Abstract
The documentation and protection of archaeological and cultural heritage (ACH) using remote sensing, a non-destructive tool, is increasingly popular for experts around the world, as it allows rapid searching and mapping at multiple scales, rapid analysis of multi-source data sets, and dynamic monitoring of ACH sites and their environments. The exploitation of remote sensing data and their products have seen an increased use in recent years in the fields of archaeological science and cultural heritage. Different spatial and spectral analysis datasets have been applied to distinguish archaeological remains and detect changes in the landscape over time, and, in the last decade, archaeologists have adopted more thoroughly automated object detection approaches for potential sites. These approaches included, among others, object detection methods, such as those of machine learning (ML) and deep learning (DL) algorithms, as well as convolutional neural networks (CNN) and deep learning (DL) models using aerial and satellite images, airborne and spaceborne remote sensing (ASRS), multispectral, hyperspectral images, and active methods (synthetic aperture radar (SAR) and light detection and ranging radar (LiDAR)). Researchers also refer to the potential for archaeologists to explore such artificial intelligence (AI) approaches in various ways, such as identifying archaeological features and classifying them. Here, we present a review study related to the contributions of remote sensing (RS) and artificial intelligence in archaeology. However, a main question remains open in the field of research: the rate of positive contribution of remote sensing and artificial intelligence techniques in archaeological research. The scope of this study is to summarize the state of the art related to AI and RS for archaeological research and provide some further insights into the existing literature.
Subject
General Earth and Planetary Sciences
Reference112 articles.
1. A brave new world for archaeological survey: Automated machine learning-based potsherd detection using high-resolution drone imagery;Orengo;J. Archaeol. Sci.,2019
2. Renfrew, C., and Bahn, P. (1991). Archaeology, Theories, Methods and Practice, Thames and Hudson Ltd.
3. Alcock, S.E., and Cherry, J.F. (2004). Side-By-Side Survey. Comparative Regional Studies in the Mediterranean World, Oxbow Books.
4. Methods for the extraction of archaeological features from very high-resolution Ikonos-2 remote sensing imagery, Hisar (southwest Turkey);De Laet;J. Archaeol. Sci.,2007
5. Barone, P.M., Wueste, E., and Hodges, R. (2020). Remote Sensing Materials for a Preliminary Archaeological Evaluation of the Giove Countryside (Terni, Italy). Remote Sens., 12.
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