Measuring dynamic public transit accessibility to local centres in Warsaw

Open access

Abstract

Over the last decade the number of studies on public transit accessibility has significantly increased. The aim of the study was to analyse the scope of application of measurements of the dynamic time accessibility in transportation systems for evaluation purposes. It was assumed that the indicator is a feasible measure for basic analysis however additional indicators are needed for reliable assessment. The study included assessing access to the global centre of Warsaw and to local and district centres in particular units. Public transit accessibility was analysed using schedule-based travel time and the population data statistic. The results of the study confirm the dynamic character of public transit time accessibility and its usefulness as a measure. Spatial and transit barriers were identified in local distribution centres and public transit operation. The work presented in the paper highlights the relevance of the in-depth evaluation of the public transit system in relation to the major congestion problems in Warsaw.

Introduction

Public transport plays an important role in the functioning of every large city. It facilitates the flow of people and goods and connects the strategic areas of housing, labour, commerce or entertainment (Cervero et al. 2004). Cities cannot develop properly when the relationships between those areas are not satisfactory (Sanchez & Brenman 2007). Public transport accessibility is a key factor to the stable operation of the whole system that the city creates. It is generally understood as the ease of access to the means of transport and the ease of travelling to desired destinations. Concepts of transport availability are used in research on the settlement network, transportation systems and spatial development at every level (Olszewski, Dybicz & Śleszyński 2013).

Evaluation of public transport accessibility may significantly support the management of components of the city and the whole transit network. This analysis should precede every major construction investment. It may also help local authorities intervene in cases of deficiency in public transport services in certain areas, especially housing developments poorly connected to public service areas and workplaces. Hence, those authorities responsible for creating, managing and enhancing such systems (including local government, urban planners, transport engineers, etc.) should introduce proper tools and methods of assessment of public transport accessibility. Since GIS has become more and more common as an aid in different areas of the public sector, it seems obvious that methods of assessment of public transport accessibility will also be implemented through such systems.

Cities around the world use different methods to study and analyse their public transport systems. They are usually based on evaluating time taken to access public transport or distance between the stations and locations of residence (Fransen et al. 2015). Nevertheless, many other substantial factors may be taken into account to receive a more precise view of a particular public transport system. For instance, PTAL (Public transport accessibility level, a method introduced in London and then implemented in other British cities after modifications (e.g. GMAL, Greater Manchester Accessibility Level), consists of evaluating time to get to public transport stations from a defined Point of Interest and waiting time based on time tables (Transport for London 2010). S. Mishra and T. F. Welch (2013), during their research on the Washington-Baltimore region multimodal transport system and its impact on the environment, added the factor of the importance of stations. They analysed public transport frequency in peak and off-peak periods. The element that significantly improves the public transport accessibility assessment is evaluation of the time or cost of the journey to the defined destinations. Research on estimates of public transport vs. private car accessibility in the Tel-Aviv metropolitan area (Benenson et al. 2011) included walking time from the point of origin to a stop, waiting time, summarised journey time (travel times and waiting times between different buses) and walking time from the final stop to the destination (employment areas and other urban functional areas). Through the GIS tool Urban.Access, developed by the researchers, the BTT (Bus Travel Time) was compared with CTT (Car Travel Time). T. L. Lei and R. L. Church (2010) noted that the inclusion of estimated travel time into public transport accessibility assessment may be insufficient. The value fluctuates depending on timetables. Including this factor into public transport accessibility assessment methods demands sophisticated GIS analyses implemented into a specific public transport system.

This paper presents an attempt to assess public transit time accessibility based on the example of a medium-sized European city - Warsaw. The aim of the study was to research the spatial distribution relationship between public transportation accessibility and population in relation to the location of local centres; to investigate the scope of application of the new standard of public transportation schedule data storage (GTFS) in network analysis and to formulate preliminary recommendations for Warsaw’s transport policy development. In the following study it has been assumed that the indicator is a feasible measure for basic analysis providing overall information concerning the system’s quality of operation. On the other hand, this basic model does not take into account e.g. land use, job distribution, travel patterns and other factors, thus additional indicators are needed for more sophisticated and reliable assessment.

The public transport system in Warsaw

Warsaw is a city of comparatively low population density (3 300 persons per km2) with strongly irregular distribution of the demography statistic. The public transportation system in Warsaw (Figure 1) consists of 267 bus lines, 26 tram lines, 4 city train lines (SKM) and 2 metro lines (a shared ticket is also valid on 2 rail lines); it serves over 1 billion passengers annually (Urząd m. st. Warszawy 2015: 42, 54). Despite the well-developed network, public transport modal share dropped by around 10% in 2005-2015 to 46.8% (Kostelecka 2015a: 21). Moreover, it is estimated that during the working day about 1 million cars cross the Warsaw city boundary as well as the central area of the city (in both directions), contributing to the great congestion found in the city (Kostelecka 2015a: 13; TomTom Traffic Index…).

Figure 1
Figure 1

Public transportation system and road network in Warsaw

Source: own study based on: PZGiK and OpenStreetMap data (OpenStreetMap…)

Citation: Urban Development Issues 58, 1; 10.2478/udi-2018-0021

Methodology

Identifying district and local centres

In order to measure the accessibility of public transport in Warsaw, it was crucial to identify key areas which are frequently attended by the inhabitants. Those areas play an important role in the city structure as they ensure workplaces, trade, education, recreation and community interactions. During the study, points which represent district (major) centres and local (minor) centres were selected in every Warsaw district in order to assess transit accessibility by measuring travel time to them. Distinguishing accurate points was performed on the basis of the Study of the Conditions and Directions of Spatial Management (Rada m. st. Warszawy 2006), the results of expert workshops organised by the Warsaw Branch of the Association of Polish Architects (Oddział Warszawski Stowarzyszenia Architektów Polskich 2015), which consisted of analyses of the city’s spatial layout as well as observing the mode of functioning of particular places in the whole urban structure; and on the basis of the outcomes from interviewing experts in the Warsaw University of Technology. Considering the fact that a database of places potentially most visited by residents was needed to analyse the transport accessibility of the research area, a set of points (local centres) was selected based on existing source materials (given in the text), taking into account that forming a methodology for designating centres on a city scale required a separate study. When calculating travel time, the distance between the aforementioned centres represented by points assigned to buildings, intersections or the centre of a key area, and the nearest bus or tram stops was taken into consideration. The calculations assumed a walking speed of 4 km/h.

