Spatiotemporal Dynamics and Driving Forces of Urban Land-Use Expansion: A Case Study of the Yangtze River Economic Belt, China
Round 1
Reviewer 1 Report
The paper I have reviewed provide important insights to how remote sensing products night time light can be used to evaluate urban development by measure both magnitude and expansion. The paper are using one megaregion in China. Growth pattern changes are based on Gravity Center and weighted Standard Deviation Ellipses and of the megaregions’ spillover effect on surrounding areas. The result indicate that the initial face gave development both in terms of magnitude for the Yangtze River Delta (YRD).
The research objective are sound and can be developed into two aims: 1. to provide development of methods by using Remote Sensing data and 2. To actually study and map the change in the megaregion. The authors are relating the topic to the problems of defining urban areas because the definition is based on administrative borders or decisions and not to the dynamic change in terms of a process of urbanization. The method developed in the paper to measure urban magnitude and expansion is a major strength that can be applicable to other geographical areas with fasting growing urban areas. The megaregion is chosen in reference to the importance to the Chinese development.
The methods and data section is well developed however there is no reference to using the conventional methods for calibration of the DMSP-OLS nighttime data. Has that been done? In case no why? And could it be performed?
Results are reported in a mix of maps, graphs and tables and often in a combination of the three. All illustrations are made with high cartographic quality and provide important insights to the study. Figure 6 is the key figure for the study reporting and illustrating the spillover effects from innercity development to the surrounding regions.
I have a few minor comments for the authors to address in order to strengthen the manuscript:
Comment 1
The abstract is rather long and I wonder if the abstract could be condensed and more focused.
Comment 2
Why is there no reference to calibration of the DMSP-OLS data. There are several methods available for example see: Hall, O., Bustos, M.F.A., Olén, N.B. et al. Population centroids of the world administrative units from nighttime lights 1992-2013. Sci Data 6, 235 (2019) doi:10.1038/s41597-019-0250-z
Overall the manuscript is of high relevance for social science research using remote sensing and is fit for publication in the present journal after the above comments have been addressed.
Author Response
Response to Reviewer 1 Comments
Dear reviewer:
Merry Christmas! I sincerely thank you for reviewing our manuscript 《Spatiotemporal Dynamics and Driving Forces of Urban Land Use Expansion: A Case Study of the Yangtze River Economic Belt, China》 (ID: remotesensing-679656). These comments are valuable for revising and improving our papers. They are also very helpful and have important guiding significance for our research. According to your suggestion, my tutor and I have try our best to revise this paper. We responded carefully and provide a point-by-point response to your comments. We also marked the changes in the manuscript in red and wrote a revision note. We hope that the revised manuscript will be accepted by you. Thank you very much for your work! We wish you all the best! All our authors sincerely wish you a Merry Christmas and a Happy New Year! We sincerely wish you and your family a wonderful, lucky and happy New Year!
The detailed description of the modification is as follows:
Point 1:
Comment 1
The abstract is rather long and I wonder if the abstract could be condensed and more focused.
Response 1:
Dear reviewer:
Thank you very much for your valuable suggestions. Your suggestion will be of great help to the improvement of this paper. Based on this, we have done our best to condense and summarize the "Abstract" part of the paper. Specifically, the number of words in the "Abstract" section has dropped from the original "484" to the current "343". We hope that our modifications can be accepted and approved by you. Thank you very much! Merry Christmas! We wish you all the best! We sincerely wish you and your family a wonderful, lucky and happy New Year!
Point 2:
Comment 2
Why is there no reference to calibration of the DMSP-OLS data. There are several methods available for example see。
Response 2:
Dear reviewer:
Thank you very much for your valuable modification suggestions. We believe that your suggestions will bring great help to the improvement of this paper.
In this paper, we have used conventional methods to calibrate DMSP-OLS nighttime data, which is the most basic first step to extract the urban area of a town based on night light data. Considering that there are many research methods and results in this paper, the focus of this paper is the presentation and explanation of the research results. Therefore, this paper does not introduce the calibration of DMSP-OLS nighttime data. Your suggestion is very correct. Therefore, based on your suggestions, we have added some new content to explain the calibration of DMSP-OLS nighttime data. In addition, we also carefully read the paper "Population centroids of the world administrative units from nighttime lights 1992-2013" that you suggested. This paper is very meaningful and they did a great job. Therefore, this paper is very worthy of our learning and reference in the follow-up research.We hope that our modifications can be accepted and approved by you. To be honest, we all think you are a very nice person, and we would like to express our sincere thanks again for your kindness! Thank you very much! Merry Christmas! We wish you all the best! We sincerely wish you and your family a wonderful, lucky and happy New Year!
Point 3: Extensive editing of English language and style required
Response 3:
Dear reviewer:
Thank you very much for your valuable modification suggestions. We believe your suggestion is very valuable and meaningful. Before our paper has been submitted, we have used the English editing service of MDPI to improve the English language problem of this paper, and we also have English-editing-certificate. The English editor certificate can be viewed in the attachment "English-editing-certificate-Yang Zhong". Therefore, after modification by the English editor, the English editor of MDPI believes that the English language of this paper is good.
Based on your Suggestions, you think the English language and style of this paper still need to be improved. Therefore, we have contacted an assistant professor to improve the English language and style of this paper. He works at the University of North Carolina at Chapel Hill. We hope that our modifications can be accepted and approved by you. Thank you very much! Merry Christmas! We wish you all the best! We sincerely wish you and your family a wonderful, lucky and happy New Year!
