Measurement of the Degree of Compactness of Large municipal Cities in Coastal Provinces in

China: A Conceptual Analysis

Roger C.K.CHAN Associate Professor XIE Yongqing Research Student

Centre of Urban Planning and Environmental Management

The University of Hong Kong

Outline• Background

• Relevant Theories

• Empirical Study

• Conclusion

Global perspective

China’s perspective

Concept of compact city

Features of compact city

Conceptual Model of compact city Research design

Findings

Part 1BACKGROUND

1. Global Perspective

• Rapid urbanization, boom of urban residents• Urban Growth

Urbanization in 1975

Urbanization in 2000

Urbanization in 2025(estimated by UN)

annual Urban growth rate

All the world 37.7% 49% 61.1% 2.38%

Developed countries

69.8% 76% 84.0% 0.71%

Developing countries

26.7% 39.9% 57.1% 3.21%

Source: UNCHS (1996) An Urbanising World: Global Report on Human Settlements, Oxford, University Press, Oxford.

Compact city

Sustainable Development

“Sustainable development declaration”, 1980

The announcement regarding sustainable cities in the Toronto Declaration, 1990

The answer to the sustainable city form

Sustainability becomes a planning goal

Relevant policies in the world

UK:Planning Policy Statement [Part1: Delivering Sustainable Development] (Office of the Deputy Prime Minister, 2005)

Netherlands:The National Spatial Strategy (2020) (Netherlands Ministry of Housing, Spatial Planning and the Environment)

Hong Kong: Hong Kong 2030 Planning vision and Strategy (HKSAR, 2007)

………………………….

2. China’s Perspective Rapid Urbanization

Unit:10 thousand

Urban Residents Change

Source: China Statistical Yearbook - 2006

2. China’s Perspective

Year Built-up Area (sq.km)

1997 136131998 146581999 154392000 162212001 176052002 198442003 232672004 23943

Change of Built-up area in municipal cities

China’s Situation

Rapid population growth and urbanization

National Population and Family Planning Commission(2004) reported:

by 2010, 1.37 billion people by 2020, 1.46 billion people by 2033, 1.5 billion people

National Development and Reform Commission(2004) reported:

By 2020, the urbanization will reach 57%, and the number of urban residents would be 0.84 billion.

China’s Situation

Limited land resource and extensive construction area

Ministry of Land and Resources reported in 2005

the area of territory per person per person is 0.73 hectare in China, and 2.9 hectare in the world

the cultivated land per person is 933 sq.m. in China, and 3200 sq.m. in the world

the construction area per person in China is more than 130 sq.m., and 82.4 sq.m in developed countries, 83.3 sq.m in developing countries.

The Compact city paradigm could be one of the approaches that cities could choose to maintain sustainability.

Urban area

Rapid urbanization & Population Growth

Economic Cost

Environm-ental Cost

Extensive land use

(Limited land resource)

Pressure

Sprawl Sprawl

Relevant Policies in China

Ministry of Development and Reform CommissionThe Outline of the Eleventh Five-Year Plan for National Economic and Social Development (Chapter 6)(2007)…………

The Ministry of Land and Resources P.R.C.National Land Use Master Plan Outline (1997—2010) …………..

Ministry of Construction P.R.C.Reply to Chongqing’s Master Plan (国函 [2007]90 号 );Reply to Hangzhou’s Master Plan (国函 [2007]19 号 );…………

Stimulating factors

China’s Status Policies Experiences in the World

Urban form developing trend Compact city

A question is proposed What is the existing degree of the compactness in Chinese cities?

