A Comprehensive Review on Land Use/Land Cover (LULC) Change Modeling for Urban Development: Current Status and Future Prospects
Round 1
Reviewer 1 Report
ENGLISH:
- quite good, but there are many errors here and there,
needs revisions.
KEYWORDS:
- in alphabetical order, please. Plus,
"SDG-15" is an acronym, remove "SDG-15" or put the
complete word here
MAIN TEXT:
- rows 61-64: NOT in bold
- Tables 1, 2 and 3 are informationally very inadequate.
Softwares must be described much more in depth, adding
the following information for each software:
Name
Developers
First public release
Latest stable version
Operating system (Windows, Mac OS, Linux, Ubuntu etc.)
Language (Java, C, VBA, Matlab etc.)
Methods (cellular automata, logistic reressions etc.)
Cost (free, commercial, limited etc.)
License (GPL, proprietary etc.)
- Figure 2 is hardly representative of agent-based models.
Readers who do not know agent-based models could hardly understand this schematic representation. Please, replac this image with a figure showing agents, interactions between agents, background, interaction between agents and background
- Paragraph 2.3. Available modeling software packages for LULC predictions. There are many softwares for LULC modeling and predictions that are not described here, but they should because they're frequently used:
Netlogo
Starlogo
LanduseSim
FUTURES library for GRASS GIS
MOLUSCE plugin for QGIS
LULCC library for R
SIMECOL library for R
SIMLANDER library for R
Author Response
Response to the reviewer’s comments:
The text representing the responses to the comment of Reviewer 1 is highlighted with yellow, colour in the revised version of the manuscript. The responses to the common comments of Reviewers 1 and 3 are highlighted in grey.
Reviewer 1:
- KEYWORDS:
- in alphabetical order, please. Plus,
"SDG-15" is an acronym, remove "SDG-15" or put the
complete word here
Response: We would like to thank Reviewer-1 for the constructive suggestion. As per the suggestion of the reviewer, the required correction has been performed in the revised version of the manuscript (Page: 1 Lines: 20-21, Page: 1 Line:20).
- MAIN TEXT:
- rows 61-64: NOT in bold
Response: We would like to thank Reviewer-1 for pointing this out. As per the reviewer’s suggestion the required correction has been performed in the revised version of the manuscript.
- Tables 1, 2 and 3 are informationally very inadequate.
Softwares must be described much more in depth, adding
the following information for each software:
Name
Developers
First public release
Latest stable version
Operating system (Windows, Mac OS, Linux, Ubuntu etc.)
Language (Java, C, VBA, Matlab etc.)
Methods (cellular automata, logistic reressions etc.)
Cost (free, commercial, limited etc.)
License (GPL, proprietary etc.)
Response: We would like to thank the reviewer for the construction comment and thoughtful suggestion. Tables 1-3 provide the details about the models, not the software. However, we have added the suggested details in the software under section 2.3 (Pages: 7-8 Lines: 261-268, Page: 8 Lines: 278-283, Page: 9 Lines: 295-299, Page: 9 Lines: 312-315, Page: 9 Line: 325). For some software, few details are not available e.g. License (GPL, proprietary, etc.). We hope that the reviewer understands our concern and excuses us.
- Figure 2 is hardly representative of agent-based models.
Readers who do not know agent-based models could hardly understand this schematic representation. Please, replace this image with a figure showing agents, interactions between agents, background, interaction between agents and background
Response: We would like to thank the reviewer for the constructive suggestion. The required correction has been performed in Figure 2.
- Paragraph 2.3. Available modeling software packages for LULC predictions. There are many softwares for LULC modeling and predictions that are not described here, but they should because they're frequently used:
Netlogo
Starlogo
LanduseSim
FUTURES library for GRASS GIS
MOLUSCE plugin for QGIS
LULCC library for R
SIMECOL library for R
SIMLANDER library for R
Response: We would like to thank the reviewer for the constructive suggestion. As per the suggestion of the reviewer, the required correction has been performed in the revised version of the manuscript (Pages: 9-10, Lines: 328-342).
Reviewer 2 Report
The manuscript is written by 2 authors in 11 pages, has 38 references, 4 tables, 2 figures. The review further highlights the utility of the hybridization of different techniques (e.g., machine learning model combined with statistical models) to LULC modeling to complement their strengths. Authors considered the features and limitations of individual software packages.
Comments: in authors metadata add address, zip code.
Lines 102-104: I suggest adding classes of models. stochastic model ? regression? adaptive (with examples).
Check spelling. Table X presentS.
Table 2 and 3 should be moved up (near the mentioned place in the text).
2.1.5. Agent-based models - add abbreviation (ABM).
Line 158 two commas.
Please, enlarge the explanation of the differences between agents and driving factors.
2.3.2 and 2.3.4 software programs are not mentioned in the tables. Why?
References^
[2] add Pages 1997-2010
[5] Ren, Y.; Lü, Y.; Comber, A. et al. Please, use full link.
Check points, commas and text color.