The model of Warsaw public transport

The model of public transit used in the study was based on data in the General Transit Feed Specification (GTFS) – a standardised data format for storing public transit routes, stops, and schedules (ESRI 2018). GTFS data is used e.g. in Google Maps transit trip planning or other planning applications. Since 2008 the number of transit agencies sharing open schedule data in common format has increased from barely a dozen to over a thousand from almost every country around the world (GTFS Data Exchange). Many major public transit systems, especially operators in the US, have made up-to-date GTFS data for their systems readily available for download. Open-data movement also contributes to producing schedules in GTFS format, commonly available from a dedicated feed registry list (Transitland website…).

Public transit accessibility was evaluated using schedule-based transit analyses in the ESRI environment. The “Add GTFS to a Network Dataset” tool, created by M. Morang, allows one to add GTFS data to an ArcGIS network dataset and perform schedule-aware analyses using ArcGIS’s Network Analyst extension (ESRI 2018). GTFS schedule data for Warsaw was obtained from Transitart (Inovatica website). A network dataset was built using source point features (stop locations, based on GTFS dataset) and line features (roads) based on the official database of cartographic geodetic data (państwowy zasób geodezyjny i kartograficzny [PZGiK]). The evaluation of public transit accessibility was performed using service area layers from the “Network Analyst” extension. A network service area is a region that encompasses all accessible streets within given time breaks and is calculated on the basis of a given cost - in the following study travel time with transit (ESRI 2017).

Accessibility was measured on the basis of travel time, which is crucial for assessing public transit quality. The average travel time by public transport in Warsaw differs in years 1980–2015 (Tab. 1) and the estimates of 41 minutes in 2015, which exceeds the 30 min benchmark proposed in several studies (Cox 2012: 21; Goliszek & Połom 2016: 53). What is more, journeys between house and work destinations are the most common (44.1%; Kostelecka 2015b: 16), and around half of them are made by public transport (Kostelecka 2015b: 19). It is worth mentioning that the number of trips longer than 45 min, a limit time value of travel between city areas, was the biggest in this group (Kostelecka 2015b: 23; Urząd m. st. Warszawy 2015: 104).

Table 1

Average travel time by public transport in Warsaw in the years 1980-2015

Source: Kostelecka 2015b: 105 (Table IX.6)

Year19801993199820052015

Travel time4545434441

The methodology of the study was based on detailed positioning of isochrones of access in 5 minute intervals. In the following study Warsaw University of Technology was chosen as the destination facility, the city centre in this case. The choice of the destination facility was based on the outcomes of the expert interview performed at the Warsaw University of Technology and this was related to difficulties in identifying one, precise centre in Warsaw. The isochrones covered 15 min, 30 min, 45 min, 60 min and 90 min travel time to the destination. The test was performed within the morning rush hours, 6:00–9:00 a.m., on a working day (Fig. 5).

Deviations in the operation of public transport were analysed using population data from 2011, derived from the geostatistics portal (Geostatistics portal…), which is divided into census blocks. The area of high population density was later used to select high population density areas and low public transport time accessibility was identified with the use of the public transit time accessibility indicator. To obtain this, travel time and population data were normalized (Fig. 2) and summed, resulting in a public transit time accessibility indicator. Areas where average travel time was lower than 30 min were classified as satisfactory from the point of view of public transport handling. Outside this area, the public transit time accessibility indicator was classified using the method of Natural Breaks into three classes: 0-0.02, 0.02-0.06 and 0.06-0.53 (Fig. 6), providing information about crucial areas in terms of public transit quality improvement (measured as a function of travel time).

Figure 2
Figure 2

Formula for normalized values

Source: Szeląg 2015: 27

Citation: Urban Development Issues 58, 1; 10.2478/udi-2018-0021

Then the accessibility of district and local city centres was analysed. Based on the map of recognised areas (Fig. 4), containing analysis destination points, isochrones were created covering travel time to the nearest destination in 10 min intervals (from 10 min to 60 min). The test performed included travel time towards the facility, at 9:00 am, on a working day.

Results

Distribution of district and local centres in Warsaw

It is possible to distinguish district and local centres in the urban environment, except for the inner city area where the multiplicity of key destinations did not allow one to select one central point in Warsaw. District centres are usually anchored by local government head offices, shopping malls or educational institutions, especially universities. According to the Study of Conditions and Directions of Spatial Management (Rada m. st. Warszawy 2006: 96–100), district centres should be located so as to be easily accessible and well connected with the city centre and housing developments. At this point, it is necessary to highlight the fact that transport hubs strongly influence the city environment and often become district centres.

Local centres can be defined as multifunctional areas dedicated to residents of particular districts, which provide them with various services including retail, healthcare, education, culture, as well as places of recreation and community integration (Oddział Warszawski Stowarzyszenia Architektów Polskich 2015: 11–15). Local centres were determined on the basis of the Warsaw Local Centres project conducted by the Association of Polish Architects (Warsaw Branch of the Association of Polish Architects, 2015: 32–59).

Figure 3 shows the location of important points in the urban space of Warsaw which can be divided into two groups based on their place in the hierarchy of district and local centres.

