Landscapes are increasingly recognized for providing valuable cultural ecosystem services with numerous non-material benefits by serving as places of rest, relaxation, and inspiration that ultimately improve overall mental health and physical well-being. Maintaining and enhancing these valuable benefits through targeted management and conservation measures requires understanding the spatial and temporal determinants of perceived landscape values. Content contributed through mobile technologies and the web are emerging globally, providing a promising data source for localizing and assessing these landscape benefits. These georeferenced data offer rich in situ qualitative information through photos and comments that capture valued and special locations across large geographic areas. We present a novel method for mapping and modeling landscape values and perceptions that leverages viewshed analysis of georeferenced social media data. Using a high resolution LiDAR (Light Detection and Ranging) derived digital surface model, we are able to evaluate landscape characteristics associated with the visual-sensory qualities of outdoor recreationalists. Our results show the importance of historical monuments and attractions in addition to specific environmental features which are appreciated by the public. Evaluation of photo-image content highlights the opportunity of including temporally and spatially variable visual-sensory qualities in cultural ecosystem services (CES) evaluation like the sights, sounds and smells of wildlife and weather phenomena.

景观作为休息，放松和启发的场所，最终改善了整体的心理健康和身心健康，提供了许多非物质利益的有价值的文化生态系统服务，从而日益受到认可。通过有针对性的管理和保护措施来维持和增强这些宝贵的利益，需要了解所感知景观价值的时空决定因素。通过移动技术和网络贡献的内容正在全球涌现，为本地化和评估这些景观优势提供了有希望的数据源。这些地理参考数据提供了丰富的原位通过照片和评论获得定性信息，这些照片和评论可捕获大范围地理区域中的重要位置和特殊位置。我们提出了一种新的映射和建模景观价值和感知的方法，该方法利用了地理参考社交媒体数据的视域分析。使用高分辨率LiDAR（光检测和测距）衍生的数字表面模型，我们能够评估与户外休闲者的视觉感知品质相关的景观特征。我们的结果表明，除了特定的环境特征外，历史古迹和景点的重要性也得到了公众的赞赏。对照片图像内容的评估突显了将时空变化的视觉品质纳入景点等文化生态系统服务（CES）评估的机会，