# Rebuilding long time series global soil moisture products using the neural network adopting the microwave vegetation index (Correction)

Panpan Yao, Jiancheng Shi, Tianjie Zhao, Hui Lu, Amen Al Yaari

► To cite this version:

Panpan Yao, Jiancheng Shi, Tianjie Zhao, Hui Lu, Amen Al Yaari. Rebuilding long time series global soil moisture products using the neural network adopting the microwave vegetation index (Correction). Remote Sensing, 2017, 9 (8), 1 p. 10.3390/rs9080849. [https://doi.org/10.3390/rs9080849](https://doi.org/10.3390/rs9080849)

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Submitted on 25 May 2020

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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*

Panpan Yao<sup>1,2</sup> <sup>ID</sup>, Jiancheng Shi<sup>2,3,*</sup>, Tianjie Zhao<sup>2,3</sup>, Hui Lu<sup>3,4</sup> and Amen Al-Yaari<sup>5</sup>

Received: 10 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 m<fnref n="3" />/m<fnref n="3" />" should be replaced with "RMSE = 0.084 m<fnref n="3" />/m<fnref n="3" />".

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. [CrossRef]

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© 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/).

<footnote n="1">1 Graduate School of University of Chinese Academy of Sciences, Beijing 100049, China; yaopp@radi.ac.cn</footnote>

<footnote n="2">2 State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China; zhaotj@radi.ac.cn</footnote>

<footnote n="3">3 The Joint Center for Global Change Studies, Beijing 100875, China; luhuil@tsinghua.edu.cn</footnote>

<footnote n="4">4 Ministry of Education Key Laboratory for Earth System Modeling, and Department of Earth System Science, Tsinghua University, Beijing 100084, China</footnote>

<footnote n="5">5 INRA, UMR1391 ISPA, 33140 Villenave d'Ornon, France; amen.al-yaari@inra.fr</footnote>

<footnote>* Correspondence: shijc@radi.ac.cn; Tel.: +86-10-6483-8048</footnote>