Correction: Yao, P. et al. Rebuilding Long Time Series Global Soil Moisture Products Using the Neural Network Adopted the Microwave Vegetation Index. Remote Sens. 2017, 9, 35

Panpan Yao; Jiancheng Shi; Tianjie Zhao; Hui Lu; Amen Al-Yaari

doi:10.3390/rs9080849

,

and

¹

Graduate School of University of Chinese Academy of Sciences, Beijing 100049, China

²

State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

³

The Joint Center for Global Change Studies, Beijing 100875, China

⁴

Ministry of Education Key Laboratory for Earth System Modeling, and Department of Earth System Science, Tsinghua University, Beijing 100084, China

Remote Sens.2017, 9(8), 849;https://doi.org/10.3390/rs9080849

Version Notes

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After publication of the research paper [1], the authors wish to make the following correction to this paper. In the fourth line from the bottom in abstract, due to a typing error, “RMSE = 0.84 m³/m³” should be replaced with “RMSE = 0.084 m³/m³”.

The changes do not affect the scientific results. The manuscript will be updated and the original will remain online on the article webpage, with a reference to this addendum. We apologize for any inconvenience caused by this mistake.

Reference

Yao, P.; Shi, J.; Zhao, T.; Lu, H.; Al-Yaari, A. Rebuilding Long Time Series Global Soil Moisture Products Using the Neural Network Adopting the Microwave Vegetation Index. Remote Sens. 2017, 9, 35. [Google Scholar] [CrossRef]

© 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

Correction: Yao, P. et al. Rebuilding Long Time Series Global Soil Moisture Products Using the Neural Network Adopted the Microwave Vegetation Index. Remote Sens. 2017, 9, 35

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