Data Driven Spatial Analysis of Urban Renewal. Network Kernel Density Estimation of Building Renovation
5th International Symposium Formal Methods in Architecture
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.
Building renovation,NKDE,urban renewal,spatial analysis