以agent-based model模擬都市發展複雜時空動態之初探

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。

關鍵字

agent-based model ；都市發展動態；土地利用變遷；模型精確度評估

並列摘要

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.

並列關鍵字

Agent-based model ； Urban dynamics simulation ； Land use change ； Model evaluation

參考文獻

An, L., Linderman, M., Qi, J., Shortridge, A., and 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. DOI: 10.1111/j.1467-8306.2005.00450.x.

Bonabeau, E. (2002). Agent-based modeling: Methods and techniques for simulating human systems, Proceedings of the National Academy of Sciences, 99(3): 7280-7287. DOI: 10.1073/pnas.082080899.

Brown, D. G., Page, S., Riolo, R., Zellner, M., and 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. DOI: 10.1080/13658810410001713399.

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Dietzel, C. and 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. DOI: 10.1016/j.compenvurbsys.2005.04.001.

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以agent-based model模擬都市發展複雜時空動態之初探

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