Articles | Volume 389
https://doi.org/10.5194/piahs-389-45-2026
https://doi.org/10.5194/piahs-389-45-2026
Post-conference publication
 | 
16 Sep 2026
Post-conference publication |  | 16 Sep 2026

A remote sensing–based approach to the regionalization of socioeconomic indicators in an agricultural headwater catchment in Northern Benin

Yaovi Aymar Bossa, Adjo Brigitte Bossa, Yacouba Yira, Kpade Ozias Laurentin Hounkpatin, Octave Djangni, Jean Hounkpè, Hélyette Arielle Odoumbourou, and Ernest Amoussou

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Cited articles

Bai, Z. G., Dent, D. L., Olsson, L., and Schaepman, M. E.: Proxy global assessment of land degradation, Soil Use Manage., 24, 223–234, https://doi.org/10.1111/j.1475-2743.2008.00169.x, 2008. 
Dupras, J., Revéret, J.-P., and He, J.: L'évaluation économique des biens et services écosystémiques dans un contexte de changements climatiques: un guide méthodologique pour une augmentation de la capacité à prendre des décisions d'adaptation, Ouranos, Montréal, Québec, Canada, https://www.ouranos.ca/sites/default/files/2023-05/proj-horspg-reveret-rapportfinal.pdf (last access: 28 August 2026), 2013. 
Forkuor, G.: Agricultural Land Use Mapping in West Africa Using Multi-sensor Satellite Imagery, Thèse de doctorat, Julius-Maximilians-Universität Würzburg, Würzburg, Germany, https://opus.bibliothek.uni-wuerzburg.de/frontdoor/index/index/docId/10868 (last access: 4 September 2026), 2014. 
Hengl, T., Rossiter, D. G., and Stein, A.: Soil sampling strategies for spatial prediction by correlation with auxiliary maps, Aust. J. Soil Res., 41, 1403–1422, https://doi.org/10.1071/SR03005, 2003. 
Holleran, M., Levi, M., and Rasmussen, C.: Quantifying soil and critical zone variability in a forested catchment through digital soil mapping, SOIL, 1, 47–64, https://doi.org/10.5194/soil-1-47-2015, 2015. 
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This study mapped key differences across the landscape and linked them to farmers’ costs and incomes. By combining satellite information with field data on soils and harvests, the researchers showed that natural variation in land conditions leads to higher labor and input needs in some areas. The results help improve decisions that support more sustainable farming and fairer outcomes for farmers.
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