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Evaluating transport externalities of urban growth: a critical review of scenario-based planning methods

Abstract

Urban growth is an important phenomenon, which is taking place on an unprecedented scale, and its impacts on society and the environment are evident. In theory, an evaluation of such urban growth through scenario-based planning helps planners to better assess the future impacts of growth and develop better policies and plans. Within this context, the assessment of transport impacts is particularly important as transport plays an important role in shaping urban growth. Additionally, transport sector alone is responsible for about one-third of the greenhouse gas emissions of cities, which has detrimental effects on the environment, economy, community health, and quality of life. In practice, however, scarce evidence exists outlining the challenges of scenario-based evaluation and how to best address these while modelling the transport impacts of various urban growth scenarios. This research addresses these gaps in the literature and assesses the effectiveness of scenario-based planning methods that are used for modelling the transport impacts of alternative urban growth scenarios. The methodological approach of the study consists of a critical review of the key literature and relevant methods that are commonly used to assess transport impacts. The results of this analysis highlight limitations of existing methods for effectively evaluating transport externalities of urban growth scenarios. The findings suggest that among many reviewed models, the ILUTE, URBANSIM and TRANUS simulation models are identified as significant ones. However, due to various limitations of the former two, TRANUS is noted as the most suitable one for evaluating the transport impacts of urban growth scenarios.

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Fig. 1

Derived from Lindgren and Bandhold (2009)

References

  • Abdel-Galil RES (2012) Desert reclamation, a management system for sustainable urban expansion. Prog Plan 78:151–206. doi:10.1016/j.progress.2012.04.003

    Article  Google Scholar 

  • Al-shalabi M, Billa L, Pradhan B, Mansor S, Al-sharif AA (2013) Modelling urban growth evolution and land-use changes using GIS-based cellular automata and SLEUTH models: the case of Sana’a metropolitan city, Yemen. Environ Earth Sci 70:425–437. doi:10.1007/s12665-012-2137-6

    Article  Google Scholar 

  • Armstrong JM, Khan AM (2004) Modelling urban transportation emissions: role of GIS. Comput Environ Urban Syst 28:421–433. doi:10.1016/S0198-9715(02)00070-4

    Article  Google Scholar 

  • Ayad HM, Saad Allah DM, Abd ElAzeem HS (2012) Investigating urban growth scenarios in Wadi El Natrun area, Egypt, using the UPlan land use allocation model. J Land Use Sci 8:304–320. doi:10.1080/1747423X.2012.667449

    Article  Google Scholar 

  • Aysan M, Demir O, Altan Z, Dokmeci V (1997) Industrial decentralization in Istanbul and its impact on transport. J Urban Plan Dev 123:40–58. doi:10.1061/(ASCE)0733-9488(1997)123:3(40)

    Article  Google Scholar 

  • Bailey K, Grossardt T, Pride-Wells M (2007) Community design of a light rail transit-oriented development using casewise visual evaluation (CAVE). Socio Econ Plan Sci 41:235–254. doi:10.1016/j.seps.2006.04.002

    Article  Google Scholar 

  • Banister D, Berechman J (2003) Transport investment and economic development. Routledge, New York

    Google Scholar 

  • Bartholomew K, Ewing R (2009) Land use transportation scenarios and future vehicle travel and land consumption: a Meta-Analysis. Am Plan Assoc J Am Plan Assoc 75:13–27. doi:10.1080/01944360802508726

    Article  Google Scholar 

  • Beardsley K, Thorne JH, Roth NE, Gao S, McCoy MC (2009) Assessing the influence of rapid urban growth and regional policies on biological resources. Landsc Urban Plan 93:172–183. doi:10.1016/j.landurbplan.2009.07.003

    Article  Google Scholar 

  • Bhatta B (2010) Causes and Consequences of Urban Growth and Sprawl. In:  Analysis of Urban Growth and Sprawl from Remote Sensing Data, vol 1st. Springer, DE, pp 17–36. doi:10.1007/978-3-642-05299-6

