Remote Sensing Mapping of Land Use and Land Cover Changes in Upper Casamance, Senegal, 1987-2018

Boubacar Solly; El Hadji Balla Dieye; Oumar Sy

doi:doi:10.11648/j.ajrs.20200802.11

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Remote Sensing Mapping of Land Use and Land Cover Changes in Upper Casamance, Senegal, 1987-2018

Boubacar Solly, El Hadji Balla Dieye, Oumar Sy

Published in American Journal of Remote Sensing (Volume 8, Issue 2)

Received: 6 September 2020 Accepted: 19 September 2020 Published: 28 September 2020

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Abstract

In order to study the evolution of land use and the changes in land cover in Upper Casamance, from Landsat images acquired in 1987 and 2018, we used a method of multistage unsupervised classification. Recently developed to mapping and quantification of vegetation land cover changes in West-African coastal, this method is based on the following stages: first classification (K-means) over 15 classes, interpretation of the spectral signatures of the resulting classes followed by reclassification according to the chosen nomenclature, creation of thematic masks, classifications on masks, and finally reclassification. With the only difference, our study aims also to contribute, methodologically, to the knowledge of the spectral profiles of plant formation types. On a thematic level, the results show that between 1987 and 2018, forest areas decreased by 377,118.7 ha (or 27.4%), while wooded areas and agricultural and soil surfaces increased by 263,172.4 ha (or 19.1%) and 1560 75.5 ha (11.3%). In terms of change, deforestation by increasing agricultural and soil surfaces is noted along the border with the Gambia, savanization and anthropization is noted along the central part, and stability of forest surfaces followed by a slight increase in savannas and agricultural and soil surfaces is noted in the south.

Published in	American Journal of Remote Sensing (Volume 8, Issue 2)
DOI	10.11648/j.ajrs.20200802.11
Page(s)	35-49
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2020. Published by Science Publishing Group

Keywords

Soil Occupation, Change Maps, Unsupervised Classification, Vegetation Cover, Upper Casamance

