XJ_COTTON10: The 10-m cotton maps in Xinjiang, China during 2018-2021

The datasets accompany the paper "The 10-m cotton maps in Xinjiang, China during 2018–2021" that was published in Scientific Data on Oct. 10, 2023. The datasets contain the 10-m cotton maps of Xinjiang (XJ_COTTON10) from 2018 to 2021. They were developed through supervised classification using high-quality in-field samples and multi-source remote sensing data on the Google Earth Engine (GEE) platform.

Citation:

[1] Kang, X., Huang, C., Chen, J.M., Lv, X., Wang, J., Zhong, T., Wang, H., Fan, X., Ma, Y., Yi, X., Zhang, Z., Zhang, L., Tong, Q., 2023. The 10-m cotton maps in Xinjiang, China during 2018-2021. Sci Data 10, 688. doi:10.1038/s41597-023-02584-3

[2] Lang, P., Zhang, L., Huang, C., Chen, J., Kang, X., Zhang, Z., Tong, Q., 2023. Integrating environmental and satellite data to estimate county-level cotton yield in Xinjiang Province. Frontiers in Plant Science 13, 1048479. doi:10.3389/fpls.2022.1048479

[3] Kang, X., Huang, C., Zhang, L., Zhang, Z., Lv, X., 2022. Downscaling solar-induced chlorophyll fluorescence for field-scale cotton yield estimation by a two-step convolutional neural network. Computers and Electronics in Agriculture 201, 107260. doi:10.1016/j.compag.2022.107260

[4] Kang, X., Huang, C., Zhang, L., Wang, H., Zhang, Z., Lv, X., 2023. Regional-scale cotton yield forecast via data-driven spatio-temporal prediction (STP) of solar-induced chlorophyll fluorescence (SIF). Remote Sensing of Environment 299, 113861. doi:10.1016/j.rse.2023.113861