  • Bowman JL, Ben-Akiva ME (2001) Activity-based disaggregate travel demand model system with activity schedules. Transp Res Part A Policy Pract 35:1–28. doi:10.1016/S0965-8564(99)00043-9

    Article  Google Scholar 

  • Bracken, I (2014) Urban planning methods: Research and policy analysis. Routledge

  • Brown AL, Affum JK (2002) A GIS-based environmental modelling system for transportation planners. Comput Environ Urban Syst 26:577–590. doi:10.1016/S0198-9715(01)00016-3

    Article  Google Scholar 

  • Burke M, Li T, Dodson J (2011) What happens when government workers move to the suburbs?: impact on transport of planned decentralization of employment in Brisbane, Australia. Transp Res Rec J Transp Res Board 2255:110–116. doi:10.3141/2255-12

    Article  Google Scholar 

  • Button KJ (1994) Special issue transport externalities alternative approaches toward containing transport externalities: an international comparison. Transp Res Part A Policy Pract 28:289–305. doi:10.1016/0965-8564(94)90004-3

    Article  Google Scholar 

  • Cervero R (2006) Alternative approaches to modeling the travel-demand impacts of smart growth. Am Plan Assoc J Am Plan Assoc 72:285–295

    Article  Google Scholar 

  • Chakrabarty BK (2001) Urban management: concepts, principles, techniques and education. Cities 18:331–345. doi:10.1016/S0264-2751(01)00026-9

    Article  Google Scholar 

  • Chakraborty A, Mishra S (2013) Land use and transit ridership connections: implications for state-level planning agencies. Land Use Policy 30:458–469. doi:10.1016/j.landusepol.2012.04.017

    Article  Google Scholar 

  • Chen T-C, Huang S-L (1998) Towards a symbiosis: urban development and environmental quality in the Taipei metropolitan region. J Environ Plan Manag 41:77–94. doi:10.1080/09640569811803

    Article  Google Scholar 

  • Choe K, Laquian AA (2008) City cluster development: toward an urban-led development strategy for Asia. Asian Development Bank, Mandaluyong

    Google Scholar 

  • Correia FN, Da Graça SM, Da Silva FN, Ramos I (1999) Floodplain management in urban developing areas. Part I. Urban growth scenarios and land-use controls. Water Resour Manag 13:1–21. doi:10.1023/A:1008097403587

    Article  Google Scholar 

  • Corvalan CF, ebrary I, World Health O (2005) Ecosystems and human well-being: a report of the millennium ecosystem assessment. vol Book, Whole. World Health Organization. http://www.millenniumassessment.org/documents/document.356.aspx.pdf

  • Dark SJ, Bram D (2007) The modifiable areal unit problem (MAUP) in physical geography. Prog Phys Geogr 31:471–479. doi:10.1177/0309133307083294

    Article  Google Scholar 

  • De Ridder K et al (2008) Simulating the impact of urban sprawl on air quality and population exposure in the German Ruhr area. Part II: development and evaluation of an urban growth scenario. Atmos Environ 42:7070–7077. doi:10.1016/j.atmosenv.2008.06.044

    Article  CAS  Google Scholar 

  • De Vos J, Witlox F (2013) Transportation policy as spatial planning tool; reducing urban sprawl by increasing travel costs and clustering infrastructure and public transportation. J Transp Geogr 33:117–125. doi:10.1016/j.jtrangeo.2013.09.014

    Article  Google Scholar 

  • Dizdaroglu D, Yigitcanlar T (2014) A parcel-scale assessment tool to measure sustainability through urban ecosystem components: the MUSIX model. Ecol Ind 41:115–130. doi:10.1016/j.ecolind.2014.01.037

    Article  Google Scholar 

  • Dizdaroglu D, Yigitcanlar T (2016) Integrating urban ecosystem sustainability assessment into policy-making: insights from the Gold Coast City. J Environ Plan Manag 59:1982–2006. doi:10.1080/09640568.2015.1103211