Author Response File: 
Author Response.pdf
Reviewer 2 Report
In this study, the authors used night-time lighting data and nine methods, including a comparison method based on auxiliary data, the landscape index method, a spatial expansion strength index, a compactness index, an urban land fractal index, the elasticity coefficient, and the standard deviation ellipse, to analyze the evolution of urban expansion in the YREB in China.
This study is really interesting and I think it could fit in the reader’s scope. After I reviewed that, I am including some few suggestions:
Please try to summarize the abstract. Right now, this is too large. An interesting point is related to the indicators used: “this study is based on DMSP-OLS night lighting data, using the landscape index, the spatial expansion force index, the compactness index, the index Urban land fractal, elasticity coefficient, ellipse deviation standard, spatial correlation analysis and partial least squares regression to analyze the spatial and temporal evolution of urban land expansion and its driving factors in the YREB over a long time frame ". In my opinion, I would suggest one additional indicator: the so-called street based metrics which allow to characterize urban typologies. These are computed by using technologies for collecting geodata such as LiDAR and remote sensing. I understand that you are not focusing on this indicator, but I strongly recommend that you at least include some reference to it. With great interest, I note that the authors used the center of gravity such an indicator. I strongly trust on this indicator, which provides very relevant information for studies related to space-time dynamics. I can recommend some very recent studies, which would have much interest for your current manuscript:
Balsa-Barreiro et al. (2019): "Globalization and the shifting centers of gravity of world's human dynamics: Implications for sustainability". Journal of cleaner Production.
Sauter, C. (2019): "A global compass for the great divergence: emissions vs. production centers of gravity 1820-2008". The World Economy
Kharas, H (2010): "The New Global Middle Class: A Cross-Over from West to East." Wolfensohn Center for Development at Brookings.
In these paper, the authors show the impact of the accumulation of wealth (in terms of GDP) and urban population in China and Southeastern Asia at a global scale. These ideas are very important at the beginning of the manuscript when the authors state “Urbanization is the only way for China to build a well-off society and achieve modernization. China's urbanization will not only determine China's future, but also the process of urbanization in the world [1]. Urban agglomeration is the main area of new national urbanization and a core strategic area of economic development, which plays an irreplaceable role in promoting urbanization in China [2]”. In addition, the methodology used could be compared to the used in this study, where the authors proposed a flat center of gravity (2D).
Author Response
Response to Reviewer 2 Comments
Dear reviewer:
Merry Christmas! I sincerely thank you for reviewing our manuscript “A Study on Urban Expansion and its Driving Forces in the Yangtze River Economic Belt, China, Based on Night Light Data” (ID: remotesensing-679656). These comments are valuable for revising and improving our papers. They are also very helpful and have important guiding significance for our research. According to your suggestion, my tutor and I have try our best to revise this paper. We responded carefully and provide a point-by-point response to your comments. We also marked the changes in the manuscript in red and wrote a revision note. We hope that the revised manuscript will be accepted by the you. Thank you very much for your work! We wish you all the best! All our authors sincerely wish you a Merry Christmas and a Happy New Year! We sincerely wish you and your family a wonderful, lucky and happy New Year!
The detailed description of the modification is as follows:
Point 1: Please try to summarize the abstract. Right now, this is too large.
Response 1:
Dear reviewer:
Thank you very much for your valuable suggestions. Your suggestion will be of great help to the improvement of this paper. Based on this, we have done our best to condense and summarize the "Abstract" part of the paper. Specifically, the number of words in the "Abstract" section has dropped from the original "484" to the current "343". We hope that our modifications can be accepted and approved by you. Thank you very much! Merry Christmas! We wish you all the best! We sincerely wish you and your family a wonderful, lucky and happy New Year!
Point 2: In my opinion, I would suggest one additional indicator: the so-called street based metrics which allow to characterize urban typologies. These are computed by using technologies for collecting geodata such as LiDAR and remote sensing. I understand that you are not focusing on this indicator, but I strongly recommend that you at least include some reference to it.
Response 2:
Dear reviewer:
Thank you very much for your valuable modification suggestions. We believe that your suggestions will bring great help to the improvement of this paper. According to your suggestion, Thank you very much for understanding "I understand that you are not focusing on this indicator" .We still did our best to modify the paper. Firstly, we have added references about "street Based metrics" in the "introduction" section of this paper, and listed three papers on urbanization research using "street based metrics". Secondly, we also pointed out that "street based metrics" is a method that can be extended and applied in subsequent research. We hope that our modifications can be accepted and approved by you.
Your suggestion is very valuable and meaningful, which provides me with a new research idea and method. Therefore, in subsequent research, I will apply "street based metrics" to my research work. In addition, I also carefully read the recent studies you recommended to me. These studies have done a very good job, they are very meaningful and valuable, and they have inspired me a lot. Therefore, in subsequent research, I will also learn from these studies.
To be honest, we all think you are a very nice person, and we would like to express our sincere thanks again for your kindness! Thank you very much! Merry Christmas! We wish you all the best! We sincerely wish you and your family a wonderful, lucky and happy New Year!
