Large-Area Road-Surface Quality and Land-Cover Classification Using Very-High Spatial Resolution Aerial and Satellite Data
The project aims to combine the image analysis and classification expertise of the University of Colorado with the large data observational and analysis capabilities of DigitalGlobe Inc. to develop two products:
(a) large-area very-high spatial resolution classification map of widely applicable land-cover classes and
(b) satellite- based estimates of paved surface quality using the International Roughness Index (IRI).
This will provide our partner transportation organizations the ability to leverage this information for planning and monitoring activities. The relationship of surface quality metrics to remote sensing data will first be established through the correlation of in-situ IRI measurements with aerial data. This relationship will then be extended to a large-area using very-high resolution satellite data. This data will also form the foundation of the classification maps, providing the eight-band multispectral and panchromatic resolution necessary to develop urban scale (on the order of a meter) resolution information.
Page last updated: April 15, 2014