Exportar Publicação
A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.
Correia, Ricardo Mendes, Guerreiro, Maria Rosália & Brandão, Filipe J.S. (2020). Data Driven Spatial Analysis of Urban Renewal. Network Kernel Density Estimation of Building Renovation. 5th International Symposium Formal Methods in Architecture.
R. F. José et al., "Data Driven Spatial Analysis of Urban Renewal. Network Kernel Density Estimation of Building Renovation", in 5th Int. Symp. Formal Methods in Architecture, Lisboa, 2020
@misc{josé2020_1711727214188, author = "Correia, Ricardo Mendes and Guerreiro, Maria Rosália and Brandão, Filipe J.S.", title = "Data Driven Spatial Analysis of Urban Renewal. Network Kernel Density Estimation of Building Renovation", year = "2020", doi = "ISBN 978-3-030-57509-0", howpublished = "Ambos (impresso e digital)" }
TY - CPAPER TI - Data Driven Spatial Analysis of Urban Renewal. Network Kernel Density Estimation of Building Renovation T2 - 5th International Symposium Formal Methods in Architecture AU - Correia, Ricardo Mendes AU - Guerreiro, Maria Rosália AU - Brandão, Filipe J.S. PY - 2020 DO - ISBN 978-3-030-57509-0 CY - Lisboa AB - Local and national governments are increasingly sharing openly large amounts of geo-referenced data related to city planning and administrative procedures. As such new opportunities arise for advanced data-oriented tools that are capable of providing insights on the spatio-temporal correla-tion of these phenomena. Kernel Density Estimation (KDE) appears to be an efficient tool for overcoming incomplete data, because not all urban re-habilitation needs to be reported to city hall services. Recently, new re-search has proposed Network Kernel Density Estimation (NKDE) as a more accurate alternative to estimate data in urban areas. This paper aims to provide a vision of the possibilities of integrating urban renewal dispersed datasets. We propose a method to measure the intensity of renovation in a network using the spatial database of building permits from the city of Lis-bon. ER -