Author Response File: Author Response.pdf
Reviewer 3 Report
Authors have applied DMSP-OLS satellite imagery along with other secondary satellite products: LST and NDVI. The manuscript is too complicated without clear focus. The abstract too large (See Author Guidlline for the journal )and results are not as per the title. Beside such, major complication is multi resolution multi source data were applied without proper justification. It is quite uncertain if the resolution of night light would be good enough for the claimed result resolution.
1.In 2.2.1, the article says “The non-radio-calibrated DMSP-OLS night-stabilized lighting data has a spatial resolution of 30 arc seconds and approximately 1 KM at the equator.” Why the unit is not meter? How to understand arc seconds as a unit?
2.In 2.2.1, the article said the data had been removed interference factors like fire, sunlight, moonlight, clouds, and aurora. Did the author do this? How to remove those interference factors specifically? Maybe it is better to explain clearly.
3.In 2.2.2, the article said “The vegetation index data used in this study include the NOAA/AVHRR NDVI data from 1992, 1993, 1995, and 1996 and the SPOT/VG data from 1998 to 2012 synthesized in 10 days.” What does it mean to synthesize data from 1998-2012 in 10 days? It is very unclear.
4.In 3.1, What is the meaning of “find the threshold that can make the extraction result and the land use data spatially closest”?
5.After read 3.2, I still don`t understand how to analyze the extracted urban land area of the YREB by Landscape Index or in other words, how does Landscape Index work? Readers will be quite confused.
6.In 3.2, The author seems not explain how these eight pattern indicators describe the characteristics of landscape type. What is the correlation between them? Were those picked in random or some factor selection technique were applied?
7.In Table 1, the description for Aggregation Index seems not clear. Please clearify.
8.In 4.1 and 4.3, where is the data from? How are these figures calculated? Authors don’t seem to have any basis for the data.
9.In 4.6, the authors said they conducted a correlation analysis. How did they get the correlation coefficients here? Please clarify with some literature as well.
10.In 5.2, the authors conclude that there are nine ways to analyze the evolution of urban expansion. But while reading, all the content of the nine methods are quite similar, the focus is not clear enough result are parochial which can be done from secondary data.
Author Response
Response to Reviewer 3 Comments
Dear reviewer:
Merry Christmas! I sincerely thank you for reviewing our manuscript “A Study on Urban Expansion and its Driving Forces in the Yangtze River Economic Belt, China, Based on Night Light Data” (ID: remotesensing-679656). These comments are valuable for revising and improving our papers. They are also very helpful and have important guiding significance for our research. According to your suggestion, my tutor and I have try our best to revise this paper. We responded carefully and provide a point-by-point response to your comments.We also marked the changes in the manuscript in red and wrote a revision note. We hope that the revised manuscript will be accepted by the you. Thank you very much for your work! We wish you all the best! All our authors sincerely wish you a Merry Christmas and a Happy New Year! We sincerely wish you and your family a wonderful, lucky and happy New Year!
The detailed description of the modification is as follows:
Point 1: The abstract too large.
Response 1:
Dear reviewer:
Thank you very much for your valuable suggestions. Your suggestion will be of great help to the improvement of this paper. Based on this, we have done our best to condense and summarize the "Abstract" part of the paper. Specifically, the number of words in the "Abstract" section has dropped from the original "484" to the current "343".
We hope that our modifications can be accepted and approved by you. Thank you very much! Merry Christmas! We wish you all the best! We sincerely wish you and your family a wonderful, lucky and happy New Year!
Point 2: In 2.2.1, the article says “The non-radio-calibrated DMSP-OLS night-stabilized lighting data has a spatial resolution of 30 arc seconds and approximately 1 KM at the equator.” Why the unit is not meter? How to understand arc seconds as a unit?
Response 2:
Dear reviewer:
Thank you very much for your valuable modification suggestions. We believe that your suggestions will bring great help to the improvement of this paper.
The reason why the spatial resolution of DMSP-OLS nightly stable lighting data uses arc seconds instead of meters. Firstly, it is determined by the source attribute of the DMSP-OLS nighttime stable lighting data, which is downloaded from the National Geographic Data Center (https://www.ngdc.noaa.gov /eog/dmsp.html), including F10, F12, F14, F15, F16, F18 and other six satellites obtained at least one period of archive data per year. The reference frame of each phase of the image is the WGS-84 coordinate system. The acquired width is 3000 km, which is about 1 km near the equator and about 0.8 km at 40 ° north. Because of this position, the spatial resolution is 30 arc seconds, and arc seconds are the most suitable unit.
Secondly, we consider that many published papers were both use 30 arc seconds to describe the spatial resolution of DMSP-OLS nighttime stable lighting data. Therefore, we also listed four papers that use 30 arc seconds to describe the spatial resolution of DMSP-OLS nighttime stable lighting data,such as：（1）Xin Cao, Yang Hua, Xiaolin Zhu, Feng Shic Li Zhuo, Jin Chen.A simple self-adjusting model for correcting the blooming effects in DMSP-OLS nighttime light images. Remote Sensing of Environment.2019,224.401–411.
（2）Mohammed Alahmadi,Peter M. Atkinson.Three-Fold Urban Expansion in Saudi Arabia from 1992 to 2013 Observed Using Calibrated DMSP-OLS Night-Time Lights Imagery.remote sensing.2019,11,1-19.
（3）Wu jian sheng,Niu yan,Peng jian,Wang zheng,Huang xiu xiu. Energy Consumption Trends of Chinese Prefecture-level Cities in 1995-2009 Based on DMSP / OLS Night Light Data. Geographical Research,2014,33(04):625-634. (In Chinese).
