Land use/land cover dynamics using support vector machine in the area of Lambaréné, Gabon, from 1988 to 2022
Article Main
Abstract
Land use dynamics depict territorial changes, which include conversions and adjustments to landscape units caused by natural and human-induced processes. Human pressures impact landscape changes and various degradation in Lambaréné, which was established as a fully-fledged commune in 1963. The present study aimed to assess several Land Satellite (LANDSAT) pictures from 1988, 2000, 2013, and 2022 was utilized to map land use. The study generated data on land use changes in Lambaréné by cross-referencing these multiple maps. The supervised technique was utilized, and the Support Vector Machine algorithm (SVM) was used to study land-use changes over the last three decades. The resulting transition matrices were used to study the spatial and temporal dynamics of built-up areas, vegetation, and water bodies. The findings showed that urban areas had grown significantly, from 204.73 hectares in 1988 to 736.54 hectares in 2022, a 14.22 % rise, while vegetation dropped from 4057.40 hectares to 3488.86 hectares, a 67.36 % loss during the same time. This trend emphasized the disturbing influence of development on the region's already fragile ecosystems. Nonetheless, there was a slight recovery in the area's vegetation cover between 2013 and 2022, which was most likely due to the area's vulnerability to flooding disasters and thus low investment in infrastructural development during this time, particularly on the left bank of River Lambaréné compared to the right bank. Although these findings looked noteworthy, the use of higher-resolution images might be better for clearly understanding the complexity of land use change in Lambaréné.
Article Details
Article Details
Keywords
Dynamics, Change, Support Vector Machine (SVM), Land use, Lambaréné
References
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Allen, R. G., Trezza, R., Kilic, A., Tasumi, M. & Li, H. (2013). Sensitivity of Landsat‐Scale Energy Balance to Aerodynamic Variability in Mountains and Complex Terrain. JAWRA Journal of the American Water Resources Association, 49(3), 592–604. https://doi.org/10.1111/jawr.12055
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Gebeyehu Abebe, · Dodge Getachew & · Alelgn Ewunetu. (2022). Analysing land use/land cover changes and its dynamics using remote sensing and GIS in Gubalafito district, Northeastern Ethiopia | SN Applied Sciences. https://link.springer.com/article/10.1007/s42452-021-04915-8
Gil, M., Lerique, J. & Oltvry, J.-C. (1990). Le fleuve Ogooué au Gabon. https://www.researchgate.net/profile/Gil-Mahe/publiction/32980574 _Le_fleuve_Ogooue_au_ Gabon_reconstitution_des_debits_manquants_et_mise_ en_evidence_de_variations_ climatiques_a_l'equateur/links/0deec534ba 9829f595000000/ Le-fleuve-Ogooue-au-Gabon-reconstitution-des-debits-manquants-et-mise-en-evidence-de-variations-climatiques-a-lequateur.pdf
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Hassan, Z., Shabbir, R., Ahmad, S. S., Malik, A. H., Aziz, N., Butt, A., & Erum, S. (2016). Dynamics of land use and land cover change (LULCC) using geospatial techniques: A case study of Islamabad Pakistan. SpringerPlus, 5(1), 812. https://doi.org/10.1186/s40064-016-2414-z
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Koumba, A. A., Koumba, C. R. Z., Nguema, R. M., Djogbenou, L. S., Ondo, P. O., Ketoh, G. K., Comlan, P., M’Batchi, B., & Mavoungou, J. F. (2018). Distribution spatiale et saisonnière des gîtes larvaires des moustiques dans les espaces agricoles de la zone de Mouila, Gabon. International Journal of Biological and Chemical Sciences, 12(4), Article 4. https://doi.org/10.4314/ijbcs.v12i4.19
Li, X., Chen, W. Y., Sanesi, G., & Lafortezza, R. (2019). Remote Sensing in Urban Forestry: Recent Applications and Future Directions. Remote Sensing, 11(10), Article 10. https://doi.org/10.3390/rs11101144
Loubamono, S., & Faugères, L. (1993). Risques naturels en Afrique équatoriale. L’exemple du Gabon (Natural Hazards in Equatorial Africa. Gabon case). Bulletin de l’Association de Géographes Français, 70(2), 114–128. https://doi.org/10.3406/bagf.1993.1677
Maloba-Makanga, J. D. (2011a). Les précipitations au Gabon: Climatologie analytique en Afrique.
