A Partitioned and Heterogeneous Land-Use Simulation Model by Integrating CA and Markov Model
Round 1
Reviewer 1 Report
The structure of the document is good, however I find things that can be improved.
The introduction and discussion of the results should be expanded by adding citations.
The same applies to the conclusions. If possible, they should be supported by other studies, either in favor or against.
In section 2.3.2 weights are mentioned, however, these weights do not appear in the text.
With a little effort in literature search to support the study, this work can be published.
Author Response
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Author Response File: 
Author Response.docx
Reviewer 2 Report
Review of manuscript "A partitioned and heterogeneous land-use simulation model by integrating CA and Markov model" (land-2179851)
Dear authors, your research tries to simulate and predict the future urban land use changes in the Pearl River Delta region, China by using a partitioned and heterogeneous land-use simulation model (PHLUS) based on the Markov-CA model. It is a well-designed manuscript and fits the aims and scope of the journal topic, but some revisions need to be done before further consideration. Specifically, the reviewer has the following comments and suggestions:
(1) Please explain why the Markov-CA model was selected in this study as there are many different types of more novel CA models.
(2) The literature review paragraph: in this part, the authors need to look further into the latest research about land use and land cover simulation models. In particular, a number of recent studies have not been systematically reviewed.
(3) Section 2.1. Study Area: in this part, the description of the background of the study area is too lengthy. I suggest that this subsection can be shortened.
(4) The Data Centre for Resources and Environmental Sciences, Chinese Academy of Sciences, has contributed the land-use data, which is based on Landsat TM images with a spatial resolution of 1000 m. What are the classification accuracies for these land use and land cover data?
(5) Please explain why the PRD region's land-use statistics for the years 2000, 2010, and 2020 were used for modeling and forecasting. In other words, why these years were used?
(6) Distance to highways, distance to national roads, distance to provincial roads, distance to railways, distance to tourist attractions, distance to restaurants, distance to supermarkets, distance to transport stations, and distance to rivers were used as influencing factors (Figure 2). Please provide adequate references to support the selection of these spatial influencing factors.
(7) Table 3 has not been mentioned in the main text. Therefore, please explain how to classify the land-use potential evaluation indexes. In other words, how to determine the interval of these factors?
(8) How to determine the number of the partition in this study area?
(9) Figure 5: in this figure, the differences between different results are not obvious. Therefore, I suggest to enlarge some parts of the results.
(10) Figure 6. Land-use prediction of Pearl River Delta in 2030 based on PHLUS: this result looks a bit weird, please double check the prediction result.
Author Response
Please see the attachment.
Author Response File: Author Response.docx
Reviewer 3 Report
The article shows a high level of applicability in decision-making process regarding land use conversion for any country in the world.
My observations are:
1. Between lines 142 and 145, there is an explanation regarding how land use is classified in 5 categories. One of the categories is BUILD-UP LAND (line 142). However, other names are used through the paper that I suppose represent subcategories of that main category, although it is not mentioned in the paper. The same situation is seen in category CULTIVATED LAND. In table 3 (line 242), categories such as GARDEN LAND, ARABLE LAND, OTHER AGRICULTURAL LAND are written for the LAND CLASS COMPOSITION. Again, I suppose these represent subcategories for Cultivated Land, but it is not said in any part of the document. I recommend that this issue should be clarified at the beginning of the document.
2. In line 152, the words "POI data" appears in the document. Does POI acronym stand for "Point of Interests"? This should be clarified in the document.
3. In equation 8, between lines 253 and 254, one of the elements of the matrix is rnm. However, between lines 256 and 259, the explanation of each part of the matrix shows rij. This should be clarified or corrected because it could generate misleading interpretations to the reader.
4. In Line 257, a space should be introduced between "R" and "is."
5. In Line 319, I think there is a "Z" that is not necessary to be there regarding the explanation of equation 13 (line 317); unless it should be written as F(Z). This should be corrected or clarified.
6. Finally, the following is only a commentary: I do not clearly see how country or region policies for land-use conversion is included as a driving force in the prediction. Could it be included? Is it implicit in the analysis? I think this should be comment in the conclusions or in the introduction.
Author Response
Please see the attachment.
Author Response File: Author Response.docx
Round 2
Reviewer 1 Report
The document has been substantially improved
On my side it is ready for publication.
Reviewer 2 Report
I appreciate the authors' efforts to improve this manuscript. Now it is acceptable for publication.
