The effect of urban growth on commuting patterns in Christchurch, New Zealand

Journal of Transport Geography 14 (2006) 342–354 www.elsevier.com/locate/jtrangeo

The eVect of urban growth on commuting patterns in Christchurch, New Zealand Nick Buchanan

a,¤

, Ross Barnett b, Simon Kingham b, Doug Johnston

b

a

b

GHD Pty Ltd, 10 Bond Street, Sydney NSW 2000, Australia Department of Geography, University of Canterbury, Christchurch, New Zealand

Abstract The rising demand for residential development in the urban fringe of Christchurch, New Zealand, has led to an increase in car use and lengthening journeys, both of which have serious environmental implications. In light of this, the relationship between urban form and transport was investigated in Christchurch through the analysis of journey to work data from 1991 and 2001. Low density suburban areas were found to generate and receive the highest percentages of car trips in both 1991 and 2001. It was also found that the majority of worktrips involved suburb-to-suburb commuting, rather than to the centre of the city. Average trip length did not increase substantially over this period, although increases were apparent in separate modes. Multivariate regression analysis established that the key variable determining modal split and trip length was the distance the residence was located from the central business district. Results were similar when compared to larger cities elsewhere. © 2005 Published by Elsevier Ltd. Keywords: Urban growth; Commuting patterns; Christchurch; New Zealand

1. Introduction Over the last 15 years the international debate on urban sustainability has rapidly accelerated. A key component of this has been the relationship between urban form and transport. One of the main arguments has centred on the size and shape of cities and how these aVect daily activities. The recent debate has focused on the issue of a sustainable city size: should the city be allowed to become dispersed, as has been happening through decentralisation, or should cities become more compact? At present, the compact city discourse has taken precedence over one based around dispersion, urban sprawl, and relative inactivity, due to increasing environmental and social problems (Burton, 2000). Higher densities, less car use and other beneWts have led scholars to praise the positives of a compact city (Cervero, 1998; Duany et al., 2000; Thomas and Cousins, 1996; *

Corresponding author. Tel.: +61 2 9239 733. E-mail addresses: [email protected], nickbuchanan26@ yahoo.co.nz (N. Buchanan). 0966-6923/$ - see front matter © 2005 Published by Elsevier Ltd. doi:10.1016/j.jtrangeo.2005.10.008

Williams et al., 1996). These beneWts primarily function around urban processes that concentrate development, reduce the need to travel and result in a reduced environmental impact. Conversely, several negative points have also been argued that can result from urban consolidation; these are based around overcrowding, loss of urban quality and increased congestion and pollution (Breheny, 1997; Burton et al., 1996; Jarvis, 2003; Jenks et al., 1996; Stilwell, 1993). Many of these debates and concerns can be seen in New Zealand, a country where almost 87% of the population live in urban areas (MfE, 2005). This debate has risen up the political agenda in recent times with the Ministry for the Environment stating that “the global imperative of sustainable development means urban areas need to be more socially inclusive, economically prosperous and environmentally friendly” (MfE, 2002). Although debate about urban form and transport has been wide, few deWnitive conclusions have been made (Maat et al., 2005). For example, links between higher density and shorter travel distances in certain cities have not

N. Buchanan et al. / Journal of Transport Geography 14 (2006) 342–354

always been replicated elsewhere. One suggested reason for this inconsistency is that most of the research has been conducted in very large cities. While it may be important to Wnd results for cities with large populations, there is a notable gap in the literature where medium-sized cities have received little attention. This is especially important in New Zealand, where only one city, Auckland, has over one million people. Relationships between urban form and transport may diVer for diVerent sized cities. The relationship may diVer due to the diVerence in population numbers and density, as medium-sized cities often lack areas of high density, which have previously been tested with modal split and trip length (Steiner, 1994). This paper, therefore, attempts to understand the complexities of urban growth and travel patterns in a medium-sized city, providing a signiWcant contribution to the literature. This paper seeks to examine how the changing shape of Christchurch, in particular through continued peripheral expansion, has aVected journey to work (JTW) travel patterns. Although Christchurch is a medium sized city, with an Urban Area population of 363,700 in 2004 (Statistics New Zealand, 2005), peripheral residential developments have placed stress on the existing transportation network. People are now required to travel greater distances for work, shopping and leisure purposes, as these new peripheral residential developments are often isolated from large employment areas, and accessibility to local facilities and services is limited. To achieve this aim the paper is organised as follows. First, we place our research within the context of previous work on the relationship between urban form and transport. Second, we brieXy outline the context of urban decentralisation in Christchurch. Third, we discuss the methodology of the study and justify the dependent and independent variables used in the statistical analyses. In the fourth section, we examine how JTW travel patterns changed in the city between 1991 and 2001 and analyse the key population and urban structural variables which have been related to changes in JTW travel patterns. Fifth, we discuss our Wndings in the light of existing research. We conclude by summarising the key Wndings of the study and discussing their implications for future urban research in New Zealand. 2. The relationship between urban form and transport It has been shown that a number of land use characteristics, on a range of diVerent scales, can aVect travel patterns (Boarnet and Crane, 2001; Stead et al., 2000). At the regional level the location of new development has the potential to aVect travel demand. The size, type and shape of the new development and the mixture of land uses have been shown to aVect how people travel. At the city level varying levels of concentration of development are likely to aVect travel demand, while at the neighbourhood level, the density and the shape of development inXuence travel (Richardson and Bae, 2004). It has been concluded that

