garden cities theory

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Ecological Modelling 289 (2014) 2635

Contents lists available at ScienceDirect

Ecological Modelling

journa l homepage: www.elsevier .com/ locate /ecolmodel

From design to digital model: A quantitative analysis approach toGarden Cities theory

Zhiyuan Yuan a, Xinqi Zheng b,, Lina Lv a, Chunlu Xue a

a School of Land Science andTechnology, China University of Geoscience, Beijing 100083, Chinab Schoolof Information Engineering, China University of Geoscience, Beijing 100083, China

a r t i c l e i n f o

Article history:

Received 4 March 2014Received in revised form 22 June 2014

Accepted 23 June 2014

Available online 11 July 2014

Keywords:

Garden City

Digital city modeling

Geographic information system (GIS)

Comparative analysis

Land use structure

Open green space accessibility

a b s t r a c t

As a complementto the development ofnew theories, the reevaluation and knowledge mining ofclassical

theories can be beneficial for urban development. In particular, quantitative analyses for cities can now

take advantage of geographic information systems (GIS). Proposed more than one hundred years ago,

Ebenezer Howards Garden City is a generally acknowledged classical urban theory. On the basis ofthe

original work, we model a digital Garden City in ArcGIS. The model is accurate to within 1% for both areal

and length measures, and enables our further quantitative evaluation of the urban land-use structure

and open green space accessibility. We then compare the classical theory with a modern-built area for

the quantitative evaluation results. Zhujiajiao Town in Shanghai, winner ofthe International Award for

Livable Communities in 2008, provides a reference. Although the central areas ofGarden City and Zhu-

jiajiao Town have different geographical and historical backgrounds, the measured land-use structures,

including indicators ofarea proportion and area per capita, exhibits similarities on land-use types ofres-

idential, transportation, and ecological conservation, which offer a considerable reference for land-use

structure ofa livable urban area. Comparison ofthe accessibility to open green spaces in both cities shows

that the average access time from a residential area to open green space in Garden City is just 186.77 s,

which is much shorter than that in Zhujiajiao. Our research shows that the classical Garden City theory

can be modeled into highly accurate digital forms, allowing richer information in quantitative terms to be

obtained than from the original theory, and enabling comparisons with modern cities. Besides, the pro-posed digital modeling approach is widely applicable to classical theories and historical planning cases.

2014 Elsevier B.V. All rights reserved.

1. Introduction

In 1898, Ebenezer Howardproposed the GardenCity in his book

To-morrow: A Peaceful Path to Real Reform, which has been widely

known through subsequent editions named Garden Cities of To-

morrow. The Garden City is characterized as a living space that

combines the advantages of urban and rural life, with a social city

designedto overcome further increasesin population afterthe limit

of the Garden City is reached (Howard, 1898, 1902). The theory, its

practical applications in Letchworth (Miller, 1989; Purdom, 1963)

andWelwyn(Reiss, 1920), andthe resultingworldwideGarden City

movement (Jin, 2007; Ward, 1992) have all been extensively stud-

ied.For example, the theory has beenrecognized as the cornerstone

of modernurbanplanning (Alexander, 1992; Buder, 1969). Further,

Correspondingauthorat: No.29, XueyuanRoad, Haidian District,Beijing100083,

China. Tel.: +86 13401184568; fax: +86 1082321807.

E-mail address: [email protected] (X. Zheng).

the idea of the towncountry magnet has caused general debate

(Clark, 2003; Mumford, 1961), and the changes in residential living

conditions have also been discussed (Edwards, 1913; Reade, 1913).

Bottlenecks in the progress of urbanization, such as traf-

fic congestion, environmental pollution, and urban smog, have

encouraged people to explore new solutions. The development of

further studies on classical theories and historical urban planning

cases for modern practice can be an effective means of finding

new solutions. Therefore, it is sensible to study Garden City the-

ory more in-depth. However, a survey of studies on Garden Cities

over the past 100 years suggests that Howards theory has only

been considered qualitatively. That is, researchers have attempted

to understand and discuss Howards idea by analyzing the text and

accompanying diagrams in the original work, while an accurate

analysis of the theorys physical characteristics (layout, land-use

structure, per capita indicators, etc.) has not been researched.

