Light Detection and Ranging (LiDAR) sensors might be most famous for their applications in self-driving vehicles1 but LiDAR technology has a number of other uses for research and exploratory work in fields such as archaeology.
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LiDAR works by combining a light source and sensor to measure the time taken between an emitted and reflected light pulse. The light sources used for LiDAR set-ups are typically pulsed lasers. The types of detectors used range from photodiodes that can offer excellent sensitivity, robustness and compactness to CMOS or CCD array detectors that have imaging capabilities.
For field work in archeology, the choice of laser system for LiDAR is very important as it determines which objects and materials are ‘transparent’ to the incident LiDAR beam.
Some of the key applications of LiDAR in archeology include providing topographical surveys of land and bathymetric LiDAR to map riverbeds and underwater structures.2 Through choosing the right wavelength for the LiDAR measurements, it is possible for the LiDAR to ‘see’ through dense regions of overgrowth to find structures that are hidden underneath.
Hidden Treasures
Written historical records suggested that precious metal mining had been common in Ancient Greece, but many of the locations of the mines had remained unknown.3 The use of analytical techniques for rock analysis has helped researchers and archeologists locate regions likely to be the sites of mines.
However, using analytical methods to look at soil composition requires samples to be taken and analyzed, potentially back in a laboratory setting. With aerial LiDAR now, it is possible for an unmanned aerial vehicle (UAV) to scan a region, even with dense overgrowth, for prospecting or identification of the geological features that may be associated with archeological mine sites.4
Some of the advantages of combining LiDAR with UAVs are that LiDAR can achieve very high spatial resolutions that make it possible to identify both small and large-scale archaeological events and UAVs make it feasible to scan regions that would normally be too remote or otherwise inaccessible.
The aerial images that can be captured with LiDAR technologies go beyond simple satellite photographs of a region, allowing for full 3D reconstructions with high levels of detail owing to LiDAR's good spatial resolution.4
While improved energy efficiency and battery storage mean UAVs can cover greater areas than ever before, archaeological discovery with LiDAR faces a relatively unique challenge in terms of image interpretation.
Archeological sites are normally in states of poor repair and the amount of degradation and its nature can be highly unpredictable. Manual analysis is very time-consuming, but it can be challenging to automate due to the breadth of the scope of possible features associated with a site or object.5
There are now efforts to describe buildings and mounds found in archeological sites as a series of ‘shaped’ objects that can be extracted from the digital elevation models captured by LiDAR.5 Although there was a relatively high percentage (~ 20 %) of missed sites using an image recognition algorithm, the automated analysis did still show an efficiency advantage over manual analysis with a good scope for future improvements to the algorithm.
Precision Scanning
Improving the precision of LiDAR scanning can be achieved in a number of ways. One is to improve the resolution of the sensor used in the LiDAR device or even to incorporate multiple sensors. Another method is to change the way the scanning is performed through the incorporation of multiple scanning angles or processing algorithms to improve the discrimination between real signals and background.6
The ‘point cloud’ – the network of spatial information recorded by the LiDAR sensor, which provides the Z information, and GPS, which provides the XY information – is passed through a reconstruction algorithm to generate the visualization of the object or area.
Resolutions better than 1 m are now routinely achievable with LiDAR sensor technologies. However, the accuracy of the point cloud maps and information reconstructed from the LiDAR depends heavily on the quality of the algorithms that are used to optimize and extract the visualized information from the data.7
During manual analysis of LiDAR data, expert analysts will use many ‘tricks’ such as removing particular features or changing shading to help them spot features or aberrations that might indicate a region of interest. One example of this is ‘bonemapping’, where the morphological LiDAR data has an additional processing step to apply a shaded slope map.7
At the El Pilar site between Belize and Guatemala, the bonemapping process helped reveal a number of subtle details on the forest floor and helped find a number of new features in the Mayan site there, including a sunken plaza and ball court.7
While most archeological analysis algorithms do contain some automated classification of object types, such as vegetation or possible buildings, full automation of the analysis and image recognition is still somewhat problematic and so many techniques like bonemapping are still analyzed manually.
Over the last decade, LiDAR has been a key tool for archeologists looking to discover and explore new sites, particularly in remote locations, and to provide geographical profiling information.
References and Further Reading
Shreyas, V., Bharadwaj, S. N., Srinidhi, S., Ankith, K. U., & Rajendra, A. B. (2020). Self-driving cars: An overview of various autonomous driving systems. Advances in Data and Information Sciences: Proceedings of ICDIS 2019, 361-371. https://doi.org/10.1007/978-981-15-0694-9_34
Schindling, J., & Gibbes, C. (2014). LiDAR as a tool for archaeological research : a case study. Archeol Anthropol Sci, 6, 411–423. https://doi.org/10.1007/s12520-014-0178-3
Gerwin, R. (1984). Recent archaeological discoveries by research workers from the Max Planck Society: gold and silver mines in ancient Greece. Universitas, 26(1), 223. https://www.proquest.com/docview/1311290635
Fernández-lozano, J., & Gutiérrez-alonso, G. (2016). Improving archaeological prospection using localized UAVs assisted photogrammetry : An example from the Roman Gold District of the Eria River Valley ( NW Spain ). Journal of Archaeological Science: Reports, 5, 509–520. https://doi.org/10.1016/j.jasrep.2016.01.007
Albrecht, C. M., Fisher, C., Freitag, M., Hamann, H. F., Pezzutti, F., & Rossi, F. (2019). Learning and Recognizing Archeological Features from LiDAR Data. 2019 IEEE International Conference on Big Data (Big Data), 5630–5636.
Nguyen, T., Cheng, C., Liu, D., & Le, M. (2022). Improvement of Accuracy and Precision of the LiDAR System Working in High Background Light Conditions. Electronics, 11, 45. https://doi.org/https://doi.org/10.3390/electronics11010045
Pingel, T. J., Clarke, K., Ford, A., Pingel, T. J., Clarke, K., & Bonemapping, A. F. (2015). Bonemapping : a LiDAR processing and visualization technique in support of archaeology under the canopy. Cartography and Geographic Information Science, 42(1), 18–26. https://doi.org/10.1080/15230406.2015.1059171
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