléogéographiques. Ann Mines et Géol 26:33–47
Rouvier H (1977) Géologie de l’extrémité nord tunisien. Thèse Doct. Es-Sciences, Université Pierre et Marie Curie, Paris VI, France
Saaty TL (1980) The analytic hierarchy process: planning, priority setting, resources allocation. McGraw-Hill California University, p 287
Serey A, Escobar P, Moya S, Sepúlveda S A, Petley D (2017) Landslide inventory of the 2010 Mw 8.8 Maule earthquake, Central Chile. 16th world conference on earthquake 16WCEE 2017: 1873
Shao X, Ma S, Xu C, Shen L, Lu Y (2020) Inventory, distribution and geometric characteristics of landslides in Baoshan City, Yunnan Province, China. Sustainability 12(6):2433. https://doi.org/10.3390/su12062433
Shit PK, Bhunia GS, Maiti R (2016) Potential landslide susceptibility map** using weighted overlay model (WOM). Model EarthSyst Environ 2:21
Singh R, Umrao RK, Singh TN (2013) Probabilistic analysis of slope in Amiyan landslide area, Uttarakhand. Geomat Nat Haz Risk 4(1):13–29. https://doi.org/10.1080/19475705.2012.661796
Thiery Y, Maquaire O, Fressard M (2013) Application of expert rules in indirect approaches for landslide susceptibility assessment. Landslides 11:411–424. https://doi.org/10.1007/s10346-013-0390-8
Upreti BN, Dhital MR (1996) Landslide studies and management in Nepal. International centre for inte grated mountain development (ICIMOD), Kathmandu, Nepal, pp 87
Van Den Eeckhaut M, Hervás J, Malet JP, Guzzetti F (2012) The European landslide inventory map: a tool for the assessment of landslide hazards and risks in Europe. Bull Eng Geol Env 71(2):207–221
Van Westen CJ, Rengers N, Soeters R (2003) Use of geomorphological information indirect landslide susceptibility assessment. Nat Hazards 30(3):399–419
Van Westen CJ (1993) Application of geographic information systems to landslide hazard zonation. ITC Publication, vol. 15. International Institute for Aerospace and Earth Resources Survey, Enschede pp 245
Wu Y, Li W, Wang Q et al (2016) Landslide susceptibility assessment using frequency ratio, statistical index and certainty factor models for the Gangu County, China. Arab J Geosci 9:84. https://doi.org/10.1007/s12517-015-2112-0
Yalcin A (2008) A GIS-based landslide susceptibility map** using analytical hierarchy process (AHP) and bivariate statistics in Ardesen (Turkey): comparisons of results and confirmations. CATENA 72(1):1–12
Zadeh L (1965) Fuzzy sets. Inf Control 8(3):338–353
Acknowledgements
For their cooperation during our days in the field, we would like to thank the team at the Geomatics and Geosystems Laboratory of the University of Manouba, Tunisia.
Author information
Authors and Affiliations
Contributions
Adel Klai, Rim Katlane, and Mohamed Chedly Rabia conceived the manuscript, discussed the methodology, and wrote the original draft. Adel Klai, Rim Katlane, and Romdhane Haddad carried out the data analysis. Adel Klai and Romdhane Haddad prepared the maps and tables and draw the figures. All authors read and approved the published version of the manuscript.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Klai, A., Katlane, R., Haddad, R. et al. Landslide susceptibility map** by frequency ratio and fuzzy logic approach: a case study of Mogods and Hedil (Northern Tunisia). Appl Geomat 16, 91–109 (2024). https://doi.org/10.1007/s12518-023-00544-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12518-023-00544-5