In recent decades, geographic information system (GIS) technol-

ogy has been widely used in urban planning. The advantages

of spatial-data organization, management, and especially spatial

http://dx.doi.org/10.1016/j.ecolmodel.2014.06.015

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Z. Yuan et al. / Ecological Modelling 289 (2014) 2635 27

analysis, make GIS particularly suitable for complicated calcula-

tions (Fotheringham and Rogerson, 1994; Matejcek et al., 2006).

The application of GIS in urban planning generally falls into one

of the two categories. The first assists with the visual presentation

and quick editing of planning schemes (Beregovskih et al., 2010;

Malczewski, 2004), andthe secondsupports urban modeling, anal-

ysis, and prediction for real cities (Jiang and Yao, 2010). Both are

implemented in modern cities in the real world. Even the leading

studies of smartcities focuson the visual representationand simple

analysis of real cities (Al-Hader and Rodzi,2009). However, model-

ing classical and historical theories or cases is a challenge, because

we have only incomplete data, inaccurate diagrams, and poorly

organized descriptions. The archeological mining of these classi-

cal theories based on GIS, although rarely reported, can provide

considerable benefits to modern urban planning.

Ongoing studies of urban spatial analysis are mainly focused

on open-space accessibility (Geurs and van Wee, 2004; Tsou et al.,

2005), landscape pattern measurement (Herold et al., 2002; Kong

and Nakagoshi, 2006; Seto and Fragkias, 2005), complex trans-

portation network analysis (Brockmann and Helbing,2013; Crucitti

et al., 2006), and energy metabolism and sustainability (Hall, 2011;

Yang et al., 2014; Zhang et al., 2014). Since the 1950s, accessibility

has been an important indicator for the urban green-space distri-

bution (Van Herzele and Wiedemann, 2003). Accessibility can bemeasured by various methods, such as the buffer zone, minimum

distance, travel impedance, andgravityindex (Luo andWang, 2003;

Oh and Jeong, 2007; Talen and Anselin, 1998). Modern-built cities

are generally the basis of these studies, andthe analysis of classical

and historical theories or cases is rare.

Therefore, our study considers the following three questions.

First, is there a reliable modeling procedure for those classical

urban theories presented in texts and diagrams but only available

on papery material? If so, what are the differences between the

modelingprocedure for cities in classical theories andmodern soci-

ety? Second, is the urban land-use structure comparable in cities

or towns with different geographical and historical backgrounds?

Will the land-use structure designed by Howard be similar to that

in modern cities? Third, as the pioneer of urban planning, Howardtried to solve the environmental problems of urbanization with a

spatial allocation of opengreen spaces. Thus,what are the quantita-

tive results of judging his planning scheme through an open green

space accessibility analysis? In theremainder of this paper, we first

reorganize the data and diagrams in Howards original work, and

model a highly accurate digital Garden City using the ArcGIS soft-

ware. We then quantitatively analyze Howards theory in terms of

a land-use structure calculation and an open green space accessi-

bilitymeasurementon the basis of the digital model. Finally, taking

Zhujiajiao Town as a reference, we apply the urban modeling pro-

cedure of modern cities, and analyze the results with the same

land-use structure calculation and open green space accessibility

measurement procedure used for the Garden City. We then con-

trast the modeling procedure for classical theories with that formodern cities, and compare the land-use structure and open green

space accessibility of Howards Garden City with that of modern

Zhujiajiao Town.

2. Method

2.1. Modeling classical theory

The modeling procedure provides the foundation for further

quantitative study. We have previously attempted to model a dig-

ital Garden City (Yuan et al., 2013a). Further improvements and

repeated experiments have enabled us to identify the main mod-

eling process for a digital Garden City, and this procedure is also

suitable for other classical theories expressed by a literal descrip-

tion and schematic pictures. The modeling process consists of

an analysis of the original theory, the selection of an appropri-

ate mathematical foundation, data extraction and calculation, the

systematic organization and design of an attribute structure, vec-

torization and digitization, verification of the model accuracy, and

(if necessary) corrections to the model (see Fig. 1).

2.1.1. Original theory analysis

Analyzing the original theory ensures that the natural idea

and characteristics are understood and accurately reflected in the

model. The analysis is also important for the data calculations and

framework design, which are strongly influenced by the informa-

tion in the original work.

