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  • 标题:Measuring Urban Renewal: A Dual Kernel Density Estimation to Assess the Intensity of Building Renovation—Case Study in Lisbon
  • 本地全文:下载
  • 作者:Filipe J. S. Brandão ; Ricardo M. Correia ; Alexandra Paio
  • 期刊名称:Urban Science
  • 印刷版ISSN:2413-8851
  • 出版年度:2018
  • 卷号:2
  • 期号:3
  • 页码:91-105
  • DOI:10.3390/urbansci2030091
  • 出版社:MDPI Publishing
  • 摘要:In the cities of post-industrialized countries, renovation is the main part of building construction activity and has a major urban impact. Measuring this ongoing phenomenon and its distribution is of great usefulness for municipality urban planning and public policies. In this context, it is essential to introduce tools and processes that can allow for describing and predict how building renovation evolves. Open databases have become a valuable resource for observing processes and interactions in urban context. Data-driven analysis methods were used to directly interact with open city data, thus aiming to propose an alternative building renovation approach based on data gathering, parametric modeling, and visualization. Kernel Density Estimation (KDE) is an efficient tool that overcomes incomplete data, as not all renovation is reported to city halls. This article presents a preliminary study on a method of measuring building renovation intensity using the city of Lisbon building permit alphanumerical and spatial database as a case study.
  • 关键词:building renovation; dual kernel density estimation; Lisbon building renovation ; dual kernel density estimation ; Lisbon
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