Frontiers in ICT | |
Algorithmic Identification of Looted Archaeological Sites from Space | |
Parcak, Sarah1  Granger, Richard2  Bowen, Elijah F. W.2  Tofel, Brett B.2  | |
[1] Department of Anthropology, University of Alabama at Birmingham, USA;Department of Psychological and Brain Sciences, Dartmouth College, USA | |
关键词: Machine Vision; Archaeology; heritage; Looting; Automation; computational analysis; high resolution; Egypt; | |
DOI : 10.3389/fict.2017.00004 | |
学科分类:计算机网络和通讯 | |
来源: Frontiers | |
【 摘 要 】
In response to widespread looting of archaeological sites, archaeologists have used satellite imagery to enable the investigation of looting of affected archaeological sites. Such analyses often require time-consuming direct human interpretation of images, with the potential for human-induced error. We introduce a novel automated image processing mechanism applied to the analysis of very high resolution panchromatic satellite images, and demonstrate its ability to identify damage at archaeological sites with high accuracy and low false-positive rates compared to standard image classification methods. This has great potential for large scale applications whereby country-wide satellite datasets can be batch processed to find looting hotspots. Time is running out for many archaeological sites in the Middle East and elsewhere, and this mechanism fills a needed gap for locating looting damage in a cost and time efficient manner, with potential global applications.
【 授权许可】
CC BY
【 预 览 】
Files | Size | Format | View |
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RO201904026745566ZK.pdf | 3150KB | download |