Towards a Core Set of Landscape Metrics of Urban Land Use in Wuhan, China
Round 1
Reviewer 1 Report
The manuscript entitled "Towards A Core Set of Landscape Metrics and Its Applications for Urban Land Use of Wuhan, China" is dealing with the effectiveness of landscape metrics in assesing the spatial composition and configuration of the urban landscape of Wuhan (China). The authors have selected a core of six indices out of a total of 45 through factor analysis. And they have concluded that this core of 6 indexes is enough to measure the variation of the Wuhan urban landscape in all its complexity.
The statistical analysis to select the six indices seems to be correctly carried out, however there are already some previous papers that deal with the issue of the redundancy of many of the existing landscape metrics and that reach similar conclusions (for example the work of Ritters et al, 1995 which the authors also cite). In this sense the work is not very original.
Some aspects to improve:
- Linguistic improvement: The English is not always correct. Some sentences are ambiguous and need to be rephrased.
-Content improvement: A table indicating the full name of the landscape metrics cited in the text by means of acronyms is absolutely necessary. Even readers familiar with landscape metrics find it difficult to understand which index each acronym refers to.
I find that a Discussion section is missing. The investigation is mainly based on statistical analysis and then on descriptive explanations about the results obtained from the spatial patterns indicated by the core metrics and their spatial distribution. In the discussion the authors have to consider their findings more in global context. They could be able to answer and discuss why their findings are important and which gap they will fill in the scientific context. Compare their findings with other regions and discuss similarities and differences.
Author Response
The statistical analysis to select the six indices seems to be correctly carried out, however there are already some previous papers that deal with the issue of the redundancy of many of the existing landscape metrics and that reach similar conclusions (for example the work of Ritters et al, 1995 which the authors also cite). In this sense the work is not very original.
Response: Thank you for your recommendation. We have revised the paper in response to your comments.
Some aspects to improve:
- Linguistic improvement: The English is not always correct. Some sentences are ambiguous and need to be rephrased.
Response: Thank you for your feedback, which led us to re-read the manuscript to identify and refine potentially confusing language.
-Content improvement: A table indicating the full name of the landscape metrics cited in the text by means of acronyms is absolutely necessary. Even readers familiar with landscape metrics find it difficult to understand which index each acronym refers to.
Response: Thank you for your feedback. An acronym table is also added to the appendix, listing all metrics included in this study (Table A1). Also, we add the full name of metrics after the first appearance. Below is a list of acronyms used ordered by first appearance in the text.
- SHAPE (shape index)
- FRAC (fractal dimension)
- LSI (landscape shape index)
- PROX (proximity index)
- SIMI (similarity index)
- TA (total area)
- TE (total edge length)
- NP (number of patches)
- LPI (largest patch index)
- AREA_AM (area-weighted mean patch size)
- ED (edge density)
- AREA_MN (mean cell size)
- PD (patch density)
- PROX_MN (mean proximity index)
- PROX_AM (area-weighted mean proximity index)
- PR (patch richness)
- PRD (patch richness density)
- RPR (relative patch richness)
- SHDI (Shannon’s diversity index)
- SIDI (Simpson’s diversity index)
- MSIDI (modified Simpson’s diversity index)
- SHEI (Shannon’s evenness index)
- SIEI (Simpson’s evenness index)
- MSIEI (modified Simpson’s evenness index)
- AREA_CV (coefficient of variation of cell size)
- IJI (interspersion and juxtaposition index)
- ENN_MN (mean Euclidean nearest-neighbor distance)
- ENN_AM (area-weighted mean Euclidean nearest-neighbor distance)
- ENN_CV (coefficient of variation of Euclidean nearest-neighbor distance)
- PROX_CV (coefficient of variation of proximity index)
- SIMI_MN (mean similarity index)
- SIMI_AM (area-weighted mean similarity index)
- SIMI_CV (coefficient of variation of similarity index)
- PARA_CV (coefficient of variance of perimeter-area ratio)
- SHAPE_MN (mean shape index)
- FRAC_MN (mean fractal dimension)
- FRAC_AM (area-weighted mean fractal dimension)
- CIRCLE_CV (coefficient of variation of related circumscribing circle)
- CWED (contrast-weighted edge density)
- TECI (total edge contrast index)
- ECON_MN (mean edge contrast index)
- ECON_AM (area-weighted mean edge contrast index)
- ECON_CV (coefficient of variance of edge contrast index)
I find that a Discussion section is missing. The investigation is mainly based on statistical analysis and then on descriptive explanations about the results obtained from the spatial patterns indicated by the core metrics and their spatial distribution. In the discussion the authors have to consider their findings more in global context. They could be able to answer and discuss why their findings are important and which gap they will fill in the scientific context. Compare their findings with other regions and discuss similarities and differences.
Response: Thank you for your suggestion. There are few studies that could be suitable for comparison with this study due to our concern in urban scenario and vector data format. Despite this, we manage to compare our findings with those by Schindler et al. (2008) for both studies are at the scale of 500 hectares.