References

[1]	Nouaceur, Z. Rain recovery and flooding in Sahel West Africa. Physio-Geo. 2020. 15, 89-109.
[2]	Stancioff, A. Staljanssens, M. and Tappan, G. Mapping and remote sensing of the resources of the Republic of Senegal. Study of geology, hydrogeology, soils, vegetation and land use potentials. Remote Sensing Institute, SDSU-RSI-86-01, 1986. pp. 653.
[3]	Michel, P. The degradation of landscapes in Senegal. In "The degradation of landscapes in West Africa, J-F Richard. (eds)." Dakar Seminar, 21-26 November 1988. 1990. 37-53.
[4]	Li, J. Lewis, J. Rowland, J. Tappan, G. and Tiezen, L. L. Evaluation of land performande in Senegal using multi-temporal NDVI and rainfall series. Journal of Arid Environments. 2004. 59, 463-480.
[5]	Tappan, G. G. Sall, M. Wood, E. C. and Cushing, M. Ecoregions and land cover trends in Senegal. Journal of arid Environments. 2004. 59, 427-462.
[6]	Hountondji, Y-C. H. Environmental dynamics in the Sahel and Sudanese areas of West Africa: Analysis of changes and assessment of degradation of the vegetal cover. Thesis of PhD in Science and Environmental Management at the University of Liège. 2008. pp. 181.
[7]	CILSS. West African Landscapes: A Window on a Changing World. U.S. Geological Survey EROS, 47914 252nd St, Garretson, SD 57030, UNITED STATES, 2016. pp. 219.
[8]	FAO. Global Forest Resources Assessment 2015. FRA data directory. Rome, Italy, 2015. pp. 244.
[9]	Ariori, S. L. and Ozer, P. Development of forest resources in the Sahel West Africa over the last 50 years. Geo-Eco-Trop. 2005. 61-68.
[10]	Solly, B. Dieye, E. H. B. Mballo, I. Sy, O. Sane, T. and Thior, M. Spatio-temporal dynamics of forest landscapes in the south of Senegal: case of the department of Vélingara. Physio-Geo. 2020, 15, 41-67.
[11]	Hamel, O. Dieng, C. Niang, A. Diop, A. B. Kairé, M. and Tamba, A. Covering Senegal's household energy needs by managed natural forests: dream or reality? Impacts on national policies and opportunities related to Carbon Mechanisms. Édit. PACAF-Sénégal/CASCADe-Afrique. 2011. pp. 26.
[12]	Mbow, C. Spatio-temporal characteristics of wildfires and their relation to vegetation in Niokolo Koba National Park (southeastern Senegal). Thesis of PhD, 3rd Cycle of the Institute of Environmental Sciences, Dakar. 2000. pp. 120.
[13]	Sane, T. Climate variability and its impact on the environment and human activities in Upper Casamance (South Senegal). PhD Thesis 3rd cycle of Geography, Cheikh Anta Diop University, Dakar. 2003. pp. 370.
[14]	San Emeterio, J-L. Lacaze, B. and Mering, C. Detection of changes in vegetation cover in the Sahel during the period 1982-2002 from NDVI and rainfall data. Télédétection. 2011. 10 (2-3), 135-143.
[15]	Herrmann, S. M. Anyamba, A. and Tucker, C. J. Recent trends in vegetation dynamics in the African Sahel and their relationship to climate. Global Approx. Change. 2005. 15, 394-404.
[16]	Giffard, P. L. The tree in the Senegalese landscape. Forestry in dry tropical zone. Tropical Forestry Technical Center, Dakar, 1974. pp. 431.
[17]	UNEP. The future of the environment in Africa, the past, the present and the future. Earthscan, United Kingdom, 2002. pp. 422.
[18]	Tsayem Demaze, M. Remote sensing as a tool to measure deforestation reduction (REDD). Remote Sensing Review, Research and Application, 2011. 9 (3-4), 245-257.
[19]	UNITED NATIONS. Rio Declaration on Environment and Development. Rio de Janeiro, 3-14 June 1992, A/CONF. 151/26, Vol. I, https://www.un.org/french/events/rio92/aconf15126vol1f.htm.
[20]	Chamard, P. C. and Courel, M. F. Sahelian forest threatened. Drought Paper, 1999. 10 (1), 11-18.
[21]	Bamba, I. Anthropization and spatial-temporal dynamics of forest landscapes in the Democratic Republic of Congo. Thesis of PhD in Science, Université Libre de Bruxelles. 2010. pp. 189.
