Use of Indices Applied to Remote Sensing for Establishing Winter–Spring Cropping Areas in the Republic of Kazakhstan

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

the proposed work brings to mind a problem that unfortunately involves different areas of the globe. the proposed initiatives it could be useful but it should be taken into account, and from the text it doesn't is evident from the processing costs which will certainly increase.

  greater care and attention must be given to the system economic-political nature of the country

Author Response

Comments: The proposed work suggests a problem that unfortunately involves different areas of the globe. the proposed initiatives it could be useful, but it should be considered, and from the text it doesn't is evident from the processing costs which will certainly increase. Greater care and attention must be given to the system economic-political nature of the country

Response: Yes, totally agree, thank you. We are updated with more attention to the processing cost and system economic-political nature of the country.

Reviewer 2 Report

Comments and Suggestions for Authors

 1.  The title is not clear regarding the content

2.      About ABSTRACT

Please delimit the abstract to objective, methodology, results and conclusion in 200 words

3.      There is disorder and lack of clarity in the writing, the writing must be corrected throughout the document

4.      It is not clear what the problem is to be solved and how remote sensing supports them.

                     *Why should you recognize where the winter crops are?

*Don't farmers know how much land they cultivate?...

*Or is it the government side or the banks that want to know how much was grown?

*Will knowing this help improve crops? Yes like?

                     *How do you combine different technologies to achieve that?

5.      Please mention how crop management will be improved with your contribution.

6. References should be used at discretion, if you are only using them to point out that there are more people doing the same thing, without a description of the facts, it is not necessary to use three, just one is enough.

7.      On the other hand, if what you want is to test an index to improve something...the job´s title should mention it.

Author Response

Comments: The title is not clear regarding the content

Response: Yes, the title was updated

Comments: Please delimit the abstract to objective, methodology, results and conclusion in 200 words

Response: The abstract was updated with delimitation to the objective, methodology, results and conclusion in 200 words.

Comments: There is disorder and lack of clarity in the writing, the writing must be corrected throughout the document

Response: The writing was updated with emphasize on the clarity.

Comments: It is not clear what the problem is to be solved and how remote sensing supports them. *Why should you recognize where the winter crops are?

Response: The wheat production is one of the main agricultural crop productions in Kazakhstan, which is regulated and subsidize by the Kazakh Government. The monocultural crops are often get sick with different type of viruses. Moreover, Kazakhstan is very unstable with water availability: in some period of time the big floods cover the planning areas, in other period of time the big drought may happen. The proper strategies are necessary to adapt to mitigate these issues. Crop monitoring on the big plantations' areas would help to work on these issues.    

Winter crops constitute the main activity of Kazakh farmers in the foothill zone. The area sown with winter grain crops varies significantly from year to year depending on crop rotations carried out on farms and weather conditions. The development of a method for automatically recognizing the sowing mask of winter grain crops based on remote sensing is the basis for solving various problems of space monitoring and directly affects the condition and yield of winter grain crops and the timing and volume of various field work on farms.

Comments: *Don't farmers know how much land they cultivate.

Response:  The wheat production is one of the main agricultural crop productions in Kazakhstan, which is regulated and subsidize by the Kazakh Government.

The determination of the areas for cultivating fields and sowing crops on farms is based on taking into account the field area according to their land use map, which has not changed on farms for many years. Data from space monitoring of land cultivation show that there is a change in the area of ​​individual fields due to the development of new fields or changes in the configuration of fields (adding or reducing areas). Space data is capable of recording all changes occurring in the fields in real mode.

Comments: *Or is it the government side or the banks that want to know how much was grown?

Response: Yes, exactly. Actual data on the sown areas of agricultural crops according to remote sensing data are in demand information on farms, government agencies, insurance and banking structures with the different level of subsidize percentages.

Comments: *Will knowing this help improve crops? Yes like?

Response: Yes, it will these efforts will help to improve the crop monitoring activities. The actual sowing pattern of winter grain crops in a particular year is the basis for assessing the condition, yield, and volumes of agricultural work in the fields. It allows to detail the condition of the fields, identify depressed areas and timely carry out agrotechnical measures to improve the condition of the crops, including the required support from the Kazakh Government. For example, in foothill areas, depending on the topography and location of the fields, the contamination and condition of the crops on the field is uneven. In lowlands there is often increased contamination, which adversely affects the condition and yield of crops. Timely treatment of heavily infested areas can improve the condition and increase the yield of crops.

