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Allometric relationships for selected macrophytes of kettle holes in northeast Germany as a basis for efficient biomass estimation using unmanned aerial systems (UAS)

机译:东北德国水壶孔的选定宏观物质的同传关系作为使用无人机空中系统(UAS)有效生物量估计的基础

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Quantifying plant biomass in ecosystems is an essential basis for many ecological questions. A direct estimation of macrophyte biomass proves to be difficult for the large number of kettle holes in Pleistocene landscapes, due to their strong heterogeneities. This study compared a classical non-destructive method for biomass estimation based on allometric relationships built from a larger selection of plant trait variables with regressions only based on plant height and cover of four macrophyte species typical for kettle holes in northeast Germany (i.e. Carex riparia, Phalaris arundinacea, Persicaria amphibia, Rorippa amphibia). Their predictive power and potential applicability for remotely sensed biomass estimation using unmanned aerial systems (UAS) was evaluated. The usage of several in-situ measured plant traits of individual plants revealed best macrophyte biomass predictions (R-2 = 0.84 to 0.95). Yet, using only plant height and cover to predict biomass still showed a moderate to good correlation (R-2 = 0.52 to 0.81). Using P. anmdinacea as an example, we demonstrated for one kettle hole the potential of calculating plant patch height from digital surface models (DSM) derived from UAS RGB images processed with structure-from-motion (SfM) photogrammetry. After applying a site-specific correction factor for discrepancies between reference field measurements of plant heights and DSM derived plant heights, we were able to calculate P. anmdinacea biomass of the entire kettle hole based on allometric relationships using plant height and cover. Finally, we briefly discuss how further methodological development can improve UAS-derived plant height as predictor variable for biomass estimation.
机译:在生态系统中量化植物生物质是许多生态问题的重要基础。由于其强烈的异质性,对宏观物质生物量的直接估计被证明很难对更新的景观中的大量水壶孔。该研究比较了基于从植物高度和植物高度和覆盖德国水壶孔的植物高度和四种宏粒孔的植物高度和覆盖的植物性状变量,基于植物性状变量的种类关系的种类关系进行了经典的非破坏性方法Phalaris arundinacea,Persicaria amphibia,罗利帕两栖动物)。评估了使用无人空中系统(UAS)的预测力和对远程感测生物质估计的潜在适用性。几种原位测量的个体植物的使用情况显示出最佳的宏体生物质预测(R-2 = 0.84至0.95)。然而,仅使用植物高度和盖子来预测生物质仍然显示出中等至良好的相关性(R-2 = 0.52至0.81)。使用P.Anmdinacea作为示例,我们向一个水壶孔证明了从使用结构 - 来自运动(SFM)摄影测量的UAS RGB图像的数字表面模型(DSM)计算植物贴片高度的电位。在施加特定于场地的校正因子以进行植物高度和DSM衍生的植物高度的参考现场测量之间的差异,我们能够根据使用植物高度和盖子的同种关系来计算整个水壶孔的P.Anmdinacea生物量。最后,我们简要讨论了进一步的方法,如何改善uas衍生的植物高度作为生物质估计的预测变量。

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