Potential of Multitemporal Lidar for the Detection of Subtle Archaeological Features under Perennial Dense Forest
2022
Iban Berganzo-Besga | Hector A. Orengo | Joan Canela | Maria Carme Belarte
This paper presents a method for the merging of lidar-derived point clouds of the same area taken at different moments, even when these are not co-registered. The workflow also incorporates the filtering of vegetation allowing the classification of unclassified point clouds using the ground points of reliable coverages. The objective is to produce a digital terrain model by joining all ground points to generate a higher resolution model than would have been possible using a single coverage. The workflow is supplemented by a multi-scale relief visualisation tool that allows for better detection of archaeological micro-reliefs of variable size even in areas of complex topography. The workflow is tested in six Iberian Iron Age sites, all of them located in mountain areas with dense Mediterranean perennial forests and shrub vegetation.
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