以agent-based model模擬都市發展複雜時空動態之初探

An Agent-based Model for Simulating Complex Urban Dynamic Development Patterns

10.6128/CP.202006_47(2).0002

顧嘉安(Chia-An Ku)

agent-based model ； 都市發展動態 ； 土地利用變遷 ； 模型精確度評估 ； Agent-based model ； Urban dynamics simulation ； Land use change ； Model evaluation

都市與計劃

47卷2期（2020 / 06 / 30）

149 - 172

繁體中文

都會區人口成長所帶來的建成環境開發一直是都市研究者及規劃者非常關注的議題，因其對區域社經結構及自然環境都會造成顯著的影響。近年來，氣候變遷調適與極端災害等議題，亦與都會區空間型態變化息息相關。為能制定出兼具效益及效率的氣候變遷及災害調適策略，了解都會區土地利用變遷的實際機制就成為了規劃者必須面對的課題。 然而，由於都會區土地利用變遷在時間與空間上具有複雜地交互作用過程，且牽涉之機制亦相當繁複，較難透過傳統統計式或靜態式的土地利用推估方法深入探討。有鑒於此，本研究建置了一整合性的都會區土地利用模擬模型，以大組數模擬等方式，透過agent-based modelling技術重建都會區發展變遷的重要機制，做為了解過去變化及推估未來發展情境之重要科學依據。模型中考量權益關係人（stakeholders）彼此間及其與都市環境間的複雜時空交互作用，以形塑初步的空間動態整合模型。根據敏感性分析（sensitivity analysis）、校正（calibration）及驗證（validation）之結果，說明本研究所建立之agent-based模型能夠有效反映其變化過程，並期望所建構之模型未來能夠成為評估都會區發展策略之有效工具。

Rapid urban population growth has changed urban land uses significantly, which has influenced the balance of human and natural environments. The government has recently begun developing climate change and disasters adaptation strategies, which are also significantly related to land-use change in the urban areas. Developing effective and efficient strategies requires an understanding of the actual mechanisms underlying the land-use change processes. However, the complex interactions amongst these mechanisms are extremely difficult to understand using conventional statistics-based or static models, which failed to explore the dynamic relationships between processes. Therefore, the aim of this study was to integrate agent behaviours in a simulation model of urban land-use change in Taipei City. In this model, the decision-making behaviours of stakeholders in the land-use change processes are constructed, which form the essential elements in the model. The sensitivity analysis results indicate a stable relationship between input and output parameters, suggesting the stability of the model when generating future scenarios is ideal. The calibration and validation processes also show that the model generates reasonable simulated results, comparing with actual land-use pattern according to five indicators. The integrated model developed in this research is hoped to serve as a useful tool for evaluating the effectiveness of different urban strategies. Finally, the use of an open-source platform enables integration of different impact analysis models for strategy evaluation under different climate and disaster circumstances.

