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Correction

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

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
5
INRA, UMR1391 ISPA, 33140 Villenave d’Ornon, France
*
Author to whom correspondence should be addressed.
Submission received: 10 August 2017 / Revised: 14 August 2017 / Accepted: 14 August 2017 / Published: 16 August 2017
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

  1. 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]

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MDPI and ACS Style

Yao, P.; Shi, J.; Zhao, T.; Lu, H.; Al-Yaari, A. 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. Remote Sens. 2017, 9, 849. https://0-doi-org.brum.beds.ac.uk/10.3390/rs9080849

AMA Style

Yao P, Shi J, Zhao T, Lu H, Al-Yaari A. 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. Remote Sensing. 2017; 9(8):849. https://0-doi-org.brum.beds.ac.uk/10.3390/rs9080849

Chicago/Turabian Style

Yao, Panpan, Jiancheng Shi, Tianjie Zhao, Hui Lu, and Amen Al-Yaari. 2017. "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" Remote Sensing 9, no. 8: 849. https://0-doi-org.brum.beds.ac.uk/10.3390/rs9080849

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