Remote sensing applications and archaeological research in the Northern Lagoon of Venice: the case of the lost settlement of Constanciacus

Traviglia, Arianna; Cottica, Daniela

doi:10.1016/j.jas.2010.10.024

Cited by 41 publications

(22 citation statements)

References 2 publications

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“…Indeed, in most cases the different processed and geocoded remote sensing data were inserted in a Geographical Information System (GIS), followed by simple superimposition of the diverse ortho-rectified datasets for visual and/or semi-automatic multilayer analysis (e.g., [8,9,19,20]). Some studies have also presented interesting results on data integration and fusion by employing quantitative means for multiple data sources [21][22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

Fusion of Satellite Multispectral Images Based on Ground-Penetrating Radar (GPR) Data for the Investigation of Buried Concealed Archaeological Remains

et al. 2017

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Abstract:The paper investigates the superficial layers of an archaeological landscape based on the integration of various remote sensing techniques. It is well known in the literature that shallow depths may be rich in archeological remains, which generate different signal responses depending on the applied technique. In this study three main technologies are examined, namely ground-penetrating radar (GPR), ground spectroscopy, and multispectral satellite imagery. The study aims to propose a methodology to enhance optical remote sensing satellite images, intended for archaeological research, based on the integration of ground based and satellite datasets. For this task, a regression model between the ground spectroradiometer and GPR is established which is then projected to a high resolution sub-meter optical image. The overall methodology consists of nine steps. Beyond the acquirement of the in-situ measurements and their calibration (Steps 1-3), various regression models are examined for more than 70 different vegetation indices (Steps 4-5). The specific data analysis indicated that the red-edge position (REP) hyperspectral index was the most appropriate for developing a local fusion model between ground spectroscopy data and GPR datasets (Step 6), providing comparable results with the in situ GPR measurements (Step 7). Other vegetation indices, such as the normalized difference vegetation index (NDVI), have also been examined, providing significant correlation between the two datasets (R = 0.50). The model is then projected to a high-resolution image over the area of interest (Step 8). The proposed methodology was evaluated with a series of field data collected from the Vésztő-Mágor Tell in the eastern part of Hungary. The results were compared with in situ magnetic gradiometry measurements, indicating common interpretation results. The results were also compatible with the preliminary archaeological investigations of the area (Step 9). The overall outcomes document that fusion models between various types of remote sensing datasets frequently used to support archaeological research can further expand the current capabilities and applications for the detection of buried archaeological remains.

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Section: Introductionmentioning

confidence: 99%

Fusion of Satellite Multispectral Images Based on Ground-Penetrating Radar (GPR) Data for the Investigation of Buried Concealed Archaeological Remains

et al. 2017

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“…Results from the analysis of satellite images allowed the identification of shallow and outcropping adobe walls, the gradiometric maps enabled the identification of tombs and ceremonial offerings, finally radargrams allowed the discovery of a rich ceremonial offering made up mainly of ceramics, textiles, and painted pumpkins. Traviglia and Cottica (2011) show the results from investigations addressed to shed new light on early patterns of occupation in the Northern Venetian Lagoon. The authors explore the communication network between the mainland and the sea and examine the evolution of settlements along the commercial routes of the Lagoon through time.…”

Section: The Special Issue Of the Journal Of Archaeological Sciencementioning

confidence: 99%

Satellite remote sensing in archaeology: past, present and future perspectives

Lasaponara

Masini

2011

Journal of Archaeological Science

119

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“…High spatial resolution and hyperspectral optical images acquired by multiple sensors onboard aerial aircrafts [1], satellites [2] and unmanned aerial vehicles (UAVs) [3] have been widely applied to detect crop and soil marks of ancient sites and remnants above or below the surface [4,5] in numerous archeological investigations worldwide. Ancient human activities have greatly impacted the soil characteristics by altering the natural soil forming processes.…”

Section: Introductionmentioning

confidence: 99%

Phenological Observations on Classical Prehistoric Sites in the Middle and Lower Reaches of the Yellow River Based on Landsat NDVI Time Series

et al. 2017

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Abstract:Buried archeological features show up as crop marks that are mostly visible using high-resolution image data. Such data are costly and restricted to small regions and time domains. However, a time series of freely available medium resolution imagery can be employed to detect crop growth changes to reveal subtle surface marks in large areas. This paper aims to study the classical Chinese settlements of Taosi and Erlitou over large areas using Landsat NDVI time series crop phenology to determine the optimum periods for detection and monitoring of crop anomalies. Burial areas (such as the palace area and the sacrificial area) were selected as the research area while the surrounding empty fields with a low density of ancient features were used as reference regions. Landsat NDVI covering two years' growth periods of wheat and maize were computed and analyzed using Pearson's correlation coefficient and Euclidean distance. Similarities or disparities between the burial areas and their empty areas were computed using the Hausdorff distance. Based on the phenology of crop growth, the time series NDVI images of winter wheat and summer maize were generated to analyze crop anomalies in the archeological sites. Results show that the Hausdorff distance was high during the critical stages of water for both crops and that the images of high Hausdorff distance can provide more obvious subsurface archeological information.

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Remote sensing applications and archaeological research in the Northern Lagoon of Venice: the case of the lost settlement of Constanciacus

Cited by 41 publications

References 2 publications

Fusion of Satellite Multispectral Images Based on Ground-Penetrating Radar (GPR) Data for the Investigation of Buried Concealed Archaeological Remains

Fusion of Satellite Multispectral Images Based on Ground-Penetrating Radar (GPR) Data for the Investigation of Buried Concealed Archaeological Remains

Satellite remote sensing in archaeology: past, present and future perspectives

Phenological Observations on Classical Prehistoric Sites in the Middle and Lower Reaches of the Yellow River Based on Landsat NDVI Time Series

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