[22]	Dibi N’Da, H. N’Guessan, E. K. Wajda, M. E. and Affian, K. Remote sensing to monitoring deforestation in the Marahoué National Park (Côte d’Ivoire). Bulletin - French Society of Photogrammetry and Remote Sensing, 8 (1), 2008. 17-34.
[23]	Mama, A. Bamba, I. Sinsin, B. Bogaert, J. and De Canniere, C. Deforestation, savanization and agricultural development of savanna-forest landscapes in the Sudano-Guinean area of Benin. Tropical wood and forests. 2014. 322 (4), 65-75.
[24]	Sylla, D. Ba, T. and Guisse, A. Mapping of changes in vegetation cover in Ferlo protected areas (North Senegal): Biosphere Reserve case. Physio-Geo. 2019. 13, 115-132.
[25]	Diedhiou, I. Between the use and preservation of woody resources in West Africa: The dynamics of the forest landscapes in Southern Senegal. Thesis of Doctorate in Co-Trusteeship of the University of Paris and Assane Seck University of Ziguinchor, Senegal, 2019. pp. 444.
[26]	Kyale Koy, J. Wardell, D. A. Mikwa, J.-F. Kabuanga, J. M. Monga Ngonga, A. M. Oszwald, J. and Doumenge, C. Dynamics of deforestation in the Yangambi Biosphere Reserve (Democratic Republic of Congo): Spatial and temporal variability over the past 30 years, Tropical Wood and Forests, 2019. 341, 15-28.
[27]	Joly, G. Computer processing of satellite image. The EPI Bulletin. 1987. 47, 233-239.
[28]	Girard, M. C. and Girard, C. M. Processing remote sensing data: Environment and natural resources. Dunod, Paris, 2nd edition, 2010. pp. 553.
[29]	Caloz, R. and Collet, C. Remote Sensing Specifications. Geographic information system and digital image processing. University of Quebec Press/AUPELF-UREF, Sainte-Foy, 2001. 3, pp. 386.
[30]	Idbraim, S. Methods for extracting spatial information and classifying in remote sensing imaging: Applications to thematic mapping of the Agadir region (Morocco). Thesis of PhD in Remote Sensing and Image Processing, University of Toulouse III - Paul Sabatier. 2009. pp. 143.
[31]	Masse, A. Development and automation of classification methods from time series of remote sensing images — Application to land use change and carbon balance estimation. PhD Thesis in Remote Sensing Image Processing, University of Toulouse III Paul Sabatier. 2013. pp. 223.
[32]	Janodet, E. and Blasco, F. Green maps of vegetation and satellite remote sensing. Ed. AUPELF-UREF. Québec university press. 1993. 247-261.
[33]	Andrieu, J. and Mering, C. Vegetation land cover change mapping of West African coastal zone from remotely sensed images: example of “Rivières-du-Sud” from Salum Delta (Senegal) to Rio Geba (Guinea-Bissau). Remote Sensing. 2008. 2. 93-118.
[34]	Sagna, P. Climate dynamics and recent developments in the western part of West Africa. Thesis of Doctorate of State Es Lettres, Department of Geography, University Cheikh Anta Diop, Dakar. 2005. 1, pp. 270.
[35]	Aubreville A. Yangambi Agreement on the nomenclature of African vegetation types. Bois et Forêts des Tropiques. 1957. 51. 23-27.
[36]	Descoings, B. The herbal formations in the phytogeographical classification of Yangambi. Adansonia, ser. 2, 18 (2). Paris, 1978. 243-256.
[37]	Da Lage, A. and Metailie, G. Dictionary of plant biogeography. CNRS Editions, Paris, 2005. pp. 579.
[38]	Rodes Arnau, I. Estimate of large-scale land use for the exploitation of Earth observation images at high spatial, spectral and temporal resolutions. Thesis of PhD at the Center d’Études Spatiales de la BIOsphere, University Toulouse III Paul Sabatier, France. 2016. pp. 205.
[39]	Ball, G. H. and Hall, D. J. ISODATA, a novel method of data analysis and pattern classification: DTIC Document. 1965.
[40]	MacQueen, J. Some methods for classification and analysis of multivariate observations. Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability. 1967. 1:281-297.
[41]	Ducrot, D. Methods of analysis and interpretation of multi-source remote sensing images, extraction of landscape features. Research Brief, Entitlement to Conduct Research INP Toulouse, 2005. pp. 240.
