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Mapping and estimating land change between 2001 and 2013 in a heterogeneous landscape in West Africa: Loss of forestlands and capacity building opportunities / Hèou Maléki Badjana in International journal of applied Earth observation and geoinformation, vol 63 (December 2017)  

Public [article]  inInternational journal of applied Earth observation and geoinformation > vol 63 (December 2017) . - pp 15 - 23 Titre : Mapping and estimating land change between 2001 and 2013 in a heterogeneous landscape in West Africa: Loss of forestlands and capacity building opportunities Type de document : Article/Communication Auteurs : Hèou Maléki Badjana, Auteur ; Pontus Olofsson, Auteur ; Curtis E. Woodcock, Auteur ; Jörg Helmschrot, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 15 - 23 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Afrique occidentale [Termes IGN] analyse diachronique [Termes IGN] Bénin [Termes IGN] changement d'occupation du sol [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] déboisement [Termes IGN] forêt [Termes IGN] image Landsat-8 [Termes IGN] image Landsat-ETM+ [Termes IGN] image Landsat-OLI [Termes IGN] logiciel libre [Termes IGN] occupation du sol [Termes IGN] Orfeo Tool Box [Termes IGN] QGIS [Termes IGN] Togo Résumé : (auteur) In West Africa, accurate classification of land cover and land change remains a big challenge due to the patchy and heterogeneous nature of the landscape. Limited data availability, human resources and technical capacities, further exacerbate the challenge. The result is a region that is among the more understudied areas in the world, which in turn has resulted in a lack of appropriate information required for sustainable natural resources management. The objective of this paper is to explore open source software and easy-to-implement approaches to mapping and estimation of land change that are transferrable to local institutions to increase capacity in the region, and to provide updated information on the regional land surface dynamics. To achieve these objectives, stable land cover and land change between 2001 and 2013 in the Kara River Basin in Togo and Benin were mapped by direct multitemporal classification of Landsat data by parameterization and evaluation of two machine-learning algorithms. Areas of land cover and change were estimated by application of an unbiased estimator to sample data following international guidelines. A prerequisite for all tools and methods was implementation in an open source environment, and adherence to international guidelines for reporting land surface activities. Findings include a recommendation of the Random Forests algorithm as implemented in Orfeo Toolbox, and a stratified estimation protocol − all executed in the QGIS graphical use interface. It was found that despite an estimated reforestation of 10,0727 ± 3480 ha (95% confidence interval), the combined rate of forest and savannah loss amounted to 56,271 ± 9405 ha (representing a 16% loss of the forestlands present in 2001), resulting in a rather sharp net loss of forestlands in the study area. These dynamics had not been estimated prior to this study, and the results will provide useful information for decision making pertaining to natural resources management, land management planning, and the implementation of the United Nations Collaborative Programme on Reducing Emissions from Deforestation and Forest Degradation in Developing Countries (UN-REDD). Numéro de notice : A2017-411 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jag.2017.07.006 En ligne : https://doi.org/10.1016/j.jag.2017.07.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86298 [article]