The modeling process of a digital Garden City offers a specific

example. The analysis of Howards original theory helps us under-

stand what should and can be present and calculated in its digital

form, and thus determine the extent and object of the model. The

Garden City is part of a citygroup named the social city. Eachsocial

city includes several separate urban areas (one central city encir-

cled by several Garden Cities), agricultural areas in the intervals

between cities, and transportation systems of highways and rail-

roads connecting each urban area. The most detailed part of the

theory concerns the urban area of the Garden City, and this is themost important part of our study on urban planning. Thus, we con-

sider the models extent to be the entire social city, and focus on

the central area of a single Garden City.

2.1.2. Mathematical foundation selection

Being ideal, the cities in classical theories are usually designed

without spatial reference. Therefore, it is necessary to select a

mathematical foundation that includes a suitable spatial coordi-

nate system, a mapprojection thatminimizes deformation,modern

international units, and a scale that is appropriate to the size of the

modeled city.

Because of theideal andhypothetical characteristics of thesocial

city, the mathematical foundation of a digital Garden City model

need not consider the citys geographical location. Therefore, webuild a new projection coordinate system called garden city. To

minimize the deformation of the model, we use the Aitoff projec-

tion because of the round shape of the social city and the Garden

Cities. The false easting, false northing, and central meridian are all

set to 0 because of the theorys idealistic construction. The model

uses length units of meters. The geographic coordinate system of

the garden city projection coordinates is GCS Beijing 1954 with

Greenwich as the prime meridian, D Beijing 1954 as the datum,

and Krasovsky 1940 as the spheroid.

2.1.3. Data preparation

The data in theories are usually scattered, incomplete, or hid-

den within text and diagrams. Data preparation aims to form a

systematic, complete, and accurate data list through data extrac-tion and calculation (see Fig. 2). Extracting the core points of a

theory can make the data more systematic. The main references

for this step are the data given in the text, urban layouts shown

in diagrams, and geometric formulae. In some cases, data cannot

be calculated because of deficiencies in the original work. Thus,

it is necessary to add one or more assumptions to the authors

design. These assumptions should be reasonable and reliable, and

be related tothe geometricfeatures of modelingobjects,suchas the

lengthand width of roads,area of parks,and so on. Both exact num-

bers and numerical relations can be assumed. Some assumptions

may prove to be false, whereasothers maybefoundtobepoorwhen

compared to other calculation results. Such assumptions should be

abandoned or corrected. After comparing and adjusting, the final

datalistshouldbebasedonasinglebestassumption,orthegroupof


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28 Z. Yuan et al. / Ecological Modelling 289 (2014) 2635

Fig. 1. Modeling procedure for classical urban theories.

assumptions that provide optimal results. The comparison of mod-

els formed under different assumptions might offer further insight

into the development of cities.

For the data preparation step in the modeling of digital Garden

City, all original data are extracted from the original work. Then,

the corepoint system is confirmedpreciselyaccordingto the center

points of the central city and six Garden Cities in the concentric-

circle layout of Howards design. The calculation is performed in

the following sequence: (1) urban boundaries of the central city

and Garden Cities; (2) inner and outer radii of the rings of the cen-

tral garden, the whole town, the factories and warehouses, and

the circular railway; (3) inner and outer radii of Grand Avenue;

Corepointssystem Modeling object

Modeling object A Modeling objectB1 Modeling objectB2 Modeling objectB3

Core point

A

Core point B 1 Core point B 2 Core point B 3

Text descripon & Data

Diagram pictures

Certaindata

Uncertaindata Assumpon

Xi

Calculangresult Ri

Geometric formula

Validassumpon

Invalidassumpon

Review&Contrast& Analysis

Sasfied Data discrepancy or

against common sense

Correconor

adjustment

Opmalresults Rm

Comparison

Calculaon results RA

Geometric formula

Calculaon results RB1 Calculaon results RB2 Calculaon results RB3

Data list (based on assumpon groups Xm)

Fig. 2. Detailed data preparation procedure.


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(4) road (referring to radial roads connecting outer border of the

Grand Avenue and the boundary of central urban area) widths; (5)

widths of residential rings and avenues; and (6) inner and outer

radii of the Crystal Palace, central park, and the ring of large public

buildings. The calculation is based on the four following assump-

tions: (1) the four residential rings are of equal width; (2) the 2nd,

4th, and 5th avenues have the same widths as the road, because

they have the same urban function (can be regarded as roads divid-

ing two adjacent residential patches); (3) the area of the factory

and warehouse rings in the original work does not include area of

these roads between adjacent patches; (4) the ring of large public

buildings and the Crystal Palace are of equal width (referring to the

difference between inner and outer radii of the ring).

