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Use of Landsat and SRTM Data to Detect Broad-Scale Biodiversity Patterns in Northwestern Amazonia

机译:利用Landsat和SRTM数据检测西北亚马逊地区的大规模生物多样性模式

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摘要

Vegetation maps are the starting point for the design of protected areas and regional conservation plans. Accurate vegetation maps are missing for much of Amazonia, preventing the development of effective and compelling conservation strategies. Here we used a network of 160 inventories across northwestern Amazonia to evaluate the use of Landsat and Shuttle Radar Topography Mission (SRTM) data to identify floristic and edaphic patterns in Amazonian forests. We first calculated the strength of the relationship between these remotely-sensed data, and edaphic and floristic patterns in these forests, and asked how sensitive these results are to image processing and enhancement. We additionally asked if SRTM data can be used to model patterns in plant species composition in our study areas. We find that variations in Landsat and SRTM data are strongly correlated with variations in soils and plant species composition, and that these patterns can be mapped solely on the basis of SRTM data over limited areas. Using these data, we furthermore identified widespread patch-matrix floristic patterns across northwestern Amazonia, with implications for conservation planning and study. Our findings provide further evidence that Landsat and SRTM data can provide a cost-effective means for mapping these forests, and we recommend that maps generated from a combination of remotely-sensed and field data be used as the basis for conservation prioritization and planning in these vast and remote forests.
机译:植被图是设计保护区和区域保护计划的起点。亚马逊河大部分地区都缺少准确的植被图,这阻碍了制定有效而引人注目的保护战略。在这里,我们使用了由西北亚马逊地区160个清单组成的网络来评估对Landsat和航天飞机雷达地形任务(SRTM)数据的使用,以识别亚马逊森林中的植物区系和前缘模式。我们首先计算了这些遥感数据与这些森林中的植被和植物区系之间的关系强度,并询问了这些结果对图像处理和增强的敏感性。我们还询问了SRTM数据是否可用于在我们研究区域的植物物种组成模式中建模。我们发现,Landsat和SRTM数据的变化与土壤和植物物种组成的变化密切相关,并且这些模式可以仅基于SRTM数据在有限区域内进行映射。利用这些数据,我们进一步确定了西北亚马逊地区广泛的斑块矩阵植物区系,对保护区规划和研究具有重要意义。我们的发现提供了进一步的证据,证明Landsat和SRTM数据可以为绘制这些森林提供一种经济有效的方法,并且我们建议将遥感和现场数据的组合生成的地图用作这些区域的保护优先次序和规划的基础广阔而偏远的森林。

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