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Modeling the Urban Ecosystem: A Conceptual Framework

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  • M Alberti

    (Department of Urban Design and Planning, University of Washington, Box 355740, Seattle, WA 98195, USA)

Abstract

In this paper I build on current research in urban and ecological simulation modeling to develop a conceptual framework for modeling the urban ecosystem. Although important progress has been made in various areas of urban modeling, operational urban models are still primitive in terms of their ability to represent ecological processes. On the other hand, environmental models designed to assess the ecological impact of an urban region are limited in their ability to represent human systems. I present here a strategy to integrate these two lines of research into an urban ecological model (UEM). This model addresses the human dimension of the Puget Sound regional integrated simulation model (PRISM)—a multidisciplinary initiative at the University of Washington aimed at developing a dynamic and integrated understanding of the environmental and human systems in the Puget Sound. UEM simulates the environmental pressures associated with human activities under alternative demographic, economic, policy, and environmental scenarios. The specific objectives of UEM are to: quantify the major sources of human-induced environmental stresses (such as land-cover changes and nutrient discharges); determine the spatial and temporal variability of human stressors in relation to changes in the biophysical structure; relate the biophysical impacts of these stressors to the variability and spatial heterogeneity in land uses, human activities, and management practices; and predict the changes in stressors in relation to changes in human factors.

Suggested Citation

  • M Alberti, 1999. "Modeling the Urban Ecosystem: A Conceptual Framework," Environment and Planning B, , vol. 26(4), pages 605-629, August.
  • Handle: RePEc:sae:envirb:v:26:y:1999:i:4:p:605-629
    DOI: 10.1068/b260605
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    References listed on IDEAS

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    1. Dowlatabadi, Hadi, 1995. "Integrated assessment models of climate change : An incomplete overview," Energy Policy, Elsevier, vol. 23(4-5), pages 289-296.
    2. Anas, Alex, 1983. "Discrete choice theory, information theory and the multinomial logit and gravity models," Transportation Research Part B: Methodological, Elsevier, vol. 17(1), pages 13-23, February.
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    Cited by:

    1. Hu, Guangwen & Mu, Xianzhong, 2018. "Dominants in evolution of urban energy metabolism: A case study of Beijing," Ecological Modelling, Elsevier, vol. 385(C), pages 26-34.
    2. Wang, Szu-Hua & Huang, Shu-Li & Budd, William W., 2012. "Integrated ecosystem model for simulating land use allocation," Ecological Modelling, Elsevier, vol. 227(C), pages 46-55.
    3. Yaxiong Ma & Sucharita Gopal, 2018. "Geographically Weighted Regression Models in Estimating Median Home Prices in Towns of Massachusetts Based on an Urban Sustainability Framework," Sustainability, MDPI, vol. 10(4), pages 1-27, March.
    4. Xiao, Lan & Haiping, Tang & Haoguang, Liang, 2017. "A theoretical framework for researching cultural ecosystem service flows in urban agglomerations," Ecosystem Services, Elsevier, vol. 28(PA), pages 95-104.
    5. A. Meenatchi Sundaram, 2011. "Urban green-cover and the environmental performance of Chennai city," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 13(1), pages 107-119, February.
    6. Huang, Shu-Li & Kao, Wei-Chieh & Lee, Chun-Lin, 2007. "Energetic mechanisms and development of an urban landscape system," Ecological Modelling, Elsevier, vol. 201(3), pages 495-506.

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