<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. The land biomass is extracted through machine learning. The quality control mainly uses the 2021-2022 land biomass measurement data for training samples and verification samples selection, and part of it uses soil quality survey data from the natural resources department 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 the random forest algorithm for terrestrial biomass inversion calculation. The data resolution is 10m. Among them, the training samples of the random forest algorithm include measured forest data from the western section of Tianshan Mountains.
Quality control mainly uses the measured land biomass data from 2021 to 2022 in Xinjiang for training samples and verification samples, and combines the use of survey data from the forestry and natural resources department for accuracy inspection and evaluation.
| # | number | name | type |
| 1 | 2021xjkk1400 | 2021xjkk1400 | National Science and technology support program |
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CSTR:33110.11.ariddc.01333
10.12389/ariddc.01333