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Research ArticleResearch on Sustainable Development Ability andSpatial-Temporal Differentiation of UrbanHuman Settlements inChina and Japan Based on SDGs Taking Dalian andKobe as Examples

Xueping Cong 12 Xueming Li 12 Songbo Li 12 and Yilu Gong 123

1School of Geography Liaoning Normal University Dalian 116029 China2Human Settlements Research Center Liaoning Normal University Dalian 116029 China3Art and Design School Dalian Polytechnic University Dalian 116034 China

Correspondence should be addressed to Xueping Cong congxueping163com

Received 16 August 2020 Revised 18 October 2020 Accepted 28 December 2020 Published 20 January 2021

Academic Editor Jianhong (Cecilia) Xia

Copyright copy 2021 Xueping Cong et alis is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

e sustainable development of the human settlements (HS) has become a global universal program e comparison of cities indifferent countries is of great significance to provide international experience for future urban construction Combined with theUN 2030 Sustainable Development Goals (SDGs) this paper establishes an evaluation index system for the sustainable de-velopment ability of urban HS and constructs a three-dimensional research framework of ldquodevelopment-coordination-sus-tainabilityrdquo which compares the sustainable development ability of the HS of Dalian China and Kobe Japan from 2005 to 2018and explores the spatial evolution characteristics and obstacle factors of the HS of the two cities e results show that (1) thedevelopment degree of the HS of the two cities is on the rise e development level of Kobe is always higher than that of Dalianand the gap is gradually narrowing Kobe has advantages in natural and residential environment while Dalian has advantages incultural and economic environment (2) e coordination degree of the development of the HS of the two cities has improvedsteadily and the coordination degree of Kobe is better than that of Dalian (3) e sustainability of the development of the HS ofthe two cities is fluctuating and the average sustainable growth rate of Dalian is higher than that of Kobe (4) e sustainabledevelopment space of the HS in Dalian presents a pattern of ldquohigh in the south and low in the northrdquo and the spatial characteristicsof the subsystems are different the main obstacles have changed from economic-natural to economic-natural-cultural-publicservices and the obstacles to development in districts are different (5)e sustainable development space of the HS in Kobe has ahigh level of development in the southeast radiating to the surrounding area and the spatial characteristics of the subsystems aredifferent the main obstacles have changed from economic-cultural-natural to economic-natural-population and the obstacles todevelopment in districts are different Finally it puts forward targeted suggestions for the sustainable construction of Dalian ispaper can provide methodological reference for quantitative assessment of the sustainable development of HS and provide policyreference for scientific planning of the construction of HS

1 Introduction

As a complex open and dynamic giant system the urbanHS is an organic combination of material and nonmaterialenvironments needed by residents Compared with thetraditional HS the sustainable HS emphasizes the simul-taneous improvement of the growth rate and quality It alsounderlines the continuity coordination and stability of

development including economy ecological environmentspiritual culture living conditions and other factors Withthe acceleration of globalization urbanization and infor-matization the urban population has increased from 746million in 1950 (296 of the global population) to morethan half of the population living in cities in 2008 [1] Whilecapital material information and population continue togather in cities it has also brought about a series of

HindawiComplexityVolume 2021 Article ID 8876021 22 pageshttpsdoiorg10115520218876021

unsustainable development problems such as excessiveconsumption of resources deterioration of the ecologicalenvironment and disorderly expansion of urban space etcwhich affects the healthy development of human-land re-lationship and the improvement of the quality of HS Es-pecially the sudden arrival of the COVID-19 epidemicthreatens urban development It has caused economic lossessocial turbulence poverty issues the destruction of healthsystems education issues etc on a global scale and hasbrought new and severe challenges to the sustainable de-velopment of the HS

e science of HS originated from the theory ofekistics first proposed by the Greek architect C ADoxiadis in the 1950s Subsequently the United Nationsfirst held UN Conference on HS (Habitat I) in Vancouverin 1976 and established the United Nations Commissionon HS in 1978 this conference has promoted the worldrsquosattention to HS e HS has the characteristics of inter-disciplinary integration which makes the data of the HSresearch diverse wide-scale rich in perspective anddeepened in content e data come from interviews basedon the subjective feelings of residents [2] questionnaires[3] and official statistical data [4] With the rapid de-velopment of science and technology data acquisitionmethods are more advanced such as night light data [5]vegetation coverage data [6] land cover data [7] andother remote sensing image data as well as electronic mappoints of interest [8] cell phone signaling data [9] socialnetwork data [10] real estate network data [11] and othernetwork data which enrich the new data environmentcomposed of big data and open data In terms of researchmethods with the diversification of research data re-search technical means are gradually enriched mainlyincluding quantitative analysis such as entropy method[12] analytic hierarchy process [13] Delphi method [14]principal component analysis [15] structural equationmodel [16] and the combination of GIS spatial analysisand geographic measurement model which is currentlywidely used [17 18] On the scale of geospatial researchthe administrative geographic scale includes global [19]country [20] urban agglomerations [21] cities [22]communities [23] urban fringe areas [24] and rural areas[3] and specific research areas include islands [25] basins[6] mountains [26] and informal settlements [27] Interms of research perspective and research content thecontent of human settlements is researched frommacro tomicro from multidisciplinary and multiperspective ofenvironmental science [28] biology [29] history [30]sociology [31] geography [32] planning [33] and ar-chitecture [34] such as theoretical research on the HSincluding the related concepts development history anddisciplinary framework of the HS [35] research on thespatial-temporal differentiation of environmental quality[36] livability [37] satisfaction [38] sustainability [39]research on the coupling and coordination degree of HSsystem [40] influencing factors of HS including vege-tation [41] resource richness [42] topography [43] newpollutants [44] social welfare [45] economy [46] andurban governance [47] At the same time the evolution of

HS also has varying degrees of impact on nature reserves[48] land use [49] cultural landscapes [34] and diseases[50]

In summary the theory and practice of the HS havealready produced fruitful research results but the studies onthe sustainability of the urban HS are mostly theoreticaldiscussions and quantitative indicators are rarely used forresearch especially the direct comparative study betweendifferent countries based on first-hand data In this paperfirst of all it selects the coastal cities of Kobe Japan andDalian China in terms of the research objects ey have ahigh degree of similarity in terms of geographic environ-ment production and lifestyle and urban functionsHowever due to differences in economic systems resourceutilization government policies etc the development ofurban HS is different Second in terms of indicator selectioncompared with the selection of traditional urban HS qualityindicators this paper combines the United Nations 2030Sustainable Development Goals and strives to build com-prehensive and targeted indicators for the sustainable de-velopment of HS to make up for the lack of indicators forquantitative analysis of sustainability ird in terms ofanalysis methods the combination of subjective and ob-jective methods is used to determine the index weight inorder to make the results more accurate which not onlyreduces the subjective bias but also avoids the problem ofindex value selection en it compares and analyses theevolution characteristics and differences of the sustainabledevelopment capacity of HS in Dalian and Kobe in the past14 years is paper attempts to construct a measurementmodel for the sustainable development of HS to quantita-tively describe the practical significance of basic parameterssuch as the degree of development coordination and sus-tainability which can better interpret the sustainable de-velopment of HS under long-term conditions e methodof GIS spatial analysis is used to explore the temporal andspatial differentiation pattern and obstacle factors of thesustainable development of the HS in each city in order tofurther understand the advantages and disadvantages of thedevelopment of each city and to provide advice and sug-gestions for the construction and management of the HS inDalian Not only has it enriched the research on the HS andmade up for the lack of empirical cases it also proposed anew assessment framework for the sustainable developmentof the HS which helps to summarize the inherent laws of thesustainable development of the HS It can also providereference for the sustainable and coordinated developmentof coastal cities with similar development backgrounds

2 Overview of the Study Area

Both Kobe in Japan and Dalian in China have been rated aslivable cities and have many similarities (1) Historical andcultural background both Kobe and Dalian have been in-vaded by foreign forces in modern history and they haveintegrated multinational cultural backgrounds Kobe wasjointly managed by European and American powers Dalianwas once reduced to a Russian lease and was invaded byJapan for 40 years (2) Natural conditions Kobe and Dalian

2 Complexity

are both surrounded by mountains and seas Kobe is locatedat 34deg41prime north latitude and 135deg1prime east longitude It is locatedin the southeastern part of Hyogo Prefecture in the Kinkiregion of western Japan along the coast of the Seto InlandSea facing Osaka Bay and the Rokko Mountain Systemtraverses the northern part of the city from east to westDalian is located at 38deg43primendash40deg12prime north latitude and120deg58primendash123deg31prime east longitude It is located on the south-ernmost coast of Liaoning Province China with the YellowSea to the east the Bohai Sea to the west and the ShandongPeninsula to the south In terms of climate the two citieshave a pleasant climate four distinct seasons no scorchingheat in summer no severe cold in winter abundant sun-shine and concentrated rainfall (3) Urban functions Kobeand Dalian are both trading port cities and transportationhub cities Kobe is a city designated by Japanese governmentdecree the function of the city is mainly foreign tradeindustrial economy tourism etc Dalian is a city separatelylisted in Chinarsquos planning it mainly takes equipmentmanufacturing petrochemical electronic information andhigh-tech as its pillar industries At the same time it is afamous tourist city

e research scope of Kobe is the 9 districts under itsadministrative division namely Higashinada-ku Nada-kuChuo-ku Hyogo-ku Nagata-ku Suma-ku Tarumi-ku Kita-ku and Nishi-ku e scope of administrative divisions ofChinese and Japanese cities is different In order to make theresults comparable the two cities need to be on the sameresearch scale erefore 6 districts within the scope ofDalian are selected as the research area including Zhong-shan District Xigang District Shahekou District GanjingziDistrict Lushunkou District and Jinzhou District

3 Index System Construction and Methods

31 Construction of an Evaluation Index System Based onSDGs for the Sustainable Development Ability of Urban Hu-man Settlements e United Nations Sustainable Devel-opment Goals (SDGs) are 17 global development goalsofficially adopted on September 25 2015 after the com-pletion of the United Nations Millennium DevelopmentGoals (MDGs) ey are designed to promote economicprosperity in an integrated manner while protecting theEarth from 2015 to 2030 which not only achieve economicgrowth but also address social needs promote the pro-tection of natural resources and the ecological environ-ment and strive to create a sustainable inclusive andresilient future settlement Among them Goal 11 ldquoSus-tainable Cities and Communitiesrdquo focuses on issues such ashousing basic services transportation facilities livingenvironment public space and other issues in the HS Inorder to evaluate the sustainable development ability of theurban HS more objectively not only the quality of theresidential area but also the natural conditions populationquality and economic development and other aspects mustalso be considered erefore while comprehensivelyconsidering the other 16 sustainable development goals inaddition to ldquoGoal 11rdquo the International Green Model City(IGMC) Standards 30 proposed by the Global Forum on

Human Settlements and existing research should also bereferred [51 52] Following the principles of people-ori-ented uniformity of data statistics comprehensivenesscomparability and operability of indicators 48 indicatorsare selected from the four aspects of natural environmenthumanity environment HS and economic environment tobuild the evaluation index system of sustainable develop-ment ability of HS (Table 1)

32 Data Sources e spatial vector data of Dalian comesfromDalianMaster Plan (2009ndash2020) the spatial vector dataof Kobe comes from the website of the Japanese GovernmentStatistics Comprehensive Window and the Kobe MasterPlan the economic and social data of Dalian comes from2005ndash2019 Dalian Statistical Yearbook Liaoning ProvinceStatistical Yearbook and regional national economic andsocial development statistical bulletins the socio-economicdata of Kobe comes from the 2005ndash2019 Kobe StatisticalYearbook the statistical information of various industriesand the annual tax statistics bulletins the relief degree ofland surface of Dalian is calculated from SRTM DEM 90mdata the housing price data of Dalian are taken fromAnjukethe exchange rate is calculated according to the averageexchange rate value of the Peoplersquos Bank of China for theyear is paper uses the range standardization method toprocess the data and some of the data are the result ofstatistical data calculation

Among them the temperature-humidity index is one ofthe main evaluation indicators of human comfort It wasused earlier by the National Weather Service [53] and thenwidely used worldwide It reflects the heat exchange betweenthe human body and the surrounding environment throughtemperature and humidity e calculation equation is

THI (18t + 32) minus 055 times(1 minus f)(18t minus 26) (1)

In the equation THI is the temperature and humidityindex t is the temperature in degrees celsius (degC) and f isthe relative humidity ()

e wind effect index proposed by American biologistTerjung [54] represents the influence of wind speed tem-perature and solar radiation on the comfort of human skinunder different environments that is the amount of heatexchange per unit area of the body surface e calculationequation is

WEI minus (10v

radic+ 1045 minus v) times(33 minus t) +

200S

D (2)

In the equation WEI is the wind efficiency index v is theaverage wind speed (ms) t is the temperature in degreesCelsius (degC) S is the sunshine hours (h) and D is the daylength (h)

e clothing index proposed by the Australian scholarFreitas [55] reflects the uncomfortable effects of peoplewearing different clothes to adjust the climate environmentIts calculation equation is

ICL 33 minus t

0155Hminus

H + aR cos α(062 + 19

v

radic)H

(3)

Complexity 3

Table 1 e evaluation index system and weight of urban human settlements sustainable development ability based on SDGs

System layer Index layer Unit Corresponding to thetarget in SDGs

Entropyweight

Analytichierarchyprocessweight

Comprehensiveweight

Naturalenvironment(A1)

Relief degree of land surface(B1)

m Goal 15 life on land 00162 00207 00225

Temperature-humidityindex (B2) degC

Goal 13 climateaction 00189 00403 00337

Wind effect index (B3) kcalm2 middot h Goal 13 climateaction 00182 00390 00326

Clothing index (B4) clo Goal 13 climateaction 00206 00509 00396

Standardized precipitationindex (B5)

mdash Goal 13 climateaction 00073 00427 00216

Air quality index (B6) mdashGoal 11 sustainable

cities andcommunities

00157 00971 00477

Green coverage rate ofbuilt-up area (B7)

Goal 15 life on land 00306 00167 00277

Park area per capita (B8) m2Goal 11 sustainable


00149 00191 00207

Sewage treatment rate (B9) Goal 6 clean waterand sanitation 00621 00239 00472

Harmless treatment rate ofdomestic garbage (B10)

Goal 11 sustainable


00082 00202 00158

Energy consumption perunit of GDP (B11)

tcemillion dollarsGoal 12 responsibleconsumption and

production00094 00294 00203

Water resources per capita(B12)

m3 Goal 6 clean waterand sanitation 00225 00587 00444

Humanityenvironment(A2)

Population density (B13) personkm2Goal 11 sustainable


00068 00491 00223

Natural population growthrate (B14)

Goal 11 sustainable


00042 00457 00169

Gender ratio (B15) Goal 5 genderequality 00141 00252 00231

Aging rate (B16) Goal 11 sustainable


00123 00408 00274

Minimum living securityrate (B17)

