国家自然科学基金项目
红树林水域水色参数无人机遥感反演研究
基本信息
项目批准号：42006162
申请代码：D0607
项目名称：红树林水域水色参数无人机遥感反演研究
项目负责人：余小龙
依托单位：厦门大学
研究期限：2021-01-01 至 2023-12-31
资助经费：24.0（万元）
中文摘要：
红树林水域水体光学特性复杂且时空异质性强，其水色参数时空分布的精细特征是促进理解红树林生态系统在全球碳循环中作用的核心基础之一。高空间分辨的无人机遥感是观测红树林水域水色参数的有效手段，但迄今发展的水色算法和无人机水色遥感系统尚未有在目标区成功应用的先例，极大限制了对红树林水体水色参数时空分布的精细描述和研究，尤其是水体与红树林林区的耦合研究。针对上述问题，本研究选择福建漳江口红树林生态系统为实验区域，通过1）优化无人机观测水体遥感反射率光谱的校正算法；2）发展复杂水体CDOM吸收系数、颗粒物后向散射系数和浓度的遥感反演算法；3）研发混合像元水色参数提取算法；最终建立一套无人机高光谱成像遥感系统，获取目标区亚米级分辨的水色参数时空分布特征。本项目成果将不仅在复杂水环境的无人机遥感技术上取得突破，更将为研究红树林生态系统有机碳水平输出提供数据来源，促进全球“蓝碳”研究。
英文摘要：
Water optical properties of the mangrove ecosystems are typically optically complex and with strong spatiotemporal heterogeneity. To better understand the role of the mangrove ecosystem in the global carbon cycle, it is important and necessary to observe the water optical properties of the ecosystem with high-spatial-resolution. Remote sensing using an unmanned aerial vehicle (UAV) could be an effective technique for such purpose, but no successful application has been reported yet, which limits the observation of the detailed distribution pattern of the water optical properties, especially in the coupled regions of waters and mangrove species. In this study, we select the mangrove ecosystem in the Zhangjiang estuary of the Fujian province as the study area and develop a system using UAV imagery to interpret the water optical properties of the mangrove ecosystem at the sub-meter level. The following three research aspects have been proposed to ensure a successful implementation of this system. First, a more consistent and accurate method is proposed to correct the UAV-measured Rrs for the surface reflection residuals using spectral optimization. Second, inversion algorithms to retrieve the water optical properties are developed and optimized for the mangrove waters, particularly for the CDOM absorption coefficient, the backscattering coefficient, and the concentration of SPM. Finally, a novel approach to extract the water optical properties from mixed pixels is also proposed to ensure a seamless observation from the mangrove fringe to the adjacent waters. The system developed in this effort will contribute to the ocean color remote sensing of optically complex waters by UAV. The system will also provide an innovative technique to investigate the horizontal transport of organic carbon in the mangrove ecosystems and thus promote the “blue carbon” research on a global scale.
结题摘要
针对项目三个研究任务，项目负责人开展了相关算法的研发工作。具体地，1）研发了基于天空光遮蔽法测量遥感反射比的阴影校正算法，使得针对不同类型水体高质量原位遥感反射比的测量成为可能，为无人机遥感数据校正提供参考真值；2）发展了基于神经网络的遥感算法估算颗粒物后向散射系数的光谱斜率，并改进了传统的反演固有光学特性（IOPs）的准分析算法，提高了光学复杂水体的IOPs反演精度，为无人机遥感红树林水色参数奠定基础；3）开展了3次红树林水域无人机和地面的同步观测，无人机搭载Headwall成像高光谱仪获得了目标区域植被和水体的高空间分辨遥感影像，现场通过走航模式，利用天空光遮蔽法和水面之上法测量获得了水体的遥感反射率，并匹配了欧空局的Sentinel 2号卫星数据。目前正利用这些匹配的数据开展无人机数据校正和混合像元解译工作，预计2024年可投稿相关成果。在上述研究任务之外，在本项目支持下，开展了水体离水反照率遥感估算和原位测量方面的研究工作。累计在国际知名SCI期刊发表项目标注论文5篇，第一标注3篇，第二标注2篇。另有投稿中SCI论文一篇和准备中SCI论文1-2篇。
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