Skip to main content
SpringerLink
Log in

GIScience, Spatial Analysis, and Decision Support

  • Chapter
  • First Online:
Book cover Multicriteria Decision Analysis in Geographic Information Science

Part of the book series: Advances in Geographic Information Science ((AGIS))

Abstract

This chapter outlines the connections between Geographic Information Science (GIScience), spatial analysis, and decision support. GIScience is concerned with the nature of geographic information and geographic phenomena. It provides theoretical foundations for Geographic Information Systems (GIS) and related geographic information technologies. A variety of theoretical and methodological perspectives on Multicriteria Decision Analysis (MCDA) in GIScience have been suggested over the last 20 years or so. Spatial analysis (including related fields of GIScience such as geocomputation and geovisualization) and spatial decision support systems provide perceptive perspectives on integrating MCDA into GIS. This chapter argues that it is the confluence of two research areas: spatial analysis and spatial decision support where the concept of integrating GIS and MCDA can offer substantial contributions to the development of GIScience.  

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 249.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 249.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Aerts, J. C. J. H., & Heuvelink, G. B. M. (2002). Using simulated annealing for resource allocation. International Journal of Geographical Information Science, 16(6), 571–587.

    Google Scholar 

  • Alexander, E. R. (2000). Rationality revisited: Planning paradigms in a post-postmodernist perspective. Journal of Planning Education and Research, 19(3), 242–256.

    Google Scholar 

  • Andrienko, G., Andrienko, N., Jankowski, P., Keim, D. A., & Kraak, M. J. (2007). Geovisual analytics for spatial decision support: Setting the research agenda. International Journal of Geographical Information Science, 21(8), 839–857.

    Google Scholar 

  • Balram, S., & Dragićević, S. (2006). Collaborative geographic information systems. Hershey: Idea Group Publishing.

    Google Scholar 

  • Banai, R. (1993). Fuzziness in geographic information systems: Contributions from the analytic hierarchy process. International Journal of Geographical Information Systems, 7(4), 315–329.

    Google Scholar 

  • Bell, D. E., Raiffa, H., & Tversky, A. (Eds.). (1988). Decision making: Descriptive, normative, and prescriptive interactions. Cambridge: Cambridge University Press.

    Google Scholar 

  • Bell, M. L., Hobbs, B. F., & Ellis, H. (2003). The use of multi-criteria decision-making methods in the integrated assessment of climate change: Implications for IA practitioners. Socio-Economic Planning Sciences, 37(4), 289–316.

    Google Scholar 

  • Benenson, I., & Torrens, P. (2004). Geosimulation: Automata based modeling of urban phenomena. London: Wiley.

    Google Scholar 

  • Berry, B. J. L., & Marble, D. F. (1968). Spatial analysis. Englewood Cliffs: Prentice Hall.

    Google Scholar 

  • Bettinger, P., & Kim, Y.-H. (2008). Spatial optimisation—computational methods. In K. von Gadow & T. Pukkala (Eds.), Designing Green Landscapes (pp. 111–135).

    Google Scholar 

  • Bone, C., Dragićević, S., & White, R. (2011). Modeling-in-the-middle: Bridging the gap between agent-based modeling and multi-objective decision making for land use change. International Journal of Geographical Information Science, 25(5), 717–737.

    Google Scholar 

  • Bong, C. W., & Wang, Y. C. (2004). A multiobjective hybrid metaheuristic approach for GIS-based spatial zoning model. Journal of Mathematical Modelling and Algorithms, 3(3), 245–261.

    Google Scholar 

  • Boroushaki, S., & Malczewski, J. (2010). ParticipatoryGIS: A web-based collaborative GIS and multicriteria decision analysis. URISA Journal, 22(1), 23–32.

    Google Scholar 

  • Bouyssou, D., Marchant, T., Pirlot, M., Tsoukiàs, A., & Vincke, P. (2006). Evaluation and decision models with multiple criteria: Stepping stones for the analyst. Boston: Springer.

