ABSTRACT The study of precontact anthropogenic mounded features—earthen mounds, shell heaps, and shell rings—in the American Southeast is stymied by the spotty distribution of systematic surveys across the region. Many extant, yet unidentified, archaeological mound features continue to evade detection due to the heavily forested canopies that occupy large areas of the region, making pedestrian surveys difficult and preventing aerial observation. Object-based image analysis (OBIA) is a tool for analyzing light and radar (lidar) data and offers an inexpensive opportunity to address this challenge. Using publicly available lidar data from Beaufort County, South Carolina, and an OBIA approach that incorporates morphometric classification and statistical template matching, we systematically identify over 160 previously undetected mound features. This result improves our overall knowledge of settlement patterns by providing systematic knowledge about past landscapes.

中文翻译：

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在南卡罗来纳州博福特县使用激光雷达和基于对象的图像分析自动检测土丘

摘要 对美国东南部接触前人为丘陵特征（土丘、贝壳堆和贝壳环）的研究受到该地区系统调查分布不均的阻碍。由于该地区的大片森林覆盖着茂密的树冠，许多现存但身份不明的考古土墩特征继续躲避检测，这使得行人调查变得困难并阻碍了空中观察。基于对象的图像分析 (OBIA) 是一种用于分析光和雷达（激光雷达）数据的工具，为应对这一挑战提供了廉价的机会。使用来自南卡罗来纳州博福特县的公开激光雷达数据，以及结合了形态测量分类和统计模板匹配的 OBIA 方法，我们系统地识别了 160 多个以前未检测到的土丘特征。