    Google Scholar 

  • Dizdaroglu D, Yigitcanlar T, Dawes L (2012) A micro-level indexing model for assessing urban ecosystem sustainability. Smart Sustain Built Environ 1:291–315. doi:10.1108/20466091211287155

    Article  Google Scholar 

  • Dobranskyte-Niskota A, Perujo A, Pregl M (2007). Indicators to assess sustainability of transportation activities. European Commission Joint Research Centre Institute for Environment and Sustainability, Ispra

    Google Scholar 

  • Duque JAG, Panagopoulos T (2010) Urban planning throughout environmental quality and human well-being. Spat Organ Dyn Discuss Pap 4:7–20

    Google Scholar 

  • Dur F, Yigitcanlar T (2015) Assessing land-use and transport integration via a spatial composite indexing model. Int J Environ Sci Technol 12:803–816. doi:10.1007/s13762-013-0476-9

    Article  Google Scholar 

  • Dur F, Yigitcanlar T, Bunker J (2014) A spatial-indexing model for measuring neighbourhood-level land-use and transport integration. Environ Plan 41:792–812. doi:10.1068/b39028

    Article  Google Scholar 

  • Dutta P, Saujot M, Arnaud E, Lefevre B, Prados E (2012) Uncertainty propagation and sensitivity analysis during calibration of TRANUS, an integrated land use and transport model. In: ICURPT 2012-International Conference on Urban, Regional Planning and Transportation, vol 65

  • Duvarci Y, Yigitcanlar T, Mizokami S (2015) Transportation disadvantage impedance indexing: a methodological approach to reduce policy shortcomings. J Transport Geogr 48:61–75. doi:10.1016/j.jtrangeo.2015.08.014

    Article  Google Scholar 

  • Feng X, Zhang J, Fujiwara A (2009) Adding a new step with spatial autocorrelation to improve the four-step travel demand model with feedback for a developing city. Int Assoc Traffic Saf Sci Res 33:44–54. doi:10.1016/S0386-1112(14)60236-3

    Google Scholar 

  • Fertner C, Jørgensen G, Nielsen TS (2012) Land use scenarios for Greater Copenhagen: modelling the impact of the Fingerplan. J Settl Spat Plan 3:1–10

    Google Scholar 

  • Feudo FL (2014) How to Build an alternative to sprawl and auto-centric development model through a TOD scenario for the North-Pas-de-Calais region? Lessons from an integrated transportation-land use modelling. Transp Res Proced 4:154–177. doi:10.1016/j.trpro.2014.11.013

    Article  Google Scholar 

  • Fotheringham AS, Wong DWS (1991) The modifiable areal unit problem in multivariate statistical analysis. Environ Plan A 23:1025–1044

    Article  Google Scholar 

  • Gärling T, Schuitema G (2007) Travel demand management targeting reduced private car use: effectiveness, public acceptability and political feasibility. J Soc Issues 63:139–153

    Article  Google Scholar 

  • Goonetilleke A, Yigitcanlar T, Ayoko GA, Egodawatta P (2014) Sustainable urban water environment: climate, pollution and adaptation. Edward Elgar Publishing, Northampton

    Book  Google Scholar 

  • Gwilliam KM (2002) Cities on the move: a world bank urban transport strategy review. World Bank Publications, Washington, DC

    Google Scholar 

  • Harries C (2003) Correspondence to what? Coherence to what? What is good scenario-based decision-making? Technol Forecast Soc Change 70:797–817. doi:10.1016/S0040-1625(03)00023-4

    Article  Google Scholar 

  • Haslauer E, Biberacher M, Blaschke T (2012) GIS-based backcasting: an innovative method for parameterisation of sustainable spatial planning and resource management. Futures 44:292–302. doi:10.1016/j.futures.2011.10.012

    Article  Google Scholar 

  • Hatzopoulou M, Miller EJ (2010) Linking an activity-based travel demand model with traffic emission and dispersion models: transport’s contribution to air pollution in Toronto. Transp Res Part D Transp Environ 15:315–325. doi:10.1016/j.trd.2010.03.007