Maloba-Makanga, J. D. (2011b). Mosaïque forêt-savane et exploitation des ressources forestières du Gabon. Geo-Eco-Trop, 35, 41–50.
Mbadinga I, Indjieley M, & Maloba M. (2019). Quelques indicateurs de vulnerabilite aux inondations dans le bassin-versant de l’Ogooué À Lambaréné. 217–222.
Medina, J. A. V., & Atehortúa, B. E. A. (2019). Comparison of maximum likelihood, support vector machines, and random forest techniques in satellite images classification. Tecnura, 23(59), 13–26.
Menie Ovono, Z., & Pottier, P. (2019). Le risque inondation dans les petits bassins- versants côtiers urbains de Libreville (Gabon): Exemple d’Ogombié et d’Indongui.
Moumbongoyo, R., & Kombila-Mouloungui, A. G. (2020). Impact de l’arrêt de l’exportation des grumes dans la région lacustre du Gabon: Enjeux territoriaux et nouvelles perspectives de développement géotouristique. Dynamiques environnementales. Journal international de géosciences et de l’environnement, 45, Article 45. https://doi.org/10.4000/dynenviron.4544
Okanga Guay, M., Simba, M.C., Nadine, N., Ghislain, M., Obiang Ebanéga, M., Biboutou, A., Bruno, N., & Mintsa Nguema, R. (2018). Transformations des paysages périurbains de Libreville (Gabon): Dynamiques de l’occupation du sol par télédétection de la zone de Bambouchine – Bikélé, 1990-2014.
Okanga-Guay, M., Assoumou, E. O., Akendengue, A.I., Simba, M.C., Mombo, J-B., Obiang,E.M., Mbadinga, M., Rogombe, L., & Mouketou-Tarazewicz, D. (2019). Suivi des changements spatiaux et environnementaux dans les mangroves de la province de l’Estuaire du Gabon, 28.
Olofsson, P., Foody, G. M., Stehman, S. V., & Woodcock, C. E. (2013). Making better use of accuracy data in land change studies: Estimating accuracy and area and quantifying uncertainty using stratified estimation. Remote Sensing of Environment, 129, 122–131. https://doi.org/10.1016/j.rse.2012.10.031
Pal, M., & Mather, P. M. (2005). Support vector machines for classification in remote sensing. International Journal of Remote Sensing, 26(5), 1007–1011. https://doi.org/10.1080/01431160512331314083
Paneque-Gálvez, J., Mas, J.-F., Moré, G., Cristóbal, J., Orta-Martínez, M., Luz, A. C., Guèze, M., Macía, M. J., & Reyes-García, V. (2013). Enhanced land use/cover classification of heterogeneous tropical landscapes using support vector machines and textural homogeneity. International Journal of Applied Earth Observation and Geoinformation, 23, 372–383. https://doi.org/10.1016/j.jag.2012.10.007
Simba, M.C. (2022). Dynamiques des paysages périurbains de la presqu’île de Libreville. De la caractérisation des trajectoires à la modélisation prospective [PhD thesis., UNIVERSITÉ DE TOURS]. https://mail.google.com/mail/u/0/?tab=rm&ogbl#inbox/FMfcgzGtxKTrvBxDVGh KzKSBz ZVmZrpr?projector=1&messagePartId=0.1
Tchatchou, B., Sonwa, D. J., Ifo, S., & Tiani, A. M. (2015). Déforestation et dégradation des forêts dans le Bassin du Congo: État des lieux, causes actuelles et perspectives. CIFOR.