    Google Scholar 

  • Bozkaya, B., Erkut, E., & Laporte, G. (2003). Discrete optimization: A tabu search heuristic and adaptive memory procedure for political districting. European Journal of Operational Research, 144(1), 12–26.

    Google Scholar 

  • Brail, R., & Klosterman, R. (Eds.). (2001). Planning support systems. Redlands: ESRI Press.

    Google Scholar 

  • Cao, K., Huang, B., Li, M., & Li, W. (2014). Calibrating a cellular automata model for understanding rural–urban land conversion: A Pareto front-based multi-objective optimization approach. International Journal of Geographical Information Science, 28(5), 1028–1046.

    Google Scholar 

  • Carver, S. J. (1991). Integrating multi-criteria evaluation with geographical information systems. International Journal of Geographical Information Systems, 5(3), 321–339.

    Google Scholar 

  • Carver, S. (1999). Developing web-based GIS/MCE: Improving access to data and spatial decision support tools. In J. C. Thill (Ed.), Spatial multicriteria decision-making and analysis (pp. 49–75). Aldershot: Ashgate.

    Google Scholar 

  • Chakhar, S., & Mousseau, V. (2007). Spatial multicriteria decision making. In S. Shehkar & H. Xiong (Eds.), Encyclopedia of geographic information science. New York: Springer.

    Google Scholar 

  • Chakhar, S., & Mousseau, V. (2008). GIS-based multicriteria spatial modeling generic framework. International Journal of Geographical Information Science, 22(11–12), 1159–1196.

    Google Scholar 

  • Chang, K. T. (2011). Introduction to geographic information systems. New York: McGraw Hill.

    Google Scholar 

  • Chang, N. B., Lu, H. Y., & Wie, Y. L. (1997). GIS technology for vehicle routing and scheduling in solid waste collection systems. Journal of Environmental Engineering, 123(9), 901–910.

    Google Scholar 

  • Chisholm, M. (1979). Human Geography: Evolution or Revolution? Harmondsworth: Penguin Books Ltd.

    Google Scholar 

  • Church, R. L., Gerrard, R. A., Gilpin, M., & Stine, P. (2003). Constructing cell-based habitat patches useful in conservation planning. Annals of the Association of American Geographers, 93(4), 814–827.

    Google Scholar 

  • Cohon, J. L. (1978). Multiobjective programming and planning. London: Academic Press.

    Google Scholar 

  • Couclelis, H., & Monmonier, M. (1995). Using SUSS to resolve NIMBY: How spatial understanding support systems can help with ‘Not in My Backyard’ syndrome. Geographical Systems, 2(2), 83–101.

    Google Scholar 

  • Cova, T. J., & Church, R. L. (2000). Exploratory spatial optimization and site search: Neighborhood operator approach. Computers, Environment and Urban Systems, 21, 401–419.

    Google Scholar 

  • Cowen, D. (1988). GIS versus CAD versus DBMS: What are the differences? Photogrammetric Engineering and Remote Sensing, 54(11), 1551–1555.

    Google Scholar 

  • Craig, W., Harris, T., & Weiner, D. (Eds.). (2002). Community participation and geographic information systems. London: Taylor & Francis.

    Google Scholar 

  • Current, J., Min, H., & Schilling, D. (1990). Multiobjective analysis of facility location decisions. European Journal of Operations Research, 49(3), 295–307.

    Google Scholar 

  • Densham, P. J. (1991). Spatial decision support systems. In D. J. Maguire, M. S. Goodchild, & D. W. Rhind (Eds.), Geographical information systems: Principles and applications (pp. 403–412). London: Longman.

    Google Scholar 

  • Dias, L. C., & Tsoukiàs, A. (2004). On the constructive and other approaches in decision aiding. In C.A. Hengeller Antunes, J. Figueira, J. Clímaco (Eds.), Proceedings of the 56th Meeting of the EURO MCDA Working Group (pp. 13–28). Coimbra, Portugal: CCDRC.

