Automated Extraction of the Archaeological Tops of Qanat Shafts from VHR Imagery in Google Earth

Remote Sensing

Lei Luo²  Xinyuan Wang²  Huadong Guo²  Chuansheng Liu²  Jie Liu²  Li Li²  Xiaocui Du²  Guoquan Qian³  Rosa Lasaponara¹  Nicola Masini¹  Clement Atzberger¹ 

[1] Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China;;Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China; E-Mails:;Gansu Provincial Institute of Urban Development, Lanzhou 730070, China; E-Mail:

关键词: qanats;    extraction;    archaeological traces;    circular Hough transform;    Google Earth;    very high resolution;   

DOI  :  10.3390/rs61211956

来源: mdpi

【 摘 要 】

Qanats in northern Xinjiang of China provide valuable information for agriculturists and anthropologists who seek fundamental understanding of the distribution of qanat water supply systems with regard to water resource utilization, the development of oasis agriculture, and eventually climate change. Only the tops of qanat shafts (TQSs), indicating the course of the qanats, can be observed from space, and their circular archaeological traces can also be seen in very high resolution imagery in Google Earth. The small size of the TQSs, vast search regions, and degraded features make manually extracting them from remote sensing images difficult and costly. This paper proposes an automated TQS extraction method that adopts mathematical morphological processing methods before an edge detecting module is used in the circular Hough transform approach. The accuracy assessment criteria for the proposed method include: (i) extraction percentage (E) = 95.9%, branch factor (B) = 0 and quality percentage (Q) = 95.9% in Site 1; and (ii) extraction percentage (E) = 83.4%, branch factor (B) = 0.058 and quality percentage (Q) = 79.5% in Site 2. Compared with the standard circular Hough transform, the quality percentages (Q) of our proposed method were improved to 95.9% and 79.5% from 86.3% and 65.8% in test sites 1 and 2, respectively. The results demonstrate that wide-area discovery and mapping can be performed much more effectively based on our proposed method.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.