2.1.4. Systematic organization and attribute structure design

The model framework design must consider the available data,

the feasibility of vectorization in a GIS software, and further

research intentions. Each item in the model should be represented

in feature files. Generally, point features areused to denotecritical

points in the model, which determine the positions of objects, and

attributes of point features should include location, coordinate,

and governmental authority. The central lines of roads, outer con-

tours of buildings, and park walls are signified by the line feature,

and attributes should include the serial number, length, function,etc. Thepolygon features representareasor regions of pavements,

buildings, and parks, and its major attributes include area,land-use

type, and so on.

The data framework and structure of the digital Garden City

model includes two levels. One is the social city, including the

central city, the Garden Cities, agricultural land, and the transporta-

tion systems linking the central city and Garden Cities. The other

is the urban area of a Garden City, which is reorganized accord-

ing to land-use details, i.e., buildings (including boundaries and

patches of building areas for residential, public, and factorial use),

urban transportation system (including central lines, boundaries

and patches for boulevards, avenues, streets and roads, and patches

of their intersections), and greenspaces (including cut-off linesand

patches of green belts, and boundaries and patches of open greenspaces).

2.1.5. Vectorization and digitization

Vectorization is implemented in the GIS software. The process

follows a specific spatial sequence: (1) core points, (2) other control

points, (3) polylines, (4) topologycheck and correction of polylines,

(5) polygons, and (6) topology check and correction of polygons.

For the modeling process of the Garden City, vectorization is

implemented in ArcGIS 10.0. All geometric data is precise to three

decimal places. The most time-consuming part is the segmentation

and extraction ofthe road network andgreen beltsin the urbanarea

of a GardenCity. Further,the topology is built and checked after the

vectorization process.

2.1.6. Accuracy verification and correction

The model accuracy is controlled by comparing the data list

extracted from the theory with the corresponding measurement

results from the digital model in the GIS. If the relative error of

certain parts is unsatisfactory, the items causing the error should

be recalculated, and the entire model should be adjusted or rebuilt

according to the location or calculation sequence of these items.

The model can be accepted and used for further analysis when the

relative errors of all parts and the entire model are small enoughto

accurately reflect the relevant theory.

In modeling the Garden City, the relative errors are calculated

by comparingthe datasets obtained from theoriginalwork andthe

digital model. We calculate the relative error of each item men-

tioned in the original work, and summarize the average relative

errors of the length measurements, arealmeasurements, and count

measurements. The final digital model and accuracy calculation

results are given in Section 3.1.

2.2. Measurement of open green space

On the basis of the digital model, we quantitatively measure

the Garden Citys open green space as the proportion of the whole

central urban area and the open green space area per capita, and

study the accessibility in terms of travel impedance.

The accessibility analysis measures the shortest distance from a

starting point (only residential areas are considered in this study)

to the destination area (i.e., the open green space). If we regard

the travel impedance distribution as homogeneous and undiffer-

entiated in the city, the shortest distance should be the length of

a straight line connecting the starting point and destination area.

However, factors such as the land-use type, population distribu-

tion, and traffic network affect travel impedance. Various routes

connecting the starting point and destination area are therefore

considered, and that one with the minimum travel impedance

is selected and used to confirm the corresponding accessibility

between the starting point and destination area.

In this study, we use the access time of the route with the min-

imum travel impedance to represent the accessibility. The betterthe accessibility, the lower the minimum accumulated impedance,

andthus the shorter the access time. We divide the entire area into

cells (i.e., rasterization), and value each of them according to the

impedance per unit distance. For a given walking speed, the time

required to move diagonally through each cell can be calculated.

Then, the total access time for each possible route linking the start-

ing cell to the identified destination areas is easily obtained, and

the accessibility can be confirmed by comparing the access times

of all possible routes. The necessary calculations and comparison

can be performed by the spatial analyst tool in ArcGIS. The spe-

cificsteps are as follows (VanHerzele andWiedemann, 2003; Zhou

et al., 2008):

