<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 for lake water transparency in Xinjiang. The data is Abers projection in the CGCS2000 coordinate system with an accuracy of 10 meters. </p>
Use 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 are used to conduct model research. The results show that the RFR transparency algorithm has high accuracy, with an uncertainty of 11.24%, a deviation of 2.37%, a slope of 0.97, and a root-mean-square logarithmic error of 0.119.
| # | number | name | type |
| 1 | 2021xjkk1400 | 2021xjkk1400 | National Science and technology support program |
This work is licensed under a
Creative
Commons Attribution 4.0 International License.
CSTR:33110.11.XIEG.xjsedata.2022.00000109
10.12389/XIEG.XJSEDATA.2024.00100098