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.

基础设施在景观中的视觉影响在一天，一个月，一个月以及更长的时间内会有所不同。本文介绍了如何使用澳大利亚塔斯马尼亚州风电场的时移图像，根据观测到的能见度变化，开发模拟视觉影响的时间序列。比较了许多候选参数（最大，平均，中位数，超过给定阈值的时间百分比和影响百分位数），这些参数指示了在主要的局部气候条件下视觉影响如何随时间变化。研究了潜在指标之间的空间相关性，发现平均数和中位数与其他可能的测量值最佳相关。对于拟建风电场的地点，可以使用监视的能见度水平来创建与这些导出的指标条件相对应的图像。由于它很容易解释并且与所有其他潜在指标高度相关，因此中值能见度条件似乎是要分析和可视化的最佳条件，最坏的情况是要在公开讨论中使用。还将说明和讨论不断变化的条件（将图像，地图和图表组合在一起）在不断变化的条件下的动画序列的潜力。