Goal 1 no poverty 00071 00275 00171

Public collection of booksper 10000 population (B18)

volumeGoal 11 sustainable


00110 00040 00081

Teacher-student ratio inprimary and secondary

schools (B19) Goal 4 quality

education 00225 00129 00208

Number of college studentsper 10000 (B20)

person Goal 4 qualityeducation 00123 00071 00115

Per capita educationexpenditure (B21)

dollar Goal 4 qualityeducation 00301 00066 00172

Number of cultural centersowned by 10000 people

(B22)number

Goal 11 sustainablecities and

communities00385 00034 00140

e proportion of scienceand technology expenditurein fiscal expenditure (B23)

Goal 9 industryinnovation andinfrastructure

00412 00037 00151

4 Complexity

Table 1 Continued


Entropyweight


Comprehensiveweight

Livingenvironment(A3)

Housing area per capita(B24)

m2Goal 11 sustainable


00118 00117 00144

Housing price-to-incomeratio (B25)

Goal 11 sustainable


00111 00117 00140

Gas penetration rate (B26) Goal 7 affordable andclean energy 00217 00117 00195

Water supply penetrationrate (B27)

Goal 6 clean waterand sanitation 00193 00233 00259

Mobile phone penetrationrate (B28)


00102 00050 00087

Internet penetration rate(B29)


00184 00070 00139

Road network density (B30) kmkm2Goal 11 sustainable


00613 00058 00231

Road area per capita (B31) m2Goal 11 sustainable


00063 00073 00083

Number of buses per 10000people (B32)

numberGoal 11 sustainable


00095 00046 00081

Number of stadiums ownedby 10000 people (B33)



00672 00019 00138

Number of hospital bedsper 10000 people (B34)

number Goal 3 good healthand well-being 00283 00067 00169

Number of physicians per10000 people (B35)

person Goal 3 good healthand well-being 00148 00081 00134

Number of welfare facilitiesper 100 elderly people (B36)



00267 00033 00115

Road accident mortality rate(B37)

Goal 11 sustainable


00017 00354 00094

Economicenvironment(A4)

GDP per capita (B38) dollar Goal 8 decent workand economic growth 00250 00274 00320

GDP growth rate (B39) Goal 8 decent workand economic growth 00167 00180 00212

Fiscal revenue growth rate(B40)

Goal 8 decent workand economic growth 00142 00098 00144

e proportion of tertiaryindustry in GDP (B41)


00182 00171 00216

Fixed asset investmentgrowth rate (B42)


Dependence on foreigntrade (B43)

Goal 17 partnershipfor the goals 00155 00057 00115

Unemployment rate (B44) Goal 10 reducedinequalities 00060 00227 00143

Per capita disposableincome growth rate (B45)

Goal 1 no poverty 00138 00227 00217

Engel coefficient (B46) Goal 8 decent workand economic growth 00631 00227 00463

Per capita food production(B47)

kg Goal 2 zero hunger 00648 00124 00347

Per capita production ofmarine products (B48)

kg Goal 14 life belowwater 00049 00053 00062

Complexity 5

In the equation ICL is the clothing index t is thetemperature in Celsius (degC) H is 75 metabolic rate of thehuman body (Wm2) this paper takes the metabolic rateunder light activity at this time H 87Wm2 a is thehuman bodyrsquos absorption of solar radiation usually it takes006 as the maximum value R is the solar radiation receivedby a unit area of land with vertical sunlight (Wm2) usuallytaken as the solar constant1367 (Wm2) α is the solar al-titude angle taking the average value and v is the averagewind speed (ms)

e standardized precipitation index is an indicatorcommonly used by the World Meteorological Organizationto monitor the degree of drought Reflecting the drought andflood situation in a certain period of time it is obtained bycalculating the precipitation in a long period of time throughstandardized transformation of normal distribution [56]

e air quality index is a dimensionless index thatquantitatively describes the air pollution situation obtainedby Mayerrsquos improvement of the air quality index proposedby the US Environmental Protection Agency [57] Itsequation is

IAQIi IAQIhi minus IAQIlo

Chi minus Clotimes Ci minus Clo( 1113857 + IAQIlo

AQI max IAQI1 IAQI2 IAQI3 IAQIn1113864 1113865

(4)

In the equation AQI is the air quality index IAQIi is theair quality index of pollutant i Ci is the concentration ofpollutant i Chi Clo are respectively the high and low valuesof the similar pollutant concentration limit IAQIhi IAQIloare the corresponding air quality score Index of Chi Clo n isthe pollutant item the concentration standard of eachpollutant refers to the Air Quality Guidelines for ParticulateMatter Ozone Nitrogen Dioxide and Sulfur Dioxide issuedby the World Health Organization

33 Research Method

331 Combination Weighting Method e entropy methodis an objective weighting method which has strong objec-tivity and high precision but its application range is limitedand the decision-makerrsquos participation is poor e analytichierarchy process is a subjective weighting method Expertsjudge the importance of various factors based on their ex-perience is method has a strong system but it is toosubjective and errors are prone to occur when there are toomany indicators In order to make the weighting resultsmore accurate this study uses a combination of subjectiveand objective methods to determine the indicator weights ofthe urban HS sustainable development ability evaluationsystem Firstly the entropy weight method and the analytichierarchy process are used to calculate the weight respec-tively and then the combined weight is calculated by theprinciple of minimum information entropy

Entropy method uses information entropy theory toevaluate the orderliness and utility of each indicator esmaller the information entropy value of an indicator thegreater its information utility value and the weight of the

indicator indicating that the indicator is more importantOn the contrary the larger the information entropy thesmaller the information utility value and the smaller theindex weight the smaller the importance for evaluationSpecific calculation steps

(1) Standardize the raw data

Positive indexyij xij minus ximin

ximax minus ximin

Negative indexyij ximax minus xij

ximax minus ximin

(5)

In the equation yij is the j-th index of the i-th unitthat has undergone dimensionless processing xij isthe original value ximin ximax are respectively theminimum and maximum value in the data of thei unit

(2) e proportion of the j-th index in the i-th unit

Yij yij

1113936ni1 yij

(6)

(3) Information entropy value of the j-th index

ej minus1ln n

1113944

n

i1Yij times lnYij1113872 1113873 ej isin [0 1] (7)

(4) Coefficient of difference of the j-th index

dj 1 minus ej (8)

(5) e weight of the j-th index

wj dj

1113936mj1 dj

(9)

e analytic hierarchy process takes the multiobjectivemulticriteria and multielement decision-making problem asa system uses the measurement theory to hierarchize thevarious factors and calculates the order of each level throughthe fuzzy quantification method of qualitative indicatorsproviding a simple and optimized decision-making methodfor multi-index unstructured complex decision-makingproblems e specific calculation steps are as follows

(1) Establish a hierarchical structure model which en-ables the relevant indicators of the research target tobe decomposed into several levels according todifferent attributes from top to bottom e indi-cators of the same level belong to the previous leveland dominate the next level

(2) Constructing judgment matrices at each level in theprocess of inviting evaluators to judge the impor-tance of pairs of indicators at the same level andconstructing a judgment matrix the relative im-portance of important factors that have a greaterimpact on the research goal will be increased erelative importance value of the secondary influ-encing factor will be reduced

6 Complexity

(3) Hierarchical single sorting and consistency test firstcalculate the maximum eigenvalue λmax of thejudgment matrix and its corresponding eigenvectorW and perform normalization with W that is theweight vector of each index then perform consis-tency test the calculation equation is

CI λmax minus n

n minus 1

CR CIRI

(10)

In the equation CI is the consistency index of thedeviation of the judgment matrix if CI 0 thestructure is consistent with the actual situation elarger the value of CI is the worse the consistency ofthe result obtained by the judgment matrix with theactual situation is n is the order of the matrix CR isthe consistency ratio when CR lt 01 the consistencyof the judgment matrix is considered acceptable RIis the random consistency index

(4) Hierarchical total ranking and consistency testcalculate the weight of the relative importance of allfactors of a certain level to the overall goal which isthe total ranking of the hierarchy

is paper formulates corresponding questionnairesbased on the constructed HS sustainability evaluation indexsystem and invites 6 experts in the field of HS and sus-tainable development to compare the importance of theprimary and secondary indicators and construct the cor-responding judgment matrix Taking the first-level indexjudgment matrix (Table 2) as an example the eigenvectorW [04588 02260 01436 01716]T is obtained themaximum eigenvalue is λmax 40458 CR 00172 and thejudgment matrix has satisfactory consistency after inspec-tion so the weight values of the system layer are 0458802260 01436 and 01716 e same method can be used toobtain the weight of the index layer It can be seen fromTable 3 that all the second-level index judgment matrices canpass the consistency test and have relatively high credibility

Determine the combined weight in order to make thecombinedweight value as close as possible to the entropy weightmethod weight and the analytic hierarchy process weightaccording to the principle of minimum relative informationentropy the combined weight is obtained by optimizing theLagrangian multiplier method [58] the calculation equation is

Wj w1jw2j1113872 1113873

05

1113936nj1 w1jw2j1113872 1113873

05 (j 1 2 3 n) (11)

In the equation Wj is the combined weight of the indexj and w1j w2j are respectively the entropy weight methodand the analytic hierarchy process weight of the index j

332 Measurement Model of Urban Human SettlementsSustainable Development Ability e urban HS is an or-ganic complex composed of natural system humanity

system residential system and economic system Eachsubsystem does not exist independently but interacts andinfluences each other On a certain spatial-temporal scalelong-term sustainable urban development and structuraladjustment can make the HS not only meet the needs ofcontemporary reality but also ensure the needs of futuredevelopment In order to evaluate the sustainable devel-opment ability of the harmonious and healthy urbanHS thisresearch is based on the quality of the sustainable devel-opment of the HS combined with the internal structure ofthe human settlements system and the external extensiontrend starting from the three aspects of the developmentcoordination and sustainability of the urban HS to conductcomprehensive research on the sustainable developmentability e equations are as follows

Development degree of urban HS is a measure of thedevelopment level at a certain point in time e higher thevalue the better the development level Its equation is

hi 1113944n

j1wj times yij1113872 1113873

H 1113944m

i1Wi times hi( 1113857

(12)

In the equation hi is the development level of the naturalenvironment the humanity environment the living envi-ronment and the economic environment wj is the weight ofeach index yij is the standardized index value H is thedevelopment level of the urban HS and Wi is the systemweight when calculating the development level of the systemlayer separately the index weight is the ratio of the originalindex weight to the weight of the system layer where it islocated

Coordination degree of urban HS which measures thedegree of coordination among the four systems of naturalenvironment humanity environment residential environ-ment and economic environment characterizes the devel-opment balance of each system and judges the mutualpromotion or restriction of each systeme closer the valueis to 1 the higher the degree of coordination the equation is

C 4 timesh1 times h2 times h3 times h4

h1 + h2 + h3 + h4( 11138574

⎧⎨

⎩

⎫⎬

⎭

14

T αh1 + βh2 + ch3 + δh4

D C times T

radic

(13)

In the equation C is the degree of coupling h1 h2 h3and h4 are the comprehensive evaluation values of naturalenvironment humanity environment living environment

Table 2 First-level index judgment matrix

First-level index A1 A2 A3 A4 Wi

A1 1 2 3 3 04588A2 12 1 2 1 02260A3 13 12 1 1 01436A4 13 1 1 1 01716

Complexity 7

and economic environment respectively T is the coordi-nation index α β c and δ are undetermined coefficients thispaper believes that the four systems are equally importantthe value is 025 D is the coordination degree is paperuses themedian segmentationmethod [40] the classificationstandard of coordination degree type is obtained (Table 4)

Sustainability of urban HS uses the sustainable growthrate to measure the sustainability of the urban HS to a highlevel of development If the value is positive its developmentis sustainable and the sustainability intensity is positivelycorrelated With reference to the sustainable growth modelproposed by the American financial scientist Robert Higginsand existing research [59] the equation is improved as

SGR Ht minus Htminus 1

Htminus 1 (14)

In the equation SGR is the sustainable growth rate andHt is the development level of the urban HS in a certain year

333 Obstacle Model of Urban Human Settlements Sus-tainable Development In order to grasp the causes of thedifferences in the development level of HS more accuratelypathological diagnosis and obstacles models should also beused to clarify the main obstacles affecting the quality ofurban HS in order to make more targeted suggestions on theoptimization of urban HS e main idea of the obstacledegree model is to calculate the degree of restriction of thevarious indicators at various levels on the development ofthe HS e larger the value the stronger the obstacle to thedevelopment of the HS e calculation equation is

Fj Wi times Pij

Vj 1 minus Kj

Oj Fj times Vj

1113936nj1 Fj times Vj

times 100

(15)

In the equation Fj is the factor contribution degree Wi

is the system weight Pij is the weight of the j-th index in thei-th system Vj is the index deviation degree Kj is thestandardized index value and Oj is the obstacle degree ofeach index

4 Results and Discussion

First equation (12) is used to calculate the developmentdegree of the overall urban HS and each subsystem in thetwo cities from 2005 to 2018 equation (13) is used to cal-culate the coordination degree of the urban HS of the twocities equation (14) is used to calculate the sustainability ofthe urban HS of the two cities en 2005 2010 2015 and

2018 are selected as representatives and the overall urbanHSof the urban areas of the two cities and the development levelof each subsystem are matched spatially using the naturalbreakpoint method the development of HS is divided intothree levels of low medium and high Finally the mainobstacle factors and obstacle degrees for the sustainabledevelopment of the urban HS of the two cities and eachurban area are calculated by equation (15)

41 Comparison of Sustainable Development Ability of UrbanHuman Settlements between Dalian and Kobe

411 Comparison of Development Degree of Urban HumanSettlements e overall development level of the urban HSin Dalian and Kobe has shown a good upward trend edevelopment level of Kobe has always been higher than thatof Dalian but the development gap between the two citieshas gradually narrowed (Figure 1) e development trendof the urban HS in Kobe has shown a steady and smallincrease e development rate of urban HS has increasedfrom 0507 in 2005 to 0576 in 2018 with an average annualgrowth rate of 0997 e quality of the HS in Kobe hasbeen increasing slowly from 2005 to 2014is is the stage ofurban economic recovery and stable life of residents after thereconstruction of the Great Hanshin Earthquake in 2015 onthe basis of the ldquoFifth Kobe Basic Planrdquo and the ldquoLowCarbon Natural Symbiosis and Recycling Societyrdquo it ad-justed the urban spatial structure and industrial structurecreated a comprehensive transportation environment by sealand and air and promoted personnel exchanges andeconomic development to a new level rough the estab-lishment of ldquoRegional Welfare Network Usersrdquo and ldquoEm-ployment Promotion Associationsrdquo to provide professionalsupport to socially disadvantaged groups in all aspectsimprove the peace of mind index the quality of the HS israpidly improved e quality of the urban HS in Dalian hasfluctuated upwards and the increase is more obvious thanthat in Kobe It has increased from 0323 in 2005 to 0509 in2018 with an average annual growth rate of 3568 e

