Title | ||
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Archeological crop marks identified from Cosmo-SkyMed time series: the case of Han-Wei capital city, Luoyang, China. |
Abstract | ||
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The development of spaceborne Synthetic Aperture Radar (SAR) technology declares that the golden era of SAR remote sensing in archeology is approaching; however, nowadays its methodology framework is still lacking due to the inadequate case studies validated by ground-truths. In this study, we investigated the crop marks using multi-temporal Cosmo-SkyMed data acquired in 2013 by applying a two-step decision-tree classifier in conjunction with a spatial analysis in an area of archeological interest nearby the archeological site of Han-Wei capital city (1900-1500 BP), in Luoyang, China. The time-series backscattering anomalies related to the wheat growth cycle were identified and then further validated in two zones by geophysical investigations (Ground Penetration Radar and electrical measurements) and in a third zone by archeological excavations made after the SAR data acquisition. This study provides a new approach for the relic detection, shallowly buried and covered by the crop vegetation, by temporal crop marks on spaceborne SAR images. We also emphasize the necessity to establish a satellite-to-ground methodology framework for the promotion of remote-sensing technology in archeology. |
Year | DOI | Venue |
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2017 | 10.1080/17538947.2016.1254686 | INTERNATIONAL JOURNAL OF DIGITAL EARTH |
Keywords | Field | DocType |
SAR,crop mark,archeological prospection,Luoyang,Han-Wei capital city,geoarcheology | Radar,Vegetation,Excavation,Synthetic aperture radar,China,Remote sensing,Geoarchaeology,Geology,Archaeology | Journal |
Volume | Issue | ISSN |
10.0 | 8.0 | 1753-8947 |
Citations | PageRank | References |
1 | 0.85 | 6 |
Authors | ||
11 |
Name | Order | Citations | PageRank |
---|---|---|---|
Aihui Jiang | 1 | 1 | 0.85 |
Fulong Chen | 2 | 27 | 7.17 |
Nicola Masini | 3 | 47 | 15.10 |
Luigi Capozzoli | 4 | 5 | 1.79 |
Gerardo Romano | 5 | 5 | 1.45 |
M. Sileo | 6 | 5 | 2.46 |
Ruixia Yang | 7 | 1 | 0.85 |
Panpan Tang | 8 | 20 | 5.74 |
Panpan Chen | 9 | 5 | 2.12 |
Rosa Lasaponara | 10 | 95 | 26.67 |
Guolin Liu | 11 | 4 | 3.95 |