乌拉圭原生森林外来木本入侵物种的遥感研究

Olivera
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引用次数: 1

摘要

外来物种对生态系统的入侵已被确定为全球生物多样性丧失的第二大原因,也是最难扭转的威胁之一。在乌拉圭,外来入侵物种的引进和传播已被确定为一个严重的环境问题,可能成为原生森林目前面临的最大危险。IAS通常代表森林冠层的光学差异,因此可以远程检测。在该国森林中分布最广、最具侵略性的两种木质IAS是女贞草(Ligustrum lucidum)和皂荚(Gleditsia triacanthos)。本研究的目的是利用遥感技术在乌拉圭原生林(主要是这两个物种)内对IAS进行空间识别。这项工作基于中分辨率卫星图像(Landsat)的多光谱数据,并使用归一化差分分数指数(NDFI)进行分类。NDFI对冠层覆盖度敏感,通过亚像元光谱混合分析(SMA)计算,将每个像元的反射率信息分解成分数。结果显示,这些IAS入侵的原始森林面积为22,009 ha,总体精度为87.6%,占该国原始森林总面积的2.63%。这项工作的结果将有助于从地理上分析IAS在森林中的入侵,并将其与可能的驱动因素联系起来。此外,该地图现在可作为相关信息,用于在该国设计IAS预防、缓解、恢复和最终根除战略。
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Remote sensing of invasive alien woody species in Uruguayan native forests
The invasion of ecosystems by exotic species has been identified as the second cause of biodiversity loss worldwide, and is one of the most difficult threats to reverse. In Uruguay, the introduction and spread of invasive alien species (IAS) has been identified as a serious environmental problem, becoming perhaps the greatest danger that native forests currently face. IAS often represents optical differences in the forest canopy and can therefore be detected remotely. The two most widespread and aggressive woody IAS in the country's forests are Ligustrum lucidum and Gleditsia triacanthos . The objective of this study was to spatially identify IAS within the native forest of Uruguay, mainly these two species, using remote sensing techniques. This work is based on multispectral data from medium-resolution satellite images (Landsat) and uses the normalized difference fraction index (NDFI) for classification. The NDFI is sensitive to canopy coverage and is calculated through a sub-pixel spectral mixture analysis (SMA), decomposing the reflectance information for each pixel into fractions. The results showed an area of 22,009 ha of native forest invaded by these IAS, with an overall accuracy of 87.6%, representing 2.63% of the total native forest area in the country. The results presented in this work will help to geographically analyze the invasion by IAS in the forest, linking it to possible drivers. Furthermore, this map can now be used as relevant information when designing IAS prevention, mitigation, restoration, and eventual eradication strategies in the country.
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