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Journal Article

Prediction of land use and land cover change in two watersheds in the Senegal River basin (West Africa) using the Multilayer Perceptron and Markov chain model

Authors

Astou Sambou,  Mame Henriette
External Organizations;

Albergel,  Jean
External Organizations;

Vissin,  Expédit Wilfrid
External Organizations;

/persons/resource/Stefan.Liersch

Liersch,  Stefan
Potsdam Institute for Climate Impact Research;

/persons/resource/Hagen.Koch

Koch,  Hagen
Potsdam Institute for Climate Impact Research;

Szantoi,  Zoltan
External Organizations;

Baba,  Wassim
External Organizations;

Sane,  Moussé Landing
External Organizations;

Toure,  Ibrahima
External Organizations;

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Citation

Astou Sambou, M. H., Albergel, J., Vissin, E. W., Liersch, S., Koch, H., Szantoi, Z., Baba, W., Sane, M. L., Toure, I. (2023): Prediction of land use and land cover change in two watersheds in the Senegal River basin (West Africa) using the Multilayer Perceptron and Markov chain model. - European Journal of Remote Sensing, 56, 1, 2231137.
https://doi.org/10.1080/22797254.2023.2231137


Cite as: https://publications.pik-potsdam.de/pubman/item/item_28588
Abstract
Land use and Land cover change (LULCC) is a major global problem, and projecting change is critical for policy decision-making. Understanding LULCCs at the watershed level is essential for transboundary river basin management. The present study aims to analyse the past and future LULCCs in two significant watersheds of the Senegal River basin (SRB) in West Africa: Bafing and Faleme. This study used Landsat images from 1986, 2006 and 2020 and the Random Forest classification method to analyze past LULCCs in these two watersheds. The results revealed: In Bafing, vegetation, settlement, agricultural areas and water increased, while the bareground decreased significantly between 1986-2020. In Faleme, two periods have different trends. Between 1986-2006, vegetation, settlement, agricultural areas and water increased, while bareground decreased. Between 2006-2020, settlement increased, while vegetation, agricul-tural areas, water and bareground decreased. To predict LULCCs in 2050 under business-as- usual assumptions, the Multilayer Perceptron and Marcov Chain model (MLP-MC) was used. The MLP-MC shows better results on Bafing than on Faleme but without questioning its application on the two watersheds. Bafing has seen a trend towards ”more people, more trees”, while Faleme has seen a trend towards ”more people, more deforestation”. These results contribute to develop appropriate land management policies and strategies to achieve or to maintain sustainable development in the SRB.