[42]	Guyot, G. and Saint, G. The main contributions of the international symposium "spectral signature of objects in remote sensing" in the spectral domain of the visible and near infrared. In "Proceedings of the International Symposium of the International Society for Photogrammetry and Remote Sensing", Vol2, Toulouse, 13-17 September, Ed.-Berlin, 1982. 95-108.
[43]	Chaume, R. and Combeau, A. Comparative seasonal changes in spectral signatures of various perennial environments (forests, meadows, bare soils) from Landsat documents. Remote Sensing, ORSTOM, 1983. 8, pp. 49.
[44]	Courel, M-F. Study of the recent evolution of the Sahel environment from satellite measurements. Thesis of Doctorate of State, Letters and Humanities, Université Panthéon-Sorbonne, Paris I, 1984. pp. 407.
[45]	Guyot, G. Spectral Signatures of Natural Surfaces. Satellite Remote Sensing Collection, Paradigm, 1989. 43, 106145.
[46]	Chamard, P. Courel, M-F. Ducousso, M. Guenegou, M-C. Le Rhun, J. Levasseur, J-E. Loisel, C. and Togola, M. Use of green and red spectral bands for better evaluation of active plant formations. Remote sensing and mapping. Ed. AUPELF-UREF. Les Presses de l’Université du Québec, 1993. 203-209.
[47]	CSE Use of high-resolution satellite imagery. Technical Report, Edit, Ecological Monitoring Center, Dakar, Senegal, 1996. pp. 59.
[48]	Chatelain, C. Pichiger, R. and Gautier, L. "Spectral signs and degradation of the dense wet forest cover of Côte d’Ivoire". In: Remote Sensing in La Francophonie: critical analysis and perspectives. Ed. AUF. 2000. 349-355.
[49]	Boulogne, M. Vulnerability of forest landscapes in Ranomafana Park (Madagascar): environmental dynamics and agroforestry trajectories. Thesis of PhD, Université Grenoble Alpes. 2016. pp. 269.
[50]	Dessay, N. The dynamics of vegetation and climate: remote sensing study of five Brazilian biomes, dense and open rainforest, Cerrados, Caatinga and Campanha Gaúcha. PhD thesis, Université Paris X Nanterre, 2006. pp. 364.
[51]	ANAT. National Plan for Spatial Development and Development (NAPDP) 2035. Provisional version, Edition, National Agency for Land Management. Dakar. Senegal, 2018. p. 277.
[52]	Rouse, J. W. Haas, R. W. Schell, J. A. Deering, D. W. and Harlem, J. C. Monitoring the vernal advancement and retrogradation (Greenwave effect) of natural vegetation. NASA/GSFC Type-III, Final Report, Greenbelt, Maryland. 1974. pp. 164.
[53]	Muller, E. "Test for a standard spectral signature database: application in the Garonne Valley (France)". In: Remote Sensing in La Francophonie: critical analysis and perspectives. Ed. AUF. 2000. 349-355.
[54]	Desclees, B. Mayaux, P. Hansen, M. Lola Amani, P. Sannier, C. Mertens, B. Häusler, T. Ngamabou Siwe, R. Poilve, H. Gond, V. Rahm, M. Haarpaintner, J. and Kibambe Lubamba, J. P. "Evolution of forest cover from national to regional level and drivers of change". In: De Wasseige C. (ed.), Flynn J. (ed.), Louppe D. (ed.), Hiol Hiol F. (ed.), Mayaux P. (ed.) The forests of the Congo Basin: state of the forests 2013. Neufchâteau: Weyrich, 2014. 21-46.
[55]	Fanchette, S. A peripheral region in the test of decentralization: Fuladu, the Peul country of Upper-Casamance (Senegal). Paris, Karthala, (Men and Companies). IRD. 2011. pp. 393.
[56]	Aubreville, A. Climates, forests and desertification of tropical Africa. Geographic, maritime and colonial publishing company, Paris. 1949. pp. 351.
[57]	Jacquin, A. Vegetation dynamics of savannas in relation to the use of fires in Madagascar. Time series analysis of remote sensing images. PhD thesis in Functioning of ecosystems and agrosystems, University of Toulouse. 2010. pp. 144.
[58]	Chave, J. The spatial-temporal dynamics of the rainforest. Ann. Phys. Fr. 25, 2000. 6, p. 184.