Table 3 Consistency test of index level judgment matrix

Index level B1ndash6 B7ndash10 B11-12 B13ndash17 B18ndash23 B24-25 B26ndash29 B30ndash32 B33ndash36 B38ndash43 B44ndash48λmax 65753 41855 2 52839 65354 2 40606 30536 42230 64209 50198CR 00913 00695 0 00634 00850 0 00227 00516 00835 00668 00044

Table 4 e classification criteria of coordinative degree

Coordination degree Coordination level0000ndash0099 Extreme disorder0100ndash0199 Serious disorder0200ndash0299 Moderate disorder0300ndash0399 Mild disorder0400ndash0499 On the verge of disorder0500ndash0599 Barely coordinated0600ndash0699 Primary coordination0700ndash0799 Intermediate coordination0800ndash0899 Good coordinated0900ndash1000 Quality coordination

8 Complexity

development of the HS in Dalian is roughly divided intothree stages e rapid development stage is from 2005 to2011 the ldquoEnriching People Projectrdquo during the ldquoEleventhFive-Year Planrdquo period has significantly improved thequality of life of residents in terms of income housing andsocial security At the same time it promoted the balanceddevelopment of compulsory education across the entireterritory investing heavily in emission reduction andleaping development in transportation has resulted in anoverall improvement in the quality of the HS during theperiod of gradual decline from 2012 to 2014 Dalianrsquos eco-nomic decline was severe during this period the growth rateof GDP and fiscal revenue has dropped significantly andfixed asset investment has shrunk which also affected theability to govern the ecological environment resuminggrowth stage is from 2015 to 2018 when Dalian became anational comprehensive pilot city for new urbanization in2015 and the comprehensive deepening of reforms inecology economy culture and society has once again im-proved the development level of the HS

In terms of natural environment thanks to Japanrsquosadvanced environmental awareness the environmentalconditions of Kobe have always been ahead of Dalian(Figure 2(a)) e natural environment of Kobe remainsstable and good Driven by the goal of ldquoBuilding an Eco-logical and Livable Cityrdquo in Dalian the sustainable devel-opment level of the natural environment has risen involatility and the gap with Kobe has been greatly reducedDalian has certain advantages in topography which is rel-atively flat and conducive to water and soil conservation andvegetation growth Kobersquos awareness of energy conservationand emission reduction in every detail of production and lifegives it a strong advantage in terms of energy consumptionsper GDP and air quality at the same time represented by theldquoRokko Mountain Forest Improvement Strategyrdquo ldquoBasicWater Planrdquo and ldquo2020 Kobe Biodiversity Planrdquo it willcomprehensively enhance environmental protectionawareness and establish a good ecological cycle system thecityrsquos ecological zone has been expanded to 128 areas andthe green coverage of built-up areas and the per capita parkarea is 15 times that of Dalian under the requirements of

building a ldquoMaterial Recycling Societyrdquo strict classificationof waste and 3R (Reduce Reuse and Recycle) treatmenthave made it better in terms of the harmless treatment rate ofdomestic waste

In terms of humanity environment the level of sus-tainable development of humanities in Dalian is better thanthat of Kobe (Figure 2(b)) e development of humanityenvironment in Kobe is slow without any significant im-provement Although Dalian has experienced a phaseddecline it has maintained an overall upward trend In termsof demographic characteristics due to the prolongation ofaverage life-span in Kobe the aging problem is serious theaging rate is nearly twice that of Dalian and the fertility rateis low the population has been declining since 2012 whencombined with population density and sex ratio the pop-ulation structure of Kobe is at a disadvantage In terms ofculture and innovation Japan implemented nine-yearcompulsory education earlier making Kobersquos teaching re-sources more reasonable and complete with higher percapita education expenditures and more public culturalinstitutions in addition the Kobe Government attachesgreat importance to technological development and makesfull use of the advantages of ldquoK Computerrdquo in the fields ofdrug research and development semiconductor materialsetc and accelerate the development of Kobe TechnologyDalian is accelerating the modernization of education In2018 per capita education expenditure increased to 9 timesthat of 2005 and the per capita collection of books tripledAlthough the cultural resource base is relatively weak thegap between the overall cultural environment and Kobe hasnarrowed significantly

In terms of the living environment although Dalian is ina good trend of continuous growth the overall level ofsustainable development of the living environment has beenlagging behind Kobe (Figure 2(c)) e reason is that interms of housing security although the per capita housingarea has been increasing and the housing price-to-incomeratio has continued to decline in Dalian Kobe has formu-lated housing development plans every five years to meet thedifferent needs of residents in different periods At the sametime it continues to enhance the buildingrsquos seismic

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018Com

preh

ensiv

e sco

re o

f hum

an se

ttlem

ents

DalianKobe

0

01

02

03

04

05

06

Figure 1 Development degree of urban human settlements in Dalian and Kobe from 2005 to 2018

Complexity 9

fireproof and waterproof capabilities e two cities havecomparable levels of development in municipal infrastruc-ture In terms of traffic facilities and safety Kobersquos roadnetwork is more reasonable the road barrier-free design ismore complete the death rate of traffic accidents is lowerand the quality of travel is higher In terms of public servicesKobe attaches great importance to the development ofpeople-oriented and social justice strengthens legislationand has established a relatively developed public servicesystem in areas such as sports and fitness medical carefacilities for the elderly and the disabled which continu-ously promotes the sustainable development of the livingenvironment

In terms of economic environment the overall level ofsustainable economic development in Dalian is higher thanthat in Kobe (Figure 2(d)) Before 2013 the developmentlevels of the two cities were quite different However as thequality of Dalianrsquos economy continued to decline Kobe rosesteadily and surpassed in 2015 Dalian Affected by the GreatHanshin Earthquake Kobe has been committed to eco-nomic recovery A large amount of finance has been used tosupport the lives of residents and help enterprises e fi-nancial demand is dozens of times higher than usual Inaddition Kobersquos serious aging problem has affected thesupply of labor resources e reduction in consumptionalso affects government investment and social savings in2014 through vigorously developing the medical industry itformed ldquoJapanrsquos largest biomedical clusterrdquo turning Han-shin Port into an ldquointernational container hub portrdquo whichstrengthened international logistics competitiveness and

increased demand in overseas markets such as clothingsake and pearls and achieved rapid economic growthDalian has a good economic foundation Before 2013 sig-nificant progress was made in transforming the economicgrowth mode and developing a brand economy whichresulted in faster growth in GDP fiscal revenue fixed assetinvestment and per capita disposable income far surpassingthat of Kobe after 2013 under the influence of the inter-national financial crisis wharf trade suffered huge lossescoupled with the lack of industrial innovation and theeconomic level fell severely in a short period of time until2015 the pace of transformation and upgrading of tradi-tional industries was accelerated to enhance the competi-tiveness of emerging industries the economy came backrapidly In terms of the supply of living material resourcesfor residents Dalianrsquos per capita grain output and seafoodoutput have always been far ahead of Kobe

412 Comparison of Coordination Degree of Urban HumanSettlements As shown in Figure 3 the coordination degreeof urban HS in Dalian and Kobe has shown a good upwardtrend e interaction among the four systems continues toincrease e overall coordination degree of the develop-ment of HS in Kobe is higher than that of Daliane degreeof coordination of urban HS in Kobe has risen steadily In2005 the coordination degree was in the stage of primaryand the increase was significant in 2014 and it was stable atthe stage of intermediate After experiencing the devastatingimpact of the Great Hanshin Earthquake in 1995 Kobe

0

01

02

03

04

05

06

07

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

DalianKobe

Scor

e of n

atur

al en

viro

nmen

t

(a)

DalianKobe

0

01

02

03

04

05

06

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Scor

e of p

opul

atio

n an

d cu

ltura

l

(b)

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

DalianKobe

0

01

02

03

04

05

06

07

08

Scor

e of l

ivin

g co

nditi

ons

(c)

DalianKobe

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 20180

01

02

03

04

05

06

07

Scor

e of e

cono

mic

dev

elopm

ent

(d)

Figure 2 Development degree of the subsystems of urban human settlements in Dalian and Kobe from 2005 to 2018 (a) Natural en-vironment (b) humanity environment (c) living environment and (d) economic environment

10 Complexity

basically completed an innovative urban regeneration theldquoHyogo Phenomenon Projectrdquo in 2005 After that the Kobemunicipal government vigorously supports the economy andtakes the residents as the main body to comprehensivelyimprove the environmental construction which makes thecoordination degree of the HS in Kobe rise smoothly andsteadily after 2014 the booming economy of Kobe attractstalents and companies and the government pays attention tothe problem of population decline and aging and it has issuedpolicies to comprehensively guarantee birth and educatechildren and strive to promote ldquoUniversal Design (UD)rdquo tocreate an environment buildings services etc that are easyfor anyone to use It makes every effort to build a future-oriented city open to the world and promote the coordinationof urban HS to an intermediate level of coordination ecoordination degree of Dalianrsquos urban HS development hasfluctuated upward It was barely coordinated from 2005 to2006 and remained in the primary coordination stage from2007 to 2017 However the degree of coordination decreasedfrom 2012 to 2014 and began to slowly rise in 2015 Until 2018it developed to the stage of intermediate coordination Duringthe ldquoEleventh Five-Year Planrdquo period Dalian has undergonemajor changes in its urban spatial layout and industriallayout and its infrastructure and greening levels have rapidlyimproved During this period it has been awarded the titles ofldquoNational Civilized Cityrdquo and ldquoInternational Garden Cityrdquowhich realized the coordinated growth of the HS From 2012to 2014 Dalianrsquos economic development was undergoingtransformation economic development was lagging behindand land water and energy resources were relatively tightwhich made it difficult for the natural and economic envi-ronment to improve simultaneously with population qualityand living conditions after 2015 the ldquoBelt and Roadrdquo ini-tiative and a new round of revitalization of the old northeastindustrial base have brought new opportunities for the de-velopment of Dalian and promoted a slight increase in thecoordination of the urban HS subsystem

413 Comparison of Sustainability of Urban HumanSettlements As shown in Figure 4 the sustainability of the

urban HS in Dalian and Kobe is in a fluctuating devel-opment state and the sustainability is relatively unstablee average sustainable growth rate of the HS in Dalian ishigher than that in Kobe During the study period thesustainable growth rate of HS in Kobe was negative innearly half of the years and the HS was in an unsustainablestate Before 2014 Kobe was committed to economic re-vival but the growth rate was slow which restricts theimprovement of urban infrastructure and public serviceCoupled with social factors such as population aging itresulted in a low sustainable growth rate of urban HS after2014 with the United Nationsrsquo 2030 Agenda for SustainableDevelopment Japan has re-formulated its developmentoutline in various fields based on its national conditionssuch as the Environmental Basic Plan and the Basic Plan forEstablishing a Circular Society Development On this basisit will further improve the urban ecological environmentdevelop the natural history tourism and cultural industryand strengthen technological innovation with a view torealizing ldquoSmart Society 50rdquo as soon as possible whichgives full play to the advantages of youth and female re-searchers and strives to achieve a sustainable HS withstrong resilience to disasters so that the sustainability ofurban HS has improved but in terms of comprehensivepoverty alleviation and the utilization of marine resourcesthe performance is insufficient and there is still a distancefrom the goal of sustainable and stable development esustainable growth rate of Dalianrsquos HS continued to declinefrom 2006 to 2011 but remained basically positive indi-cating that even if sustainability weakened the HS was in astate of sustainable development from 2012 to 2014 thesustainable growth rate of HS is negative e reason is thatunder the influence of global trade imbalance the down-ward pressure on Dalianrsquos economy has increased whilerestricting the development of other aspects of the HS itresulted in poor continuity and stability of the developmentof the HS in an unsustainable state After 2015 the sus-tainable growth rate of the HS has increased to a positivevalue During this period under the guidance of the na-tional supply-side structural reform Dalian has made everyeffort to promote citywide urbanization development and

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018Coo

rdin

atio

n de

gree

of h

uman

settl

emen

ts

05

06

07

08

DalianKobe

Figure 3 Coordination degree of urban human settlements in Dalian and Kobe from 2005 to 2018

Complexity 11

at the same time striven to build a green low-carbonresource-efficient city so that the sustainability of thedevelopment of the HS was enhanced and in a sustainablestate

42 Spatial-Temporal Differentiation and Influencing Factorsof Sustainable Development Ability of Urban HumanSettlements in Dalian

421 Spatial Characteristics of Sustainable DevelopmentAbility of Urban Human Settlements From 2005 to 2018 theoverall quality of the development of the urban HS in Daliangradually improved with a pattern of high in the south andlow in the north (Figure 5) e quality of the HS inZhongshan District and Xigang District has always been in aleading position Zhongshan District is the financial com-mercial and tourist center of Dalian Due to the early start ofregional construction it has strong economic strength andexcellent ecological environment Xigang District is the ad-ministrative and cultural center of Dalian and the first full-scale provincial-level modern service industry cluster in thecoastal economic belt of Liaoning Lushunkou District has agood ecological environment and rich tourism resources It isan important transportation hub in Northeast China Underthe guidance of the goal of building a ldquogreen economic zonerdquothe quality of HS has been raised to a high level of devel-opment Shahekou District has been transformed from anindustrial area to a commercial area relying on the XinghaiBay Financial and Business District to enhance the regionaleconomy while continuously upgrading and transformingold communities and the quality of the HS has beenmaintained at a medium level Jinzhou District is an im-portant part of Dalianrsquos new urban area It has a solidfoundation for opening up However due to the continuousadjustment of the urban spatial layout the pace of im-provement of the HS is slow resulting in a low level of the HSGanjingzi District implemented the ldquoremoval of towns tobuild streetsrdquo in 2007 Due to the low level of urbanization andlate regional construction the development of its HS hasalways been at a medium or low level of development

e level of the natural environment development inDalian has generally risen (Figure 6) Zhongshan DistrictXigang District and Lushunkou District have a higherdegree of greening In addition Lushunkou District is also anational-level scenic spot nature reserve and ecologicaldemonstration area while Ganjingzi District and JinzhouDistrict focus on regional construction and industrial de-velopment they also put pressure on the ecological envi-ronment causing the natural environment to be at adisadvantage e quality of the humanity environmentpresents a spatial pattern of ldquohigh on both sides and low inthe middlerdquo (Figure 7) e population density of Lush-unkou District and Jinzhou District is moderate the agingrate is low the per capita education and cultural resourcesare abundant and the humanity environment is at a highlevel of development Xigang District is home to Dalianlibrary science and technology museum etc cultural andcreative industries are booming there and the humanityenvironment is constantly improving to a high level ofdevelopment Zhongshan District is the old city of Dalianwith a high population density and a high aging rate whichaffects the overall humanity environment with the devel-opment of high-tech industries Ganjingzi District hasattracted many young talents and the quality of humanityhas improved from low to medium level significantlyShahekou District has a high population density and a highaging rate with a relatively large proportion of peopleenjoying subsistence allowances and the shortage of percapita educational resources has led to a low-level devel-opment of the humanity environment e spatial-temporalpattern of the living environment quality is relatively stableshowing a spatial pattern of high in the south and low in thenorth (Figure 8) e quality of the living environment inGanjingzi District and Jinzhou District has always been at alow level of development mainly due to incomplete infra-structure and public service facilities and low living con-venience e development level of the economicenvironment presents the spatial characteristics of ldquohigh inthe east and low in the westrdquo (Figure 9) With the advantagesof the financial and commercial center the economic level ofZhongshan District has always been far ahead the Xigang