Our depiction of urban landscape needs six core indicators, which is more than four as in the compared study on natural habitats. Both studies find that diversity and shape groups are important source of core indicators, although the relative importance of indicators differs across urban and natural scenarios. Specifically, in our findings, shape complexity (FRAC_AM), variation of patch sizes (AREA_CV), and isolation (PROX_AM) are more useful in characterizing urban landscapes than in natural ones. Also interestingly, the variation of fragmentation (ECON_CV) appears more important in urban landscapes while the fragmentation itself (ECON_MN) better captures natural landscapes in the compared study.
In this view, our findings provide evidence for the difference between landscape description based on vector and raster formats.
Reviewer 2 Report
Analyses of landscape structure with statistical methods can help to get a better understanding of landscape composition, configuration as well as other aspects, e.g. such as connectivity.
Title should be corrected:
"Towards a core set of landscape metrics and their applications for urban land use in Wuhan, China".
The manuscript tries to make use of several methodological approaches and selection procedures to reduce redundancy and find a good combination of informative metrics of landscape structure. It is also an application of a special ArcGIS tool for the calculation of landscape metrics based on vector data (Arc_LIND).
However, for the reader, it is difficult to clearly recognize what is special with this tool and the results of the calculations. There is only one sentence with a reference referring to this tool. Without carefully reading, an inexperienced but interested reader will have difficulties to find out, that the particular emphasis of the vector-based approach is related to the above-mentioned tool but not to the selection of informative indices with rather multivariate statistical methods and comparisons of correlations. This is misleading. The authors need to explain this in a better way, perhaps in more than only one sentence.
The introduction is difficult to read. I know that the concept of the Chinese language is very different from English and that it can be challenging to find a good translation. However, the simple stringing together of bulleted lists with long explanations in running text is very difficult to read and to understand. It is rather a matter of style than of grammar. The introduction as well as many other parts would definitely benefit from a better structure (separated paragraphs in the bullet list) and stylistic overhaul.
The arrows in figure 1 are misleading. I assume that they should point to the three different districts Hankou, Wuchang, Hanyang. If this was the aim, the authors should either use a simple line without an arrow head turn the direction and let the arrow heads pointing on the city districts of the town instead of pointing on the labels.
Line 237, The Effective Mesh Size is a special landscape metric useful for the estimation of landscape fragmentation or, better, dissection but not contagion or dispersion.
Table 2 should go to the appendix, and only selected metrics with higher correlation should be compiled in a table or (if only a few) written in the text.
Figure 3: The legend bar and the arrow should be turned upside down, that the highest values are on the top and the lowest on the bottom.
I would recommend using a colour palette instead of b/w.
The authors conclude, that the selected core landscape metrics could be used as effective indicators for land use planning and decision-making processes in the development of resource-based cities and ecological cities. However, I doubt in this. Landscape metrics are useful to extract special information from the raw data based on a grid, hexagons (like in this case) or different kind of regions to relate them with other information based on the same spatial units, e.g. biodiversity, single species occurrences or to monitor landscape changes. I think the authors should find a better justification or, much better, give still an example for either the monitoring of changes (comparing two time periods) or the correlation with other processes observed on the same spatial units.
Author Response
Title should be corrected:
"Towards a core set of landscape metrics and their applications for urban land use in Wuhan, China".
Response: Thank you for your suggestion. The title is now corrected.
The manuscript tries to make use of several methodological approaches and selection procedures to reduce redundancy and find a good combination of informative metrics of landscape structure. It is also an application of a special ArcGIS tool for the calculation of landscape metrics based on vector data (Arc_LIND).
However, for the reader, it is difficult to clearly recognize what is special with this tool and the results of the calculations. There is only one sentence with a reference referring to this tool. Without carefully reading, an inexperienced but interested reader will have difficulties to find out, that the particular emphasis of the vector-based approach is related to the above-mentioned tool but not to the selection of informative indices with rather multivariate statistical methods and comparisons of correlations. This is misleading. The authors need to explain this in a better way, perhaps in more than only one sentence.
Response: Thank you for your feedback, which leads to our rework of the confusing parts in the second paragraph of the Method section.
“Given the difference in landscape metrics between the raster format and vector format data presented above, necessary adjustments in metric calculation must be made for the vector data used in this study. A plug-in [22] for ArcMap 10.1 has been developed to implement the adjustments for vector data. Therefore, we used it to calculate landscape metrics for our data in the vector format as the basis of the subsequent exploratory analysis.”
The introduction is difficult to read. I know that the concept of the Chinese language is very different from English and that it can be challenging to find a good translation. However, the simple stringing together of bulleted lists with long explanations in running text is very difficult to read and to understand. It is rather a matter of style than of grammar. The introduction as well as many other parts would definitely benefit from a better structure (separated paragraphs in the bullet list) and stylistic overhaul.
Response: Thank you for your suggestion. We reorganize the Introduction section to present it in a more coherent structure and style, and also fix the stylistic problem of listing bullet points by explaining the related methods in a logically natural order.