Tropicos. (2019). http://legacy.tropicos.org/Project Web Portal.aspx? pagename=LowerOgoou%C3%A9& projected = 75
United Nations. (2018). United Nations Economic Commission for Africa -68% of the world population projected to live in urban areas by 2050, says UN | UN DESA |
United Nations Department of Economic and Social Affairs. https://www.un.org/development/desa/en/news/popula tion/2018-revision-of-world-urbanization-prospec ts.html
Wasseige, C., Flynn, J., Louppe, D., Hiol Hiol, F, & Mayaux, P. (2014). Les forêts du bassin du Congo – Etat des Forêts. https://ec.europa.eu/jrc/en/publication/books/les-tsdu-bassin-du-congo-etat-des-ts-2013
Yan, L., Roy, D. P., Zhang, H., Li, J. & Huang, H. (2016). An Automated Approach for Sub-Pixel Registration of Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) Imagery. Remote Sensing, 8(6), Article 6. https://doi.org/10.3390/rs8060520
African Union. (2021). Green Recovery Action Plan 2021-2027. https://au.int/sites/default/files/documents/40790-doc-AU_Green_Recovery_Action_Plan_ENGLISH1.pdf
Akoma Miyono, J. A. J., Makak, J.-S., Palla, F. & Trebossen, H. F. (2019). Images satellites pour l’évaluation de l’occupation du sol dans les sites de gestion au Gabon. In M. Benoit & O. Vincent (Eds.), Conférence OSFACO : Des images satellites pour la gestion durable des territoires en Afrique. https://hal.science/hal-02189351
Allen, R. G., Trezza, R., Kilic, A., Tasumi, M. & Li, H. (2013). Sensitivity of Landsat‐Scale Energy Balance to Aerodynamic Variability in Mountains and Complex Terrain. JAWRA Journal of the American Water Resources Association, 49(3), 592–604. https://doi.org/10.1111/jawr.12055
Bouaziz, M., Eisold, S. & Guermazi, E. (2017). Semiautomatic approach for land cover classification: A remote sensing study for arid climate in southeastern Tunisia. Euro-Mediterranean Journal for Environmental Integration, 2(1), 24. https://doi.org/10.1007/s41207-017-0036-7
Boucka, F. N., Obame, C. V., Manfoumbi, F., Mba, A. N., Ondo, M. N., Ovono, V. & Ndjoungui, A. M. (2021). Cartographie de l’occupation du sol du Gabon en 2015—Changements entre 2010 et 2015. Revue Française de Photogrammétrie et de Télédétection, 223(1), Article 1. https://doi.org/10.52638/rfpt.2021.567
Chalmin, P. & Jégourel, Y. (2016). L’Afrique et les marchés mondiaux de matières premières: Leurres et lueurs. Books & Reports. https://ideas.repec.org//b/ocp/dbbook/9-789954-955789.html
Cornélis, D, Abitsi, G, Moubagou, Y. É, Ngwapaza, M, Massoukou, L, Elogh’Asseko, M. & Vigneron, P. (2022). Gabon—Vers une gestion durable de la chasse villageoise. FAO; CIRAD; CIFOR; https://doi.org/10.4060/cb9765fr
Crouzat, É., Byczek, C., Lasseur, R., Cordonnier, T., Longaretti, P.-Y. & Lavorel, S. (2017). Cartographier les services écosystémiques: Quelles données, quels modèles, quelles incertitudes? Exemple autour du bassin de vie de Grenoble (p. 30).
Defossez, S., Vinet, F. & Leone, F. (2017). Assessing Vulnerability to Flooding: Progress and Limitations. In Floods (pp. 241–257). Elsevier. https://doi.org/10.1016/B978-1-78548-268-7.50014-6
Dembélé, S., Soumare, M., Diakite, C. & Gaillard, D. (2018). Dynamiques des paysages régionaux en zone cotonnière du Mali.
