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Towards a Planning Decision Support System for Low-Carbon Urban Development

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Computational Science and Its Applications - ICCSA 2011 (ICCSA 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6782))

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Abstract

The flows of carbon and energy produced by urbanized areas represent one of the aspects of urban sustainability that can have an important impact on climate change. For this reason, in recent years the quantitative estimation of the so-called urban metabolism components has increasingly attracted the attention of researchers from different fields. On the other hand, it has been well recognized that the structure and design of future urban development can significantly affect the flows of material and energy exchanged by an urban area with its surroundings. In this context, the paper discusses a software framework able to estimate the carbon exchanges accounting for alternative scenarios which can influence urban development. The modelling system is based on four main components: (i) a Cellular Automata model for the simulation of the urban land-use dynamics; (ii) a transportation model, able to estimate the variation of the transportation network load and (iii) the ACASA (Advanced Canopy-Atmosphere-Soil Algorithm) model which was tightly coupled with the (iv) mesoscale weather model  WRF for the estimation of the relevant urban metabolism components. An in-progress application to the city of Florence is presented and discussed.

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Author information

Authors and Affiliations

  1. DADU, Department of Architecture, Planning and Design, University of Sassari, Alghero, Italy

    Ivan Blecic, Arnaldo Cecchini & Giuseppe A. Trunfio

  2. LAWR, Land, Air and Water Resources, University of California, Davis, CA, USA

    Matthias Falk & David R. Pyles

  3. DESA, Dipartimento di Economia e Sistemi Arborei, Università di Sassari, Italy

    Serena Marras & Donatella Spano

  4. CMCC, Centro Euro-Mediterraneo per i Cambiamenti Climatici, IAFENT-Sassari, Italy

    Ivan Blecic, Matthias Falk, Serena Marras, David R. Pyles, Donatella Spano & Giuseppe A. Trunfio

Authors
  1. Ivan Blecic
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  2. Arnaldo Cecchini
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  3. Matthias Falk
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  4. Serena Marras
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  5. David R. Pyles
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  6. Donatella Spano
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  7. Giuseppe A. Trunfio
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Editor information

Editors and Affiliations

  1. L.I.S.U.T. - D.A.P.I.T., Basilicata University Potenza, 10, Viale dell’Ateneo Lucano, 85100, Potenza, Italy

    Beniamino Murgante

  2. Department of Mathematics and Computer Science, University of Perugia, Via Vanvitelli, 1, 06123, Perugia, Italy

    Osvaldo Gervasi

  3. Department of Applied Mathematics and Computational Sciences, University of Cantabria, Avda. de los Castros, s/n, C.P. 39005, Santander, Spain

    Andrés Iglesias

  4. School of Business Systems, Monash University, 3800, Clayton, VIC, Australia

    David Taniar

  5. Department of Intelligent Informatics, Kyushu Sangyo University, 2-3-1 Matsukadai, Higashi-ku, 813-8503, Fukuoka, Japan

    Bernady O. Apduhan

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© 2011 Springer-Verlag Berlin Heidelberg

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Blecic, I. et al. (2011). Towards a Planning Decision Support System for Low-Carbon Urban Development. In: Murgante, B., Gervasi, O., Iglesias, A., Taniar, D., Apduhan, B.O. (eds) Computational Science and Its Applications - ICCSA 2011. ICCSA 2011. Lecture Notes in Computer Science, vol 6782. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21928-3_30

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  • DOI: https://doi.org/10.1007/978-3-642-21928-3_30

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21927-6

  • Online ISBN: 978-3-642-21928-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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