Abstract
The extraction of the huge amount of information stored in the last generation of VHR satellite imagery, is a big challenge to be addressed. At the current state of the art, the available classification techniques are still inadequate for the analysis and classification of VHR data. This issue is much more critical in the field of archaeological applications being that the subtle signals, which generally characterize the archaeological features, cause a decrease in: (i) overall accuracy, (ii) generalization attitude and (iii) robustness. In this paper, we present the methods used up to now for the classification of VHR data in archaeology. It should be considered that: (i) pattern recognition and classification using satellite data is a quite recent research topic in the field of cultural heritage; (ii) early attempts have been mainly focused on monitoring and documentation much more than detection of unknown features. Finally, we discuss the expected improvements needed to fully exploit the increasing amount of VHR satellite data today available also free of charge as in the case of Google Earth.
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Lasaponara, R., Masini, N. (2012). Pattern Recognition and Classification Using VHR Data for Archaeological Research. In: Lasaponara, R., Masini, N. (eds) Satellite Remote Sensing. Remote Sensing and Digital Image Processing, vol 16. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-8801-7_3
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