    Article  Google Scholar 

  • Healey P (2001) Planning theory: interaction with institutional contexts. In: Baltes NJSB (ed) International encyclopedia of the social and behavioral sciences. Pergamon, Oxford, pp 11485–11491. doi:10.1016/B0-08-043076-7/04432-6

    Chapter  Google Scholar 

  • Hensher D (2002) A systematic assessment of the environmental impacts of transport policy. Environ Resour Econ 22:185–217. doi:10.1023/A:1015527601997

    Article  Google Scholar 

  • Hu R (2015) Sustainability and competitiveness in Australian cities. Sustainability 7:1840–1860. doi:10.3390/su7021840

    Article  Google Scholar 

  • Hua L, Tang L, Cui S, Yin K (2014) Simulating urban growth using the SLEUTH model in a coastal peri-urban district in China. Sustainability 6:3899–3914. doi:10.3390/su6063899

    Article  Google Scholar 

  • Hunt JD, Kriger DS, Miller EJ (2005) Current operational urban land-use–transport modelling frameworks: a review. Transp Rev 25:329–376

    Article  Google Scholar 

  • Jantz CA, Goetz SJ, Shelley MK (2004) Using the SLEUTH urban growth model to simulate the impacts of future policy scenarios on urban land use in the Baltimore—Washington metropolitan area. Environ Plan 31:251–271. doi:10.1068/b2983

    Article  Google Scholar 

  • Jarke M, Bui XT, Carroll JM (1998) Scenario management: an interdisciplinary approach. Requir Eng 3:155–173. doi:10.1007/s007660050002

    Article  Google Scholar 

  • Johnson RA, McCoy MC (2006) Assessment of integrated transportation/land use models. Information Center for the Environment. Department of Environmental Science & Policy, University of California, Davis

    Google Scholar 

  • Jovicic G (2001) Activity based travel demand modelling: a literature survey. Danmarks Transport Forskning ISSN:1601-0841

  • Jun M-J, Hur J-W (2001) Commuting costs of “leap-frog” newtown development in Seoul. Cities 18:151–158. doi:10.1016/S0264-2751(01)00007-5

    Article  Google Scholar 

  • Kahn H, Wiener AJ (1967) The next thirty-three years: a framework for speculation. Daedalus 96:705–732. doi:10.2307/20027066

    Google Scholar 

  • Kamruzzaman M, Baker D, Washington S, Turrell G (2014) Advance transit oriented development typology: case study in Brisbane, Australia. J Transp Geogr 34:54–70. doi:10.1016/j.jtrangeo.2013.11.002

    Article  Google Scholar 

  • Kamruzzaman M, Hine J, Yigitcanlar T (2015) Investigating the link between carbon dioxide emissions and transport-related social exclusion in rural Northern Ireland. Int J Environ Sci Technol 12:3463–3478. doi:10.1007/s13762-015-0771-8

    CAS  Article  Google Scholar 

  • Kamruzzaman M, Yigitcanlar T, Yang J, Mohamed A (2016) Measures of transport-related social exclusion: a critical review of the literature. Sustainability 8:696. doi:10.3390/su8070696

    Article  Google Scholar 

  • Khodabakhshi S (2013) Density and Sustainable Urban Development. http://www.ecocitybuilders.org/wp-content/uploads/2013/10/Khodabakhshi-Understanding.pdf

  • Kumar DS, Arya D, Vojinovic Z (2013) Modeling of urban growth dynamics and its impact on surface runoff characteristics. Comput Environ Urban Syst 41:124–135. doi:10.1016/j.compenvurbsys.2013.05.004

    Article  Google Scholar 

  • Kwan M-P, Weber J (2008) Scale and accessibility: implications for the analysis of land use–travel interaction. Appl Geogr 28:110–123. doi:10.1016/j.apgeog.2007.07.002

    Article  Google Scholar 

  • Lauf S, Haase D, Seppelt R, Schwarz N (2012) Simulating demography and housing demand in an urban region under scenarios of growth and shrinkage. Environ Plan 39:229–246. doi:10.1068/b36046t