(1) For each factor affecting travel impedance (e.g., land-use type,population distribution, traffic network), determine the rela-

tive travel impedance under every condition and the weight of

each factor. Differences caused by the means of transportation

androad grades should be taken into account. In our accessibil-

ity analysis, the land-use type is the only factor affecting travel

impedance in the digital Garden City. This is because the pop-

ulation distribution is missing from the original work, and the

effectof allthe roads canbe reflected by regarding their patches

as a land-use type. The categories and corresponding relative

impedances of land-usetypes are determined on thebasis of the

land-use conditions and a summary of similar research cases in

China (Guo et al., 2012; Hu et al., 2005; Li et al., 2008; Yin and

Kong, 2006; Yu et al., 1999; Zhou et al., 2008; Zhou and Guo,

2003) (Table 1).(2) Add attribute fields of factors affecting travel impedance in the

digital model vector file and insert corresponding attributes to

eachpatch.The impedance attributeof the patches in the vector

file canthen be obtainedby a weighted-sumcalculation, i.e.,the

sum of three products multiplying the travel impedance value

under the specific condition of each factor and the associated

weight. In the digital Garden City, the impedance of each patch

depends on its land-use type.

(3) Set the transportation means for access and basic travel

speed, and assign travel speeds to patches according to their

impedance. Travel speed is a representation of impedance

that combines all affecting factors and transportation means.

Because of the urban size and centralized planning of the Gar-

den City, we only consider walking, and set a basic walking


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Table 1

Relative travel impedanceof different land-use types forwalking in GardenCity.

Land-use types Physical items Relative travel impedance

Roads Boulevards, avenues, streets, roads, and their green belts 1

Residential areas Four residential rings 3

Open green space Central garden, central park, and the grand avenue 4

Administrative areas Administrative ring, schools, and churches 5

Commercial- and industrial-related areas Crystal palace, industrial ring 100

speed of 1m/s according to the general setting ranges in traf-

fic engineering (Oh and Jeong, 2007), regardless of the impact

of different road grades on the travel cost. The relative travel

speed is numerically equal to the travel impedance when the

walking speed on a road is 1m/s.

(4) Select the physical categories of open green space according to

the original theory, and extract them as a single vector file. This

is the source data for the cost distance. The open green space in

the Garden City is composed of the central garden, the central

park, and the grand avenue.

(5) Convert the polygon data to raster data with the conversion

tools in ArcGIS. Recheck the attribute representing impedance

conditions, namely the travel speed, of each cell. In the digital

Garden City, we use a cell size of 10m10m for rasterization.

(6) Extract the study area (in this study, the residential areas) as

a single polygon layer. This layer should be selected as the

processing extent in the environment settingsin theArcGIS tool

of cost distance. The four residential rings in the digital Garden

City are considered to be study areas.

(7) Calculate the minimum distance (measured in accumulated

access time) of each cell in the study area to the open green

space using the cost distance tool in ArcGIS, and output the

distance raster (the distance is measured by access time). The

whole calculation and comparison process can be performed by

the ArcGIS software.

(8) Classify all cells in the output raster of step (7) according to

travel time. The intervals canbe determined autonomously.The

classification map can be obtained in the software by setting

the intervals in the classification label of the files properties.Statistics on the area and proportion of each accessibility class

can also be computed with the spatial analysis tool of ArcGIS.

This allows the accessibility distribution in the study area to be

plotted. In thedigital GardenCity,we select300 s (5min) as the

interval, considering the results of step (7). The equal interval

classification map and statistics with a class interval of 5min

walking time are shown in Section 3.2.2.

3. Results

3.1. Digital Garden City

3.1.1. Interface of the digital model

Through the modeling process described in Section 2.1, we suc-

cessfully transformed Howards Garden City theory into a digital

model (see Fig. 3). This digital form is equipped with systematic

organization and structured attributes, and enables quantitative

measurements and calculations.

3.1.2. Accuracy verification

We calculate the relative errors by comparing two datasets, one

extracted from the original work and the other measured from

the digital model (Table 2). The results confirm that the digital

model is fit for further analysis, with an average relative error of

0.90% for the areal measures, 0.57% for the length measures, and

0 for the count measures. The maximum errors occur for the total

area of the gardens and the total road length (measured along the

centreline), and are 5.57% and 3.65%, respectively. Considering the

high accuracy of the individual parts and the entire model, we con-

clude that this model is accurate enough for further analysis.

3.2. Measurement of open green space in the digital Garden City

3.2.1. Summary statistics for open green space

The results from the verified model show that the total area of

open green space is 1422763.01m2, which is 35.16% of the total

urban area. The area per capita, according to the population of

30,000 set by Howard, is 47.43 m2.