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Susta

inab

le g

row

th ra

te o

f hum

an se

ttlem

ents

ndash01

ndash005

0

005

01

015

02

DalianKobe

Figure 4 Sustainability of urban human settlements in Dalian and Kobe from 2006 to 2018

12 Complexity

District continues to give full play to the advantages of theadministrative center to develop the characteristic businessand tourism economy e level has developed from a

medium level to a high level Jinzhou District vigorouslydevelops equipment manufacturing industry which is a hotspot for foreign investment and its economy has developed

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Medium level of developmentLow level of development

High level of development

N

0 20 km2005 2010 2015 2018

Figure 6 Spatial differentiation of the natural subsystem development level of urban human settlements of Dalian in 2005 2010 2015 and2018

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018

Figure 7 Spatial differentiation of the humanity subsystem development level of urban human settlements of Dalian in 2005 2010 2015and 2018

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km

2005 2010 2015 2018

Figure 5 Spatial differentiation of the development level of urban human settlements of Dalian in 2005 2010 2015 and 2018

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018

Figure 8 Spatial differentiation of the residential subsystem development level of urban human settlements of Dalian in 2005 2010 2015and 2018

Complexity 13

rapidly from a low level to a medium level the economicfoundation of Ganjingzi District is poor the industrialstructure is unreasonable and the regional development isextremely uneven In addition the area is large and theradiation effect is weak and the economy has been in a stateof low development

422 Obstacle Factors for the Sustainable DevelopmentAbility of Urban Human Settlements Table 5 lists the ob-stacles and their degree of obstacles to the sustainable de-velopment of the HS in Dalian which ranked the top 6 in2005 2010 2015 and 2018 e table shows that the mainobstacles to the sustainable development of the HS arecaused by economy-nature transformed into economy-na-ture-culture-public services From 2005 to 2018 among themain obstacles the Engel coefficient GDP per capita theproportion of tertiary industry in GDP and the greencoverage of built-up areas have reduced resistance to thedevelopment of the human settlements whereas per capitadisposable income the ratio of teachers and students inprimary and secondary schools and the number of doctorsper 10000 people have increased the obstacles to the de-velopment of the HS e air quality index and per capitawater resources have shown fluctuations It shows that theecological environment has improved Residentsrsquo require-ments for the HS have shifted from the material level to thespiritual civilization level and the consumption structurehas changed from survive to enjoyment For the sustainabledevelopment of the urban HS in Dalian in terms of naturalenvironment it improves the level of urban greening andpromotes resource conservation and utilization in thehumanity environment it improves the allocation of edu-cational resources and the level of social civilization in theliving environment it increases the quantity and quality ofpublic services in the economic environment it promotesthe healthy development of the economy and pay attentionto the lives of residents quality

ere are also differences in the main obstacle factors indifferent districts (Table 6) In 2005 the main obstaclefactors in the six urban areas of Dalian were relativelyconsistent which focused on urban greening municipalinfrastructure and economic development quality in 2018the main obstacle factors in Dalianrsquos urban areas were quitedifferent the economic volume barriers of Zhongshan

District have decreased the obstruction degrees in the agingrate the ratio of teachers and students in primary andsecondary schools the proportion of science and technologyexpenditures and the number of 10000-person stadiumshave all increased the impact of the economic scale ofXigang District has decreased and the impact of demo-graphic characteristics has increased it shows that althoughthe HS of Zhongshan District and Xigang District is rela-tively high they still need to improve population qualityincrease investment in science education culture andtechnological innovation In addition it is necessary to payattention to the problem that the large population makes theinfrastructure per capita small e main obstacle factors inShahekou District are population characteristics urbangreening and economic development the main obstaclefactors in Ganjingzi are relatively scattered the main ob-stacle factors in Lushunkou District come from the level ofeconomic scale the obstacles to economic development inJinzhou District are reduced and the degree of obstacles tourban greening and public services has increased e de-velopment level of the HS in these areas is not high Whilefocusing on economic development it is necessary to bal-ance the ecological environment and promote the quality ofurban public services

43 Spatial-Temporal Differentiation and Influencing Factorsof Sustainable Development Ability of Urban HumanSettlements in Kobe

431 Spatial Characteristics of Sustainable DevelopmentAbility of Urban Human Settlements From 2005 to 2018the overall development quality of the urban HS in Kobeshowed a steady upward trend with a spatially high level ofdevelopment in the southeast radiating to the surroundings(Figure 10) e HS of Chuo-ku and Higashinada-ku alwayshas strong advantages Chuo-ku is the commercial enter-tainment administrative center and transportation hub ofKobe It is rich in tourism resources and is an area withconcentrated urban functions Higashinada-ku has a betternatural environment and its reconstruction was fast afterthe Hanshin earthquake the regional industry there is richand the degree of openness is relatively high Residentsconsider it as a place of residence that they want to continueliving or want to return to e urbanization of Hyogo-ku

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018

Figure 9 Spatial differentiation of the economic subsystem development level of urban human settlements of Dalian in 2005 2010 2015and 2018

14 Complexity

developed earlier After 2010 it has formed a spatialstructure with emphasis on the ecological environment inthe north commercial and cultural activities in the middleand industry in the south making the quality of the HS froma medium level to a high level of development Nada-kumakes full use of natural historical and cultural advantagesvigorously promotes the tourism industry builds a com-mercial and residential complex and continuously improvesthe quality of HS to a high-level development stage Tarumi-ku is dominated by residential land with complete infra-structure sitting on the Akashi Strait Bridge connectingAwaji Island and the four countries of Honshu promotingcultural exchanges and economic development and coupledwith a good ecological environment the HS has moved froma low level to a medium development level earlier In Nishi-ku the development of the new town and industrial park hasdriven other improvements Nagata-ku has made full use ofopen space in recent years and eliminated old houses andthe cultural and creative industries have attracted manyyoung creators and artists e quality of the HS in the twodistricts has been continuously improved from a low level toa medium level e construction of the Kita-ku and Suma-ku started late the development level is low the economicfoundation is weak and the transportation is inconvenientso that the HS has been at a low level of development

e overall development level of the natural environ-ment in Kobe continues to rise showing a spatially differ-entiated pattern of ldquoroofingrdquo (Figure 11) e level ofsustainable development of natural environmentCentralgtWestgt Southeast e Suma-ku and the Kita-kuare affected by the low level of urbanization e environ-mental pressure is small e two districts retain a large areaof rural green space and there are many parks in the Suma-ku Kita-ku has natural scenery represented by Arima HotSprings and it was the first to implement container pack-aging classification in 2008 and the natural environment ofthe two districts has been at a high level of developmentNishi-ku and Tarumi-ku vigorously protect the rural sceneryand coastal environment and they plant flowers to improve

the level of regional greening so that the quality of thenatural environment has increased from a medium level to ahigh level due to the relatively high level of regional de-velopment Chuo-ku and Higashinada-ku have severelydamaged the ecological environment and is in a low-leveldevelopment state Although the overall humanity envi-ronment of Kobe has improved the progress has not beenobvious relatively speaking the development level of thesoutheast is relatively high (Figure 12) e developmentlevel of the humanity environment of Higashinada-ku isalways high this is mainly due to the highmigration rate andthe young population At the same time there are manyuniversities and cultural art galleries here with a highpopulation quality and a good cultural atmosphere theChuo-ku initially has a high aging rate and with the de-velopment of the region it continues to attract young peopleand high-quality talents and the quality of the humanityenvironment continues to improve Kita-ku and Suma-kuhave low population density low education level and pooreducational resources making the humanity environmentlagging behind e living environment of Kobe is im-proving steadily and the high-quality development areas ofthe living environment are mainly concentrated in thesoutheast (Figure 13) Chuo-ku Higashinada-ku andHyogo-ku have complete infrastructure high quality ofpublic services convenient transportation and the livingenvironment is always in a leading state the northern part ofNagata-ku continues to develop into a residential area for ITprofessionals and with the development of the industrialpark in Nishi-ku the infrastructure is constantly improvedwhich promotes the development of the living environmentof the two districts from low to medium level as newlydeveloped residential areas Suma-ku and Kita-ku are notmature enough with inconvenient traffic and relatively poorpublic security resulting in a disadvantaged living envi-ronment e economic environment of Kobe is on a risingtrend (Figure 14) Chuo-ku relies on the advantages ofcommercial and entertainment centers Higashinada-kutakes advantage of the wine industry and the coastal

Table 6 e obstacle indicators and degree of the sustainable development of urban human settlements of different districts of Dalian in2018

District 1 2 3 4 5 6Zhongshan B16 (939) B19 (850) B39 (743) B23 (727) B45 (578) B33 (546)Xigang B16 (847) B15 (767) B39 (671) B38 (656) B45 (520) B47 (516)Shahekou B39 (773) B7 (670) B38 (612) B16 (599) B13 (594) B8 (486)Ganjingzi B38 (763) B41 (691) B19 (604) B45 (591) B7 (484) B34 (482)Lushunkou B38 (796) B45 (774) B39 (720) B1 (630) B41 (616) B40 (522)Jinzhou B7 (741) B38 (665) B39 (647) B8 (566) B33 (553) B1 (497)

Table 5 e obstacle indicators and degree of the sustainable development of urban human settlements of Dalian in 2005 2010 2015 and2018

Year 1 2 3 4 5 62005 B46 (616) B38 (599) B7 (555) B41 (487) B6 (476) B12 (418)2010 B46 (736) B38 (685) B12 (651) B41 (627) B45 (605) B6 (482)2015 B19 (850) B35 (663) B45 (624) B46 (610) B12 (552) B32 (496)2018 B19 (968) B35 (804) B45 (755) B6 (734) B44 (728) B12 (651)

Complexity 15



Kita

NishiNada

SumaTarumi

ChuoHigashinadaHyogo

Nagata

Kita

NishiNada

SumaTarumi

Chuo HigashinadaHyogo

Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018

Figure 11 Spatial differentiation of the natural subsystem development level of urban human settlements of Kobe in 2005 2010 2015 and2018



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018

Figure 12 Spatial differentiation of the humanity subsystem development level of urban human settlements of Kobe in 2005 2010 2015and 2018



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018

Figure 13 Spatial differentiation of the residential subsystem development level of urban human settlements of Kobe in 2005 2010 2015and 2018

Kita

NishiNada

SumaTarumi


Nagata



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km2005 2010 2015 2018

Figure 10 Spatial differentiation of the development level of urban human settlements of Kobe in 2005 2010 2015 and 2018

16 Complexity

industrial zone and the Hyogo-ku vigorously developscommercial streets which has kept the economic develop-ment in a good state Nada-ku and Tarumi-ku developtourism economy and the economic environment has al-ways beenmaintained at a medium level of development therapid development of cultural and creative industries inNagata-ku and the industrial park in Nishi-ku have pro-moted the economic environment of the two districts from alow level to a medium level of development the economicfoundation of Suma-ku and Kita-ku is relatively poor andthe primary industry is the leading industry which makeseconomic growth slow and the level of economic develop-ment low

432 Obstacle Factors for the Sustainable DevelopmentAbility of Urban Human Settlements It can be seen fromTable 7 the top 6 obstacles to sustainable development ofHS in Kobe in 2005 2010 2015 and 2018 and their degreeof obstacles Great changes were made from 2005 to 2010e obstacles to sustainable development of the HS in2005 were concentrated on economic growth educationand urban greening and the obstacles in 2010 wereconcentrated on the level of economic development anddemographic characteristics the indicators that hinderthe development of the HS in Kobe are relatively stable in2015ndash2018 mainly focusing on the natural environmentdemographic characteristics and tertiary industryrsquos shareof GDP Among them the proportion of the added valueof the tertiary industry has dropped slightly the obstaclesto the aging rate and the natural growth rate of thepopulation continue to rise they all indicate that thequality of the ecological environment the economy andthe quality of life are steadily improving and the problemof population structure has become more and more se-rious which become a key factor hindering the sustainabledevelopment of HS e sewage treatment rate has agreater hindrance mainly due to the slight decrease in thesewage treatment rate of Kobe in recent years High reliefdegree of land surface can lead to soil erosion and affecturban construction and economic development and it isalso the main factors hindering sustainable developmentIn order to improve the sustainable development of the HSin Kobe it is necessary to promote the coordinated and

healthy development of industries stimulate the potentialand vitality of economic development take into accountthe effective prevention and control of regional pollutionpay attention to population issues effectively increase thefertility rate of residents and promote population balance

ere are also differences in the main obstacle factorsin different districts (Table 8) Regions with higher qualityof HS have strong advantages in terms of economicfoundation infrastructure and public service levels andthe obstacles are generally lower than other regions suchas Chuo-ku and Higashinada-ku due to population ag-glomeration and the imbalance of the population struc-ture the shortage of per capita public service resourcesshortage of education resources and relatively highhousing prices are the biggest obstacles to the sustainabledevelopment of the HS In addition the topography ofHigashinada-ku is also the main factor hindering regionaldevelopment Due to the early start of regional con-struction in Hyogo-ku Nada-ku and Tarumi-ku theinfrastructure is becoming perfect however the agingproblem has gradually become prominent the degree ofbarriers to economic quality is gradually decreasing andthe barriers to the ratio of teachers and students inprimary and secondary schools and the number of hos-pital beds for 10000 people are gradually increasing isshows that while improving economic strength we mustpay attention to the quality and quantity of public ser-vices e quality of HS in the Nishi-ku Nagata-kuSuma-ku and Kita-ku is relatively poor Although theecological environment has strong advantages the quality



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018

Figure 14 Spatial differentiation of the economic subsystem development level of urban human settlements of Kobe in 2005 2010 2015and 2018

Table 7 e obstacle indicators and degree of the sustainabledevelopment of urban human settlements of Kobe in 2005 20102015 and 2018

Year 1 2 3 4 5 6

2005 B38 (925) B39 (694) B21 (539)B19

(536)B8

(514)B15

(510)

2010 B38 (601) B41 (584) B13 (557)B16

(524)B17

(515)B15

(473)

2015 B16 (820) B14 (680) B9 (625)B41

(525)B15

(504)B1

(486)

2018 B16 (1051) B14 (972) B9 (609)B15

(590)B41

(565)B1

(515)

Complexity 17

of economic development is the biggest obstacle to re-gional development and the degree of obstacles has in-creased to varying degrees Its weak economic foundationand unbalanced industrial structure have led to a lowstandard of living of residents a continuous outflow oftalents and an increase in the aging rate At the sametime it also restricts the improvement of regional sup-porting facilities