    Google Scholar 

  • Duh, J. D., & Brown, D. G. (2005). Generating prescribed patterns in landscape models. In D. J. Maguire, M. F. Goodchild, & M. Batty (Eds.), GIS, spatial analysis and modeling (pp. 423–444). Redlands: ESRI Press.

    Google Scholar 

  • Duh, J. D., & Brown, D. G. (2007). Knowledge-informed Pareto simulated annealing for multi-objective spatial allocation. Computers, Environment and Urban Systems, 31(3), 253–281.

    Google Scholar 

  • Dunn, C. E. (2007). Participatory GIS: A people’s GIS? Progress in Human Geography, 31(5), 616–637.

    Google Scholar 

  • Eastman, J. R., Kyem, P. A. K., Toledano, J., & Jin, W. (1993). GIS and decision making. Geneva: UNITAR.

    Google Scholar 

  • Faiz, S., & Krichen, S. (2012). Geographical information systems and spatial optimization. Boca Raton: CRC Press.

    Google Scholar 

  • Feick, R. D., & Hall, G. B. (1999). Consensus-building in a multi-participant spatial decision support system. URISA Journal, 11(2), 17–23.

    Google Scholar 

  • Feick, R. D., & Hall, B. G. (2004). A method for examining the spatial dimension of multi-criteria weight sensitivity. International Journal of Geographical Information Science, 18(8), 815–840.

    Google Scholar 

  • Fotheringham, S., & Rogers, P. (1994). Spatial analysis and GIS. London: Taylor & Francis.

    Google Scholar 

  • Geertman, S., & Stillwell, J. (Eds.). (2002). Planning support systems in practice. Berlin: Springer.

    Google Scholar 

  • Gen, M., & Cheng, R. (2007). Genetic algorithms and engineering optimization. New York: Wiley.

    Google Scholar 

  • Ghosh, A., & Rushton, G. (1986). Spatial analysis and location-allocation models. New York: Van Nostrand Reinhold Company.

    Google Scholar 

  • Giaglis, G. M., Minis, I., Tatarakis, A., & Zeimpekis, V. (2004). Minimizing logistics risk through real-time vehicle routing and mobile technologies: Research to date and future trends. International Journal of Physical Distribution and Logistics Management, 34(9), 749–764.

    Google Scholar 

  • Goodchild, M. F. (1992). Geographical information science. International Journal of Geographical Information Systems, 6(1), 31–45.

    Google Scholar 

  • Goicoechea, A., Hansen, D. R., & Duckstein, L. (1982). Multiobjective decision analysis with engineering and business applications. New York: John Wiley & Sons.

    Google Scholar 

  • Goodchild, M.F. (2001). Issues in spatially explicit modeling. In D.C. Parker, T. Berger, S.M. Manson (Eds.), Agent-Based Models of Land-Use and Land-Cover Change (pp. 13–16). Proceedings of an International Workshop, October 4–7, Irvine, California, USA.

    Google Scholar 

  • Goodchild, M. F. (2004). GIScience, geography, form, and process. Annals of the Association of American Geographers, 94(4), 709–714.

    Google Scholar 

  • Goodchild, M. F., & Haining, R. P. (2004). GIS and spatial data analysis: Converging perspectives. Papers in Regional Science, 83(1), 363–385.

    Google Scholar 

  • Goodchild, M. F., & Janelle, D. G. (2004). Thinking spatially in the social sciences. In M. F. Goodchild & D. G. Janelle (Eds.), Spatially integrated social science (pp. 3–22). New York: Oxford University Press.

    Google Scholar 

  • van Herwijnen, M., & Rietveld, P. (1999). Spatial dimensions in multicriteria analysis. In J. C. Thill (Ed.), Spatial multicriteria decision making and analysis: A geographic information sciences approach (pp. 77–99). London: Ashgate.

    Google Scholar 

  • Heywood, I., Cornelius, A., & Carver, S. (2012). An introduction to geographical information systems. Harlow: Prentice Hall.

