Polar grid fraction as an estimator of montane tropical forest canopy structure using airborne lidar
Polar grid fraction as an estimator of montane tropical forest canopy structure using airborne lidar
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DOI：
10.1080/2150704x.2013.820003
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发表时间：
2013-11
影响因子：
3.4
通讯作者：
N. Vaughn;G. Asner;C. Giardina
中科院分区：
文献类型：
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作者：
N. Vaughn;G. Asner;C. Giardina
森林冠层的结构是光传输、利用和林下可利用性的关键决定因素。机载光探测和测距（LiDAR）已成功用于测量多种冠层结构特性，从而大大减少了绘制结构空间变化所需的实地工作。然而，迄今为止，激光雷达指标并不能反映数据中可用的三维信息的全部范围。为此，我们基于极坐标激光雷达的网格化数据，开发了一种新的度量方法——极坐标网格分数（grid），以便与野外仪器提供的叶面积指数（LAI）、间隙分数（GF）和光合有效辐射透过率百分比（tPAR）更接近。该指标总结了单一地面位置的激光雷达点返回的排列，而不是该位置周围的区域。与更传统的基于比例和高度百分位数的估计器相比，GRID估计器将GF的验证R2提高了14.5%，tPAR的验证R2提高了6.0%。采用基于14 m × 14 m移动核的地面回波比例的更传统的统计方法估计LAI仍然是最好的。通过将模型应用于整个激光雷达覆盖区域的2 × 2 m网格，当使用基于比例和基于高度百分位数的估计值时，所有三个响应变量的估计值都出现了极值。然而，使用GRID估计器的模型没有估计出极值，这表明基于GRID的模型可能受虚假数据的影响较小。这些结果表明，GRID估算器是任何需要估算大面积冠层指标的项目的有力候选。
The structure of a forest canopy is the key determinant of light transmission, use and understory availability. Airborne light detection and ranging (LiDAR) has been used successfully to measure multiple canopy structural properties, thereby greatly reducing the fieldwork required to map spatial variation in structure. However, lidar metrics to date do not reflect the full extent of the three-dimensional information available from the data. To this end, we developed a new metric, the polar grid fraction (GRID), based on gridding lidar returns in polar coordinates, in order to more closely match measurements provided by field instruments on leaf area index (LAI), gap fraction (GF) and percentage photosynthetically active radiation transmittance (tPAR). The metric summarizes the arrangement of lidar point returns for a single ground location rather than to an area surrounding the location. Compared with more traditional proportion-based and height percentile-based estimators, the GRID estimator increased validation R2 by 14.5% for GF and 6.0% for tPAR over the next best estimator. LAI was still best estimated with the more traditional statistic based on the proportion of ground returns in 14 m × 14 m moving kernels. By applying the models to a 2 × 2 m grid across the lidar coverage area, extreme values occurred in the estimations of all three response variables when using proportion-based and height percentile-based estimators. However, no extreme values were estimated by models using the GRID estimator, indicating that models based on GRID may be less influenced by spurious data. These results suggest that the GRID estimator is a strong candidate for any project requiring estimates of canopy metrics for large areas.