<p>This data uses Sentinel-2 optical satellite data from April to October 2022 as the data source, and a sampling random forest regression (RFR) method is used to build a remote sensing estimation model of chlorophyll a concentration in Xinjiang lakes. The data is Abers projection in the CGCS2000 coordinate system with an accuracy of 10 meters. </p>
| data size | 3.9 GiB |
|---|---|
| data format | grid |
| Coordinate system | CGCS2000 |
| Projection | Albers projection |
Using Sentinel 2 optical satellite data from April to October 2022 as the data source
Use Sentinel 2 A/B MSI with good radiation performance. Obtained L1C data from ESA's Copernicus Data Open Center. Atmospheric correction is carried out using the SEN2COR algorithm provided by ESA. However, SEN2COR is a terrestrial atmosphere correction algorithm that needs to be targeted to further remove the effects of sky light, solar flares and residual aerosol scattering. A sampling random forest regression (RFR) method was used to build a water quality parameter model. By adjusting the optimal input variables of the input algorithm, the optimal hyperparameters of each algorithm are obtained through the grid search method.
A large number of field surveys and satellite-earth synchronous data were used to conduct model research. The results showed that the RFR chlorophyll a concentration algorithm had high accuracy, with an uncertainty of 21.92%, a deviation of 4.29%, a slope of 0.64, and a root-mean-square logarithmic error of 0.235.
| # | number | name | type |
| 1 | 2021xjkk1400 | 2021xjkk1400 | National Science and technology support program |
This work is licensed under a
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Commons Attribution 4.0 International License.
| # | title | file size |
|---|---|---|
| 1 | 2021xjkk1400-76-2023031076 |
©Copyright 2021-. Xinjiang Institute of Ecology and Geography, CAS
No. 818 Beijing South Road, Urumqi, Xinjiang, China, 830011
