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Recognition of ecological vegetation fairy circles in intertidal salt marshes from UAV LiDAR point clouds
International Journal of Applied Earth Observation and Geoinformation ( IF 7.5 ) Pub Date : 2022-09-27 , DOI: 10.1016/j.jag.2022.103029
Pengjie Tao, Kai Tan, Tao Ke, Shuai Liu, Weiguo Zhang, Jianru Yang, Xiangjie Zhu

Fairy circles (FC) are a type of spatial self-organized patterns that widely exist in various vegetation ecosystems and the accurate detection and quantitative characterization of these mysterious circles remain a technical challenge. In this study, vegetation FC in intertidal salt marshes are recognized from the derived reflectance information (backscattered intensity) and geometric quantities of light detection and ranging (LiDAR) carried on unmanned aerial vehicle (UAV). The specular effect on the UAV LiDAR intensity data over nadir regions of wet salt marshes is eliminated using the laser radar equation and Phong model where the absent distances and incidence angles are approximately retrieved on the basis of geometric and temporal relations in data collection. The FC are progressively recovered through three interconnected procedures. First, the retrieved reflectance information is used to discriminate the mudflat and vegetation points. Second, a spatial connectivity clustering algorithm is utilized on the extracted vegetation points to form individual spatially disconnected clusters. Finally, FC and regular vegetation are successfully recognized by jointly using the salient, size, and circularity features of the generated clusters. A multi-echo UAV LiDAR system is used for data collection at an intertidal salt marsh to assess the feasibility and prospects of the proposed method. Taking the manual detection results from the orthophoto generated by images of a UAV camera system as a reference, the missing detection rate, false detection rate, and area detection error of the proposed method are 6%, 9%, and 5%, respectively. Results suggest that UAV LiDAR is an extremely promising technique to characterize the geometric properties (e.g., location, size, and quantity) of FC from a holistic perspective.



中文翻译:

无人机LiDAR点云对潮间带盐沼生态植被仙圈的识别

仙女圈(FC)是一种广泛存在于各种植被生态系统中的空间自组织模式,对这些神秘圈的准确检测和定量表征仍然是一项技术挑战。在这项研究中,潮间带盐沼中的植被 FC 是从无人机(UAV)上携带的衍生反射率信息(反向散射强度)和光探测和测距(LiDAR)的几何量来识别的。使用激光雷达方程和 Phong 模型消除了湿盐沼天底区域无人机 LiDAR 强度数据的镜面效应,其中基于数据收集中的几何和时间关系近似检索了缺失的距离和入射角。FC通过三个相互关联的程序逐渐恢复。第一的,检索到的反射率信息用于区分泥滩和植被点。其次,在提取的植被点上使用空间连通性聚类算法形成单独的空间不连接聚类。最后,通过联合使用生成的簇的显着性、大小和圆形特征,成功识别了 FC 和规则植被。多回波无人机 LiDAR 系统用于潮间带盐沼的数据收集,以评估所提出方法的可行性和前景。以无人机摄像系统图像生成的正射影像的人工检测结果为参考,该方法的漏检率、误检率和区域检测误差分别为6%、9%和5%。

更新日期:2022-09-27
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