Comparison of MODIS-based models for retrieving suspended particulate matter concentrations in Poyang Lake,China |
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| Institution: | 1. School of Resource and Environmental Science & Key Laboratory of Geographic Information System of the Ministry of Education, Wuhan University, 430079 Wuhan, China;2. Institute of Wetland Research, Chinese Academy of Forestry, 100091 Beijing, China;3. State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, 210008 Nanjing, China;1. Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China;2. China South China Sea Environment Monitoring Center, State Oceanic Administration, Guangzhou 510300, China;3. Dipartimento Farmaco Chimico Tecnologico, CSGI, University of Siena, Siena, Italy;4. Guangdong Key Laboratory of Ocean Remote Sensing, South China Sea Institute of Oceanology Chinese Academy of Sciences, Guangzhou 510300, China;5. South China Sea Institute of Planning and Environmental Research, State Oceanic Administration, Guangzhou 510310, China;6. Guangdong Provincial Key Laboratory of Silviculture, Protection and Utilization, Guangdong Academy of Forestry, Guangzhou 510520, China;1. Centre for Water in the Minerals Industry, Sustainable Minerals Institute, The University of Queensland, St. Lucia Campus, QLD 4072, Australia;2. School of Environmental and Geographical Sciences, Faculty of Science, University of Nottingham Malaysia Campus, Jalan Broga, Semenyih 43500, Malaysia;3. Rio Tinto Limited, 123 Albert St., Brisbane City, QLD 4000, Australia;1. University of South Florida, 140 Seventh Avenue South, St. Petersburg, FL 33701, United States;2. Florida Fish and Wildlife Conservation Commission, 100 Eighth Avenue South, St. Petersburg, FL 33701, United States |
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| Abstract: | Suspended particulate matter (SPM) is a key parameter describing water quality, and developing the retrieval model of SPM concentration (CSPM) is fundamental for obtaining the spatiotemporal information of CSPM and further for understanding, managing and protecting aquatic ecosystems. This study aimed to compare moderate resolution imaging spectroradiometer (MODIS)-based CSPM retrieval models in order to find the optimal model for improving the CSPM estimation in Poyang Lake. The CSPM measurements on 27 September 2007 and their coincident MODIS Terra image were used to calibrate retrieval models with the least-squares technique. The CSPM 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 CSPM 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 CSPM 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 CSPM, respectively; while model validation indicated that, after removing two samples, the exponential models of blue and green band got biased CSPM estimations, the agreement between the measured and estimated CSPM 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 CSPM estimation and was the optimal model for CSPM estimation in this study, and more independent datasets should be obtained to further validate our finding for improving the CSPM estimation in Poyang Lake. |
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