[en] An in-depth understanding of the main factors behind built-up development is a key prerequisite for designing policies dedicated to a more efficient land use. Infill development policies are essential to curb sprawl and allow a progressive recycling of low-density areas inherited from the past. This paper examines the controlling factors of built-up expansion and densification processes in Wallonia (Belgium). Unlike the usual urban/built-up expansion studies, our approach considers various levels of built-up densities to distinguish between different types of developments, ranging from low-density extensions (or sprawl) to high-density infill development. Belgian cadastral data for 1990, 2000, and 2010 were used to generate four classes of built-up areas, namely, non-, low-, medium- and high-density areas. A number of socioeconomic, geographic, and political factors related to built-up development were operationalized following the literature. We then used a multinomial logistic regression model to analyze the effects of these factors on the transitions between different densities in the two decades between 1990 and 2010. The findings indicate that all the controlling factors show distinctive variations based on density. More specifically, the centrality of zoning policies in explaining expansion processes is highlighted. This is especially the case for high-density expansions. In contrast, physical and neighborhood factors play a larger role in infill development, especially for dense infill development.
Research Center/Unit :
LEMA
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Mustafa, Ahmed Mohamed El Saeid ; Université de Liège - ULiège > Département ArGEnCo > LEMA (Local environment management and analysis)
Van Rompaey, Anton; KU Leuven > Department of Earth and Environmental Sciences
Cools, Mario ; Université de Liège - ULiège > Département ArGEnCo > Transports et mobilité
Saadi, Ismaïl ; Université de Liège - ULiège > Département ArGEnCo > Transports et mobilité
Teller, Jacques ; Université de Liège - ULiège > Département ArGEnCo > Urbanisme et aménagement du territoire
Language :
English
Title :
Addressing the determinants of built-up expansion and densification processes at the regional scale
Publication date :
2018
Journal title :
Urban Studies
ISSN :
0042-0980
eISSN :
1360-063X
Publisher :
Sage, London, United Kingdom
Volume :
55
Issue :
15
Pages :
3279–3298
Peer reviewed :
Peer Reviewed verified by ORBi
Funders :
The research was funded by the ARC grant for Concerted Research Actions for project number 13/17-01 entitled “Land-use change and future flood risk: influence of micro-scale spatial patterns (FloodLand)
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Bibliography
Achmad A, Hasyim S, Dahlan B. (2015) Modeling of urban growth in tsunami-prone city using logistic regression: Analysis of Banda Aceh, Indonesia. Applied Geography 62: 237–246
Aguayo M, Wiegand T, Azócar G. (2007) Revealing the driving forces of mid-cities urban growth patterns using spatial modeling: A case study of Los Angeles, Chile. Ecology and Society 12(1): 1–30
Ban H, Ahlqvist O, (2009) Representing and negotiating uncertain geospatial concepts – Where are the exurban areas? Computers, Environment and Urban Systems 33: 233–246
Batisani N, Yarnal B, (2009) Urban expansion in Centre County, Pennsylvania: Spatial dynamics and landscape transformations. Applied Geography 29: 235–249
Belgian Federal Government Statistics (2013) Population statistics. Available at: http://statbel.fgov.be/fr/statistiques/chiffres/ (accessed 29 April 2014)
Braimoh AK, Onishi T, (2007) Spatial determinants of urban land use change in Lagos, Nigeria. Land Use Policy 24: 502–515
Burchell RW, Listokin D, Galley CC, (2000) Smart growth: More than a ghost of urban policy past, less than a bold new horizon. Housing Policy Debate 11: 821–879
Cammerer H, Thieken AH, Verburg PH, (2013) Spatio-temporal dynamics in the flood exposure due to land use changes in the Alpine Lech Valley in Tyrol (Austria). Natural Hazards 68: 1243–1270