    Article  Google Scholar 

  • Li K, Zhang P, Crittenden JC, Guhathakurta S, Chen Y, Fernando H, Joshi H (2007) Development of a framework for quantifying the environmental impacts of urban development and construction practices. Environ sci technol 41(14):5130–5136

    CAS  Article  Google Scholar 

  • Lindgren M, Bandhold H (2009) Scenario planning: revised and updated. Palgrave Macmillan, Basingstoke. doi:10.1057/9780230233584

    Book  Google Scholar 

  • Mahbub P, Ayoko GA, Goonetilleke A, Egodawatta P (2011) Analysis of the build-up of semi and non volatile organic compounds on urban roads. Water Res 45:2835–2844. doi:10.1016/j.watres.2011.02.033

    CAS  Article  Google Scholar 

  • Manzo S, Nielsen OA, Prato CG (2015) How uncertainty in input and parameters influences transport model: output A four-stage model case-study. Transp Policy 38:64–72. doi:10.1016/j.tranpol.2014.12.004

    Article  Google Scholar 

  • Martínez A, Mirás J (2009) Review essay: the second industrial revolution and urban growth: the impact of transport in Spanish cities. J Urban Hist 35:298–305. doi:10.1177/0096144208327357

    Article  Google Scholar 

  • Mehaffy MW (2013) Prospects for scenario-modelling urban design methodologies to achieve significant greenhouse gas emissions reductions. Urban Des Int 18:313–324. doi:10.1057/udi.2013.9

    Article  Google Scholar 

  • Mikelbank BA (2010) Quantitative Geography: perspectives on spatial data analysis. Geogr Anal 33(4):370–370. doi:10.1111/j.1538-4632.2001.tb00453.x

    Article  Google Scholar 

  • Minnery JR (1992) Urban form and development strategies : equity, environmental and economic implications Background papers (Australia. National Housing Strategy), vol 7. Australian Govt. Pub. Service, Canberra. http://nla.gov.au/nla.cat-vn330385

  • Mittal S, Dai H, Shukla PR (2015) Low carbon urban transport scenarios for China and India: a comparative assessment. Transp Res Part D Transp Environ. doi:10.1016/j.trd.2015.04.002

    Google Scholar 

  • Morrow E, Park J, Randall E, Sivasailam D, Son D (2013) Linking transportation and land use goals through scenario planning. Transp Res Rec J Transp Res Board 2397:22–29. doi:10.3141/2397-03

    Article  Google Scholar 

  • Næss P (2001) Urban planning and sustainable development. Eur Plann Stud 9:503–524. doi:10.1080/713666490

    Article  Google Scholar 

  • Newby-Clark IR, Ross M, Buehler R, Koehler DJ, Griffin D (2000) People focus on optimistic scenarios and disregard pessimistic scenarios while predicting task completion times. J Exp Psychol Appl 6:171–182. doi:10.1037/1076-898X.6.3.171

    CAS  Article  Google Scholar 

  • Newman P (2001) Planning issues and sustainable development. In: Baltes NJSB (ed) International Encyclopedia of the Social & Behavioral Sciences. Pergamon, Oxford, pp 11479–11482. http://dx.doi.org/10.1016/B0-08-043076-7/04424-7

  • Newton P (2000) Urban form and environmental performance. In: Achieving sustainable urban form, pp 46–53

  • Nguyen D, Coowanitwong N (2011) Strategic environmental assessment application for sustainable transport-related air quality policies: a case study in Hanoi City, Vietnam. Environ Dev Sustain 13:565–585. doi:10.1007/s10668-010-9277-1

    Article  Google Scholar 

  • Oana PL, Harutyun S, Brendan W, Sheila C (2011) Scenarios and indicators supporting urban regional planning. Proced Soc Behav Sci 21:243–252. doi:10.1016/j.sbspro.2011.07.012

    Article  Google Scholar 

  • Openshaw S (1996) Developing GIS-relevant zone-based spatial analysis methods. Spatial analysis: modelling in a GIS environment, pp 55–73

