On the Processing of Aerial LiDAR Data for Supporting Enhancement, Interpretation and Mapping of Archaeological Features

Airborne Laser Scanning (ALS) technology, also referred to as LiDAR (Light Detection and Ranging), represents the most relevant advancement of Earth Observation (EO) techniques for obtaining highprecision information about the Earth's surface. This includes basic terrain mapping (Digital terrain model, bathymetry, corridor mapping), vegetation cover (forest assessment and inventory), coastal and urban areas, etc. Recent studies examined the possibility of using ALS in archaeological investigations to identify earthworks, although the ability of ALS measurements in this context has not yet been studied in detail. It is widely recognized that there are numerous open issues that must be addressed. The most important of these limitations are: (i) data processing, (ii) interpretation and (iii) reliable mapping of archaeological features. In particular, there is a pressing need to generate very detailed maps of subtle archaeological remains as required for planning field survey, excavations etc. Up to now, the visualisation has been approached using hill-shaded LiDAR DTMs, namely different DTMs are produced by different illuminations from arbitrary azimuths and elevations using GIS hill-shading techniques. But numerous limitations characterize this approach, mainly linked to the following aspects: (i) the use of numerous hill-shaded LiDAR DTMs is time consuming, (ii) the same features may be replicated from several angles, (iii) the interpretation is strongly subjective (depending on the interpreter), and (iv) this implies the impossibility to have reliable maps. In this paper, these critical issues have been addressed using: 1) slope and convexity algorithms; 2) Principal Component Analysis (PCA) of hill-shaded LiDAR DTMs. The investigations were carried out near Monte Irsi, a significant archaeological area in the Basilicata Region (Southern Italy) characterized by complex topographical and morphological features.

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