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existing literature shows that the relationship between urban form and travel behaviour is highly complex, and that diVerent characteristics of the built environment, such as city size, density and urban structure, are interwoven and have a composite impact on travel patterns (Dieleman et al., 2002). However, other authors have concluded that previous work has provided little, if any, support that urban design aVects travel (Crane and Crepeau, 1998). Overall, the relationship between land use and transport is far from clear and seems to vary according to each individual city research has been conducted in (Giuliano, 1995; Handy, 1996; Kitamura et al., 1997; Stead et al., 2000). 2.1. Journey to work One of the important Wndings in recent years is that urban decentralisation has resulted in more dispersed JTW patterns which are not as uniquely determined or as predictable as in the past. Historically, this trip involved the daily movement to the downtown area by the head of the household from the suburbs (Hartshorn, 1992). Four main JTW commuting patterns have been identiWed in United States (US) cities: 1. City-to-city, including Xows within the central city; 2. Suburb-to-city, where travel originates in the suburbs and ends in the central city; 3. Suburb-to-suburb, where a journey is made from an outlying residential area to a nearby suburban employment centre, but can include cross-town movement; 4. Reverse commuting, or travel from the city centre to the suburbs for employment. The third category was by far the most important and had the greatest increase (58%) in the number of trips from 1980 to 1990 in the US (Giuliano, 1998). In theory, the suburbanisation of both population and employment has the potential to shorten travel distances if households choose residential locations close to their place(s) of employment (Ingram, 1998). However, it has been argued that decentralisation has not brought people and jobs closer together because of diVuse commuting patterns (Cervero, 1995, 1998) and that people often make a conscious trade oV between accessibility and their space requirements (Alonso, 1964). Furthermore, people are sometimes not able to live close to where they work because of a lack of aVordable housing in many metropolitan areas (Giuliano, 1991). In the US, lower cost housing is often unavailable in peripheral areas and, as a result of not living close to their place of employment, many low income people are forced to drive long distances to work (Wachs and Taylor, 1998). In contrast to typical US cities, the most socio-economically disadvantaged areas in Australia are located in outer suburban locations, as opposed to the centre of the city (Dodson, 2004; Freestone and Murphy, 1998). Higher income groups, on the other hand, will often make a conscious choice to distance themselves from employment

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zones and their negative externalities. The recent emergence of gated and semi-gated communities is a case in point (Blakely and Snyder, 1997). Internationally, average trip lengths have increased dramatically in the last 20 years (Giuliano, 1998; Newman and Kenworthy, 1999) and this increase has been linked to the growing use of the car, allowing greater distances to be travelled (Banister et al., 1997). Some of the blame for rising trip distances has been credited to exclusionary zoning policies (Newman and Kenworthy, 1999), while other factors such as residential preferences and school location have also played a role (Cervero, 1998; Giuliano, 1991). Nevertheless, research has shown when sites of employment and residence are close together, the commute to work is shorter than when employment and residential locations are further apart (Ingram, 1998) and that large cities are characterised by longer distance trips than smaller cities (Spence and Frost, 1995). 2.2. Urban density and travel patterns Population, or residential, density is important because higher densities reduce the need to travel (Steiner, 1994). In general, the population density of a city decreases as the distance from the city centre increases. While it is possible that the pattern of employment density matches that of population density, employment density is more likely to exhibit a pronounced nodal pattern according to the dispersion of employment. Density is also closely related to travel patterns, more speciWcally modal split and trip length (Breheny, 1996). Population density has been shown to be one of the most important land use related factors inXuencing travel behaviour with higher densities being strongly related to lower travel distances and to the increasing use of modes other than the car (Barrett, 1996; Newman and Kenworthy, 1999). A number of studies have examined the link between urban density and travel patterns, although the exact nature of the relationship has often been diYcult to determine (Cervero, 1998; Crane, 2000; Levinson and Kumar, 1997; Maat et al., 2005). Assumptions have been made that people living in high-density developments will make fewer and shorter car trips and will walk or use public transport more frequently (Maat et al., 2005; Steiner, 1994). However, it has been shown that travel patterns depend on the location and type of development (Ewing et al., 1994). It has also been assumed by scholars that people will be willing to move into high-density areas and, if they do, that they will change their travel patterns. If the assumptions prove to be true, there will be environmental beneWts. If not, there may be increased emissions and traYc congestion (Maat et al., 2005; Steiner, 1994). Any relationship between urban density and travel is not necessarily straightforward as neighbourhoods with the highest densities are usually located close to town or city centre facilities, and these neighbourhoods are often disproportionately occupied by households with below average incomes and relatively low rates of car ownership (Barrett,

1996; Kitamura et al., 1997). However, this is not the case in Australia (Dodson, 2004; Freestone and Murphy, 1998). New Zealand cities are similar to those in Australia, although they typically have a lower rate of public transport (Laird et al., 2001). 2.3. Household composition and travel patterns Household size and composition has been shown to be important in determining how many trips the household produces (Giuliano, 1998) and because the type of the household is related to the distance travelled to work (Hanson and Schwab, 1995; LTSA, 2000; Turner and Niemeier, 1997). This is important as the structure of households is changing, particularly since the 1950s. Household sizes have declined since the post-World War 2 boom. Declining household sizes mean that there is more travel for individual and personal needs such as shopping, cleaning, house maintenance and social visits, and less sharing of resources (car pooling for example), resulting in the generation of more household trips (Giuliano, 1998). However, household travel patterns are strongly aVected by location (Naess, 2005) and the socio-economic status of the household, with higher income suburban households being more likely to be those making the longest trips (Gillespie et al., 1998). Ethnic composition also plays an important role in understanding how the household travels, however, this has not been included in many international studies (Dieleman et al., 2002; Kitamura et al., 1997; Naess and Sandberg, 1996). In the US, Turner and Niemeier (1997) found that ethnicity played a role in commuting to work with African American women travelling longer than their European counterparts, a pattern most likely reXecting the spatialmismatch between residential and work locations (Cooke, 1997). By contrast, ethnic diVerences in New Zealand seem diVerent from those in the US. Evidence suggests New Zealanders of European descent travel further and drive more often than people of Maori and PaciWc Island origin (LTSA, 2000), although diVerences in income (much lower for Maori and PaciWc Islanders) and car ownership may contribute to this statistic. 2.4. Residential relocation and travel patterns Relatively few studies have focused on the impact of residential relocation on travel patterns. Research in the United Kingdom (UK) found that there is an association between housing migration and increased commuting distances, with increased travel accompanying moves out of the central city (Barrett, 1996). Research in Sydney found similar increases in travel time after moving out and also found that people had Wxed travel mode preferences when travelling to work and that a change in residential location did not lead to a large change in travel mode after relocation (Burnley et al., 1997). Research in Denmark by Naess (2005) and the US by Krizek (2003) have found similar Wndings. In Auckland, a study was conducted on the

