GIS-based multidimensional processes for the optimal development of building land in urban planning – demonstrated with the example of the inner-city project Holsten-Areal in Hamburg




Suitability assessment, Land-use optimization, Fuzzy suitability modelling, Parameterized region-growing, Decision support


The global urban growth trend is also evident in Germany and the pressure on the real estate markets is pushing construction activity to the threshold of available building land. To limit urban expansion, additional space is to be created primarily through brownfield development, but here large housing potentials are usually only to be found on sites that are difficult to develop. The framework conditions that have arisen here in the interplay between land and real estatemarkets in conjunction
with the multidimensionality of urban planning problems suggest a need for urban planners and researchers to develop more effectivemethods. This paper therefore describes a GISbasedmethod for optimising building sites, which can be used to evaluate sites in context and optimise them attribute-spatially. It combines a fuzzy methodology with a heuristic optimisation algorithm, the Parameterised Region-Growing, and demonstrates it using the example of the Holsten site in Hamburg. It successfully generates spatially compact and coherent, highly valued residential building areas, to which urban development parameters are assigned. Comparisons with existing planning show instructive results, e.g., regarding more effective utilisation of good micro-locations, realistic building
density values and realisable area parameters. 


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Abart-Heriszt, L. (1999): GIS-Modell zur landesweiten Beurteilung der Standorteignung für Industrie und Gewerbe in der Steiermark. In: Strobl, J.; Blaschke, T. (Hrsg.): Angewandte Geographische Informationsverarbeitung – Beiträge zum AGIT-Symposium Salzburg IX. Salzburg, 1–10.

Alda, W.; Hirschner, J. (2016): Projektentwicklung in der Immobilienwirtschaft. Grundlagen für die Praxis. Wiesbaden.

Brookes, C. J. (1997a): A genetic algorithm for locating optimal sites on raster suitability maps. In: Transactions in GIS 2, 3, 201–212.

Brookes, C. J. (1997b): A parameterized region-growing programme for site allocation on raster suitability maps. In: International Journal of Geographical Information Science 11, 4, 375–396.

Brookes, C. J. (1998): A genetic algorithm for designing optimal patch configurations in GIS. Dissertation am University College London.

Cao, K.; Huang, B. (2019): Spatial optimization for land use planning: Opportunities and challenges. In: Transactions in GIS 23, 4, 641–644.

Cao, K.; Huang, B.; Wang, S.; Lin, H. (2012): Sustainable land use optimization using Boundary-based Fast Genetic Algorithm. In: Computers, Environment and Urban Systems 36, 3, 257–269.

Caprioli, C.; Bottero, M. (2020): Addressing complex challenges in transformations and planning: A fuzzy spatial multicriteria analysis for identifying suitable locations for urban infrastructures. In: Land Use Policy, 102, 105147.

Cardone, B.; Di Martino, F. (2021): GIS-based hierarchical fuzzy multicriteria decision-making method for urban planning. In: Journal of Ambient Intelligence and Humanized Computing 12, 1, 601–615.

Chaidee, S.; Pakawanwong, P.; Suppakitpaisarn, V.; Teerasawat, P. (2017): Interactive land-use optimization using Laguerre Voronoi Diagram with Dynamic Generating Point Allocation. In: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W7, 1091–1098.

Chandramouli, M.; Huang, B.; Xue, L. (2009): Spatial change optimization: Integrating GA with visualization for 3D scenario generation. In: Photogrammetric Engineering and Remote Sensing 75, 8, 1015–1022.

Chen, S.-J.; Hwang, F. P.; Hwang, C.-L. (1992): Fuzzy multiple attribute decision making. Methods and applications. Berlin.

Church, R.L.; Gerrard, R. A.; Gilpin, M.; Stine, P. (2003): Constructing Cell-Based Habitat Patches Useful in Conservation Planning. In: Annals of the Association of American Geographers 93, 4, 814–827.

Destatis (2021): Bevölkerung und Demografie. Auszug aus dem Datenreport 2021. Wiesbaden.

