A profiling approach
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https://doi.org/10.7480/rius.4.824Abstract
Lingering vacant facilities deteriorate the condition of an urban environment, and, as a consequence, actuate neighboring companies to leave the area as well. In addition, new development efforts keep depleting scarce land resources. In this paper, a framework is presented to match existing vacant facilities to the requirements of potential customers or owners to promote sustainable redevelopment and reuse. Important attributes for facility reuse are identified from literature. To automatically extract these attributes from models and their surroundings, Geospatial information and Building Information Models (BIM) are combined. In the proposed framework, a profile is created for each existing vacant facility by combining BIM and GIS attributes. As a result, these profiles can be matched to the desired BIM model, which the aspiring users have provided, based on a weighted distance calculation. The framework presents the most suitable vacant facilities to the users in order to promote facility reuse. These facility reuse alternatives are evaluated based on a single monetary metric that represents the effort required to partially or fully accommodate the requirements of the aspiring users, which is reflected in the weighted distance between profiles from existing vacant facilities and the facility desired by the end-user. This framework identifies suitable areas for redevelopment after which a process is started that forms an iterative and comprehensive evaluation dialog between demand and supply parties, on multiple scale levels, including various design alternatives to adapt the existing facility to the desires of the consumer and revitalize the surroundings according to Geodesign principles. A proof-of-concept of the framework is presented together with the conceptual system structure. Evaluation of the attributes and the technical implementation of their extraction from BIM and GIS data show the technical feasibility of the approach.
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Copyright (c) 2016 Tong Wang, Thomas Krijnen, Bauke de Vries
This work is licensed under a Creative Commons Attribution 4.0 International License.
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