首页|星载激光雷达估测森林结构参数研究现状分析与展望

星载激光雷达估测森林结构参数研究现状分析与展望

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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.
Current Status and Development Trend in Estimating Forest Structural Parameters with Spaceborne LiDAR
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.

forest structure parameterspaceborne LiDARmulti-scalemulti-source data

黄佳鹏、李国元、刘诏

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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

森林结构参数 星载激光雷达 多尺度 多源数据

辽宁省教育厅基本科研项目辽宁省博士科研启动基金计划项目国家重点研发计划项目国家重点研发计划项目兴辽人才计划项目

JYTQN20232022023-BS-2022020YFA06085012021YFE0117700XLYC1802027

2024

农业机械学报
中国农业机械学会 中国农业机械化科学研究院

农业机械学报

CSTPCD北大核心
影响因子:1.904
ISSN:1000-1298
年,卷(期):2024.55(6)