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Auteur Vincent R. Nyirenda |
Documents disponibles écrits par cet auteur (2)
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Modelling areas for sustainable forest management in a mining and human dominated landscape: A Geographical Information System (GIS)- Multi-Criteria Decision Analysis (MCDA) approach / Xavier Takam Tiamgne in Annals of GIS, vol 28 n° 3 (July 2022)
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Titre : Modelling areas for sustainable forest management in a mining and human dominated landscape: A Geographical Information System (GIS)- Multi-Criteria Decision Analysis (MCDA) approach Type de document : Article/Communication Auteurs : Xavier Takam Tiamgne, Auteur ; Félix Kanungwe Kalaba, Auteur ; Vincent R. Nyirenda, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 343 - 357 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] analyse multicritère
[Termes IGN] gestion forestière durable
[Termes IGN] modélisation environnementale
[Termes IGN] outil d'aide à la décision
[Termes IGN] processus de hiérarchisation analytique
[Termes IGN] protection des forêts
[Termes IGN] système d'information géographique
[Termes IGN] ZambieRésumé : (auteur) Protected forest areas are fraught with severe threats from mining, agriculture and settlement expansion, and unsustainable use of forest resources. Due to funding and technical challenges, the inadequate monitoring and lack of information limits the conservation efforts in Zambia in general and Solwezi district in particular. Field-based methods in monitoring forest quality and suitability are time consuming and inefficient especially in inaccessible areas. However, with the advent of technology, Geographical Information System (GIS) and remote sensing, important data for forest quality can easily be accessed. This study aimed at assessing the state of protected forest areas in Zambia’s Solwezi Copper mining district, prone to forest fragmentation. Furthermore, this study identifies suitable areas for conservation, based on standardized criteria that combine Multi Criteria Decision Analysis (MCDA) and GIS approach. A suitability model was developed for the selection of the suitable areas, and elimination of the unsuitable ones, using GIS and Analytical Hierarchy Process (AHP). Five suitability criteria and two restriction criteria were used in this model. The results show different ranked levels of suitability which include 15.4% restricted, 18.1% lowly suitable, 14.9% moderately suitable, 21.2% highly suitable and 30.4% extremely suitable. Our approach informs conservationists, and other stakeholders about the status of protected forest areas and avails novel opportunities for creating new ones. This study’s modelling approach can be a prerequisite to sustainable forest management by policy makers and practitioners, and an essential input into forest monitoring. Numéro de notice : A2022-642 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/19475683.2022.2026469 Date de publication en ligne : 17/01/2022 En ligne : https://doi.org/10.1080/19475683.2022.2026469 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101450
in Annals of GIS > vol 28 n° 3 (July 2022) . - pp 343 - 357[article]An assessment of forest loss and its drivers in protected areas on the Copperbelt province of Zambia: 1972–2016 / Darius Phiri in Geomatics, Natural Hazards and Risk, vol 13 (2022)
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Titre : An assessment of forest loss and its drivers in protected areas on the Copperbelt province of Zambia: 1972–2016 Type de document : Article/Communication Auteurs : Darius Phiri, Auteur ; Collins Chanda, Auteur ; Vincent R. Nyirenda, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 148 - 166 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] aire protégée
[Termes IGN] analyse d'image orientée objet
[Termes IGN] analyse diachronique
[Termes IGN] carte d'occupation du sol
[Termes IGN] carte thématique
[Termes IGN] classification par arbre de décision
[Termes IGN] couvert forestier
[Termes IGN] déboisement
[Termes IGN] détection de changement
[Termes IGN] gestion forestière durable
[Termes IGN] protection de la biodiversité
[Termes IGN] ZambieRésumé : (auteur) In sub-Saharan Africa, protected areas provide a platform for conserving biodiversity. However, these areas are facing massive pressure due to deforestation, and information on forest dynamics and factors driving the changes in protected areas is generally lacking. This study has two objectives: (1) to assess forest cover changes that have occurred between 1972 and 2016 in Copperbelt Province’s protected areas, and (2) understand the drivers of forest cover changes. The study used thematic land cover maps for six selected years, which were classified using an object-based image analysis (OBIA) approach. We also applied a Classification Tree (CT) approach to assess the drivers of forest cover changes using R statistical software. The findings showed that forest cover in protected areas has been characterised by massive deforestation due to various factors. Between 1972 and 2016, primary and secondary forests showed a decrease of 2,226.43 km2 (11.06%) and an increase of 1,082.93 km2 (4.05%), respectively. The major factors driving forest changes include the levels of precipitation, human population density, elevation, distance from roads, towns and rivers. This study presents consistent information for long-term forest monitoring in protected areas, and informs decision-makers on the levels of deforestation and their drivers for effective forest management. Numéro de notice : A2022-092 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET/IMAGERIE Nature : Article DOI : 10.1080/19475705.2021.2017021 Date de publication en ligne : 21/12/2021 En ligne : https://doi.org/10.1080/19475705.2021.2017021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99515
in Geomatics, Natural Hazards and Risk > vol 13 (2022) . - pp 148 - 166[article]