Intercomparison of methods for estimating leaf inclination angle distribution with terrestrial lidar for broadleaf tree species

Abstract

Leaf inclination angle distribution (LIAD) is a fundamental parameter of models that illustrate the energy and mass exchanges for vegetation at all scales. Terrestrial laser scanning (TLS) instruments have emerged as valuable tools for acquiring detailed measurements of canopy structure. Here, we present the first intercomparison of the available LIAD estimation techniques using TLS data.The available LIAD estimation techniques were evaluated using TLS point clouds of both real and synthetic trees covering the full range of the existing LIAD types. The performance of the proposed TLS-based methods was also compared with the established, non-TLS-based leveled digital photography approach.The study highlighted that the algorithms that used merged point clouds performed better than their single-scan counterparts. TLS offered a more comprehensive representation of the canopy structure and overcame the limitations of the traditional leveled digital photography approach for both real and simulated trees.This study may serve as a template for establishing benchmark datasets, evaluation protocols, and accessibility of algorithms that could facilitate systematic comparisons of LIAD estimation algorithms. This collaborative effort promotes fairness, reproducibility, and the advancement of LIAD estimation techniques by enabling researchers to identify strengths, weaknesses, and areas for improvement in their algorithms.