1. Agarwal, C.,Green, G. M.,Grove, J. M.,Evans, T. P.,Schweik, C. M.(2002).Gen. Tech. Rep.Gen. Tech. Rep.,Newton Square:U.S. Department of Agriculture, Forest Service, Northeastern Research Station.
2. An, L.,Linderman, M.,Qi, J.,Shortridge, A.,Liu, J.(2008).Exploring complexity in a human–environment system: An agent-based spatial model for multidisciplinary and multiscale integration.Annals of the Association of American Geographers,95(1),54-79.
3. Auyung, S. Y.(1998).Foundations of Complex-Systems Theories in Economics, Evolutionary Biology, and Statistical Physics.Cambridge:Cambridge University Press.
4. Bonabeau, E.(2002).Agent-based modeling: Methods and techniques for simulating human systems.Proceedings of the National Academy of Sciences,99(3),7280-7287.
5. Brown, D. G.,Page, S.,Riolo, R.,Zellner, M.,Rand, W.(2005).Path dependence and the validation of agent-based spatial models of land use.International Journal of Geographical Information Science,19(2),153-174.
6. Carver, S. J.(1991).Integrating multi-criteria evaluation with geographical information systems.International Journal of Geographical Information Systems,5(3),321-339.
7. Dietzel, C.,Clarke, K.(2006).The effect of disaggregating land use categories in cellular automata during model calibration and forecasting.Computer, Environment and Urban Systems,30(1),78-101.
8. Epstein, J. M.(2006).Generative Social Science: Studies in Agent-based Computational Modeling.Princeton:Princeton University Press.
9. Epstein, J. M.,Axtell, A.(1996).Growing Artificial Societies: Social Science from the Bottom Up.Cambridge:MIT Press.
10. Farmer, J. D.,Foley, D.(2009).The economy needs agent-based modelling.Nature,460(7256),685-686.
11. Filatova, T.,Parker, D.,van der Veen, A.(2009).Agent-based urban land markets: Agent's pricing behavior, land prices and urban land use change.Journal of Artificial Societies and Social Simulation,12(13),1-30.
12. Freeman, R. E.(1984).Strategic Management: A Stakeholder Approach.Boston:Pitman.
13. Grimm, V.,Berger, U.,DeAngelis, D. L.,Polhill, J. G.,Giske, J.,Railsback, S. F.(2010).The ODD protocol: A review and first update.Ecological modelling,221(23),2760-2768.
14. Guan, Q.,Wang, L.,Clarke, K. C.(2005).An artificial-neural-network-based, constrained ca model for simulating urban growth.Cartography and Geographic Information Science,32(4),369-380.
15. Haase, D.,Haase, A.,Kabisch, N.,Kabisch, S.,Rink, D.(2012).Actors and factors in land-use simulation: The challenge of urban shrinkage.Environmental Modelling & Software,35,92-103.
16. Hansen, H. S.(2012).Empirically derived neighbourhood rules for urban land-use modelling.Environment and Planning B: Planning and Design,39(2),213-228.
17. Jjumba, A.,Dragićević, S.(2012).High resolution urban land-use change modeling: Agent iCity approach.Applied Spatial Analysis,5(4),291-315.
18. Klosterman, R. E.(1999).The what if? Collaborative planning support system.Environment and Planning B: Planning and Design,26(3),393-408.
19. Ku, C. A.(2016).UK,University of Cambridge.
20. Labiosa, W. B.,Forney, W. M.,Esnard, A. M.,Mitsova-Boneva, D.,Bernknopf, R.,Hearn, P.,Hogan, D.,Pearlstine, L.,Strong, D.,Gladwin, H.,Swain, E.(2013).An integrated multi-criteria scenario evaluation web tool for participatory land-use planning in urbanized areas: The ecosystem portfolio model.Environmental Modelling & Software,41,210-222.
21. Ligtenberg, A.,Bregt, A. K.,van Lammeren, R.(2001).Multi-actor-based land use modelling: Spatial planning using agents.Landscape and Urban Planning,56(1-2),21-33.
22. Manson, S. M.(2006).Bounded rationality in agent based models: Experiments with evolutionary programs.International Journal of Geographical Information Science,20(9),991-1012.
23. Matthews, R. B.,Gilbert, N. G.,Roach, A.,Polhill, J. G.,Gotts, N. M.(2007).Agent-based land-use models: A review of applications.Landscape Ecology,22(10),1447-1459.
24. Mena, C. F.,Walsh, S. J.,Frizzelle, B. G.,Xiaozheng, Y.,Malanson, G. P.(2011).Land use change on household farms in the Ecuadorian Amazon: Design and implementation of an agentbased model.Applied Geography,31(1),210-222.
