Exploring the 4D scales of eco-geomorphic interactions along a river corridor using repeat UAV Laser Scanning (UAV-LS), multispectral imagery, and a functional traits framework
Exploring the 4D scales of eco-geomorphic interactions along a river corridor using repeat UAV Laser Scanning (UAV-LS), multispectral imagery, and a functional traits framework
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DOI：
10.5194/esurf-2021-102
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发表时间：
2022-01
期刊：
影响因子：
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通讯作者：
Chris Tomsett;J. Leyland
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文献类型：
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作者：
Chris Tomsett;J. Leyland
抽象的。植被在河流过程和形态演化的调节中起着至关重要的作用。然而，充分捕捉植被特征的空间变异性和复杂性仍然是一个挑战。目前，大多数寻求解决这些问题的研究要么在单个植物规模上进行，要么通过更大规模的批量分类进行，前者寻求描述植被流相互作用的特征，后者寻求识别植被类型的空间变化。在这里，我们设计了一种使用无人机激光扫描和多光谱图像提取功能性植被特征的方法，并将其升级以达到规模行会分类。对形态变化进行同步监测，以确定不同行会之间的生态地貌联系以及系统在长期十年变化背景下的地貌响应。通过基于地面和无人机激光扫描分析的定量结构模型识别了四个行会，并通过图像分析识别了另外两个行会。这些被升级到达到规模的公会分类，总体准确度达到 80%，并与所探索的地貌活动的强度相关联。我们表明，不同的植被群通过稳定河岸而在影响形态变化方面发挥着作用，但在之前的长期分析中，这种影响的限制是显而易见的。这项研究表明，遥感为生态地貌研究中基于特征的方法的扩展困难提供了解决方案，并且这些方法可以使用机载激光扫描和卫星图像数据集应用于更大的区域。
Abstract. Vegetation plays a critical role in the modulation of fluvial process and morphological evolution. However, adequately capturing the spatial variability and complexity of vegetation characteristics remains a challenge. Currently, most of the research seeking to address these issues takes place at either the individual plant scale or via larger scale bulk classifications, with the former seeking to characterise vegetation-flow interactions and the latter identifying spatial variation in vegetation types. Herein, we devise a method which extracts functional vegetation traits using UAV laser scanning and multispectral imagery, and upscale these to reach scale guild classifications. Simultaneous monitoring of morphological change is undertaken to identify eco-geomorphic links between different guilds and the geomorphic response of the system in the context of long-term decadal changes. Identification of four guilds from quantitative structural modelling based on analysis of terrestrial and UAV based laser scanning and two further guilds from image analysis was achieved. These were upscaled to reach-scale guild classifications with an overall accuracy of 80 % and links to magnitudes of geomorphic activity explored. We show that different vegetation guilds have a role in influencing morphological change through the stabilisation of banks, but that limits on this influence are evident in the prior long-term analysis. This research reveals that remote sensing offers a solution to the difficulty of scaling traits-based approaches for eco-geomorphic research, and that these methods may be applied to larger areas using airborne laser scanning and satellite imagery datasets.