Chen Y, Li X, Liu X. (2014) Modeling urban land-use dynamics in a fast developing city using the modified logistic cellular automaton with a patch-based simulation strategy. International Journal of Geographical Information Science 28: 234–255
Christiansen P, Loftsgarden T, (2011) Drivers behind urban sprawl in Europe. Institute of Transport Economics-TØI, Report 1136 (accessed 18 May 2016)
Danielsen KA, Lang RE, Fulton W, (1999) Retracting suburbia: Smart growth and the future of housing. Housing Policy Debate 10: 513–540
De Decker P, (2008) Facets of housing and housing policies in Belgium. Journal of Housing and the Built Environment 23: 155–171
De Smet F, Teller J, (2016) Characterising the morphology of suburban settlements: A method based on a semi-automatic classification of building clusters. Landscape Research 41: 113–130
Dormann CF, (2007) Assessing the validity of autologistic regression. Ecological Modelling 207: 234–242
Downs A, (2001) What does smart growth really mean. Planning 67: 20–25
Dubovyk O, Sliuzas R, Flacke J, (2011) Spatio-temporal modelling of informal settlement development in Sancaktepe district, Istanbul, Turkey. ISPRS Journal of Photogrammetry and Remote Sensing 66(2): 235–246
Dujardin S, Marique A-F, Teller J, (2014) Spatial planning as a driver of change in mobility and residential energy consumption. Energy and Buildings 68: 779–785
Dujardin S, Pirart F, Brévers F. (2012) Home-to-work commuting, urban form and potential energy savings: A local scale approach to regional statistics. Transportation Research Part A: Policy and Practice 46(7): 1054–1065
European Environment Agency (2006) Urban sprawl in Europe – The ignored challenge. Available at: http://www.eea.europa.eu/publications/eea_report_2006_10 (accessed 28 August 2015)
European Environment Agency (2011) Landscape Fragmentation in Europe. Copenhagen: European Environment Agency
European Spatial Planning Observation Network (2005) Governance of territorial and urban policies (No. 2nd Interim Report), ESPON Project 2.3.2. European Spatial Planning Observation Network. Valncia: Spain
Feng Y, Liu Y, Tong X. (2011) Modeling dynamic urban growth using cellular automata and particle swarm optimization rules. Landscape and Urban Planning 102(3): 188–196
Fraile A, Larrodé E, Alberto Magreñán Á. (2016) Decision model for siting transport and logistic facilities in urban environments: A methodological approach. Journal of Computational and Applied Mathematics 291: 478–487
Grant JL, (2009) Theory and practice in planning the suburbs: Challenges to implementing new urbanism, smart growth, and sustainability principles. Planning Theory & Practice 10(1): 11–33
Guzy M, Smith C, Bolte J. (2008) Policy research using agent-based modeling to assess future impacts of urban expansion into farmlands and forests. Ecology and Society 13(1): 1–38
Hao P, Hooimeijer P, Sliuzas R. (2013) What drives the spatial development of urban villages in China? Urban Studies 50: 3394–3411
Hennig EI, Schwick C, Soukup T. (2015) Multi-scale analysis of urban sprawl in Europe: Towards a European de-sprawling strategy. Land Use Policy 49: 483–498
Herbert DT, Thomas CJ, (1982) Urban Geography: A First Approach. New York: Wiley
Hu Z, Lo CP, (2007) Modeling urban growth in Atlanta using logistic regression. Computers, Environment and Urban Systems 31(6): 667–688
Huang B, Xie C, Tay R, (2010) Support vector machines for urban growth modeling. GeoInformatica 14: 83–99
Jantz CA, Goetz SJ, Shelley MK, (2003) Using the sleuth urban growth model to simulate the impacts of future policy scenarios on urban land use in the Baltimore–Washington metropolitan area. Environment and Planning B: Planning and Design 31(2): 251–271
Jehling M, Hecht R, Herold H, (in press) Assessing urban containment policies within a suburban context – An approach to enable a regional perspective. Land Use Policy, in press
Jelinski DE, Wu J, (1996) The modifiable areal unit problem and implications for landscape ecology. Landscape Ecology 11(3): 129–140
Jenks GF, Caspall FC, (1971) Error on choroplethic maps: Definition, measurement, reduction. Annals of the Association of American Geographers 61(2): 217–244
