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

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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, MDPI, 2017, 9 (8), 1 p. �10.3390/rs9080849�. �hal-01607067�

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remote sensing

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^1,2 ^ID, Jiancheng Shi^2,3,*, Tianjie Zhao^2,3, Hui Lu^3,4and Amen Al-Yaari⁵

1 Graduate School of University of Chinese Academy of Sciences, Beijing 100049, China; [email protected]

2 State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China; [email protected]

3 The Joint Center for Global Change Studies, Beijing 100875, China; [email protected]

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; [email protected]

* Correspondence: [email protected]; Tel.: +86-10-6483-8048

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 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. [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/).

Remote Sens.2017,9, 849; doi:10.3390/rs9080849 www.mdpi.com/journal/remotesensing