Figure 3
Figure 3

District and local centres in Warsaw

Source: own study based on PZGiK data

Citation: Urban Development Issues 58, 1; 10.2478/udi-2018-0021

Among the selected points, the most numerous are those belonging to the group of department stores (Mirowskie Hall, Hala Marymont, Hala Wola, Hala Banacha, etc.), shopping centres, and marketplaces or bazaars (Różycki bazaar, Wolumen bazaar, Falenica marketplace, Bakalarka marketplace, etc.) as well as district councils which overweight the number of squares or community centres (KADR community centre, Artystyczny Dom Animacji, etc.). Moreover, a significant share have transport hubs which include railway and metro stations, but also universities (Warsaw University of Technology, Warsaw University, Józef Piłsudski University of Physical Education, War Studies University, etc.) and places of interest (Plac Zamkowy in front of The Royal Castle in Warsaw, PGE National Stadium, The Wilanów Palace, Children’s Memorial Health Institute or the Former Kino Femina cinema).

In addition to the fact that the distribution of the selected points is uneven between the west side and the east side of Warsaw, their number differs between particular districts. For example there are fewer centres in younger, outer districts which are still in the process of rapid development and urbanisation like Białołęka or Rembertów. However it is also noticeable that the number of półnts between central districts is unequal. The case of Praga Północ which is similarly close to Śródmieście as Wola or Ochota, but has a lower number of local and district centres, illustrates this situation the best.

Public transit time accessibility

Transit accessibility was measured on the basis of time travelled to the city centre (Warsaw University of Technology) or the centres identified above. The service area layers covering regions accessible within a given cost differed significantly depending on the time of day. The results of service area analyses show public transit accessibility at the following arrival times: 6:00, 7:00, 8:00 and 9:00 AM during the working day (Fig. 4).

Figure 4
Figure 4

Public transit time accessibility at (a) 6:00 a.m., (b) 7:00 a.m., (c) 8:00 a.m. and (d) 9:00 on a working day

Source: own study based on PZGiK data

Citation: Urban Development Issues 58, 1; 10.2478/udi-2018-0021

Differences in travel time could be observed on the borders of the intervals. Although the core, central part of Warsaw does not reflect strong variations in the time needed for travel, the areas along rail transit routes show strong dependence on the given time of day. The impact of rail transit can be observed on each of the maps, especially of the metro lines and two rail lines in the southern-eastern part of the city. To obtain a quantitative assessment of public transit accessibility in the morning peak, the average travel time isochrones were calculated on the basis of raster isochrones at 5 min intervals in the period 6:00 - 9:00 a.m. (Fig. 5). The colour scale is the same as on Figure 4, the blue line indicates a satisfactory 30 min travel time service area.

Figure 5
Figure 5

Public transit average time accessibility in the morning peak on a working day

Source: own study based on PZGiK data

Citation: Urban Development Issues 58, 1; 10.2478/udi-2018-0021

The map in Figure 5 shows that the area of the lowest, 15 min travel time is relatively small and covers an area that can also be reached within a 30 min walking distance. The satisfactory, 30 min travel time area covers both sides of the river, however, the River Vistula is a visible barrier for public transit accessibility. It is strongly influenced by the fact that The Warsaw University of Technology, used as the destination point in the study, is located on the left side of the river. Moreover, the main transit nodes are located on the left side of the river as well. In general, the right side of the river has a lower level of transit service to the city centre area located on the west side of the river. The strong influence of the metro lines and rail transport can be observed. Outside their service area, the average travel time from the external parts of the city can reach up to 90 min and higher.

Areas with a lower time accessibility to the city centre, but still close to it, can generally be divided into two groups. The first group includes areas closed for public transit, such as railway areas, cemeteries, parks, industrial areas and those also mostly closed to pedestrian traffic - airports. The second group consists of new, rapid developments - attractive in terms of location, nevertheless, not able to provide sufficient public transit service. E.g. the Czerniaków housing estate is exceptionally negative in the context of travel time. Located only 3 km in a south-easterly direction from the city centre, but with 45 min average travel time, it is intended for new, intensive housing investments, which might lead to increased traffic congestion.

With the use of the public transit time accessibility indicator (Fig. 6), highly populated areas, strategic in terms of public transit time, could be assigned. Areas with acceptable (30 min) time accessibility cover only 10% of the city area. Based on the population distribution data (for 2011), derived from the Central Statistical Office of Poland, it was calculated that 1 283 875 residents of Warsaw live outside the satisfactory area of 30 minutes average travel time to the city centre, which gives 74% of the total population of Warsaw. These areas are mostly located in large-panel system built settlements to the north of Warsaw. The low quality of transit service was also observed on the western edge of the Ursus district and in the Ursynów district, despite their rail connection with the city centre.

Figure 6
Figure 6

Public transit time accessibility indicator

Source: own study based on PZGiK data

Citation: Urban Development Issues 58, 1; 10.2478/udi-2018-0021

The second part of the study consisted of identification and analysis of the public transit accessibility of district and local centres. The evaluation of access to the desired destinations represented by the aforementioned centres is crucial for the city in terms of its proper functioning and polycentric development. The results of the analysis show significant differences in the spatial distribution of travel time with public transportation. The map shown in Figure 7 presents district and local centre locations and the time of accessing them from every place in Warsaw at 9 am on a working day. It may be clearly noticed that the centres are distributed unevenly. They occur mainly in the centre of the city and along the major transit routes, where the access time approximates 10 minutes. Satisfactory results for travel time isochrones cover more remote areas, such as Ursus and Włochy districts in the West, characterised with a planned urban layout, as well as areas with metro line stations. However, many service-deficient areas may also be indicated. They usually cover developments placed away from the major transit routes and close to Warsaw’s city limits. Nevertheless, critical areas such as part of Mokotów district near the River Vistula or Rembertów and Targówek located relatively close to the city centre also have excessive access time to district and local centres. Such a state of affairs is partially determined by the lack of centres in those areas and the lack of proper public transport connections between them and the nearest centres. Another peculiar phenomenon is the differentiation of public transport time accessibility to district and local centres on both sides of the Vistula. The number of centres in the west part of the city is far greater and the distribution of their locations is more regular.

