TY - JOUR
T1 - Satellite Retrieval of Water Quality Indicators Under High Solar Zenith Angles
AU - Wang, Yongquan
AU - Liu, Huizeng
AU - Man Wong, Ching
AU - Shen, Fang
AU - Yu, Xiaolong
AU - Wang, Yanru
AU - Zhang, Yu
AU - Zhang, Zhengxin
AU - Li, Qingquan
AU - Wu, Guofeng
N1 - Publisher Copyright:
© 1980-2012 IEEE.
PY - 2025
Y1 - 2025
N2 - Accurate and high spatiotemporal resolution water quality data are critical for the effective management of marine and coastal ecosystems. However, accurate atmospheric correction under high solar zenith angles (SZAs) remains a challenge, introducing substantial uncertainties in satellite-derived water quality indicators (WQIs) under high SZA. With an attempt to fill the gap, this study evaluated three types of strategies for satellite retrieval of suspended particulate matter (SPM) and chlorophyll-a (Chl-a) concentrations from top-of-atmosphere reflectance (ρt), Rayleigh-corrected reflectance (ρrc), and remote sensing reflectance (Rrs). The models, named XGBWQI, based on three types of remote sensing data were tested with in situ data and compared with the geostationary ocean color imager (GOCI) standard algorithms. Results showed that: 1) ρt-based XGBWQI had the best accuracy (R2 = 0.90 and mean absolute percentage deviation (MAPD) = 14.65% for SPM, and R2 = 0.85 and MAPD = 5.34% for Chl-a); 2) model testing results with in situ data also confirmed the advantage of ρt-based XGBWQI over other models (R2 = 0.88 , MAPD = 26.9%, and mean relative percentage deviation (MRPD) = 11.8% for SPM; R2 = 0.78 , MAPD = 43.3%, and MRPD = -15.5 % for Chl-a); and 3) the XGBWQI models obtained more valid WQI values for GOCI images under high SZA and successfully revealed the diurnal variations of a red tide event in the Yellow Sea and the SPM dynamics in the East China Sea. Therefore, ρt-based XGBWQI models were recommended as the best strategy for satellite retrievals of WQI under high SZA. The methods can serve as an effective tool in retrieving WQI in coastal waters under high SZA and thus contribute to better and high-frequency water quality monitoring.
AB - Accurate and high spatiotemporal resolution water quality data are critical for the effective management of marine and coastal ecosystems. However, accurate atmospheric correction under high solar zenith angles (SZAs) remains a challenge, introducing substantial uncertainties in satellite-derived water quality indicators (WQIs) under high SZA. With an attempt to fill the gap, this study evaluated three types of strategies for satellite retrieval of suspended particulate matter (SPM) and chlorophyll-a (Chl-a) concentrations from top-of-atmosphere reflectance (ρt), Rayleigh-corrected reflectance (ρrc), and remote sensing reflectance (Rrs). The models, named XGBWQI, based on three types of remote sensing data were tested with in situ data and compared with the geostationary ocean color imager (GOCI) standard algorithms. Results showed that: 1) ρt-based XGBWQI had the best accuracy (R2 = 0.90 and mean absolute percentage deviation (MAPD) = 14.65% for SPM, and R2 = 0.85 and MAPD = 5.34% for Chl-a); 2) model testing results with in situ data also confirmed the advantage of ρt-based XGBWQI over other models (R2 = 0.88 , MAPD = 26.9%, and mean relative percentage deviation (MRPD) = 11.8% for SPM; R2 = 0.78 , MAPD = 43.3%, and MRPD = -15.5 % for Chl-a); and 3) the XGBWQI models obtained more valid WQI values for GOCI images under high SZA and successfully revealed the diurnal variations of a red tide event in the Yellow Sea and the SPM dynamics in the East China Sea. Therefore, ρt-based XGBWQI models were recommended as the best strategy for satellite retrievals of WQI under high SZA. The methods can serve as an effective tool in retrieving WQI in coastal waters under high SZA and thus contribute to better and high-frequency water quality monitoring.
KW - Coastal waters
KW - geostationary ocean color imager (GOCI)
KW - high solar zenith angle (SZA)
KW - ocean color remote sensing
KW - water quality indicators (WQIs)
UR - https://www.scopus.com/pages/publications/105008663807
U2 - 10.1109/TGRS.2025.3580137
DO - 10.1109/TGRS.2025.3580137
M3 - 文章
AN - SCOPUS:105008663807
SN - 0196-2892
VL - 63
JO - IEEE Transactions on Geoscience and Remote Sensing
JF - IEEE Transactions on Geoscience and Remote Sensing
M1 - 4207816
ER -