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Landslide susceptibility mapping of the Mediterranean coastal zone of Morocco between Oued Laou and El Jebha using artificial neural networks (ANN)

  • Hasnaa Harmouzi
  • Hakan Ahmet Nefeslioglu
  • Mohamed Rouai
  • Ebru Akcapinar Sezer
  • Abdelillah Dekayir
  • Candan GokceogluEmail author
Original Paper

Abstract

The goal of this study was to experiment artificial neural network (ANN) classifier on various available physical factors in the study area to produce a reliable landslide susceptibility map. The mapping of landsides is classically established through the identification and analysis of hillslope instability factors. Even if a variety of approaches use these analyses with geographic information system (GIS) performances to carry out a good result, there is no satisfaction because of the complexity of the landslides encountered in the field. In the present study, landslide susceptibility models were produced by using multilayer perceptron (MLP) ANN in the Mediterranean Rif coastal zone of Morocco. This was established in the following steps: (i) production of landslide inventory map; (ii) production of the hillslope factors, twenty factors composed of geology, geomorphometry, proximity, and thematic data derived from satellite imageries; (iii) extraction of vector model to be used to train ANN, construction of ANN models; (iv) validation and evaluation of results. The results of the prediction models were evaluated by the receiver operating characteristic (ROC) curves. The obtained area under the curve (AUC) values are greater than 0.90, indicating that the models are quite accurate. The visual comparisons between landslide susceptibility maps and the input factor maps show that roads and geology are the most important factors influencing five types of mass movements (complex, slide, flow, and rockfall). The success of this work will be helpful to expand this method to the whole Rif mountains in Morocco.

Keywords

Landslide susceptibility Artificial neural networks Mediterranean coast Rif mountains (Morocco) 

Notes

Acknowledgments

The authors would like to thank Ms. Begum Mutlu for her support during MATLAB implementations.

Funding information

This research was supported by TUBITAK (the Scientific and Technological Research Council of Turkey) with a project number of 114Y702 and the Convention Moroccan CNRST-TUBITAK 2015-2016.