    Google Scholar 

  • Huang, B., Yao, L., & Raguraman, K. (2006). Bi-level GA and GIS for multi-objective TSP route planning. Transportation Planning and Technology, 29(2), 105–124.

    Google Scholar 

  • Jankowski, P., Andrienko, N., & Andrienko, G. (2001). Map-centred exploratory approach to multiple criteria spatial decision making. International Journal of Geographical Information Science, 15(2), 101–127.

    Google Scholar 

  • Jankowski, P., Ligmann-Zielinska, A., & Swobodzinski, M. (2008). Choice modeler: A web-based spatial multiple criteria evaluation tool. Transactions in GIS, 12(4), 541–561.

    Google Scholar 

  • Jankowski, P., & Nyerges, T. (2001). Geographic information systems for group decision making: Towards a participatory geographic information science. London: Taylor & Francis.

    Google Scholar 

  • Jankowski, P., Robischon, S., Tuthill, D., Nyerges, T., & Ramsey, K. (2006). Design considerations and evaluation of a collaborative, spatio-temporal decision support system, Transactions in GIS, 10(2): 335–354.

    Google Scholar 

  • Jankowski, P., & Stasik, M. (1997). Spatial understanding and decision support system: A prototype for public GIS. Transactions in GIS, 2(1), 73–84.

    Google Scholar 

  • Janssen, R. (1992). Multiobjective decision support for environmental management. Dordrecht: Kluwer Academic Publishers.

    Google Scholar 

  • Joerin, F., Theriault, M., & Musy, A. (2001). Using GIS and outranking multi-criteria analysis for land-use suitability assessment. International Journal of Geographical Information Science, 15(2), 153–174.

    Google Scholar 

  • Keeney, R. (1992). On the Foundations of Prescriptive Decision Analysis. In W. Edwards (Ed.), Utility theories: Measurement and applications (pp. 57–72). Boston: Kluwer Academic Publishers.

    Google Scholar 

  • Killen, J. (1983). Mathematical programming methods for geographers and planners. London: Croom Helm.

    Google Scholar 

  • Klosterman, R. E. (2001). Planning support systems: A new perspective on computer-aided planning. In R. K. Brail & R. E. Klosterman (Eds.), Planning support systems (pp. 1–35). Redlands: ESRI Press.

    Google Scholar 

  • Krzanowski, R., & Raper, J. (2001). Spatial evolutionary modeling. Oxford: Oxford University Press.

    Google Scholar 

  • Laaribi, A., Chevallier, J. J., & Martel, J. M. (1996). A spatial decision aid: A multicriterion evaluation approach. Computers, Environment and Urban Systems, 20(6), 351–366.

    Google Scholar 

  • Langlois, P. (2011). Simulation of complex systems in GIS. London: Wiley.

    Google Scholar 

  • Leung, Y. (1997). Intelligent spatial decision support systems. Berlin: Springer.

    Google Scholar 

  • Li, X., Chen, Y., Liu, X., Li, D., & He, J. (2011a). Concepts, methodologies, and tools of an integrated geographical simulation and optimization system. International Journal of Geographical Information Science, 25(4), 633–655.

    Google Scholar 

  • Li, X., Shi, X., He, J. Q., & Liu, X. P. (2011b). Coupling simulation and optimization to solve planning problems in a fast developing area. Annals of the Association of American Geographers, 101(5), 1032–1048.

    Google Scholar 

  • Li, X., & Liu, X. (2007). Defining agents’ behaviors to simulate complex residential development using multicriteria evaluation. Journal of Environmental Management, 85(4), 1063–1075.

    Google Scholar 

  • Li, X., & Yeh, A. G. O. (2000). Modelling sustainable urban development by the integration of constrained cellular automata and GIS. International Journal of Geographical Information Science, 14(2), 131–152.

    Google Scholar 

  • Li, X., & Yeh, A. G. O. (2002). Neural-network-based cellular automata for simulating multiple land use changes using GIS. International Journal of Geographical Information Science, 16(4), 323–343.

