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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Assessing the relationship between macro-faunal burrowing activity and mudflat geomorphology from UAV-based Structure-from-Motion photogrammetry
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Assessing the relationship between macro-faunal burrowing activity and mudflat geomorphology from UAV-based Structure-from-Motion photogrammetry

机译:评估从基于UAV的结构从运动摄影测量的宏观传统挖洞活动与Mudflat地貌之间的关系

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Characterisation of the ecosystem functioning of mudflats requires insight on the morphology and facies of these coastal features, but also on biological processes that influence mudflat geomorphology, such as crab bioturbation and the formation of benthic biofilms, as well as their heterogeneity at cm or less scales. Insight into this fine scale of ecosystem functioning is also important as far as minimizing errors in upscaling are concerned. The realisation of high-resolution ground surveys of these mudflats without perturbing their surface is a real challenge. Here, we address this challenge using UAV-supported photogrammetry based on the Structure-from-Motion (SfM) workflow. We produced a Digital Surface Model (DSM) and an orthophotograph at 1 cm and 0.5 cm pixel resolutions, respectively, of a mudflat in French Guiana, and mapped and classed into different size ranges intricate morphological features, including crab burrow apertures, tidal drainage creeks and depressions. We also determined subtle facies and elevation changes and slopes, and the footprint of different degrees of benthic biofilm development. The results generated at this scale of photogrammetric analysis also enabled us to relate macrofaunal crab burrowing activity to various parameters, including mudflat elevation, spatial distribution and sizes of creeks and depressions, benthic biofilm distribution, and flooding duration. SfM photogrammetry offers interesting new perspectives in fine-scale characterisation of the geomorphology, benthic activity and degree of biofilm development of dynamic muddy intertidal environments that are generally difficult of access. The main shortcomings highlighted in this study are a drift of accuracy of the DSM outside areas of ground control points and the deployment of which perturb the mudflat morphology and biology, the water-logged or very wet surfaces which generate reconstruction artefacts through the sun glint effect, and the time-consuming task of manual interpretation of extraction of features such as crab burrow apertures. On-going developments in UAV positioning integrating RTK/PPK GPS solutions for image-georeferencing and precise orientation with high-quality inertial measurement units will limit the difficulties inherent to ground control points, while conduction of surveys during homogeneous cloudy conditions could reduce the sun-glint effect. Manual extraction of image features could be automated in the future through the use of deep-learning algorithms.
机译:Mudflats的生态系统功能的特征需要了解这些沿海特征的形态和相位,也需要对影响泥板地貌的生物过程,例如蟹生物症和底栖生物膜的形成,以及它们在Cm或更小的尺度下的异质性。尽可能最大限度地减少升级错误,洞察这一细微生态系统功能的洞察也很重要。在没有扰动其表面的情况下,实现这些泥浆的高分辨率地面调查是一个真正的挑战。在这里,我们使用基于结构 - 来自运动(SFM)工作流程的UAV支持的摄影测量来解决这一挑战。我们在法国圭亚那的Mudflat分别产生了一个数字表面模型(DSM)和一个正常的像素分辨率,并分为不同尺寸范围的泥浆,绘制和归类为复杂的形态特征,包括螃蟹挖洞孔,潮汐排水溪和萧条。我们还确定了微妙的相和高程变化和斜坡,以及不同程度的底栖生物膜发育的占地面积。在这种摄影测量分析中产生的结果也使我们能够将Macrofaunal螃蟹挖洞活动与各种参数相关,包括泥滩和洼地的泥滩和凹陷,底栖生物膜分布和洪水持续时间。 SFM摄影测量提供了有趣的新视角,在微量地表征地貌,底栖活动和生物膜发育的动态潮流环境的发育程度,这通常很难进入。本研究突出的主要缺点是地面控制点外部的DSM的准确性以及涉及泥泞形态和生物学,水记录或非常潮湿的表面通过太阳闪光效应产生的部署以及手工解释提取特征的耗时任务,如螃蟹洞穴孔径。 UAV定位的持续开发集成RTK / PPK GPS解决方案的图像地理率和高质量惯性测量单位的精确取向将限制地面控制点固有的困难,同时在均匀多云条件下传导调查可能会降低阳光闪烁效果。通过使用深度学习算法,将来可以在将来自动化图像特征的手动提取。

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