5 Conclusion and Policy Implications

51 Conclusion With the global focus on sustainable de-velopment the sustainable development ability of urban HSprovides new directions for urban construction Howeverthe empirical analysis in this field especially the comparativeanalysis among transnational cities is still insufficient Inthis paper it chooses cities that are both close to themountains and the seamdashDalian China and Kobe JapanUnder the concept of sustainable development first anindicator system is built for the sustainable development ofHS based on SDGs and then from the perspective of theoverall development level of the urban HS the mutualcoordination among the various subsystems and the sus-tainability of the sustainable growth rate of the HS thesustainable development ability of the urban HS in Dalianand Kobe from 2005 to 2018 were comparatively analyzedand the strengths and weaknesses of each city were iden-tified it separately analyzed the spatial evolution pattern ofthe sustainable development level of the HS in each city andits obstacle factors and degree of obstacles is paper canprovide methodological reference for quantitative analysis ofthe sustainability of HS and at the same time provide ref-erence for scientific planning and improvement of urban HSquality and sustainable development ability e mainconclusions of this research are as follows

(1) e development degree of the HS in Dalian andKobe has shown a steady and fluctuating upwardtrend respectively e overall development level ofKobe has always been higher than that of Dalian butthe gap has gradually narrowed In terms of naturalenvironment and residential environment Kobe hasalways been better than Dalian In terms of pop-ulation and cultural environment Dalian has moreadvantages and Kobe has not made significantprogress In terms of economic environment Dalian

is far ahead of Kobe before 2013 after that it showeda phased decline and Kobe caught it up in 2015

(2) e coordination degree of urban HS of Dalian andKobe has shown a good upward trend and theoverall coordination degree of HS development ofKobe is higher than that of Dalian Kobersquos HScoordination degree was in the stage of primary in2005 and then it steadily increased which enteredand stabilized at the stage of intermediate in 2014Dalianrsquos HS coordination degree was barely coor-dinated from 2005 to 2006 it has been maintainedin the primary coordination stage from 2007 to2017 but the degree of coordination decreased from2012 to 2014 and began to slowly rise in 2015 untilit developed to the stage of intermediate level in2018

(3) e sustainability of urban HS in Dalian and Kobe isin a fluctuating development state and the averagesustainable growth rate of HS in Dalian is higherthan that in Kobe e sustainability of Kobersquos HS isrelatively unstable and the sustainable growth ratehas been negative for nearly half of the years e HSin Dalian was in a state of sustainable developmentfrom 2006 to 2011 but its sustainability weakenedand it was unsustainable from 2012 to 2014 andrecovered to a state of sustainable development from2015 to 2018

(4) e sustainable development space of the HS inDalian presents a pattern of ldquohigh in the south andlow in the northrdquo e spatial characteristics of thedevelopment level of each subsystem are differente spatial differentiation characteristics of thenatural environment and the residential environ-ment are similar to the overall development spatialpattern e humanity environment presents aspatial pattern of ldquohigh on both sides low in themiddlerdquo and the economic environment develop-ment level presents a spatial pattern of ldquohigh in theeast and low in the westrdquo e main obstacles to thesustainable development of the HS in Dalian havechanged from economic-natural to economic-nat-ural-cultural-public services Economic barriers havedeclined and cultural and public services barriershave increased In addition there are also signifi-cantly differences in obstacle factors in each region

Table 8 e obstacle indicators and degree of the sustainable development of urban human settlements of different districts of Kobe in2018

District 1 2 3 4 5 6Higashinada B19 (1045) B34 (966) B13 (672) B16 (587) B25 (512) B1 (497)Nada B41 (1045) B1 (966) B38 (672) B19 (587) B34 (512) B39 (479)Chuo B19 (1101) B16 (1019) B33 (709) B25 (619) B15 (540) B17 (505)Hyogo B16 (1039) B13 (961) B39 (668) B19 (583) B34 (523) B14 (510)Kita B41 (1107) B38 (1024) B45 (712) B16 (622) B1 (543) B17 (508)Nagata B38 (1010) B41 (935) B16 (650) B13 (586) B42 (568) B14 (496)Suma B41 (1168) B38 (1081) B16 (752) B34 (656) B15 (573) B37 (536)Tarumi B41 (1061) B16 (981) B13 (683) B34 (596) B19 (520) B38 (486)Nishi B38 (1058) B40 (979) B41 (681) B16 (594) B19 (533) B15 (519)

18 Complexity

(5) e sustainable development of the urban HS inKobe has a spatially high level of development in thesoutheast radiating to the surroundings e spatialcharacteristics of the development of each subsystemare different e natural environment presents aldquoroofrdquo pattern of differentiation in themiddlegtwestgt southeast e areas with high levelsof development of humanity environment resi-dential environment and economic environment areconcentrated in the southeast e main obstacles tothe sustainable development of the HS in Kobe havetransitioned from economic-cultural-natural toeconomic-population and then to economic-natu-ral-population Economic barriers have declined andpopulation structure barriers have increased Inaddition there are also differences in barrier factorsin each region

e limitations of this research are as follows First dueto the limitation of data the research unit of this paper isthe urban area For urban areas with a large area thedevelopment level within the unit is also different In thefuture the division of research units can be improved toimprove the accuracy of the research Second due to thelimitation of long-term sequence analysis the combinationof network data and subjective survey data is not sufficientIn the future dynamic and continuous accumulation ofdata can make the evaluation results more convincing andvaluable

52 Policy Implications e research conclusions abovereflect the different characteristics of the growth foundationand development path of the two cities e urban devel-opment of Kobe is relatively mature and that of Dalian isstill in a rising period Compared with Kobe Japanrsquos gradualcomprehensive and detailed process of improving HS thedevelopment model of HS in Dalian China is more ex-tensive and there are many remaining problems In order topromote the coordinated and stable development of the HSin Dalian it puts forward the following suggestions

e construction of the ecological environment shouldbe vigorously strengthened and green development shouldbe comprehensively promoted Beautiful natural landscapesvast clear waters and fresh air are the natural basic con-ditions for the sustainable construction of urban HS Dalianshould build a livable model city with stricter standardsimprove the level of fine dust control strengthen the cityrsquosaccessibility of parks expand the per capita public greenarea promote the conservation and utilization of waterresources strengthen the control of marine pollutionsources implement garbage classification managementstrengthen biodiversity protection and comprehensivelyrectify phenomena that damage the HS such as illegal oc-cupation of roads private construction and random pilesand at the same time build a green industry system vigor-ously improve the level of green industry technology andequipment such as energy conservation environmentalprotection resource utilization and so on and exercisestrong supervision over the adjustment of the energy

structure to make the energy system cleaner safer and moreefficient

e housing security system to achieve ldquoliving and liv-ablerdquo Should be improved Residentsrsquo basic housing rightsare guaranteed which is conducive to social stability andharmony Dalianrsquos urban housing prices are relatively highand urban residents are under greater pressure to buyhouses School districts and residential communities withbetter living conditions have relatively high housing pricesAs a result low- and middle-income and sandwich-classfamilies are unbearable and the relatively low-pricedhousing away from the city center has disadvantages such asinconvenient transportation and imperfect supporting fa-cilities erefore it is necessary to adhere to the people-oriented and city-specific policies for housing security andreal estate management stabilize land prices and housingprices and solve housing problems more accurately in-depth and meticulously At the same time it shouldstrengthen the governance and transformation of dilapi-dated houses improve residential facilities and upgradecommunity management capabilities etc to improve thehappiness of residents

Improve public service facilities and pay attention todisadvantaged groups A sustainable urban HS shouldprovide residents with high-accessibility diversificationand level-based supporting service facilities Dalianrsquos publicservice facilities are concentrated in the southwest leadingto uneven development within the city and restricting thesimultaneous improvement of the quality of life It isnecessary to build a high-quality public service systembased on local conditions such as improving the level ofsanitation and health services improving the built envi-ronment of communities building an urban travel servicesystem with public transportation as the main body andlaunching national fitness exercises In addition it isnecessary to fully respect and understand different socialgroups and meet differentiated needs to resist the lack ofhuman care and insecurity in the construction of urban HSFor example a safe outdoor activity space is needed forchildren It is necessary to build high-standard communityservice centers for the elderly For the disabled it is nec-essary to improve supporting facilities and provide con-venient and stress-free travel services

Transform the economic development model and fo-cus on driving urban economic growth with innovationand human capital In order to resist economic downwardpressure and promote the transformation and upgradingof urban industrial structure we should no longer blindlypursue economic growth but should emphasize thecompetitiveness diversity and stability of economic de-velopment Firstly the wisdom and branding of traditionalcompetitive industries should be promoted such asreshaping the ldquoDalian machine toolrdquo brand acceleratingthe construction of equipment manufacturing in JinzhouDistrict building a strong marine economy etc whileexpanding strategic emerging industries such as high-endequipment andnew energy vehicles secondly social in-novation vitality should be promoted which takes high-tech parks as a demonstration builds a modern industrial

Complexity 19

system with core competitiveness increases efforts tobuild scientific and technological innovation platformssuch as Dalian Institute of Chemical Technology DalianUniversity of Technology and other scientific researchinstitutes and enhances technological transformationcapabilities thirdly it must not only pay attention tocultivating talents improve the quality of all kinds ofeducation and comprehensively improve the culturalliteracy of residents but also improve the talent intro-duction policy select talents based on actual needs andprovide a source of power for talents

Data Availability

e primary data used to support the findings of this studyare available from the corresponding author upon request

Conflicts of Interest

e authors declare no conflicts of interest

Acknowledgments

is work was supported by the National Natural ScienceFoundation of China (Grant no 41671158) Ministry ofEducation Humanities and Social Sciences Research Pro-gram (Grant no 18YJCZH035) Liaoning Social SciencePlanning Fund Program (Grant no L18CGL002) LiaoningEducation Department Scientific Research Project (Grantno J2020060) and Dalian Science and Technology Inno-vation Fund Project (Grant no 2020JJ26GX039)

References

[1] A K Chowdhury ldquoPromoting the construction of globalsustainable human settlementsrdquo Low Carbon World vol 14pp 13-14 2013

[2] J M Senoamadi Intergovernmental Relations SustainableHuman Settlements in the City of Tshwane MetropolitanMunicipality in Gauteng Province University of South AfricaPretoria South Africa 2014

[3] X Zhao H Sun B Chen X Xia and P Li ldquoChinarsquos ruralhuman settlements qualitative evaluation quantitativeanalysis and policy implicationsrdquo Ecological Indicatorsvol 105 pp 398ndash405 2019

[4] L Tang M Ruth Q He and S Mirzaee ldquoComprehensiveevaluation of trends in human settlements quality changesand spatial differentiation characteristics of 35 Chinese majorcitiesrdquo Habitat International vol 70 pp 81ndash90 2017

[5] J J Nieves A Sorichetta C Linard et al ldquoAnnually mod-elling built-settlements between remotely-sensed observa-tions using relative changes in subnational populations andlights at nightrdquo Computers Environment and Urban Systemsvol 80 Article ID 101444 2019

[6] W Halik A Mamat J H Dang B S H Deng and T TiyipldquoSuitability analysis of human settlement environment withinthe Tarim basin in Northwestern Chinardquo Quaternary Inter-national vol 311 pp 175ndash180 2013

[7] P K R Chowdhury B L Bhaduri and J J McKee ldquoEsti-mating urban areas new insights from very high-resolutionhuman settlement datardquo Remote Sensing Applications Societyand Environment vol 10 pp 93ndash103 2018

[8] T Chen W B Wu J J He et al ldquoUrban human settlementsmonitoring model and its application based on multi-sourcespatial data fusionrdquo Acta Ecologica Sinica vol 39 no 4pp 1300ndash1308 2019

[9] B Chen Y M Song B Huang and B Xu ldquoA novel method toextract urban human settlements by integrating remotesensing and mobile phone locationsrdquo Science of RemoteSensing vol 1 Article ID 100003 2020

[10] T V T Nguyen H Y Han and N Sahito ldquoRole of urbanpublic space and the surrounding environment in promotingsustainable development from the lens of social mediardquoSustainability vol 11 no 21 pp 1ndash15 2019

[11] C Li ldquoComprehensive evaluation of human settlements in 36central cities of Chinardquo Journal of Arid Land Resources andEnvironment vol 31 no 5 pp 1ndash6 2017

[12] Y Q Gu J Yang X L Feng C Li and X M Li ldquoSpatialdifferentiation of human settlement environment suitabilityin Chinese typical tourist citiesrdquo Scientia Geographica Sinicavol 35 no 4 pp 410ndash418 2015

[13] J A Parry S A Ganaie and M Sultan Bhat ldquoGIS based landsuitability analysis using AHP model for urban servicesplanning in Srinagar and Jammu urban centers of JampK IndiardquoJournal of Urban Management vol 7 no 2 pp 46ndash56 2018

[14] J V Meijering H Tobi and K Kern ldquoDefining and mea-suring urban sustainability in Europe a Delphi study onidentifying its most relevant componentsrdquo Ecological Indi-cators vol 90 pp 38ndash46 2018

[15] S Krishnan and M Firoz ldquoRegional urban environmentalquality assessment and spatial analysisrdquo Journal of UrbanManagement vol 9 no 2 pp 191ndash204 2020

[16] M A Mohit and S A Iyanda ldquoLiveability and low-incomehousing in Nigeriardquo ProcediamdashSocial and Behavioral Sciencesvol 222 pp 863ndash871 2016

[17] A Komeily and R S Srinivasan ldquoA need for balanced approachto neighborhood sustainability assessments a critical review andanalysisrdquo Sustainable Cities and Society vol 18 pp 32ndash43 2015

[18] W Musakwa R M Tshesane and M Kangethe ldquoe stra-tegically located land index support system for human set-tlements land reform in South Africardquo Cities vol 60pp 91ndash101 2017

[19] F Sabo C Corbane A J Florczyk S Ferri M Pesaresi andT Kemper ldquoComparison of built-up area maps producedwithin the global human settlement frameworkrdquo Transactionsin GIS vol 22 no 6 pp 1406ndash1436 2018

[20] X M Li and P Y Jin ldquoCharacteristics and spatial-temporaldifferences of urban human settlement environment in ChinardquoScientia Geographica Sinica vol 32 no 5 pp 521ndash529 2012

[21] Q Q Yang J Chen B H Li and Y Y Zhu ldquoEvolution anddriving force detection of urban human settlement envi-ronment at urban agglomeration in the middle reaches of theYangtze riverrdquo Scientia Geographica Sinica vol 38 no 2pp 195ndash205 2018

[22] X X Jing S L Ye X Y Wu Y Wang and Y Cheng ldquoAquality evaluation of human settlements in island cities acomparison between Xiamen and Pingtanrdquo Acta EcologicaSinica vol 36 no 12 pp 3678ndash3686 2016