N. Buchanan et al. / Journal of Transport Geography 14 (2006) 342–354

impacts of moving to a new medium-density housing development (Dixon and Dupuis, 2003). This new development was situated within the existing framework of metropolitan Auckland and not on the urban periphery. The development was located in close proximity to a local shopping area and rail and bus stations. For nearly half of the residents, their car usage remained the same as at their previous residence. Importantly, over one-third of the residents used their car less, while only a small percentage used their car more often (Dixon and Dupuis, 2003). 3. Urban growth processes in Christchurch In New Zealand, as elsewhere, concerns over urban growth and its transport implications are becoming more important in both national and local political agendas (MfE, 2005). This is particularly true in Christchurch, where new peripheral developments have resulted in increased congestion and placed stress upon the local transport network. These recent developments are part of a long term trend, but nevertheless one which has been accentuated in recent years by the lack of a coherent urban growth strategy compared to the past (Memon, 2003). In response to this, an urban development strategy has begun to be formulated (GCUDSF, 2005). Urban growth in Christchurch increased rapidly after World War 2 leading to an increasingly decentralised city (Barber, 1983; Pryor, 2003). By the end of the 1960s more people were living outside the city centre than in it, and this trend has been linked to central and local government policy that encouraged and often restricted homebuyers to purchase new housing on the urban periphery (Barber, 1983). More recently peripheral urban expansion has been encouraged by the Resource Management Act 1991 (RMA) that, although advocating sustainability, encouraged an eVectsbased urban growth policy and a dismantling of former regulatory controls. An important outcome of this legislative change has been the “shot-gun” spread of development within separate but adjoining territorial authorities around Christchurch (Pryor, 2003). The construction of new residential subdivisions has rapidly accelerated since the introduction of the RMA, as the new “eVects based” district plans by the Christchurch City, Selwyn, Waimakariri and Banks Peninsula District Councils are more “market” responsive and less restrictive (Memon, 2003). This coincided when Christchurch greenbelt policies ceased to be binding in 1993 after the establishment of the RMA. The Christchurch City Council has rezoned a large amount of land for urban development, approximately 1100 ha (Memon, 2003). The large amount of land rezoned for peripheral development in the 1990s was justiWed through the demand of population movement outwards from the city. Demand was also created by private developers who marketed their developments, many of which have been gated and semi-gated communities to attract potential buyers (Ansley, 2004). The new peripheral residential developments have grown in conjunction with a decentralisation

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of commercial and industrial activities and increasing pressure on port and airport facilities (Pryor, 2003). This has led to major links and interchanges of the road network becoming increasingly congested. Despite some incipient gentriWcation and apartment construction within the inner city, Christchurch has been described as a polycentric city (Memon, 2003). The polycentric model still has a highly accessible CBD, but it is joined by suburban nodes or subcentres. The location of suburban employment continues to play a role in commuting patterns, and with more jobs in the suburbs, the result is a more balanced ratio between employment and housing (Schwanen et al., 2003). This type of urban development has been encouraged by the current City Plan in Christchurch, which has focused on promoting 10 suburban focal points, around which are mixed activities and low–medium and medium density housing. 4. Methodology Following Dieleman et al. (2002), two dependent variables, modal split and trip length, were used in order to assess patterns of, and changes in, travel behaviour. Data were obtained from the 1991 and 2001 censuses of population and housing (from Statistics New Zealand) which reported JTW travel by mode of transport at the census area unit level (CAU—115 CAUs in the Christchurch Urban Area). Modal split data were obtained for both CAU of origin (residence) and CAU of destination (workplace). The modes identiWed were: car, public transport (bus in the case of Christchurch), bicycle, and walking. Because individual survey data was unavailable for the time period studied, the analysis therefore relies on aggregate-level census data to determine changes in trip patterns and interpretations of their likely causes. However, given the well known problem of the ecological fallacy (Dogan and Rokkan, 1969), the caveat must, therefore, be added regarding the limitations of using ecological data when attempting to make causal inferences regarding decisions underlying individual travel behaviour. A trip length variable was computed speciWcally for this study. Rather than use straight-line distances, more realistic estimates were obtained by calculating distances between the CAU centroids (the centre of each area unit) through the road network using TransCAD, a transportation-based geographical information system program. CAU to CAU JTW data were taken from the 1991 and 2001 origin–destination matrices for each of the modes examined. Each CAU to CAU Xow was multiplied by the appropriate distance, summed for all Xows originating in a given CAU, and averaged by the total number of trips originating from that CAU. This provided an estimate of the average worktrip length for each CAU. Trips within the CAU were calculated as 1 km. As these measures of average trip length were calculated from the shortest distance on the road network, the stated distances are likely to be shorter than those actually travelled and cannot be taken to reXect relative journey times. This is because trips are not always taken by