25. Mitchell, R. K.,Agle, B. R.,Wood, D. J.(1997).Toward a theory of stakeholder identification and salience: Defining the principle of who and what really counts.The Academy of Management Review,22(4),853-886.
26. Murray-Rust, D.,Rieser, V.,Robinson, D. T.,Mili i, V.,Rounsevell, M.(2013).Agentbased modelling of land use dynamics and residential quality of life for future scenarios.Environmental Modelling & Software,46,75-89.
27. Parker, D. C.,Manson, S. M.,Janssen, M. A.,Hoffmann, M. J.,Deadman, P.(2003).Multiagent systems for the simulation of land-use and land-cover change: A review.Annals of the Association of American Geographers,93(2),314-337.
28. Patel, M.,Kok, K.,Rothman, D. S.(2007).Participatory scenario construction in land use analysis: An insight into the experiences created by stakeholder involvement in the Northern Mediterranean.Land Use Policy,24(3),546-561.
29. Pijanowski, B. C.,Brown, D. G.,Shellito, B. A.,Manik, G. A.(2002).Using neural networks and GIS to forecast land use changes: A Land Transformation Model.Computers, Environment and Urban Systems,26(6),553-575.
30. Pourebrahim, S.,Hadipour, M.,Mokhtar, M. B.(2011).Integration of spatial suitability analysis for land use planning in coastal areas; case of Kuala Langat District, Selangor, Malaysia.Landscape and Urban Planning,101(1),84-97.
31. Robinson, D. T.,Brown, D. G.(2009).Evaluating the effects of land use development policies on ex urban forest cover: An integrated agent based GIS approach.International Journal of Geographical Information Science,23(9),1211-1232.
32. Robinson, D. T.,Brown, D. G.,Parker, D. C.,Schreinemachers, P.,Janssen, M. A.,Huigen, M.,Barnaud, C.(2007).Comparison of empirical methods for building agent-based models in land use science.Journal of Land Use Science,2(1),31-55.
33. Saltelli, A.,Annoni, P.,Azzini, I.,Campolongo, F.,Ratto, M.,Tarantola, S.(2010).Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index.Computer Physics Communications,181(2),259-270.
34. Schneider, L. C.,Pontius, R. G., Jr.(2001).Modeling land-use change in the Ipswich watershed, Massachusetts, USA.Agriculture, Ecosystems & Environment,85(1-3),83-94.
35. Schreinemachers, P.,Berger, T.(2006).Land use decisions in developing countries and their representation in multi-agent systems.Journal of Land Use Science,1(1),29-44.
36. Sobol, I. M.(2001).Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates.Mathematics and Computers in Simulation,55(1-3),271-280.
37. Syphard, A. D.,Clarke, K. C.,Franklin, J.(2005).Using a cellular automaton model to forecast the effects of urban growth on habitat pattern in southern California.Ecological Complexity,2(2),185-203.
38. Tian, G.,Ouyang, Y.,Quan, Q.,Wu, J.(2011).Simulating spatiotemporal dynamics of urbanization with multi-agent systems–A case study of the Phoenix metropolitan region, USA.Ecological Modelling,222(5),1129-1138.
39. van Vliet, J.,Bregt, A. K.,Hagen-Zanker, A.(2011).Revisiting Kappa to account for change in the accuracy assessment of land-use change models.Ecological Modelling,222(8),1367-1375.
40. Veldkamp, A.,Lambin, E. F.(2001).Predicting land-use change.Agriculture, Ecosystems & Environment,85(1-3),1-6.
41. Villamor, G. B.,Le, Q. B.,Djanibekov, U.,van Noordwijk, M.,Vlek, P. L.(2014).Biodiversity in rubber agroforests, carbon emissions, and rural livelihoods: An agent-based model of land-use dynamics in lowland Sumatra.Environmental Modelling & Software,61,151-165.
42. Wang, H.,Shen, Q.,Tang, B. S.,Skitmore, M.(2013).An integrated approach to supporting land-use decisions in site redevelopment for urban renewal in Hong Kong.Habitat International,38,70-80.
43. Yu, J.,Chen, Y.,Wu, J.(2011).Modeling and implementation of classification rule discovery by ant colony optimisation for spatial land-use suitability assessment.Computers, Environment and Urban Systems,35(4),308-319.
44. Zhao, F.,Chung, S.(2006).A report to FDOT Systems Planning OfficeA report to FDOT Systems Planning Office,未出版

1. 賴世剛,陳志閣,柯博晟(2022)。土地開發過程中自我組織特性之探討：經濟財產權、賽局理論及電腦模擬分析。建築與規劃學報，22(1&2)，1-18。