[23] J Yang X M li Y H Li C Z Sun and F X Wang ldquoAs-sessment on spatial differences of human settlement envi-ronment in communities based on DPSIRM model the casestudy of Dalianrdquo Geographical Research vol 31 no 1pp 135ndash143 2012

[24] A G Aguilar ldquoPeri-urbanization illegal settlements andenvironmental impact in Mexico cityrdquo Cities vol 25 no 3pp 133ndash145 2008

20 Complexity

[25] M Zarei and M Zakeri ldquoStrategic planning of human set-tlement development of Qeshm island by using SWOTmodelrdquo World Review of Science Technology and SustainableDevelopment vol 13 no 4 pp 382ndash396 2017

[26] W M Zhao and Y Wang ldquoeoretical construction ofmountain human settlements info-spectrum and its academicsignificancerdquo City Planning Review vol 38 no 4 pp 9ndash162014

[27] J Montoya I Cartes and A Zumelzu ldquoIndicators for eval-uating sustainability in Bogotarsquos informal settlements defi-nition and validationrdquo Sustainable Cities and Society vol 53Article ID 101896 2020

[28] N K Asare-Donkor T A Boadu and A A AdimadoldquoEvaluation of groundwater and surface water quality andhuman risk assessment for trace metals in human settlementsaround the Bosomtwe Crater lake in Ghanardquo SpringerPlusvol 5 p 1812 2016

[29] S Lhoest D Fonteyn K Daınou et al ldquoConservation value oftropical forests distance to human settlements matters morethan management in central Africardquo Biological Conservationvol 241 Article ID 108351 2020

[30] R Rante E Fouache and D Mirzaakhmedov ldquoDynamics ofhuman settlements ensuing from river transformation andchanges in commercial behaviour the birth of the ldquonorth-eastern silk roadrdquordquo Journal of Archaeological Science Reportsvol 9 pp 437ndash447 2016

[31] A J Njoh ldquoModernist urban planning as a tool of accul-turation implications for sustainable human settlement de-velopment in Cameroonrdquo City Culture and Society vol 4no 2 pp 111ndash120 2013

[32] W R Dickinson ldquoBeach ridges as favored locales for humansettlement on Pacific islandsrdquo Geoarchaeology vol 29 no 3pp 249ndash267 2014

[33] H Badland S Mavoa C Boulange et al ldquoIdentifying creatingand testing urban planning measures for transport walkingfindings from the Australian national liveability studyrdquo Journal ofTransport amp Health vol 5 pp 151ndash162 2017

[34] C C Turkyılmaz ldquoInterrelated values of cultural landscapesof human settlements case of Istanbulrdquo Procedia-Social andBehavioral Sciences vol 222 pp 502ndash509 2016

[35] Q Mao ldquoeory and practice of the science of human set-tlements in Chinardquo Urban Planning International vol 34no 4 pp 54ndash63 2019

[36] H Li X M Li S Z Tian S B Li and P F Zhao ldquoTemporaland spatial variation characteristics and mechanism of urbanhuman settlements case study of Liaoning provincerdquo Geo-graphical Research vol 36 no 7 pp 1323ndash1338 2017

[37] Y Wang C Jin M Lu and Y Lu ldquoAssessing the suitability ofregional human settlements environment from a differentpreferences perspective a case study of Zhejiang provinceChinardquo Habitat International vol 70 pp 1ndash12 2017

[38] Y G Cong B Xia and L H Wei ldquoResearch of polarizationand human settlements satisfactory of communities inGuangzhourdquo Human Geography vol 28 no 4 pp 53ndash572013

[39] S Schetke D Haase and T Kotter ldquoTowards sustainablesettlement growth a new multi-criteria assessment forimplementing environmental targets into strategic urbanplanningrdquo Environmental Impact Assessment Review vol 32no 1 pp 195ndash210 2012

[40] X M Li Y J Guo S Z Tian Z Z Bai and H Liu ldquoespatio-temporal pattern evolution and driving force of thecoupling coordination degree of urban human settlements

system in Liaoning provincerdquo Scientia Geographica Sinicavol 39 no 8 pp 1208ndash1218 2019

[41] F J Aceituno and N Loaiza ldquoe role of plants in the earlyhuman settlement of northwest south Americardquo QuaternaryInternational vol 363 pp 20ndash27 2015

[42] G A Martınez D L Mazzanti C Quintana et al ldquoGeo-archaeological and paleoenvironmental context of the humansettlement in the eastern Tandilia range Argentinardquo Qua-ternary International vol 299 pp 23ndash37 2013

[43] C-w Xiao Z-m Feng P Li Z You and J-k TengldquoEvaluating the suitability of different terrains for sustaininghuman settlements according to the local elevation range inChina using the ASTERGDEMrdquo Journal of Mountain Sciencevol 15 no 12 pp 2741ndash2751 2018

[44] S Rezaian ldquoEnvironmental health and safety risks of thepower lines nearby the human settlementsrdquo Human andEcological Risk Assessment An International Journal vol 22no 8 pp 1696ndash1707 2016

[45] H Shekhar A J Schmidt and H-W Wehling ldquoExploringwellbeing in human settlementsmdasha spatial planning per-spectiverdquo Habitat International vol 87 pp 66ndash74 2019

[46] Y Y Song D Q Xue and L H Dai ldquoSpatial-temporalpattern and evolution mechanism of coordinated develop-ment of human settlement environment and economy inenergy accumulation and vulnerable ecology regions a case ofcontiguous areas among Shanxi-Shaanxi-Inner MongoliardquoArid Land Geography vol 40 no 6 pp 1328ndash1337 2017

[47] N Chabbi-Chemrouk and N Drioueche ldquoUrban solidarity akey issue to sustainable human settlementsrdquo Procedia Engi-neering vol 21 pp 707ndash710 2011

[48] J Y Yang J Yang X Y Luo and C H Huang ldquoImpacts byexpansion of human settlements on nature reserves in ChinardquoJournal of Environmental Management vol 248 Article ID109233 2019

[49] A B Reinmann L R Hutyra A Trlica and P OlofssonldquoAssessing the global warming potential of human settlementexpansion in a mesic temperate landscape from 2005 to 2050rdquoScience ofGe Total Environment vol 545-546 pp 512ndash524 2016

[50] A E Larsen A J MacDonald and A J Plantinga ldquoLymedisease risk influences human settlement in the wildland-urban interface evidence from a longitudinal analysis ofcounties in the northeastern United Statesrdquo Ge AmericanJournal of Tropical Medicine and Hygiene vol 91 no 4pp 747ndash755 2014

[51] L Y Wu Introduction to Sciences of Human SettlementsChina Architecture amp Building Press Beijing China 2001

[52] Y Asami Residential Environment Evaluation Method andGeory Tsinghua University Press Beijing China 2006

[53] D G Tout ldquoe discomfort index mortality and the Londonsummers of 1976 and 1978rdquo International Journal of Bio-meteorology vol 24 no 4 pp 323ndash328 1980

[54] W H Terjung ldquoPhysiologic climates of the conterminousUnited States a bioclimatic classification based on manrdquoAnnals of the Association of American Geographers vol 56no 1 pp 141ndash179 1966

[55] C R D Freitas ldquoHuman climates of northern Chinardquo At-mospheric Environment vol 13 no 1 pp 71ndash77 1979

[56] T B Mckee N J Doesken and J Kleist ldquoe relationship ofdrought frequency and duration to time scalesrdquo in Pro-ceedings of the 8th Conference on Applied ClimatologyAnaheim CA USA January 1993

[57] H Mayer L Makra F Kalberlah D Ahrens and U ReuterldquoAir stress and air quality indicesrdquoMeteorologische Zeitschriftvol 13 no 5 pp 395ndash403 2004

Complexity 21

[58] S Li H Wei X L Ni Y W Gu and C X Li ldquoEvaluation ofurban human settlement quality in Ningxia based on AHPand the entropy methodrdquo Chinese Journal of Applied Ecologyvol 25 no 9 pp 2700ndash2708 2014

[59] C Wang H Y Li Y Z He X S Ma and M M ZhouldquoSustainable development ability and its spatiotemporal dif-ferentiations of rural human settlements in Chongqing mu-nicipality from 1997 to 2015rdquo Progress in Geography vol 38no 4 pp 556ndash566 2019

22 Complexity

unsustainable development problems such as excessiveconsumption of resources deterioration of the ecologicalenvironment and disorderly expansion of urban space etcwhich affects the healthy development of human-land re-lationship and the improvement of the quality of HS Es-pecially the sudden arrival of the COVID-19 epidemicthreatens urban development It has caused economic lossessocial turbulence poverty issues the destruction of healthsystems education issues etc on a global scale and hasbrought new and severe challenges to the sustainable de-velopment of the HS

e science of HS originated from the theory ofekistics first proposed by the Greek architect C ADoxiadis in the 1950s Subsequently the United Nationsfirst held UN Conference on HS (Habitat I) in Vancouverin 1976 and established the United Nations Commissionon HS in 1978 this conference has promoted the worldrsquosattention to HS e HS has the characteristics of inter-disciplinary integration which makes the data of the HSresearch diverse wide-scale rich in perspective anddeepened in content e data come from interviews basedon the subjective feelings of residents [2] questionnaires[3] and official statistical data [4] With the rapid de-velopment of science and technology data acquisitionmethods are more advanced such as night light data [5]vegetation coverage data [6] land cover data [7] andother remote sensing image data as well as electronic mappoints of interest [8] cell phone signaling data [9] socialnetwork data [10] real estate network data [11] and othernetwork data which enrich the new data environmentcomposed of big data and open data In terms of researchmethods with the diversification of research data re-search technical means are gradually enriched mainlyincluding quantitative analysis such as entropy method[12] analytic hierarchy process [13] Delphi method [14]principal component analysis [15] structural equationmodel [16] and the combination of GIS spatial analysisand geographic measurement model which is currentlywidely used [17 18] On the scale of geospatial researchthe administrative geographic scale includes global [19]country [20] urban agglomerations [21] cities [22]communities [23] urban fringe areas [24] and rural areas[3] and specific research areas include islands [25] basins[6] mountains [26] and informal settlements [27] Interms of research perspective and research content thecontent of human settlements is researched frommacro tomicro from multidisciplinary and multiperspective ofenvironmental science [28] biology [29] history [30]sociology [31] geography [32] planning [33] and ar-chitecture [34] such as theoretical research on the HSincluding the related concepts development history anddisciplinary framework of the HS [35] research on thespatial-temporal differentiation of environmental quality[36] livability [37] satisfaction [38] sustainability [39]research on the coupling and coordination degree of HSsystem [40] influencing factors of HS including vege-tation [41] resource richness [42] topography [43] newpollutants [44] social welfare [45] economy [46] andurban governance [47] At the same time the evolution of

HS also has varying degrees of impact on nature reserves[48] land use [49] cultural landscapes [34] and diseases[50]

In summary the theory and practice of the HS havealready produced fruitful research results but the studies onthe sustainability of the urban HS are mostly theoreticaldiscussions and quantitative indicators are rarely used forresearch especially the direct comparative study betweendifferent countries based on first-hand data In this paperfirst of all it selects the coastal cities of Kobe Japan andDalian China in terms of the research objects ey have ahigh degree of similarity in terms of geographic environ-ment production and lifestyle and urban functionsHowever due to differences in economic systems resourceutilization government policies etc the development ofurban HS is different Second in terms of indicator selectioncompared with the selection of traditional urban HS qualityindicators this paper combines the United Nations 2030Sustainable Development Goals and strives to build com-prehensive and targeted indicators for the sustainable de-velopment of HS to make up for the lack of indicators forquantitative analysis of sustainability ird in terms ofanalysis methods the combination of subjective and ob-jective methods is used to determine the index weight inorder to make the results more accurate which not onlyreduces the subjective bias but also avoids the problem ofindex value selection en it compares and analyses theevolution characteristics and differences of the sustainabledevelopment capacity of HS in Dalian and Kobe in the past14 years is paper attempts to construct a measurementmodel for the sustainable development of HS to quantita-tively describe the practical significance of basic parameterssuch as the degree of development coordination and sus-tainability which can better interpret the sustainable de-velopment of HS under long-term conditions e methodof GIS spatial analysis is used to explore the temporal andspatial differentiation pattern and obstacle factors of thesustainable development of the HS in each city in order tofurther understand the advantages and disadvantages of thedevelopment of each city and to provide advice and sug-gestions for the construction and management of the HS inDalian Not only has it enriched the research on the HS andmade up for the lack of empirical cases it also proposed anew assessment framework for the sustainable developmentof the HS which helps to summarize the inherent laws of thesustainable development of the HS It can also providereference for the sustainable and coordinated developmentof coastal cities with similar development backgrounds

2 Overview of the Study Area

Both Kobe in Japan and Dalian in China have been rated aslivable cities and have many similarities (1) Historical andcultural background both Kobe and Dalian have been in-vaded by foreign forces in modern history and they haveintegrated multinational cultural backgrounds Kobe wasjointly managed by European and American powers Dalianwas once reduced to a Russian lease and was invaded byJapan for 40 years (2) Natural conditions Kobe and Dalian

2 Complexity











WEI minus (10v


200S

D (2)



ICL 33 minus t

0155Hminus

H + aR cos α(062 + 19

v

radic)H

(3)

Complexity 3



Entropyweight


Comprehensiveweight












00157 00971 00477


Goal 15 life on land 00306 00167 00277



00149 00191 00207



Goal 11 sustainable


00082 00202 00158



production00094 00294 00203






00068 00491 00223


Goal 11 sustainable


00042 00457 00169




00123 00408 00274


Goal 1 no poverty 00071 00275 00171




00110 00040 00081



education 00225 00129 00208






(B22)number


communities00385 00034 00140



00412 00037 00151

4 Complexity

Table 1 Continued


Entropyweight


Comprehensiveweight





00118 00117 00144


Goal 11 sustainable


00111 00117 00140






00102 00050 00087



00184 00070 00139



00613 00058 00231



00063 00073 00083




00095 00046 00081




00672 00019 00138








00267 00033 00115


Goal 11 sustainable


00017 00354 00094








00182 00171 00216







Goal 1 no poverty 00138 00227 00217






Complexity 5







(4)


33 Research Method






ximax minus ximin


ximax minus ximin

(5)



Yij yij

1113936ni1 yij

(6)


ej minus1ln n

1113944

n



dj 1 minus ej (8)


wj dj

1113936mj1 dj

(9)




6 Complexity


CI λmax minus n

n minus 1

CR CIRI

(10)





Wj w1jw2j1113872 1113873

05

1113936nj1 w1jw2j1113872 1113873

05 (j 1 2 3 n) (11)





hi 1113944n

j1wj times yij1113872 1113873

H 1113944m


(12)




h1 + h2 + h3 + h4( 11138574

⎧⎨

⎩

⎫⎬

⎭

14

T αh1 + βh2 + ch3 + δh4

D C times T

radic

(13)




