| SPECTROMETRY
AND HYPERSPECTRAL REMOTE SENSING OF URBAN ROAD INFRASTRUCTURE
Martin Herold, Margaret E. Gardner, Val Noronha and Dar
A. Roberts
Department of Geography
University
of California Santa Barbara
Santa Barbara, CA 93106 USA
Email: martin@geog.ucsb.edu / Tel. 001-805-893-4196
Abstract
Based on a comprehensive regional spectral library from
spectrometer ground measurements and high-resolution hyperspectral
AVIRIS data, this research investigates generic spectral
characteristics, and related mapping capabilities and limitations
for extracting roads of various types, delineating road
centerlines, and surveying pavement quality within the urban
environment. The methods are generally successful in identifying
roads and road pavement types, but inaccuracies arise from
spectral similarities between asphalt surfaces and specific
roofing materials. Findings indicate that it is possible
to spectrally characterize and estimate age of pavement
and a few specific asphalt surface quality parameters (e.g.
raveling). Finally, this research argues that the complex
spectral characteristics of the urban environment result
in distinct limitations in mapping urban areas using common
multispectral sensor data. Sensors with an “optimized”
set of narrow spectral bands would be preferred for prospective
applications.
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