Back to Search Start Over

Hyperspectral PRISMA and Sentinel-2 Preliminary Assessment Comparison in Alba Fucens and Sinuessa Archaeological Sites (Italy)

Authors :
Maria Alicandro
Elena Candigliota
Donatella Dominici
Francesco Immordino
Fabrizio Masin
Nicole Pascucci
Raimondo Quaresima
Sara Zollini
Source :
Land, Vol 11, Iss 11, p 2070 (2022)
Publication Year :
2022
Publisher :
MDPI AG, 2022.

Abstract

Over the last decades, remote sensing techniques have contributed to supporting cultural heritage studies and management, including archaeological sites as well as their territorial context and geographical surroundings. This paper aims to investigate the capabilities and limitations of the new hyperspectral sensor PRISMA (Precursore IperSpettrale della Missione Applicativa) by the Italian Space Agency (ASI), still little applied to archaeological studies. The PRISMA sensor was tested on Italian terrestrial (Alba Fucens, Massa D’Albe, L’Aquila) and marine (Sinuessa, Mondragone, Caserta) archaeological sites. A comparison between PRISMA hyperspectral imagery and the well-known Sentinel-2 Multi-Spectral Instrument (MSI) was performed in order to better understand features and outputs useful to investigate the aforementioned areas. At first, bad bands analysis and noise removal were performed, in order to delete the numerically corrupted bands. Principal component analysis (PCA) was carried out to highlight invisible details in the original image; then, spectral signatures of representative areas were extracted and compared to Sentinel-2 data. At last, a classification analysis (ML and SAM) was performed both on PRISMA and Sentinel-2 imagery. The results showed a full agreement between Sentinel and PRISMA data, enhancing the capability of PRISMA in extrapolating more spectral information and providing a better reliability in the extraction of the features.

Details

Language :
English
ISSN :
2073445X
Volume :
11
Issue :
11
Database :
Directory of Open Access Journals
Journal :
Land
Publication Type :
Academic Journal
Accession number :
edsdoj.47d80730c2d41cc8ab27b3c422f6e1b
Document Type :
article
Full Text :
https://doi.org/10.3390/land11112070