  • Pearman AD (1988) Scenario construction for transport planning. Transp Plan Technol 12:73–85. doi:10.1080/03081068808717361

    Article  Google Scholar 

  • Rocha WP, Delgado MG, Sendra JB, (2011) Simulating urban growth scenarios using GIS and multicriteria analysis techniques: a case study of the Madrid region, Spain. Environ Plan 38:1012–1031. doi:10.1068/b37061

    Article  Google Scholar 

  • Porter DR (1997) Managing growth in America’s communities. Island Press, Washington, DC

    Google Scholar 

  • Pucher J, Zr Peng, Mittal N, Zhu Y, Korattyswaroopam N (2007) Urban transport trends and policies in China and India: impacts of rapid economic growth. Transp Rev 27:379–410. doi:10.1080/01441640601089988

    Article  Google Scholar 

  • Rafiee R, Mahiny AS, Khorasani N, Darvishsefat AA, Danekar A (2009) Simulating urban growth in Mashad City, Iran through the SLEUTH model (UGM). Cities 26:19–26. doi:10.1016/j.cities.2008.11.005

    Article  Google Scholar 

  • Ratcliffe J, Krawczyk E (2011) Imagineering city futures: the use of prospective through scenarios in urban planning. Futures 43:642–653. doi:10.1016/j.futures.2011.05.005

    Article  Google Scholar 

  • Ren W et al (2015) Inter-city passenger transport in larger urban agglomeration area: emissions and health impacts. J Clean Prod. doi:10.1016/j.jclepro.2015.03.102

    Google Scholar 

  • Rikkonen P, Tapio P (2009) Future prospects of alternative agro-based bioenergy use in Finland—Constructing scenarios with quantitative and qualitative Delphi data. Technol Forecast Soc Change 76:978–990. doi:10.1016/j.techfore.2008.12.001

    Article  Google Scholar 

  • Roth NE, Thorne JH, Johnston RA, Quinn JF, McCoy MC (2012) Modeling impacts to agricultural revenue and government service costs from urban growth. J Agric Food Syst Commun Dev 2:1–20

    Google Scholar 

  • Rowe G, Wright G (1999) The Delphi technique as a forecasting tool: issues and analysis. Int J Forecast 15:353–375. doi:10.1016/S0169-2070(99)00018-7

    Article  Google Scholar 

  • Schoemaker PJH (1993) Multiple scenario development: its conceptual and behavioral foundation. Strateg Manag J 14:193–213. doi:10.1002/smj.4250140304

    Article  Google Scholar 

  • Schroeder MJ, Lambert JH (2010) Scenario-based multiple criteria analysis for infrastructure policy impacts and planning. J Risk Res 14:191–214. doi:10.1080/13669877.2010.515314

    Article  Google Scholar 

  • Seo Y, Kim S-M (2013) Estimation of greenhouse gas emissions from road traffic: a case study in Korea. Renew Sustain Energy Rev 28:777–787

    CAS  Article  Google Scholar 

  • Shearer AW et al (2009) Land use scenarios: environmental consequences of development. CRC Press, Hoboken

    Google Scholar 

  • Shiftan Y (2008) The use of activity-based modeling to analyze the effect of land-use policies on travel behavior. Ann Reg Sci 42:79–97

    Article  Google Scholar 

  • Singh YJ, Fard P, Zuidgeest M, Brussel M, Mv Maarseveen (2014) Measuring transit oriented development: a spatial multi criteria assessment approach for the City Region Arnhem and Nijmegen. J Transp Geogr 35:130–143. doi:10.1016/j.jtrangeo.2014.01.014

    Article  Google Scholar 

  • Smith JW, Floyd MF (2013) The urban growth machine, central place theory and access to open space. City Cult Soc 4:87–98. doi:10.1016/j.ccs.2013.03.002

    Article  Google Scholar 

  • Solesbury, W (2013) Policy in urban planning: structure plans, programmes and local plans, vol 8. Elsevier