Part 2RELEVANT THEORIES

What is the “compact city”? Three defining approaches: Unitary Definition, Composition

Definition and Measurement based Approach

An Image of a compact city

What is the “compact city”? Unitary Definition

high-density or monocentric development (Gordon and Richardson, 1997)

centralized compact development and decentralized compact development (Anderson, 1996)

some concentration of employment and housing, as well as some mixture of land uses (Ewing, 1997)

What is the “compact city”? Composition definition

high density, mix-used city, based on an efficient public transport system and dimensions that encourage walking and cycling (Burton, 2000)

to increase built area and residential population densities; to intensify urban economic, social and cultural activities and to manipulate urban size, form and structure and settlement systems (Burgess, 2000)

What is the “compact city”? Measurement based definition

a compactness index, rho—the ratio between the average distance from home to central business district (CBD), and its counterpart in a hypothesized cylindrical city with equal distribution of development (Bertaud and Malpezzi, 1999)

the degree to which development is clustered and minimizes the amount of land developed in each square mile (Galster, 2001)

Features of Compact city

High-density

Mixed-use

Intensification

Status quo

Changing process

High-density What is urban density?

In the geographical field, density means a theoretical ratio between a quantity of a statistical indicator and the occupied surface (Fouchier, 1994).

Why is high density important to compact city?

High densities are seen to be fundamental to urban vitality and creativity (Haughton and Hunter, 1994)

“take away the high concentration of people and activities, together with the diversity and vitality which go with them, and there is no longer any point living in a city ” (Sherlock, 1991).

Mixed-use What is mixed-use?

a coherent plan with three or more functionally and physically integrated revenue-producing uses (The Urban Land Institute, 1987)

a comprehensive conceptual model, based on the internal texture of a settlement: grain, density and permeability. (Rowley, 1996)

Four dimensions added to Rowley’s conceptual model: the shared premises dimension, horizontal dimension, vertical dimension and time dimension

Dimensions of mixed use

Dimensions of mixed use

Dimensions of mixed use

Dimensions of mixed use

Mixed-useWhy is mixed-use important to compact city?

a fine-grain mixing of diverse uses creates vibrant and successful neighborhoods (Jacobs, 1961) .

Housing White Paper, Our Future Homes (DoE, 1995a) asserts that:

“There is a trend back to mixed use development, providing homes alongside shops and offices. Such development can increase vitality through activity and diversity, help to make areas safer, and help to reduce travel… A balanced mix of households helps ensure sustainable city communities”.

IntensificationWhat is intensification?

a generic term for the process of making cities more compact

an increase in population, an increase in development, and an increase in the mix of uses within the city boundary (Burton, 2000)

Why is intensification important to compact city?

The aims to make city more intensified are reducing the need to travel by car, conserving land and encouraging regeneration of rundown city centers (Burton, 2002)

Source: Coupland,1997 (Originally: Department of the Environment, 1995)

Scales of research on compact city

a macro approach, at the city-wide or even metropolitan level

a micro approach, at the neighborhood or community level

a spatial structure approach, emphasizing a pattern oriented to downtown or the central city versus a polycentric (or dispersed) spatial pattern

Conceptual model

Compact city

High density

Mixed-use

Intensification

Population

Building

Employment

Public transport

Provision of facilities

Land use variety

Housing-job mix

Part 3Empirical Study

Research Design

City Selection

Indicator Selection

Research Method

Output the result

Economic and Social Factors

validity, reliability, availability and plausibility

Principal components analysis

Large Municipal citiesIn Coastal Provinces

Relevant data from statistic yearbooks and modification

Calculation of the score for each feature

Data collection and modification

Collection• China city statistical yearbook 2001,…, 2005 (中国城市统计年鉴 )• China city construction statistical yearbook 2001,…,2005 (中国城市建设年鉴 )• China statistical yearbook 2001,…,2005 (中国统计年鉴 )• Data from The fifth Census in 2000 (五普 ), 1% Population Sample Survey of China in

2005 (2005全国 1%人口抽样调查 )• Local statistical yearbook: Shanghai Statistical Yearbook 2001, 2005• Beijing Statistical Yearbook 2001, 2005• …………………….• Websites of Local statistical information: e.g. http://www.bjstats.gov.cn/ (北京市统计信息

网 ); http://www.stats-sh.gov.cn/2005shtj/index.asp(上海统计 ),......

