PreprintArticleVersion 1Preserved in Portico This version is not peer-reviewed
Assessing and Modeling the Vegetation Cover in the W and Pendjari National Parks and Their Peripheries Using Landsat Imagery and Climatic Data in Benin, West Africa
Version 1
: Received: 27 October 2023 / Approved: 30 October 2023 / Online: 30 October 2023 (09:03:36 CET)
How to cite:
Dossou-Yovo, H.O.; Osseni, A.A.; Hegbe, A.D.; Khan, M.N.; Sinsin, B. Assessing and Modeling the Vegetation Cover in the W and Pendjari National Parks and Their Peripheries Using Landsat Imagery and Climatic Data in Benin, West Africa. Preprints2023, 2023101846. https://doi.org/10.20944/preprints202310.1846.v1
Dossou-Yovo, H.O.; Osseni, A.A.; Hegbe, A.D.; Khan, M.N.; Sinsin, B. Assessing and Modeling the Vegetation Cover in the W and Pendjari National Parks and Their Peripheries Using Landsat Imagery and Climatic Data in Benin, West Africa. Preprints 2023, 2023101846. https://doi.org/10.20944/preprints202310.1846.v1
Dossou-Yovo, H.O.; Osseni, A.A.; Hegbe, A.D.; Khan, M.N.; Sinsin, B. Assessing and Modeling the Vegetation Cover in the W and Pendjari National Parks and Their Peripheries Using Landsat Imagery and Climatic Data in Benin, West Africa. Preprints2023, 2023101846. https://doi.org/10.20944/preprints202310.1846.v1
APA Style
Dossou-Yovo, H.O., Osseni, A.A., Hegbe, A.D., Khan, M.N., & Sinsin, B. (2023). Assessing and Modeling the Vegetation Cover in the W and Pendjari National Parks and Their Peripheries Using Landsat Imagery and Climatic Data in Benin, West Africa. Preprints. https://doi.org/10.20944/preprints202310.1846.v1
Chicago/Turabian Style
Dossou-Yovo, H.O., Muhammad Nauman Khan and Brice Sinsin. 2023 "Assessing and Modeling the Vegetation Cover in the W and Pendjari National Parks and Their Peripheries Using Landsat Imagery and Climatic Data in Benin, West Africa" Preprints. https://doi.org/10.20944/preprints202310.1846.v1
Abstract
Today, satellite imagery has made a major contribution to the reconstruction and spatial prediction of sensitive or complex areas such as Pendjari and W Transboundary Reserves which constitute biodiversity reservoirs and habitats for wildlife conservation. Despite the protection to which they are subject, they remain dependent on climatic hazards that can influence their stability. This study has applied remote sensing techniques, combined with climate records from the last thirty years, to analyze the past dynamics of land use and climate changes, to predict the future states of the vegetation cover of the two national parks in Benin, as well as their periphery. The methodology used remote sensing and GIS techniques that allowed the supervised classification of Landsat images of 1985, 2000 and 2015. Climatic data were combined in R software to identify the break periods for climatic parameters. Finally, the predictive vegetation cover for the year 2030 was made by combining vegetation and climate in the "Land Change Modeler" extension. Ten land use and land cover classes were obtained. These are the agglomerations, mosaics of fields and fallows, water bodies, dense forests, gallery forests, clear forests and wooded savannahs, swamp forests and shrubby wooded savannahs, saxicolous savannahs and bare ground. The natural vegetation decreased from 90.85% in 1985 to 83.54% in 2000 then to 79.56% in 2015, a decline of 11.39% over a 30-year period. The analysis of the climatic curves revealed the presence of break, meaning drought frequency. The predictive modeling revealed that land use units projected to 2030 are consistent with past trends, but with the continued expansion of fields and fallows (2%) at the expense of vegetation cover. This study will motivate many others in the field.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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