Front. Environ. Sci. Frontiers in Environmental Science Front. Environ. Sci. 2296-665X Frontiers Media S.A. 1205591 10.3389/fenvs.2023.1205591 Environmental Science Correction Corrigendum: Spatiotemporal features of the soil moisture across Northwest China using remote sensing data, reanalysis data, and global hydrological model Wang et al. 10.3389/fenvs.2023.1205591 Wang Meijun 1 2 Yin Gang 1 3 Mao Min 1 2 Zhang Hao 4 Zhang Hua 1 Hu Zengyun 2 4 5 * Chen Xi 2 4 5 * 1 College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, Xinjiang, China 2 Research Center for Ecology and Environment of Central Asia, Chinese Academy of Sciences, Urumqi, Xinjiang, China 3 Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi, Xinjiang, China 4 University of Chinese Academy of Sciences, Beijing, China 5 State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang, China

Edited and reviewed by: Lunche Wang, China University of Geosciences Wuhan, China

 *Correspondence: Zengyun Hu, huzengyun@ms.xjb.ac.cn; Xi Chen, chenxi@ms.xjb.ac.cn 05 05 2023 2023 11 1205591 14 04 2023 21 04 2023 Copyright © 2023 Wang, Yin, Mao, Zhang, Zhang, Hu and Chen. 2023 Wang, Yin, Mao, Zhang, Zhang, Hu and Chen

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 A Corrigendum on Spatiotemporal features of the soil moisture across Northwest China using remote sensing data, reanalysis data, and global hydrological model by Wang M, Yin G, Mao M, Zhang H, Zhang H, Hu Z and Chen X (2023). Front. Environ. Sci. 11:1164895. doi: 10.3389/fenvs.2023.1164895 soil moisture microwave remote sensing data lobal hydrological model reanalysis data spatiotemporal characteristics section-at-acceptance Atmosphere and Climate

In the published article, there are some missing references both in section 2 Study area, dataset, and methodology, sub-section 2.3 Methodologies and in the section References. The corrected paragraph and the corresponding references appear below:

“The accuracy evaluation methods include the correlation coefficient (CC), relative error (RE), root mean square error (RMSE), distance between indices of simulation and observation (DISO) and the triple collocation (TC) method. The DISO index is widely used in many fields, such as climate change, medicine, and economics (Hu et al., 2019; Hu et al., 2020; Zhou et al., 2021; Hu et al., 2022; Liu et al., 2022; Yin et al., 2022; Zhang et al., 2022). TC (Stoffelen, 1998; Gruber et al., 2016) is a statistical method used to estimate the random error variance of three independent datasets. The specific method is described in the Supplementary Materials.”

The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.

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