遥感叶绿素a浓度数据重构研究进展%Research Progress on Reconstruction Methods of Remote Sensing Chlorophyll-a Concentration Data
河南省软科学研究所 自然资源部第二海洋研究所 北京国遥新天地信息技术股份有限公司 烟台大学土木工程学院
2026-03-12
浮游植物 数据重构 遥感 叶绿素a浓度
现有业务化遥感叶绿素a浓度数据存在不同程度空间不完整、时间不连续的数据缺失问题,严重制约了遥感叶绿素a浓度数据的应用潜力,数据重构是解决该问题的主要手段.依据近年来国内外水色遥感数据重构方法的研究成果,研究总结了水色遥感数据重构方法的理论基础和发展历程,重点讨论了叶绿素a浓度数据重构研究的热点方向、常用的数据、常用方法和主要研究区域等内容,总结了叶绿素a浓度数据重构研究存在的问题,进一步揭示了叶绿素a浓度数据重构研究亟待解决的数据极端匮乏区的数据重构、短时间尺度数据重构方法构建、多变量结合的重构方法、经验正交函数数据插值法的改进以及遥感与数值模拟相结合的数据重构方法等关键难点,并展望了未来研究的方向.%Ocean color remote sensing chlorophyll a concentration data are of great significance for a wide range of scientific issues,such as global change and biogeochemical cycle studies.However,the existing operational remote sensing data on chlorophyll-a concentrations suffer from spatial incompleteness and temporal discontinuity,significantly limiting their application potential.Research shows that data reconstruction is the primary approach to address this issue.Based on recent research findings on ocean color remote sensing data reconstruction,this research summarizes the theoretical foundations and development history of data reconstruction methods.It par-ticularly discusses the hot topics in chlorophyll-a concentration data reconstruction,including common datasets,methods,and major research areas.The paper also identifies existing challenges in chlorophyll-a concentration data reconstruction,highlighting critical issues such as data reconstruction in extremely data-scarce regions,the development of short-time scale data reconstruction methods,multivariate combined reconstruction methods,improvements in Empirical Orthogonal Function data interpolation,and the integration of remote sensing with numerical simulation for data reconstruction.The paper concludes by outlining future research directions in this field.
