Research on fine recognition of site spatial archaeology based on multisource high-resolution data
SHU Huiqin1,2(), FANG Junyong1(), LU Peng3, GU Wanfa4, WANG Xiao1, ZHANG Xiaohong1, LIU Xue1, DING Lanpo4
1. Areospace Information Research Institute, China Academy of Sciences, Beijing 100094, China 2. University of Chinese Academy of Sciences, Beijing 100049, China 3. Institute of Geographical Sciences, Henan Academy of Sciences, Zhengzhou 450052, China 4. Zhengzhou Institute of Cultural Relics and Archaeology,Zhengzhou 450000, China
The ancient city of Pingtao, Zhengzhou City, Henan Province, was an important city in the Eastern Zhou Dynasty and has important historical value. Due to the problems of time-consuming, heavy investment and heavy workload in traditional archaeological investigations, the settlement layout and relic distribution of the old city of Pingtao are still unclear. In this study, the authors selected Corona, Google Earth historical images and aerial thermal infrared images, comparatively analyzed the tonal and texture features on images of different loads, phases and scales, and extracted the archaeological anomalous areas of the Pingtao City site and Dianjuntai site. Suspected ruins such as city walls, gates, corner platforms and rectangular building foundations were discovered, and the spatial structure of the ruins was initially reconstructed based on the identification results. The results of the study show that Corona imagery helps to identify the early appearance of the site, Google Earth historical imagery provides assistance for the detection and extraction of tiny suspected relic features, and aerial thermal infrared imagery can reveal such archeological features as indistinct burial on the ground or optical image. The research proves that the comprehensive utilization of multi-source high-score data can investigate, predict and reconstruct the distribution and spatial structure of the relics, thus providing a reference for further archaeological research and site protection.
舒慧勤, 方俊永, 鲁鹏, 顾万发, 王潇, 张晓红, 刘学, 丁兰坡. 基于多源高分辨率数据的遗址空间考古精细识别研究[J]. 国土资源遥感, 2021, 33(2): 162-171.
SHU Huiqin, FANG Junyong, LU Peng, GU Wanfa, WANG Xiao, ZHANG Xiaohong, LIU Xue, DING Lanpo. Research on fine recognition of site spatial archaeology based on multisource high-resolution data. Remote Sensing for Land & Resources, 2021, 33(2): 162-171.
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