TY - GEN
T1 - Urban Mosaic
T2 - 2020 ACM CHI Conference on Human Factors in Computing Systems, CHI 2020
AU - Miranda, Fabio
AU - Hosseini, Maryam
AU - Lage, Marcos
AU - Doraiswamy, Harish
AU - Dove, Graham
AU - Silva, Cláudio T.
N1 - Funding Information:
We would like to thank Carmera for providing the NYC image data set that motivated this work. We also thank our colleagues from Kohn Pedersen Fox, Draw Brooklyn, and New York University for their help in this research. This work was supported in part by: the Moore-Sloan Data Science Environment at NYU; NASA; NSF awards CNS-1229185, CCF-1533564, CNS-1544753, CNS-1730396, CNS-1828576, CNS-1626098; CNPq grant 305974/2018-1; FAPERJ grant E-26/202.915/2019; and the NVIDIA NVAIL at NYU. C. T. Silva is partially supported by the DARPA D3M program. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of DARPA. We also thank Nvidia Corporation for donating GPUs used in this research.
Publisher Copyright:
© 2020 ACM.
PY - 2020/4/21
Y1 - 2020/4/21
N2 - Urban planning is increasingly data driven, yet the challenge of designing with data at a city scale and remaining sensitive to the impact at a human scale is as important today as it was for Jane Jacobs. We address this challenge with Urban Mosaic, a tool for exploring the urban fabric through a spatially and temporally dense data set of 7.7 million street-level images from New York City, captured over the period of a year. Working in collaboration with professional practitioners, we use Urban Mosaic to investigate questions of accessibility and mobility, and preservation and retrofitting. In doing so, we demonstrate how tools such as this might provide a bridge between the city and the street, by supporting activities such as visual comparison of geographically distant neighborhoods, and temporal analysis of unfolding urban development.
AB - Urban planning is increasingly data driven, yet the challenge of designing with data at a city scale and remaining sensitive to the impact at a human scale is as important today as it was for Jane Jacobs. We address this challenge with Urban Mosaic, a tool for exploring the urban fabric through a spatially and temporally dense data set of 7.7 million street-level images from New York City, captured over the period of a year. Working in collaboration with professional practitioners, we use Urban Mosaic to investigate questions of accessibility and mobility, and preservation and retrofitting. In doing so, we demonstrate how tools such as this might provide a bridge between the city and the street, by supporting activities such as visual comparison of geographically distant neighborhoods, and temporal analysis of unfolding urban development.
KW - data analysis
KW - interactive visualization
KW - urban data
KW - urban planning
UR - http://www.scopus.com/inward/record.url?scp=85091280396&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85091280396&partnerID=8YFLogxK
U2 - 10.1145/3313831.3376399
DO - 10.1145/3313831.3376399
M3 - Conference contribution
AN - SCOPUS:85091280396
T3 - Conference on Human Factors in Computing Systems - Proceedings
BT - CHI 2020 - Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems
PB - Association for Computing Machinery
Y2 - 25 April 2020 through 30 April 2020
ER -