Space-Time Dynamics of Land Use in the Municipality of Goianésia Do Pará, Brazil
Round 1
Reviewer 1 Report
The topic of this paper is certainly within the journal scope, but I am not sure that it is in the topic of the special issue.
Looking at the call for papers and at the position of the two guest editors,
I guess that the special issue is intended for papers covering technical aspects of spatial and temporal databases, in the field of computer science and engineering.
This paper, instead is definitively on the side of applications, i.e.,
environmental sciences. It presents a case study and, as far as I can be competent to judge, it is a good paper.
Lines 128-129: this is a repeated sentence.
Table 1 (and maybe Table 2): it can be useful for the reader to have a plot
with the same information, in addition to the table. (not mandatory)
Figure 2: the labels with highway names cover quite a large part of the images, and they are already shown in Figure 1. I suggest to remove them from Figure 2. On line 201, Figure 1 can be referred instead of Figure 2.
Lines 169-172, 184-188, 255-261:
It is not so useful to repeat the same numbers, alteady apperaring in the table, in the text. Such numbers have many digits and are visually difficult to follow in text (and they are already in the tables).
In the text, one could say "about" and round the numbers, or provide
redution/increasing rate, instead.
Highway names are sometimes written as PA-150 and sometimes as PA150, etc.
The red color in Figure 2 (urban areas) is very hardly visible. It is almost
impossible to appreciate the increasing presence of this color through the years. Can we have a close-up on the area of town Goianesia do Para'?
Lines 272-275: this paragraph is not so clear, probably it needs more words to explain.
Line 285 has a typo: .... fragmentation HAS ....
Author Response
Response to Reviewer 1 Comments
The topic of this paper is certainly within the journal scope, but I am not sure that it is in the topic of the special issue. Looking at the call for papers and at the position of the two guest editors, I guess that the special issue is intended for papers covering technical aspects of spatial and temporal databases, in the field of computer science and engineering. This paper instead is definitively on the side of applications, i.e., environmental sciences. It presents a case study and, as far as I can be competent to judge, it is a good paper.
Response: We appreciate the time you took to thoroughly review our work. In terms of the special issue. Our paper works with Geographic information sciences and remote sensing, which usually are connected to spatiotemporal data and databases, a topic included in the special issue theme of spatiotemporal data.
Below, we respond to each of your comments:
Point 1: Lines 128-129: this is a repeated sentence.
Response 1: We agree with you. The respective adjustments have been made in the lines 131-135.
Point 2: Table 1 (and maybe Table 2): it can be useful for the reader to have a plot with the same information, in addition to the table. (not mandatory)
Response 2: We appreciate your suggestion; however, we have consulted similar studies and we have noted that this type of data is usually presented in tables. We would prefer to leave it as it is.
Point 3: Figure 2: the labels with highway names cover quite a large part of the images, and they are already shown in Figure 1. I suggest to remove them from Figure 2. On line 201, Figure 1 can be referred instead of Figure 2.
Response 3: We understood your observation. To address it, we have made the corresponding adjustments to Figure 2. In terms of line 201(now line 212), the respective change has been made.
Point 4: Lines 169-172, 184-188, 255-261: It is not so useful to repeat the same numbers, already appearing in the table, in the text. Such numbers have many digits and are visually difficult to follow in text (and they are already in the tables). In the text, one could say "about" and round the numbers, or provide reduction/increasing rate, instead.
Response 4: We understood your point of view. To address it, adjustments have been made. You can find them in lines 180- 183, 196- 198, and 267.
Point 5: Highway names are sometimes written as PA-150 and sometimes as PA150, etc.
Response 5: We thank you for your observation. The corresponding adjustments have been made.
Point 6: The red color in Figure 2 (urban areas) is very hardly visible. It is almost impossible to appreciate the increasing presence of this color through the years. Can we have a close-up on the area of town Goianesia do Para'?
Response 6: We understood your point of view. To increase the visualization, we decided to reduce the width of the line that represents the highway. We consider that change to have improved the visualization of the urban areas. We would prefer not to include a zoom to avoid visually polluting the map.
Point 7: Lines 272-275: this paragraph is not so clear, probably it needs more words to explain.
Response 7: We agree with your point of view. To address it, we have made the corresponding adjustments that can be find in lines 285-286.
Point 8: Line 285 has a typo: .... fragmentation HAS ....
Response 8: We appreciate your observation. The corresponding adjustment was made, and can be find in line 297.
Finally, we wish to thank you for all the pertinent observations made, which allowed us to improve our work. We hope to have responded in the best possible way to all your suggestions.
Reviewer 2 Report
The paper analyzes the space-time dynamics of land use in an area where installation of hydroelectric plants in the Amazon means land cover changes, forest loss, degradation, and fragmentation, having the interpretation key of the classes based on the spectral behavior of the objects. There were used Landsat images.
The introduction could be improved by including elements from the international state of the art, especially regarding satellite images processing workflow for detecting land cover changes. There would be better to be mentioned at least Copernicus CORINE Land Cover services.
The paper presents a well done analysis, emphasizing the dynamics of the landscape using known methods.
The results are discussed in a clear way, explaining the impact of the execution of industrial projects and the expansion of deforested areas, but there are also emphasized some implicit conclusions, well-known before, as "a spatial relationship between deforestation and roads".
Author Response
Response to Reviewer 2 Comments
The paper analyzes the space-time dynamics of land use in an area where installation of hydroelectric plants in the Amazon means land cover changes, forest loss, degradation, and fragmentation, having the interpretation key of the classes based on the spectral behavior of the objects. There were used Landsat images.
The introduction could be improved by including elements from the international state of the art, especially regarding satellite images processing workflow for detecting land cover changes. There would be better to be mentioned at least Copernicus CORINE Land Cover services.