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the shortest possible distance and are also likely to be subject to variations in road conditions, congestion, and the presence of speed limits. Origin–destination data for the JTW was analysed for car, bus, bicycle and walking, although the latter variable was unavailable for 1991. For the interpretation of city-wide travel patterns, the CAUs were amalgamated into four categories grouped according to how each CAU related to the median values of one structural and one compositional variable. The structural variable chosen, population density, represents the form of the city, and the compositional variable, an index of household deprivation (Crampton et al., 2001), represents socio-economic factors inXuencing travel patterns. The resulting categories can be labelled: (i) high density (above the median) and low deprivation (below the median); (ii) high density and high deprivation; (iii) low density and low deprivation; (iv) low density and high deprivation. Given that most peripheral development has catered for middle and higher income households, we expected that this would result in substantial variations in JTW distances and modal split across these four categories. Modal split and trip length were related, in turn, to six diVerent independent variables: (a) population density; (b) employment density; (c) distance from the central business district (CBD); (d) family status; (e) ethnicity; (f) household deprivation. These independent variables represented both compositional and contextual components. The compositional variables consisted of household deprivation, family status and ethnicity, while the contextual or structural variables were residential density, employment density and distance from the CBD. These independent variables were selected on the basis of the model devised by Dieleman et al. (2002). Relationships between the independent variables and each of the two dependent variables (modal split and work-trip length) were analysed by stepwise multipleregression analysis to investigate the connections among variables aVecting urban travel behaviour. Population density and employment density were computed by dividing the number of people who resided (or worked) in each CAU by its area. Total employment in each CAU was taken from the destination column of the JTW origin–destination matrix. CAU distance from the centre of the city (Cathedral Square) was measured using TransCAD, which also computed the shortest road distance between pairs of CAU centroids. Distance from the CBD has been shown to play a signiWcant role in determining travel behaviour, aVecting modal split, trip length and travel time (Spence and Frost, 1995; Naess and Sandberg, 1996; Stead et al., 2000; Naess, 2005). Three measures of the family status of each CAU (the percentages of households that were: (i) couples with children; (ii) couples without children; (iii) single parents with children) were obtained from Statistics New Zealand. In addition four measures of CAU ethnicity were obtained (percentages of CAU populations that were persons of Pakeha/European, Maori, PaciWc Island, and Asian descent). The Wnal compositional variable was the NZDep01 depriva-

tion score for each CAU. NZDep01 classiWes CAUs into deciles based upon the national rankings on nine diVerent demographic and socio-economic variables (Crampton et al., 2001). The New Zealand Deprivation Index (NZDep01) provides a measure of poverty or economic hardship (Crampton et al., 2001). The Deprivation Index ranks areas in terms of relative deprivation. This has been included as an independent variable because evidence suggests that both modal split and travel distances are aVected by socio-economic status (Stead et al., 2000). Thus, it is important to control for such eVects in attempting to isolate the contribution of contextual and compositional factors aVecting travel patterns. The use of aggregated data eliminates intra-CAU variation (e.g., centroid to centroid distances, intra-CAU travel distances, household deprivation) in dependent and independent variables and therefore generates stronger relationships than would be the case for individual data. For some of the independent variables (population density, employment density) the use of an aggregate measure of urban structure is probably unavoidable but in this case it does introduce further simpliWcations because CAUs are deWned for statistical (census administration) purposes rather than to represent “natural” clusters of population or employment. Furthermore, the employment density measure reXects only the employment in the CAU of residence and takes no account of the wider employment opportunities in adjacent or nearby CAUs. For these reasons the use of aggregate data based on CAUs is likely to produce stronger relationships between the contextual and compositional variables and the dependent variables indexing travel behaviour. Individual level data were not available for this study and so a decision was made to proceed with aggregate CAU level information. 5. Results Between 1991 and 2001, on the basis of a broad classiWcation of CAUs into CBD, Inner Suburbs and Outer Suburbs, there was relatively little change in the distribution of workers’ residences. A 42% increase in the relatively small number of CBD residents is the only notable feature. Slightly more change occurred in the distribution of workplaces with a decline (both absolute and relative) in the role of the CBD and increases (both absolute and relative) in Inner and Outer Suburbs. The transport implications of changing patterns of residences and workplaces depend on the particular Xows between residence and workplace and any changes in the modes of transport used. The following sections explore these implications and analyse the role of selected variables that are expected to inXuence the Xow patterns. 5.1. Origins and destinations Overall, the major share of work-trips was contributed by journeys that began and ended within the Outer

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Suburbs: 29.0% in 1991 and 30.7% in 2001 (Fig. 1). The next most important Xows were trips from Outer to Inner Suburbs (15.4% in 1991 and 16.8% in 2001) and from Outer Suburbs to the CBD (16.9–14.2%, respectively) (Table 1). Clearly, suburb-to-suburb commuting is the dominant pattern and a distinct trend in the Christchurch Urban Area. Overall, JTW trips to the Outer Suburbs from all other areas rose from 38.5% to 40.2% between 1991 and 2001. JTW trips ending in the Inner Suburbs also rose from 31.1% to 33.3% over this period. By contrast, the share of the trips from the Inner and Outer Suburbs to the CBD in Christchurch suVered a noticeable decline from 29.4% to 25.1%, or a reduction of almost 2000 trips over the period studied.

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When examined in terms of this broad zone to zone classiWcation of origins and destinations, the various modes reveal quite diVerent patterns (Table 2). Work-trips by car were dominated by Outer to Outer Suburb movements for both 1991 and 2001. Outer to Inner Suburb and Outer Suburb to CBD Xows by car were also important but whereas, the former increased in relative importance between 1991 and 2001, the latter declined in signiWcance. Bus work-trips were dominated by Outer Suburb to CBD and Inner Suburb to CBD Xows though both of these declined in relative importance over the study period. Work travel by cycle was dominated by Outer to Outer Suburb trips with Inner Suburb to CBD and Inner to Inner Suburb Xows slightly less signiWcant. Data for walk trips were available only for 2001

Fig. 1. Travel Xows (%) for Christchurch by urban zone for total trips in 2001.

