Authors : MBOU FOBASSO Jessica; BIKIE GERALD Anicet; Dongmo Hile Bertrand; Elime Boubouama Aime; YASSINE Mouniane

Volume/Issue : Volume 9 - 2024, Issue 8 - August

Google Scholar : https://shorturl.at/toHYE

Scribd : https://shorturl.at/W1USL

DOI : https://doi.org/10.38124/ijisrt/IJISRT24AUG127

Abstract : Faced with an arid and semi-arid climate and limited surface water resources, the Far North Region of Cameroon prioritizes groundwater exploration. Indeed, these waters, being more potable than surface water, represent a crucial issue for the region. It is in this context that our study focused on mapping the groundwater potential of this area. To do this, we combined multi- criteria analysis with remote sensing. Multi-criteria analysis allowed us to consider various key factors such as climate, slope, lineament density, drainage network, geology, soil types, land use, and soil moisture. Each of these factors was weighted according to its relative importance for the presence of groundwater. Remote sensing provided us with powerful tools to collect spatial data. Satellites and other image capture technologies enabled us to acquire valuable information about the Earth's surface, such as surface temperature, vegetation density, and much more. These images then underwent extensive processing, including resampling, composite channel creation, and mosaicking. Texture analysis was also performed to identify fine lineaments in the landscape, potentially indicative of tectonic fractures or faults, which are important clues to the presence of groundwater. The study results revealed a heterogeneous distribution of groundwater potential in the region. 32.93% of the area (10,905.661 Km2) has low water content, 37.5% (12,416.402 Km2) moderate water content, 29.54% (9,781.646 Km2) good water content, and only 0.01% (9.04 Km2) excellent water content. The use of remote sensing for groundwater exploration in the Far North Region of Cameroon is a promising approach that should continue to develop. Technological advancements and access to more sophisticated data will enable even more precise and detailed information about the region's water resources. This will undoubtedly contribute to better management of this precious resource and increased water security for local populations.

Keywords : Multi-Criteria Analysis, Groundwater, Remote Sensing, Texture Analysis, Resampling.

References :

1. Saaty, T.L. (1980). The analytic hierarchy process, planning, priority setting, resource allocation. McGraw-Hill: New-York.
2. Guillaume, P. Félix, P., Jean-Marc, T. & Antoine, G. (2018). Aide à la décision par l’application de la méthode AHP (Analytic Hierarchy Process) à l’analyse multicritère des stratégies d’aménagement du grand Buech à la Faurie. Sciences Eaux & Territoires, p. 54-57.
3. Hossain. Maharufa. Abdul, W. and Golam, M. (2003). Introduction to remote sensing. Afghan. Inf. Manag.Serv. UN Dev. Program. 02(10). P 248-255.
4. Huete, A.R. (1988). A soil-adjusted vegetation index (SAVI). Remote sensing of Environment 25. P 295-309.
5. Lehoux, N., & Valée, P. (2004). Multi_criteres2004.pdf. Multi_criteres
   2004.pdfhttps://www.performancepublique.budget.gouv.fr/sites/performance_publique/files/files/documents/performance/controle_gestion/qualite_et_CG/Analyse_multicriteres/1_Multi_criteres2004.pdf
6. Mena, S. (2000). Introduction aux méthodes multicritères d’aide à la décision.
   Biotechnol.Agron. Soc.Environ.2000 4 (2), p 83-93.
7. Christian Seignobos et Olivier Iyébi-Mandjek.(2023). Atlas de la province Extrême-Nord Cameroun.
8. PANGIRE. (2009). Connaissance et usages des ressources en eau.
9. MANGOUA M. J.1, YAO A. B., DOUAGUI G. A., KOUASSI K. A., GOULA B. T. A. et BIEMI. (2019). Evaluation des potentialités en eau souterraine des aquifères fissures dans le bassin versant du Bandama (côte d’ivoire). N°37. p. 53-74.
10. ONG MAINS UNIES D’AFRIQUE. (2023). Situation de l’eau au Cameroun.
11. Phillipe DUTARTRE, Laurent STIELTJES. (1990). Utilisation de l’imagerie satellitaire SPOT pour la prospection hydrogéologique en milieu volcanique : exemple de la Réunion océan indien.
12. Gaëlle Guesdon. (2011). Méthodes et outils Aide multicritère à la décision comparaison de Saaty.
13. Hafida Lmoussaoui, Hicham Jamouli. (2015). Evaluation des risques-projet par une approche AHP/WPM : Application à un projet réel BTP.
14. HANQIU XU. (2006). Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery. International Journal of Remote Sensing, vol. 27, n^o. 14, p 3025–3033.
15. Anouk SUCHET. (2016). Détection et caractérisation des zones humides d’altitude par télédétection à haute et très haute résolution spatiale. Rennes.