References

  1. Ada M, San BT (2018) Comparison of machine-learning techniques for landslide susceptibility mapping using two-level random sampling (2LRS) in Alakir catchment area, Antalya, Turkey. Nat Hazards 90:237–263CrossRefGoogle Scholar
  2. Akgun A, Sezer E, 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):23–34CrossRefGoogle Scholar
  3. Aleotti P, Balzeli P, De Marchi D (1996) Le reti neurali nella valutazione della suscettibilita’ da frana. Geologia tecnica e ambientale 4:37–47Google Scholar
  4. Ayenew T, Barbieri G (2005) Inventory of landslides and susceptibility mapping in the Dessie area, northern Ethiopia. Eng Geol 77:1–15CrossRefGoogle Scholar
  5. Begueria S (2006) Validation and evaluation of predictive models in hazard assessment and risk management. Nat Hazards 37:315–329CrossRefGoogle Scholar
  6. Beven KJ, Kirkby MJ (1979) A physically based, variable contributing area model of basin hydrology. Hydrol Sci Bull 24:43–69CrossRefGoogle Scholar
  7. Cetin M (2015) Evaluation of the sustainable tourism potential of a protected area for landscape planning: a case study of the ancient city of Pompeipolis in Kastamonu. Int J Sust Dev World 22(6):490–495CrossRefGoogle Scholar
  8. Cetin M (2016) Sustainability of urban coastal area management: a case study on Cide. J Sustain For 35(7):527–541CrossRefGoogle Scholar
  9. Cetin M, Sevik H (2016) Evaluating the recreation potential of Ilgaz Mountain National Park in Turkey. Environ Monit Assess 188(1):52CrossRefGoogle Scholar
  10. Cetin M, Sevik H, Canturk U, Cakir C (2018) Evaluation of the recreational potential of Kutahya urban forest. Fresenius Environ Bull 27(5):2629–2634Google Scholar
  11. Chalouan A, Michard A (1990) The Ghomarides nappes, Rif coastal range, Morocco: a Variscan chip in the Alpine belt. Tectonics 9:1565–1583CrossRefGoogle Scholar
  12. Combe M, Thauvin J (1971) Ressources en eau du Maroc: domaines du Rif et du Maroc oriental. Service géologique du Maroc.Google Scholar
  13. Corominas J, van Westen C, Frattini P (2014) Recommendations for the quantitative analysis of landslide risk. Bull Eng Geol Environ 73:209–263Google Scholar
  14. Cruden DM, Varnes DJ (1996) Landslide types and processes. In: Turner AK, Schuster RL (eds) Landslides, investigation and mitigation: Transportation Research Board (Special Report 247). US National Research Council, Washington, DC, pp 36–75Google Scholar
  15. Dagdelenler G, Nefeslioglu HA, Gokceoglu C (2016) A modified seed cell sampling strategy for landslide susceptibility assessment: the eastern part of the Gallipoli Peninsula (Canakkale, Turkey). Bull Eng Geol Environ 75(2):575–590CrossRefGoogle Scholar
  16. Dumas B, Guéremy P, Lhenaff R, Raffy T (1984) Mouvements de terrain et risques associés: présentation d'un essai cartographique. Coll. on “Mouvements de terrain”. Assoc Fr Géogr Phys, Caen 161–171Google Scholar
  17. El Fellah B, Azzouz O, Assebriy L (1996) Sikha Asfalou; exemple de glissement de terrain littoral sur la côte méditerranéenne des Bokoya entre Torrès et Badis, Rif, Maroc. - ORSTOM, réseau érosion, 16 pGoogle Scholar
  18. El Kharim Y (2012) Rasgos geológicos de la inestabilidad de laderas en la región de Tetuán (Rif septentrional, Marruecos). Boletín de la Real Sociedad Española de Historia Natural. Sección geológica, ISSN 0583-7510, Tomo 106(1):39–52Google Scholar
  19. El Khattabi J (1997) Caractérisation des zones à risques le long du trace routier Tetouan-Al Hoceima: application au tronçon Cala Iriks Taghzoute (Rif, Maroc). Université de Lille, DEA Géographie PhysiqueGoogle Scholar
  20. El Khattabi J, Carlier E (2004) Tectonic and hydrodynamic control of landslides in the northern area of the Central Rif, Morocco. Eng Geol 71(3):255–264CrossRefGoogle Scholar
  21. Faleh A, Sadiki A (2002) Glissement rotationnel de Dhar El Harrag: exemple d’instabilité de terrain dans le Prérif central (Maroc). Water:41–48Google Scholar
  22. EMSC (2018) European Mediterranean Seismological Centre. https://www.emsc-csem.org/#2 (21.05.2018)
  23. Fares A (1994) Essai méthodologique de la cartographie des risques naturels liés aux mouvements de terrain. Application à l’aménagement de la ville de Taounate (Rif, Maroc). Thèse de doctorat, université de Franche ComtéGoogle Scholar
