Loghin Ana-Maria, Otepka-Schremmer Johannes, Pfeifer Norbert
Department of Geodesy and Geoinformation, Technische Universität Wien, Wiedner Hauptstraße 8-10, 1040 Vienna, Austria.
Sensors (Basel). 2020 May 9;20(9):2695. doi: 10.3390/s20092695.
High-resolution stereo and multi-view imagery are used for digital surface model (DSM) derivation over large areas for numerous applications in topography, cartography, geomorphology, and 3D surface modelling. Dense image matching is a key component in 3D reconstruction and mapping, although the 3D reconstruction process encounters difficulties for water surfaces, areas with no texture or with a repetitive pattern appearance in the images, and for very small objects. This study investigates the capabilities and limitations of space-borne very high resolution imagery, specifically Pléiades (0.70 m) and WorldView-3 (0.31 m) imagery, with respect to the automatic point cloud reconstruction of small isolated objects. For this purpose, single buildings, vehicles, and trees were analyzed. The main focus is to quantify their detectability in the photogrammetrically-derived DSMs by estimating their heights as a function of object type and size. The estimated height was investigated with respect to the following parameters: building length and width, vehicle length and width, and tree crown diameter. Manually measured object heights from the oriented images were used as a reference. We demonstrate that the DSM-based estimated height of a single object strongly depends on its size, and we quantify this effect. Starting from very small objects, which are not elevated against their surroundings, and ending with large objects, we obtained a gradual increase of the relative heights. For small vehicles, buildings, and trees (lengths <7 pixels, crown diameters <4 pixels), the Pléiades-derived DSM showed less than 20% or none of the actual object's height. For large vehicles, buildings, and trees (lengths >14 pixels, crown diameters >7 pixels), the estimated heights were higher than 60% of the real values. In the case of the WorldView-3 derived DSM, the estimated height of small vehicles, buildings, and trees (lengths <16 pixels, crown diameters <8 pixels) was less than 50% of their actual height, whereas larger objects (lengths >33 pixels, crown diameters >16 pixels) were reconstructed at more than 90% in height.
高分辨率立体和多视图影像被用于在大面积区域上推导数字表面模型(DSM),以用于地形学、制图学、地貌学和3D表面建模等众多应用。密集影像匹配是3D重建和测绘中的关键组成部分,尽管3D重建过程在水面、图像中无纹理或具有重复图案外观的区域以及非常小的物体方面会遇到困难。本研究调查了星载甚高分辨率影像,特别是昴宿星(0.70米)和WorldView - 3(0.31米)影像在小孤立物体自动点云重建方面的能力和局限性。为此,对单个建筑物、车辆和树木进行了分析。主要重点是通过估计其高度作为物体类型和大小的函数,来量化它们在摄影测量推导的DSM中的可检测性。针对以下参数研究了估计高度:建筑物的长和宽、车辆的长和宽以及树冠直径。将从定向影像中手动测量的物体高度用作参考。我们证明基于DSM的单个物体估计高度强烈依赖于其大小,并对这种效应进行了量化。从相对于周围环境没有抬高的非常小的物体开始,到大型物体结束,我们得到了相对高度的逐渐增加。对于小型车辆、建筑物和树木(长度<7像素,树冠直径<4像素),昴宿星推导的DSM显示不到实际物体高度的20%或根本没有显示。对于大型车辆、建筑物和树木(长度>14像素,树冠直径>7像素),估计高度高于实际值的60%。在WorldView - 3推导的DSM的情况下,小型车辆、建筑物和树木(长度<16像素,树冠直径<8像素)的估计高度不到其实际高度的50%,而较大物体(长度>33像素,树冠直径>16像素)的高度重建率超过90%。