（4）Lu xiu,Li jia,Duan ping,Zhang bi rong,Li chen. Correction of DMSP / OLS night light image in China. Surveying and Mapping,2019(07):127-131+159. (In Chinese).
We hope that our modifications can be accepted and approved by you.Thank you very much! Merry Christmas! We wish you all the best! We sincerely wish you and your family a wonderful, lucky and happy New Year!
Point 3: In 2.2.1, the article said the data had been removed interference factors like fire, sunlight, moonlight, clouds, and aurora. Did the author do this? How to remove those interference factors specifically? Maybe it is better to explain clearly.
Response 3:
Dear reviewer:
Thank you very much for your valuable suggestions. Your suggestion will be of great help to the improvement of this paper. Each issue of DMSP / OLS (Version4) non-radiation calibration night issued by the National Geophysical Data Center of the United States National Oceanic and Atmospheric Administration (https://www.ngdc.noaa.gov/eog/dmsp.html) Light images include three types of average images throughout the year: cloudless observation frequency images, average light images, and stable light images.
Stable light image is an annual raster image that calibrates the average light intensity at night. The image includes permanent light sources in cities, towns, and other places, and removes the effects of occasional noise such as moonlight clouds, light fires, and oil and gas combustion.That is to say, the stable light image has been removed from interference factors such as fire, daylight, moonlight, clouds and aurora before release.
Therefore, we also listed two papers that said the data had been removed interference factors like fire, sunlight, moonlight, clouds, and aurora，such as：（1）Bhartendu Pandey, Qingling Zhang, Karen C. Seto.Comparative evaluation of relative calibration methods for DMSP/OLS nighttime lights.Remote Sensing of Environment.2017.195. 67–78.（2）Sophak Pok, Bunkei Matsushita, Takehiko Fukushima.An easily implemented method to estimate impervious surface area on a large scale from MODIS time-series and improved DMSP-OLS nighttime light data.ISPRS Journal of Photogrammetry and Remote Sensing.2017.133. 104–115.
We hope that our modifications can be accepted and approved by you. Thank you very much! Merry Christmas! We wish you all the best! We sincerely wish you and your family a wonderful, lucky and happy New Year!
Point 4: In 2.2.2, the article said “The vegetation index data used in this study include the NOAA/AVHRR NDVI data from 1992, 1993, 1995, and 1996 and the SPOT/VG data from 1998 to 2012 synthesized in 10 days.” What does it mean to synthesize data from 1998-2012 in 10 days? It is very unclear.
Response 4:
Dear reviewer:
Thank you very much for your valuable suggestions. Your suggestion will be of great help to the improvement of this paper.
“The vegetation index data used in this study include the NOAA/AVHRR NDVI data from 1992, 1993, 1995, and 1996 and the SPOT/VG data from 1998 to 2012 synthesized in 10 days.”This involves the property of the data source itself, which means that in each of the four years of 1992, 1993, 1995, and 1996, ten days are selected to synthesize NOAA / AVHRR NDVI data. Therefore, it can be connected with SPOT / VG data from 1998 to 2012.In addition, we have also added new content, introducing the two categories of data downloaded from the United States Geological Survey (USGS) and the VITO website (http://free.vgt.vito.be).
Previously published papers also used such data, and also introduced the data like our paper: such as
（1）He, C.Y.; Liu, Z.F.; Tian,J.; Ma,Q. Urban expansion dynamics and natural habitat loss in China： a multi-scale landscape perspec-tive. Global Change Biology.2014,20,2886-2902.
（2）Yang yang,Li yajing,He chunyang,Li zhifeng,Huang qingxu. Dynamic comparison of the city size distribution of the three major urban agglomerations in the Bohai Rim region—Analysis and perspective based on night light data from 1992 to 2012. Economic geography,2016,36(04):59-69. (In Chinese).
（3）Yang yang,Li yajing,Huang qingxu,Huang cong. Spatial and Temporal Comparison of Urban Land Use and Population Size Distribution in China: A Case Study of the Bohai Rim Region.Geographical Research,2016,35(09):1672-1686. (In Chinese).
We hope that our modifications can be accepted and approved by you. Thank you very much! Merry Christmas! We wish you all the best! We sincerely wish you and your family a wonderful, lucky and happy New Year!
Point 5: In 3.1, What is the meaning of “find the threshold that can make the extraction result and the land use data spatially closest”?
Response 5:
Dear reviewer:
Thank you very much for your valuable suggestions. Your suggestion will be of great help to the improvement of this paper. This part of the content you pointed out is superfluous and we are careless. This is my input error. This part of the content belongs to one of the methods of my previous paper. This paper chooses the stratified SVM method to extract the built-up area of urban. Therefore, we delete this paragraph.
We hope that our modifications can be accepted and approved by you. Thank you very much! Merry Christmas! We wish you all the best! We sincerely wish you and your family a wonderful, lucky and happy New Year!
Point 6: After read 3.2, I still don`t understand how to analyze the extracted urban land area of the YREB by Landscape Index or in other words, how does Landscape Index work? Readers will be quite confused.
Response 6:
Dear reviewer:
Thank you very much for your valuable suggestions. Your suggestion will be of great help to the improvement of this paper.