Comments: *How do you combine different technologies to achieve that?

Response: To solve the problem of automatically determining the sowing mask of winter grain crops based on the satellite index PLI (Plowed Land Index), the technology of joint processing of satellite and ground-based data on the location of fields of agricultural crops, including winter grains, is used. Subsequent tasks of assessing the condition, infestation, and determining the yield of winter grain crops based on satellite and ground-based information are under development in the subsequent studies

Comments: Please mention how crop management will be improved with your contribution.

Response: Satellite data will allow real-time assessment of the actual areas and timing of sowing winter grain crops, which will later be used to assess the condition and carry out agricultural work in depressed areas of fields. These efforts will also help farmers in communications and efficiency in demanding information preparations for the government agencies, insurance and banking structures to receive the proper level of subsidizing support.

Comments: References should be used at discretion, if you are only using them to point out that there are more people doing the same thing, without a description of the facts, it is not necessary to use three, just one is enough.

Response: Yes, updated

Comments: On the other hand, if what you want is to test an index to improve something...the job´s title should mention it.

Response: Yes, the title was updated

 

 

Reviewer 3 Report

Comments and Suggestions for Authors

Corrections and suggestions are in the attached file.

 

In general, the scientific manuscript shows quality for publication in the future. But currently it shows many basic errors easily fixed.

Comments for author File: Comments.pdf

Author Response

Comments: In general, the scientific manuscript shows quality for publication in the future. But currently it shows many basic errors easily fixed.

Response: Thank you, the manuscript was updated

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

Second review

Thank you for your attention

Abstract, is better

The wording is also clearer.

From this, it can be indicated that no new index is being developed, the combination of others that already make the determinations raised is being mentioned as a novelty itself and all of them use verification points. And that is the contribution, to establish that relationship, where it would have to be considered if this combination is more useful than others.

It is mentioned that with this it supports sustainable development, how is this? If the information it provides is merely descriptive, how is the association with sustainable development? Considering that this is a list of social, economic and environmental activities that allow maintaining a balance, which has as its goal, preserving heritage for future generations.

Now with a Drone flight and the associated software, more can be achieved to determine problems in crops or to establish their areas.

Title suggestion

“USE OF INDICES APPLIED TO REMOTE SENSING FOR ESTABLISHING WINTER-SPRING CROPPING AREAS IN THE REPUBLIC OF KAZAKHSTAN”

But please review the following

1. Line 84-87

How does this help to increase land productivity and sustainable development?

Please expand

2. Table 2. I don't understand, are these the names of the images used? If so, please describe the further

Why are there columns with empty spaces?

3. Line 206-207

Please correct the wording, it is very confusing “developed a methodology to identify winter crops and verify with satellite data”

Could it not be that “a combination of indices was used, using satellite data, to identify winter crops”

4. Line 399-401,

Please correct, it is not clear what you indicate about changes, were these in the entire area, or only in one section and you mention that you used the PLI index, but to determine surfaces should have a combination of this and another been used, you aren´t?

5. Table 3. Please change the way you mention the time periods, use month-year, I do not understand what 11-27.11 means, for example, and it only refers to the year 2021...work was done in 2022, where is that data.

5. Figure 15, I do not understand what the changes indicate, what is said in lines 399-401, does not indicate anything

7. Line 456-460

If you want to mention these quotes, which are not necessary, talk about them in depth, I had already asked you to remove them.

 

Conclusion

There is talk that the changes detected in the planted areas will be used to support improving government statistics, but that seems to be the only contribution of this modification to the indices

I recommend that the work adjust its wording to the facts, that it not talks about sustainability when there is none and that it supports the veracity of its methodology with tables that compare results of each one the indices, using the same satellite photos

 I hope I have helped improve this writing

Author Response

Comment 0:

Thank you for your attention

Abstract, is better

The wording is also clearer.

From this, it can be indicated that no new index is being developed, the combination of others that already make the determinations raised is being mentioned as a novelty itself and all of them use verification points. And that is the contribution, to establish that relationship, where it would have to be considered if this combination is more useful than others.

It is mentioned that with this it supports sustainable development, how is this? If the information it provides is merely descriptive, how is the association with sustainable development? Considering that this is a list of social, economic and environmental activities that allow maintaining a balance, which has as its goal, preserving heritage for future generations.

Now with a Drone flight and the associated software, more can be achieved to determine problems in crops or to establish their areas.

