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Statistical model development and estimation of suspended particulate matter concentrations with Landsat 8 OLI images of Dongting Lake, China.

Authors :
Wu, Guofeng
Cui, Lijuan
Liu, Liangjie
Chen, Fangyuan
Fei, Teng
Liu, Yaolin
Source :
International Journal of Remote Sensing; Jan2015, Vol. 36 Issue 1, p343-360, 18p, 2 Charts, 3 Graphs, 2 Maps
Publication Year :
2015

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 theCSPMretrieval models and further to estimate theCSPMvalues of Dongting Lake. One Landsat 8 OLI image and 53CSPMmeasurements were employed to calibrate Landsat 8-basedCSPMretrieval models. TheCSPMvalues derived from coincident Landsat 8 OLI and Moderate Resolution Imaging Spectroradiometer (MODIS) images were compared to validate calibrated Landsat 8-basedCSPMmodels. After the best stable Landsat 8-basedCSPMretrieval model was further validated using an independent Landsat 8 OLI image and its coincidentCSPMmeasurements, it was applied to four Landsat 8 OLI images to retrieve theCSPMvalues 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 ofCSPM; 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 ofCSPM(SE = 5.18–5.52 mg l–1). By comparing the MODIS- and Landsat 8-basedCSPMvalues, an exponential model of the Landsat 8 OLI red band (CSPM = 1.1034 × exp(23.61 × R)) obtained the best consistentCSPMestimations 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 estimatedCSPMvalues at a significance level of 0.05 (r = 0.91,p < 0.05). TheCSPMspatiotemporal distribution derived from four Landsat 8 images revealed a clear spatial distribution pattern ofCSPMin 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 retrievingCSPMand provided a foundation for retrieving the spatial distribution ofCSPMaccurately from this new data source in Dongting Lake. [ABSTRACT FROM PUBLISHER]

Details

Language :
English
ISSN :
01431161
Volume :
36
Issue :
1
Database :
Complementary Index
Journal :
International Journal of Remote Sensing
Publication Type :
Academic Journal
Accession number :
100437682
Full Text :
https://doi.org/10.1080/01431161.2014.995273