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Open AccessCorrection

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

by 1,2, 2,3,*, 2,3, 3,4 and 5
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.
Remote Sens. 2017, 9(8), 849; https://doi.org/10.3390/rs9080849
Received: 10 August 2017 / Revised: 14 August 2017 / Accepted: 14 August 2017 / Published: 16 August 2017
Note: In lieu of an abstract, this is an excerpt from the first page.

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”.[...] View Full-Text
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.

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