Figure 7
Figure 7

Public transit time accessibility to district and local centres at 9 am on a working day

Source: own study based on PZGiK data

Citation: Urban Development Issues 58, 1; 10.2478/udi-2018-0021

Discussion

The main aim of the study was to analyse the quality of the public transport service in Warsaw. The model of public transport created on the basis of total travel time to the city centre or to the key, centre-forming destinations permits, with the use of the public transit time accessibility indicator, the identification of areas which are densely populated yet insufficiently serviced. Warsaw is very diverse in terms of services distribution and public transit accessibility, understood as a function of journey time. Public transit time accessibility is a simple measure of the whole system however it provides a basic, valuable assessment of its operation. The analysis, if supplemented with additional factors, may be an effective evaluation tool.

First of all, the public transit time accessibility map, the outcome of the analysis, presents an irregular shape of isochrones, which confirms the spatially diverse character of the phenomenon. It may be caused by different factors, both natural and infrastructural. One of the natural factors that affects the analysis of public transit time accessibility in Warsaw is the River Vistula splitting the city into two halves in its central area. Although there are several rail and road bridges, as well as an underground metro line crossing the river, the east side of the city is definitely poorly serviced as far as public transport is concerned (Fig. 5 and Fig. 6). However, according to A. Kostelecka (2015a: 10), only 23.2% of trips made by Warsaw inhabitants require the crossing of the River Vistula. A similar problem was presented by S. Goliszek and M. Połom (2016) based on the example of Szczecin. In their study, the authors noted that the fact that there are only two transit connections between the two sides of the River Odra makes it difficult to integrate the city and therefore the functioning of public transport. On the other hand, the outcomes of the analysis identify significant spatial and transit barriers, like airports or areas closed to transit. They do not however give an insight into the decreased level of mobility caused by terrain only accessible to a specific group of people e.g. allotment gardens or gated communities. Isolating a part of the urban tissue for a particular group of society is a problem clearly described in the literature (Domanowska 2014; Dymek & Bednorz 2017; Vesselinov, Cazessus & Falk 2007), as well as methods of modernisation including increasing public utility and decreasing spatial barriers (Szczęsny & Kimic 2012; Urząd m. st. Warszawy 2016). When used in an adjusted (local) scale, with network data containing information about fenced areas, public transit time accessibility could be a useful indicator for measuring the impact of closed areas on urban mobility.

The outcomes of the study in comparison with the public transport network leads to the conclusion that the rail transport system presents the major infrastructural factor in terms of the pattern of accessibility to the city centre. The outward expansion of isochrones seems to be determined by the course of rail lines. A similar conclusion was drawn during analysis of the most efficient time availability in Szczecin (Goliszek & Połom 2016) where the authors attributed the greatest impact on the lengthening or shortening of isochrones to the system of tram lines complemented by the bus network. On the other hand, rail transport is characterised by a good time-efficiency, significant passenger capacity and, at the same time, low running frequency. Assuming that below some level (3 vehicles/hour) passengers will not rely on the frequency of operation (Olszewski, Dybicz & Śleszyński 2013), it is suggested that one should extend the methodology with indicators fully describing the impact of the rail transit system.

Significant challenges were identified in providing sufficient public transit accessibility, these mostly occurring within the large-panel system-built settlements with high population density, which are found to the north of Warsaw. These challenges are commonly recognised in Poland (Rybka, Kozlowski, & Plewako 2007; Majewski and Beim 2008) and other Central and Eastern European countries (Melgaard et al. 2007). Due to the small area of coverage of the 30-minute travel time layer, the public transport system can be described as insufficient. Although the public transport modal share is relatively high in Warsaw, the constant occurrence of traffic congestion indicates that it may not be attractive enough to combat the problem.

Visualising processed data on maps enables many relations and phenomena to be analysed. However, in studying the locations of the centres, the observers are unable to conclude if they fulfil their role. Although the method of assessing public transport accessibility applied in research served to evaluate the time to get to district and local centres, it does not give a full insight into real time journeys not connected with a job or studying destinations and the effect of the afternoon traffic peak on local centres. The public transit accessibility indicator, used in the study, gives a brief insight into the relationship between population density distribution and public transit operation. This approach enables one to focus on the physical aspects of the public transportation system, capturing the value of psychical proximity, but lacking functional connectivity, considered as the Transit Adjacent Development approach (Cervero, Ferrell & Murphy 2002). As a shift to a mixed-used, pedestrian friendly and compact design of areas in the neighbourhood of stations, called Transit-Oriented Development (Renne 2009), has been recommended it is also worthwhile considering other factors in dynamic public transit accessibility analysis: the accessibility of transit nodes, place intensity, and diversity characteristics (Vale 2015) and other factors describing a population’s travel behaviour. The source data processed in the study may be characterised as generalised and approximate. This is the reason for many limitations on the outcome. First of all, the analysis refers to a 3-hour period during a single day. Timetables are the input data for the public transit course. Therefore, the study does not consider the real time situation, traffic jams and unplanned schedule variations caused by unforeseen events. What is more, the population statistics from the 2011 census do not show precisely the real distribution of inhabitants and do not fully correspond with the schedule from 2016 that is analysed. Furthermore, visualisation and storage of spatial data requires its proper classification, normalisation and generalisation. The locations of local and district centres are represented by point symbols. Their spatial approximation affects the process of evaluation of their public transport accessibility. Moreover, definition of the city centre is problematic in terms of service distribution and for the purpose of identification of the destination facilities. The approach proposed in the study (determining one, precise point) gives very different outcomes from that considering the centre as the whole inner city area (Zarząd Transportu Miejskiego w Warszawie 2017). It is also important to take into account the fact that the population density distribution data processed in this study is classified into polygons that define statistical circuits. The results of the study are very much determined by the way the data are assembled and classified.