Title suggestion

“USE OF INDICES APPLIED TO REMOTE SENSING FOR ESTABLISHING WINTER-SPRING CROPPING AREAS IN THE REPUBLIC OF KAZAKHSTAN”

Response 0:

Thank you very much for the valuable thoughts, comments.  

The title was updated, based on your recommendations:

Use of indices applied to Remote Sensing for establishing winter – spring plowing cropping areas in the republic of Kazakhstan. 

The article was updated accordingly following your suggestions.

Comment 1: Line 84-87

How does this help to increase land productivity and sustainable development?

Please expand

Response 1:

Remote sensing technologies applications allow monitoring the big farming areas of soil and crops condition with connected subsiding support systems by the state controlling agencies. The timely implementation of agricultural measures, such as fertilization and plant protection, control of land productivity works on the sustainable development of crop yields and soil conditions. Digitized data on the condition of farm fields allows more effectively to plan and manage resources, including water, fertilizers and pesticides. Optimization of winter grain production using remote sensing allows them to obtain the monitoring data more efficiently.The development of modern agricultural technologies and the need for their maintenance create advancements in remote sensing technologies applications.

Comment 2:

Table 2. I don't understand, are these the names of the images used? If so, please describe the further

Why are there columns with empty spaces?

Response 2:

The names of the images are the standard identifiers for the Sentinel-2 satellite datasets. Each identifier consists of several parts that provide information about the location and date of acquisition. As an example, T42TWN_20210913, T42TXN_20210928, T42TXM_20210918 images: The First letter T - indicates that this is a level 1C image, atmospherically corrected and ready for use. 

The next two numbers 42 - are related to the UTM (Universal Transverse Mercator) zone code.

The TWN, TXN, TXM are related to the different scenes within the UTM zone, including the letter T is the latitude band strip within the zone 42. The two-letters codes WN, XN, XM are the territory squares within the UTM zone 42, designed by the MGRS (Military Grid Reference System). Each MGRS square (WN, XN, XM) is 100x100 km within the UTM zone 42. The left part of the combination letters W, X, X represent the square image position on the longitude axis.The right part of the combination letters N, N, M represent the square image position on the latitude axis.

WN: W - indicates a specific longitude position (east-west) within the zone. N - indicates a latitude position (north-south) within the zone.

XN: X - another longitude square adjacent to square "W", N - the same latitude position as square "WN".

XM: X - the same longitude square as "XN", M - a square located further south in latitude compared to "N".

The square codes WN, XN, XM represent different areas within the same UTM zone 42. These squares are necessary to indicate exactly what part of the earth's surface was captured by the Sentinel-2 satellite. Such designations allow precisely identifying the territory covered by a specific image.

The final numbers represent the image collected in the format year month day YYYYMMDD, such as 20210913 (2021-year September 13), 20210928 (2021-year September 09), 20210918 2021-year year September 18). 

Within each territory, square scenes (WN, XN, XM) have differences in cloudiness. The scenes without cloudiness were used for the research applications. The WN scenes were without cloudiness. Some   XN, XM had high cloudiness and were excluded from the data processing, that is why some columns within the XN, XM scenes are empty.  

Comment 3:

Line 206-207

Please correct the wording, it is very confusing “developed a methodology to identify winter crops and verify with satellite data”

Could it not be that “a combination of indices was used, using satellite data, to identify winter crops”

Response 3:

yes, corrected, your suggestions were applied:

“a combination of indices was used, using satellite data, to identify winter crops”,

Comment 4:

Line 399-401,

Please correct, it is not clear what you indicate about changes, were these in the entire area, or only in one section and you mention that you used the PLI index, but to determine surfaces should have a combination of this and another been used, you aren´t?

Response 4:

yes, updated, corrected:

“In the research area section, covered by the collected Satellite datasets.” 

Comment 5:

Table 3. Please change the way you mention the time periods, use month-year, I do not understand what 11-27.11 means, for example, and it only refers to the year 2021...work was done in 2022, where is that data.

Response 5:

Yes, the time periods were updated to day-month-year format.

 The investigated remote sensing datasets included the Autumn 2021 and Spring 2022.  The Autumn period of 2021 was the main investigated period of time, shown in the table 3 and Figure 15, since this is the time when the main agrotechnical works were provided for the winter crops. Spring 2022 was used just for the exclusion of other Spring crops, that is why they were now included in table 3 and Figure 15. The main research goal was dedicated to the Autumn period 2021, winter crops.

