The use of remote-sensing images for field surveys and exploration has become an important part of the preliminary stage of archaeological research. With the development of the global positioning system (GPS), users can pinpoint their locations using a wide range of available navigation applications (such as Amap, Baidu Map, and the BeiDou Navigation Satellite System) and professional GIS software (such as Ovitalmap and Map Plus). Some of these applications support user-defined layers, which allow users to import their data for real-time locating. In this study, the authors (the research team) applied this feature to archaeological field surveys and exploration. By importing the required image layers into mobile devices in advance, the research team was able to observe the features of archaeological ruins in the study area while on site based on the topographical characteristics presented by the image.
Named after the town of Liangzhu in the Yuhang district of Hangzhou, Zhejiang, where it was discovered, the Liangzhu culture dates back about 4,300–5,300 years. It is regarded as the culmination of the Neolithic Age in the Taihu Lake area in the lower reaches of the Yangtze River. As a testimony to the 5,000-year history of Chinese civilization, the Archaeological Ruins of Liangzhu City (referred to hereinafter as the “Liangzhu site”) was added to the UNESCO World Heritage List in 2019. The study area features a relatively visible and concentrated distribution of Liangzhu ruins, which is helpful for archaeological ruins identification using remote-sensing images.
Most of the Liangzhu-period ruins in the Taihu Lake area are clay or stone terraces that rise several meters above the ground surface. The terraces vary in height, indicating their grade and size. Waters and rice fields are distributed in lower regions around the terraces. This pattern has remained largely unchanged, and these terraces have been in use ever since they were built. Instead of levelling up the terraces and building new ones, people of later generations built upon the original terraces and carried out planting, processing, and other activities on the periphery of the terraces, thus preserving the early pattern of the archaeological ruins(Wang, 2011). Based on this feature, researchers believe that elevation is a key indicator for distinguishing the types and grades of Liangzhu ruins, as it can better reflect the original ruins distribution pattern in this area and is more effective in identifying ruins than high-definition satellite images and digital line graphs(Liu and Wang, 2016) . Water management was an important social activity for agricultural settlements. The builders of many now ruined structures similar to those at the Liangzhu site acquired a good knowledge of local hydrological features before they started construction. Liu Jianguo built a digital elevation model (DEM) for the Qujialing, Shijiahe, and Chenghe sites and for other major prehistoric settlements in Jianghan Plain. By identifying and analyzing the performance of the settlements in the hydrological environment, he was able to explain the structures and functions of these archaeological ruins(Liu, 2008). To some extent, therefore, elevation information can be used as an indicator of ruin patterns. However, given that most available DEM data can only reflect the topography of the modern environment, the ever-changing surface of plains, lowlands, and uplands in the Yangtze River Delta, and the vegetation and buildings, have to varying extents affected the accuracy of identification of archaeological ruins.
From a professional perspective, the discovery and identification of archaeological ruins cannot be achieved without a balance between factors such as the timeline of landform evolution, data accuracy, easy access to data, efficient data processing, and convenience in interpreting remote-sensing images for archaeological field workers. Considering the temporal and environmental characteristics of the Liangzhu site, the research team used stereo pairs of historical remote-sensing images to present the stereo effect of the archaeological ruins instead of building a DEM based on digital topographic maps or aerial survey data. At present, Keyhole (KH) satellites are the only source of historical remote-sensing images that have a high resolution and can be acquired easily. Among them, the CORONA images (mostly KH-4B images with a ground resolution of 6 feet) were taken mainly in the 1960s, when the study area had not yet undergone massive urban expansion and intensive agricultural development and the landforms could still reflect early surface features, thus providing an important basis for the identification of archaeological ruins. By comparing the CORONA image of the Liangzhu ancient city with that from Google Maps (as shown in Figure 1), one can see that the CORONA image, with clear layers and surface features, is as good as the one taken by modern commercial high-resolution satellites in terms of the details of houses and streets.