3.2.2. Accessibility analysis of open green space

The statistics show that the shortest walking time from a resi-dential area tothe open greenspace is zero (for residentslivingnext

door to an open green space). Residents living in the farthest areas

have a travel time of 520s (82/3 min), and the average access time

is 186.77s (about 3 min). The standard deviation of access time for

the entire area is 86.24 s.

Using a classification interval of 300s (5min), Fig. 4 shows a

thematic map of the spatial variation in accessibility. Most people

in the study area can access open space within 300s, whereas parts

of theinnermost andoutermost rings haveaccesstimes in therange

300520 s. According to statistics of spatial analysis tool in ArcGIS,

some 14725 cells are within 0300 s, accounting for 89.10% of the

four residential rings. Only 1747 (10.90%) cells have access times

greater than 300s. Therefore, residents of the Garden City enjoy

fairly good spatial accessibility.

4. Discussion

Zhujiajiao Town in Shanghai won the International Award

for Livable Communities in 2008 (silver award for category B,

which is aimed at populations of 20,00075,000) (United Nations

Environment Programme, 2008). Therefore, we consider it a realis-

tic reference for the digital Garden City model and its calculated

accessibility given its population and urban characteristics. We

modeled Zhujiajiaos township applying regular urban modeling

procedure of modern cities in GIS, and analyzed its accessibility

statistics in accordance with the process forthe digital GardenCity.

The base map for the digitization is a regulatory land-use plan-

ningmap. Boththe textof Zhujiajiaos Regulatory DetailedPlanning(20012020) and remote sensing image data obtained from Google

Earth were used as references.

4.1. Comparison of the modeling of classical theories and real

cities

By comparing the modeling process of the Garden City the-

ory and Zhujiajiaos township, we can identify several differences

between urban modeling in classical theories and the modern

world, especially in terms of the modeling foundation and empha-

sis, factors affecting model accuracy, and the requirements of

modelers (Table 3).

In addition, models based on theories may be limited because

the data needed has not been explicitly presented in the original


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Fig. 3. From sketches (inHowards original work) to digital GardenCity (in ArcGIS 10).

work. For example, Howard did not set the population distribution

or house heights forhis GardenCity.Thereare also some incompat-

ibilities between theoretical and real cities in terms of the different

historical backgrounds. Thus, some land-use types do not exist in

Garden City, such as multiple public utilities, and some land-use

designs are no longer suitable for modern cities, such as ring-shaped traffic systems which were designed for gharries but are

not suitable for cars. However, these non-existent land-use types

and unsuitable designs provide wide scope for city-related studies.

4.2. Similarity of land-use structures between Garden City and

Zhujiajiao

There are differences between the geographical and historical

backgrounds of Garden Citys urbanarea and Zhujiajiaos township.

However, there are also similarities, as can be demonstrated by

land-use conditions for several urban functions. We divided land-

use types of Garden Citys urban area and Zhujiajiaos township

based on land-use type division in Code for Classification of Urban

Land Use and the Planning Standards of the Development Land

(Ministry of Housing and Urban-Rural Development of the Peoples

Republic of China, 2011) and corresponding urban functions. Area

proportionand per capita indicators for land-usestructure arecom-

pared (Table 4).

The residential, transportation, and ecology land-use types are

quite similar in both proportion and area per capita. The ecolog-ical land uses are mainly green space and water. Without water

design, the proportion of green space in Garden City is equal to

the sum of the water and green space in Zhujiajiao. The compari-

son of land-use types for other functions shows large differences.

For example, Garden City lacks public utilities, whereas Zhujiajiao

has no industrial and warehousing areas, which cause differences

in the land-use regions of multiple utilities, industrial areas, and

logistics and warehouses. As Zhujiajiaos central industry, leisure

tourism accounts for a larger proportion of commercial use than

the Crystal Palace in Garden City. The difference in administra-

tion and public services is partly caused by the number of sites

of cultural relics in Zhujiajiao, with the enhancement and devel-

opment of government during the past 100 years also playing a

role.


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Table 2

Accuracy verification of digital Garden City model.