Landscape index is a simple quantitative indicator that highly condenses landscape pattern information and reflects some aspects of its structural composition and spatial configuration. It is suitable for quantitative analysis of spatial analysis methods of landscape patterns and ecological processes. At present, the landscape index method and landscape pattern analysis software FRAG-STATS 4.2 have been widely used in the field of urbanization research, and academic circles have also published many research results.
Based on your suggestions, we added a new content in the part of "landscape index", and made a detailed explanation of how to use the landscape index to analyze the urban land area of the Yangtze river delta and how the landscape index works.
The details are,after using the stratified SVM method to extract the urban built-up area of the Yangtze River Economic Belt in each year from 1992 to 2013, the data was exported to TIF format, and then the TIF format data was imported into the landscape pattern analysis software FRAG-STATS 4.2. Considering the complex and diverse size of the urban land area in the Yangtze River Economic Belt, this paper selects eight typical pattern indicators (total area, total patch number, patch density, maximum patch index, total boundary length, average boundary density, landscape shape index, and aggregate index).
The eight different landscape pattern indicators represent different meanings, and the meanings of these indicators are described in detail in “Table 1. The landscape pattern index”. Then, select the eight landscape pattern indicators on the operation page of the landscape pattern analysis software FRAG-STATS 4.2, and then execute the calculation command to obtain the calculation result of the Yangtze River Economic Belt landscape pattern index.
In addition, we briefly listed five papers that use the same landscape index to analyze urban land use,such as：
（1）Nathan M. Tarr.Demonstrating a conceptual model for multispecies landscape pattern indices in landscape conservation.LANDSCAPE ECOLOGY.2019，34:2133–2147.
（2）Yujin Park, Jean-Michel Guldmann. Measuring continuous landscape patterns with Gray-Level Co-Occurrence
Matrix (GLCM) indices: An alternative to patch metrics? Ecological Indicators.2020.109. 105802.
（3）Ebru Gül. Sabit Erşahin. Evaluating the desertification vulnerability of a semiarid landscape under different land uses with the environmental sensitivity index. LAND DEGRADATION & DEVELOPMENT.2019.30.7.811-823.
（4）Chen wenbo,Xiao duning,Li xiuzhen. Research on Classification, Application and Construction of Landscape Index. Journal of Applied Ecology,2002(01):121-125. (In Chinese).
（5）Liu jiafu,Wang ping,Li jing,Xu jie,Liu xiaonan. Land use pattern landscape index algorithm and application . Geography and Geographic Information Science,2009,25(01):107-109. (In Chinese).
We hope that our modifications can be accepted and approved by you. Thank you very much! Merry Christmas! We wish you all the best! We sincerely wish you and your family a wonderful, lucky and happy New Year!
Point 7: In 3.2, The author seems not explain how these eight pattern indicators describe the characteristics of landscape type. What is the correlation between them? Were those picked in random or some factor selection technique were applied?
Response 7:
Dear reviewer:
Thank you very much for your valuable suggestions. Your suggestion will be of great help to the improvement of this paper.
The meanings of the eight landscape indicators selected in this paper are shown in "Table 1. The landscape pattern index". Each landscape indicator has its own landscape ecological meaning.After extracting the urban built-up area of the Yangtze River Economic Belt from 1992 to 2013 based on DMSP-OLS lighting data, the TIF format data derived from this data is imported into FRAG-STATS 4.2，Then select the eight landscape pattern indicators for calculation on the operation page of FRAG-STATS 4.2. The calculated results of the eight indicators are shown in "Table 2. Results on the landscape pattern indicators for the YREB from 1992 to 2013".Then combined with the analysis of the meanings of the eight landscape pattern indicators, the characteristics of landscape types can be described. Urban land area as the basis for landscape types.
The eight landscape pattern indicators can form a good complementarity and combination effect, which can well reflect the landscape pattern evolution characteristics of urban land expansion in the Yangtze River Economic Belt.
When selecting the landscape pattern index, we not only referred to the previous studies [82-83], but also considered the complex features of YREB urban land landscape types extracted from dmsp-ols lighting data. The Yangtze River Economic Belt spans the three regions of East, Middle, and West in China, including 11 provinces and cities.The size and area of construction land in different cities and towns vary greatly. Therefore, the landscape types of urban land use in the Yangtze river economic belt are relatively complex.
