Building Envelopes in New York's CBD: Normalized Signed Distance Function Representation
This dataset, developed to substantiate the findings of the study by Zhuang et al. [1], comprises 1,521 building envelopes from the Central Business District (CBD) of New York City (NYC), represented in three formats: the wavefront (obj) format, the Signed Distance Function (SDF) format and 3D binar...
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Zusammenfassung: | This dataset, developed to substantiate the findings of the study by Zhuang et al. [1], comprises 1,521 building envelopes from the Central Business District (CBD) of New York City (NYC), represented in three formats: the wavefront (obj) format, the Signed Distance Function (SDF) format and 3D binary-volume format. The original mesh data is procured from the NYC Open Data Portal [2]. The process of data manipulation is thoroughly delineated in the referenced research paper [1]. [1] Zhuang, X., Ju, Y., Yang, A., & Caldas, L. (2023). Synthesis and Generation for 3D Architecture Volume with Generative Modeling. International Journal of Architecture Computing, AI, Architecture, Accessibility, & Data Justice. DOI: 10.1177/14780771231168233. [2] New York city department of city planning. NYC 3D model by community district, manhattan district, MN05. 2018. Available at: https://www.nyc.gov/site/planning/data-maps/open-data/dwn-nyc-3d-model-download.page. Accessed 15 July 2023. |
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DOI: | 10.5281/zenodo.8151196 |