Urban Origins/Destinations from High-Resolution Remote Sensing Images
Publication: Journal of Urban Planning and Development
Volume 132, Issue 2
Abstract
High-resolution remote sensing (RS) image data were used to identify commercial and industrial (C&I) origins and destinations (O/D). Imperviousness, derived from a RS-based land cover classification, is utilized as a surrogate for C&I locations. Imperviousness is quantified using three parameters that indicate the percent of impervious surface in a block of interest and in surrounding blocks, each quantified through an intensity of red, green, or blue. The three parameters are combined in a meaningful way through the combination of the intensity of the three colors to represent which impervious surfaces are associated with C&I locations. A block size analysis was performed to determine the block size that best differentiates between C&I and non-C&I locations. Training sites were used to develop a land cover classification with two classes—C&I or non-C&I, that incorporates the color variations associated with C&I locations, including the impact of boundaries. An accuracy assessment was performed by comparing C&I/non-C&I designations with actual land use. C&I O/D are of use in determining travel distances and as a measure of transportation system accessibility.
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Acknowledgments
The authors acknowledge the contribution of Aderbal C. Correa and Janggam Adhityawarma in the development of the Columbia, Missouri land cover classification. The authors would also like to thank the members of the Advisory Panel, as well as the other members of the overall Corridor Project team: Thomas G. Johnson, Vickie Rightmyre, Guohua Li, D. Scott Adams, and Yeesook Shin. H. Wang thanks Kathleen M. Trauth, Thomas E. Johnson, and Aderbal C. Correa for serving on his thesis committee.
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© 2006 ASCE.
History
Received: May 18, 2004
Accepted: Feb 25, 2005
Published online: Jun 1, 2006
Published in print: Jun 2006
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