Table 1. The landscape pattern index
|
Landscape Index |
Shorthand |
Description |
|
Total Area |
TA |
The sum of the areas of all patches |
|
Number of Patches |
NP |
The total number of all patches in the landscape |
|
Patch Density per 100 km2 |
PDH |
Number of patches in an area of 100 km2 |
|
Largest Patch Index |
LPI |
The largest patches in a patch type as a percentage of the total landscape area |
|
Total Edge |
TE |
Total patch length of all patches |
|
Edge Density |
ED |
Length of the patch boundary per unit area |
|
Landscape Shape Index |
LSI |
A landscape shape indicator for patches |
|
Aggregation index |
AI |
The number of similar adjacencies of the corresponding type divided by the maximum value when the type is most confluent as a patch (multiplied by 100 to produce a percentage) |
Table 2. Results on the landscape pattern indicators for the YREB from 1992 to 2013
|
Year |
TA（km2） |
NP |
PDH |
LPI（%） |
TE（km） |
ED（m/km2） |
LSI |
AI |
|
1992 |
10383 |
370 |
2.13 |
99.44 |
679 |
3.91 |
4.50 |
99.71 |
|
1993 |
8505 |
243 |
1.40 |
99.54 |
440 |
2.77 |
4.13 |
99.76 |
|
1994 |
16527 |
414 |
2.39 |
99.15 |
902 |
5.21 |
4.93 |
99.66 |
|
1995 |
16806 |
410 |
2.36 |
99.13 |
901 |
5.19 |
4.93 |
99.66 |
|
1996 |
14430 |
357 |
2.06 |
99.25 |
773 |
4.46 |
4.68 |
99.69 |
|
1997 |
13639 |
355 |
2.05 |
99.29 |
762 |
4.39 |
4.66 |
99.69 |
|
1998 |
15623 |
415 |
2.39 |
99.19 |
882 |
5.08 |
4.89 |
99.67 |
|
1999 |
16855 |
411 |
2.37 |
99.13 |
906 |
5.22 |
4.93 |
99.66 |
|
2000 |
23692 |
491 |
2.83 |
98.80 |
1172 |
6.76 |
5.44 |
99.60 |
|
2001 |
24418 |
501 |
2.89 |
98.74 |
1192 |
6.87 |
5.48 |
99.59 |
|
2002 |
36031 |
703 |
4.05 |
98.14 |
1707 |
9.84 |
6.46 |
99.48 |
|
2003 |
30555 |
568 |
3.27 |
98.41 |
1426 |
8.22 |
5.92 |
99.54 |
|
2004 |
42523 |
720 |
4.15 |
97.73 |
1870 |
10.78 |
6.77 |
99.44 |
|
2005 |
35584 |
543 |
3.13 |
98.05 |
1465 |
8.44 |
6.00 |
99.53 |
|
2006 |
47437 |
642 |
3.70 |
97.37 |
1814 |
10.46 |
6.66 |
99.45 |
|
2007 |
58669 |
786 |
4.53 |
96.88 |
2211 |
12.74 |
7.41 |
99.36 |
|
2008 |
59920 |
777 |
4.48 |
96.82 |
2207 |
12.72 |
7.41 |
99.36 |
|
2009 |
52011 |
697 |
4.02 |
97.32 |
2010 |
11.59 |
7.03 |
99.41 |
|
2010 |
94120 |
1095 |
6.31 |
95.24 |
3240 |
18.68 |
9.37 |
99.13 |
|
2011 |
86121 |
1046 |
6.03 |
95.63 |
3032 |
17.48 |
8.97 |
99.18 |
|
2012 |
92424 |
1083 |
6.24 |
95.30 |
3266 |
18.83 |
9.42 |
99.12 |
|
2013 |
110915 |
1253 |
7.22 |
94.40 |
3898 |
22.47 |
10.62 |
98.98 |
In addition, we also briefly listed three papers that were referenced in writing this part of the content, such as:
（1）Qiuping Huang,Jiejun Huang,Yunjun Zhan,Wei Cui,Yanbin Yuan. Using landscape indicators and Analytic Hierarchy Process (AHP) to determine the optimum spatial scale of urban land use patterns in Wuhan, China. Earth Science Informatics.2018.11. 567–578.
（2）Haoyuan Hong.Abolfazl Jaafari.Eric K. Zenner. Predicting spatial patterns of wildfire susceptibility in the Huichang County,
China: An integrated model to analysis of landscape indicators. Ecological Indicators.2019.101.868-891.
（3）Fan junfu,Ma ting,Zhou chenghu,Zhou yuke. Analysis on the spatial pattern of the Bohai Rim urban agglomeration based on DMSP-OLS images from 1992 to 2010. Journal of Geoinformatics,2013,15(02):280-288.
We hope that our modifications can be accepted and approved by you. Thank you very much! Merry Christmas! We wish you all the best! We sincerely wish you and your family a wonderful, lucky and happy New Year!
Point 8: In Table 1, the description for Aggregation Index seems not clear. Please clearify.
Response 8:
Dear reviewer:
Thank you very much for your valuable suggestions. Your suggestion will be of great help to the improvement of this paper. Based on this,
Based on your suggestions, after reading related books and papers, we further summarized on this basis, changing the description for Aggregation Index to "Reflects the non-randomness or degree of aggregation of different patch types in the landscape, and is used to describe the degree of aggregation of landscape patches "，We have also listed these papers as shown below.
（1）Hong S. He, Barry E. DeZonia and David J. Mladenoff. An aggregation index (AI) to quantify spatial patterns of landscapes. Landscape Ecology .2000,15: 591–601,
（2）Li xiuzhen,Bu cangren,Chang yu,Hu yuanman,Wen qingchun,Wang xugao,Xu chonggang,Li yuehui,He hongshi..Response of landscape pattern indicators to different landscape patterns. Acta Ecologica Sinica.2004(01):123-134.
We hope that our modifications can be accepted and approved by you. Thank you very much! Merry Christmas! We wish you all the best! We sincerely wish you and your family a wonderful, lucky and happy New Year!
Point 9: In 4.1 and 4.3, where is the data from? How are these figures calculated? Authors don’t seem to have any basis for the data.
Response 9:
Dear reviewer:
Thank you very much for your valuable suggestions. Your suggestion will be of great help to the improvement of this paper.
Based on your suggestions, I have added new content in "4.1", explaining where the data comes from and how it is calculated.After using the stratified SVM method to extract the urban land area of the Yangtze River Economic Belt from 1992 to 2013, the data was exported to the year-by-year TIF format, and then the year-by-year TIF format data was imported into FRAG-STATS 4.2. Eight landscape pattern indicators are selected on the operation page of FRAG-STATS 4.2. Then, FRAG-STATS 4.2 was used to calculate the eight landscape pattern indicators.
