Tree Canopies

This dataset represents the extent of the City of Cape Town’s Tree Canopy. This dataset was generated in order to provide the Recreation and Parks with a better understating of the extent of; and to aid its management decision making in relation to this green infrastructure.A Near Infra-Red (NIR) imagery dataset was acquired simultaneously with the 2018 aerial imagery. The NIR dataset was then combined into the Colour Infra-Red (CIR) composite where plant health shows up as red. A height mask of ground height to 2.75m and above was then used to remove undesirable features such as lawns and bushes using LiDAR and an auto-correlated DSM. Feature extraction using sample selections were then applied to the CIR to select all vegetation over 2.75m above ground. Input data was packaged into a 5 x 5km grid, comprising of 147 blocks across the City.Data then underwent manual GIS cleaning and quality control based on the 2018 aerial imagery, to remove anomalies from the dataset and to conduct edge-matching along the grid boundaries. All spatial layers are served live from internal systems, an item's "Last Updated" or "Publish Date" refers to the Metadata only.本数据集展示了开普敦市的树冠覆盖范围。本数据集的制作旨在为娱乐与公园管理部门提供更清晰的树冠覆盖范围认知，并辅助其针对该绿色基础设施开展管理决策。研究团队同步于2018年航空影像采集周期，获取了近红外（Near Infra-Red, NIR）影像数据集；随后将该近红外数据集与可见光波段融合，生成彩色红外（Colour Infra-Red, CIR）合成影像，植被健康状况可在该影像中以红色呈现。随后借助激光雷达（LiDAR）与自相关数字表面模型（Digital Surface Model, DSM），构建了地面高度2.75米及以上的高度掩码，以剔除草坪、灌丛等非目标地物。随后针对该彩色红外合成影像应用基于样本选择的特征提取方法，以筛选出所有地面高度2.75米以上的植被。输入数据被封装为5×5公里的网格单元，整个开普敦市共包含147个网格区块。随后基于2018年航空影像，对数据集开展人工地理信息系统（Geographic Information System, GIS）清理与质量控制工作，以剔除数据中的异常值，并完成网格边界的边缘匹配处理。所有空间图层均从内部系统实时调取，数据集条目的「最后更新时间」或「发布日期」仅指元数据本身的更新或发布时间。