基于多源数据协同作业的森林信息提取研究进展

传统森林调查手段正逐渐被激光雷达、光学遥感及卫星遥感等新兴的遥感技术所代替。随着研究的不断深入，单一遥感数据源往往难以满足高精度的森林信息提取需求。因此，文中以激光雷达为研究主体，综述摄影测量、高光谱遥感及卫星遥感等多种遥感技术在森林信息提取中不同遥感技术协同作业的研究进展。相较于单一数据源，多源数据协同作业在森林结构参数提取、生物量估测以及树种识别等领域均有明显优势。结合目前的研究工作，从数据获取成本、获取方式、多源数据融合、配套软件及系统构建等方面展望了多源数据协同作业方式的发展趋势。

Research Progress in Forest Information Extraction Based on Multi-source Data Collaboration Operation

Traditional forest inventory methods are gradually being replaced by emerging remote sensing technologies such as LiDAR, optical remote sensing and satellite remote sensing. As the research goes deeper, the use of single remote sensing data source are often difficult to meet the needs of high-precision forest information extraction. This paper is focused on LiDAR and uses various remote sensing technologies such as photogrammetry, hyperspectral remote sensing and satellite remote sensing to discuss the research progress in the collaborative operation of different remote sensing technologies in forest information extraction. Compared with a single data source, multi-source data collaborative operations have significant advantages in the areas of forest structure parameters extraction, biomass estimation and tree species identification. At the end, based on the current research work, the future development trend of multi-source data collaborative operation mode is prospected in terms of data acquisition cost, acquisition method, multi-source data fusion, supporting software and system construction.