ABSTRACT

The detection of pre-Colombian geoglyphs, geometric structures outlined by trenches or walls, from airborne LiDAR data is usually made by visual observation of the variation in elevation and commonly using additional hillshading. Depending on the area covered by LiDAR to inspect and the variation in elevation, this method can be time consuming and inaccurate as it required to constantly adjust the contrasts of the elevation image or the parameter of the hillshading function, and the user can miss some important archaeological features. Here, we present a method to enhance the anomaly of the terrain without using focal operations to normalize the elevation of each pixel in relation to its neighbours. An example is given for two areas covered by LiDAR and containing geoglyphs under the forest cover in the Amazon and with a synthetic LiDAR footprint over a simulated dense forested area containing four geoglyphs with different shapes and height/depth characteristics. The normalization enables to remove the influence of the landscape mean elevation, to highlight the fine anomaly of the terrain. The produced equalized images enable a fast visual assessment of relief anomaly and of the presence of geoglyphs in large LiDAR datasets of hundreds or thousands of LAS files.

摘要

从机载 LiDAR 数据中检测前哥伦比亚时期的地理标志、由沟槽或墙壁勾勒出的几何结构通常是通过目测海拔变化并通常使用额外的山体阴影来进行的。根据激光雷达所覆盖的区域和高程的变化，这种方法可能耗时且不准确，因为它需要不断调整高程图像的对比度或山体阴影函数的参数，用户可能会错过一些重要的考古特征。在这里，我们提出了一种增强地形异常的方法，而不使用焦点操作来标准化每个像素相对于其邻居的高程。举例说明了 LiDAR 覆盖的两个区域并包含亚马逊森林覆盖下的地理标志，以及在模拟的茂密森林区域上的合成 LiDAR 足迹，其中包含四个具有不同形状和高度/深度特征的地理标志。归一化可以消除景观平均高程的影响，突出地形的精细异常。生成的均衡图像可以快速直观地评估地形异常和包含数百或数千个 LAS 文件的大型 LiDAR 数据集中是否存在地理标志。