Using LiDAR and GEOBIA for automated extraction of eighteenth–late nineteenth century relict charcoal hearths in southern New England
Using LiDAR and GEOBIA for automated extraction of eighteenth–late nineteenth century relict charcoal hearths in southern New England
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DOI：
10.1080/15481603.2018.1431356
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发表时间：
2018-02
影响因子：
6.7
通讯作者：
C. Witharana;W. Ouimet;Katharine M. Johnson
中科院分区：
文献类型：
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作者：
C. Witharana;W. Ouimet;Katharine M. Johnson
越来越多的可用性和航空光探测和测距（LiDAR）数据的进步已经从根本上改变了考古调查的方式。与光学遥感图像不同，激光雷达脉冲穿过茂密树冠中的小缝隙，使考古学家能够发现“隐藏”的过去定居点和人为景观特征。虽然激光雷达在世界范围内的考古研究中被越来越多地采用，但它的全部潜力仍在美国被探索。此外，虽然遥感数据集的手工数字化特征仍然是考古调查的一种有价值的方法，但它往往是时间和劳动密集型的。本研究的中心目标是开发一个基于地理对象的图像分析驱动的方法框架，将低级特征和领域知识连接起来，从基于激光雷达的数字地形模型（dtm）中自动提取感兴趣的目标，并仔细检查基于知识的规则集在不同研究地点之间的互操作性程度，这些规则集集中在相同的语义类上。我们将这一框架应用于新英格兰南部，这是美国东北部的一个地理区域，那里有许多17世纪到20世纪早期的特征，如废弃的木炭炉（RCHs）、石墙和建筑地基，这些特征被遗弃在茂密的森林地形中。在本研究中，我们的研究结果表明，人工和自动检测这些特征之间有很大的一致性。总的来说，我们表明使用激光雷达数据与基于对象的分类工作流程相结合，为未来的考古研究和过去300年土地利用/土地覆盖变化的重建提供了有价值的基线数据。
Increasing availability and advancements of aerial Light Detection and Ranging (LiDAR) data have radically been shifting the way archeological surveys are performed. Unlike optical remote sensing imagery, LiDAR pulses travel through small gaps in dense tree canopies enabling archeologists to discover “hidden” past settlements and anthropogenic landscape features. While LiDAR has been increasingly adopted in archeological studies worldwide, its full potential is still being explored in the United States. Furthermore, while hand-digitizing features in remote-sensing datasets remain a valuable method for archeological surveys, it is often time- and labor intensive. The central objective of this research is to develop a geographic object-based image analysis-driven methodological framework linking low-level features and domain knowledge to automatically extract targets of interest from LiDAR-based digital terrain models (DTMs) and to closely examine the degree of interoperability of knowledge-based rulesets across different study sites focusing on the same semantic class. We apply this framework in southern New England, a geographic region in the northeastern United States where numerous seventeenth-century to early twentieth-century features such as relict charcoal hearths (RCHs), stone walls, and building foundations lie abandoned in densely forested terrain. Focusing on RCHs in this study, our results show promising agreement between manual and automated detection of these features. Overall, we show that the use of LiDAR data augmented with object-based classification workflows provides valuable baseline data for future archeological study and reconstruction of land-use/land-cover change over the past 300 years.