Research | 2013
Use of Geospatial Information and Remote Sensing Data to Support Improved Roadway Access Management.
Souleyrette, Reginald R; Plazak, P E; Plazak, David J. Use of Geospatial Information and Remote Sensing Data to Support Improved Roadway Access Management. Urban Transport XII. Urban Transport and the Environment in the 21st Century. (2006, pp 477-489)
This paper highlights four examples from the State of Iowa in the United States of the use of remote sensing imagery to extract access features and crash records to identify corridors with the most promise for improving safety through better access management. Applications discussed in this paper include using remote sensing for estimating the level of access management, high priority commuting corridor identification the state of Iowa, regional access management planning for the Des Moines, Iowa USA metropolitan area, and the use of remote sensing for land use change detection and traffic monitoring. It will be useful in the corridor management planning chapter and other areas where we address methodologies for prioritizing corridors for access improvement.
(See also Plazak, D. and R. Souleyrette, Process to Identify High Priority Corridors for Access Management near Large Urban Areas in Iowa Using Spatial Data, Mid-Continent Transportation Research Symposium (2003). This study was conducted to assist the Iowa Department of Transportation in systematically identifying commuter corridors radiating out from urban areas that are most likely to need access management. Existing and likely future indicators of access management problems are considered. The project focused on four-lane expressways and two-lane arterials most likely to serve extensive commuter traffic. Spatial and statistical data was used to identify existing and possible future problem corridors. A scheme for ranking commuter routes was developed based on their need for access management. A number of data sources were integrated using geographic information systems technology. Sources included crash data, land use data, U.S. Census data, roadway configuration data, traffic data, and remote sensing data (e.g., orthophotography and satellite imagery.)