id |
caadria2021_135 |
authors |
Mo, Yichen, Li, Biao, Wu, Jiaqian and Tang, Peng |
year |
2021 |
title |
Archibase:A City-Scale Spatial Database for Architectural Research |
doi |
https://doi.org/10.52842/conf.caadria.2021.2.519
|
source |
A. Globa, J. van Ameijde, A. Fingrut, N. Kim, T.T.S. Lo (eds.), PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 2, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, pp. 519-528 |
summary |
The explosion of geolocation data and data-based algorithms has the potential to analyze sophisticated urban areas and foster a more robust urban model. To better collect and organize the city data, this paper introduces a city-scale spatial database called ArchiBase, built upon Java and web APIs of open source databases. With hierarchical, layered, and regularly-updated spatial data defined by relation table, ArchiBase allows indexing and geometric searching of the entire city and supports applications and extensions for different cities. This research is from a graduate urban design course aiming to renew Prato, an industrial city in Italy. ArchiBase first creates the base version of Prato from multiple data sources, then illustrates the usability and expandability through three simple applications. The use of ArchiBase can better interpret future cities and demonstrate the unparalleled opportunities of collaboration and remote work for urban researchers and designers. |
keywords |
Spatial Database; Data Model; Urban Design; Design Support Tools |
series |
CAADRIA |
email |
moyichen@seu.edu.cn |
full text |
file.pdf (12,726,422 bytes) |
references |
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last changed |
2022/06/07 07:58 |
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