Dewberry, S. O. (2019): Land development handbook. A practical guide to planning, engineering, and surveying. New York.

Dickinson, D.; Shahab, S. (2021): Post planning-decision process: Ensuring the delivery of high-quality developments in Cardiff. In: Land Use Policy 100, 105114.

Dueker, K. J.; Delacy, P. B (1990): GIS in the land development planning process. Balancing the needs of land use planners and real estate developers. In: Journal of the American Planning Association 56, 4, 483–491.

Eastman, J. R.; Jin, W.; Kyem, P.; Toledano, J. (1995): Raster procedure for multi-criteria/multi-objective decisions. In: Photogrammetric Engineering and Remote Sensing 61, 5, 539–547.

Fina, S.; Henger, R.; Siedentop, S. (2020): Erfolgreiche Wege für mehr Wohnungsbau. Eine Analyse der Mobilisierung von Baulandpotenzialen in NRW. Köln. = IW-Report 41/2020.

Guhl, P. (2018): Die Entwicklung neuer Stadtquartiere aus städtebaulicher Sicht. Analyse der Projekte seit 1990. Essen. = Dortmunder Beiträge zur Raumplanung 148.

Isenhöfer, B.; Väth, A.; Hofmann, P. (2008): Immobilienanalyse. In: Schulte, K.-W. (Hrsg.): Immobilienökonomie. Band 1: Betriebswirtschaftliche Grundlagen. München, 391–451.

Johnson, D. E. (2008): Fundamentals of land development. A real world guide to profitable large-scale development. Hoboken.

Juszczak, A.; Reith, H. (2020): Mehr Wohnbauland am Rhein. Eine GIS-gestützte Flächenanalyse als Grundlage für die Regionalplanung. In: Informationen zur Raumentwicklung 47, 3, 56–65.

Kaufman, L.; Rousseeuw, P.J. (2005): Finding groups in data. An introduction to cluster analysis. Hoboken.

Köster, C. (2006): Städtebauliche Qualitätssicherung bei der Entwicklung neuer Stadtquartiere. Zur Zusammenarbeit öffentlicher und privater Partner. Münster.

Krivoruchko, K.; Gribov, A.; Krause, E. (2011): Multivariate Areal Interpolation for Continuous and Count Data. In: Procedia Environmental Sciences 3, 14–19.

LBS – Westdeutsche Landesbausparkasse (2017): Wohnwünsche 2017. Münster.

Leitstelle XPlanung/XBau (2020): Handreichung XPlanung-XBau. Hamburg.

Ma, C.; Zhou, M. (2018): A GIS-Based Interval Fuzzy Linear Programming for Optimal Land Resource Allocation at a City Scale. In: Social Indicators Research 135, 1, 143–166.

Malczewski, J.; Jankowski, P. (2020): Emerging trends and research frontiers in spatial multicriteria analysis. In: International Journal of Geographical Information Science 34, 7, 1257–1282.

Malczewski, J.; Rinner, C. (2015): Multicriteria decision analysis in geographic information science. New York.

Mantelas, L.; Prastacos, P.; Hatzichristos, T.; Koutsopoulos, K. (2012): Using fuzzy cellular automata to access and simulate urban growth. In: GeoJournal 77, 1, 13–28.

Morio, M.; Schädler, S.; Finkel, M. (2013): Applying a multi-criteria genetic algorithm framework for brownfield reuse optimization: Improving redevelopment options based on stakeholder preferences. In: Journal of Environmental Management 130, 331–346.

Mrosek, H.F. (2012): Städtebauliche Projektentwicklung durch private Immobilienunternehmen. Essen. = Dortmunder Beiträge zur Raumplanung 140.

Müller, K.; Weber, K. (2002): Städtebauliche Projektentwicklung. Optimierung der Wirtschaftlichkeit durch Methoden der Immobilienökonomie. Regensburg. = Volkswirtschaftliche Schriften 24.

