Spekboom (Portulacaria afra) UAV imagery and reference data (raw)

This dataset includes drone (Uncrewed Aerial Vehicles, UAV) orthomosaics (RGB, n =32) of Spekboom (Portulacaria afra) acquired between 2020-21 in South Africa. The resolution (ground sampling distance) of the orthomosaics amounts to approx. 1 cm. The orthomosaics are partially labelled (polygon shapefiles) in terms of Spekboom cover. Each orthomosaic comes with an AOI (area of interest, polygon shapefile) that indicates the areas where the labelling was performed. Within the extent of this AOI Spekboom canopies are assumed to be completely delineated (by visual interpretation). For visual inspection of the imagery we recommend to generate image pyramids since the image data has a very high spatial resolution. Details on the dataset are mentioned in the corresponding publication:<br> Galuszynski, N. C., Duker, R., Potts, A. J., &amp; Kattenborn, T. (2022). Automated mapping of Portulacaria afra canopies for restoration monitoring with convolutional neural networks and heterogeneous unmanned aerial vehicle imagery. <em>PeerJ</em>, <em>10</em>, e14219. https://doi.org/10.7717/peerj.14219 https://peerj.com/articles/14219/本数据集包含2020至2021年间于南非采集的共32幅RGB正射影像，由无人驾驶航空器（Uncrewed Aerial Vehicles, UAV，即无人机）航拍获取，拍摄对象为玉树（学名：Portulacaria afra，当地俗称Spekboom）。该正射影像的地面采样距离约为1厘米。部分正射影像已针对玉树覆盖范围完成标注，标注格式为多边形形状文件。每幅正射影像均附带一份感兴趣区域（area of interest, AOI，多边形形状文件），该文件明确标注了已完成标注的区域范围。在该感兴趣区域的覆盖范围内，玉树冠层已通过目视解译完成全部轮廓勾画。鉴于本数据集图像空间分辨率极高，建议生成图像金字塔以开展图像目视检查工作。本数据集的详细信息可参见以下已发表学术文献：Galuszynski, N. C., Duker, R., Potts, A. J., & Kattenborn, T. (2022). 面向修复监测的玉树冠层自动化制图：基于卷积神经网络与异构无人机影像. 《PeerJ》, 10, e14219. https://doi.org/10.7717/peerj.14219 https://peerj.com/articles/14219/