"Marin Drăcea" Romanian National Institute for Research and Development in Forestry, Department of Forest Monitoring, 128 Eroilor Blvd., Voluntari 077190, Ilfov, Romania; "Transilvania" University, Faculty of Silviculture and Forest Engineering, Department of Forest Engineering, Forest Management Planning and Terrestrial Measurements, 1, Ludwig van Beethoven Str., 500123 Braşov, Romania.
"Marin Drăcea" Romanian National Institute for Research and Development in Forestry, Department of Forest Monitoring, 128 Eroilor Blvd., Voluntari 077190, Ilfov, Romania; "Transilvania" University, Faculty of Silviculture and Forest Engineering, Department of Forest Engineering, Forest Management Planning and Terrestrial Measurements, 1, Ludwig van Beethoven Str., 500123 Braşov, Romania.
Sci Total Environ. 2019 Nov 15;691:205-215. doi: 10.1016/j.scitotenv.2019.06.536. Epub 2019 Jul 2.
Forest stands are often parameterized by vegetation indices such as the Leaf Area Index (LAI). However, other indices (i.e. stand denseness, espacement, canopy density, canopy cover, foliage cover, crown porosity, gap fraction) may better characterize forest structure. Terrestrial and airborne active sensor data has been used to describe canopy structural diversity and provide accurate estimates of forest structure indices. This study uses Terrestrial Laser Scanner (TLS) to characterize forest structure through the above-mentioned indices. The relationship between all of them was studied to assess the extent to which they relate and their capability to properly describe forest stands. A strong correlation was visible between LAI and the canopy density index (r = 0.87 to 0.91 depending on the extraction methods) despite the underevaluated values of the first. Even though more precise LAI estimates were expected from using co-registered multiple scans, the LAI variability proved to be low and correlations with the remaining indices weakened when compared to a single scan approach. An exception was canopy cover, a structural index that disregards the three-dimensionality of the canopy, with which the LAI obtained from multiple scans maintained a strong correlation. This suggests that multiple scanning leads to an unweighted oversampling of the scene, overshadowing its advantages in removing tree occlusions. Weak correlations were visible between classic forest structural indices (basal area density index, espacement index, denseness index) and the rest of the descriptors. Despite this exception, most of the forest indices showed average to strong correlations in-between each other. Therefore, we conclude that a better description of forest stands structure may be achieved through unsegmented single scan point cloud processing in both 3D and 2D space, optical data from the incorporated digital camera being a plus, but not an essential requirement.
森林通常通过植被指数进行参数化，例如叶面积指数（LAI）。然而，其他指数（即林分密度、间距、树冠密度、树冠覆盖、叶盖、冠层孔隙率、间隙分数）可能更好地描述森林结构。地面和机载主动传感器数据已被用于描述冠层结构多样性，并提供森林结构指数的准确估计。本研究使用地面激光扫描仪（TLS）通过上述指数来描述森林结构。研究了它们之间的关系，以评估它们之间的关系程度及其适当描述林分的能力。尽管第一个指数的值被低估了，但 LAI 与树冠密度指数之间存在很强的相关性（取决于提取方法，r 值为 0.87 到 0.91）。尽管使用配准的多次扫描可以更精确地估计 LAI，但与单扫描方法相比，当 LAI 变异性被证明很低时，与剩余指数的相关性减弱。一个例外是树冠覆盖，这是一个忽略树冠三维性的结构指数，从多次扫描中获得的 LAI 与该指数保持很强的相关性。这表明多次扫描导致对场景的无权重过采样，掩盖了其在去除树木遮挡方面的优势。经典森林结构指数（基面积密度指数、间距指数、密度指数）与其余描述符之间存在较弱的相关性。尽管存在这种例外，但大多数森林指数之间的相关性平均到较强。因此，我们得出结论，通过 3D 和 2D 空间中的未分段单扫描点云处理，可以更好地描述林分结构，同时结合数字相机的光学数据是一个优势，但不是必需的。
