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Integrated Forest Biometrics for Landscape-Responsive Coastal Urbanism

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Abstract

Within this research project, forestry and architecture are merged through an integration of data and modeling protocols for the design of urban landscapes. More specifically, this approach couples simulation of landscape systems, in this case mangrove forest, with 3d modeling software commonly used in design professions. The goals of the work include enabling feedback from living systems in the evolution of urban forms, development of an interdisciplinary design tool for coastal urban areas, and speculation on possible future alternatives for development in ecologically-fragile zones. Although the forms developed herein reduce the challenge to a minimum of variables, they also lay the groundwork for future added complexity in the research. The results of the modeling investigation indicated a higher level of integration would benefit the work, while at the same time maintaining the discrete quantifiable means to extracting values from the system for evaluating the designs. Ultimately, this framework may serve to challenge conventional planning and urban design methodologies that lack ecosystem services as part of the equation in formulating urban landscapes. This more holistic approach may serve to better integrate the dynamics of living systems and to consider real-time feedback as part of the datasets to be utilized in understanding and adapting our habitat as it evolves over time.

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Acknowledgements

The authors gratefully acknowledge Anna Dyson at the Center for Architecture, Science and Ecology (CASE) at Rensselaer Polytechnic Institute and Uwe Grueters at The Dresden University of Technology for their support in this research.

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Correspondence to Keith Van de Riet .

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Van de Riet, K., Berger, U. (2015). Integrated Forest Biometrics for Landscape-Responsive Coastal Urbanism. In: Thomsen, M., Tamke, M., Gengnagel, C., Faircloth, B., Scheurer, F. (eds) Modelling Behaviour. Springer, Cham. https://doi.org/10.1007/978-3-319-24208-8_36

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  • DOI: https://doi.org/10.1007/978-3-319-24208-8_36

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