林分平均高度卫星遥感新进展

林分平均高度是生态系统模型重要的输入参数之一,与生物量估算与碳循环研究高度相关。通过系统回顾林分平均高度研究的发展历史和最新进展,总结了不同传感器林分平均高度(SAR树高与LiDAR冠层高度)研究的主要模型和方法,通过单一传感器技术进行林分平均高度研究的内在特征的不同,分析了多传感器的区域林分平均高度联合反演方法的优劣性,并从科学发展趋势和社会需求出发,认识目前存在的主要问题与难点及未来面临的挑战和机遇,为今后更好地进行森林垂直结构和全球碳循环研究提供思路和借鉴。

New Development of Forest Canopy Height Remote Sensing

Forest canopy height is one of important input parameters of ecosystem model,and had a high correlation with the estimation of biomass and the study of carbon cycle.This paper reviewed systematically the development history and the newest trends of forest canopy height studies,summarized the mainly models and methods of forest canopy height studies among different sensors(SAR tree height and LiDAR forest canopy height),including polarization interference model and tree height algorithm,ploarization coherence tomography(PCT),LiDAR canopy height estimation methods and forest canopy height profile simulation,deliberated on the intrinsic characteristics of different research techniques on the single sensor of forest canopy height,and analyzes the advantages and disadvantages of the multi\|sensor joint inversion method of the regional forest canopy height.Analysis shows that the interpolation results of Kriging and CoKriging methods is not very good,hybrid model is more suitable for the space interpolation of the regional forest height compared with other single time or space model.From the scientific trends and social needs,the existing problems and difficulties were understudied and the new challenge and chances in forest canopy height studies were analyzed.This will provide new trajectories and new methods for further studies of forest vertical structure and global carbon cycle.