The results of the analysis give basic characteristics of public transit time accessibility in Warsaw. The values of the calculated accessibility indicator varied in relation to its spatial distribution, which was connected to land use, spatial development patterns and therefore to the population distribution. The simulation showed significant differences in the spatial distribution of access to the city centre and to the local centres. It proves to be the case that peripheral areas can function effectively in terms of public transit accessibility if the principle of policentricity and balanced development of the settlement structure are preserved. Preparation of more precise and up to date data (population distribution, spatial barriers, etc.), inclusion of other transit operation factors (real time journeys, timetable modifications, etc.) and more precise, aerial centre designation might give more reliable results and lead to the implementation of a proper strategic transportation policy in Warsaw.

Conclusions

This paper presents the scope of application of the dynamic time accessibility assessment based on the example of Warsaw. The following study assumes that the measure is feasible for basic analysis, however, additional indicators should be considered for a reliable assessment.

There is a noticeable deficiency of district and local centres in new developments. The existing centres have overlaps of transport nodes and well communicated areas. Future public transport policy should be proactively managed in relation to the location of new centres. When the system seems to be insufficient to connect the area with the central part of the city, local and district centres fulfil a crucial role.

The results of the analysis presented on Figure 7 confirmed the dynamic character of public transit time accessibility. The isochrones presenting proper time values differ in shape at different times.

Public transit time accessibility in Warsaw shows strong spatially varied features (Figure 5 and Figure 6). The main reasons for the irregular distribution of the phenomenon are the location of the River Vistula as a natural barrier and of a public rail transport system as an infrastructural factor.

Public transit time accessibility assessment provides a basic insight into system functionality. Other factors should be included, such as the public transport system and land use characteristics, the impact of the suburban areas, planned public transport and building investments, new travel trends, the influence of rail transit. The model should be extended with traffic data.

The data concerning the size of traffic jams and the number of cars coming to Warsaw every day shows the significance of carrying out such studies and managing metropolitan transport policy properly. The expanded analysis of public transport accessibility in Warsaw may provide a strategic tool in creating spatial policy integrated with the development of transport infrastructure.

Acknowledgements

We would like to acknowledge our special recognition to the Inovatica company for providing GTFS data for Warsaw.

References

  • Benenson I. Martens K. Rofé Y. & Kwatler A. (2011) Public transport versus private car GIS-based estimation of accessibility applied to the Tel Aviv metropolitan area. Available from: https://link.springer.com/content/pdf/10.1007%2Fs00168-010-0392-6.pdf [accessed: 27.04.2017].

  • Cervero R. Ferrell C. & Murphy S. (2002) Transit-oriented development and joint development in the United States: A literature review Transportation Cooperative Research Program TCRP) Report 52 Transportation Research Board Washington DC 6. Available from: http://onlinepubs.trb.org/onlinepubs/tcrp/tcrp_rrd_52.pdf [accessed: 8.10.2017].

  • Cervero R. Murphy S. Ferrell C. Goguts N. Tsai Y-H. Arrington G.B. Boroski J. Smith-Heimer J. Golem R. Peninger P. Nakajima E. Chui E. Dunphy R. Myers M. & McKay S. (2004) Transit-Oriented Development in the United States: ExperiencesChallengesand Prospects Transportation Cooperative Research Program (TCRP) Report 102 Transportation Research Board Washington. Available from: https://www.valleymetro.org/sites/default/files/legacy-im-ages/uploads/general_publications/TCRP-Report-102_TOD-in-the-US-Experiences-Challenges-and-Prospects_10-04.pdf [accessed: 8.10.2017].

  • Cox W. (2012) Urban Travel and Urban Population Density JOURNEYS. Sharing Urban Transport Solutions 9 19–28. Available from: https://www.lta.gov.sg/ltaacademy/doc/JOURNEYS_Nov%202012.pdf [accessed: 27.04.2017].

  • Domanowska M. (2014) Odnowa terenów zieleni w Miniprogramach Rewitalizacji Dzielnic Warszawy Zeszyty Naukowe. Inżynieria Środowiska/Uniwersytet Zielonogórski 154 (34) 74–86 [in Polish with English abstract].

  • Dymek D. & Bednorz L. (2017) Zagospodarowanie Rodzinnych Ogrodów Działkowych (ROD) na przykładzie ROD im. Józefa Chociszewskiego w Poznaniu Studia Miejskie 25 133–147 [in Polish with English abstract].

  • ESRI (2017) Service area analysis. Available from: http://desktop.arcgis.com/en/arcmap/latest/extensions/network-analyst/service-area.htm [accessed: 27.04.2017].

  • ESRI (2018) Add GTFS to a Network Dataset. Available from: https://esri.github.io/public-transit-tools/AddGTFStoaNetworkDataset.html [accessed: 19.06.2018].

  • Fransen K. Neutens T. Farber S. De Maeyer P. Deruyter G. & Witloc F. (2015) Identifying public transport gaps using time-dependent accessibility levels Journal of Transport Geography 48 176–187.

    • Crossref
    • Export Citation
  • Goliszek S. & Połom M. (2016) The use of general transit feed specification (GTFS) application to identify deviations in the operation of public transport at morning peak hours on the example of Szczecin Europa XXI 31 51–60.

    • Crossref
    • Export Citation
  • Kostelecka A. (2015a) Warszawskie Badanie Ruchu 2015 wraz z opracowaniem modelu ruchu. Synteza. Available from: http://transport.um.warszawa.pl/sites/default/files/WBR%202015%20SYNTEZA%20POL.pdf [accessed 14.05.2017] [in Polish].