  • Son H (2013) Alternative future scenarios for South Korea in 2030. Futures 52:27–41. doi:10.1016/j.futures.2013.06.005

    Article  Google Scholar 

  • Song Y, Ding C, Knaap G (2006) Envisioning Beijing 2020 through sketches of urban scenarios. Habitat Int 30:1018–1034. doi:10.1016/j.habitatint.2005.10.006

    Article  Google Scholar 

  • Stead D, Banister D (2003) Transport policy scenario-building. Transp Plan Technol 26:513–536. doi:10.1080/0308106032000167382

    Article  Google Scholar 

  • Storch H, Downes NK (2011) A scenario-based approach to assess Ho Chi Minh City’s urban development strategies against the impact of climate change. Cities 28:517–526. doi:10.1016/j.cities.2011.07.002

    Article  Google Scholar 

  • Sung H, Oh J-T (2011) Transit-oriented development in a high-density city: identifying its association with transit ridership in Seoul, Korea. Cities 28:70–82. doi:10.1016/j.cities.2010.09.004

    Article  Google Scholar 

  • Sushinsky JR, Rhodes JR, Possingham HP, Gill TK, Fuller RA (2013) How should we grow cities to minimize their biodiversity impacts? Glob Change Biol 19:401–410. doi:10.1111/gcb.12055

    Article  Google Scholar 

  • Thapa RB, Murayama Y (2012) Scenario-based urban growth allocation in Kathmandu Valley, Nepal. Landsc Urban Plan 105:140–148. doi:10.1016/j.landurbplan.2011.12.007

    Article  Google Scholar 

  • Thorne JH, Santos MJ, Bjorkman JH (2013) Regional assessment of urban impacts on landcover and open space finds a smart urban growth policy performs little better than business as usual. PLoS ONE. doi:10.1371/journal.pone.0065258

    Google Scholar 

  • Tian G, Qiao Z (2014) Modeling urban expansion policy scenarios using an agent-based approach for Guangzhou Metropolitan Region of China. Ecol Soc. doi:10.5751/ES-06909-190352

    Google Scholar 

  • Timmermans H (2006) Modelling land use and transportation dynamics: methodological issues, state of the art, and applications in developing countries. Discussion Paper Series

  • Torrens PM (2000) How land-use-transportation models work. CASA Working Paper 29

  • Vacík E, Fotr J, Spacek M, Soucek I (2014) Scenarios and their application in strategic planning. E+M Ekon Manag 3:118–135

    Google Scholar 

  • Verburg PH, Rounsevell MDA, Veldkamp A (2006) Scenario-based studies of future land use in Europe. Agric Ecosyst Environ 114:1–6. doi:10.1016/j.agee.2005.11.023

    Article  Google Scholar 

  • Vermeiren K, Van Rompaey A, Loopmans M, Serwajja E, Mukwaya P (2012) Urban growth of Kampala, Uganda: pattern analysis and scenario development. Landsc Urban Plan 106:199–206. doi:10.1016/j.landurbplan.2012.03.006

    Article  Google Scholar 

  • Villarreal ML, Norman LM, Boykin KG, Wallace CSA (2013) Biodiversity losses and conservation trade-offs: assessing future urban growth scenarios for a North American trade corridor. Int J Biodivers Sci Ecosyst Serv Manag 9:90–103. doi:10.1080/21513732.2013.770800

    Article  Google Scholar 

  • Von Wirth T, Wissen Hayek U, Kunze A, Neuenschwander N, Stauffacher M, Scholz RW (2014) Identifying urban transformation dynamics: Functional use of scenario techniques to integrate knowledge from science and practice. Technol Forecast Soc Chang 89:115–130. http://dx.doi.org/10.1016/j.techfore.2013.08.030

    Article  Google Scholar 

  • Waddell P (2002) UrbanSim: modeling urban development for land use, transportation, and environmental planning. Am Plan Assoc J Am Plan Assoc 68:297–314

