Comparison of MODIS-based models for retrieving suspended particulate matter concentrations in Poyang Lake, China

摘要

Suspended particulate matter (SPM) is a key parameter describing water quality, and developing the retrieval model of SPM concentration (C_(SPM)) is fundamental for obtaining the spatiotemporal information of C_(SPM) and further for understanding, managing and protecting aquatic ecosystems. This study aimed to compare moderate resolution imaging spectroradiometer (MODIS)-based C_(SPM) retrieval models in order to find the optimal model for improving the C_(SPM) estimation in Poyang Lake. The C_(SPM) measurements on 27 September 2007 and their coincident MODIS Terra image were used to calibrate retrieval models with the least-squares technique. The C_(SPM) measurements on 31 August 2012 and the MODIS Terra image on 30 August 2012 were applied to validate the calibrated models, and the correlation coefficient (r) between the measured and estimated C_(SPM) values, the root mean square error (RMSE) and relative root mean square error (RRMSE) of estimation as well as the model bias evaluation result were compared to determine the optimal model for estimating the C_(SPM) values of Poyang Lake from MODIS images. Model calibration showed that, after two samples were removed, the exponential models of blue, green and red band, the linear model of infrared band, the cubic model of red band as well as the exponential model of red minus infrared band explained about 92%, 88%, 90%, 89%, 90% and 76% of the variation of C_(SPM), respectively; while model validation indicated that, after removing two samples, the exponential models of blue and green band got biased C_(SPM) estimations, the agreement between the measured and estimated C_(SPM) values was not very high (r = <0.8) for the models with single red and infrared band, and the exponential model of red minus infrared band got the best result among all calibrated models (r = 0.87, RMSE = 22.1 mg/l, RRMSE = 52.8%). We concluded that the exponential model of red minus infrared band obtained stable C_(SPM) estimation and was the optimal model for C_(SPM) estimation in this study, and more independent datasets should be obtained to further validate our finding for improving the C_(SPM) estimation in Poyang Lake.