Towards Extending CityGML for Property Valuation
Property Valuation ADE
S. El Yamani (TU Delft - Urban Data Science, Université de Liège, Institut agronomique et vétérinaire Hassan-II (IAV Hassan-II))
Rafika Hajji (Institut agronomique et vétérinaire Hassan-II (IAV Hassan-II))
Roland Billen (Université de Liège)
Ken Arroyo Arroyo Ohori (TU Delft - Urban Data Science)
Jasper van der van der Vaart (TU Delft - Urban Data Science)
Amir Hakim (TU Delft - Urban Data Science)
JE Stoter (TU Delft - Urban Data Science)
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Abstract
This paper introduces Property Valuation Application Domain Extension (ADE) within CityGML 3.0, aiming to integrate relevant indoor and outdoor 3D variables (cost estimation, view quality, etc.) for accurate property valuation. Current models lack the necessary features for this specific application. Leveraging IFC data for indoor elements, this ADE extends CityGML, addressing the existing gap. This paper identifies and categorizes data requirements, leading to the conceptualization and development of the model. By enriching CityGML 3.0 with IFC data, the approach introduces new features like the "Property Unit" to ensure adaptability across diverse valuation scenarios. Despite encountering data integrability challenges, we here commit to refining the model and overcoming these obstacles. A preliminary implementation using CityJSON demonstrates successful integration and paves the way for future implementation. These include developing an API platform and establishing an official repository to facilitate practical usability and scalability. This research significantly contributes to advancing property valuation processes by providing accurate valuations for stakeholders and promoting the use of 3D urban data in domain-specific extensions.
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