Nadler, M.; Spieß, F.; Müller, G. (2018): Landeignungsprüfung in prosperierenden Großstädten. Ein GIS-basiertes Entscheidungsunterstützungssystem für Unternehmensimmobilienentwicklungen in der Stadt Düsseldorf. In: Raumforschung und Raumordnung | Spatial Research and Planning 76, 5, 437–460.

Natividade-Jesus, E.; Coutinho-Rodrigues, J.; Henggeler Antunes, C. (2007): A multicriteria decision support system for housing evaluation. In: Decision Support Systems 43, 3, 779–790.

Nguyen, X. L.; Chou, T. Y.; Fang, Y. M.; Lin, F. C.; Hoang, V. T.; Huang, Y. M. (2017): Combination of Geographic Information System, Fuzzy Set Theory And Analytic Hierarchy Process For Rationality Assessment Of Planned Industrial Zones: A Case Study In Vietnam. In: International Refereed Journal of Engineering and Science 6, 3, 72–79.

Nissen, V. (2007): Ausgewählte Grundlagen der Fuzzy Set Theorie. Ilmenau. = Ilmenauer Beiträge zur Wirtschaftsinformatik 2007-03.

Peiser, R.; Hamilton, D. (2012): Professional Real Estate Development. The ULI Guide to the Business. Washington DC.

Rezayan, H.; Najian, A. H. (2008): Land use allocation optimization using advanced geographic information analyses. In: World Applied Sciences Journal 3, S1, 136–142.

Schütz, E.; Feldmann, P. (2008): Quartiersentwicklung am Beispiel des Arnulfparks in München. In: Schulte, K.-W.; Bone-Winkel, S. (Hrsg.): Handbuch Immobilien-Projektentwicklung. Köln, 843–868.

Stewart, T. J.; Janssen, R.; van Herwijnen, M. (2004): A genetic algorithm approach to multiobjective land use planning. In: Computers and Operations Research 31, 14, 2293–2313.‑6

Suppakitpaisarn, V.; Ariyarit, A.; Chaidee, S. (2021): A Voronoi-based method for land-use optimization using semidefinite programming and gradient descent algorithm. In: International Journal of Geographical Information Science 35, 5, 999–1031.

Ustaoglu, E.; Aydinoglu, A. C. (2019): Land suitability assessment of green infrastructure development: A case study of Pendik district (Turkey). In: Journal of Land Use, Mobility and Environment 12, 2, 165–178.

Ustaoglu, E.; Aydinoglu, A. C. (2020): Suitability evaluation of urban construction land in Pendik district of Istanbul, Turkey. In: Land Use Policy 99, 104783.

Vanegas, P.; Cattrysse, D.; van Orshoven, J. (2008): Comparing exact and heuristic methods for site location based on multiple attributes. An afforestation application. In: Gervasi, O.; Murgante, B.; Laganà, A.; Taniar, D.; Mun, Y.; Gavrilova, M. L. (Hrsg.): Computational Science and Its Applications – ICCSA 2008. Berlin, 389–404.

Wieland, A. (2014): Projektentwicklung nutzungsgemischter Quartiere. Analyse zur Generierung von Erfolgsfaktoren. Wiesbaden.

Wilson, M. W. (2020): GIS: A method and practice. In: Ward, K. (Hrsg.): Researching the city. A guide for students. Los Angeles, 125–144.

Zhao, Y.; Zhang, Y.; Murayama, Y. (2011): Field-based fuzzy spatial reasoning model for constraint satisfaction problem. In: Murayama, Y.; Thapa, R. B (Hrsg.): Spatial Analysis and Modeling in Geographical Transformation Process. GIS-based Applications. Dordrecht, 29–44.


Issue publication date 2022-04-29 (version 2)
Published online first 2022-01-14 (version 1)




Research Article

How to Cite

Naumann LL, Nadler M. GIS-based multidimensional processes for the optimal development of building land in urban planning – demonstrated with the example of the inner-city project Holsten-Areal in Hamburg. RuR [Internet]. 2022 Apr. 29 [cited 2024 Jul. 22];80(2):202-18. Available from: