Archaeology and Object-Based Image Analysis: potential and issues for the application of semantic models
Abstract
In recent years, the field of remote sensing experienced an incredible growth thanks to the increasing quality and variety of sensors and the reduction of instrumental costs. The benefits for archaeology were soon apparent. So far, data interpretation remains essentially a prerogative of the human operator and is mediated by his skills and experiences. However, the continuous increase of datasets volume and the increasing necessity to work on large scale projects require an overall revision of the methods traditionally used in the archaeological field. With the progressive diffusion of OBIA in archeology during the last few years, it is now essential to find a shared language and a common protocol of investigation (ideally passing from operational practice to operational routine), necessary to allow the comparability of data. This presentation will offer a general review on the topic considering both the results published in the literature and new case studies developed by the author and his research group, which will be used to illustrate the possibilities of the method in archeology. The case studies will comprise object-based procedures for the treatment of aerial/ satellite imaging, such as VHR multispectral data, and digital elevation models acquired by airborne and terrestrial laser scanning. These data will serve as a starting point to discuss the limits and the potential of OBIA in the archaeological field, with specific reference to the prospects for the future in light of the recent developments in other disciplines such as environmental and biomedical sciences. The objective is therefore to examine a series of crucial methodological issues linked to the residuality of the archaeological remains, also through the exemplification of practical results. In fact, the archaeological remains are always affected by post-depositional processes which have progressively altered, with different degrees of impact, their original characteristics, leading to a high variability within the same category of evidences. Diachronic semantic models were thus developed to fine-tune the classification tree and obtain a better accuracy of the results. For the same purpose, a systematic integration of OBIA and targeted ground surveys seems to be the best option of a cross-validation of the results, in order to achieve an appropriate balance between processing speed and reliability of data.