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

Institutions

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

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Observations of Optical Properties and Chlorophyll-a Concentration in Qiandao Lake Using Shipborne Lidar

Chang Han, Youzhi Li, Xianliang Zhang, Zhihua Mao et al.
1 citations
Remote Sensing
Marine and coastal ecosystems
0.48
article

Observations of Optical Properties and Chlorophyll-a Concentration in Qiandao Lake Using Shipborne Lidar

Chang Han, Youzhi Li, Xianliang Zhang, Zhihua Mao, Xuan Sang, Haiqing Huang, Longwei Zhang
article en
1 citations

Abstract

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.

Remote SensingVol. 16(24)
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)
National Natural Science Foundation of China, Zhejiang University, Shanghai Jiao Tong University, National Key Research and Development Program of China
Life below water
Openalex Percentile: Top 31%
Marine and coastal ecosystems
0.48
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.