Analysis and visualization of temporal variation in visual impacts

Abstract

The visual impact of infrastructure in the landscape varies through the day, month to month and over longer time periods. This paper describes the use of time-lapse imagery of a wind farm in Tasmania, Australia to develop time series of modelled visual impacts based on changes in the observed visibility. A number of candidate parameters (maximum, mean, median, percentage of time over given thresholds and impact percentiles), which indicate how visual impact changes over time under prevailing local climatic conditions, were compared. Spatial correlations between the potential indicators were examined and it was found that mean and median best correlate with the other possible measures. For locations with proposed wind farms, monitored visibility levels can be used to create images that correspond to these derived indicator conditions. As it is both easy to explain and highly correlated with all other potential indicators, the median visibility condition appears to be the best condition to be analyzed and visualized, along with the worst case, for use in public discussion. The potential of animated sequences of changing conditions—combining imagery, mapping and graphs over an extended period—is also illustrated and discussed.