Table 1 Urban zone of origin and destination for total JTW trips Urban zone

1991

% 1991

2001

% 2001

Change

% Change

CBD–CBD CBD–Inner CBD–Outer Inner–CBD Inner–Inner Inner–Outer Outer–CBD Outer–Inner Outer–Outer

1224 486 366 14367 17535 10620 19416 17721 33324

1.1 0.4 0.3 12.5 15.2 9.2 16.9 15.4 29.0

1812 702 441 13722 20298 11658 18087 21282 38958

1.4 0.6 0.3 10.8 16.0 9.2 14.2 16.8 30.7

588 216 75 ¡645 2763 1038 ¡1329 3561 5634

48.0 44.4 20.5 ¡4.5 15.7 9.8 ¡6.8 20.1 16.9

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Table 2 Origin–destination trips by urban zone and modal split (%) Urban zone

CBD–CBD CBD–Inner CBD–Outer Inner–CBD Inner–Inner Inner–Outer Outer–CBD Outer–Inner Outer–Outer

Car

Bus

Cycle

Walk

1991

2001

1991

2001

1991

2001

1991

2001

0.3 0.4 0.3 11.0 13.7 10.6 17.6 17.8 28.1

0.5 0.5 0.4 9.8 13.7 10.8 15.3 19.6 29.5

0.3 0.9 0.7 29.4 5.1 4.4 44.7 8.3 6.1

0.9 1.3 1.2 23.6 10.4 5.8 34.9 12.3 9.7

1.5 1.1 0.3 19.9 18.8 8.8 12.6 12.0 24.8

1.4 1.0 0.4 19.1 19.9 9.6 13.9 12.3 22.5

– – – – – – – – –

13.9 1.2 0.3 18.7 26.3 3.8 2.3 4.9 28.6

Table 3 Modal split (%) from origin by urban structure category Category

Car

Bus

Cycle

Walk

1991

2001

Change

1991

2001

Change

1991

2001

Change

1991

2001

Change

Low den./low dep. High den./low dep. Low den./high dep. High den./high dep.

82.5 78.3 68.4 69.4

85.4 80.9 75.4 72.4

2.9 2.6 7.0 3.0

3.4 4.7 3.8 5.9

2.9 3.8 3.5 5.4

¡0.5 ¡0.9 ¡0.3 ¡0.5

5.5 9.9 11.1 12.5

3.9 7.1 5.9 8.4

¡1.6 ¡2.8 ¡5.2 ¡4.1

3.6 3.0 10.0 6.5

3.0 3.6 8.4 7.5

¡0.6 0.6 ¡1.6 1.0

Christchurch avg.

75.1

78.6

3.5

4.9

4.1

¡0.8

10.0

6.7

¡3.3

4.9

5.2

0.3

and revealed the dominance of Outer to Outer Suburb and Inner to Inner Suburb Xows. 5.2. Changes in travel mode Table 3 gives an indication of how travel modes changed in Christchurch between 1991 and 2001. Over the decade the absolute number of JTW trips increased by 22,116 (from 109,008 to 131,124) or by 20.3%. For the city as a whole the proportion of people travelling to work by car increased slightly from 75.1% in 1991 to 78.6% in 2001. By contrast, the percentage of trips by bus decreased slightly (from 4.9% to 4.1%), despite a minimal increase in absolute numbers, while cycling has had a more pronounced decline (10.0–6.7%). The proportion walking to work increased minimally over the last 10 years (4.9–5.2%). When the CAUs were separated into the four urban structure categories based upon population density and deprivation, greater variations in patterns of change became evident (Table 3). In both 1991 and 2001, car use was higher than the overall Christchurch average in the low deprivation areas and especially for the lower density CAUs (although high rates of car use were also evident for high density areas). By contrast, more deprived CAUs, especially those in higher density locations, had lower levels of car use, approximately 6% less than the average. However, over the decade the largest increase in the proportional share of JTW trips by car occurred in high deprivation/low density areas (Table 3). This was also true when absolute (%) rates of change were examined. While CAUs in this category generally had lower levels of car ownership (the correlations between cars per household

and deprivation were ¡0.80 and ¡0.85 in 1991 and 2001), they nevertheless recorded the greatest percentage increase (38.7%) in car trip generation over the decade, a rate marginally ahead of more aZuent low density CAUs (31.1%), but substantially greater than both lower and higher income more densely settled areas of the city (24.2% and 19.8%, respectively). Bus use declined slightly over the period studied amongst all four categories, with low density areas, regardless of deprivation, having the lowest levels of bus use in 2001. Cycle use for the JTW also declined between 1991 and 2001 with peripheral CAUs, especially those that were the least deprived, having the lowest levels of cycle use in 2001. People living in more deprived CAUs were more likely to walk to work, but again it was the poorer, low density suburbs which revealed the greatest decline in this mode between 1991 and 2001. 5.3. Changes in trip length Overall average work-trip length in Christchurch increased slightly from 6.8 km in 1991 to 7.0 km in 2001 with changes being more apparent for speciWc modes. The average distances travelled by car and cycle did increase (by 0.4 km (7.6–8.0) and 0.5 km (5.5–6.0 km), respectively), but not to a great extent. DiVerences were more noticeable when the average trip lengths were analysed in terms of the four urban structure categories (Table 4). CAUs in the low density/low deprivation category generated the longest average distance to work, at 9.3 km in 2001. This group along with the low density/high deprivation CAUs (which had the second longest average JTW distance), also

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Table 4 Average distance (km) travelled by urban structure category Category

Low den./low dep. High den./low dep. Low den./high dep. High den./high dep. Christchurch avg.

