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Auto-Extraction of Linear Archaeological Traces of Tuntian Irrigation Canals in Miran Site (China) from Gaofen-1 Satellite Imagery

Academic Article
Publication Date:
2018
abstract:
This paper describes the use of the Chinese Gaofen-1 (GF-1) satellite imagery to automatically extract tertiary Linear Archaeological Traces of Tuntian Irrigation Canals (LATTICs) located in the Miran site. The site is adjacent to the ancient Loulan Kingdom at the eastern margin of the Taklimakan Desert in western China. GF-1 data were processed following atmospheric and geometric correction, and spectral analyses were carried out for multispectral data. The low values produced by spectral separability index (SSI) indicate that it is difficult to distinguish buried tertiary LATTICs from similar backgrounds using spectral signatures. Thus, based on the textual characteristics of high-resolution GF-1 panchromatic data, this paper proposes an automatic approach that combines joint morphological bottom and hat transformation with a Canny edge operator. The operator was improved by adding stages of geometric filtering and gradient vector direction analysis. Finally, the detected edges of tertiary LATTICs were extracted using the GIS-based draw tool and converted into shapefiles for archaeological mapping within a GIS environment. The proposed automatic approach was verified with an average accuracy of 95.76% for 754 tertiary LATTICs in the entire Miran site and compared with previous manual interpretation results. The results indicate that GF-1 VHR PAN imagery can successfully uncover the ancient tuntian agricultural landscape. Moreover, the proposed method can be generalized and applied to extract linear archaeological traces such as soil and crop marks in other geographic locations.
Iris type:
01.01 Articolo in rivista
Keywords:
auto-extraction; remote sensing archaeology; tuntian; LATTICs; GF-1; Silk Road; Miran
List of contributors:
Lasaponara, Rosa
Authors of the University:
LASAPONARA ROSA
Handle:
https://iris.cnr.it/handle/20.500.14243/372811
Published in:
REMOTE SENSING (BASEL)
Journal
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URL

http://www.mdpi.com/2072-4292/10/5/718
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