    Google Scholar 

  • Ligmann-Zielinska, A., & Jankowski, P. (2008). A framework for sensitivity analysis in spatial multiple criteria evaluation. In T.J. Cova, H.J. Miller, K. Beard, A.U. Frank, M.F. Goodchild (Eds.), Geographic Information Science, Proceedings 5th International Conference, GIScience (pp. 217–233). Park City, UT. Berlin/Heidelberg: Springer.

    Google Scholar 

  • Ligmann-Zielinska, A., & Jankowski, P. (2010). Exploring normative scenarios of land use development decisions with an agent-based simulation laboratory. Computers, Environment and Urban Systems, 34(5), 409–423.

    Google Scholar 

  • Ligmann-Zielinska, A., & Jankowski, P. (2012). Impact of proximity-adjusted preferences on rank-order stability in geographical multicriteria decision analysis. Journal of Geographical Systems, 14(2), 167–187.

    Google Scholar 

  • Liu, Y., Lv, X., Qin, X., Guo, H., Yu, Y., Wang, J., et al. (2007). An integrated GIS-based analysis system for land-use management of lake areas in urban fringe. Landscape and Urban Planning, 82(4), 233–246.

    Google Scholar 

  • Liu, X., Li, X., Shi, X., Huang, K., & Liu, Y. (2012). A multi-type ant colony optimization (MACO) method for optimal land use allocation in large areas. International Journal of Geographical Information Science, 26(7), 1325–1343.

    Google Scholar 

  • Makropoulos, C. K., & Butler, D. (2006). Spatial ordered weighted averaging: Incorporating spatially variable attitude towards risk in spatial multi-criteria decision-making. Environmental Modelling and Software, 21(1), 69–84.

    Google Scholar 

  • Makropoulos, C. K., Butler, D., & Maksimovic, C. (2003). Fuzzy logic spatial decision support system for urban water management. Journal of Water Resources Planning and Management, 129(1), 69–77.

    Google Scholar 

  • Malczewski, J. (1996). A GIS-based approach to multiple criteria group decision-making. International Journal of Geographical Information Science, 10(8), 955–971.

    Google Scholar 

  • Malczewski, J. (1999). GIS and multicriteria decision analysis. New York: Wiley.

    Google Scholar 

  • Malczewski, J. (2000). On the use of weighted liner combination method in GIS: Common and best practice approaches. Transactions in GIS, 4(1), 5–22.

    Google Scholar 

  • Malczewski, J. (2006). GIS-based multicriteria decision analysis: A survey of the literature. International Journal of Geographical Information Science, 20(7), 703–726.

    Google Scholar 

  • Malczewski, J. (2011). Local weighted linear combination. Transactions in GIS, 15(4), 439–455.

    Google Scholar 

  • Malczewski, J., & Ogryczak, W. (1995). The multiple criteria location problem—Part 1: A generalized network model and the set of efficient solutions. Environment and Planning A, 27(12), 1931–1960.

    Google Scholar 

  • Malczewski, J., & Ogryczak, W. (1996). The multiple criteria location problem—part 2: Preference-based methods and interactive decision support. Environment and Planning A, 28(1), 69–98.

    Google Scholar 

  • Marinoni, O. (2004). Implementation of the analytical hierarchy process with VBA in ArcGIS. Computers and Geosciences, 30(6), 637–646.

    Google Scholar 

  • Mark, D. M. (2003). Geographic information science: Defining the field. In M. Duckham, M. F. Goodchild, & M. F. Worboys (Eds.), Foundations of geographic information science (pp. 3–18). New York: Taylor and Francis.

    Google Scholar 

  • Martin, N. J., St Onge, B., & Waaub, J. P. (2003). An integrated decision aid system for the development of Saint Charles River alluvial plain, Quebec, Canada. International Journal of Environment and Pollution, 12(2–3), 264–279.