Li X, Zhou W, Ouyang Z, (2013) Forty years of urban expansion in Beijing: What is the relative importance of physical, socioeconomic, and neighborhood factors? Applied Geography 38: 1–10
Lin Y-P, Chu H-J, Wu C-F. (2011) Predictive ability of logistic regression, auto-logistic regression and neural network models in empirical land-use change modeling – A case study. International Journal of Geographical Information Science 25(1): 65–87
Litman T, (2016) Evaluating Transportation Land Use Impacts: Considering the Impacts, Benefits and Costs of Different Land Use Development Patterns. Available at: https://trid.trb.org/view.aspx?id=1424022 (accessed 14 July 2016)
Liu C, Ma X, (2011) Analysis to driving forces of land use change in Lu’an mining area. Transactions of Nonferrous Metals Society of China 21(Suppl. 3): s727–s732
Liu X, Li X, Shi X. (2008) Simulating complex urban development using kernel-based non-linear cellular automata. Ecological Modelling 211(1–2): 169–181
Liu Y, He Q, Tan R. (2016) Modeling different urban growth patterns based on the evolution of urban form: A case study from Huangpi, Central China. Applied Geography 66: 109–118
Loibl W, Toetzer T, (2003) Modeling growth and densification processes in suburban regions – Simulation of landscape transition with spatial agents. Environmental Modelling & Software 18(6): 553–563
Loo BPY, Cheng AHT, Nichols SL, (2017) Transit-oriented development on greenfield versus infill sites: Some lessons from Hong Kong. Landscape and Urban Planning 167: 37–48
McConnell V, Wiley K, (2011) Infill development: Perspectives and evidence from economics and planning. Resources for the Future 1–34
Marique A-F, Dujardin S, Teller J. (2013) Urban sprawl, commuting and travel energy consumption. Proceedings of the Institution of Civil Engineers. Energy 166(1): 1–13
Montgomery DC, Runger GC, (2003) Applied Statistics and Probability for Engineers, Fourth Edition. New York: John Wiley & Sons
Mustafa A, Bruwier M, Teller J. (2016) Impacts of urban expansion on future flood damage: A case study in the River Meuse basin, Belgium. In: Erpicum S, Dewals B, Archambeau P. (eds) Sustainable Hydraulics in the Era of Global Change. Proceedings of the 4th IAHR Europe Congress, 27–29 July 2016, Liege, Belgium. London: CRC Press, pp: 856–862
Mustafa A, Cools M, Saadi I. (2015) Urban development as a continuum: A multinomial logistic regression approach. In: Gervasi O, Murgante B, Misra S. (eds) Computational Science and Its Applications – ICCSA 2015. Lecture Notes in Computer Science. Cham: Springer International Publishing, pp. 729–744
Mustafa A, Cools M, Saadi I. (2017) Coupling agent-based, cellular automata and logistic regression into a hybrid urban expansion model (HUEM). Land Use Policy 69C: 529–540
Mustafa A, Saadi I, Cools M. (2014) Measuring the effect of stochastic perturbation component in cellular automata urban growth model. In: Timmermans H, (ed.) Procedia Environ. Sci., 12th International Conference on Design and Decision Support Systems in Architecture and Urban Planning. DDSS 2014 22, Amsterdam: Elsevier B.V. pp. 156–168
Nabielek K, (2012) The compact city: Planning strategies, recent developments and future prospects in the Netherlands – PBL Netherlands Environmental Assessment Agency. In: Proceedings of the AESOP 26th Annual Congress, 11–15 July, 2012, Ankara, Turkey. Available at: http://www.pbl.nl/en/publications/2012/the-compact-city-planning-strategies-recent-developments-and-future-prospects-in-the-netherlands (accessed 12 March 2016)
Nong Y, Du Q, (2011) Urban growth pattern modeling using logistic regression. Geo-Spatial Information Science 14(1): 62–67
Office for Official Publications of European Communities (1997) The EU Compendium of Spatial Planning Systems and Policies. Roma: Italy
Ooi JTL, Le TTT, (2013) The spillover effects of infill developments on local housing prices. Regional Science and Urban Economics 43(6): 850–861
Openshaw S, (1984) The modifiable areal unit problem. Geo Abstracts University of East Anglia, Norwich (Catmog: Concepts and techniques in modern geography). Available at: https://www.uio.no/studier/emner/sv/iss/SGO9010/openshaw1983.pdf (accessed 8 June 2016)