The content of the "4.3" part of the thesis comes from the data of urban built-up areas in the Yangtze River Economic Zone from 1992 to 2013 based on the DMSP / OLS night light data and then extracted using the stratified SVM method. Demographic data of all provinces and cities in the Yangtze River Economic Belt from 1992-2013 were all downloaded from the China Economic and Social Big Data Research Platform (http://data.cnki.net/Home/Index).These data can be calculated using excel or spss.
In addition, the data source "2.2.2" and method introduction "3.2"、“3.4”、“3.5”and“3.6” in the paper also explained the data source and how to calculate. From the formulas of these methods, it is easy to see how the calculations are performed. Morever ,some methods used in 4.1 and 4.3 are learned from some existing studies, which are relatively mature, reliable and trustworthy.
We hope that our modifications can be accepted and approved by you. Thank you very much! Merry Christmas! We wish you all the best! We sincerely wish you and your family a wonderful, lucky and happy New Year!
Point 10: In 4.6, the authors said they conducted a correlation analysis. How did they get the correlation coefficients here? Please clarify with some literature as well.
Response 10:
Dear reviewer:
Thank you very much for your valuable suggestions. Your suggestion will be of great help to the improvement of this paper. Based on this,
Correlation analysis is a very common method, which can be calculated with spss software. In this paper, the data of the four driving factors and the area of the built-up area of the Yangtze River Economic Belt are imported into the spss software, and a correlation analysis can be performed to calculate the correlation coefficient between the four driving factors and the built-up area of the Yangtze River Economic Belt.
According to your suggestion, we have add new content and cited two related papers for clarify. The two papers are shown below:
（1）Abolghasem, A.; Mohammad,A.S.; Ali,S.Exploring the relationship between spatial driving forces of urban expansion and socioeconomic segregation: The case of Shiraz. Habitat International.2018.81.33-44.
（2）Zhang,R.T .; Jiao,H.F. Study on Urban Land Use Efficiency Pattern Evolution and Driving Mechanism in the Yangtze River Economic Belt.Yangtze River Basin Resources and Environment,2015,24(03):387-394. (In Chinese)
Based on your suggestion, we have add new content does improve the paper. We hope that our modifications can be accepted and approved by you. Thank you very much! Merry Christmas! We wish you all the best! We sincerely wish you and your family a wonderful, lucky and happy New Year!
Point 11: 10.In 5.2, the authors conclude that there are nine ways to analyze the evolution of urban expansion. But while reading, all the content of the nine methods are quite similar, the focus is not clear enough result are parochial which can be done from secondary data.
Response 11:
Dear reviewer:
Thank you very much for your valuable suggestions. Your suggestion will be of great help to the improvement of this paper. All our authors believe that our paper has some significance and value.
First, it is of significance and value to select the Yangtze River Economic Belt in China as the research object. The Yangtze River Economic Belt spans the three major regions of China's east, west, and west. It is not only one of the "three major strategies" implemented by the central government, but also an inland river economic belt with global influence.
Second, the paper uses the DMSP / OLS night light data and other remote sensing data to apply the stratified SVM method to extract the area of the built-up area of the city. It can better reflect the change of urban land in the Yangtze River Economic Belt over a long period of time from 1992 to 2018.
Third, the nine research methods used in this paper have a good combination effect, which can comprehensively reflect all aspects of the spatial dynamics of urban land expansion in the Yangtze River Economic Belt. Such as：a.Landscape index method can reflect the evolution pattern of urban land landscape pattern in the Yangtze River Economic Belt. b.Expansion intensity index can reflect the spatiotemporal process of urban land expansion in the Yangtze River Economic Belt. c. Compactness Index, Urban Land Fractal Index, and Elasticity Coefficient can reflect the spatial pattern of urban land expansion in the Yangtze River Economic Belt . d. The standard deviation ellipse method can reflect the spatial dynamic pattern of urban land expansion in the Yangtze River Economic Belt. e. Moran's I Index can reflect the spatial and temporal correlation pattern of urban expansion in the Yangtze River Economic Belt. f. The driving force analysis can analyze the influencing factors of urban expansion in the Yangtze River Economic Belt from another perspective, which has certain significance for rationally promoting urbanization.
All these contents can give us a comprehensive grasp of the spatial and temporal dynamics of urban expansion in the Yangtze River Economic Belt from 1992 to 2013. This research is a new exploration and further analysis based on the summary of the existing research status, so it has a certain significance for enriching the depth and breadth of related research. In addition, the findings found in this article can also provide some guidance for the scientific and rational development of urbanization in the Yangtze River Economic Belt.
We hope that our modifications can be accepted and approved by you. Thank you very much! Merry Christmas! We wish you all the best! We sincerely wish you and your family a wonderful, lucky and happy New Year!
Point 12: Moderate English changes required.
Response 12:
Dear reviewer:
Thank you very much for your valuable modification suggestions. We believe your suggestion is very valuable and meaningful. Before our paper has been submitted, we have used the English editing service of MDPI to improve the English language problem of this paper, and we also have English-editing-certificate. The English editor certificate can be viewed in the attachment "English-editing-certificate-Yang Zhong". Therefore, after modification by the English editor, the English editor of MDPI believes that the English language of this paper is good.
