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Remote Sensing
Volume 14
Issue 15
10.3390/rs14153817
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Article
Peer-Review Record

Monitoring Land Vegetation from Geostationary Satellite Advanced Himawari Imager (AHI)

Remote Sens. 2022, 14(15), 3817; https://doi.org/10.3390/rs14153817
by Shengqi Li 1,2, Xiuzhen Han 3 and Fuzhong Weng 2,*
Reviewer 1:
David Boansi
Reviewer 2: Anonymous
Reviewer 3: Anonymous
Remote Sens. 2022, 14(15), 3817; https://doi.org/10.3390/rs14153817
Submission received: 23 June 2022 / Revised: 1 August 2022 / Accepted: 2 August 2022 / Published: 8 August 2022
(This article belongs to the Special Issue Atmospheric and Surface Modeling, Data Assimilation, and Forecasting of Remote Sensing)

Round 1

Reviewer 1 Report

The work is ok, but requires some minor spell checks

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

1、I suggest simplifying the formulas in sections 2.4 and 2.5. The formulas quoted from the literature are recommended to be placed in the appendix.

2、In Figure 1, for the red band (0.64 μ m), AHI has a larger bandwidth than MODIS. Does this affect NDVI calculation?

3、In Figure 11, it is suggested to add the comparison of NDVI derived from 1 day AHI and 16 day MODIS, thus the advantages of higher time resolution could be presented.

4、How to make a quantitative comparison of NDVI from different data sources? That is, how to calibrate the accuracy of NDVI? I suggest supplementing relevant analysis, such as the correlation with MODIS and the amplitude difference between AHI and MODIS.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

This study used the observation data of the geostationary satellite Advanced Himawari Imagers (AHI). The AHI reflectance at visible and near-infrared bands was first corrected to the surface reflectance, and then further normalized to form an angular independent reflectance by using a BRDF model. Finally, the surface vegetation index is calculated and synthesized from the day-time AHI data. Geostationary satellite datasets were used to solve the problem of more cloud cover, which was the main innovation point of this research. The following problems need to be solved:

1) In Table 1, a column should be added to indicate the wavelength range of each band (for example, Red, NIR, etc.).

2) There is no relevant introduction to the study area of this research.

3) The formats of the formulas should be consistent.

4) The serial numbers (e.g. :(g) and (h)) in FIG. 6 , 7 and 10 are not clearly marked as in FIG. 8 and FIG. 9.

 

5) Reference No. 21 should be translated into English.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 3 Report

Accept.

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