Statistical model development and estimation of suspended particulate matter concentrations with Landsat 8 OLI images of Dongting Lake,China |
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| Authors: | Guofeng Wu Lijuan Cui Liangjie Liu Fangyuan Chen Teng Fei Yaolin Liu |
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| Affiliation: | 1. Key Laboratory for Geo-Environmental Monitoring of Coastal Zone of the National Administration of Surveying, Mapping and GeoInformation and Shenzhen Key Laboratory of Spatial Smart Sensing and Services and College of Life Sciences, Shenzhen University, 518060 Shenzhen, China;2. School of Resource and Environmental Science and Key Laboratory of Geographic Information System of the Ministry of Education, Wuhan University, 430079 Wuhan, Chinaguofeng.wu@szu.edu.cn;4. Institute of Wetland Research, Chinese Academy of Forestry, 100091 Beijing, China;5. Tianjin Institute of Surveying and Mapping, 300381 Tianjin, China;6. School of Resource and Environmental Science and Key Laboratory of Geographic Information System of the Ministry of Education, Wuhan University, 430079 Wuhan, China |
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| Abstract: | Suspended particulate matter (SPM) is a dominant water constituent of case-II waters, and SPM concentration (CSPM) is a key parameter describing water quality. This study, using Landsat 8 Operational Land Imager (OLI) images, aimed to develop the CSPM retrieval models and further to estimate the CSPM values of Dongting Lake. One Landsat 8 OLI image and 53 CSPM measurements were employed to calibrate Landsat 8-based CSPM retrieval models. The CSPM values derived from coincident Landsat 8 OLI and Moderate Resolution Imaging Spectroradiometer (MODIS) images were compared to validate calibrated Landsat 8-based CSPM models. After the best stable Landsat 8-based CSPM retrieval model was further validated using an independent Landsat 8 OLI image and its coincident CSPM measurements, it was applied to four Landsat 8 OLI images to retrieve the CSPM values in the South and East Dongting Lake. Model calibration results showed that two exponential models of the red band explained 61% (estimated standard error (SE) = 7.96 mg l–1) and 67% (SE = 6.79 mg l–1) of the variation of CSPM; two exponential models of the red:panchromatic band ratio obtained 81% (SE = 5.48 mg l–1) and 77% (SE = 4.96 mg l–1) fitting accuracy; and four exponential and quadratic models of the infrared band explained 72–83% of the variation of CSPM (SE = 5.18–5.52 mg l–1). By comparing the MODIS- and Landsat 8-based CSPM values, an exponential model of the Landsat 8 OLI red band (CSPM = 1.1034 × exp(23.61 × R)) obtained the best consistent CSPM estimations with the MODIS-based model (r = 0.98, p < 0.01), and its further validation result using an independent Landsat 8 OLI image showed a significantly strong correlation between the measured and estimated CSPM values at a significance level of 0.05 (r = 0.91, p < 0.05). The CSPM spatiotemporal distribution derived from four Landsat 8 images revealed a clear spatial distribution pattern of CSPM in the South and East Dongting Lake, which was caused by natural and anthropogenic factors together. This study confirmed the potential of Landsat 8 OLI images in retrieving CSPM and provided a foundation for retrieving the spatial distribution of CSPM accurately from this new data source in Dongting Lake. |
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