Vegetated roofs provide many ecosystem services and support urban biodiversity. While it would be interesting to study the contribution of vegetated roofs to ecological corridors, vegetated roofs are listed in no French databases. Because of their intrinsic nature as roofs, their small number, their small size, and the type of vegetation planted on them, vegetated roofs seem to be very difficult to identify. We propose a method to automatically identify vegetated roofs. Using infrared aerial photographs and building shape data, we were able to build a model detecting vegetated roofs using remote sensing and supervised classification techniques. The major difficulty lies in distinguishing between real vegetated roofs and roofs partially covered by tree foliage growing on the ground. In this operation, our classification model obtains an error rate of ∼18 % . We improve the knowledge of vegetation detection in cities. Moreover, it opens interesting perspectives on the analysis of ecological networks in cities as a function of building height. In addition, it could be an interesting tool for municipalities to monitor urban vegetation development and to prioritize vegetated roofs planning.

中文翻译：

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法国巴黎采用新的可复制方法评估植被屋顶的遥感

植被屋顶可提供许多生态系统服务并支持城市生物多样性。虽然研究植被屋顶对生态走廊的贡献会很有趣，但法国数据库中都没有列出植被屋顶。由于其作为屋顶的固有性质，数量少，尺寸小以及种植在上面的植被类型，植被屋顶似乎很难识别。我们提出了一种自动识别植被屋顶的方法。利用红外航拍照片和建筑物形状数据，我们能够建立使用遥感和监督分类技术检测植被屋顶的模型。主要困难在于区分真实的植被屋顶和地面上生长的树木部分覆盖的屋顶。在此操作中，我们的分类模型得出的错误率约为18％。我们提高了城市植被检测的知识。此外，它为根据建筑高度对城市生态网络进行分析开辟了有趣的观点。此外，它对于市政当局监控城市植被发展并优先安排植被屋顶计划来说可能是一个有趣的工具。