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- W578391238 abstract "Integrated land use-transportation models predict future transportation demand by taking into account how households and firms arrange themselves partly as a function of the transportation system. Parcels, or land lots, are required inputs to more recent integrated models that simulate household and employment distributions at the parcel scale. Block subdivision algorithms automatically generate parcel patterns within street blocks. They can be used to prepare missing parcels from base year inputs to integrated models and in software designed to visualize their results. By generating parcels and then comparing them to ones found in a parcel database, it is possible to evaluate how well block subdivision algorithms perform. Understanding how best to subdivide blocks into parcels improves the quality of input data to integrated models and could also improve the spatial accuracy of their household and employment predictions, and consequently, their transportation demand forecasts. In this study, three block subdivision algorithms are evaluated on how closely they reproduce parcels of different block types found in a parcel database from the region of Montreal, Canada. A standardized block type classification is used that consists of mutually exclusive and nearly comprehensive categories. The results suggest that the Oriented Bounding Box algorithm is better for loose grid road networks, while the Straight Skeleton and Generalized Parcel Divider 1 algorithms are better for rectilinear and radial networks. The Straight Skeleton appears to be better for loop & lollipop road networks." @default.
- W578391238 created "2016-06-24" @default.
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- W578391238 date "2015-01-01" @default.
- W578391238 modified "2023-09-23" @default.
- W578391238 title "Testing Block Subdivision Algorithms on Block Designs" @default.
- W578391238 hasPublicationYear "2015" @default.
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