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Temporal Variation of Chlorophyll-a Concentrations in Highly Dynamic Waters from Unattended Sensors and Remote Sensing Observations
Li, Jian; Tian, Liqiao1; Song, Qingjun2,3; Sun, Zhaohua4; Yu, Hongjing5; Xing, Qianguo6
2018
Source PublicationSENSORS
ISSN1424-8220
Volume18Issue:8Pages:2699
AbstractMonitoring of water quality changes in highly dynamic inland lakes is frequently impeded by insufficient spatial and temporal coverage, for both field surveys and remote sensing methods. To track short-term variations of chlorophyll fluorescence and chlorophyll-a concentrations in Poyang Lake, the largest freshwater lake in China, high-frequency, in-situ, measurements were collected from two fixed stations. The K-mean clustering method was also applied to identify clusters with similar spatio-temporal variations, using remote sensing Chl-a data products from the MERIS satellite, taken from 2003 to 2012. Four lake area classes were obtained with distinct spatio-temporal patterns, two of which were selected for in situ measurement. Distinct daily periodic variations were observed, with peaks at approximately 3:00 PM and troughs at night or early morning. Short-term variations of chlorophyll fluorescence and Chl-a levels were revealed, with a maximum intra-diurnal ratio of 5.1 and inter-diurnal ratio of 7.4, respectively. Using geostatistical analysis, the temporal range of chlorophyll fluorescence and corresponding Chl-a variations was determined to be 9.6 h, which indicates that there is a temporal discrepancy between Chl-a variations and the sampling frequency of current satellite missions. An analysis of the optimal sampling strategies demonstrated that the influence of the sampling time on the mean Chl-a concentrations observed was higher than 25%, and the uncertainty of any single Terra/MODIS or Aqua/MODIS observation was approximately 15%. Therefore, sampling twice a day is essential to resolve Chl-a variations with a bias level of 10% or less. The results highlight short-term variations of critical water quality parameters in freshwater, and they help identify specific design requirements for geostationary earth observation missions, so that they can better address the challenges of monitoring complex coastal and inland environments around the world.
DepartmentLTO
Keywordchlorophyll-a remote sensing Poyang Lake temporal scale sampling strategy
DOI10.3390/s18082699
Citation statistics
Document Type期刊论文
Identifierhttp://ir.scsio.ac.cn/handle/344004/17584
Collection热带海洋环境国家重点实验室(LTO)
Affiliation1.Wuhan Univ, Sch Remote Sensing & Informat Engn, Wuhan 430079, Hubei, Peoples R China
2.Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Hubei, Peoples R China
3.State Ocean Adm, Natl Satellite Ocean Applicat Serv, Beijing 100081, Peoples R China
4.State Ocean Adm, Key Lab Space Ocean Remote Sensing & Applicat, Beijing 10081, Peoples R China
5.Chinese Acad Sci, South China Sea Inst Oceanol, State Key Lab Trop Oceanog, Guangzhou 510301, Guangdong, Peoples R China
6.Inst Water Resources & Hydropower Res, State Key Lab Simulat & Regulat Water Cycle River, Beijing 100038, Peoples R China
7.Chinese Acad Sci, Yantai Inst Coastal Zone Res, Key Lab Coastal Environm Proc & Ecol Remediat, Yantai 264003, Peoples R China
Recommended Citation
GB/T 7714
Li, Jian,Tian, Liqiao,Song, Qingjun,et al. Temporal Variation of Chlorophyll-a Concentrations in Highly Dynamic Waters from Unattended Sensors and Remote Sensing Observations[J]. SENSORS,2018,18(8):2699.
APA Li, Jian,Tian, Liqiao,Song, Qingjun,Sun, Zhaohua,Yu, Hongjing,&Xing, Qianguo.(2018).Temporal Variation of Chlorophyll-a Concentrations in Highly Dynamic Waters from Unattended Sensors and Remote Sensing Observations.SENSORS,18(8),2699.
MLA Li, Jian,et al."Temporal Variation of Chlorophyll-a Concentrations in Highly Dynamic Waters from Unattended Sensors and Remote Sensing Observations".SENSORS 18.8(2018):2699.
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