Deep Learning Method Based on Spectral Characteristic Rein-Forcement for the Extraction of Winter Wheat Planting Area in Complex Agricultural Landscapes

Round 1

Reviewer 1 Report

1. Why use GF ‐ 6 WFV/16m and Sentinel‐2A data? What is the reason?

2.Huaihe River is not on Figure 1

3. Line 92-131. The expression is a little confused. The difficulty of extracting winter wheat information is not clearly expressed.

4. What precision  is acceptable? It is not clear what precision is achieved in other documents and why this problem should still worth to be studied.

5.Figure 4. Flowchart is confusing

6. line 179 what is the details of "standard false color images"

7. With so many pixels, how do you get the  Figure 6 and Figure 7. 

8. Description of the CNN Model  is not clear enough

9. Line 345-346  What's the meaning of "improved after excluding the bands with poor distinguishing capacities." Which bands? what is the  excluding rule.

10. The full text only based on two images data, and the conclusion is not  reliable.

11. Line 375, What kind of  deep neural network. CNN is also a kind of DNN.

 

 

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

With interest, I read the manuscript. It is appreciated that the manuscript is easy to follow and not too long. The message is clear and of interest to the community. The authors proposed a method for large‐scale extraction of winter wheat by spectral-characteristic enhancement combined with a convolutional neural network (CNN). Proposed method seemed to be promising, however, I would suggest revision before the manuscript could be accepted. Please allow me to clarify.

 

1. There is a scope for improvement in the introduction section: a) additional emphasis on the significance of the study, b) scientific contribution of the paper.

2. There is not enough information provided as far as machine learning modeling is concerned. To mention a few: a. Details of hyperparameters used in this study for machine learning model and how they are tuned? b. Was there any feature normalization/scaling involved? Which sampling methos was used to pick samples to train and to test the model.

3. Line 159: Elaborate more on “These data were not included in the experiment and were only used for fine confirmation of feature types and to enhance the reliability of sample establishment”. What do you mean by fine confirmation? Was there any quantitative assessment of reliability of samples, if so, why? or why not?

 

4. Please provide more information on satellites products used in this study, were they TOA reflectance or surface reflectance? Was there any cloud/haze removal involved as part of preprocessing?

 

5. Since the manuscript focuses on winter wheat crop, its plant physiology plays an important role. More importantly, please elaborate on the implication of wheat plant life cycle on remote sensing data collection. How collecting the data in a particular time frame could impact the classification process in light of the critical growth benchmarks in wheat growth and development.

6. In the discussion section please explain how this methodology can be extended for other crops: potential challenges, advantages? 

 

 

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Round 2

Reviewer 2 Report

I would like to thank the authors for sincerely addressing my questions/concerns, I recommend the manuscript for publication in its current form.