Comment 6:

Figure 15, I do not understand what the changes indicate, what is said in lines 399-401, does not indicate anything

Response 6:

Figure 15 is a bar chart illustrating the percentage change in plowing during the Autumn period of 2021. The chart displays the data by periods to highlight the key stages and intensity of plowing activities: from September 5 to September 13, 29% of the total plowing work activities, from September 14 to September 26, 14% of the total plowing work, and so on for the following periods. This approach is important in the period of time, days and how long the plowing works were. In Southern Kazakhstan, it is critical to complete the Autumn plowing by the end of October with some correction on days, depending on weather conditions, soil moisture and temperature. This is necessary to ensure that winter crops can germinate before the onset of winter. Successful germination ensures deep rooting of plants, which contributes to their good overwintering and, subsequently, has a positive effect on crop yields. If plowing and sowing are carried out later or too earlier than the optimal period, the plants do not have time to take root before the onset of cold weather, which leads to poor wintering and, as a consequence, a decrease in yield in the spring. Thus, the data presented in Figure 15 allow us to monitor, to analyze the periods of the main plowing activity and their compliance with the agronomic requirements for the optimal growth of winter crops in South Kazakhstan.

Comment 7:

Line 456-460

If you want to mention these quotes, which are not necessary, talk about them in depth, I had already asked you to remove them.

Response 7:

These quotes were deleted.

 

 

 

 

 

 

 

 

 

 

 

Reviewer 3 Report

Comments and Suggestions for Authors

The corrections and suggestions were made.

Author Response

Comment 0:

Thank you for your attention

Abstract, is better

The wording is also clearer.

From this, it can be indicated that no new index is being developed, the combination of others that already make the determinations raised is being mentioned as a novelty itself and all of them use verification points. And that is the contribution, to establish that relationship, where it would have to be considered if this combination is more useful than others.

It is mentioned that with this it supports sustainable development, how is this? If the information it provides is merely descriptive, how is the association with sustainable development? Considering that this is a list of social, economic and environmental activities that allow maintaining a balance, which has as its goal, preserving heritage for future generations.

Now with a Drone flight and the associated software, more can be achieved to determine problems in crops or to establish their areas.

Title suggestion

“USE OF INDICES APPLIED TO REMOTE SENSING FOR ESTABLISHING WINTER-SPRING CROPPING AREAS IN THE REPUBLIC OF KAZAKHSTAN”

Response 0:

Thank you very much for the valuable thoughts, comments.  

The title was updated, based on your recommendations:

Use of indices applied to Remote Sensing for establishing winter – spring plowing cropping areas in the republic of Kazakhstan. 

The article was updated accordingly following your suggestions.

Comment 1: Line 84-87

How does this help to increase land productivity and sustainable development?

Please expand

Response 1:

Remote sensing technologies applications allow monitoring the big farming areas of soil and crops condition with connected subsiding support systems by the state controlling agencies. The timely implementation of agricultural measures, such as fertilization and plant protection, control of land productivity works on the sustainable development of crop yields and soil conditions. Digitized data on the condition of farm fields allows more effectively to plan and manage resources, including water, fertilizers and pesticides. Optimization of winter grain production using remote sensing allows them to obtain the monitoring data more efficiently.The development of modern agricultural technologies and the need for their maintenance create advancements in remote sensing technologies applications.

Comment 2:

Table 2. I don't understand, are these the names of the images used? If so, please describe the further

Why are there columns with empty spaces?

Response 2:

The names of the images are the standard identifiers for the Sentinel-2 satellite datasets. Each identifier consists of several parts that provide information about the location and date of acquisition. As an example, T42TWN_20210913, T42TXN_20210928, T42TXM_20210918 images: The First letter T - indicates that this is a level 1C image, atmospherically corrected and ready for use. 

The next two numbers 42 - are related to the UTM (Universal Transverse Mercator) zone code.

The TWN, TXN, TXM are related to the different scenes within the UTM zone, including the letter T is the latitude band strip within the zone 42. The two-letters codes WN, XN, XM are the territory squares within the UTM zone 42, designed by the MGRS (Military Grid Reference System). Each MGRS square (WN, XN, XM) is 100x100 km within the UTM zone 42. The left part of the combination letters W, X, X represent the square image position on the longitude axis.The right part of the combination letters N, N, M represent the square image position on the latitude axis.

