Contribution of GIS to the mapping of landslide risk areas in the city of Bafoussam
DOI:
https://doi.org/10.48346/IMIST.PRSM/ajlp-gs.v6i1.35386Keywords:
landslide, GIS, risk areas, multicriteria analysis, preventionAbstract
Landslide risk prevention remains a major global concern. This work allowed the characterization and mapping of landslide risk areas and the evaluation of their accessibility in the city of Bafoussam.
The methodological approach was based on the integration in a geographic information system (GIS) of data interpreted from satellite images, pedology, climatic data and the digital elevation model (DEM). On the basis of multi-criteria analysis, the main factors of landslide risk were considered: relief, rainfall, occupation and nature of soils.
The multi-criteria spatial analysis carried out in a GIS allowed the elaboration of hazard maps as well as the map of landslide risk areas. This map includes five classes: areas with very low landslide risk (18.36%), areas with low landslide risk (34.33%), areas with moderate landslide risk (26.36%), areas with high landslide risk (16.67%) and areas with very high landslide risk (4.28%). A buffer zone around road traffic routes allowed us to obtain the accessible areas for the last four classes. Thus, we have the following accessibility rates: 10.57% for low landslide risk areas, 11.36% for moderate landslide risk areas, 11.29% for high landslide risk areas and 18.19% for very high landslide risk areas. This rate represents for each area, the percentage of the accessible surface. The results of our work can be used not only for landslide risk prevention but also for potential crisis management.References
Abay, A., Barbieri, G., & Woldearegay, K. (2019).GIS-based Landslide Susceptibility Evaluation Using Analytical Hierarchy Process (AHP) Approach : The Case of Tarmaber District Ethiopia Momona Ethiopian Journal District, Ethiopia. Momona Ethiopian Journal of Science,11,14.https://doi.org/10.4314/mejs.v11i1.2
Adimi, O. S. C., Oloukoi, J., & Tohozin, C. A. B. (2018). Analyse spatiale multicritère et identification des sols propices à la production du maïs à Ouessè au Bénin. VertigO - la revue électronique en sciences de l’environnement. https://doi.org/10.4000/vertigo.19885
Ahmed, N., & Ferhat, K. (2016). Using a Hierarchical Multi-criteria Analysis to Evaluate Elevators for Server the Date Palm Crown. 8.
Ahn, So Ra․Jang, Cheol Hee․Kim, Sang Ho․Han, Myoung Sun․Kim, Jin Hoon․Kim, Seong Joon. (2013). Discussion for the Effectiveness of Radar Data through Distributed Storm Runoff Modeling. Journal of the Korean Society of Agricultural Engineers , ISSN 1738-3692, eISSN 2093-7709
Akgun, A., Dag, S., & Bulut, F. (2008). Landslide susceptibility mapping for a landslide-prone area (Findikli, NE of Turkey) by likelihoodfrequency ratio and weighted linear combination models |SpringerLink. springerlink,54,11271143.https://doi.org/10.1007/s00254-007-0882-8 06-0435-6
Alain, H. (2012). Eau,milieux aquatiques et territoires durables 2030. Annexe du rapport de fin d’étude Fiches Variables. Irstea/Cemagref,DP2VIST.
Ali, S. and Aslam, M. (2018) GIS Based Landslide Susceptibility Mapping with Application of Analytical Hierarchy Process in District Ghizer, Gilgit Baltistan Pakistan. Journal of Geoscience and Environment Protection, 6, 34-49. doi: 10.4236/gep.2018.62003.”
Bétard, F., Delbart, N., & Piel, C. (2014). Cartographie de la susceptibilité aux glissements de terrain dans la région de Nova Friburgo (État de Rio de Janeiro, Brésil). Une étape vers l’évaluation et la gestion du risque. https://journals.openedition.org/bagf/1603
Bódis, K. (2008). Digital elevation models and their applications in flood risk management (doctoral dissertation, university of Szeged).
C. F. Mahler, E. Varanda and L. C. D. de Oliveira, (2012),"Analytical Model of Landslide Risk Using GIS," Open Journal of Geology, Vol. 2 No. 3, pp. 182-188. doi: 10.4236/ojg.2012.23018.” And “Rahim, I.,
Direction de la surveillance et de la prévention des risques. (2008). Etude pour la réalisation d’une cartographie et d’un système d’information géographique sur les risques majeurs au Maroc.
Meyer C., Geldreich P., Yesou H (2001) Apport des données simulées SPOT 5 pour l’évaluation des dégâts de tempête dans la forêt d’Haguenau (Alsace, France). Conférence SPOT 5 « vers de nouvelles applications », Toulouse27-28 novembre ,2001
Office de la recherche scientifique et technique outre-mer – ORSTOM (1966). Note explicative – carte pédologique du Cameroun oriental au 1 / 1 000 000.