  24. 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 102:85–98CrossRefGoogle Scholar
  25. Fick S, Hijmans R (2017) WorldClim 2: New 1-km spatial resolution climate surfaces for global land areas. Int J Climatol.  https://doi.org/10.1002/joc.5086 CrossRefGoogle Scholar
  26. Flageollet J C (1989) « Les mouvements de terrain et leur prévention » collection Géographie, édition Masson, ParisGoogle Scholar
  27. Fonseca AF DE PSC (2014) Large deep-seated landslides in the northern Rif Mountains (Northern Morocco): inventory and analysis. Thèse de doctorat, LisboaGoogle Scholar
  28. Hagan MT, Demuth HB, Beale MH (1996) Neural Network Design, Boston, MA., PWS Publishing, 734 pGoogle Scholar
  29. Hansen A (1984) Engineering geomorphology: the application of an evolutionary model of Hong Kong’s terrain. Zeitschrift für Geomorphologie, Supplement band 51:39–50Google Scholar
  30. Kaya E, Agca M, Adiguzel F, Cetin M (2018) Spatial data analysis with R programming for environment. Hum Ecol Risk Assess.  https://doi.org/10.1080/10807039.2018.1470896 CrossRefGoogle Scholar
  31. Lee S (2005) Application of logistic regression model and its validation for landslide susceptibility mapping using GIS and remote sensing data. Int J Remote Sens 26:1477–1491CrossRefGoogle Scholar
  32. Lee S, Ryu J, Min K, Won J (2001) Proceedings of the Geoscience and Remote Sensing Symposium, IGARSS ’01, IEEE 2001 International 5:2364–2366Google Scholar
  33. LP DAAC (2018) NASA EOSDIS Land Processes Distributed Active Archive Center (LP DAAC) at the USGS Earth Resources Observation and Science (EROS) Center, Sioux Falls, South Dakota. https://lpdaac.usgs.gov (21.05.2018)
  34. Mansour M (1998) Geodynamic processes and cartography of ground movements in the area of Chefchaouen (District of Bouhalla-Amtrass). Application to the stabilization of main road Nb: 39. Western Rif, Morocco. Thèse de doctorat, université Paris-Diderot (Paris 7)Google Scholar
  35. Margaa KH (1994) Essai de cartographie des risques naturels: application à l’aménagement de la région d’Al Hoceïma. Thèse Univ. Franche-Comté, Besançon, FranceGoogle Scholar
  36. Mastere M (2011) La susceptibilité aux mouvements de terrain dans la province de Chefchaouen (Rif central, Maroc): analyse spatiale, modélisation probabiliste multi-échelle et impact sur l’aménagement et l’urbanisme. Université de Bretagne occidentale, ThèseGoogle Scholar
  37. Maurer G (1968) Les montagnes du Rif central. Étude géomorphologique. Thèse, universtité de ParisGoogle Scholar
  38. Maurer G (1965) Carte géomorphologique du Rif central. Travaux de l’institut Scientifique Chérifien, Service Géographie Physique, RabatGoogle Scholar
  39. Mayoraz F, Cornu T, Vuillet L (1996) Using Neural networks to predict slope movements. Proc. VII Int. Symp. on Landslides, Trondheim, June 1966, 1. Balkema, Rotterdam, pp 295–300Google Scholar
  40. Michard A, Sadiqi O, Chalouane A et al. (2008) Continental evolution: the geology of Morocco. Structure, stratigraphy, and tectonics of the Africa-Atlantic-Mediterranean triple junction. Advances in geographic information science. Springer, 438 p.Google Scholar
  41. Millies-Lacroix CA (1968) Les glissements de terrain. Présentation d’une carte prévisionnelle des mouvements de masse dans le Rif (Maroc septentrional). Mines et Géologie 27:45–55Google Scholar
  42. Moore ID, Grayson RB, Ladson AR (1991) Digital terrain modelling: a review of hydrological, geomorphological, and biological applications. Hydrol Process 5:3–30CrossRefGoogle Scholar
  43. 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(3-4):401–418CrossRefGoogle Scholar
  44. Nefeslioglu HA, Gokceoglu C (2011) Probabilistic risk assessment in medium scale for rainfall induced earthflows: Catakli catchment area (Cayeli, Rize, Turkey). Mathematical Problems in Engineering Article ID 280431.  https://doi.org/10.1155/2011/280431 CrossRefGoogle Scholar
  45. Nefeslioglu HA, San BT, Gokceoglu C, Duman TY (2012) An assessment on the use of Terra ASTER L3A data in landslide susceptibility mapping. Int J Appl Earth Obs Geoinf 14:40–60CrossRefGoogle Scholar