A1 1 2 3 3 04588A2 12 1 2 1 02260A3 13 12 1 1 01436A4 13 1 1 1 01716

Complexity 7




Htminus 1 (14)



Fj Wi times Pij

Vj 1 minus Kj

Oj Fj times Vj


times 100

(15)












8 Complexity






2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018Com

preh

ensiv

e sco

re o

f hum

an se

ttlem

ents

DalianKobe

0

01

02

03

04

05

06


Complexity 9





0

01

02

03

04

05

06

07

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

DalianKobe

Scor

e of n

atur

al en

viro

nmen

t

(a)

DalianKobe

0

01

02

03

04

05

06

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Scor

e of p

opul

atio

n an

d cu

ltura

l

(b)

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

DalianKobe

0

01

02

03

04

05

06

07

08

Scor

e of l

ivin

g co

nditi

ons

(c)

DalianKobe

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 20180

01

02

03

04

05

06

07

Scor

e of e

cono

mic

dev

elopm

ent

(d)


10 Complexity




2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018Coo

rdin

atio

n de

gree

of h

uman

settl

emen

ts

05

06

07

08

DalianKobe


Complexity 11





2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Susta

inab

le g

row

th ra

te o

f hum

an se

ttlem

ents

ndash01

ndash005

0

005

01

015

02

DalianKobe


12 Complexity



Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km

2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Complexity 13







Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


14 Complexity








Complexity 15



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018




Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018




Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018


Kita

NishiNada

SumaTarumi


Nagata



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km2005 2010 2015 2018


16 Complexity







Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018



Year 1 2 3 4 5 6

2005 B38 (925) B39 (694) B21 (539)B19

(536)B8

(514)B15

(510)

2010 B38 (601) B41 (584) B13 (557)B16

(524)B17

(515)B15

(473)

2015 B16 (820) B14 (680) B9 (625)B41

(525)B15

(504)B1

(486)

2018 B16 (1051) B14 (972) B9 (609)B15

(590)B41

(565)B1

(515)

Complexity 17











18 Complexity









Complexity 19


Data Availability




Acknowledgments


References

























20 Complexity



































Complexity 21



22 Complexity











WEI minus (10v


200S

D (2)



ICL 33 minus t

0155Hminus

H + aR cos α(062 + 19

v

radic)H

(3)

Complexity 3



Entropyweight


Comprehensiveweight












00157 00971 00477


Goal 15 life on land 00306 00167 00277



00149 00191 00207



Goal 11 sustainable


00082 00202 00158



production00094 00294 00203






00068 00491 00223


Goal 11 sustainable


00042 00457 00169




00123 00408 00274


Goal 1 no poverty 00071 00275 00171




00110 00040 00081



education 00225 00129 00208






(B22)number


communities00385 00034 00140



00412 00037 00151

4 Complexity

Table 1 Continued


Entropyweight


Comprehensiveweight





00118 00117 00144


Goal 11 sustainable


00111 00117 00140






00102 00050 00087



00184 00070 00139



00613 00058 00231



00063 00073 00083




00095 00046 00081




00672 00019 00138








00267 00033 00115


Goal 11 sustainable


00017 00354 00094








00182 00171 00216







Goal 1 no poverty 00138 00227 00217






Complexity 5







(4)


33 Research Method






ximax minus ximin


ximax minus ximin

(5)



Yij yij

1113936ni1 yij

(6)


ej minus1ln n

1113944

n



dj 1 minus ej (8)


wj dj

1113936mj1 dj

(9)




6 Complexity


CI λmax minus n

n minus 1

CR CIRI

(10)





Wj w1jw2j1113872 1113873

05

1113936nj1 w1jw2j1113872 1113873

05 (j 1 2 3 n) (11)





hi 1113944n

j1wj times yij1113872 1113873

H 1113944m


(12)




h1 + h2 + h3 + h4( 11138574

⎧⎨

⎩

⎫⎬

⎭

14

T αh1 + βh2 + ch3 + δh4

D C times T

radic

(13)




A1 1 2 3 3 04588A2 12 1 2 1 02260A3 13 12 1 1 01436A4 13 1 1 1 01716

Complexity 7




Htminus 1 (14)



Fj Wi times Pij

Vj 1 minus Kj

Oj Fj times Vj


times 100

(15)












8 Complexity






2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018Com

preh

ensiv

e sco

re o

f hum

an se

ttlem

ents

DalianKobe

0

01

02

03

04

05

06


Complexity 9





0

01

02

03

04

05

06

07

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

DalianKobe

Scor

e of n

atur

al en

viro

nmen

t

(a)

DalianKobe

0

01

02

03

04

05

06

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Scor

e of p

opul

atio

n an

d cu

ltura

l

(b)

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

DalianKobe

0

01

02

03

04

05

06

07

08

Scor

e of l

ivin

g co

nditi

ons

(c)

DalianKobe

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 20180

01

02

03

04

05

06

07

Scor

e of e

cono

mic

dev

elopm

ent

(d)


10 Complexity




2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018Coo

rdin

atio

n de

gree

of h

uman

settl

emen

ts

05

06

07

08

DalianKobe


Complexity 11





2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Susta

inab

le g

row

th ra

te o

f hum

an se

ttlem

ents

ndash01

ndash005

0

005

01

015

02

DalianKobe


12 Complexity



Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km

2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Complexity 13







Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


14 Complexity








Complexity 15



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018




Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018




Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018


Kita

NishiNada

SumaTarumi


Nagata



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km2005 2010 2015 2018


16 Complexity







Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018



Year 1 2 3 4 5 6

2005 B38 (925) B39 (694) B21 (539)B19

(536)B8

(514)B15

(510)

2010 B38 (601) B41 (584) B13 (557)B16

(524)B17

(515)B15

(473)

2015 B16 (820) B14 (680) B9 (625)B41

(525)B15

(504)B1

(486)

2018 B16 (1051) B14 (972) B9 (609)B15

(590)B41

(565)B1

(515)

Complexity 17











18 Complexity









Complexity 19


Data Availability




Acknowledgments


References

























20 Complexity



































Complexity 21



22 Complexity



Entropyweight


Comprehensiveweight












00157 00971 00477


Goal 15 life on land 00306 00167 00277



00149 00191 00207



Goal 11 sustainable


00082 00202 00158



production00094 00294 00203






00068 00491 00223


Goal 11 sustainable


00042 00457 00169




00123 00408 00274


Goal 1 no poverty 00071 00275 00171




00110 00040 00081



education 00225 00129 00208






(B22)number


communities00385 00034 00140



00412 00037 00151

4 Complexity

Table 1 Continued


Entropyweight


Comprehensiveweight





00118 00117 00144


Goal 11 sustainable


00111 00117 00140






00102 00050 00087



00184 00070 00139



00613 00058 00231



00063 00073 00083




00095 00046 00081




00672 00019 00138








00267 00033 00115


Goal 11 sustainable


00017 00354 00094








00182 00171 00216







Goal 1 no poverty 00138 00227 00217






Complexity 5







(4)


33 Research Method






ximax minus ximin


ximax minus ximin

(5)



Yij yij

1113936ni1 yij

(6)


ej minus1ln n

1113944

n



dj 1 minus ej (8)


wj dj

1113936mj1 dj

(9)




6 Complexity


CI λmax minus n

n minus 1

CR CIRI

(10)





Wj w1jw2j1113872 1113873

05

1113936nj1 w1jw2j1113872 1113873

05 (j 1 2 3 n) (11)





hi 1113944n

j1wj times yij1113872 1113873

H 1113944m


(12)




h1 + h2 + h3 + h4( 11138574

⎧⎨

⎩

⎫⎬

⎭

14

T αh1 + βh2 + ch3 + δh4

D C times T

radic

(13)




A1 1 2 3 3 04588A2 12 1 2 1 02260A3 13 12 1 1 01436A4 13 1 1 1 01716

Complexity 7




Htminus 1 (14)



Fj Wi times Pij

Vj 1 minus Kj

Oj Fj times Vj


times 100

(15)












8 Complexity






2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018Com

preh

ensiv

e sco

re o

f hum

an se

ttlem

ents

DalianKobe

0

01

02

03

04

05

06


Complexity 9





0

01

02

03

04

05

06

07

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

DalianKobe

Scor

e of n

atur

al en

viro

nmen

t

(a)

DalianKobe

0

01

02

03

04

05

06

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Scor

e of p

opul

atio

n an

d cu

ltura

l

(b)

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

DalianKobe

0

01

02

03

04

05

06

07

08

Scor

e of l

ivin

g co

nditi

ons

(c)

DalianKobe

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 20180

01

02

03

04

05

06

07

Scor

e of e

cono

mic

dev

elopm

ent

(d)


10 Complexity




2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018Coo

rdin

atio

n de

gree

of h

uman

settl

emen

ts

05

06

07

08

DalianKobe


Complexity 11





2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Susta

inab

le g

row

th ra

te o

f hum

an se

ttlem

ents

ndash01

ndash005

0

005

01

015

02

DalianKobe


12 Complexity



Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km

2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Complexity 13







Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


14 Complexity








Complexity 15



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018




Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018




Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018


Kita

NishiNada

SumaTarumi


Nagata



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km2005 2010 2015 2018


16 Complexity







Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018



Year 1 2 3 4 5 6

2005 B38 (925) B39 (694) B21 (539)B19

(536)B8

(514)B15

(510)

2010 B38 (601) B41 (584) B13 (557)B16

(524)B17

(515)B15

(473)

2015 B16 (820) B14 (680) B9 (625)B41

(525)B15

(504)B1

(486)

2018 B16 (1051) B14 (972) B9 (609)B15

(590)B41

(565)B1

(515)

Complexity 17











18 Complexity









Complexity 19


Data Availability




Acknowledgments


References

























20 Complexity



































Complexity 21



22 Complexity

Table 1 Continued


Entropyweight


Comprehensiveweight





00118 00117 00144


Goal 11 sustainable


00111 00117 00140






00102 00050 00087



00184 00070 00139



00613 00058 00231



00063 00073 00083




00095 00046 00081




00672 00019 00138








00267 00033 00115


Goal 11 sustainable


00017 00354 00094








00182 00171 00216







Goal 1 no poverty 00138 00227 00217






Complexity 5







(4)


33 Research Method






ximax minus ximin


ximax minus ximin

(5)



Yij yij

1113936ni1 yij

(6)


ej minus1ln n

1113944

n



dj 1 minus ej (8)


wj dj

1113936mj1 dj

(9)




6 Complexity


CI λmax minus n

n minus 1

CR CIRI

(10)





Wj w1jw2j1113872 1113873

05

1113936nj1 w1jw2j1113872 1113873

05 (j 1 2 3 n) (11)





hi 1113944n

j1wj times yij1113872 1113873

H 1113944m


(12)




h1 + h2 + h3 + h4( 11138574

⎧⎨

⎩

⎫⎬

⎭

14

T αh1 + βh2 + ch3 + δh4

D C times T

radic

(13)




A1 1 2 3 3 04588A2 12 1 2 1 02260A3 13 12 1 1 01436A4 13 1 1 1 01716

Complexity 7




Htminus 1 (14)



Fj Wi times Pij

Vj 1 minus Kj

Oj Fj times Vj


times 100

(15)












8 Complexity






2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018Com

preh

ensiv

e sco

re o

f hum

an se

ttlem

ents

DalianKobe

0

01

02

03

04

05

06


Complexity 9





0

01

02

03

04

05

06

07

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

DalianKobe

Scor

e of n

atur

al en

viro

nmen

t

(a)

DalianKobe

0

01

02

03

04

05

06

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Scor

e of p

opul

atio

n an

d cu

ltura

l

(b)

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

DalianKobe

0

01

02

03

04

05

06

07

08

Scor

e of l

ivin

g co

nditi

ons

(c)

DalianKobe

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 20180

01

02

03

04

05

06

07

Scor

e of e

cono

mic

dev

elopm

ent

(d)


10 Complexity




2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018Coo

rdin

atio

n de

gree

of h

uman

settl

emen

ts

05

06

07

08

DalianKobe


Complexity 11





2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Susta

inab

le g

row

th ra

te o

f hum

an se

ttlem

ents

ndash01

ndash005

0

005

01

015

02

DalianKobe


12 Complexity



Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km

2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Complexity 13







Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


14 Complexity








Complexity 15



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018




Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018




Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018


Kita

NishiNada

SumaTarumi


Nagata



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km2005 2010 2015 2018


16 Complexity







Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018



Year 1 2 3 4 5 6

2005 B38 (925) B39 (694) B21 (539)B19

(536)B8

(514)B15

(510)

2010 B38 (601) B41 (584) B13 (557)B16

(524)B17

(515)B15

(473)

2015 B16 (820) B14 (680) B9 (625)B41

(525)B15

(504)B1

(486)

2018 B16 (1051) B14 (972) B9 (609)B15

(590)B41

(565)B1

(515)

Complexity 17











18 Complexity









Complexity 19


Data Availability




Acknowledgments


References

























20 Complexity



































Complexity 21



22 Complexity







(4)


33 Research Method






ximax minus ximin


ximax minus ximin

(5)



Yij yij

1113936ni1 yij

(6)


ej minus1ln n

1113944

n



dj 1 minus ej (8)


wj dj

1113936mj1 dj

(9)




6 Complexity


CI λmax minus n

n minus 1

CR CIRI

(10)





Wj w1jw2j1113872 1113873

05

1113936nj1 w1jw2j1113872 1113873

05 (j 1 2 3 n) (11)





hi 1113944n

j1wj times yij1113872 1113873

H 1113944m


(12)




h1 + h2 + h3 + h4( 11138574

⎧⎨

⎩

⎫⎬

⎭

14

T αh1 + βh2 + ch3 + δh4

D C times T

radic

(13)




A1 1 2 3 3 04588A2 12 1 2 1 02260A3 13 12 1 1 01436A4 13 1 1 1 01716

Complexity 7




Htminus 1 (14)



Fj Wi times Pij

Vj 1 minus Kj

Oj Fj times Vj


times 100

(15)












8 Complexity






2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018Com

preh

ensiv

e sco

re o

f hum

an se

ttlem

ents

DalianKobe

0

01

02

03

04

05

06


Complexity 9





0

01

02

03

04

05

06

07

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

DalianKobe

Scor

e of n

atur

al en

viro

nmen

t

(a)

DalianKobe

0

01

02

03

04

05

06

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Scor

e of p

opul

atio

n an

d cu

ltura

l

(b)

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

DalianKobe

0

01

02

03

04

05

06

07

08

Scor

e of l

ivin

g co

nditi

ons

(c)

DalianKobe

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 20180

01

02

03

04

05

06

07

Scor

e of e

cono

mic

dev

elopm

ent

(d)


10 Complexity




2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018Coo

rdin

atio

n de

gree

of h

uman

settl

emen

ts

05

06

07

08

DalianKobe


Complexity 11





2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Susta

inab

le g

row

th ra

te o

f hum

an se

ttlem

ents

ndash01

ndash005

0

005

01

015

02

DalianKobe


12 Complexity



Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km

2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Complexity 13







Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


14 Complexity








Complexity 15



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018




Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018




Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018


Kita

NishiNada

SumaTarumi


Nagata



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km2005 2010 2015 2018


16 Complexity







Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018



Year 1 2 3 4 5 6

2005 B38 (925) B39 (694) B21 (539)B19

(536)B8

(514)B15

(510)

