AI 中文总结
研究提出基于Roofpedia改进的深度卷积神经网络屋顶分类框架，结合高分辨率航空影像与屋顶坡度信息及公开数据集，将屋顶分为四类，识别绿色屋顶扩展机会，为城市规划提供信息，且开源可全球转移。
AI 中文摘要
有效的城市气候适应策略的发展需要关于屋顶和建筑物的全面空间信息，因为此类信息是评估绿色基础设施提供的生态系统服务的基础，特别是对于缓解城市热岛效应。虽然绿色屋顶被广泛认为是改善城市热舒适性的一项有前景的措施，但大多数现有研究要么绘制当前的绿色屋顶，要么绘制有绿化潜力的屋顶，而非两者兼顾。本研究提出了一种基于新加坡国立大学城市分析实验室开发的Roofpedia的改进型深度卷积神经网络屋顶分类框架。该模型将高分辨率航空影像与从数字表面模型得出的屋顶坡度信息相结合，并完全依赖于公开可用的瑞士地形测量局数据集：SWISSIMAGE正射影像、swissSURFACE3D高程数据和swissTLM3D建筑物足迹。应用于瑞士伯尔尼，该模型将屋顶分为四类：现有的绿色屋顶、适合安装绿色屋顶的屋顶、有太阳能板的屋顶以及不适合绿化的平屋顶。该框架识别出绿色屋顶扩展的实际机会，并为城市规划者提供基于证据的信息，以用于伯尔尼和其他瑞士城市的绿色基础设施部署。由于它是完全开源的，该框架可转移到世界各地的城市。
英文摘要
The development of effective urban climate adaptation strategies requires comprehensive spatial information on rooftops and buildings, since such information underpins the assessment of ecosystem services provided by green infrastructure, particularly for urban heat island (UHI) mitigation. Although green roofs are widely acknowledged as a promising measure for improving urban thermal comfort, most existing research maps either current green rooftops or rooftops with greening potential, but not both. This study presents a modified deep convolutional neural network rooftop classification framework based on Roofpedia, developed by the Urban Analytics Lab at the National University of Singapore. The proposed model combines high resolution aerial imagery with rooftop slope information derived from a digital surface model and relies entirely on publicly available Swisstopo datasets: SWISSIMAGE orthophotos, swissSURFACE3D elevation data, and swissTLM3D building footprints. Applied to Bern, Switzerland, the model labels rooftops into four categories: existing green roofs, rooftops suitable for green roof installation, rooftops with solar panels, and flat rooftops unsuitable for greening. The framework identifies realistic opportunities for green roof expansion and supplies urban planners with evidence-based information for green infrastructure deployment in Bern and other Swiss cities. Because it is fully open source, the framework is transferable to cities worldwide.
