Cultural ecosystem services such as aesthetic value are highly context-specific and often present difficulties in their assessment. Here we present a case study in the northern English Protected Area of the Yorkshire Dales National Park. Utilising publicly available images, paired-comparison surveys, probability modelling, machine-learning based text annotations, natural language processing and regression analysis, we developed a spatial model to predict and map landscape aesthetics across the whole site. The predictive model found eighteen significant variables, including the positive role of rural areas, mountainous landforms and vegetation for aesthetic value. Finally, we demonstrate the potential of our approach to varying size datasets and partial paired-comparison matrices, finding a very good agreement with only 20% of paired comparisons. This study demonstrates the use of freely available data and mostly open source tools to ascertain landscape aesthetic value in a large Protected Area.

诸如审美价值之类的文化生态系统服务具有高度的针对性，并且在评估中常常遇到困难。在这里，我们将介绍约克郡河谷国家公园北部英语保护区的案例研究。利用公开可用的图像，配对比较调查，概率模型，基于机器学习的文本注释，自然语言处理和回归分析，我们开发了空间模型来预测和绘制整个站点的景观美感。该预测模型发现了18个重要变量，包括农村地区，山区地貌和植被对于审美价值的积极作用。最后，我们证明了我们的方法在改变大小数据集和部分成对比较矩阵中的潜力，发现只有20％的成对比较具有很好的一致性。