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Boubacar Solly, El Hadji Balla Dieye, Oumar Sy. (2020). Remote Sensing Mapping of Land Use and Land Cover Changes in Upper Casamance, Senegal, 1987-2018. American Journal of Remote Sensing, 8(2), 35-49. https://doi.org/10.11648/j.ajrs.20200802.11

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ACS Style

Boubacar Solly; El Hadji Balla Dieye; Oumar Sy. Remote Sensing Mapping of Land Use and Land Cover Changes in Upper Casamance, Senegal, 1987-2018. Am. J. Remote Sens. 2020, 8(2), 35-49. doi: 10.11648/j.ajrs.20200802.11

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AMA Style

Boubacar Solly, El Hadji Balla Dieye, Oumar Sy. Remote Sensing Mapping of Land Use and Land Cover Changes in Upper Casamance, Senegal, 1987-2018. Am J Remote Sens. 2020;8(2):35-49. doi: 10.11648/j.ajrs.20200802.11

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@article{10.11648/j.ajrs.20200802.11,
  author = {Boubacar Solly and El Hadji Balla Dieye and Oumar Sy},
  title = {Remote Sensing Mapping of Land Use and Land Cover Changes in Upper Casamance, Senegal, 1987-2018},
  journal = {American Journal of Remote Sensing},
  volume = {8},
  number = {2},
  pages = {35-49},
  doi = {10.11648/j.ajrs.20200802.11},
  url = {https://doi.org/10.11648/j.ajrs.20200802.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajrs.20200802.11},
  abstract = {In order to study the evolution of land use and the changes in land cover in Upper Casamance, from Landsat images acquired in 1987 and 2018, we used a method of multistage unsupervised classification. Recently developed to mapping and quantification of vegetation land cover changes in West-African coastal, this method is based on the following stages: first classification (K-means) over 15 classes, interpretation of the spectral signatures of the resulting classes followed by reclassification according to the chosen nomenclature, creation of thematic masks, classifications on masks, and finally reclassification. With the only difference, our study aims also to contribute, methodologically, to the knowledge of the spectral profiles of plant formation types. On a thematic level, the results show that between 1987 and 2018, forest areas decreased by 377,118.7 ha (or 27.4%), while wooded areas and agricultural and soil surfaces increased by 263,172.4 ha (or 19.1%) and 1560 75.5 ha (11.3%). In terms of change, deforestation by increasing agricultural and soil surfaces is noted along the border with the Gambia, savanization and anthropization is noted along the central part, and stability of forest surfaces followed by a slight increase in savannas and agricultural and soil surfaces is noted in the south.},
 year = {2020}
}

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TY  - JOUR
T1  - Remote Sensing Mapping of Land Use and Land Cover Changes in Upper Casamance, Senegal, 1987-2018
AU  - Boubacar Solly
AU  - El Hadji Balla Dieye
AU  - Oumar Sy
Y1  - 2020/09/28
PY  - 2020
N1  - https://doi.org/10.11648/j.ajrs.20200802.11
DO  - 10.11648/j.ajrs.20200802.11
T2  - American Journal of Remote Sensing
JF  - American Journal of Remote Sensing
JO  - American Journal of Remote Sensing
SP  - 35
EP  - 49
PB  - Science Publishing Group
SN  - 2328-580X
UR  - https://doi.org/10.11648/j.ajrs.20200802.11
AB  - In order to study the evolution of land use and the changes in land cover in Upper Casamance, from Landsat images acquired in 1987 and 2018, we used a method of multistage unsupervised classification. Recently developed to mapping and quantification of vegetation land cover changes in West-African coastal, this method is based on the following stages: first classification (K-means) over 15 classes, interpretation of the spectral signatures of the resulting classes followed by reclassification according to the chosen nomenclature, creation of thematic masks, classifications on masks, and finally reclassification. With the only difference, our study aims also to contribute, methodologically, to the knowledge of the spectral profiles of plant formation types. On a thematic level, the results show that between 1987 and 2018, forest areas decreased by 377,118.7 ha (or 27.4%), while wooded areas and agricultural and soil surfaces increased by 263,172.4 ha (or 19.1%) and 1560 75.5 ha (11.3%). In terms of change, deforestation by increasing agricultural and soil surfaces is noted along the border with the Gambia, savanization and anthropization is noted along the central part, and stability of forest surfaces followed by a slight increase in savannas and agricultural and soil surfaces is noted in the south.
VL  - 8
IS  - 2
ER  -

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Author Information

Boubacar Solly

Department of Geography, Assane SECK University of Ziguinchor, Ziguinchor, Senegal
El Hadji Balla Dieye

Department of Geography, Assane SECK University of Ziguinchor, Ziguinchor, Senegal
Oumar Sy

Department of Geography, Assane SECK University of Ziguinchor, Ziguinchor, Senegal

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APA Style

Boubacar Solly, El Hadji Balla Dieye, Oumar Sy. (2020). Remote Sensing Mapping of Land Use and Land Cover Changes in Upper Casamance, Senegal, 1987-2018. American Journal of Remote Sensing, 8(2), 35-49. https://doi.org/10.11648/j.ajrs.20200802.11