    Google Scholar 

  • Mather, P.M. (1991). Computer applications in geography. Chichester: John Wiley & Sons.NCGIA (National Center for Geographic Information and Analysis), 2014, NCGIA Publications, http://ncgia.ucsb.edu/publications.php.

  • Nyerges, T. L., & Jankowski, P. (2010). Regional and urban GIS a decision support approach. New York: Guilford.

    Google Scholar 

  • Openshaw, S., & Abrahart, R. J. (2000). GeoComputation. London: Taylor & Francis.

    Google Scholar 

  • O’Sullivan, D., & Unwin, D. J. (2010). Geographic information analysis. Hoboken: John Wiley and Sons.

    Google Scholar 

  • Parker, D. C., Manson, S. M., Janssen, M. A., Hoffmann, M., & Deadman, P. (2003). Multi-agent systems for the simulation of land-use and land-cover change: A review. Annals of the Association of American Geographers, 93(2), 314–337.

    Google Scholar 

  • Payne, J. W. (1993). A constructive process view of decision making: Multiple strategies in judgment and choice. Acta Psychologica, 80(1–3), 107–141.

    Google Scholar 

  • Pereira, J. M. C., & Duckstein, L. (1993). A multiple criteria decision-making approach to GIS-based land suitability evaluation. International Journal of Geographical Information Systems, 7(5), 407–424.

    Google Scholar 

  • Pickles, J. (1995). Ground truth: The social implications of geographic information systems. New York: Guilford Press.

    Google Scholar 

  • Plata-Rocha, W., Gómez-Delgado, M., & Bosque-Sendra, J. (2011). Simulating urban growth scenarios using GIS and multicriteria analysis techniques: A case study of the Madrid region, Spain. Environment and Planning B, 38(6), 1012–1031.

    Google Scholar 

  • Reynolds, K. M., & Hessburg, P. F. (2014). An Overview of the Ecosystem Management Decision-Support System. In K. M. Reynolds, P. F. Hessburg, & P. S. Bourgeron (Eds.), Making transparent environmental management decisions (pp. 3–22). Berlin: Springer.

    Google Scholar 

  • Rinner, C. (2001). Argumentation maps—GIS-based discussion support for online planning. Environment and Planning B, 28(6), 847–863.

    Google Scholar 

  • Rinner, C. (2003). Web-based spatial decision support: Status and research directions. Journal of Geographic Information and Decision Analysis, 7(1), 14–31.

    Google Scholar 

  • Roberts, S. A., Hall, G. B., & Calamai, P. H. (2011). Evolutionary multi-objective optimization for landscape system design. Journal of Geographical Systems, 13(3), 299–326.

    Google Scholar 

  • Roy, B. (1993). Decision science or decision-aid science? European Journal of Operational Research, 66(2), 184–204.

    Google Scholar 

  • Sani, A. P., & Rinner, C. (2011). A scalable GeoWeb tool for argumentation mapping. Geomatica, 65(2), 145–156.

    Google Scholar 

  • Schlossberg, M., & Shuford, E. (2005). Delineating “public” and “participation” in PPGIS. URISA Journal, 16(2), 15–16.

    Google Scholar 

  • Sieber, R. (2006). Public participation and geographic information systems: A literature review and framework. Annals of the American Association of Geographers, 96(3), 491–507.

    Google Scholar 

  • Simão, A., Densham, P. J., & Haklay, M. (2009). Web-based GIS for collaborative planning and public participation: An application to the strategic planning of wind farm sites. Journal of Environmental Management, 90(6), 2027–2040.

    Google Scholar 

  • Simon, J., Kirkwood, C. W., & Keller, L. R. (2014). Decision analysis with geographically varying outcomes: Preference models and illustrative applications. Operations Research, 62(1), 182–194.

    Google Scholar 

  • Sugumaran, R., & DeGroote, J. (2011). Spatial decision support systems: Principles and practices. Boca Raton: CRC Press.

    Google Scholar 

  • Sui, D. Z. (1993). Integrating neural networks with GIS for spatial decision making. Operational Geographer, 11(2), 13–20.

