An important task in terrain analysis is computing \emph{viewsheds}. A viewshed is the union of all the parts of the terrain that are visible from a given viewpoint or set of viewpoints. The complexity of a viewshed can vary significantly depending on the terrain topography and the viewpoint position. In this work we study a new topographic attribute, the \emph{prickliness}, that measures the number of local maxima in a terrain from all possible angles of view. We show that the prickliness effectively captures the potential of 2.5D TIN terrains to have high complexity viewsheds. We present optimal (for 1.5D terrains) and near-optimal (for 2.5D terrains) algorithms to compute it for TIN terrains, and efficient approximate algorithms for raster DEMs. We validate the usefulness of the prickliness attribute with experiments in a large set of real terrains.
翻译:地形分析中的一项重要任务是计算 emph{ viewsheds} 。 被观测到的是从特定角度或一组角度可见的地形所有部分的组合。 被观测到的复杂程度可能因地形地形和视角位置的不同而大不相同。 在这项工作中, 我们研究一个新的地形属性, 即 emph{ pricklishity}, 从所有可能的角度测量地形中的本地最大值。 我们显示, 模糊性有效地捕捉了 2.5D TIN 地形具有高复杂度的外观层的潜力。 我们提出了最优化的算法( 1.5D 地形) 和近优的算法( 2.5D 地形), 以图解 TIN 地形的地形和 raster DEM 的高效近似算法 。 我们用大量真实地形的实验来验证刺性属性的实用性。</s>