garden cities theory
TRANSCRIPT
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Ecological Modelling 289 (2014) 2635
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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
0304-3800/ 2014 Elsevier B.V. All rightsreserved.
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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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Z. Yuan et al. / Ecological Modelling 289 (2014) 2635 33
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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34 Z. Yuan et al. / Ecological Modelling 289 (2014) 2635
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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