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Remote Sensing
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  • Open Access

22 January 2020

Correction: Zhu, Q., et al. Hyperspectral Remote Sensing of Phytoplankton Species Composition Based on Transfer Learning. Remote Sensing 2019, 11, 2001

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and
1
State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai 200241, China
2
Institute of Eco-Chongming (IEC), East China Normal University, Shanghai 200062, China
*
Author to whom correspondence should be addressed.
The authors wish to make the following corrections to this paper [1]:
1. Figure 1 had 20 validation stations that were unlabeled, so the station labels were added.
Replace:
Figure 1 (Old Figure)
Remotesensing 12 00364 i001
with
Figure 1 (New Figure)
Remotesensing 12 00364 i002
2. Figure 10 had a confusion in the number of stations (No. 4-15), and Figure 10 and Figure 11 had a reversal on the color plate of chrysophyta and chlorophyta (phytoplankton community) in the bar and the scatter plot, so these were corrected. Replace:
Figure 10 (Old Figure)
Remotesensing 12 00364 i003
with
Figure 10 (New Figure)
Remotesensing 12 00364 i004
Replace:
Figure 11 (Old Figure)
Remotesensing 12 00364 i005
with
Figure 11 (New Figure)
Remotesensing 12 00364 i006
The authors confirm that these drawing mistakes have nothing to do with the science and technology of the published paper itself. The authors would like to apologize for any inconvenience caused to the readers by these changes.

Reference

  1. Zhu, Q.; Shen, F.; Shang, P.; Pan, Y.; Li, M. Hyperspectral Remote Sensing of Phytoplankton Species Composition Based on Transfer Learning. Remote Sens. 2019, 11, 2001. [Google Scholar] [CrossRef]

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