  • Kostelecka A. (2015b) Warszawskie Badanie Ruchu 2015 wraz z opracowaniem modelu ruchu. Raport z etapu III. Opracowanie wyników badań. Available from: http://transport.um.warszawa.pl/sites/default/files/WBR%202015.%20Etap%20III.%20Raport.%20Wersja%2006_2016.pdf [accessed: 27.04.2017] [in Polish].

  • Lei T. L. & Church R. L. (2010) Mapping transit-based access: integrating GISroutes and schedules. International Journal of Geographical Information Science 24 (2) 283–304.

    • Crossref
    • Export Citation
  • Majewski B. & Beim M. (2008) Dostępność komunikacji publicznej w Poznaniu (Series „Rozwój Regionalny i Polityka Regionalna”) Biuletyn Instytutu Geografii Społeczno-Ekonomicznej i Gospodarki Przestrzennej Uniwersytetu im. Adama Mickiewicza w Poznaniu 3 115–124.

  • Melgaard E. Hadjimichael G. Almeida & M. Verhoef L. eds. (2007) COST C16 Improving the Quality of Existing Urban Building Envelopes: Needs. IOS Press Amsterdam.

  • Mishra S. & Welch T. F. (2013) A joint travel demand and environmental model to incorporate emission pricing for large transportation networks. Available from: http://smartgrowth.umd.edu/assets/documents/re-search/mishrawelch_emissionpricing_2011.pdf [accessed: 27.04.2017].

  • Oddział Warszawski Stowarzyszenia Architektów Polskich (2015) Centra Lokalne. Studium koncepcyjne dotyczące centrów lokalnych w Warszawie 11–15 & 32–59. Available from: http://sarp.warszawa.pl/wordpress/wp-content/uploads/2015/11/CENTRA-LOKALNE-OW-SARP-2015-wersja-elektroniczna.pdf [Accessed: 27.04.2017] [in Polish].

  • Olszewski P. Dybicz T. & Śleszyński P. (2013) Proponowane miary dostępności czasowej w transporcie publicznym Przegląd Komunikacyjny 12 10–17 [in Polish with English abstract].

  • Rada m. st. Warszawy (2006) Uchwała nr LXXXII/2746/2006 z dnia 10 października 2006 r. w sprawie studium uwarunkowań i kierunków zagospodarowania przestrzennego m. st. Warszawy ze zmianami. Urząd m. st. Warszawy Warszawa. Available from: http://bip.warszawa.pl/Menu_przedmiotowe/ogloszenia/plany_zagospodarowania/Studium.htm [accessed: 27.04.2017] [in Polish].

  • Renne J. L. (2009) From transit-adjacent to transit-oriented development Local Environment 14 (1) 1–15.

    • Crossref
    • Export Citation
  • Rybka A. Kozlowski A. & Plewako Z. (2007) General Overview of ProblemsNeeds and Solutions in the Polish Urban Building Envelopes[in:] E. Melgaard G. Hadjimichael M. Almeida & L. Verhoef eds. COST C16 Improving the Quality of Existing Urban Building Envelopes: Needs IOS Press Amsterdam 109–119.

  • Sanchez T. W. & Brenman M. (2007) The Right to Transportation. Moving to Equality APA Planners Press Chicago.

  • Szczęsny M. & Kimic K. (2012) Możliwości adaptacji terenów ogrodów działkowych na obiekty ogólnodostępne na przykładzie rodzinnego ogrodu działkowego przy Kanale Gocławskim w Warszawie Czasopismo Techniczne. Architektura 109 (8-A) 179–185 [in Polish with English abstract].

  • Szeląg M. (2015) Wstępne przetwarzanie i analiza danych. Available from: http://www.cs.put.poznan.pl/mszelag/Teaching/OW/wyklad_02/02_wstepne_przetwarzanie_danych.pdf [accessed: 16.06.2018][in Polish].

  • Transport for London (2010) Measuring Public Transport Accessibility LevelsPTALsSummary. Available from: https://files.datapress.com/london/dataset/public-transport-accessibility-levels/PTAL-methodology.pdf [accessed: 27.04.2017].

  • Urząd m. st. Warszawy (2015) Plan zrównoważonego rozwoju transportu zbiorowego dla m. st. Warszawy z uwzględnieniem publicznego transportu zbiorowego organizowanego na podstawie porozumień z gminami sąsiadującymi… Available from: http://transport.um.warszawa.pl/sites/default/files/Plan%20Transportowy_tekst%20ze%20spisem%20ter%C5%9B-ci_0.pdf [Accessed 17th February 2018] [in Polish].

  • Urząd m. st. Warszawy (2016) Rodzinne ogrody działkowe w planowaniu i zagospodarowaniu przestrzennym presentation made by Architecture and City Planning Department in Warsaw 15th April 2016. Available from: https://architektura.um.warszawa.pl/sites/default/files/files/ROD_w_planowaniu_i_zagospodarowaniu_przestrzennym.pdf [Accessed 30th September 2017] [in Polish].

  • Vale D. S. (2015) Transit-oriented developmentintegration of land use and transportand pedestrian accessibility: Combining node-place model with pedestrian shed ratio to evaluate and classify station areas in Lisbon Journal of transport geography 45 70–80.

    • Crossref
    • Export Citation
  • Vesselinov E. Cazessus M. & Falk W. (2007) Gated communities and spatial inequality. Journal of Urban Affairs 29 (2) 109–127.

    • Crossref
    • Export Citation
  • Zarząd Transportu Miejskiego w Warszawie (2017) Warszawa. Czas dojazdu do centrum. Available from: https://www.facebook.com/wtp.warszawa/posts/1526657634040083 [accessed: 3.10.2017].

Internet sources

  • Geostatistics portal: https://geo.stat.gov.pl/inspire [accessed 27.04.2017].

