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Proceedings Paper

Study of buried archaeological sites using vegetation indices
Author(s): P. Merola; A. Allegrini; D. Guglietta; S. Sampieri
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Paper Abstract

The identification of buried archaeological structures, using remote sensing technologies is based on the principle that any buried ruins, either of human or natural origin, affects over time, soil surface characteristics creating anomalies. These anomalies are due to different factors, such as soil physical and chemical features, and vegetation cover status. The above factors are strictly connected and are responsible of surface spectral responses. Several images processing are applied and their results compared in order to define the one that fits better the various archaeological research goals. Among them, Vegetation Indices revealed to be very useful archaeological study. Spectral Vegetation Indices are important products in observing spatial and temporal variations of vegetation biophysical properties and photosynthetic activities, by which is possible to analyse the effects of buried ruins presence on vegetation cover status. The aim of this work is to assess the usefulness of vegetation indices in order to identify archaeological traces and verify the quantitative estimates of presence of buried archaeological structures in every type of elaboration (RVI, VIN, NDVI and SAVI). Statistical analysis were conducted on several Italian archaeological test sites processing by hyperspectral MIVIS (Multispectral Infrared and Visible Imaging Spectrometer) various typologies of vegetation cover. The study of these anomalies on MIVIS hyperspectral data is the main goal of a research project that the CNR-IIA has carried ahead since 1994 over some archaeological sites: Selinunte, Lilybaeum, Sipontum and Arpi. The Arpi area could be considered as the wider Pre-roman settlement in Italy.

Paper Details

Date Published: 20 October 2006
PDF: 12 pages
Proc. SPIE 6366, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology VI, 636609 (20 October 2006); doi: 10.1117/12.689727
Show Author Affiliations
P. Merola, National Research Council Institute for Atmospheric Pollution (Italy)
A. Allegrini, National Research Council Institute for Atmospheric Pollution (Italy)
D. Guglietta, National Research Council Institute for Atmospheric Pollution (Italy)
S. Sampieri, National Research Council Institute for Atmospheric Pollution (Italy)


Published in SPIE Proceedings Vol. 6366:
Remote Sensing for Environmental Monitoring, GIS Applications, and Geology VI
Manfred Ehlers; Ulrich Michel, Editor(s)

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