The paper presents a well done analysis, emphasizing the dynamics of the landscape using known methods. The results are discussed in a clear way, explaining the impact of the execution of industrial projects and the expansion of deforested areas, but there are also emphasized some implicit conclusions, well-known before, as "a spatial relationship between deforestation and roads". The technical description shall be improved.
Response: We appreciate the time you took to thoroughly review our work. To disclose in greater detail the processing and general context, we have made some additions in the methodology. You can see the track changes in red through the text.
In addition, we only used Landsat satellite program, thus we would rather not include other products/satellite programs to avoid confusion.
Finally, we wish to thank you for all the pertinent observations made, which allowed us to improve our work with the expansion of the methodology. We hope to have responded in the best possible way to all your suggestions.
Reviewer 3 Report
This paper made an effort to analyze the spatio-temporal patterns of landscape change (mainly deforestation) in the municipality of Goianésia do Pará, one of the seven municipalities affected by the artificial lake of the Tucuruí hydroelectric plant.
Authors combined TM-Landsat 5, ETM+-Landsat 7, and OLI-Landsat 8 satellite images with landscape metrics to identify, quantify, and spatialize the loss of tropical forest. The subject is really interested, mainly for the analyzed study area. Unfortunately, important aspects of the analysis are poorly explained or not explained at all. In particular, the weakness of this paper are the method that is not detailed at all. It is not clear what authors do and how they do it.
First of all in which way the different Landsat data are pre-processed and prepared to be compared? Only some bands are listed and mentioned. How do authors use them? Which algorithm is applied? Any spectral indices? Combination of bands? Then, where do authors detailed raster to vector transformation? Moreover, at line 140 authors declare that “The interpretation key of the classes was based on the spectral behavior of the objects”. Please, explain in detail these concepts. In particular, how do you identify differently “flooded area” and “water” classes? Please, reconsider deeply method section.
Author Response
Response to Reviewer 3 Comments
This paper made an effort to analyze the spatio-temporal patterns of landscape change (mainly deforestation) in the municipality of Goianésia do Pará, one of the seven municipalities affected by the artificial lake of the Tucuruí hydroelectric plant. Authors combined TM-Landsat 5, ETM+-Landsat 7, and OLILandsat 8 satellite images with landscape metrics to identify, quantify, and spatialize the loss of tropical forest. The subject is really interested, mainly for the analyzed study area. Unfortunately, important aspects of the analysis are poorly explained or not explained at all. In particular, the weakness of this paper are the method that is not detailed at all. It is not clear what authors do and how they do it.
Response: We appreciate the time you took to thoroughly review our work. We will respond to each of your comments below.
Point 1: First of all in which way the different Landsat data are preprocessed and prepared to be compared? Only some bands are listed and mentioned. How do authors use them? Which algorithm is applied? Any spectral indices? Combination of bands?
Response 1: We understand your concern. As a result, we decided to modify the methodology, and added the much-needed context you are looking for. You can find the tracked changes in the text in red.
Point 2: Then, where do authors detailed raster to vector transformation?
Response 2: We appreciate your observation. However, in our article we do not realize any raster to vector transformation. The segmentation algorithm we used generates as a result a vector. The resulting vectorial data was a group of polygons that represent the edges of the different classes identified in the linear spectral mixture model (LSMM). Using this data, a supervised polygon-by-polygon classification was carried out (using the TerraAmazon program), which consisted of observing each polygon and classifying it according to the type of class that it discriminated against.
Point 3: Moreover, at line 140 authors declare that “The interpretation key of the classes was based on the spectral behavior of the objects”. Please, explain in detail these concepts. In particular, how do you identify differently “flooded area” and “water” classes? Please, reconsider deeply method section.
Response 3: We understand your observation. As we mentioned in our response 2, we realized a polygon-by-polygon supervised classification. All the polygons that discriminated bodies of water were classified as “water” class, except for the segments/polygons that were inside the dam. These polygons were classified as “flooded area” because they represent the reservoir. To address this in the paper, we have added more of this information in the methodology.
Finally, we wish to thank you for all the pertinent observations made, which allowed us to improve our work with the expansion of the methodology. We hope to have responded in the best possible way to all your suggestions.
Round 2
Reviewer 3 Report
Dear authors, thank you for your effort to modify this paper. It is improved but there is still something unclear. Please, modify lines 125-128: there are repetition (i.e. red band). Some suggestions (if they are correct):
- “On the TerraAmazon software, different color compositions including Red (R), Green(G), Blue (B), near infrared (NIR), and the shortwave infrared (SWIR-1) bands, were adopted in order to assist with the identification of the features in the classification process;
- Red (R), Green(G), Blue (B), near infrared (NIR), and the shortwave infrared (SWIR-1) bands were combined in TerraAmazon software in order to assist with the identification of the features in the classification process.
Author Response
Response to Reviewer Comments
Dear authors, thank you for your effort to modify this paper. It is improved but there is still something unclear. Please, modify lines 125-128: there are repetition (i.e. red band). Some suggestions (if they are correct):
- “On the TerraAmazon software, different color compositions including Red (R), Green(G), Blue (B), near infrared (NIR), and the shortwave infrared (SWIR-1) bands, were adopted in order to assist with the identification of the features in the classification process;
- Red (R), Green(G), Blue (B), near infrared (NIR), and the shortwave infrared (SWIR-1) bands were combined in TerraAmazon software in order to assist with the identification of the features in the classification process.
Response: We appreciate the time you took to review our work. We realized that we were not clear enough in that paragraph. As a result, the respective adjustments have been made in the corresponding lines. We hope to have addressed your suggestion in the best possible way.
