Retrieval of total suspended matter concentration from Gaofen-1 Wide Field Imager (WFI) multispectral imagery with the assistance of Terra MODIS in turbid water – case in Deep Bay

ABSTRACT

This study proposed a method for developing high spatial resolution Gaofen-1 satellite (GF-1) Wide Field Imager (WFI)-based total suspended matter concentration (C_TSM) retrieval model with the assistance of Moderate Resolution Imaging Spectroradiometer (MODIS) data, using the Deep Bay in China as a case. Based on long-term calibrated C_TSM measurements of optical backscatter (OBS) 3A turbidity and temperature monitoring system of two stationary stations from January 2007 through November 2008, 33 match-ups were selected to build an exponential retrieval model for MODIS atmospherically corrected remote-sensing reflectance (R_rs) ratio (R_rs,645/R_rs,555). Validation of the MODIS model showed well agreement with the seven in situ C_TSM measurements with a root mean squared error (RMSE) of 5.06 mg l⁻¹ and a coefficient of determination R² of 0.80. Aided with six MODIS retrieved C_TSM products, different band combinations (single band (R_rc,660), band subtraction (R_rc,660–R_rc,560), band ratio (R_rc,660/R_rc,560), and total suspended matter index at 660 nm band (TSMI₆₆₀) were evaluated for simultaneous GF-1 WFI Rayleigh-corrected reflectance (R_rc). The results showed that the exponential model based on the Rayleigh-corrected reflectance ratio (R_rc,660/R_rc,560) could achieve acceptable accuracy, with RMSE of 14.80 mg l⁻¹ and R² of 0.62. The proposed method would be helpful for dynamic monitoring in the Deep Bay, and more important could also provide an alternative approach for studies when in situ measurements are unreachable.

Acknowledgements

This work was supported by the National Natural Science Foundation of China [grant number 41571344], [grant number 41331174], [grant number 41071261], [grant number 40906092], [grant number 40971193], [grant number 41101415], [grant number 41401388], [grant number 41206169], [grant number 41406205]; the Open Research Fund of the Key Laboratory of Space Ocean Remote Sensing and Application, State Oceanic Administration People’s Republic of China [grant number 201502003], the Hong Kong Research Grants Council (RGC) General Research Fund [grant number B-Q23G], the Open Research Fund of State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research [grant number IWHR-SKL-201514], the Major Science and Technology Program for Water Pollution Control and Treatment [grant number 2013ZX07105-005], the Open Research Fund of Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences [grant number 2013LDE004], Special Fund by Surveying & Mapping and Geoinformation Research in the Public Interest [grant number 201512026], LIESMARS Special Research Funding, the ‘985 Project’ of Wuhan University; Special funds of State Key Laboratory for equipment. The authors thank the China Centre for Resources Satellite Data and Application (CRESDA) for providing GF-1 WFI data. A special thanks is to Prof. Chuanmin Hu (University of South Florida), for his sights and encouragements of this work.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [grant number 41571344], [grant number 41331174], [grant number 41071261], [grant number 40906092], [grant number 40971193], [grant number 41101415], [grant number 41401388], [grant number 41206169], [grant number 41406205]; the Open Research Fund of the Key Laboratory of Space Ocean Remote Sensing and Application, State Oceanic Administration People’s Republic of China [grant number 201502003], the Hong Kong Research Grants Council (RGC) General Research Fund [grant number B-Q23G], the Open Research Fund of State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research [grant number IWHR-SKL-201514], the Major Science and Technology Program for Water Pollution Control and Treatment [grant number 2013ZX07105-005], the Open Research Fund of Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences [grant number 2013LDE004], Special Fund by Surveying & Mapping and Geoinformation Research in the Public Interest [grant number 201512026], LIESMARS Special Research Funding, the ‘985 Project’ of Wuhan University; Special funds of State Key Laboratory for equipment.