Evaluating effects of remote sensed neighborhood crowding indices and depth-to-water on tree height growth

Data set containing 4 386 trees of three different species (Picea glauca, Pinus contorta and Populus tremuloides). Based on UAV derived canopy height models and canopy surface models a set of four different neighborhood crowding indices and a depth-to-water index were calculated for each tree. Abbreviations: WS: White spruce; LP: Lodgepole pine; TA: Trembling aspen; hg_19: tree height in 2019; hg_21: tree height in 2021; mch: Mean canopy height; cc: canopy cover; ca; canopy above; canopy_angle: Canopy angle.

本数据集共包含4386株树木，分属3个不同树种（白云杉Picea glauca、黑松Pinus contorta和颤杨Populus tremuloides）。基于无人机（UAV）获取的冠层高度模型与冠层表面模型，本研究为每株树木计算了4种邻体拥挤指数与1个距水深度指数。缩写说明如下：WS：白云杉（White spruce）；LP：黑松（Lodgepole pine）；TA：颤杨（Trembling aspen）；hg_19：2019年树高；hg_21：2021年树高；mch：平均冠层高度（Mean canopy height）；cc：冠层覆盖度（canopy cover）；ca：冠层上方（canopy above）；canopy_angle：冠层角度。