Document de Marketing pour la Province du MOYEN-OGOOUE by UNDP ART Initiative—Issuu (2016, ). https://issuu.com/artpublications/docs/undp-ga-artgoldg3
Dongue, S., Frappart, F., Mahe, G., Niño, F., Paris, A., Sihon, J., Ghomsi, F., Blarel, F., Bicquet, J., Onguéné, R., Etame, J., Seyler, F., Paiz, M. & Braun, J.-J. (2022). Variations hydrologiques à long terme du bassin de l’Ogooué (pp. 375–399). https://doi.org/10.1002/ 9781119842125. ch19
Essono, M.R., Okanga-Guay, M. & Mombo, J-B. (2019). (PDF) Évaluation des changements de l’occupation du sol de la commune d’Owendo (Gabon) par imagerie satellite Landsat de 1990 à 2018. https://www.researchgate.net/publication/342690796_Evaluation_des_changements_de_l'occupation_du_sol_de_la_commune_d'Owendo_Gabon_par_imagerie_satellitaire_Landsat_de_1990_a_2018
Fonteyn, D., Vermeulen, C., Deflandre, N., Cornelis, D., Lhoest, S., Houngbégnon, F. G. A., Doucet, J.-L. & Fayolle, A. (2021). Wildlife trail or systematic? Camera trap placement has little effect on estimates of mammal diversity in a tropical forest in Gabon. Remote Sensing in Ecology and Conservation, 7(2), 321–336. https://doi.org/10.1002/rse2.191
Gebeyehu Abebe, · Dodge Getachew & · Alelgn Ewunetu. (2022). Analysing land use/land cover changes and its dynamics using remote sensing and GIS in Gubalafito district, Northeastern Ethiopia | SN Applied Sciences. https://link.springer.com/article/10.1007/s42452-021-04915-8
Gil, M., Lerique, J. & Oltvry, J.-C. (1990). Le fleuve Ogooué au Gabon. https://www.researchgate.net/profile/Gil-Mahe/publiction/32980574 _Le_fleuve_Ogooue_au_ Gabon_reconstitution_des_debits_manquants_et_mise_ en_evidence_de_variations_ climatiques_a_l'equateur/links/0deec534ba 9829f595000000/ Le-fleuve-Ogooue-au-Gabon-reconstitution-des-debits-manquants-et-mise-en-evidence-de-variations-climatiques-a-lequateur.pdf
González-García, A., Palomo, I., González, J. A., López, C. A., & Montes, C. (2020). Quantifying spatial supply-demand mismatches in ecosystem services provides insights for land-use planning. Land Use Policy, 94, 104493. https://doi.org/10.1016/j.landusepol.2020.104493
Hassan, Z., Shabbir, R., Ahmad, S. S., Malik, A. H., Aziz, N., Butt, A., & Erum, S. (2016). Dynamics of land use and land cover change (LULCC) using geospatial techniques: A case study of Islamabad Pakistan. SpringerPlus, 5(1), 812. https://doi.org/10.1186/s40064-016-2414-z
Hmidi, N. (2019). INONDATION DEVASTATRICE DANS LA VILLE DE SOLIMAN (TUNISIE): CAS DE SA ZONE INDUSTRIELLE LORS DE L’ÉVÉNEMENT PLUVIOMÉTRIQUE DU 22 SEPTEMBRE 2018.
Koumba, A. A., Koumba, C. R. Z., Nguema, R. M., Djogbenou, L. S., Ondo, P. O., Ketoh, G. K., Comlan, P., M’Batchi, B., & Mavoungou, J. F. (2018). Distribution spatiale et saisonnière des gîtes larvaires des moustiques dans les espaces agricoles de la zone de Mouila, Gabon. International Journal of Biological and Chemical Sciences, 12(4), Article 4. https://doi.org/10.4314/ijbcs.v12i4.19
Li, X., Chen, W. Y., Sanesi, G., & Lafortezza, R. (2019). Remote Sensing in Urban Forestry: Recent Applications and Future Directions. Remote Sensing, 11(10), Article 10. https://doi.org/10.3390/rs11101144
Loubamono, S., & Faugères, L. (1993). Risques naturels en Afrique équatoriale. L’exemple du Gabon (Natural Hazards in Equatorial Africa. Gabon case). Bulletin de l’Association de Géographes Français, 70(2), 114–128. https://doi.org/10.3406/bagf.1993.1677
Maloba-Makanga, J. D. (2011a). Les précipitations au Gabon: Climatologie analytique en Afrique.
Maloba-Makanga, J. D. (2011b). Mosaïque forêt-savane et exploitation des ressources forestières du Gabon. Geo-Eco-Trop, 35, 41–50.
Mbadinga I, Indjieley M, & Maloba M. (2019). Quelques indicateurs de vulnerabilite aux inondations dans le bassin-versant de l’Ogooué À Lambaréné. 217–222.
Medina, J. A. V., & Atehortúa, B. E. A. (2019). Comparison of maximum likelihood, support vector machines, and random forest techniques in satellite images classification. Tecnura, 23(59), 13–26.
