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Remote sensing of tidal freshwater marsh elevation, channels, and vegetation structure.

机译:遥感潮汐淡水沼泽海拔,河道和植被结构。

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I mapped three elevation classes in a Mid-Atlantic tidal freshwater marsh using QuickBird multi-spectral imagery and field measurements of elevation and channel networks. The elevation map reveals heterogeneous surfaces at a 2.4 m pixel scale. Field collected vegetation cover data differed among the three elevation classes. Species richness and the number of positive associations among species were higher in the mid- and high-marsh than the low marsh. The number of negative associations among species increased with rising elevation. Random forest classification of elevation class using species cover vectors selected only Impatiens capensis and Nuphar luteum and had an out of box predictive error of 26%. My research shows that the vegetation of freshwater tidal marshes is diverse with ill-defined boundaries between distinct communities. Yet vegetation shifts beyond the traditional low and high marsh communities could be detected, which should provide a useful tool for restoration and management.
机译:我使用QuickBird多光谱图像以及高程和通道网络的野外测量绘制了大西洋中部潮汐淡水沼泽中的三个高程类别。高程图显示了2.4 m像素比例的异质表面。野外收集的植被覆盖数据在三个海拔类别之间有所不同。中沼泽和高沼泽地区的物种丰富度和物种之间的正向关联数高于低沼泽地区。物种之间的负关联数随着海拔的升高而增加。使用物种覆盖向量对海拔等级进行的随机森林分类仅选择了凤仙花和黄up,并且具有26%的现成预测误差。我的研究表明,淡水潮汐沼泽地的植被种类繁多,不同社区之间的界限不明确。然而,可以检测到植被转移超出了传统的低沼泽和高沼泽地社区,这应该为恢复和管理提供有用的工具。

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