Physical item Detail Data from original

work

Converted data

from original work

Measured data in

digital model

Relative

error (%)

Built area Area (round) 1000 acres 4046856.42 m2 4046375.77m2 0.01

Length (radius) 1240 yards

(approx. 3/4 miles)

1133.86

(1207.01)m

1134.87 m 0.09

Boulevards Length (width) 120 feet 36.58 m 36.58 m 0.00

Central garden Area (round) 5.5 acres 22257.71 m2 22223.04 m2 0.16

Central park Area (ring) 145 acres 586794.18 m2 586537.98 m2 0.04

Crystal Palace Length (farthest distance to

residents)

600 yards 548.64 m 548.81 m 0.03

Residential area Area (average area) 20 feet130 feet 6.10 m39.62 m Not expressed

Count 5500 5500 Not expressed

Area (the smallest area) 20 feet100 feet 6.10 m30.48 m Not expressed

Count (residential population) 30,000 30,000 Not expressed

Grand avenue Length (width) 420 feet 128.02 m 128.05 m 0.02

Length (green belts length) 3 miles 4828.03 m 4827.73 m 0.01

Area (ring) 115 acres 465388.49 m2 465330.97 m2 0.01

Length (farthest distance to

residents)

240 yards 219.46 m 201.46 m 0.00

School Area (total) 4 acres 16187.43 m2 16187.44 m2 0.00

Count 6 6 6 0.00

Gardens Area (total) 250 acres 1011714.11 m2 1068058.05m2 5.57

Warehouses, factories, and markets Area (total) 82 acres 331842.23 m2 333530.21 m2 0.51

Ring railway Length (perimeter) 4.5 miles 7242.05 m 7186.66 m 0.76

Roads Length (total) 25 miles 40233.60 m 38763.32 m 3.65

Areaaverage relative error 0.90

Lengthaverage relative error 0.57

Countaverage relative error 0.00

As a well-recognized modern garden city, the land-use structure

of Zhujiajiao reveals the demand of citizens for a livable and green

urban environmentto some extent. Thesimilarity in theland useof

Garden Citys urban area and Zhujiajiaos township demonstrates

that Howards Garden City is livable and green, under a suitable

land-use structureand area percapita,eventhough it wasdesigned

more than 100 years ago.

4.3. Comparison of open green space accessibility in Garden City

and Zhujiajiaos township

4.3.1. Accessibility analysis of Zhujiajiaos open green space

The open green space in Zhujiajiaos township mainly con-

sists of parks, squares, and structured green areas. We applied

the relative travel impedance of Garden City, adding a relative

Fig. 4. Classification map from the residential area to theopen green space (interval: 300s) of GardenCitys urban area.


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Table 3

Comparison of modeling processesof classical theories and real cities.

Items Modeling cities in classical theories Modeling real modern cities

Modeling foundation Data list extracted from the text and diagrams Planning scheme or interpretation of the remote sensing

image data

Modeling e mphasis Systematic u nderstanding a nd p resentation o f the i deal

scattered original work (predictivestudies are rare

because of a lack of reality and spatiotemporal variation)

Prediction and spatiotemporal studies

Model accuracy Mostly controlled by data extraction and calculation,

accumulated errors mainly caused by contradictionshiddenin the original work or proposed assumptions,

careless geometric calculations, and data loss during

vectorization

Depends on themethods used in data transformation and

theinterpretation of image data, errorscaused by aerialphoto techniques and interpretation

Req uirem ent s o f m odelers Capable o f unde rs tanding t he e nt ir e t heo ry s ys tematically

and recognizing the calculation sequence effectively

because of theimplicit spatial logic

Do not need to deal with the implicit spatial logic

Table 4

Comparison of land-use structures in GardenCitys urban area and Zhujiajiaos township.

Codes Land-use types Area/m2 Proportion/% Area per capita/m2

Garden City Zhujiajiao Garden City Zhujiajiao Garden City Zhujiajiao

R Residential 1553438.46 3769343.51 38.39 39.77 51.78 58.44

A Administration and public services 100275.25 510744.65 2.48 5.39 3.34 7.92

B Commercial and business facilities 39200.25 853025.25 0.97 9.00 1.31 13.23

M Industrial 271246.95 0.00 6.7 0.00 9.04 0.00W Logistics and warehouse 24658.07 0.00 0.61 0.00 0.82 0.00

S Street and transportation 634800.39 1395792.39 15.69 14.73 21.16 21.64

U Municipal utilities 0 27758.96 0 0.29 0.00 0.43

G Green space 1422763.01 1428706.99 35.16 15.07 47.43 22.15

E Water 0 1493151.31 0 15.75 0.00 23.15

Total area 4046382.38 9478523.06 100 100 134.88 134.88

Table 5

Relative travel impedanceof different land-use types forwalking in Zhujiajiao.