  • OpenStreetMap dataset: http://download.geofabrik.de/europe/poland/mazowieckie.html [accessed: 5.10.2017].

  • GTFS Data Exchange: http://www.gtfs-data-exchange.com/ [accessed: 27.04.2017].

  • Public transport accessibility level: https://en.wikipedia.org/wiki/Public_transport_accessibility_level [accessed: 27.04.2017].

  • TomTom Traffic Index website: http://www.tomtom.com/en_gb/traf-ficindex/list?citySize=LARGE&continent=ALL&country=ALL [accessed: 22.05.2017].

  • Transitland website - Feed Registry: https://transit.land/feed-registry/ [accessed: 27.04.2017].

  • Inovatica website: http://transitart.io [accessed: 27.04.2017].

If the inline PDF is not rendering correctly, you can download the PDF file here.

  • Benenson I. Martens K. Rofé Y. & Kwatler A. (2011) Public transport versus private car GIS-based estimation of accessibility applied to the Tel Aviv metropolitan area. Available from: https://link.springer.com/content/pdf/10.1007%2Fs00168-010-0392-6.pdf [accessed: 27.04.2017].

  • Cervero R. Ferrell C. & Murphy S. (2002) Transit-oriented development and joint development in the United States: A literature review Transportation Cooperative Research Program TCRP) Report 52 Transportation Research Board Washington DC 6. Available from: http://onlinepubs.trb.org/onlinepubs/tcrp/tcrp_rrd_52.pdf [accessed: 8.10.2017].

  • Cervero R. Murphy S. Ferrell C. Goguts N. Tsai Y-H. Arrington G.B. Boroski J. Smith-Heimer J. Golem R. Peninger P. Nakajima E. Chui E. Dunphy R. Myers M. & McKay S. (2004) Transit-Oriented Development in the United States: ExperiencesChallengesand Prospects Transportation Cooperative Research Program (TCRP) Report 102 Transportation Research Board Washington. Available from: https://www.valleymetro.org/sites/default/files/legacy-im-ages/uploads/general_publications/TCRP-Report-102_TOD-in-the-US-Experiences-Challenges-and-Prospects_10-04.pdf [accessed: 8.10.2017].

  • Cox W. (2012) Urban Travel and Urban Population Density JOURNEYS. Sharing Urban Transport Solutions 9 19–28. Available from: https://www.lta.gov.sg/ltaacademy/doc/JOURNEYS_Nov%202012.pdf [accessed: 27.04.2017].

  • Domanowska M. (2014) Odnowa terenów zieleni w Miniprogramach Rewitalizacji Dzielnic Warszawy Zeszyty Naukowe. Inżynieria Środowiska/Uniwersytet Zielonogórski 154 (34) 74–86 [in Polish with English abstract].

  • Dymek D. & Bednorz L. (2017) Zagospodarowanie Rodzinnych Ogrodów Działkowych (ROD) na przykładzie ROD im. Józefa Chociszewskiego w Poznaniu Studia Miejskie 25 133–147 [in Polish with English abstract].

  • ESRI (2017) Service area analysis. Available from: http://desktop.arcgis.com/en/arcmap/latest/extensions/network-analyst/service-area.htm [accessed: 27.04.2017].

  • ESRI (2018) Add GTFS to a Network Dataset. Available from: https://esri.github.io/public-transit-tools/AddGTFStoaNetworkDataset.html [accessed: 19.06.2018].

  • Fransen K. Neutens T. Farber S. De Maeyer P. Deruyter G. & Witloc F. (2015) Identifying public transport gaps using time-dependent accessibility levels Journal of Transport Geography 48 176–187.

    • Crossref
    • Export Citation
  • Goliszek S. & Połom M. (2016) The use of general transit feed specification (GTFS) application to identify deviations in the operation of public transport at morning peak hours on the example of Szczecin Europa XXI 31 51–60.

    • Crossref
    • Export Citation
  • Kostelecka A. (2015a) Warszawskie Badanie Ruchu 2015 wraz z opracowaniem modelu ruchu. Synteza. Available from: http://transport.um.warszawa.pl/sites/default/files/WBR%202015%20SYNTEZA%20POL.pdf [accessed 14.05.2017] [in Polish].

  • Kostelecka A. (2015b) Warszawskie Badanie Ruchu 2015 wraz z opracowaniem modelu ruchu. Raport z etapu III. Opracowanie wyników badań. Available from: http://transport.um.warszawa.pl/sites/default/files/WBR%202015.%20Etap%20III.%20Raport.%20Wersja%2006_2016.pdf [accessed: 27.04.2017] [in Polish].

  • Lei T. L. & Church R. L. (2010) Mapping transit-based access: integrating GISroutes and schedules. International Journal of Geographical Information Science 24 (2) 283–304.

    • Crossref
    • Export Citation
  • Majewski B. & Beim M. (2008) Dostępność komunikacji publicznej w Poznaniu (Series „Rozwój Regionalny i Polityka Regionalna”) Biuletyn Instytutu Geografii Społeczno-Ekonomicznej i Gospodarki Przestrzennej Uniwersytetu im. Adama Mickiewicza w Poznaniu 3 115–124.

  • Melgaard E. Hadjimichael G. Almeida & M. Verhoef L. eds. (2007) COST C16 Improving the Quality of Existing Urban Building Envelopes: Needs. IOS Press Amsterdam.

  • Mishra S. & Welch T. F. (2013) A joint travel demand and environmental model to incorporate emission pricing for large transportation networks. Available from: http://smartgrowth.umd.edu/assets/documents/re-search/mishrawelch_emissionpricing_2011.pdf [accessed: 27.04.2017].

  • Oddział Warszawski Stowarzyszenia Architektów Polskich (2015) Centra Lokalne. Studium koncepcyjne dotyczące centrów lokalnych w Warszawie 11–15 & 32–59. Available from: http://sarp.warszawa.pl/wordpress/wp-content/uploads/2015/11/CENTRA-LOKALNE-OW-SARP-2015-wersja-elektroniczna.pdf [Accessed: 27.04.2017] [in Polish].

