Optimum temporal and spectral window for monitoring crop marks over archaeological remains in the Mediterranean region

Αγαπίου, Άθως; Hadjimitsis, Diofantos G.; Sarris, Apostolos; Georgopoulos, Andreas; Alexakis, Dimitrios D.

doi:10.1016/j.jas.2012.10.036

Cited by 76 publications

(67 citation statements)

References 32 publications

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“…Since archaeological remains tend to retain different percentages of soil moisture in contrast to the rest of the cultivated area, spectral differences, especially in the Near Infrared (NIR) part of the spectrum, can be recorded from satellite sensors. Depending on the type of the buried archaeological features, crop vigour may be enhanced or reduced [14,15].…”

Section: Introductionmentioning

confidence: 99%

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Study of the Variations of Archaeological Marks at Neolithic Site of Lucera, Italy Using High-Resolution Multispectral Datasets

et al. 2016

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Satellite images have been systematically explored by archaeologists to detect crop marks, which are considered as a proxy for the identification of buried archaeological remains. Even though several existing algorithms are frequently applied, such as histogram enhancements and vegetation indices, the detection of crop marks still remains a difficult task, while the final interpretation results can be very poor. This paper aims to present some of the current difficulties of "remote sensing archaeology" in terms of detection and interpretation of crop marks due to the crops' phenological variations. At the same time, the presented work seeks to evaluate the recently proposed linear equations for the enhancement of crop marks, initially developed for the eastern Mediterranean region. These linear equations re-project the initial n-space spectral into a new 3D orthogonal space determined by three components: a crop mark component, a vegetation component, and a soil component. For the aims of this study, the Lucera archaeological site (southern Italy), where several Neolithic trenches have been identified, was selected. QuickBird and GeoEye high-resolution satellite images were analysed, indicating that vegetation indices may mismatch some crop marks depending on the phenological stage of the vegetation cultivated in the area of the archaeological site. On the contrary, ratios from linear equations were able to spot these crop marks even in shadow areas, indicating that improvements and developments of novel methodologies and equations based on remote sensing datasets can further assist archaeological research.

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Section: Introductionmentioning

confidence: 99%

“…For instance, [15] identified that the optimum spectral region for detection of crop marks using hyperspectral datasets is between 700 nm and 800 nm. Moreover, [23] proposed an image-based methodology to identify phenological variations linked with the presence of buried archaeological features.…”

Section: Introductionmentioning

confidence: 99%

Study of the Variations of Archaeological Marks at Neolithic Site of Lucera, Italy Using High-Resolution Multispectral Datasets

et al. 2016

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“…Previous research has shown that spectral regions of around 700-800 nm (near infrared and red bands) are suitable for detecting crop marks [7]. The Archaeology Index-computed from narrow band imagery-can enhance crop marks related to buried archeological features [8].…”

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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“…Many scholars have been able to reveal archaeological remains beneath ground surface, using a variety of existing algorithms with different rate of success [18][19][20][21][22]. However, the development of new or the modification of existing algorithms for supporting archaeological research is still very limited.…”

Section: Introductionmentioning

confidence: 99%

“…Several climatic and soil parameters should be taken into consideration when examining crop marks. In addition, the formation of crop marks is a dynamic phenomenon and therefore spectral characteristics of crops may vary during the different phenological stages [21]. Indeed several parameters should be taken into consideration, such as the characteristics of the buried features, the burial depth of them, soil characteristics, climatic and environmental parameters, cultivation techniques, etc.…”

Section: Introductionmentioning

confidence: 99%

Orthogonal Equations of Multi-Spectral Satellite Imagery for the Identification of Un-Excavated Archaeological Sites

et al. 2013

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This paper aims to introduce new linear orthogonal equations for different satellite data derived from QuickBird; IKONOS; WorldView-2; GeoEye-1, ASTER; Landsat 4 TM and Landsat 7 ETM+ sensors, in order to enhance the exposure of crop marks. The latest are of significant value for the detection of buried archaeological features using remote sensing techniques. The proposed transformations, re-projects the initial VNIR bands of the satellite image, into a new 3D coordinate system where the first component is the so called "crop mark", the second component "vegetation" and the third component "soil". For the purpose of this study, a large ground spectral signature database has been explored and analyzed separately for each different satellite image. The narrow band reflectance has been re-calculated using the Relative Spectral Response filters of each sensor, and then a PCA analysis was carried out. Subsequently, the first three PCA components were rotated in order to enhance the detection of crop marks. Finally, all proposed transformations have been successfully evaluated in different existing archaeological sites and some interesting crop marks have been exposed.

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Optimum temporal and spectral window for monitoring crop marks over archaeological remains in the Mediterranean region

Cited by 76 publications

References 32 publications

Study of the Variations of Archaeological Marks at Neolithic Site of Lucera, Italy Using High-Resolution Multispectral Datasets

Study of the Variations of Archaeological Marks at Neolithic Site of Lucera, Italy Using High-Resolution Multispectral Datasets

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

Orthogonal Equations of Multi-Spectral Satellite Imagery for the Identification of Un-Excavated Archaeological Sites

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