Environmental Research Institute, University of Waikato, Hamilton, New Zealand.
PeerJ. 2022 May 13;10:e13450. doi: 10.7717/peerj.13450. eCollection 2022.
Several smartphone applications have been developed for the purpose of low-cost and convenient assessments of vegetation canopy structure and understorey illumination. Like standard hemispherical photography, most of these applications require user decisions about image processing, posing challenges for repeatability of measurements. Here I report a test of CanopyCapture, an application that instantaneously estimates percentage canopy gap fraction without any input from the user, and has the added advantage of an intuitive levelling mechanism.
Gap fraction estimates by CanopyCapture were compared with gap fraction values computed by the LAI-2200C Canopy Analyzer, in two contrasting evergreen temperate forests in New Zealand: an even-aged southern beech () stand and an old-growth podocarp/broadleaf forest. These comparisons were repeated using a wide-angle adapter to enhance the smartphone camera's field of view from 45 to 65°. I also asked if CanopyCapture results depended on sky condition (sunny . overcast) and on the type of smartphone used.
CanopyCapture output was significantly correlated with gap fraction computed by the LAI-2200C (R = 0.39), and use of the wide-angle adapter lifted this value to 0.56. However, CanopyCapture output was not significantly correlated with LAI-2200C output in the even-aged stand, where there was less spatial variation in canopy structure. Despite being much less sensitive to variation in gap fraction than the LAI-2200C, CanopyCapture was nevertheless able to detect differences in average gap fraction between the two forests studied. CanopyCapture results beneath intact canopies were not significantly affected by sky condition, but reflection of direct light off tree trunks in sunny weather caused slight overestimation of gap fraction beneath broken canopies and gaps. Uneven or patchy cloud cover can also cause erroneous readings beneath large canopy openings. Three different models of smartphone gave different results.
CanopyCapture offers a rapid and repeatable proxy for comparisons of average canopy gap fraction in multiple stands/forests, provided large sample sizes are used. Measurement under even overcast skies is recommended, and studies involving multiple operators will need to standardize smartphones to ensure comparability of results. Although wide-angle adapters can improve performance, CanopyCapture's low sensitivity prevents high-resolution comparisons of the light environments of individual understorey plants within a stand.
已经开发出了一些智能手机应用程序，用于低成本和方便地评估植被冠层结构和林下光照。与标准半球摄影类似，这些应用程序大多需要用户决定图像处理，这给测量的可重复性带来了挑战。在此，我报告了 CanopyCapture 的测试结果，CanopyCapture 是一种应用程序，它可以即时估算冠层间隙分数，而无需用户输入任何信息，并且具有直观的水平调节机制。
在新西兰的两个截然不同的常绿温带森林中，即一个均匀年龄的南方山毛榉（）林和一个古老的罗汉松/阔叶林中，比较了 CanopyCapture 的间隙分数估算值与 LAI-2200C 冠层分析仪计算出的间隙分数值。使用广角适配器将智能手机的视野从 45 度扩展到 65 度，重复了这些比较。我还询问了 CanopyCapture 的结果是否取决于天空条件（晴天、阴天）和使用的智能手机类型。
CanopyCapture 的输出与 LAI-2200C 计算的间隙分数显著相关（R = 0.39），使用广角适配器将该值提高到 0.56。然而，在冠层结构空间变化较小的均匀年龄林中，CanopyCapture 的输出与 LAI-2200C 的输出没有显著相关。尽管 CanopyCapture 对间隙分数的变化没有 LAI-2200C 那么敏感，但它仍然能够检测到研究的两个森林之间平均间隙分数的差异。在完整树冠下，CanopyCapture 的结果不受天空条件的显著影响，但晴天直射光从树干反射会导致树冠和缝隙下的间隙分数轻微高估。不均匀或块状的云层覆盖也会导致大树冠开口下的错误读数。三种不同型号的智能手机给出了不同的结果。
CanopyCapture 提供了一种快速且可重复的方法，可用于比较多个林分/森林的平均冠层间隙分数，前提是使用大样本量。建议在均匀阴天的天空下进行测量，并需要由多个操作人员参与的研究来标准化智能手机，以确保结果的可比性。尽管广角适配器可以提高性能，但 CanopyCapture 的低灵敏度阻止了对林分内单个林下植物光照环境的高分辨率比较。
