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Vegetation monitoring in refugee-hosting areas in South Sudan


Leiterer, Reik; Bloesch, Urs; Wulf, Hendrik; Eugster, Sebastian; Joerg, Philip Claudio (2018). Vegetation monitoring in refugee-hosting areas in South Sudan. Applied Geography, 93:1-15.

Abstract

Mass population displacements put additional stress on the ecosystems and often lead to conflicts with the host communities, especially in the case of large refugee or Internally Displaced Person (IDP) camps. Therefore, there is need for the assessment of environmental impacts and, based on this, the sustainable management of natural resources between host and refugee communities. We propose a method based on high (Landsat 5,7 and 8) and very high (WorldView-2) resolution Earth Observation data to establish forest inventories combining the analysis of remote sensing satellite data along with ground-based observations in South Sudan. The resulting forest inventory mapping comprises map products on vegetation cover, tree species, and vegetation changes. We distinguished between the vegetation types grassland, shrub/tree savanna, savanna woodland, and woodland. For savanna woodland and woodland, we furthermore applied a tree species classification, differentiating between Red acacia, Desert date tree, Silak, and Doum palm. The tree species classification yielded in mean accuracies of about 61.0% for both the Landsat and WorldView based classifications, with the best results achieved for Desert palm tree and red acacia with average accuracies of 88% and 53%, respectively. The product about vegetation changes indicates a decrease of vegetation up to 50% within and in the surroundings of the refugee camps/settlement. The resulting maps can serve to estimate accessible wood resources and to identify potential harvest areas. In addition, they can support the definition of a sustainable use of wood for construction and cooking purposes for the refugee and host communities based on a community forest management.

Abstract

Mass population displacements put additional stress on the ecosystems and often lead to conflicts with the host communities, especially in the case of large refugee or Internally Displaced Person (IDP) camps. Therefore, there is need for the assessment of environmental impacts and, based on this, the sustainable management of natural resources between host and refugee communities. We propose a method based on high (Landsat 5,7 and 8) and very high (WorldView-2) resolution Earth Observation data to establish forest inventories combining the analysis of remote sensing satellite data along with ground-based observations in South Sudan. The resulting forest inventory mapping comprises map products on vegetation cover, tree species, and vegetation changes. We distinguished between the vegetation types grassland, shrub/tree savanna, savanna woodland, and woodland. For savanna woodland and woodland, we furthermore applied a tree species classification, differentiating between Red acacia, Desert date tree, Silak, and Doum palm. The tree species classification yielded in mean accuracies of about 61.0% for both the Landsat and WorldView based classifications, with the best results achieved for Desert palm tree and red acacia with average accuracies of 88% and 53%, respectively. The product about vegetation changes indicates a decrease of vegetation up to 50% within and in the surroundings of the refugee camps/settlement. The resulting maps can serve to estimate accessible wood resources and to identify potential harvest areas. In addition, they can support the definition of a sustainable use of wood for construction and cooking purposes for the refugee and host communities based on a community forest management.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Uncontrolled Keywords:Tourism, Leisure and Hospitality Management, Geography, Planning and Development, Forestry, General Environmental Science
Language:English
Date:2018
Deposited On:27 Jun 2018 12:51
Last Modified:13 Oct 2019 05:49
Publisher:Elsevier
ISSN:0143-6228
OA Status:Closed
Publisher DOI:https://doi.org/10.1016/j.apgeog.2018.01.013

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