    Google Scholar 

  • Sui, D. Z., & Goodchild, M. F. (2001). GIS as media? International Journal of Geographical Information Science, 15(5), 387–390.

    Google Scholar 

  • Thomas, R. H., & Huggett, R. J. (1980). Modelling in geography: A mathematical approach. London: Harper and Row.

    Google Scholar 

  • Tkach, R., & Simonovic, S. (1997). A new approach to multicriteria decision making in water resources. Journal of Geographical Information and Decision Analysis, 1(1), 25–43.

    Google Scholar 

  • Tong, D., & Murray, A. T. (2012). Spatial optimization in geography. Annals of the Association of American Geographers, 102(6), 1290–1309.

    Google Scholar 

  • Wang, F., Hall, G.B., & Subaryono., (1990). Fuzzy information representation and processing in conventional GIS software: Database design and applications. International Journal of Geographical Information Systems, 4(3), 261–283.

    Google Scholar 

  • Ward, D. P., Murray, A. T., & Phinn, S. R. (2003). Integrating spatial optimization and cellular automata for evaluating urban change. The Annals of Regional Science, 37(1), 131–148.

    Google Scholar 

  • Wu, F., & Webster, C. J. (1998). Simulation of land development through the integration of cellular automata and multicriteria evaluation. Environment and Planning B, 25(1), 103–126.

    Google Scholar 

  • Xiao, N., Bennett, D. A., & Armstrong, M. P. (2002). Using evolutionary algorithms to generate alternatives for multiobjective site-search problems. Environment and Planning A, 34(4), 639–656.

    Google Scholar 

  • Yatsalo, B., Didenko, V., Tkachuk, A., Gritsyuk, G., Mirzeabasov, O., Slipenkaya, V., et al. (2010). Multi-criteria spatial decision support system DECERNS: Application to land use planning. International Journal of Information Systems and Social Change, 1(1), 11–30.

    Google Scholar 

  • Yu, J., Chen, Y., & Wu, J. (2011a). Modeling and implementation of classification rule discovery by ant colony optimisation for spatial land-use suitability assessment. Computers, Environment and Urban Systems, 35, 308–319.

    Google Scholar 

  • Yu, J., Chen, Y., Wu, J., & Khan, S. (2011b). Cellular automata based spatial multi-criteria land suitability simulation for irrigated agriculture. International Journal of Geographical Information Science, 25(1), 131–148.

    Google Scholar 

  • Zarghami, M., & Szidarovszky, F. (2011). Multicriteria analysis applications to water and environment management. Berlin: Springer.

    Google Scholar 

  • Zhou, J., & Civco, D. L. (1996). Using genetic learning neural networks for spatial decision making in GIS. Photogrammetric Engineering and Remote Sensing, 62(11), 1287–1295.

    Google Scholar 

  • Zhu, X., & Dale, A. P. (2001). Java AHP: A web-based decision analysis tool for natural resource and environmental management. Environmental Modelling and Software, 16(3), 251–262.

    Google Scholar 

  • Zhu, X., Healey, R. G., & Aspinall, R. J. (1998). A knowledge-based systems approach to design of spatial decision support systems for environmental management. Environmental Management, 22(1), 35–48.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Geography, University of Western Ontario, 1151 Richmond Street, London, ON, N6A 5C2, Canada

    Jacek Malczewski

  2. Department of Geography, Ryerson University, 350 Victoria Street, Toronto, ON, M5B 2K3, Canada

    Claus Rinner

Authors
  1. Jacek Malczewski
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Claus Rinner
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jacek Malczewski .

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer Science+Business Media New York

About this chapter

Cite this chapter

Malczewski, J., Rinner, C. (2015). GIScience, Spatial Analysis, and Decision Support. In: Multicriteria Decision Analysis in Geographic Information Science. Advances in Geographic Information Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74757-4_1

Download citation

Publish with us

Policies and ethics

Search

Navigation