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Excavation

  • Bostel di Rotzo
  • Bostel di Rotzo
  •  
  • Italy
  • Veneto
  • Province of Vicenza
  • Rotzo

Tools

Credits

  • The Italian Database is the result of a collaboration between:

    MIBAC (Ministero per i Beni e le Attività Culturali - Direzione Generale per i Beni Archeologici),

    ICCD (Istituto Centrale per il Catalogo e la Documentazione) and

    AIAC (Associazione Internazionale di Archeologia Classica).

  • AIAC_logo logo

Summary (English)

  • The research in 2013 in the territory of the Comune of Rotzo was limite to air photographic and ground survey, with
    1) experimentation of the innovative procedures of Image Enhancing and Object, Pattern, and Scenery Recognition.
    2) ground truthing of the anomalies.
    In particular, the data from the following sensors were analyzed with appropriate algorithms.
    • LIDAR: Provincia Autonoma di Trento
    • RADAR: image-intensity from Intermap Technologies Ltd. of Alberta-Canada (Learjet 36: radar with synthetic aperture (STAR).
    • Aereophotographic time series: 1918, 1943, 1986, Orthophoto 2000, 2006, 2008; Close Infrared 2008

    • Cartographic time series: the Austrian cadastral survey of 1850-60 (1:2800); IGM 25.000 (series pre- and post- the First World War); 1918 Map at a scale of 1: 20.000 of the French Army; CTN at 1:10.000 (Provincia Autonoma di Trento- Cadastral Urbanistic and Landscape Services; and the Biblioteca Bertoliana-Vicenza; Regione Veneto – Unita` di Progetto Sistema Informativo Territoriale e Cartografia).
    • -eCognition and OBIA. Survey procedures. The software eCognition (Definiens 2009), among the approaches to the so-called OBIA (Object-Based Image Analysis) introduces a working method derived from artificial intelligence and artificial vision, while Object/Pattern/Scenery Recognition, extracts information from images in a (semi) automatic fashion, using a hierarchical classification of images that contrasts methods based on pixels.

    Among the results of the remote sensing should be highlighted the comparative analysis of the results produced by the NIR, near Infrared images (in particular the index of slope based vegetation growth). The LIDAR images produced information about slope, hillshade, skyview factor, principal components analysis, smooth/difference, pit-detection and more), RADAR (various filters, including an adaptive filter.) and from the algorythms of eCognition (aimed, for example, at the discovery of subcircular, linear and square objects).

    The meta-results emerging from these initial photo-interpretations concern first of all the high level of ‘spatial redundance (the indentification of the same objects using the NIR, and LIDAR, with a high level of intesection in terms of space and group) confirmed in large part by eCognition. Considering that these are techniques totally independent of the target, all together they produce a comforting confirmation of the finds. This is gratifying, but also to some extent expected, given the past work on the surface of the mountain. ( see De Guio Frizzo 2010; De Guio 2012; De Guio et Alii 2013).
    The most surprising and exciting results come, in particular, from the case study of Millegrobe (Vezzena). This comes from the processing of the interpherometric Radar, which, with a sequence of dedicated filters, has revealed whole new classes of objects of an extraordinary clarity. These relate to various archeological, ethnographic (paleo) environmental and wartime landscapes. Above all there is a remarkable network of coherent, frame-based linear features.

    Analogous results can be also be seen in the case study of Rotzo, still underway, where a preliminary analysis of the image-intensity of Intermap is showing very high resolution, particularly in the discovery of linear infrastructural features (particularly terracing and connective structures of pre- and protohistoric periods). This also sheds light on the site of Bosel, as well as its suburbs.

  • Armando De Guio - Università degli Studi di Padova - Dipartimento dei Beni Culturali 

Director

Team

  • Gessica Ferrari
  • Carlo Bressan - Museo Archeologico dell’Altopiano dei Sette Comuni Vicentini
  • Chiara Padovan
  • Riccardo Mantoan

Research Body

  • CISAS (Centro Internazionale di Studi di Archeologia di Superficie – Dip. Archeologia, Università di Padova)
  • Museo Archeologico dell’Altopiano dei Sette Comuni Vicentini
  • Università degli Studi di Padova, Dipartimento di Archeologia

Funding Body

Images

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