  • Olszewski P. Dybicz T. & Śleszyński P. (2013) Proponowane miary dostępności czasowej w transporcie publicznym Przegląd Komunikacyjny 12 10–17 [in Polish with English abstract].

  • Rada m. st. Warszawy (2006) Uchwała nr LXXXII/2746/2006 z dnia 10 października 2006 r. w sprawie studium uwarunkowań i kierunków zagospodarowania przestrzennego m. st. Warszawy ze zmianami. Urząd m. st. Warszawy Warszawa. Available from: http://bip.warszawa.pl/Menu_przedmiotowe/ogloszenia/plany_zagospodarowania/Studium.htm [accessed: 27.04.2017] [in Polish].

  • Renne J. L. (2009) From transit-adjacent to transit-oriented development Local Environment 14 (1) 1–15.

    • Crossref
    • Export Citation
  • Rybka A. Kozlowski A. & Plewako Z. (2007) General Overview of ProblemsNeeds and Solutions in the Polish Urban Building Envelopes[in:] E. Melgaard G. Hadjimichael M. Almeida & L. Verhoef eds. COST C16 Improving the Quality of Existing Urban Building Envelopes: Needs IOS Press Amsterdam 109–119.

  • Sanchez T. W. & Brenman M. (2007) The Right to Transportation. Moving to Equality APA Planners Press Chicago.

  • Szczęsny M. & Kimic K. (2012) Możliwości adaptacji terenów ogrodów działkowych na obiekty ogólnodostępne na przykładzie rodzinnego ogrodu działkowego przy Kanale Gocławskim w Warszawie Czasopismo Techniczne. Architektura 109 (8-A) 179–185 [in Polish with English abstract].

  • Szeląg M. (2015) Wstępne przetwarzanie i analiza danych. Available from: http://www.cs.put.poznan.pl/mszelag/Teaching/OW/wyklad_02/02_wstepne_przetwarzanie_danych.pdf [accessed: 16.06.2018][in Polish].

  • Transport for London (2010) Measuring Public Transport Accessibility LevelsPTALsSummary. Available from: https://files.datapress.com/london/dataset/public-transport-accessibility-levels/PTAL-methodology.pdf [accessed: 27.04.2017].

  • Urząd m. st. Warszawy (2015) Plan zrównoważonego rozwoju transportu zbiorowego dla m. st. Warszawy z uwzględnieniem publicznego transportu zbiorowego organizowanego na podstawie porozumień z gminami sąsiadującymi… Available from: http://transport.um.warszawa.pl/sites/default/files/Plan%20Transportowy_tekst%20ze%20spisem%20ter%C5%9B-ci_0.pdf [Accessed 17th February 2018] [in Polish].

  • Urząd m. st. Warszawy (2016) Rodzinne ogrody działkowe w planowaniu i zagospodarowaniu przestrzennym presentation made by Architecture and City Planning Department in Warsaw 15th April 2016. Available from: https://architektura.um.warszawa.pl/sites/default/files/files/ROD_w_planowaniu_i_zagospodarowaniu_przestrzennym.pdf [Accessed 30th September 2017] [in Polish].

  • Vale D. S. (2015) Transit-oriented developmentintegration of land use and transportand pedestrian accessibility: Combining node-place model with pedestrian shed ratio to evaluate and classify station areas in Lisbon Journal of transport geography 45 70–80.

    • Crossref
    • Export Citation
  • Vesselinov E. Cazessus M. & Falk W. (2007) Gated communities and spatial inequality. Journal of Urban Affairs 29 (2) 109–127.

    • Crossref
    • Export Citation
  • Zarząd Transportu Miejskiego w Warszawie (2017) Warszawa. Czas dojazdu do centrum. Available from: https://www.facebook.com/wtp.warszawa/posts/1526657634040083 [accessed: 3.10.2017].

  • Geostatistics portal: https://geo.stat.gov.pl/inspire [accessed 27.04.2017].

  • OpenStreetMap dataset: http://download.geofabrik.de/europe/poland/mazowieckie.html [accessed: 5.10.2017].

  • GTFS Data Exchange: http://www.gtfs-data-exchange.com/ [accessed: 27.04.2017].

  • Public transport accessibility level: https://en.wikipedia.org/wiki/Public_transport_accessibility_level [accessed: 27.04.2017].

  • TomTom Traffic Index website: http://www.tomtom.com/en_gb/traf-ficindex/list?citySize=LARGE&continent=ALL&country=ALL [accessed: 22.05.2017].

  • Transitland website - Feed Registry: https://transit.land/feed-registry/ [accessed: 27.04.2017].

  • Inovatica website: http://transitart.io [accessed: 27.04.2017].

Search
Journal information
Figures
  • View in gallery

    Public transportation system and road network in Warsaw

    Source: own study based on: PZGiK and OpenStreetMap data (OpenStreetMap…)

  • View in gallery

    Formula for normalized values

    Source: Szeląg 2015: 27

  • View in gallery

    District and local centres in Warsaw

    Source: own study based on PZGiK data

  • View in gallery

    Public transit time accessibility at (a) 6:00 a.m., (b) 7:00 a.m., (c) 8:00 a.m. and (d) 9:00 on a working day

    Source: own study based on PZGiK data

  • View in gallery

    Public transit average time accessibility in the morning peak on a working day

    Source: own study based on PZGiK data

  • View in gallery

    Public transit time accessibility indicator

    Source: own study based on PZGiK data

  • View in gallery

    Public transit time accessibility to district and local centres at 9 am on a working day

    Source: own study based on PZGiK data

Cited By
Metrics
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 933 811 25
PDF Downloads 125 96 3