Car

Bus

Cycle

Total

1991

2001

Change

%

1991

2001

Change

%

1991

2001

Change

%

1991

2001

Change

%

10.5 6.2 8.0 6.0

11.1 6.5 8.5 6.2

0.6 0.3 0.5 0.2

5.7 4.8 6.3 3.3

9.4 6.1 8.0 5.5

10.1 6.1 6.7 5.6

0.7 0 ¡1.3 0.1

7.4 0 ¡16.3 1.8

6.6 5.3 4.9 4.7

7.8 5.6 4.2 4.9

1.2 0.3 ¡0.7 ¡0.2

18.2 5.7 ¡14.3 ¡4.3

9.1 5.9 7.1 5.4

9.3 5.9 7.6 5.5

0.2 0 0.5 0.1

2.2 0 7.0 1.9

7.6

8.0

0.4

5.3

7.5

7.4

¡0.1

¡1.3

5.5

6.0

0.5

9.1

6.8

7.0

0.2

2.9

revealed the largest increases in average distance since 1991. The two high density categories generated the shortest average distances to work (5.9 km and 5.4 km, respectively, in 2001). Of more importance, given the fact that low density CAUs were highly dependent upon car transport, is the fact that average work-trip distances by car were much longer than for all work-trips as a whole. This was particularly noticeable for both groups of low density CAUs, especially those with more aZuent populations. Here, the average work-trip distance by car was 11.1 km in 2001 compared to 8.5 km for less aZuent low density suburbs. The more aZuent/low density CAUs also had the largest absolute increase in average JTW distance since 1991. Low density areas also averaged longer trips by bus. Interestingly, the distance travelled by bus increased between 1991 and 2001 in more aZuent/low density suburbs but decreased in the low density/high deprivation CAUs. As to be expected, cyclists generated the shortest average JTW in each category for both 1991 and 2001. 5.4. Predictors of modal split and average work-trip length Stepwise multiple regression analysis was used to analyse the relationship (for each travel mode: car, bus and cycle) between the structural/compositional independent variables and the two dependent variables (modal split and work-trip length). Walking was not included due to data limitations. Separate analyses were conducted for 1991 and 2001 using the 115 CAUs as observations. Because there was a high degree of intercorrelation among the independent variables, they were divided into separate compositional and structural analyses as well as being collectively tested against each JTW travel mode. As indicated previously, the compositional variables consisted of family status (couples with or without children and single parents with children), ethnicity (European, Maori, PaciWc Island and Asian) and the New Zealand Deprivation Index. The structural category comprised residential density, employment density and the distance from the CBD. Twelve tests were performed in total (3 modes multiplied by 2 years multiplied by 2 dependent variables). When compared with compositional variables, structural variables emerged as better predictors of CAU modal split for car and cycle trips, while the modal split for bus use was better predicted by the compositional variables.

These results are summarised in Table 5. In 1991, the compositional variables had a slightly greater inXuence on car use than structural variables (the R2 values were 0.679 and 0.671, respectively). However, by 2001, structural variables had rather more inXuence on car use than compositional variables (0.719 versus 0.637). Cycle use was inXuenced to a greater extent by structural variables in both 1991 and 2001. Bus use was the exception, where compositional variables were a better predictor of bus use in both years. In the cases of bus and cycle use, diVerences have widened over time. When compared to compositional variables, structural variables had a stronger relationship in 2001 than 1991, while diVerences narrowed for bus use, indicating that a higher percentage of car and cycle trips can be explained by the presence of structural variables in 2001 compared with 1991. When all the independent variables were analysed collectively, distance from the CBD was the variable that had the strongest relationship to both car and cycle use and in both cases the relationship increased over time. R2 values in 1991 and 2001 were 0.570 and 0.659, respectively, for car use and 0.522 and 0.698 for cycle use (Table 6). Car use was also highly (negatively) related to deprivation in 1991 but not in 2001, with various indicators of family status, in particular couples with children, assuming greater importance. This variable also seemed to play a secondary role in predicting levels of bus and cycle use to work, particularly in 2001. The positive relationship between couples with children and car use alludes to some journeys to work involving chauVeuring children to school, while the negative relationship with bus and cycle use suggests these modes are more impractical to travel by with the presence of children in the household (Table 6). These results also raise the issue of time constraints; parents with children may have less available time and it may be necessary to travel by a quicker mode to work. When the structural and compositional categories were analysed separately against average car work-trip length, structural variables were markedly stronger than the compositional variables (Table 7). Primarily due to the inXuence of the distance from the CBD, structural variables proved to be a better predictor of average trip length by car in both 1991 and 2001. In 1991 the R2 diVerence between structural and compositional predictors of car use was 0.462 (R2 values were 0.890 and 0.428) and 0.414 in 2001 (0.893 versus 0.479). Interestingly, Asian commuters had a

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N. Buchanan et al. / Journal of Transport Geography 14 (2006) 342–354

Table 5 Multivariate analysis of modal split and compositional and structural variables Order

Direction of relationship

Sig. level

Cum. R2

Order

Direction of relationship

Sig. level

Cum. R2

Car Dist. CBD Work den. Population den.

+ ¡ ¡

Structural 0.00 0.00 0.00

1991 0.570 0.639 0.671

Dist. CBD Work den. Population den.

+ ¡ ¡

Structural 0.00 0.00 0.00

2001 0.659 0.691 0.719

Couple WC Couple WOC Asian

+ + ¡

Composition 0.00 0.00 0.00

1991 0.531 0.601 0.679

Deprivation Maori 1 Parent WC

¡ + ¡

Composition 0.00 0.00 0.00

2001 0.377 0.607 0.637

Bus Dist. CBD Population den.

¡ +

Structural 0.00 0.01

1991 0.309 0.354

Dist. CBD Work den.

