Visual impact is one of the main factors influencing the acceptance of wind farms by the public and by the authorities. It therefore often sets the environmental and social limits of energy policy and energy use. However, the assessment of visual impacts is subjective, as is often pointed out by critics of the evaluation process. The study presented here for the first time uses accurately and objectively measurable landscape indices to directly predict the visual impact of onshore wind turbines. The method also for the first time evaluates map-based landscape indices in a panoramic simulation, and this provides a better match of visual preferences with landscape indices than the cartographic projection used until now. 400 respondents from four Central European countries (Austria, Germany, Poland and Czechia) provided an evaluation of their scenic perception of 32 different landscapes, in each case with and without wind turbines. At the same time, we analysed 12 indices characterizing the principal landscape components (relief, land cover and landscape pattern) on the basis of the 32 landscape photographs. These were further tested as predictors of visual impact. The most prominent predictors of visual impact were the Percentage of Industrial Area (including Commercial, Logistic and Mining Areas), Percentage of Forest Cover, Density of Technical Infrastructure, Number of Elevation Landmarks, and Elevation Variation. None of the three landscape pattern indices was statistically significant. On the basis of a regression model that is able to predict the potential visual impact in large areas of four Central European countries (over 830,000 km²), we present the general principles of an objectivized method for predicting the visual impact of onshore wind farms. The method makes an automatic assessment of the visual impact in large areas of entire regions or countries via a GIS analysis of Sentinel data and DEM data. This forms a good basis for both preventive evaluation and causal evaluation, and provides significant support for objectivizing the planning and decision process in order to mitigate negative environmental and social impacts of the use of wind energy.

视觉影响是影响公众和当局接受风电场的主要因素之一。因此，它经常设置能源政策和能源使用的环境和社会限制。但是，对视觉影响的评估是主观的，正如评估过程的批评者经常指出的那样。此处首次提出的研究使用准确客观的可测量景观指数直接预测陆上风力涡轮机的视觉影响。该方法还是首次在全景模拟中评估基于地图的景观指数，与迄今为止使用的制图投影相比，这提供了视觉偏好与景观指数的更好匹配。来自四个中欧国家（奥地利，德国，波兰和捷克共和国）评估了他们对32种不同景观的风景感知，每种情况都使用或不使用风力涡轮机。同时，我们根据32幅景观照片分析了12个表征主要景观成分（起伏，土地覆盖和景观格局）的指数。这些被进一步测试为视觉影响的预测指标。视觉影响最主要的预测指标是工业区（包括商业区，后勤区和采矿区）的百分比，森林覆盖率，技术基础设施密度，标高地标数量和标高变化。三个景观格局指数均无统计学意义。²），我们提出了一种客观化方法的一般原理，该方法可预测陆上风电场的视觉影响。该方法通过对Sentinel数据和DEM数据进行GIS分析，自动评估整个地区或国家/地区在大范围内的视觉影响。这为预防性评估和因果性评估奠定了良好的基础，并为客观化规划和决策过程提供了大力支持，从而减轻了使用风能的负面环境和社会影响。