On the Airborne Lidar Contribution in Archaeology: from Site Identification to Landscape Investigation

Abstract

Historically, aerial photography has been the first remote sensing technology extensively used for surveying surface archaeological remains as well as for detecting underground archaeological structures through the reconnaissance of the so-called "soil" and "crop marks" (Crawford, 1929). Soil-marks are changes of colour or texture due to the presence of surface and shallow remains. Crop-marks frequently appear as differences of height or colour in crops which are under stress due to lack of water or deficiencies in other nutrients caused by the presence of masonry structures in the subsoil. Crop-marks can also be formed above damp and nutritious soil of buried pits and ditches. Such marks are well visible from aerial photos, especially during the spring season. Nowadays two new technologies have strongly improved the performance of remote sensing in archaeology: (i) the Very High Resolution (VHR) satellite images and (ii) the airborne laser scanning. The launch in 1999 of IKONOS, the first satellite sensor which acquires VHR imagery, opened new perspectives in the field of archaeo-geophysics. The main advantages of VHR satellite imagery compared to aerial photos, are the synoptic view, the multispectral properties of the data and the possibility to extract geo-referenced information. The use of data processing algorithms, from classifications methods to geo-statistics, from Principal Component Analysis to convolution filtering, enable us i) the extraction of land patterns useful for palaeo-geographic and palaeo-environmental investigations (Masini & Lasaponara, 2006); ii) the discrimination of surface archaeological remains from the surroundings (De Laet et al., 2007). From 1999 up to now, the spatial resolution of satellite data has strongly increased, thus providing also valuable support to site discovery by means of soil/crop marks detection. The multispectral bands, available at a resolution four times lower than panchromatic channel, could be pan-sharpened by using image fusion algorithms available in several image processing software routines, thus allowing us to emphasize moisture and vegetation changes linked to the presence of buried archaeological deposits (Lasaponara & Masini, 2007).