Openshaw S, Taylor PJ, (1979) A million or so correlation coefficients: Three experiments on the modifiable areal unit problem. Statistical Applications in the Spatial Sciences 21: 127–144
Ortúzar J, de D, Willumsen LG, (1994) Modelling Transport, Second Edition. Chichester: Wiley
Oueslati W, Alvanides S, Garrod G, (2015) Determinants of urban sprawl in European cities. Urban Studies 52(9): 1594–1614
Overmars KP, de Koning GHJ, Veldkamp A, (2003) Spatial autocorrelation in multi-scale land use models. Ecological Modelling 164: 257–270
Poelmans L, Van Rompaey A, (2009) Detecting and modelling spatial patterns of urban sprawl in highly fragmented areas: A case study in the Flanders–Brussels region. Landscape and Urban Planning 93(1): 10–19
Poelmans L, Van Rompaey A, (2010) Complexity and performance of urban expansion models. Computers, Environment and Urban Systems 34(1): 17–27
Prokop G, Jobstmann H, Schönbauer A, (2011) Best Practices For Limiting Soil Sealing And Mitigating Its Effects. Technical Report No. 2011–050. Vienna: European Commission, – DG Environment
Puertas OL, Henríquez C, Meza FJ, (2014) Assessing spatial dynamics of urban growth using an integrated land use model. Application in Santiago Metropolitan Area, 2010–2045. Land Use Policy 38: 415–425
Robinson DT, Murray-Rust D, Rieser V. (2012) Modelling the impacts of land system dynamics on human well-being: Using an agent-based approach to cope with data limitations in Koper, Slovenia. Special Issue: Geoinformatics 2010. Computers, Environment and Urban Systems 36(2): 164–176
Roy Chowdhury PK, Maithani S, (2014) Modelling urban growth in the Indo-Gangetic plain using nighttime OLS data and cellular automata. International Journal of Applied Earth Observation and Geoinformation 33: 155–165
Rui Y, Ban Y, (2010) Multi-agent simulation for modeling urban sprawl in the Greater Toronto area. In: Painho M, Santos MY, Pundt H, (eds), 13th AGILE. Presented at the 13th International Conference on Geographic Information Science 2010, Portugal
Shafizadeh-Moghadam H, Helbich M, (2015) Spatiotemporal variability of urban growth factors: A global and local perspective on the megacity of Mumbai. International Journal of Applied Earth Observation and Geoinformation 35(Part B): 187–198
Shu B, Zhang H, Li Y. (2014) Spatiotemporal variation analysis of driving forces of urban land spatial expansion using logistic regression: A case study of port towns in Taicang City, China. Habitat International 43: 181–190
Song Y, Zenou Y, (2006) Property tax and urban sprawl: Theory and implications for US cities. Journal of Urban Economics 60(3): 519–534
Tannier C, Thomas I, (2013) Defining and characterizing urban boundaries: A fractal analysis of theoretical cities and Belgian cities. Comput. Environ. Computers, Environment and Urban Systems 41: 234–248
Thomas I, Frankhauser P, Biernacki C, (2008) The morphology of built-up landscapes in Wallonia (Belgium): A classification using fractal indices. Landscape and Urban Planning. 84(2): 99–115
Traore A, Watanabe T, (2017) Modeling determinants of urban growth in Conakry, Guinea: A spatial logistic approach. Urban Science 1(2): 12
Verburg PH, van Eck JRR, de Nijs TCM, (2004) Determinants of land-use change patterns in the Netherlands. Environment and Planning B: Planning and Design 31(1): 125–150
Vermeiren K, Van Rompaey A, Loopmans M. (2012) Urban growth of Kampala, Uganda: Pattern analysis and scenario development. Landscape and Urban Planning 106(2): 199–206
Xian G, Crane M, (2005) Assessments of urban growth in the Tampa Bay watershed using remote sensing data. Remote Sensing of Environment 97(2): 203–215
Yang X, (2010) Integration of remote sensing with GIS for urban growth characterization. In: Jiang B, Yao X, (eds) Geospatial Analysis and Modelling of Urban Structure and Dynamics, GeoJournal Library. Dordrecht: Springer, pp. 223–250
Zhang Z, Su S, Xiao R. (2013) Identifying determinants of urban growth from a multi-scale perspective: A case study of the urban agglomeration around Hangzhou Bay, China. Applied Geography 45: 193–202
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