Land-use types Physical items Relative travel

impedance

Roads Streets and roads 1

Residential areas First class residential, second class residential, traditional residential, and parking

lots

3

Open green space Green area for environmental protection, structured green area, parks, and squares 4Administrative a reas Administrative a reas, p ublic u tilities, e ducation a reas, a nd c ultural-relic s ites 5

Commercial- and industrial-relatedareas Leisure facilities, commercialareas, commercial-residentialcomplex, tourism

featured business, external traffic areas, and municipal public utilities

100

Water Water 999

impedance of 999 for water to represent the difficulty of walk-

ing via water (Guo et al., 2012; Hu et al., 2005; Li et al., 2008)

(Table 5). Commercialresidential complexes were grouped into

commercial- and industrial-related areas, which have higher travel

impedances than residential areas.

According to our calculations, the shortest travel time from a

residential area to an open green space is again zero, whereas

the longest walking time is 219337.55s (approximately 365min).

This is much longer than the maximum travel time in Garden

City (520s). The average access time in Zhujiajiaos township is

1038.04 s (approximately 17min), which is not long but still large

compared with Garden City. The standard deviation of the access

time over Zhujiajiaos entire residential area is 2522.37s. Clas-

sification of the residential area based on a 300-s time interval

shows that most residents can easily access open green space, but

some areas (such as the southwest corner) have poor accessibility

(Fig. 5).

4.3.2. Comparison of the accessibility of open green space

We compared the statistical results of a spatial analysis of the

two cities (Table 6). The results indicate that residents of Zhujiajiao

have good accessibility to open green space, with nearly half of the

residential area located within 300s. However, the accessibility is

still lower than inGarden City. Only77.98% of theresidentialareain

Zhujiajiaos township has access to open green space within 600s,

and 8.91% of the area is more than 1800s (30min) away from an

opengreen space. Despite theworldwide recognitionof Zhujiajiaos

green spaces, the planning and distribution of Garden Citys open

green space is superior in terms of its accessibility.

Table 6

Comparison of access-time interval proportions on open green space accessibility

in Garden Citysurban area and Zhujiajiaos township.

Time intervals/s Area proportion

Garden City (%) Zhujiajiao (%)

0300 89.10 42.69

300600 10.90 35.29

600900 10.74

9001200 1.78

12001500 0.19

15001800 0.40

1800 8.91

Sum 100.00 100.00


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Fig. 5. Classification map from theresidential area to the open green space (interval: 300s) of Zhujiajiaos township.

5. Conclusion

In this study, we built an accurate digital Garden City model

in ArcGIS. The modeling procedure consists of an analysis of the

original theory, the selection of an appropriate mathematical foun-

dation, dataextraction and calculation, the systematic organization

and design of an attribute structure, vectorization and digitization,

verification of the model accuracy, and corrections to the model.

Further quantitative studies on land-use structures and open green

space accessibilitywere conducted on the basisof the digital model.Using the officially recognized garden city of Zhujiajiaos township

as a reference, we showed that Howards Garden City has a similar

land-use structure for residential, transportation, and ecology, and

superior open green space planning. Our research expresses a new

perspective for modelingand quantifyingclassical theory using GIS,

and reveals the great value of the digitization of classical theories

into models. The processes of data presentation and system design

help us understand the theories in a clearer and more systematic

way. In addition, characteristics that have been missed in previous

qualitative analyses can be elicited by quantitative calculations and

spatial analysis. Classical theories such as Garden City and other

historical planning cases presented in text and diagrams can be

restudied with the methods and creative perspectives promoted in

this research.Our studyfirst systematically discussed the distinctions and dif-

ficulties of modeling processes in classical theories and real cities,

and then proposed a complete modeling procedure for classical

theories. According to the urban functions of land-use types, we

discovered similarities between the residential, transportation, and

ecology land-use types, as wellas distinctions between administra-

tive and public services, in Garden City and Zhujiajiao. The study

also measured accessibility to open spaces, and demonstrated that

all residents in Garden City can walk to open green space within

9 min, which is much less than the maximum access time in Zhuji-

ajiao. In future work, we will conduct further calculations with the

digital model (Yuan et al., 2013b), compare more cities from across

the world, and improve the model with regard to standardization,

openness, and non-exclusivity.

Acknowledgements

This study wassupported by the National Natural Science Foun-

dation of China under Grant (No. 40571119). We would like to

express our gratitude to the editors at Editage for polishing the

text and providing useful comments on this manuscript.

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