Observations of Optical Properties and Chlorophyll-a Concentration in Qiandao Lake Using Shipborne Lidar
Lidar technology is increasingly applied to the inversion of oceanic biological parameters and optical properties based on empirical and semi-empirical bio-optical models. However, these models cannot be directly applied to inland waters due to their complex composition, and research on the biological parameters and optical properties of inland waters remains limited. In this study, the Fernald method was employed to retrieve the vertical distribution of optical properties in Qiandao Lake for the first time using shipborne lidar data obtained in June 2019. By quantifying the depth-resolved optical contributions of biological components, the vertical distributions of chlorophyll-a concentration were mapped with greater precision. The lidar-estimated optical properties exhibited characteristic spatiotemporal distributions, which were closely related to water quality. At the inflow of Xin’an River, the attenuation and scattering coefficient showed a gradual increase with depth. At the north–south-oriented reservoir area and the outflow of Qiandao Lake, an apparently continuous subsurface layer with the maximum signal occurred at approximately 3.5 m. The vertical distributions of chlorophyll-a profiles were consistently classified as subsurface chlorophyll maxima, with the maximum value of chlorophyll-a concentration fluctuating between 4 and 12 μg/L. The subsurface phytoplankton layer was observed at water depths ranging from 1.5 to 3.5 m, with a thickness of 3 to 6 m. Furthermore, the influences of lidar ratio Sp(z) and reference value bbp(zm) were discussed as significant sources of inversion error in the Fernald method. These results indicate that lidar technology holds great potential for the long-term monitoring of lakes.
Authors
- Chang Han (ORCID: https://orcid.org/0000-0002-6282-1256)
- Youzhi Li (ORCID: https://orcid.org/0000-0002-3233-5249)
- Xianliang Zhang (ORCID: https://orcid.org/0000-0002-2870-3504)
- Zhihua Mao (ORCID: https://orcid.org/0000-0002-0066-1808)
- Xuan Sang
- Haiqing Huang (ORCID: https://orcid.org/0000-0002-8932-7995)
- Longwei Zhang (ORCID: https://orcid.org/0009-0004-8609-2758)
Institutions
- Shanghai Jiao Tong University (CN)
- Chinese Academy of Sciences (CN)
- Ministry of Natural Resources (CN)
- Zhejiang Ocean University (CN)
- Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) (CN)
- Second Institute of Oceanography (CN)
- Shanghai Institute of Technical Physics (CN)
- Zhejiang University (CN)
- Nanjing University (CN)
Publication Details
- Journal
- Remote Sensing
- Published
- 2024-12-13
- DOI
- https://doi.org/10.3390/rs16244663
- Citations
- 1
- Primary Topic
- Marine and coastal ecosystems
- Type
- article
- Field-Weighted Citation Impact
- 0.48
Funders
- National Natural Science Foundation of China
- Zhejiang University
- Shanghai Jiao Tong University
- National Key Research and Development Program of China