Reconstitution spatiale et simulation des changements futurs de l'occupation du sol dans la Réserve de Biosphère de la basse vallée de l'Ouémé (RB-BVO) au Bénin
The study area, with its extensive wetlands, belongs to the Ramsar site 1018, which was inscribed in 2000 and was classified as a Biosphere Reserve by UNESCO in 2020. The reconstruction of the spatio-temporal dynamics of the land cover will enable the analysis of changes over time and the prediction...
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Physio-Géo
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| Online Access: | https://journals.openedition.org/physio-geo/15014 |
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| author | Abdel Aziz Osseni Gbodja Houéhanou François Gbesso Gildas N'tibouti Idakou Adandé Belarmain Fandohan Ismaïla Toko Agossou Brice Hugues Tente Brice Augustin Sinsin |
| author_facet | Abdel Aziz Osseni Gbodja Houéhanou François Gbesso Gildas N'tibouti Idakou Adandé Belarmain Fandohan Ismaïla Toko Agossou Brice Hugues Tente Brice Augustin Sinsin |
| author_sort | Abdel Aziz Osseni |
| collection | DOAJ |
| description | The study area, with its extensive wetlands, belongs to the Ramsar site 1018, which was inscribed in 2000 and was classified as a Biosphere Reserve by UNESCO in 2020. The reconstruction of the spatio-temporal dynamics of the land cover will enable the analysis of changes over time and the prediction of future changes in a perspective of sustainable conservation initiatives. Landsat images from 1990, 2005 and 2020 were subjected to supervised classification using remote sensing and GIS techniques. The resulting data were combined to establish transition matrices to assess the conversion rates of the different land use classes. Future land use changes up to 2035 were simulated using the Land Change Modeler.The results obtained indicate that in 1990, 70.9% of the site was covered by spontaneous vegetation formations (shrub and tree savannahs, dense and gallery forests, swamp formations). Their share fell to 61.6% in 2005 and to 53.6% in 2020, which represents a loss of 24.4% in relative terms over a 30-year period.The scenario developed for the future shows that spontaneous formations will still be slightly dominant (52.2% of the total area), while the largest areas will remain equally occupied by swamp formations and by fields and fallow land (24.4%). However, this information must be taken with caution.Translated with www.DeepL.com/Translator (free version) |
| first_indexed | 2024-03-08T02:46:37Z |
| format | Article |
| id | doaj.art-b78b6db48e9a44f28da748b9ca221bac |
| institution | Directory Open Access Journal |
| issn | 1958-573X |
| language | English |
| last_indexed | 2024-03-08T02:46:37Z |
| publisher | Physio-Géo |
| record_format | Article |
| series | Physio-Géo |
| spelling | doaj.art-b78b6db48e9a44f28da748b9ca221bac2024-02-13T13:24:14ZengPhysio-GéoPhysio-Géo1958-573X1912810.4000/physio-geo.15014Reconstitution spatiale et simulation des changements futurs de l'occupation du sol dans la Réserve de Biosphère de la basse vallée de l'Ouémé (RB-BVO) au BéninAbdel Aziz OsseniGbodja Houéhanou François GbessoGildas N'tibouti IdakouAdandé Belarmain FandohanIsmaïla TokoAgossou Brice Hugues TenteBrice Augustin SinsinThe study area, with its extensive wetlands, belongs to the Ramsar site 1018, which was inscribed in 2000 and was classified as a Biosphere Reserve by UNESCO in 2020. The reconstruction of the spatio-temporal dynamics of the land cover will enable the analysis of changes over time and the prediction of future changes in a perspective of sustainable conservation initiatives. Landsat images from 1990, 2005 and 2020 were subjected to supervised classification using remote sensing and GIS techniques. The resulting data were combined to establish transition matrices to assess the conversion rates of the different land use classes. Future land use changes up to 2035 were simulated using the Land Change Modeler.The results obtained indicate that in 1990, 70.9% of the site was covered by spontaneous vegetation formations (shrub and tree savannahs, dense and gallery forests, swamp formations). Their share fell to 61.6% in 2005 and to 53.6% in 2020, which represents a loss of 24.4% in relative terms over a 30-year period.The scenario developed for the future shows that spontaneous formations will still be slightly dominant (52.2% of the total area), while the largest areas will remain equally occupied by swamp formations and by fields and fallow land (24.4%). However, this information must be taken with caution.Translated with www.DeepL.com/Translator (free version)https://journals.openedition.org/physio-geo/15014remote sensingland usewetlandsspatial dynamicsBiosphere ReserveOuémé |
| spellingShingle | Abdel Aziz Osseni Gbodja Houéhanou François Gbesso Gildas N'tibouti Idakou Adandé Belarmain Fandohan Ismaïla Toko Agossou Brice Hugues Tente Brice Augustin Sinsin Reconstitution spatiale et simulation des changements futurs de l'occupation du sol dans la Réserve de Biosphère de la basse vallée de l'Ouémé (RB-BVO) au Bénin Physio-Géo remote sensing land use wetlands spatial dynamics Biosphere Reserve Ouémé |
| title | Reconstitution spatiale et simulation des changements futurs de l'occupation du sol dans la Réserve de Biosphère de la basse vallée de l'Ouémé (RB-BVO) au Bénin |
| title_full | Reconstitution spatiale et simulation des changements futurs de l'occupation du sol dans la Réserve de Biosphère de la basse vallée de l'Ouémé (RB-BVO) au Bénin |
| title_fullStr | Reconstitution spatiale et simulation des changements futurs de l'occupation du sol dans la Réserve de Biosphère de la basse vallée de l'Ouémé (RB-BVO) au Bénin |
| title_full_unstemmed | Reconstitution spatiale et simulation des changements futurs de l'occupation du sol dans la Réserve de Biosphère de la basse vallée de l'Ouémé (RB-BVO) au Bénin |
| title_short | Reconstitution spatiale et simulation des changements futurs de l'occupation du sol dans la Réserve de Biosphère de la basse vallée de l'Ouémé (RB-BVO) au Bénin |
| title_sort | reconstitution spatiale et simulation des changements futurs de l occupation du sol dans la reserve de biosphere de la basse vallee de l oueme rb bvo au benin |
| topic | remote sensing land use wetlands spatial dynamics Biosphere Reserve Ouémé |
| url | https://journals.openedition.org/physio-geo/15014 |
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