基于背包式MLS与UAV遥感协同的单木-林分尺度森林地上生物量精细反演

项目名称： 基于背包式MLS与UAV遥感协同的单木-林分尺度森林地上生物量精细反演

项目编号： No.41471281

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 天文学、地球科学

项目作者： 林沂

作者单位： 北京大学

项目金额： 80万元

中文摘要： 生物量是森林生态系统碳汇能力的重要指标，估测其分布对于森林物质生产、气候调节、碳循环等领域的研究均有重要意义。然而，研究发现诸多大尺度生物量模型的估测误差较大，这导致了目前该领域对小尺度精确估测这一技术基础的回归再重视。事实证明，传统的林业调查和遥感技术，存在一个无法灵活机动高效地实现大面积与高精度同时测量的技术空白带。针对此问题，课题团队拟引入地基遥感中适于林下环境的最新技术- - 移动地基激光扫描和航空遥感中满足灵活机动的最新技术- - 无人机成像，采用自主开发的背包式移动地基激光扫描系统和无人机农业多光谱数字成像系统，开发基于三维点云的单木地上生物量异速生长反演算法，同时提取点云与无人机图像的相关特征因子并开发尺度上推协同反演算法。通过立足国内而又同步国际的上述工作，藉由背包式激光扫描与无人机新型遥感技术的组合，建立一个林分尺度森林地上生物量精细估测的技术方案，推动相关领域的研究有所突破。

中文关键词： 森林地上生物量；精细反演；背包式移动地基激光扫描；无人机；遥感协同

英文摘要： Biomass is the kernel index for assessing the capacity of forest ecosystem for carbon storage, and estimation of its distribution has great significance for the associated domains, such as forest material production, climate regulation, and carbon cycle. However, researches indicated that lots of large-scale biomass estimation models may show giant errors, and for the whole field this results in the re-emphasizes of fine-scale measurement techniques as the technical bases. In fact, there are almost no efficient and flexible solutions for the gap between the demands of large-cover and high-accuracy, based on no matter the traditional forest inventory technology or the common remote sensing (RS) technology. Aimed at this issue, the project team are going to assume mobile terrestrial laser scanning (MLS), one of the newest terrestrial RS techniques appropriate for forest environment, and unmanned aerial vehicle (UAV) based imaging, one of the airborne RS techniques flexible for forest mapping. Specifically, the backpack MLS system and the UAV-based agricultural multispectral digital camera (ADC) RS system (UAV-ADC) developed by the project team will be applied. New allometric algorithms for estimating aboveground biomasses (AGB) of individual trees will be developed based on 3D point clouds. The feature parameters of individual trees will be extracted from both the point clouds and ADC images, and their correlation relationships will be exploited and deduced into new algorithms for AGB retrievals up-scaling. With the above frontier-oriented tasks implemented by using the team-developed facilities, a novel technique for accurate AGB estimation at the forest stand scales by collaborating backpack MLS and UAV-ADC can be validated. This also means some chances for the relevant communities to make breakthroughs involving forest biomass.

英文关键词： Forest above-ground biomass;accurate retrieval;backpack mobile laser scanning (MLS);unmanned aerial vehicle (UAV);collaborative remote sensing