ModificationPopulation: permanent population(常住人口 ); Household population(户籍人口 )Study range: Urban District(市辖区 )

Measurement of High Density Indicators:

Index IndicatorsPopulation density Persons per unit in built-up areaBuilding density Residential area per personEmployment density Employees per unit in built-up area

Public transport density public transport capacityBuses per 10 thousand persons

Note: The population used in each indicator is the total permanent population in urban districts.Public transport capacity = Passenger Transport Quantity / total permanent population

Measurement of High Density Total Variance Explained

Component

Initial EigenvaluesExtraction Sums of Squared

Loadings

Total% of

VarianceCumulativ

e % Total% of

VarianceCumulativ

e %1 1.979 39.585 39.585 1.979 39.585 39.5852 1.574 31.477 71.062 1.574 31.477 71.0623 .833 16.659 87.721 .833 16.659 87.7214 .518 10.368 98.089 5 .096 1.911 100.000 Equation

Original Score = 1.979 * Fac1_1 + 1.574 * Fac2_1 + 0.833 * Fac3_1

Rank City Score Rank City Score1 Beijing 100 22 Zhenjiang 34.674412 Qingdao 91.43906 23 Yangzhou 33.375583 Xiamen 87.85232 24 Changzhou 33.235244 Dongguan 84.86636 25 Futian 30.118835 Shenzhen 81.53009 26 Jining 23.114026 Guangzhou 81.07312 27 Huizhou 22.427017 Shanghai 74.69369 28 Zibo 19.777648 Fuzhou 68.17303 29 Zaozhuang 19.447989 Nanjing 65.35981 30 Haikou 17.58064

10 Shijiazhuang 60.69593 31 Linyi 16.95725

11 Hangzhou 60.48461 32 Zhanjiang 16.0894112 Taizhou 56.68991 33 Weifang 15.643813 Xuzhou 56.31859 34 Shantou 14.7159314 Ningbo 53.31344 35 Taian 13.9903615 Handan 50.73288 36 Yancheng 13.415816 Jinan 50.55751 37 Jiangmen 11.3141117 Wuxi 45.99586 38 Huaian 10.0420318 Suzhou 42.43381 39 Maoming 8.95139919 Tianjin 41.23116 40 Zhongshan 8.03809520 Yantai 38.75769 41 Foshan 7.08156521 Tangshan 37.7687 42 Suqian 0

Measurement of Mixed-use Indicators:

Index Indicators

Provision of local facilities Numbers of libraries per 10 thousands persons

Numbers of cinemas per 10 thousands persons

Numbers of hospital beds per 10 thousands person

Land use variety Mixed use of different land use

Housing- job mix Housing-job mix index

Note: Land use variety = Land use variety = - Ph * ln(Pr) – Pi * ln(Pi) – Pr * ln(Pr) – Pg * ln(Pg), without unit;The total population employed for calculating the provision of the hospital beds and the theatres are permanent population.The housing-job mix = employees in urban districts / total household population.

Measurement of Mixed-use Total Variance Explained

Component

Initial EigenvaluesExtraction Sums of Squared

Loadings

Total% of

VarianceCumulativ

e % Total% of

VarianceCumulativ

e %1 1.690 33.798 33.798 1.690 33.798 33.7982 1.195 23.910 57.708 1.195 23.910 57.7083 .998 19.958 77.666 .998 19.958 77.6664 .807 16.139 93.805 .807 16.139 93.8055 .310 6.195 100.000 Equation

Original Score = 1.690 * Fac1_2 + 1.195 * Fac2_2 + 0.998 * Fac3_2 + 0. 807 * Fac4_2;

Rank city Score Rank city Score1 Beijing 100 22 Linyi 33.574522 Shanghai 98.17853 23 Yantai 33.220563 Fuzhou 72.9987 24 Ningbo 30.903454 Changzhou 67.73508 25 Jining 28.703325 Xiamen 65.55383 26 Jiangmen 28.5786 Handan 65.35665 27 Tangshan 27.386767 Yangzhou 64.16105 28 Zhongsha

n24.94162

8 Dongguan 57.45616 29 Weifang 24.338019 Guangzhou 55.75936 30 Yancheng 24.1939510 Jinan 52.47121 31 Foshan 23.6959211 Hangzhou 51.31587 32 Haikou 22.482112 Qingdao 50.55949 33 Zibo 21.1379813 Taizhou 48.81618 34 Zhanjiang 18.2709414 Shijiazhuang 48.35458 35 Zaozhuan

g14.16678

15 Nanjing 47.19969 36 Taian 12.0925716 Wuxi 46.78894 37 Futian 6.56649117 Zhenjiang 44.47222 38 Huaian 4.91247918 Huizhou 44.32553 39 Maoming 3.58839119 Tianjin 44.1027 40 Shantou 020 Xuzhou 38.24508 Suqian21 Suzhou 33.8626 Shenzhen

