星载激光雷达估测森林结构参数研究现状分析与展望OA北大核心CSTPCD
Current Status and Development Trend in Estimating Forest Structural Parameters with Spaceborne LiDAR
星载激光雷达系统可以覆盖机载系统难以到达的偏远地区,从机理上克服光学影像及合成孔径雷达测量的技术缺陷,为快速准确地获取林下地形、树高、生物量等森林结构参数提供了可靠的数据源.对现有的星载激光雷达技术观测体系进行综述,讨论了星载激光雷达数据估测多尺度森林结构参数的适用性,定量化分析现有星载激光雷达研究成果及存在的优缺点.最后,总结当前存在的问题,对星载激光雷达技术未来的前景和发展方向进行了展望.建议后续研究可进一步加大对反演不同森林结构参数、产品体系及标准规范、林业应用精度评价、林业用激光雷达参数设计等方面的深入研究.
The spaceborne LiDAR measurement system offers a solution by covering remote areas that are challenging to access via airborne systems.This system effectively addresses the technical limitations of optical imaging and synthetic aperture radar measurements,thereby providing a reliable data source for swiftly and accurately obtaining forest structure parameters.However,the existing review on applications of spaceborne LiDAR has a lack of analysis that measures the accuracy of forest structural parameters estimated by spaceborne LiDAR as a whole and the content of the analysis is not systematic.The existing spaceborne LiDAR technology observation system were initially reviewed,and then the applicability of spaceborne LiDAR data estimation for multi-scale forest structure parameters was explored.The current development trends,as well as the existing advantages and disadvantages of satellite-borne LiDAR were also analyzed.Finally,the current challenges and anticipates the future prospects and development directions of spaceborne LiDAR technology were summarized.The research result can serve as a valuable reference for the design and application of spaceborne LiDAR remote sensing satellites in forestry.It was suggested that further research can deepen the in-depth study on the inversion of different forest structure parameters,product systems and standard specifications,accuracy evaluation of forestry applications,and design of LiDAR parameters for forestry.
黄佳鹏;李国元;刘诏
辽宁工程技术大学测绘与地理科学学院,阜新 123000||自然资源部国土卫星遥感应用中心,北京 100048自然资源部国土卫星遥感应用中心,北京 100048
林学
森林结构参数星载激光雷达多尺度多源数据
forest structure parameterspaceborne LiDARmulti-scalemulti-source data
《农业机械学报》 2024 (006)
18-33 / 16
辽宁省教育厅基本科研项目(JYTQN2023202)、辽宁省博士科研启动基金计划项目(2023-BS-202)、国家重点研发计划项目(2020YFA0608501、2021YFE0117700)和兴辽人才计划项目(XLYC1802027)
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