Learning from urban form to predict building heights ...
Understanding cities as complex systems, sustainable urban planning depends on reliable high-resolution data, for example of the building stock to upscale region-wide retrofit policies. For some cities and regions, these data exist in detailed 3D models based on real-world measurements. However, they are still expensive to build and maintain, a significant challenge, especially for small and medium-sized cities that are home to the majority of the European population. New methods are needed to estimate relevant building stock characteristics reliably and cost-effectively. Here, we present a ma... Mehr ...
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Dokumenttyp: | Artikel |
Erscheinungsdatum: | 2020 |
Verlag/Hrsg.: |
Technische Universität Berlin
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Schlagwörter: | 710 Städtebau / Raumplanung / Landschaftsgestaltung / cities / machine learning / roads / Netherlands / Europe / Italy / machine learning algorithms / neighborhoods |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-29159434 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | https://dx.doi.org/10.14279/depositonce-11114 |