Measurement of Intensification Indicators:

Change of Population Change of persons per ha. in built-up area

Change of Building density Change of Residential area per person

Change of Plot ratio (total construction area/ built-up area)

Change of employment density Change of Employees (secondary industry and tertiary industry) per ha. in built-up area

Change of public transport density Change of buses per 10 thousand persons

Change of provision of local facilities Change of Numbers of libraries per 10 thousands persons

Change of Numbers of cinemas per 10 thousands persons

Change of Numbers of hospital beds per 10 thousands person

Change of land use variety Change of Mixed use of secondary industrial, tertiary industrial and residential land use

Chang of housing – job mix Change of Housing-job mix index

Measurement of Intensification Total Variance Explained

EquationOriginal Score = Fac1_3 * 2.506 + Fac2_3 * 2.416 + Fac3_3 * 1.237 + Fac4_3 * 1.191+ Fac5_3 * 0.952.

Component

Initial EigenvaluesExtraction Sums of Squared

Loadings

Total% of

VarianceCumulativ

e % Total% of

VarianceCumulativ

e %1 2.506 25.061 25.061 2.506 25.061 25.0612 2.416 24.164 49.225 2.416 24.164 49.2253 1.237 12.371 61.596 1.237 12.371 61.5964 1.191 11.911 73.507 1.191 11.911 73.5075 .952 9.523 83.030 .952 9.523 83.0306 .873 8.728 91.758 7 .512 5.118 96.876 8 .207 2.070 98.946 9 .077 .767 99.713 10 .029 .287 100.000

Rank City Score Rank City Score1 Futian 100 22 Xuzhou 41.54 2 Dongguan 88.67 23 Huizhou 41.27 3 Linyi 68.58 24 Tangshan 40.65 4 Shanghai 67.80 25 Wuxi 35.81 5 Zhongshan 67.47 26 Yangzhou 33.71 6 Shijiazhuan

g 62.26 27 Jiangmen 30.67 7 Taizhou 61.92 28 Jinan 30.47 8 Yantai 59.93 29 Suzhou 27.84 9 Guangzhou 58.95 30 Zhenjiang 26.32 10 Xiamen 55.87 31 Zhanjiang 25.31 11 Handan 53.15 32 Ningbo 24.30 12 Qingdao 51.50 33 Yancheng 23.75 13 Weifang 48.69 34 Hangzhou 23.32 14 Beijing 48.12 35 Maoming 20.14 15 Tianjin 46.90 36 Nanjing 11.12 16 Changzhou 46.55 37 Foshan 7.32 17 Zaozhuang 46.44 38 Haikou 4.87 18 Zibo 45.92 39 Huaian 2.61 19 Fuzhou 45.86 40 Suqian 1.40 20 Taian 44.82 41 Shantou 0.00 21 Jining 42.89 Shenzhen

The high scores of each feature would have a balanced series of variables.

Beijing, Xiamen, Shanghai, Fuzhou, Guangzhou, Dongguan rank in top 10 both in the density degree and mixed-use degree; Shantou, Taian, Huaian, Maoming, Foshan, rank in the last 10 both in the density degree and mixed-use degree.

There is not an obvious relationship between the descriptive features(high density and mixed-use) and the changing process variable (intensification).

Conclusion

The compact city paradigm is the developing trend of Chinese cities.

Set up a conceptual model of the compact city at large scale municipal cities in China, as well as the indicator system for measuring the degree of the compactness of large cities

Give a brief description of the existing degree of the compactness of the large municipal cities in coastal provinces

Thank you!Questions and Comments are welcome!