RSRHC

Overview

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.

Tasks

Create the Advisory Board (AB) and conduct Kick-off team meeting and other subsequent meetings with advisory board
Develop satellite/aerial surface quality metrics and correlate with in-situ measurements
Carry out satellite image model portability development
Creation and maintenance of a project web site for the duration of the project
Quarterly reports to DOT and local MPO’s
Develop foundation land-cover classification
Semi-annual collaboration meetings
Assess the ability of the classification scheme to identify and locate roads
Optimization of the classification scheme for high-performance computing
Perform the paved/unpaved surface condition assessments

Colorado Center for Astrodynamics Research
ECNT 320, 431 UCB
University of Colorado
Boulder, CO 80309-0431

Page last updated: April 16, 2013

Remote Sensing of Roads and Highways in Colorado

Overview

Tasks

This page written and maintained by Tomoko Koyama.