Menie Ovono, Z., & Pottier, P. (2019). Le risque inondation dans les petits bassins- versants côtiers urbains de Libreville (Gabon): Exemple d’Ogombié et d’Indongui.
Moumbongoyo, R., & Kombila-Mouloungui, A. G. (2020). Impact de l’arrêt de l’exportation des grumes dans la région lacustre du Gabon: Enjeux territoriaux et nouvelles perspectives de développement géotouristique. Dynamiques environnementales. Journal international de géosciences et de l’environnement, 45, Article 45. https://doi.org/10.4000/dynenviron.4544
Okanga Guay, M., Simba, M.C., Nadine, N., Ghislain, M., Obiang Ebanéga, M., Biboutou, A., Bruno, N., & Mintsa Nguema, R. (2018). Transformations des paysages périurbains de Libreville (Gabon): Dynamiques de l’occupation du sol par télédétection de la zone de Bambouchine – Bikélé, 1990-2014.
Okanga-Guay, M., Assoumou, E. O., Akendengue, A.I., Simba, M.C., Mombo, J-B., Obiang,E.M., Mbadinga, M., Rogombe, L., & Mouketou-Tarazewicz, D. (2019). Suivi des changements spatiaux et environnementaux dans les mangroves de la province de l’Estuaire du Gabon, 28.
Olofsson, P., Foody, G. M., Stehman, S. V., & Woodcock, C. E. (2013). Making better use of accuracy data in land change studies: Estimating accuracy and area and quantifying uncertainty using stratified estimation. Remote Sensing of Environment, 129, 122–131. https://doi.org/10.1016/j.rse.2012.10.031
Pal, M., & Mather, P. M. (2005). Support vector machines for classification in remote sensing. International Journal of Remote Sensing, 26(5), 1007–1011. https://doi.org/10.1080/01431160512331314083
Paneque-Gálvez, J., Mas, J.-F., Moré, G., Cristóbal, J., Orta-Martínez, M., Luz, A. C., Guèze, M., Macía, M. J., & Reyes-García, V. (2013). Enhanced land use/cover classification of heterogeneous tropical landscapes using support vector machines and textural homogeneity. International Journal of Applied Earth Observation and Geoinformation, 23, 372–383. https://doi.org/10.1016/j.jag.2012.10.007
Simba, M.C. (2022). Dynamiques des paysages périurbains de la presqu’île de Libreville. De la caractérisation des trajectoires à la modélisation prospective [PhD thesis., UNIVERSITÉ DE TOURS]. https://mail.google.com/mail/u/0/?tab=rm&ogbl#inbox/FMfcgzGtxKTrvBxDVGh KzKSBz ZVmZrpr?projector=1&messagePartId=0.1
Tchatchou, B., Sonwa, D. J., Ifo, S., & Tiani, A. M. (2015). Déforestation et dégradation des forêts dans le Bassin du Congo: État des lieux, causes actuelles et perspectives. CIFOR.
Tropicos. (2019). http://legacy.tropicos.org/Project Web Portal.aspx? pagename=LowerOgoou%C3%A9& projected = 75
United Nations. (2018). United Nations Economic Commission for Africa -68% of the world population projected to live in urban areas by 2050, says UN | UN DESA |
United Nations Department of Economic and Social Affairs. https://www.un.org/development/desa/en/news/popula tion/2018-revision-of-world-urbanization-prospec ts.html
Wasseige, C., Flynn, J., Louppe, D., Hiol Hiol, F, & Mayaux, P. (2014). Les forêts du bassin du Congo – Etat des Forêts. https://ec.europa.eu/jrc/en/publication/books/les-tsdu-bassin-du-congo-etat-des-ts-2013
Yan, L., Roy, D. P., Zhang, H., Li, J. & Huang, H. (2016). An Automated Approach for Sub-Pixel Registration of Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) Imagery. Remote Sensing, 8(6), Article 6. https://doi.org/10.3390/rs8060520
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How to Cite
Land use/land cover dynamics using support vector machine in the area of Lambaréné, Gabon, from 1988 to 2022. (2024). Journal of Applied and Natural Science, 16(2), 890-900. https://doi.org/10.31018/jans.v16i2.5476
