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

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.

Potential Impact of Using ChatGPT-3.5 in the Theoretical and Practical Multi-Level Approach to Open-Source Remote Sensing Archaeology, Preliminary Considerations

“…The aim here is to assess the impact ChatGPT-3.5 can have on research in the field of archaeology and RS. The data used for this study were data from the ESA Sentinel-2 (S2) L2A satellites, now considered the best in terms of spatial, spectral, and temporal resolution among the free data for RS archaeology contained in GEE [147,148]. The dataset used in all analyses is the 'COPERNICUS/S2_SR_HARMONIZED' dataset, which covers a time span from March 2017 to the present (Table 2).…”

Coastline Automatic Extraction from Medium-Resolution Satellite Images Using Principal Component Analysis (PCA)-Based Approach

“…Satellite images are widely used for environmental monitoring since they permit access to remote locations and hazardous regions without difficulty [1]. There are several possible fields of application, including forestry [2], greenhouses [3], soil moisture [4], glaciers [5], archaeology [6], cultural heritage [7], landslides [8], subsidence phenomena [9], floods [10], effects of volcanic eruptions [11], etc. Moreover, there are also applications concerning the coastal and marine environment, such as the determination of the bathymetry [12], the identification of chlorophyll quantity [13] and the monitoring of erosion and nourishment phenomena [14], for which the identification of the coastline is necessary.…”