TY - GEN
T1 - Visual Analytics for Profiling Land Use Changes
AU - Santos, Claudio
AU - Hosseini, Maryam
AU - Rulff, Joao
AU - Miranda, Fabio
AU - Wilson, Luc
AU - Silva, Claudio
AU - Ferreira, Nivan
AU - Lage, Marcos
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - The growth of cities calls for regulations and zoning rules on how each piece of urban space will be used. Tracking land use can reveal a wealth of information about urban development. For that matter, cities have been releasing data sets describing the historical evolution of the shape and the attributes of land units. The complex nature of land-use data, however, makes the analysis of such data challenging and time-consuming. To address these challenges, we propose Urban Chronicles, a visual analytics system that enables interactive exploration of land-use changes. Using New York City's Primary Land Use Tax Lot Output (PLUTO), we show the system's capabilities to explore the data from several years at different scales. UrbanChron-iclessupports on-the-fly aggregation and filtering operations that leverage the hierarchical nature of the data set to index the shape and attributes of geographical regions that change over time. Finally, we demonstrate the system's utility through case studies that analyze the impact of Hurricane Sandy on land use attributes and the effects of rezoning plans in Brooklyn.
AB - The growth of cities calls for regulations and zoning rules on how each piece of urban space will be used. Tracking land use can reveal a wealth of information about urban development. For that matter, cities have been releasing data sets describing the historical evolution of the shape and the attributes of land units. The complex nature of land-use data, however, makes the analysis of such data challenging and time-consuming. To address these challenges, we propose Urban Chronicles, a visual analytics system that enables interactive exploration of land-use changes. Using New York City's Primary Land Use Tax Lot Output (PLUTO), we show the system's capabilities to explore the data from several years at different scales. UrbanChron-iclessupports on-the-fly aggregation and filtering operations that leverage the hierarchical nature of the data set to index the shape and attributes of geographical regions that change over time. Finally, we demonstrate the system's utility through case studies that analyze the impact of Hurricane Sandy on land use attributes and the effects of rezoning plans in Brooklyn.
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U2 - 10.1109/SIBGRAPI59091.2023.10347138
DO - 10.1109/SIBGRAPI59091.2023.10347138
M3 - Conference contribution
AN - SCOPUS:85199959639
T3 - Brazilian Symposium of Computer Graphic and Image Processing
SP - 31
EP - 36
BT - Proceedings - 2023 36th Conference on Graphics, Patterns and Images, SIBGRAPI 2023
A2 - Emmendorfer, Leonardo Ramos
A2 - Goncalves, Luiz Marcos Garcia
PB - IEEE Computer Society
T2 - 36th Conference on Graphics, Patterns and Images, SIBGRAPI 2023
Y2 - 6 November 2023 through 9 November 2023
ER -