In this paper, a simple technique for Unmanned Aerial Vehicles (UAVs) potential landing site detection using terrain information through identification of flat areas, is presented. The algorithm utilizes digital elevation models (DEM) that represent the height distribution of an area. Flat areas which constitute appropriate landing zones for UAVs in normal or emergency situations result by thresholding the image gradient magnitude of the digital surface model (DSM). The proposed technique also uses connected components evaluation on the thresholded gradient image in order to discover connected regions of sufficient size for landing. Moreover, man-made structures and vegetation areas are detected and excluded from the potential landing sites. Quantitative performance evaluation of the proposed landing site detection algorithm in a number of areas on real world and synthetic datasets, accompanied by a comparison with a state-of-the-art algorithm, proves its efficiency and superiority.

中文翻译：

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通过数字高程模型分析潜在的无人机着陆点检测

在本文中，介绍了一种简单的无人机（UAV）潜在着陆点检测技术，该技术通过识别平坦区域使用地形信息。该算法利用表示区域高度分布的数字高程模型 (DEM)。在正常或紧急情况下构成 UAV 适当着陆区的平坦区域是通过对数字表面模型 (DSM) 的图像梯度幅度进行阈值处理而产生的。所提出的技术还在阈值梯度图像上使用连接组件评估，以便发现足够大小的连接区域以供着陆。此外，检测到人造结构和植被区并将其排除在潜在着陆点之外。