Forest canopy structural complexity is an emergent forest attribute that describes the three-dimensional arrangement of canopy elements. It is a critical factor that can mediate the forest ecosystem functioning with forest species diversity. In this study, we proposed a novel entropy-based method for forest canopy structural complexity quantification from multiplatform lidar points, namely Canopy Entropy (CE). It can successfully capture canopy structural complexity variations caused by both tree density and the number of vertical canopy layers, and outperform currently widely used indices (e.g., canopy height, foliage height diversity, fractal dimension). Moreover, CE estimates from multiplatform lidar point clouds are comparable from each other, and therefore it is a cross-platform adaptive index.
The source code for calculating CE is provided here, and can be downloaded freely.
Xiaoqiang Liu, Qin Ma, Xiaoyong Wu, Tianyu Hu, Zhonghua Liu, Lingli Liu, Qinghua Guo, Yanjun Su, 2022, A novel entropy-based method to quantify forest canopy structural complexity from multiplatform lidar point clouds. Remote Sensing of Environment, 282, 113280.