Coupled approach for radiometric calibration and parameter retrieval to improve SPM estimations in turbid inland/coastal waters
| Autor: | Anna Wei, Qu Zhou, Liqiao Tian, Jian Li, Qingjun Song |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Propagation of uncertainty
Mean squared error business.industry Atmospheric correction 02 engineering and technology 021001 nanoscience & nanotechnology 01 natural sciences Atomic and Molecular Physics and Optics Exponential function 010309 optics Optics 0103 physical sciences Radiative transfer Environmental science Satellite 0210 nano-technology business Image resolution Radiometric calibration Remote sensing |
| Zdroj: | Optics express. 28(4) |
| ISSN: | 1094-4087 |
| Popis: | High-precision radiometric calibration (RC) coefficients are required to retrieve reliable water quality parameter products in turbid inland/coastal waters. However, unreliable RC coefficients when satellite sensors lack accurate and in-time RC may lead to pronounced uncertainties in the products through error propagation. To address this issue, a novel approach for estimating water quality parameters, taking suspended particulate matter (SPM) as a case, was proposed by coupling the procedures of RC and SPM model development. The coupled models were established using digital numbers (DNs) from target sensors and “in-situ” SPM measurements from concurrent well-calibrated reference sensors, with the RC coefficients introduced as unknown model parameters. The approach was tested and validated in varied Chinese inland/coastal regions, including the Hongze lake (HL), Taihu lake (TL), and Hangzhou bay (HB). The results show: (1) the DN-based SPM models can achieve a degree of accuracy comparable to reflectance-based SPM models with determination coefficients (R2) of 0.94, 0.92, and 0.72, and root-mean-square errors (RMSE) of 7.02 mg/L, 15.73 mg/L, and 619.2 mg/L for the HL, TL, and HB, respectively, and the biases less than 3% between the derived and official gain RC coefficients; (2) the uncertainty of SPM products increases exponentially as the RC uncertainty increases for exponential reflectance-based SPM models; (3) the DN-based SPM models are less sensitive to the uncertainties of atmospheric correction and RC coefficients, while the reflectance-based models suffer deeply. This study provides encouraging results to the improvement of SPM retrieval using the DN-based models by coupling RC and SPM retrieving processes, especially for sensors without precise RC coefficients. |
| Databáze: | OpenAIRE |
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