期刊
ARCHAEOLOGICAL PROSPECTION
卷 19, 期 2, 页码 103-121出版社
WILEY
DOI: 10.1002/arp.1421
关键词
Pattern recognition; charcoal burning pits; pitfall traps; digital elevation model; lidar; point density
资金
- Norwegian Directorate for Cultural Heritage
This paper describes a new method for the automatic detection of pit structures in airborne laser scanning data collected with at least five emitted pulses per square metre. Oppland County, Norway, has a large number of ancient iron production sites and hunting systems. Today, these are manifested as pits in the ground. The iron production sites were used 1400-700?yr ago, and consist of charcoal burning pits, often located in groups of four around a central oven, which also occasionally can be located as a small mound. The hunting systems were used 2000-500?yr ago, and consisted of concealed pitfall traps and wooden fences, located on deer trekking routes. The fences are gone, but the pits remain. Many of the iron production sites and hunting systems are located in forested areas. The current, traditional mapping of these is relatively poor, with many individual pits missing, and poor positional accuracy of the ones that are mapped. This means that overlays of cultural heritage sites cannot be trusted when planning new highways, residential areas, cabins, etc. Experience suggests that automatic detection is clearly superior to visual inspection of the lidar data in finding small pits or pits that are not easily visible. However, visual inspection is better at finding additional information as human interpretation based on archaeological knowledge can be applied. Combining these two methods secures a very good basis for subsequent field survey. In conclusion, we demonstrate that automatic detection of hunting systems and iron extraction sites in lidar data is a valuable tool in combination with visual inspection of the lidar data, prior to field survey. Provided that the point density of the lidar data is high enough, the field survey can be accomplished ten times faster compared with the traditional approach without lidar data. Copyright (C) 2012 John Wiley & Sons, Ltd.
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