宽波段卫星传感器叶绿素遥感反演机理及高精度算法开发：以Landsat OLI为例

It is well known that inland water bodies such as lakes and reservoirs are small and optical variations are significant in spatial. Satellite image data for the land remote sensing plays a more and more important role in water color remote sensing of inland waters because of the high spatial resolution and a large spatial coverage. Based on the spectral response function of Landsat OLI data, remote sensing reflectance (Rrs) of each band mounted on the OLI sensor will be simulated by the in situ Rrs. Additionally, the absorption coefficients (a) and backscattering coefficients (bb) at each band will be also simulated using in situ/lab absorptions and backscattering coefficients. Take the widely used chlorophyll-a inversion algorithms as an example, the inherent mechanism will be revealed based on the bio-optical algorithms with the help of the Qusi-Analytical Model (QAA), and then the representative wavelength of each band is derived. Based on the mentioned above, it tries to develop a novel and high-precision chlorophyll-a inversion algorithm being applicable to a time-series satellite images with broad-bands.

湖泊/水库等内陆水体面积小、水质参数异质性显著；陆地卫星传感器具有空间分辨率高和刈幅大的特点，在陆地水体水色遥感中越来越受到重视。以现场实测光谱为基础，融合Landsat OLI光谱响应函数，模拟OLI传感器各波段的反射比数据Rrs（Remote Sensing Reflectance）；利用实测的水色组份吸收系数a和后向散射系数bb，模拟得到OLI传感器各波段的吸收和后向散射系数。以目前基于Landsat反演叶绿素常用的各种模型算法为例，基于生物光学模型，借助QAA，揭示其中的内在机理，并确定OLI每个波段的代表性波长；以此为基础，设计新的可用于长时间序列估算的高精度算法模型。

课题发表论文18篇（第二标注6篇、第3标注9篇，其它标注3篇），授权发明专利8项，登记软件著作权3件，获奖3个，培养博士3名。评估了卫星传感器带宽增加对内陆水体光学特性的影响，创建了适用于光学异质水体的区域湖泊叶绿素a反演方法，基于 linux系统语言开发了叶绿素a浓度批量化反演的软件系统，揭示了太湖等长江中下游和淮河流域11个湖泊连续36年（1984-2019）、中国东部大于1km2湖泊连续6年（2013-2018年）的叶绿素浓度时空分布特征。构建了考虑叶绿素的垂向分布特征的富营养化评价指数ABI，揭示了太湖的富营养化时空分布特征，提出了确定湖库水深和水储量的新方法ADBAR，揭示了卤水虾（BSC，Brine Shrimp Cysts）的光谱特征。