  46. Nefeslioglu HA, Sezer E, Gokceoglu C, Bozkir AS, Duman TY (2010) Assessment of landslide susceptibility by decision trees in the metropolitan area of Istanbul, Turkey. Mathematical Problems in Engineering Article ID 901095 ( https://doi.org/10.1155/2010/901095)CrossRefGoogle Scholar
  47. Ozer BC, Mutlu B, Nefeslioglu HA, Sezer EA, Rouai M, Dekayir A, Gokceoglu C (2019) On the use of hierarchical fuzzy systems (HFS) in landslide susceptibility mapping: the central part of the Rif Mountains (Morocco). B Eng Geol Environ (in press):1–18.  https://doi.org/10.1007/s10064-019-01548-5
  48. Pradhan B (2010) Remote sensing and GIS-based landslide hazard analysis and cross-validation using multivariate logistic regression model on three test areas in Malaysia. Adv Space Res 45(10):1244–1256CrossRefGoogle Scholar
  49. Pradhan B, Lee S, Buchroithner MF (2010) A GIS-based back-propagation neural network model and its cross-application and validation for landslide susceptibility analyses. Comput Environ Urban Syst 34(3):216–235CrossRefGoogle Scholar
  50. Rkiouak S, Pulido-bosch A et al (1997) Potentialités hydrogéologiques d’une plaine littorale marocaine (Oued Laou, Tétouan-Chefehaouen). Hydrolog Sci J 42(1):101–117CrossRefGoogle Scholar
  51. Rouai M, Jaaidi EB (2003) Scaling properties of landslides in the Rif Mountains of Morocco. Eng Geol 68:353–359CrossRefGoogle Scholar
  52. San BT (2014) An evaluation of SVM using polygon-based random sampling in landslide susceptibility mapping: the Candir catchment area (western Antalya, Turkey). Int J Appl Earth Obs Geoinf 26:399–412CrossRefGoogle Scholar
  53. Service géologique du Maroc (1975) Carte géologique du Rif: Talembot / Royaume du Maroc, Ministère de l'énergie et des mines, Direction de la géologie; levés: KORNPROBST J. & WILDI W / RabatGoogle Scholar
  54. Service géologique du Maroc (1980) Carte géologique du Rif NI-30-XX-1c, Bou Ahmed / Royaume du Maroc, Ministère de l’énergie et des mines, Direction de la géologie; levés: Kornprobst / RabatGoogle Scholar
  55. Service géologique du Maroc (2011) Carte géologique du Maroc 1:50 000 Feuille NI-30-XX-1a, Bab Berret / Royaume du Maroc, Ministère de l’énergie, des mines, de l’eau et de l’environnement, Département de l’énergie et des mines, Direction du développement minier; Levés: J. Kombrobst, M. Gutnic, Ph. Olivier [et al.] / RabatGoogle Scholar
  56. Sezer EA, Pradhan B, Gokceoglu C (2011) Manifestation of an adaptive neuro-fuzzy model on landslide susceptibility mapping: Klang valley, Malaysia. Expert Syst Appl 38(7):8208–8219CrossRefGoogle Scholar
  57. Thauvin JP (1971) Domaines du Rif et du Maroc oriental in: Ressources en eau du Maroc, Tome 1, Notes et Mémoires du Service Géologique du Maroc, N 231, RabatGoogle Scholar
  58. Tucker J (1979) Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens Environ 8:127–150CrossRefGoogle Scholar
  59. Turrini MC, Visintainer P (1998) Proposal of a method to define areas of landslide hazard and application to an area of the Dolomites, Italy. Eng Geol 50:255–265CrossRefGoogle Scholar
  60. Wilson JP, Gallant JC (2000) Terrain analysis, principles and applications New York: John Wiley & Sons Inc.Google Scholar
  61. Yucedag C, Kaya LG, Cetin M (2018) Identifying and assessing environmental awareness of hotel and restaurant employees’ attitudes in the Amasra District of Bartin. Environ Monit Assess 190(2):60CrossRefGoogle Scholar
  62. Zhou W (1999) Verification of nonparametric characteristics of backpropagation neural networks for image classification. IEEE T Geosci Remote 37:771–779CrossRefGoogle Scholar

Copyright information

© Saudi Society for Geosciences 2019

Authors and Affiliations

  • Hasnaa Harmouzi
    • 1
  • Hakan Ahmet Nefeslioglu
    • 2
  • Mohamed Rouai
    • 1
  • Ebru Akcapinar Sezer
    • 3
  • Abdelillah Dekayir
    • 1
  • Candan Gokceoglu
    • 2
    Email author
  1. 1.Exploration and Geotechniques Team, FSMMoulay Ismail UniversityMeknesMorocco
  2. 2.Department of Geological EngineeringHacettepe UniversityAnkaraTurkey
  3. 3.Department of Computer EngineeringHacettepe UniversityAnkaraTurkey

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