The arrows in figure 1 are misleading. I assume that they should point to the three different districts Hankou, Wuchang, Hanyang. If this was the aim, the authors should either use a simple line without an arrow head turn the direction and let the arrow heads pointing on the city districts of the town instead of pointing on the labels.
Response: Thank you for your suggestion. We remove the arrow head and indicate the names of districts with a simple line.
Line 237, The Effective Mesh Size is a special landscape metric useful for the estimation of landscape fragmentation or, better, dissection but not contagion or dispersion.
Response: Thank you for your correction. We revise the description of what excluded metrics measure to match our examples as follows.
“Eight such metrics, including the metrics that describe fragmentation and subdivision, such as the Division Index, Splitting Index, and Effective Mesh Size were not considered in this study.”
Table 2 should go to the appendix, and only selected metrics with higher correlation should be compiled in a table or (if only a few) written in the text.
Response: Thank you for your suggestion. We move the correlation table (previously Table 2) to the appendix (now Table A2). The only highly correlated pair of selected metrics is AREA_MN and LSI, which has already been written in the text.
Figure 3: The legend bar and the arrow should be turned upside down, that the highest values are on the top and the lowest on the bottom.
I would recommend using a colour palette instead of b/w.
Response: Thank you for your suggestion. We render the hexagons with a colored palette and turn the legend upside down.
The authors conclude, that the selected core landscape metrics could be used as effective indicators for land use planning and decision-making processes in the development of resource-based cities and ecological cities. However, I doubt in this. Landscape metrics are useful to extract special information from the raw data based on a grid, hexagons (like in this case) or different kind of regions to relate them with other information based on the same spatial units, e.g. biodiversity, single species occurrences or to monitor landscape changes. I think the authors should find a better justification or, much better, give still an example for either the monitoring of changes (comparing two time periods) or the correlation with other processes observed on the same spatial units.
Response: Thank you for your suggestions. We agree that previous claim about the potential application of core metrics in urban planning was not justified. In this revision, we discuss how our findings are different from (and similar to) ecological studies using raster data. The conclusion is rephrased to focus on our findings supported by vector data of urban land use.
Reviewer 3 Report
The manuscript reports a method for landscape metrics analysis applied to the case study of urban land use in Wuhan, China.
The main concepts of the paper and the terminology used are well presented and introduced. The objectives for work are laid out clearly and convincingly in the introduction.
The adopted approaches and methodologies (a combination of Spearman correlation analysis and factor analysis) are detailed, and sound, and the supporting visual material is useful to better understand the exposed concepts. The analysis of results is appropriate in content, length, and helpful in terms of overall insight, thus the reviewer suggests accepting the manuscript in the present form.
Author Response
Response: Thank you for your recommendation. We revise our manuscript in response to peer reviews.
Reviewer 4 Report
Dear Editor,
the manuscript presents an interesting and complex methodology to simplify spatial analyzes on the landscape. The procedure is documented and the results are enormously reflected in the metric analyzes. The text is well written with minor typos.
My only comments are:
- the abstract presents a first part which corresponds to an introduction. An abstract should be a short summary of the research paper and allow readers to quickly get to the gist or essence of the paper; it should prepare readers to follow the detailed information, analyzes, and arguments in the text. I suggest deleting the first part and rewriting the abstract.
- Paragraph 2 "Material" contains a description of the study area and introduces part of the methodology. These latter aspects, highlighted in the attached file, must be moved to the "Methods" section.
I think that the paper can be published after these minor changes.
Kind regards
Comments for author File: 
Comments.pdf
Author Response
The manuscript presents an interesting and complex methodology to simplify spatial analyzes on the landscape. The procedure is documented and the results are enormously reflected in the metric analyzes. The text is well written with minor typos.
I think that the paper can be published after these minor changes.
Response: Thank you for your recommendation.
My only comments are:
- the abstract presents a first part which corresponds to an introduction. An abstract should be a short summary of the research paper and allow readers to quickly get to the gist or essence of the paper; it should prepare readers to follow the detailed information, analyzes, and arguments in the text. I suggest deleting the first part and rewriting the abstract.
Response: Thank you for your advice. The abstract is rewritten to reflect what was done and found in this study and to facilitate quick understanding of the gist as follows.
“In this study, we investigate the urban landscape patterns in Wuhan, China based on the land use data in the vector format. Using the approach of landscape metric analysis, we calculate forty-four vector-based landscape metrics and then reduce redundant ones through a combination of Spearman correlation analysis and factor analysis, in order to extract a core set of characterizing landscape metrics. We find that the urban landscape can be depicted by six factors including the overall shape and diversity, mean proximity, overall area variation, fragmentation variation, elongation variation, and mean shape complexity. After analyzing typical patterns indicated by the core metrics and the spatial distribution of land use patterns, we compare our findings with other study and discuss how the factors coincide and differ.”
- Paragraph 2 "Material" contains a description of the study area and introduces part of the methodology. These latter aspects, highlighted in the attached file, must be moved to the "Methods" section.
Response: Thank you for your suggestion. We have moved the latter part into the Method section.