2010 B38 (601) B41 (584) B13 (557)B16

(524)B17

(515)B15

(473)

2015 B16 (820) B14 (680) B9 (625)B41

(525)B15

(504)B1

(486)

2018 B16 (1051) B14 (972) B9 (609)B15

(590)B41

(565)B1

(515)

Complexity 17











18 Complexity









Complexity 19


Data Availability




Acknowledgments


References

























20 Complexity



































Complexity 21



22 Complexity


CI λmax minus n

n minus 1

CR CIRI

(10)





Wj w1jw2j1113872 1113873

05

1113936nj1 w1jw2j1113872 1113873

05 (j 1 2 3 n) (11)





hi 1113944n

j1wj times yij1113872 1113873

H 1113944m


(12)




h1 + h2 + h3 + h4( 11138574

⎧⎨

⎩

⎫⎬

⎭

14

T αh1 + βh2 + ch3 + δh4

D C times T

radic

(13)




A1 1 2 3 3 04588A2 12 1 2 1 02260A3 13 12 1 1 01436A4 13 1 1 1 01716

Complexity 7




Htminus 1 (14)



Fj Wi times Pij

Vj 1 minus Kj

Oj Fj times Vj


times 100

(15)












8 Complexity






2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018Com

preh

ensiv

e sco

re o

f hum

an se

ttlem

ents

DalianKobe

0

01

02

03

04

05

06


Complexity 9





0

01

02

03

04

05

06

07

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

DalianKobe

Scor

e of n

atur

al en

viro

nmen

t

(a)

DalianKobe

0

01

02

03

04

05

06

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Scor

e of p

opul

atio

n an

d cu

ltura

l

(b)

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

DalianKobe

0

01

02

03

04

05

06

07

08

Scor

e of l

ivin

g co

nditi

ons

(c)

DalianKobe

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 20180

01

02

03

04

05

06

07

Scor

e of e

cono

mic

dev

elopm

ent

(d)


10 Complexity




2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018Coo

rdin

atio

n de

gree

of h

uman

settl

emen

ts

05

06

07

08

DalianKobe


Complexity 11





2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Susta

inab

le g

row

th ra

te o

f hum

an se

ttlem

ents

ndash01

ndash005

0

005

01

015

02

DalianKobe


12 Complexity



Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km

2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Complexity 13







Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


14 Complexity








Complexity 15



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018




Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018




Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018


Kita

NishiNada

SumaTarumi


Nagata



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km2005 2010 2015 2018


16 Complexity







Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018



Year 1 2 3 4 5 6

2005 B38 (925) B39 (694) B21 (539)B19

(536)B8

(514)B15

(510)

2010 B38 (601) B41 (584) B13 (557)B16

(524)B17

(515)B15

(473)

2015 B16 (820) B14 (680) B9 (625)B41

(525)B15

(504)B1

(486)

2018 B16 (1051) B14 (972) B9 (609)B15

(590)B41

(565)B1

(515)

Complexity 17











18 Complexity









Complexity 19


Data Availability




Acknowledgments


References

























20 Complexity



































Complexity 21



22 Complexity




Htminus 1 (14)



Fj Wi times Pij

Vj 1 minus Kj

Oj Fj times Vj


times 100

(15)












8 Complexity






2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018Com

preh

ensiv

e sco

re o

f hum

an se

ttlem

ents

DalianKobe

0

01

02

03

04

05

06


Complexity 9





0

01

02

03

04

05

06

07

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

DalianKobe

Scor

e of n

atur

al en

viro

nmen

t

(a)

DalianKobe

0

01

02

03

04

05

06

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Scor

e of p

opul

atio

n an

d cu

ltura

l

(b)

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

DalianKobe

0

01

02

03

04

05

06

07

08

Scor

e of l

ivin

g co

nditi

ons

(c)

DalianKobe

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 20180

01

02

03

04

05

06

07

Scor

e of e

cono

mic

dev

elopm

ent

(d)


10 Complexity




2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018Coo

rdin

atio

n de

gree

of h

uman

settl

emen

ts

05

06

07

08

DalianKobe


Complexity 11





2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Susta

inab

le g

row

th ra

te o

f hum

an se

ttlem

ents

ndash01

ndash005

0

005

01

015

02

DalianKobe


12 Complexity



Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km

2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Complexity 13







Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


14 Complexity








Complexity 15



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018




Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018




Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018


Kita

NishiNada

SumaTarumi


Nagata



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km2005 2010 2015 2018


16 Complexity







Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018



Year 1 2 3 4 5 6

2005 B38 (925) B39 (694) B21 (539)B19

(536)B8

(514)B15

(510)

2010 B38 (601) B41 (584) B13 (557)B16

(524)B17

(515)B15

(473)

2015 B16 (820) B14 (680) B9 (625)B41

(525)B15

(504)B1

(486)

2018 B16 (1051) B14 (972) B9 (609)B15

(590)B41

(565)B1

(515)

Complexity 17











18 Complexity









Complexity 19


Data Availability




Acknowledgments


References

























20 Complexity



































Complexity 21



22 Complexity






2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018Com

preh

ensiv

e sco

re o

f hum

an se

ttlem

ents

DalianKobe

0

01

02

03

04

05

06


Complexity 9





0

01

02

03

04

05

06

07

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

DalianKobe

Scor

e of n

atur

al en

viro

nmen

t

(a)

DalianKobe

0

01

02

03

04

05

06

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Scor

e of p

opul

atio

n an

d cu

ltura

l

(b)

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

DalianKobe

0

01

02

03

04

05

06

07

08

Scor

e of l

ivin

g co

nditi

ons

(c)

DalianKobe

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 20180

01

02

03

04

05

06

07

Scor

e of e

cono

mic

dev

elopm

ent

(d)


10 Complexity




2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018Coo

rdin

atio

n de

gree

of h

uman

settl

emen

ts

05

06

07

08

DalianKobe


Complexity 11





2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Susta

inab

le g

row

th ra

te o

f hum

an se

ttlem

ents

ndash01

ndash005

0

005

01

015

02

DalianKobe


12 Complexity



Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km

2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Complexity 13







Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


14 Complexity








Complexity 15



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018




Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018




Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018


Kita

NishiNada

SumaTarumi


Nagata



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km2005 2010 2015 2018


16 Complexity







Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018



Year 1 2 3 4 5 6

2005 B38 (925) B39 (694) B21 (539)B19

(536)B8

(514)B15

(510)

2010 B38 (601) B41 (584) B13 (557)B16

(524)B17

(515)B15

(473)

2015 B16 (820) B14 (680) B9 (625)B41

(525)B15

(504)B1

(486)

2018 B16 (1051) B14 (972) B9 (609)B15

(590)B41

(565)B1

(515)

Complexity 17











18 Complexity









Complexity 19


Data Availability




Acknowledgments


References

























20 Complexity



































Complexity 21



22 Complexity





0

01

02

03

04

05

06

07

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

DalianKobe

Scor

e of n

atur

al en

viro

nmen

t

(a)

DalianKobe

0

01

02

03

04

05

06

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Scor

e of p

opul

atio

n an

d cu

ltura

l

(b)

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

DalianKobe

0

01

02

03

04

05

06

07

08

Scor

e of l

ivin

g co

nditi

ons

(c)

DalianKobe

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 20180

01

02

03

04

05

06

07

Scor

e of e

cono

mic

dev

elopm

ent

(d)


10 Complexity




2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018Coo

rdin

atio

n de

gree

of h

uman

settl

emen

ts

05

06

07

08

DalianKobe


Complexity 11





2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Susta

inab

le g

row

th ra

te o

f hum

an se

ttlem

ents

ndash01

ndash005

0

005

01

015

02

DalianKobe


12 Complexity



Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km

2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Complexity 13







Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


14 Complexity








Complexity 15



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018




Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018




Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018


Kita

NishiNada

SumaTarumi


Nagata



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km2005 2010 2015 2018


16 Complexity







Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018



Year 1 2 3 4 5 6

2005 B38 (925) B39 (694) B21 (539)B19

(536)B8

(514)B15

(510)

2010 B38 (601) B41 (584) B13 (557)B16

(524)B17

(515)B15

(473)

2015 B16 (820) B14 (680) B9 (625)B41

(525)B15

(504)B1

(486)

2018 B16 (1051) B14 (972) B9 (609)B15

(590)B41

(565)B1

(515)

Complexity 17











18 Complexity









Complexity 19


Data Availability




Acknowledgments


References

























20 Complexity



































Complexity 21



22 Complexity




2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018Coo

rdin

atio

n de

gree

of h

uman

settl

emen

ts

05

06

07

08

DalianKobe


Complexity 11





2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Susta

inab

le g

row

th ra

te o

f hum

an se

ttlem

ents

ndash01

ndash005

0

005

01

015

02

DalianKobe


12 Complexity



Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km

2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Complexity 13







Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


14 Complexity








Complexity 15



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018




Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018




Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018


Kita

NishiNada

SumaTarumi


Nagata



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km2005 2010 2015 2018


16 Complexity







Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018



Year 1 2 3 4 5 6

2005 B38 (925) B39 (694) B21 (539)B19

(536)B8

(514)B15

(510)

2010 B38 (601) B41 (584) B13 (557)B16

(524)B17

(515)B15

(473)

2015 B16 (820) B14 (680) B9 (625)B41

(525)B15

(504)B1

(486)

2018 B16 (1051) B14 (972) B9 (609)B15

(590)B41

(565)B1

(515)

Complexity 17











18 Complexity









Complexity 19


Data Availability




Acknowledgments


References

























20 Complexity



































Complexity 21



22 Complexity





2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Susta

inab

le g

row

th ra

te o

f hum

an se

ttlem

ents

ndash01

ndash005

0

005

01

015

02

DalianKobe


12 Complexity



Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km

2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Complexity 13







Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


14 Complexity








Complexity 15



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018




Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018




Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018


Kita

NishiNada

SumaTarumi


Nagata



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km2005 2010 2015 2018


16 Complexity







Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018



Year 1 2 3 4 5 6

2005 B38 (925) B39 (694) B21 (539)B19

(536)B8

(514)B15

(510)

2010 B38 (601) B41 (584) B13 (557)B16

(524)B17

(515)B15

(473)

2015 B16 (820) B14 (680) B9 (625)B41

(525)B15

(504)B1

(486)

2018 B16 (1051) B14 (972) B9 (609)B15

(590)B41

(565)B1

(515)

Complexity 17











18 Complexity









Complexity 19


Data Availability




Acknowledgments


References

























20 Complexity



































Complexity 21



22 Complexity



Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km

2005 2010 2015 2018


Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


Complexity 13







Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


14 Complexity








Complexity 15



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018




Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018




Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018


Kita

NishiNada

SumaTarumi


Nagata



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km2005 2010 2015 2018


16 Complexity







Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018



Year 1 2 3 4 5 6

2005 B38 (925) B39 (694) B21 (539)B19

(536)B8

(514)B15

(510)

2010 B38 (601) B41 (584) B13 (557)B16

(524)B17

(515)B15

(473)

2015 B16 (820) B14 (680) B9 (625)B41

(525)B15

(504)B1

(486)

2018 B16 (1051) B14 (972) B9 (609)B15

(590)B41

(565)B1

(515)

Complexity 17











18 Complexity









Complexity 19


Data Availability




Acknowledgments


References

























20 Complexity



































Complexity 21



22 Complexity







Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang

Jinzhou

Ganjinzi

Lushunkou

Shahekou

Zhongshan

Xigang



N

0 20 km2005 2010 2015 2018


14 Complexity








Complexity 15



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018




Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018




Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018


Kita

NishiNada

SumaTarumi


Nagata



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km2005 2010 2015 2018


16 Complexity







Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018



Year 1 2 3 4 5 6

2005 B38 (925) B39 (694) B21 (539)B19

(536)B8

(514)B15

(510)

2010 B38 (601) B41 (584) B13 (557)B16

(524)B17

(515)B15

(473)

2015 B16 (820) B14 (680) B9 (625)B41

(525)B15

(504)B1

(486)

2018 B16 (1051) B14 (972) B9 (609)B15

(590)B41

(565)B1

(515)

Complexity 17











18 Complexity









Complexity 19


Data Availability




Acknowledgments


References

























20 Complexity



































Complexity 21



22 Complexity








Complexity 15



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018




Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018




Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018


Kita

NishiNada

SumaTarumi


Nagata



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km2005 2010 2015 2018


16 Complexity







Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018



Year 1 2 3 4 5 6

2005 B38 (925) B39 (694) B21 (539)B19

(536)B8

(514)B15

(510)

2010 B38 (601) B41 (584) B13 (557)B16

(524)B17

(515)B15

(473)

2015 B16 (820) B14 (680) B9 (625)B41

(525)B15

(504)B1

(486)

2018 B16 (1051) B14 (972) B9 (609)B15

(590)B41

(565)B1

(515)

Complexity 17











18 Complexity









Complexity 19


Data Availability




Acknowledgments


References

























20 Complexity



































Complexity 21



22 Complexity



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018




Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018




Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018


Kita

NishiNada

SumaTarumi


Nagata



Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km2005 2010 2015 2018


16 Complexity







Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018



Year 1 2 3 4 5 6

2005 B38 (925) B39 (694) B21 (539)B19

(536)B8

(514)B15

(510)

2010 B38 (601) B41 (584) B13 (557)B16

(524)B17

(515)B15

(473)

2015 B16 (820) B14 (680) B9 (625)B41

(525)B15

(504)B1

(486)

2018 B16 (1051) B14 (972) B9 (609)B15

(590)B41

(565)B1

(515)

Complexity 17











18 Complexity









Complexity 19


Data Availability




Acknowledgments


References

























20 Complexity



































Complexity 21



22 Complexity







Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

Kita

NishiNada

SumaTarumi


Nagata

N

0 5 km

2005 2010 2015 2018



Year 1 2 3 4 5 6

2005 B38 (925) B39 (694) B21 (539)B19

(536)B8

(514)B15

(510)

2010 B38 (601) B41 (584) B13 (557)B16

(524)B17

(515)B15

(473)

2015 B16 (820) B14 (680) B9 (625)B41

(525)B15

(504)B1

(486)

2018 B16 (1051) B14 (972) B9 (609)B15

(590)B41

(565)B1

(515)

Complexity 17











18 Complexity









Complexity 19


Data Availability




Acknowledgments


References

























20 Complexity



































Complexity 21



22 Complexity











18 Complexity









Complexity 19


Data Availability




Acknowledgments


References

























20 Complexity



































Complexity 21



22 Complexity









Complexity 19


Data Availability




Acknowledgments


References

























20 Complexity



































Complexity 21



22 Complexity


Data Availability




Acknowledgments


References

























20 Complexity



































Complexity 21



22 Complexity



































Complexity 21



22 Complexity



22 Complexity

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