Abstract
Landscape aesthetics and environmental quality have both become central investigatory areas in transportation planning and design. Environmental designers are interested in applying research-based models to study the effects of specific transportation design treatments on the built and natural landscape. The development of a perception-based visual quality predictive equation is investigated for application in both naturalistic and designed landscapes for transportation planning and design projects. The prediction model contained total area of noospheric features and total area of motorized vehicles; presence of humans, wildlife, utility structures, and foreground flowers; total area of distant nonvegetation landscape features such as mountains and buttes; perimeter of intermediate nonvegetation; total area of foreground vegetation; and openness, mystery, and environmental quality indexes (p < 0.0001 for the overall regression, p ≤ 0.05 for each regressor using Type II sums of squares, and multiple. R-square of 0.67). Other variables such as motorized boats, nonflowering foreground herbaceous plants, a greenness index, fire, total area of exposed foreground substrate, smoke, water, smoothness, and the Shafer index were not significant regressors. By using a graph plotting the 95 percent confidence limits for the equation, an investigator can predict the statistical differences between a pair of images at a 90 percent confidence level.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: Transportation Research Record: Journal of the Transportation Research Board
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.