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ACS Style

Boubacar Solly; El Hadji Balla Dieye; Oumar Sy. Remote Sensing Mapping of Land Use and Land Cover Changes in Upper Casamance, Senegal, 1987-2018. Am. J. Remote Sens. 2020, 8(2), 35-49. doi: 10.11648/j.ajrs.20200802.11

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AMA Style

Boubacar Solly, El Hadji Balla Dieye, Oumar Sy. Remote Sensing Mapping of Land Use and Land Cover Changes in Upper Casamance, Senegal, 1987-2018. Am J Remote Sens. 2020;8(2):35-49. doi: 10.11648/j.ajrs.20200802.11

Copy | Download

@article{10.11648/j.ajrs.20200802.11,
  author = {Boubacar Solly and El Hadji Balla Dieye and Oumar Sy},
  title = {Remote Sensing Mapping of Land Use and Land Cover Changes in Upper Casamance, Senegal, 1987-2018},
  journal = {American Journal of Remote Sensing},
  volume = {8},
  number = {2},
  pages = {35-49},
  doi = {10.11648/j.ajrs.20200802.11},
  url = {https://doi.org/10.11648/j.ajrs.20200802.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajrs.20200802.11},
  abstract = {In order to study the evolution of land use and the changes in land cover in Upper Casamance, from Landsat images acquired in 1987 and 2018, we used a method of multistage unsupervised classification. Recently developed to mapping and quantification of vegetation land cover changes in West-African coastal, this method is based on the following stages: first classification (K-means) over 15 classes, interpretation of the spectral signatures of the resulting classes followed by reclassification according to the chosen nomenclature, creation of thematic masks, classifications on masks, and finally reclassification. With the only difference, our study aims also to contribute, methodologically, to the knowledge of the spectral profiles of plant formation types. On a thematic level, the results show that between 1987 and 2018, forest areas decreased by 377,118.7 ha (or 27.4%), while wooded areas and agricultural and soil surfaces increased by 263,172.4 ha (or 19.1%) and 1560 75.5 ha (11.3%). In terms of change, deforestation by increasing agricultural and soil surfaces is noted along the border with the Gambia, savanization and anthropization is noted along the central part, and stability of forest surfaces followed by a slight increase in savannas and agricultural and soil surfaces is noted in the south.},
 year = {2020}
}

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TY  - JOUR
T1  - Remote Sensing Mapping of Land Use and Land Cover Changes in Upper Casamance, Senegal, 1987-2018
AU  - Boubacar Solly
AU  - El Hadji Balla Dieye
AU  - Oumar Sy
Y1  - 2020/09/28
PY  - 2020
N1  - https://doi.org/10.11648/j.ajrs.20200802.11
DO  - 10.11648/j.ajrs.20200802.11
T2  - American Journal of Remote Sensing
JF  - American Journal of Remote Sensing
JO  - American Journal of Remote Sensing
SP  - 35
EP  - 49
PB  - Science Publishing Group
SN  - 2328-580X
UR  - https://doi.org/10.11648/j.ajrs.20200802.11
AB  - In order to study the evolution of land use and the changes in land cover in Upper Casamance, from Landsat images acquired in 1987 and 2018, we used a method of multistage unsupervised classification. Recently developed to mapping and quantification of vegetation land cover changes in West-African coastal, this method is based on the following stages: first classification (K-means) over 15 classes, interpretation of the spectral signatures of the resulting classes followed by reclassification according to the chosen nomenclature, creation of thematic masks, classifications on masks, and finally reclassification. With the only difference, our study aims also to contribute, methodologically, to the knowledge of the spectral profiles of plant formation types. On a thematic level, the results show that between 1987 and 2018, forest areas decreased by 377,118.7 ha (or 27.4%), while wooded areas and agricultural and soil surfaces increased by 263,172.4 ha (or 19.1%) and 1560 75.5 ha (11.3%). In terms of change, deforestation by increasing agricultural and soil surfaces is noted along the border with the Gambia, savanization and anthropization is noted along the central part, and stability of forest surfaces followed by a slight increase in savannas and agricultural and soil surfaces is noted in the south.
VL  - 8
IS  - 2
ER  -

Copy | Download