¡ +

Structural 0.00 0.00

2001 0.379 0.438

1 Parent WC Maori European

+ ¡ ¡

Composition 0.00 0.00 0.00

1991 0.389 0.455 0.503

Deprivation Maori European

+ ¡ ¡

Composition 0.00 0.00 0.04

2001 0.371 0.515 0.533

Cycle Dist. CBD Work den. Population den.

¡ + +

Structural 0.00 0.00 0.02

1991 0.522 0.621 0.639

Dist. CBD Population den. Work den.

¡ + +

Structural 0.00 0.00 0.01

2001 0.698 0.720 0.735

Couple WC Asian Couple WOC

¡ + ¡

Composition 0.00 0.00 0.00

1991 0.469 0.527 0.589

1 Parent WC Maori Couple WC

+ ¡ ¡

Composition 0.00 0.00 0.00

2001 0.303 0.484 0.574

Sig. level

Cum. R2

Order

Direction of relationship

Table 6 Multivariate analysis of modal split and all variables Order

Direction of relationship

Sig. level

Cum. R2

Car Dist. CBD Deprivation Asian Couple WC

+ ¡ ¡ +

1991 0.00 0.00 0.00 0.01

0.570 0.758 0.792 0.806

Dist. CBD Couple WC European PaciWc Is. 1 Parent WC

+ + + + ¡

2001 0.00 0.00 0.00 0.00 0.01

0.659 0.797 0.818 0.825 0.837

Bus 1 Parent WC Population den. Asian

+ + +

1991 0.00 0.00 0.01

0.389 0.485 0.512

Dist. CBD Couple WC European

¡ ¡ ¡

2001 0.00 0.00 0.00

0.379 0.542 0.599

Cycle Dist. CBD Couple WC Maori Work den.

¡ ¡ + +

1991 0.00 0.00 0.00 0.00

0.522 0.679 0.717 0.749

Dist. CBD Couple WC Population den.

¡ ¡ +

2001 0.00 0.00 0.00

0.698 0.792 0.807

negative relationship with car trip length, while Maori had a positive relationship. This indicates that Asians live closer to their place of employment than do those of Maori descent. The positive relationship between Maori and car trip length suggests a form of spatial mismatch; in Christchurch lower-cost housing may not necessarily be located close to areas with high concentrations of entry level employment. Structural variables were also the best predictors of average work-trip length by bus in 1991 and 2001, although the relationships were not as strong as for the car variable

(Table 7). Distance from the CBD was the most important variable for work-trip distance by bus. In contrast, compositional variables emerged as better indicators of average cycle work-trip length, but only in 2001. Furthermore, the relationships between cycle trip length and the structural and compositional variables were very weak, which indicates that other non-tested inXuences are signiWcant in cycle use (e.g., age, gender and interest in recreational cycling). When the independent variables were collectively analysed, it was found (not surprisingly) that the distance to the CBD had the strongest relationship to average work-trip

N. Buchanan et al. / Journal of Transport Geography 14 (2006) 342–354

351

Table 7 Multivariate analysis of trip length and compositional and structural variables Order

Direction of relationship

Sig. level

Cum. R2

Order

Direction of relationship

Sig. level

Cum. R2

Car Dist. CBD

+

Structural 0.00

1991 0.890

Dist. CBD

+

Structural 0.00

2001 0.893

Asian 1 Parent WC Deprivation Maori

¡ ¡ + +

Composition 0.00 0.00 0.00 0.02

1991 0.242 0.324 0.400 0.428

Asian 1 Parent WC Maori PaciWc Is.

¡ ¡ + ¡

Composition 0.00 0.00 0.00 0.04

2001 0.140 0.316 0.459 0.479

Bus Dist. CBD

+

Structural 0.00

1991 0.300

Dist. CBD

+

Structural 0.00

2001 0.397

1 Parent WC Maori

¡ +

Composition 0.00 0.00

1991 0.080 0.107

1 Parent WC Maori

¡ +

Composition 0.00 0.00

2001 0.075 0.155

Cycle Population den. Work den.

¡ ¡

Structural 0.00 0.02

1991 0.065 0.107

Population den. Work den.

¡ ¡

Structural 0.00 0.01

2001 0.097 0.155

Deprivation Asian

¡ ¡

Composition 0.00 0.03

1991 0.060 0.100

Deprivation Asian

¡ ¡

Composition 0.00 0.02

2001 0.156 0.196

Table 8 Multivariate analysis of trip length and all variables Order

Direction of relationship

Sig. level

Cum. R2

Order

Direction of relationship

Sig. level

Cum. R2

Car Dist. CBD Couples WC Asian Maori European Population den.

+ ¡ ¡ ¡ ¡ ¡

1991 0.00 0.00 0.00 0.00 0.00 0.01

0.890 0.903 0.912 0.920 0.927 0.932

Dist. CBD Asian Couples WC

+ ¡ ¡

2001 0.00 0.00 0.00

0.893 0.909 0.920

Bus Dist. CBD

+

1991 0.00

0.300

Dist. CBD

+

2001 0.00

0.397

Cycle Population den. Work den.

¡ ¡

1991 0.00 0.02

0.065 0.107

Deprivation Asian

¡ ¡

2001 0.00 0.02

0.156 0.196

distance by car in 1991 and 2001 (Table 8). These results for car distance were stronger than the equivalent analysis of modal split. Distance from the CBD also remained the strongest predictor of average bus work-trip distances in 1991 and 2001, though somewhat weaker than the car. The increase in the strength of the bus relationship between 1991 and 2001 is possibly due to more bus use near the centre of the city related to parking problems and diYculties of cycling in heavy traYc. In the analysis of the combined variables and average cycle work-trip distance, it was found that the signiWcant variables changed between 1991 and 2001. Even though the R2 values were low, population density had the greatest inXuence on cycle work-trip distance in 1991, whereas deprivation was the main variable in 2001. It seems clear that variables other than those tested here, are the key inXuences on cycle use.

