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Remote Sensing for Land & Resources    2021, Vol. 33 Issue (2) : 162-171     DOI: 10.6046/gtzyyg.2020293
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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
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Abstract  

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.
Keywords remote sensing archaeology      site identification      aviation thermal infrared      hyperspectral      Corona      Google Earth     
ZTFLH:  TP79  
Corresponding Authors: FANG Junyong     E-mail: shuhq521@gmail.com;fangjy@aircas.ac.cn
Issue Date: 21 July 2021
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Huiqin SHU
Junyong FANG
Peng LU
Wanfa GU
Xiao WANG
Xiaohong ZHANG
Xue LIU
Lanpo DING
Cite this article:   
Huiqin SHU,Junyong FANG,Peng LU, et al. Research on fine recognition of site spatial archaeology based on multisource high-resolution data[J]. Remote Sensing for Land & Resources, 2021, 33(2): 162-171.
URL:  
https://www.gtzyyg.com/EN/10.6046/gtzyyg.2020293     OR     https://www.gtzyyg.com/EN/Y2021/V33/I2/162
Fig.1  Location of the study area
成像时间 数据源 空间分
辨率/m 		波段
数 		数据来源 备注
1962-04-18 Corona KH-4 3.04 1 美国地质调查局 立体像对
1963-09-25 Corona KH-4A 2.74 1 美国地质调查局
1966-06-06 Corona KH-7 0.61 1 美国地质调查局
1968-08-17 Corona KH-4B 1.82 1 美国地质调查局 立体像对
1968-11-16 Corona KH-4B 1.82 1 美国地质调查局 立体像对
2003-06-12 QuickBird02 0.64 3 Google Earth历史影像
2011-05-27 WorldView-2 0.5 3 Google Earth历史影像
2014-05-29 GF-1 0.46 3 Google Earth历史影像
2015-01-03 WorldView-2 0.55 3 Google Earth历史影像
2015-04-13 WorldView-3 0.38 3 Google Earth历史影像
2016-12-08 WorldView-2 0.52 3 Google Earth历史影像
2017-11-20 WorldView-2 0.5 3 Google Earth历史影像
2019-03-23 GF-1 0.48 3 Google Earth历史影像
2019-12-19 Pleiades 0.5 3 Google Earth历史影像
Tab.1  Multi-source high-resolution remote sensing image information
参数 数值
翼展/mm 2 500
轴距/mm 1 000
最大起飞质量/kg 5
最大任务载重/kg 3
空载悬停时间/min 40
最大爬升速度/(m·s-1) 4
最大下降速度/(m·s-1) 3
地面站控制距离/m 10 000
工作最大海拔/m 5 000
Tab.2  Main parameters of UAV
Fig.2  UAV remote sensing system
Fig.3  Sign of remote sensing interpretation of ancient road remains
Fig.4  Remote sensing image analysis of Pingtao City wall and suspected corner platform remains
Fig.5  The approximate location of the suspected gate of Pingtao City
Fig.6  Image analysis of the rectangular ruins of Pingtao City site
Fig.7  Recognition of ancient road relics from hyperspectral images
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