WN: W - indicates a specific longitude position (east-west) within the zone. N - indicates a latitude position (north-south) within the zone.

XN: X - another longitude square adjacent to square "W", N - the same latitude position as square "WN".

XM: X - the same longitude square as "XN", M - a square located further south in latitude compared to "N".

The square codes WN, XN, XM represent different areas within the same UTM zone 42. These squares are necessary to indicate exactly what part of the earth's surface was captured by the Sentinel-2 satellite. Such designations allow precisely identifying the territory covered by a specific image.

The final numbers represent the image collected in the format year month day YYYYMMDD, such as 20210913 (2021-year September 13), 20210928 (2021-year September 09), 20210918 2021-year year September 18). 

Within each territory, square scenes (WN, XN, XM) have differences in cloudiness. The scenes without cloudiness were used for the research applications. The WN scenes were without cloudiness. Some   XN, XM had high cloudiness and were excluded from the data processing, that is why some columns within the XN, XM scenes are empty.  

Comment 3:

Line 206-207

Please correct the wording, it is very confusing “developed a methodology to identify winter crops and verify with satellite data”

Could it not be that “a combination of indices was used, using satellite data, to identify winter crops”

Response 3:

yes, corrected, your suggestions were applied:

“a combination of indices was used, using satellite data, to identify winter crops”,

Comment 4:

Line 399-401,

Please correct, it is not clear what you indicate about changes, were these in the entire area, or only in one section and you mention that you used the PLI index, but to determine surfaces should have a combination of this and another been used, you aren´t?

Response 4:

yes, updated, corrected:

“In the research area section, covered by the collected Satellite datasets.” 

Comment 5:

Table 3. Please change the way you mention the time periods, use month-year, I do not understand what 11-27.11 means, for example, and it only refers to the year 2021...work was done in 2022, where is that data.

Response 5:

Yes, the time periods were updated to day-month-year format.

 The investigated remote sensing datasets included the Autumn 2021 and Spring 2022.  The Autumn period of 2021 was the main investigated period of time, shown in the table 3 and Figure 15, since this is the time when the main agrotechnical works were provided for the winter crops. Spring 2022 was used just for the exclusion of other Spring crops, that is why they were now included in table 3 and Figure 15. The main research goal was dedicated to the Autumn period 2021, winter crops.

Comment 6:

Figure 15, I do not understand what the changes indicate, what is said in lines 399-401, does not indicate anything

Response 6:

Figure 15 is a bar chart illustrating the percentage change in plowing during the Autumn period of 2021. The chart displays the data by periods to highlight the key stages and intensity of plowing activities: from September 5 to September 13, 29% of the total plowing work activities, from September 14 to September 26, 14% of the total plowing work, and so on for the following periods. This approach is important in the period of time, days and how long the plowing works were. In Southern Kazakhstan, it is critical to complete the Autumn plowing by the end of October with some correction on days, depending on weather conditions, soil moisture and temperature. This is necessary to ensure that winter crops can germinate before the onset of winter. Successful germination ensures deep rooting of plants, which contributes to their good overwintering and, subsequently, has a positive effect on crop yields. If plowing and sowing are carried out later or too earlier than the optimal period, the plants do not have time to take root before the onset of cold weather, which leads to poor wintering and, as a consequence, a decrease in yield in the spring. Thus, the data presented in Figure 15 allow us to monitor, to analyze the periods of the main plowing activity and their compliance with the agronomic requirements for the optimal growth of winter crops in South Kazakhstan.

Comment 7:

Line 456-460

If you want to mention these quotes, which are not necessary, talk about them in depth, I had already asked you to remove them.

Response 7:

These quotes were deleted.

Thank you very much for you time and very valuable comments, which help to improve our article! 

Round 3

Reviewer 2 Report

Comments and Suggestions for Authors

Thank you, the work has improved but I still have trouble understanding some sections. I suggest:

1. Work on shorter paragraphs,

2. Be very careful with your punctuation,

3. Check the periods and commas

4. Please clarify figure 15, what you explain about it is not very noticeable in the graph, in addition to repeating the name inside and outside the same.

Author Response

Comment 1. Work on shorter paragraphs,

Comment 2. Be very careful with your punctuation,

Comment 3. Check the periods and commas

Comment 4. Please clarify figure 15, what you explain about it is not very noticeable in the graph, in addition to repeating the name inside and outside the same.

Response: Yes, we worked on all your comments. Thank you very much for your time! You helped much to improve our article!