6. Discussion This paper has investigated the relationships between urban structure and transport patterns, which have been the subject of much international debate over the last decade. Several methods have been used to approach the analysis, including the grouping of Christchurch CAUs into four categories relating to levels of population density and household deprivation and the use of data on population density, employment density and average work-trip distances. A number of key Wndings are evident. First, Christchurch, like many other decentralising Western cities, became more reliant on car transport for the JTW during the 1990s. In particular, while more aZuent low density suburbs generated the highest percentage of car trips in both study years, the greatest relative increase in

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JTW by car occurred among more deprived low density CAUs. On the other hand, people living in higher density/ more deprived CAUs had the highest percentage of bus and cycle trips, while people living in low density, more deprived CAUs were more likely to walk to work than other groups. Second, and perhaps more important, however, was the fact that average work-trip distances increased over time, particularly for people living in low density suburbs. DiVerences were particularly apparent among the separate modes with car trips averaging the longest distances. Again, people living in low density/low deprivation CAUs had the greatest absolute increase and the longest trip distances in 2001. Although Christchurch residents had shorter commutes than residents in many other cities, the average JTW car travel distance of 11.1 km is not grossly diVerent from international examples of 12.5 km in the UK and 16.3 km in the US (Giuliano, 1998). These results suggest an increasing spatial mismatch between residential and job locations which is most marked for residents of more aZuent suburban CAUs. By contrast for persons living in less aZuent CAUs travel distances for households dependent upon bus and cycle use were more likely to have remained static or declined. Third, in regard to the origins and destinations of JTW trips, outer suburbs both generated and received the highest percentage of total trips in 1991 and 2001, while the CBD continued to decline as a destination over this period. Car trips were most prominent between Outer Suburbs as well as from Outer to Inner Suburbs and from Outer Suburbs to the CBD, while bus trips stood out between Outer and Inner Suburbs and from Outer Suburbs to the CBD. Cycle trips were relatively evenly distributed throughout these city zones, while walking trips were primarily intra-zonal. An increase in suburb-to-suburb commuting has become a recognisable pattern in recent decades in the US (Giuliano, 1998; Hartshorn, 1992). This suggests that people in the suburbs do not generally live close to their place of employment, despite the continuing decentralisation of employment. Fourth, it is noteworthy that as the city has expanded, the eVects of urban structure upon modal choice and distance travelled have become more important. Car, bus and cycle use was primarily inXuenced by structural, rather than compositional, variables; an eVect more pronounced in 2001. Indeed, when the variables were collectively analysed, distance from the CBD emerged as the key variable for predicting modal split and average work-trip distance in nine out of twelve tests. In contrast, many international studies reveal little as the statistical tests have not included distance from the CBD as a predictor, but have focused on density (Levinson and Kumar, 1997; Newman and Kenworthy, 1999). Density was a variable in the current analysis, but did not emerge as strong a variable as did distance from the CBD. Structural variables, in particular distance from the CBD, but also population and employment density, emerged as key predictors of average CAU work-trip length. CBD distance was the key variable in determining

trip length for car and bus users, while cycle trip length was dependent on population density in 1991 and deprivation in 2001. These Wndings from Christchurch closely relate to those of other research. For instance, Giuliano and Narayan (2003) in a comparison of the US and UK, found that while the eVect of income on distance travelled was similar in the two countries, the eVect of urban form (population density) was more pronounced in the US. Similarly, in a city such as Copenhagen (Naess, 2005), it was found that the location of the residence relative to the downtown was the key urban structural factor exerting a strong impact on the residents’ work travel patterns. In contrast, Kitamura et al. (1997) and Bagley and Mokhtarian (2002) both found in San Francisco that attitudinal and lifestyle variables had a greater impact on travel demand than residential location. In summary, while the Wndings point to broad similarities between travel patterns in Christchurch and other larger decentralised cities, a few caveats are necessary. First, the Wndings are limited to the period between 1991 and 2001, which is problematic since much peripheral urban growth has taken place since then. Second, by relying on ecological data, more nuanced accounts of the reasons for longer JTW distances and patterns of modal split can only be surmised. Third, in the light of the above we would suggest that future research pays more attention to the impact of residential relocation on travel patterns, in particular to the tradeoVs that households make in selecting suburban residences and how important JTW commuting distances and times are in those tradeoVs. For example, JTW travel behaviour may be diYcult to change especially if other travel factors such as distance to local schools are more important in the residential location decision. Moreover, increased distances from employment may be preferred by many households who wish to minimise any negative externalities associated with their place of employment, a particularly important consideration for home owners. Nevertheless, despite these concerns, such information would be important in planning for future urban growth especially if involving a greater integration of housing and employment opportunities in a more compact city. Only with better information and better management does a more sustainable city become a reality. References Alonso, W., 1964. Location and Land Use: Toward a General Theory of Land Rent. Harvard University Press, Cambridge, MA. Ansley, B., 2004. My Home, My Fortress. The New Zealand Listener, 2004, pp. 16–21. Bagley, M., Mokhtarian, P., 2002. The impact of residential neighborhood type on travel behavior: a structural equations modeling approach. Annals of Regional Science 36, 279–297. Banister, D., Watson, S., Wood, C., 1997. Sustainable cities: transport, energy, and urban form. Environment and Planning B: Planning and Design 24, 125–143. Barber, M., 1983. Population change, policy and planning in the Christchurch metropolitan area. In: Bedford, R., Sturman, A. (Eds.), Canterbury at the Crossroads: Issues for The Eighties. New Zealand Geographical Society, Christchurch.

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