Based on your Suggestions, you think the English language and style of this paper still need to be improved. Therefore, we have contacted an assistant professor to improve the English language and style of this paper. He works at the University of North Carolina at Chapel Hill. We hope that our modifications can be accepted and approved by you. Thank you very much! Merry Christmas! We wish you all the best! We sincerely wish you and your family a wonderful, lucky and happy New Year!
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
The authors have adressed my comments in an accurate way however I am not conviced about your methods calibrating the dmsp-ols data in order to perform analysis of change over time. I will leave this to the editor to decide.
Author Response
Response to first reviewer's second round of review comments
Dear reviewer:
Happy New Year! I sincerely thank you for reviewing our manuscript 《Spatiotemporal Dynamics and Driving Forces of Urban Land Use Expansion: A Case Study of the Yangtze River Economic Belt, China》 (ID: remotesensing-679656). These comments are valuable for revising and improving our papers. They are also very helpful and have important guiding significance for our research. In the last round of revisions, we have done our best to modify the paper in accordance with your comments, and we are very sure that the paper has significantly improved after the revision.Therefore, all of our authors would like to express our sincere gratitude to you again. Thank you very much！
In response to your comments in this round, all of our authors have try our best to revise this paper. We responded carefully and provide a point-by-point responses to your comments. We have made a more detailed explanation about the calibration of DMSP-OLS nighttime data, and cited four papers to prove the reliability of the Invariant target area method that we have used, and this method also has been widely used.
Moreover, We also marked the changes in the manuscript in red and wrote a revision note. We hope that the revised manuscript will be accepted by you. Thank you very much for your work! We wish you all the best! All of our authors sincerely wish you happy New Year!
The detailed description of the modification is as follows:
Point 1:
The authors have adressed my comments in an accurate way however I am not conviced about your methods calibrating the dmsp-ols data in order to perform analysis of change over time. I will leave this to the editor to decide.
Response 1:
Thank you very much for your valuable suggestions. We have done our best to modify the paper according to your suggestions. We have used the Invariant target area method to calibrate the nighttime light images. Based on your suggestions, we have done our best to make the following revisions: First, we cited four papers that also use the Invariant target area method to calibrate the nighttime light images to prove that the Invariant target area method is widely used and has high credibility. Second, we have made a more detailed description of calibration of DMSP-OLS nighttime data. For example, we have added the details of the two main steps of calibration of DMSP-OLS nighttime data. We are sincerely hope that our revisions will be accepted by you. Thank you very much! We sincerely wish you all the best! Happy New Year! We wish you have a happy, meaningful and wonderful life!
We are full of interest in social science research using remote sensing. This paper is just the beginning of our research work. We also believe that the application of remote sensing in the social sciences has obvious significance and broad space. In future research, we will continue to carry out research work on the application of remote sensing in social sciences. We also hope to continue to receive your guidance in future research, thank you very much! We sincerely wish you all the best!
Reviewer 3 Report
Dear Authors, thank you for the reply and clearing things. All the very best.
Author Response
Response to second reviewer's second round of review comments
Dear reviewer:
Happy New Year! I sincerely thank you for reviewing our manuscript 《Spatiotemporal Dynamics and Driving Forces of Urban Land Use Expansion: A Case Study of the Yangtze River Economic Belt, China》 (ID: remotesensing-679656). These comments are valuable for revising and improving our papers. They are also very helpful and have important guiding significance for our research. In the last round of revisions, we have done our best to modify the paper in accordance with your comments, and we are very sure that the paper has significantly improved after the revision.Therefore, all of our authors would like to express our sincere gratitude to you again. Thank you very much！
In response to First reviewer and academic editor comments in this round, all of our authors have try our best to revise this paper. We responded carefully and provide a point-by-point responses to their comments. We have made a more detailed explanation about the calibration of DMSP-OLS nighttime data, and cited four papers to prove the reliability of the Invariant target area method that we have used, and this method also has been widely used.
Moreover, We also marked the changes in the manuscript in red and wrote a revision note. We hope that the revised manuscript will be accepted by you. Thank you very much for your work! We wish you all the best! All of our authors sincerely wish you happy New Year!
The detailed description of the modification is as follows:
Point 1:
The authors have adressed my comments in an accurate way however I am not conviced about your methods calibrating the dmsp-ols data in order to perform analysis of change over time. I will leave this to the editor to decide.
Response 1:
Thank you very much for your valuable suggestions. We have done our best to modify the paper according to your suggestions. We have used the Invariant target area method to calibrate the nighttime light images. Based on your suggestions, we have done our best to make the following revisions: First, we cited four papers that also use the Invariant target area method to calibrate the nighttime light images to prove that the Invariant target area method is widely used and has high credibility. Second, we have made a more detailed description of calibration of DMSP-OLS nighttime data. For example, we have added the details of the two main steps of calibration of DMSP-OLS nighttime data. We are sincerely hope that our revisions will be accepted by you. Thank you very much! We sincerely wish you all the best! Happy New Year! We wish you have a happy, meaningful and wonderful life!
We are full of interest in social science research using remote sensing. This paper is just the beginning of our research work. We also believe that the application of remote sensing in the social sciences has obvious significance and broad space. In future research, we will continue to carry out research work on the application of remote sensing in social sciences. We also hope to continue to receive your guidance in future research, thank you very much! We sincerely wish you all the best!
