Characterising forest gap fraction with terrestrial lidar and photography: An examination of relative limitations
Characterising forest gap fraction with terrestrial lidar and photography: An examination of relative limitations
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DOI：
10.1016/j.agrformet.2014.01.012
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发表时间：
2014-06-01
影响因子：
6.2
通讯作者：
Huntley, Brian
中科院分区：
文献类型：
--
作者：
Hancock, Steven;Essery, Richard;Huntley, Brian
先前的研究表明，陆地激光雷达能够描述森林冠层的特征，但与半球形相机摄影相比，激光雷达低估了间隙率。本文对一系列森林结构（在受雪影响的地区）的激光雷达和相机衍生的间隙分数进行了详细的比较，并分析了任何分歧的原因。一台地面激光扫描仪（徕卡C10首次返回系统）被带到瑞典北部的阿比斯库（稀疏的白桦林）和芬兰的索丹凯拉（云杉和松林），分别扫描了五个不同密度的地块（尽管一个阿比斯库地块由于地理位置问题而被拒绝）。采用传统的半球面照片对间隙率进行了比较。结论是，对于测试的站点，可以通过使用返回强度考虑部分命中来消除报告的缺口分数低估。使用的扫描密度（每20米× 20米图扫描5-8次）足以确保激光束遮挡不显著。激光雷达数据采样密度的选择很重要，但在一定的采样密度下，间隙分数估计对进一步的变化不敏感。当所有主观参数在其完整范围内进行调整时，激光雷达间隙分数改变了约3-8%。半球形照片的手动阈值的选择被发现有很大的影响（在三个操作员之间的间隙分数高达17%的范围）。因此，我们建议，只要一个地点被足够的扫描位置覆盖，并且以足够高的分辨率采样数据，激光雷达间隙分数估计比来自相机的估计更稳定，并且避免了可变照明的问题。此外，激光雷达可以在一个地块内的每个点上确定间隙分数，而不仅仅是拍摄半球形照片的地方，从而提供更全面的树冠图像。阿比斯库的TLS（考虑强度）和相机计算的间隙分数之间的相对差异为0.7%，Sodankyla的相对均方根误差（rmse）分别为6.9%和9.8%，小于TLS和相机估计的变化，因此已经消除了偏差。(C) 2014 Elsevier B.V.版权所有
Previous studies have shown that terrestrial lidar is capable of characterising forest canopies but suggest that lidar underestimates gap fraction compared to hemispherical camera photography. This paper performs a detailed comparison of lidar to camera-derived gap fractions over a range of forest structures (in snow affected areas) and reasons for any disagreements are analysed.A terrestrial laser scanner (Leica C10 first return system) was taken to Abisko in Northern Sweden (sparse birch forests) and Sodankyla in Finland (spruce and pine forests) where five plots of varying density were scanned at each (though one Abisko plot was rejected due to geolocation issues). Traditional hemispherical photographs were taken and gap fraction estimates compared.It is concluded that, for the sites tested, the reported underestimates in gap fraction can be removed by taking partial hits into account using the return intensity. The scan density used (5-8 scans per 20 m by 20 m plot) was sufficient to ensure that occlusion of the laser beam was not significant. The choice of sampling density of the lidar data is important, but over a certain sampling density the gap fraction estimates become insensitive to further change. The lidar gap fractions altered by around 3-8% when all subjective parameters were adjusted over their complete range.The choice of manual threshold for the hemispherical photographs is found to have a large effect (up to 17% range in gap fraction between three operators). Therefore we propose that, as long as a site has been covered by sufficient scan positions and the data sampled at high enough resolution, the lidar gap fraction estimates are more stable than those derived from a camera and avoid issues with variable illumination. In addition the lidar allows the determination of gap fraction at every point within a plot rather than just where hemispherical photographs were taken, giving a much fuller picture of the canopy. The relative difference between TLS (taking intensity into account) and camera derived gap fraction was 0.7% for Abisko and -2.8% for Sodankyla with relative root mean square errors (RMSEs) of 6.9% and 9.8% respectively, less than the variation within TLS and camera estimates and so bias has been removed. (C) 2014 Elsevier B.V. All rights reserved.