Satellite Remote Sensing Analysis of the Qasrawet Archaeological Site in North Sinai

Abstract

North Sinai is of significant historical interest primarily because of its role since late prehistoric times as a land bridge between Egypt and the Levant. Access to this region is challenging due to its harsh geography and security concerns. Remote sensing constitutes a convenient method for archaeological prospection and monitoring over such regions with its low cost (relative to ground based sensing techniques), global coverage, and high temporal and spatial sampling. This paper describes part of a study to revisit a number of sites investigated during the North Sinai Survey (1972-1982) with very high resolution optical and Synthetic Aperture Radar satellite imagery. These were acquired throughout the summer of 2017 in the framework of a European Space Agency research project. The Synthetic Aperture Radar data includes Spotlight and Staring Spotlight modes of the TerraSAR-X mission, while the optical imagery was acquired by the Pleiades mission. The TerraSAR-X data were processed to derive filtered amplitude and consecutive coherence time series. The results of the TerraSAR-X data processing, and the pan-sharpened Pleiades data were compared with the results of the North Sinai Survey to detect possible additional buried structures in the radar data, or newly excavated sites in the optical data. While the analysis is still ongoing, results are reported here of the Qasrawet archaeological site, which was partially investigated by the North Sinai Survey expedition, but assumed to cover a much larger area. Herein, a number of newly excavated structures are apparent in the remote sensing data. The similarity of features in both the TerraSAR-X and Pleiades data suggest that all structures are surface residues, and therefore, that the subsurface mapping capabilities of the TerraSAR-X data in this area are limited. The utility of both data types for archaeological site monitoring are discussed.

Tests with SAR Images of the PAZ Platform Applied to the Archaeological Site of Clunia (Burgos, Spain)

“…According to Stewart et al [30], remote sensing with SAR has only been fully successful in areas covered by sand. On the other hand, Dore et al [43] maintained that the characteristics of these types of SAR sensors (independent of the external light source, penetration areas cloud cover, or soil penetration) have extended the limits of acquisitions from optical satellites, and the combined use of both types of sensors in archaeological remote sensing research was advisable.…”

“…However, the use of SAR has had results of interest in non-arid and vegetated areas, as is the case in Lazio [29,30] with the detection of archaeological forms, combining results of SAR intensity and interferometry. In both cases, the probability of locating archaeological structures has increased.…”

“…It is from this point that it is possible to perform statistical averaging operations that facilitate the generation of a final image that is more precise and sharp as compared to that obtained from a single SAR image. This method has also been applied by Stewart [29], focusing on various areas of Lazio (Italy) with COSMO-SkyMed images, and by the same author (Stewart) [30] at the archaeological site of Qasrawet (North Sinai) using TerraSAR-X images this time. We have, therefore, followed the aforementioned procedure to generate an image from a stack of six images obtained in 2019 and 2020 in the periods from July to October.…”

Identifying Linear Traces of the Han Dynasty Great Wall in Dunhuang Using Gaofen-1 Satellite Remote Sensing Imagery and the Hough Transform

“…Remote sensing (RS) provides a rapid and low-cost way of exploring, mapping and monitoring archaeological features of interest (AOIs) across the world [29]. Research that involves the identification of AOIs increasingly employs aerial photographs and spy satellite images [30][31][32][33] as well as multispectral and hyperspectral imagery [34][35][36][37][38], SAR data [39][40][41][42], and LiDAR products [43][44][45]. RS has unique advantages for detecting the large archaeological sites such as the Silk Road, Grand Canal, Nasca Lines and Great Wall [4].…”

Working with Gaussian Random Noise for Multi-Sensor Archaeological Prospection: Fusion of Ground Penetrating Radar Depth Slices and Ground Spectral Signatures from 0.00 m to 0.60 m below Ground Surface

“…The detection of sub-surface buried targets remains a challenge for different disciplines such as archaeological prospection [1][2][3]; forensic archaeology [4][5][6]; urban planning (e.g., pipe detection) [7][8][9]; military and security purposes (e.g., land-mines) [10,11].…”