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Vegetation monitoring in refugee-hosting areas in South Sudan

机译:南苏丹难民托管区植被监测

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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.
机译:大众群体位移对生态系统进行了额外的压力,往往导致与东道国社区的冲突,特别是在大型难民或国内流离失所者(IDP)营地的情况下。因此,需要对环境影响的评估,并根据此基于这一目标,对主机和难民社区之间的自然资源的可持续管理。我们提出了一种基于高(LANDSAT 5,7和8)和非常高(WorldView-2)分辨率地球观测数据的方法,以建立森林清单,将遥感卫星数据分析与南苏丹的地面观测相结合。由此产生的森林库存映射包括植被覆盖,树种和植被变化的地图产品。我们区分植被类型草地,灌木/树大草原,大草原林地和林地。对于大草原林地和林地,我们进一步应用了树种分类,区分了红色金合欢,沙漠日期树,银河和杜马掌。树木种类分类的平均准确性约为LANDSAT和WorldView的分类率约为61.0%,具有良好的棕榈树和红色金合欢实现的最佳成果,平均精度分别为88%和53%。关于植被变化的产品表明植被减少到难民营地/沉降周围内部和周围环境中的50%。由此产生的地图可以用于估计可访问的木材资源并识别潜在的收获区域。此外,他们可以支持基于社区森林管理的难民和东道国社区的建筑和烹饪目的的可持续使用木材的定义。

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