CORONA images can display an archaeological landscape that no longer exists. In addition, CORONA data consist of stereo pairs, from which 3D images of landscapes can be generated. Elevation changes in the Earth’s surface are more visible in these images than in single images, making for easier identification of surface features. However, the extraction of DEMs from CORONA stereo pairs using photogrammetric methods still has many limitations and is rarely used in practice because of its low efficiency(Day et al., 1998). Were the research team to observe CORONA images with a stereoscope, the original CORONA stereo pairs could be used directly, without complex image processing procedures such as reference point selection and image correction. However, this method, whether conducted through the observation of printed CORONA images with a stereoscope or the observation of software-generated red/blue stereo images on a computer screen, would impose great limitations on stereo effect viewing and could not be applied directly in the field survey.
Considering the research purpose, the time when CORONA images were taken, and the resolution, cloud fraction, price, and operability of the images, the research team, after collecting the CORONA images of Zhejiang province and the entire Yangtze River Delta, built an optical stereo model based on the CORONA stereo pairs of the study area at the Liangzhu site. During the field survey and exploration, the team imported the historical remote-sensing images and the optical stereo model of the study area into an application on their mobile devices and located the sites on the model using the GPS navigation system on these devices. With the help of red/blue glasses, the team performed on-site stereo observation to fully interpret the topography and surface features shown on the historical remote-sensing images, which facilitated the search for archaeological ruins.
Actually, CORONA historical satellite images have been wildly used in archaeology studies (Casana, 2021)since it was declassified in late 1990s. Utilizations in Middle East archaeological investigation is in a large majority(Beck et al., 2007; Casana and Cothren, 2008; Casana et al., 2012; Challis et al., 2004; Kennedy, 1998; Kouchoukos, 2001; Philip et al., 2002; Ur, 2003; Wilkinson et al., 2006; M. J. F. Fowler, 2004), since archaeological sites dominate these alluvial landscapes with relatively heterogeneous land cover but with less vegetation are easily indentified in panchromatic images with high-resolution(Ur, 2013). While there are few other generally discussed cases in Europe (M. Fowler, 2004). From methodological perspectives, most of the utilization concentrate on discovering disappeared sites through manual interpretation by archaeologists. Recent developments take advantage of the large coverage of the CORONA data for building up historical land cover database(Casana, 2014, 2020).
Only a few previous research considered stereo pairs collected by CORONA. Jesse Casana’s team in Dathmoth College adopted ortho-rectification technologies by various scholars and develop an online platform call “Sunspot”, which is mainly for create “a global CORONA atlas”(Casana, 2020) , but it is also proved to be available for generating high-resoluation DEM by photogrammetry( Casana and Cothren, 2008). Watanabe Nobuya worked with the authors’ team investigated the Liangzhu City and hydraulic system through similar approaches in stereo pairs but introducing both DEM with less accuracy than Casana’s work and stereoscopic viewing for a more intuitive perception for an archaeological sight(Watanabe et al., 2017).
However, although remote sensing data, especially those high-resolution categories like CORONA, are mainly introduced in supporting field survey, but the whole survey procedure largely depends on indoors image investigation other than site identification. Therefore, all these efforts are desktop approaches and time-consuming. On-site efficiency seems not be the priority.
Some researchers have adopted remote sensing technology for research on the Liangzhu site and proved its effectiveness. In particular, CORONA historical remote-sensing images and DEM data have played an important role in assisting the search for the walls, inner city ruins, and outer regions of the ancient city on the Liangzhu site. GIS elevation models and CORONA images have also provided key clues for the search for the overall structure of the massive hydrological system outside the ancient city and for the analysis of the structure, proving that the Liangzhu site has a palace/inner city/outer city structure and a large hydrological system on its periphery. Most of the remote-sensing images used for archaeological research on this area thus far have been two-dimensional (2D) images(Watanabe et al., 2017). When using CORONA remote-sensing stereo pairs for archaeological ruins identification, well-known scholars such as Watanabe Nobuya built DEMs using complex photogrammetric methods and did not turn the CORONA images into optical stereo models.