    Article  Google Scholar 

  • Walz A, Lardelli C, Behrendt H, Grêt-Regamey A, Lundström C, Kytzia S, Bebi P (2007) Participatory scenario analysis for integrated regional modelling. Landsc Urban Plan 81:114–131. doi:10.1016/j.landurbplan.2006.11.001

    Article  Google Scholar 

  • Wang L, Waddell P, Outwater M (2011) Incremental integration of land use and activity-based travel modeling. Transp Res Rec J Transp Res Board 2255:1–10. doi:10.3141/2255-01

    Article  Google Scholar 

  • Wegener M (2004) Overview of land-use transport models. Handb Transp Geogr Spat Syst 5:127–146

    Article  Google Scholar 

  • Wheeler SM, Tomuta M, Haden VR, Jackson LE (2013) The impacts of alternative patterns of urbanization on greenhouse gas emissions in an agricultural county. J Urbanism: Int Res Placemaking Urban Sustain 6:213–235. doi:10.1080/17549175.2013.777356

    Google Scholar 

  • Wegener M (2014) Land-use transport interaction models. In: Fischer MM, Nijkamp P (eds) Handbook of regional science. Springer, Berlin, pp 741–758. doi:10.1007/978-3-642-23430-9_41

    Chapter  Google Scholar 

  • Wu X, Hu Y, He H, Xi F, Bu R (2010) Study on forecast scenarios for simulation of future urban growth in Shenyang City based on SLEUTH model. Geospat Inf Sci 13:32–39. doi:10.1007/s11806-010-0155-7

    Article  Google Scholar 

  • Yigitcanlar T, Kamruzzaman M (2014) Investigating the interplay between transport, land use and the environment: a review of the literature. Int J Environ Sci Technol 11:2121–2132. doi:10.1007/s13762-014-0691-z

    Article  Google Scholar 

  • Yigitcanlar T, Kamruzzaman M (2015) Planning, development and management of sustainable cities: a commentary from the guest editors. Sustainability 7:14677–14688. doi:10.3390/su71114677

    Article  Google Scholar 

  • Yigitcanlar T, Teriman S (2015) Rethinking sustainable urban development: towards an integrated planning and development process. Int J Environ Sci Technol 12:341–352. doi:10.1007/s13762-013-0491-x

    Article  Google Scholar 

  • Yigitcanlar T, Dodson J, Gleeson B, Sipe N (2007) Travel self-containment in master planned estates: analysis of recent Australian trends. Urban Policy Res 25:129–149. doi:10.1080/08111140701255823

    Article  Google Scholar 

  • Zhang Q, Ban Y, Liu J, Hu Y (2011) Simulation and analysis of urban growth scenarios for the Greater Shanghai Area, China. Comput Environ Urban Syst 35:126–139. doi:10.1016/j.compenvurbsys.2010.12.002

    Article  Google Scholar 

  • Zhang H, Jin X, Wang L, Zhou Y, Shu B (2015) Multi-agent based modeling of spatiotemporal dynamical urban growth in developing countries: simulating future scenarios of Lianyungang city, China. Stoch Environ Res Risk Assess 29:63–78. doi:10.1007/s00477-014-0942-z

    Article  Google Scholar 

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Acknowledgments

This research is conducted with funding support from the Australian Postgraduate Award provided jointly by the Australian Federal Government and the Queensland University of Technology. Authors are grateful for the constructive comments of the editor and anonymous referees on an earlier version of this paper.

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Correspondence to T. Yigitcanlar.

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Editorial responsibility: M. Abbaspour.

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Perveen, S., Yigitcanlar, T., Kamruzzaman, M. et al. Evaluating transport externalities of urban growth: a critical review of scenario-based planning methods. Int. J. Environ. Sci. Technol. 14, 663–678 (2017). https://doi.org/10.1007/s13762-016-1144-7

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  • DOI: https://doi.org/10.1007/s13762-016-1144-7

Keywords

  • Urban growth scenarios
  • Integrated land use and transportation models
  • Environmental impact
  • Assessment methods
  • Scenario evaluation
  • Scenario generation