Automatic Identification Methods of Linear and Circular Archaeological Structures via Satellite Imagery Processing

International Aerial Archaeology Conference – AARG 2010, Bucharest, Romania, 15 – 18 September 2010

Dorel Micle, Daniela Zaharie, and Oana Borlea

“Very wide spaces, rough terrain or the lack of visual perspective are the most invoked motives because of which wide areas of a country’s territory are not archaeologically investigated, thus creating a multitude of archaeological white spots.

“The usage of satellite images to identify archaeological sites represents a common practice of this scientific community nowadays, and, more and more often, the problem of automatic processing appears, of finding new methods and techniques of automatic identification of archaeological structures through satellite imagery processing.

“Finding the best solutions means to eliminate modern structures and study only the historic ones during the process. Benefitting of an almost total coverage with very good quality satellite images offered by Google Earth of the Timis County (Romania), and also of the richness and variety of noticeable archaeological sites on these images, our team tried to identify some work patterns which are accessible to archaeologists.

“Remote sensing techniques proved to be useful in non-intrusive investigation of archaeological sites by providing information on buried archaeological remains. The presence of different remains in the ground can generate different marks identifiable in high resolution panchromatic and/or multispectral images: crop marks, soil marks, shadow marks and damp marks.

“Automatic identification of archaeological sites from digital images is a difficult task, since the small anomalies induced by the buried remains are usually hidden by stronger marks corresponding to the structures currently existing on the ground (roads, constructions, trees, rocks etc). Therefore the final identification and interpretation of the marks should be made by the expert by visually inspecting the enhanced image and by corroborating his observations with additional information (e.g. historical maps, current roads network etc).

“In order to prepare the image for visual inspection we first applied a flow of basic image processing operations: gray scale conversion, histogram equalization, edge detection (Sobel filter), thresholding, inversion and erosion. Having the aim of developing a semi-automatic tool for identification of linear and circular shapes we also investigated some more sophisticated operations. One of these operations is the Hough transform which we applied in order to identify linear structures (e.g. wave like roman fortifications) and circular structures (e.g. burial mounds).

“The main problem we encountered in identifying the ancient marks is the fact that they are somewhat obscured by the marks of current land division, roads, contemporary buildings etc. In order to deal with this problem we applied both a supplementary pre-processing and a post-processing step. As pre-processing operation we used the singular value decomposition of the image. By ignoring the components corresponding to the highest singular value(s) (which contain the most important features in the image) we obtained an image where the ancient marks are more visible. In the post-processing step we tried to eliminate the lines detected by the Hough transform which correspond to the current land division by using the remark that this lines are mainly parallel while the ancient mark (e.g. a linear fortification) has a different orientation. Using such operations we successfully identified the location of a linear „roman“ fortification.

“The perspectives appear to be promising, so we also want to identify work methods for automatic identification of irregular structures and colors.”