[19] year in the end
[22] add doi https://doi.org/10.3390/rs12071135
[33] delete ISNN, add doi https://doi.org/10.1016/j.scico.2018.02.002
everywhere use MDPI reference style "doi:"
Author Response
Response to the reviewer’s comments:
The text representing the responses to the comment of Reviewer 2 is highlighted with blue colour in the revised version of the manuscript.
Reviewer 2:
The manuscript is written by 2 authors in 11 pages, has 38 references, 4 tables, 2 figures. The review further highlights the utility of the hybridization of different techniques (e.g., machine learning model combined with statistical models) to LULC modeling to complement their strengths. Authors considered the features and limitations of individual software packages.
- Comments: in authors metadata add address, zip code.
Response: We would like to thank the reviewer for the constructive suggestion. The required correction has been incorporated in the revised version of the manuscript (Page: 1 Line: 6).
- Lines 102-104: I suggest adding classes of models. stochastic model? regression? adaptive (with examples).
Response: We would like to thank the reviewer for pointing this out. The required correction has been performed in the revised version of the manuscript (Page: 4 Lines: 125-127).
- Check spelling. Table X presentS.
Response: We would like to thank the reviewer for pointing out our mistakes and we apologize for the same. The required correction has been performed in the revised version of the manuscript (Page: 4, Line: 134; Page: 4, Line: 150; Page: 5 Line: 163).
- Table 2 and 3 should be moved up (near the mentioned place in the text).
Response: We would like to thank the reviewer for the constructive suggestion. As per the suggestion of the reviewer, the required correction has been performed in the revised version of the manuscript.
- 2.1.5. Agent-based models - add abbreviation (ABM).
Response: We would like to thank the reviewer for pointing this out. The required correction has been performed in the revised version of the manuscript (Page: 13, Line: 169).
- Line 158 two commas.
Response: We would like to thank the reviewer for pointing this out. The required correction has been performed in the revised version of the manuscript
- Please, enlarge the explanation of the differences between agents and driving factors.
Response: We would like to thank the reviewer for the thoughtful comment and constructive suggestion. As per the suggestion of the reviewer, the required explanation has been added in the revised version of the manuscript (Page: 5 Lines: 178-183).
- 2.3.2 and 2.3.4 software programs are not mentioned in the tables. Why?
Response: We would like to thank the reviewer for asking about it. For software other than CLUE, detailed sub-versions are not available. Other software has only updated versions. We hope that the reviewer would understand our concern and excuses us.
- References^
[2] add Pages 1997-2010
[5] Ren, Y.; Lü, Y.; Comber, A. et al. Please, use full link.
Check points, commas and text color.
[19] year in the end
[22] add doi https://doi.org/10.3390/rs12071135
[33] delete ISNN, add doi https://doi.org/10.1016/j.scico.2018.02.002
everywhere use MDPI reference style "doi:"
Response: We would like to thank the reviewer for pointing this out. The required correction has been performed in the revised version of the manuscript.
Reviewer 3 Report
A comprehensive review on Land use/land cover (LULC) change modeling for urban development: Current status and future prospects
The effort of reviewing status and prospects of LULC for urban development is interesting and would bring a significant contribution in this field.
Besides that, manuscript needs serious improvement.
Based on scheme from figure 1, it is a good idea to add review of possible explanatory variables.
Also, “Performance metrics” should be reviewed too.
It is a good idea to add a part about time-series modelling of LULC
Most commonly used software for LULC modelling is missing. Pay attention to “MOLUSCE” and “SCP” for QGIS, ‘lulcc’ package for R, Python probably also has some LULC packages.
I wish that my comment would be helpful in improving the quality of this research.
Thank you.
Author Response
Response to the reviewer’s comments:
The text representing the responses to the comment of Reviewer 3 is highlighted with green colors in the revised version of the manuscript. The responses to the common comments of Reviewers 1 and 3 are highlighted in grey.
Reviewer 3:
- Based on the scheme from figure 1, it is a good idea to add review of possible explanatory variables.
Response: We would like to thank the reviewer for the constructive suggestion. The suggestion has been incorporated in the revised version of the manuscript (Page: 3 Lines: 98-113).
- Also, “Performance metrics” should be reviewed too.
Response: We would like to thank the reviewer for the constructive suggestion. The suggestion has been incorporated in the revised version of the manuscript (Pages: 3-4 Lines: 114-120).
- It is a good idea to add a part about the time-series modeling of LULC
Response: We would like to thank the reviewer for the constructive comment and thoughtful suggestion. The suggestion has been performed in the revised version of the manuscript (Page: 13 Lines: 198-215).
- Most commonly used software for LULC modelling is missing. Pay attention to “MOLUSCE” and “SCP” for QGIS, ‘lulcc’ package for R, Python probably also has some LULC packages.
Response: We would like to thank the reviewer for the thoughtful suggestion. The suggestion has been performed in the revised version of the manuscript (Pages: 9-10 Lines: 328-342).
Round 2
Reviewer 1 Report
thank you for replying to my remarks
Reviewer 3 Report
The manuscript has significantly improved from the last revision and can be published in present form
