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Space lidar for archaeology? Reanalyzing GEDI data for detection of ancient Maya buildings

•GEDI is a lidar instrument mounted on the International Space Station.•We examined the use of its data for archaeological feature recognition.•Low density makes the dataset as yet unsuitable for the intended application. Airborne laser scanning (ALS) greatly accelerated and expanded traditional arc...

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Bibliographic Details
Published in:Journal of archaeological science, reports reports, 2021-04, Vol.36, p.102811, Article 102811
Main Authors: Kokalj, Žiga, Mast, Johannes
Format: Article
Language:English
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Summary:•GEDI is a lidar instrument mounted on the International Space Station.•We examined the use of its data for archaeological feature recognition.•Low density makes the dataset as yet unsuitable for the intended application. Airborne laser scanning (ALS) greatly accelerated and expanded traditional archaeological landscape surveys in the forested regions of the ancient Maya. Private and public funding enabled landscape visualizations ranging from site-scale to almost regional investigations. However large-scale, the airborne scanning missions are limited in the area they can cover. This is why in this paper we analyze the potential of a free, globally available lidar dataset for archaeological exploration in a forested environment. The Global Ecosystem Dynamics Investigation (GEDI) is a full waveform lidar instrument mounted on the International Space Station. The study area is Chactún, one of the largest Maya urban centers in the central lowlands of the Yucatan peninsula. Compared to airborne laser systems, the scanning density of GEDI is low; therefore, we examined whether the density and scanning pattern enable direct observation of buildings from a derived elevation model, and whether the presence of buildings can be assumed from the statistics of the canopy structure. Our research shows that the lack of coverage and low density of GEDI points makes the dataset as yet unsuitable for the intended application of archaeological feature recognition. The presence of buildings in our study area can neither be directly observed nor assumed based on biophysical parameters.
ISSN:2352-409X
DOI:10.1016/j.jasrep.2021.102811