<p>This data is for further processing using sentinel-2 reflectance product data. The original data is the 10-meter monthly Sentinel-2 reflectance mosaic data set in Xinjiang. Soil salt is extracted through machine learning. The quality control mainly uses the 2021-2022 soil salt measurement data in Xinjiang. Training samples and verification samples are selected, and some soil quality survey data from the natural resources department are used for accuracy inspection and evaluation. </p>
The main source of Sentinel-2 reflectivity data is downloaded from ESA. The rest of the auxiliary data sources are on-site measurement data and are generated independently.
This dataset is based on comparing verification data from various machine learning such as random forest, gradient regression, and support vector machines, and selecting random forest algorithm to carry out soil salt inversion calculation. The data resolution is 10m. Among them, the training samples of the continuous forest algorithm include 30-cm surface soil conductivity data measured from the soil surface in Turpan Hami City, Aibi Lake Basin, Aksu Xinhe County, Kashgar Shufu County, etc.
Quality control mainly uses the measured soil salt data from 2021 to 2022 in Xinjiang for training samples and verification samples, and partially uses the soil quality survey data from the natural resources department for accuracy inspection and evaluation. The measurement method for soil electrical conductivity is the electrode method, which meets the measurement requirements of (HJ 802-2016).
| # | 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.ariddc.01339
10.12389/ariddc.01339