Search

In recent decades, the application of GIS and RS in archaeological and cultural heritage (ACH) has witnessed a notable surge both in terms of quantity and scope. During the initial implementation period (2016–2021) of the Digital Belt and Road Heritage (DBAR-Heritage) working group, several instances of GIS-RS-based applications in support of cultural heritage conservation have merged. In this paper, in order to discuss the great potential of GIS and RS on the Silk Road, an overview of GIS- and RS-based applications in ACH is first presented. In a substantial portion of the published scientific literature, the identification and comprehension of archaeological sites, the monitoring and risk assessment of cultural heritage, and the management and visualization of cultural heritage data are highlighted. Following this, five illustrative case studies from the DBAR-Heritage working group are presented to exemplify how the integration of GIS and RS serves as key approaches in recognizing and appreciating cultural heritage. These selected case studies showcase the utilization of multi-source data for the identification of linear sites; detailed, refined monitoring and assessment of the Angkor Wat heritage; and the reconstruction of the Silk Road routes. These instances serve as the cornerstone for highlighting current trends in GIS and RS applications in ACH along the Silk Road. These methodologies efficiently integrate multi-source geospatial data and employ multidisciplinary approaches, ultimately furnishing sophisticated and intelligent tools for the exploration and management of archaeological and cultural heritage in the era of Big Earth Data. Subsequently, a comprehensive discussion on the merits and challenges of GIS and RS applications in ACH is presented, followed by an exploration of the current application trends. Finally, the prospects for the widespread application of GIS and RS in ACH along the Silk Road are outlined in accordance with the operational plan of DBAR-Heritage during its second implementation phase. [ABSTRACT FROM AUTHOR]

The International Centre on Space Technologies for Natural and Cultural Heritage (HIST) under the auspices of UNESCO was proposed to UNESCO by the Chinese Academy of Sciences (CAS) in May 2007. Since its inauguration in July 2011, HIST has played a vital role in assisting UNESCO and its Member States in the conservation of UNESCO-designated sites. World Heritage sites, Biosphere reserves and UNESCO Global Geoparks are three primary categories of UNESCO-designated sites. [Extracted from the article]

The tuntian system was a state-promoted system of military–agriculture, which originated in the Western Han dynasty (206 BC–9 AD). All the imperial dynasties in Chinese history adopted the practice of tuntian to cultivate and guard frontier areas as an important state policy for developing border areas and consolidating frontier defense. This paper describes the use of satellite remote sensing data to uncover an ancient canal-based tuntian system located in an oasis agricultural landscape adjacent to the ancient Kingdom of Loulan at the southern margin of the Tarim Basin. The remote sensing data examined include Chinese Gaofen-1 (GF-1) VHR imagery, Landsat-8 (LS-8) OLI data and ASTER Global Digital Elevation Model Version 2 (ASTER GDEMV2) products. The effective irrigated tuntian area was estimated to be 2800 ha and the maximum irrigated tuntian area was found to be more than 8000 ha during the area's most prosperous period. The overall spatial structure of Milan's tuntian agricultural landscape was explored using the patch–corridor–matrix model. By detailed analysis of satellite remote sensing data, this study reconstructed a 3D view of Milan's tuntian agricultural landscape in a GIS. [ABSTRACT FROM AUTHOR]

Landslides, as one of the most destructive natural phenomena, distribute extensively in Wolong Giant Panda Natural Reserve and cause damage to both humans and endangered species. Therefore, landslide susceptibility zonation (LSZ) mapping is necessary for government agencies and decision makers to select suitable locations for giant pandas. The main purpose of this study is to produce landside susceptibility maps using logistic regression (LR), analytical hierarchy process (AHP), and a combined fuzzy and support vector machine (F-SVM) hybrid method based on geographic information systems (GIS). A total of 1773 landslide scarps larger than one cell (25 × 25 m) were selected in the landslide inventory mapping, 70 % of which were selected at random to be used as test data, and the other 30 % were used as validation. Topographical, geological, and hydrographical data were collected, processed, and constructed into a spatial database. Nine conditioning factors were chosen as influencing factors related to landslide occurrence: slope degree, aspect, altitude, profile curvature, geology and lithology, distance from faults, distance from rivers, distance from roads, and normalized difference vegetation index (NDVI). Landslide susceptible areas were analyzed and mapped using the landslide occurrence factors by different methods. For conventional assessment, weights and rates of the affecting factors were assigned based on experience and knowledge of experts. In order to reduce the subjectivity, a combined fuzzy and SVM hybrid model was generated for LSZ in this paper. In this approach, the rates of each thematic layer were generated by the fuzzy similarity method, and weights were created by the SVM method. To confirm the practicality of the susceptibility map produced by this improved method, a comparison study with LR, AHP was assessed by means of their validation. The outcome indicated that the combined fuzzy and SVM method (accuracy is 85.73 %) is better than AHP (accuracy is 78.84 %), whereas it is relatively similar to LR (accuracy is 84.55 %). The susceptibility map based on combined the fuzzy and SVM approach also shows that 5.8 % of the study area is assigned as very highly susceptible areas, and 17.8 % of the study area is assigned as highly susceptible areas. [ABSTRACT FROM AUTHOR]

According to historic records, the wasteland northeast of modern Dunhuang oasis contains remarkable, undiscovered monuments of medieval courier stations. In this study, statistical analysis of historic records and census data, image processing and interpretation of satellite remote sensing images, GIS analysis, and field surveys were carried out to contribute to the discovery of courier stations and the reconstruction of the medieval royal road system from Guazhou to Shazhou. Firstly, in order to obtain the existence regions of courier stations, historic records and census data were abstracted and digitized, for generating preliminary regions of interest by using GIS tools. Secondly, dried river channels and traces of the Great Wall were extracted from the remote sensing images, and GIS buffer and overlay analyses were applied to the creation of prospective sub-areas. Thirdly, prospective sub-areas were mapped from very high resolution WorldView-2 images, and suspected sites were found based on the human-computer interactive interpretation. Fourthly, suspected sites were investigated on the GPS-based archaeological survey, and were confirmed as two courier stations based on the remains of Han-Tang period observed at sites' surface. Lastly, the royal road to ancient Dunhuang, one of the most important sections of the royal road system in the Hexi Corridor, was discussed and reconstructed with the combined application of remote sensing imagery and ground-truthing. [ABSTRACT FROM AUTHOR]

Copyright of Environmental Reviews is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Google Earth (GE), a large Earth-observation data-based geographical information computer application, is an intuitive three-dimensional virtual globe. It enables archaeologists around the world to communicate and share their multisource data and research findings. Different from traditional geographical information systems (GIS), GE is free and easy to use in data collection, exploration, and visualization. In the past decade, many peer-reviewed articles on the use of GE in the archaeological cultural heritage (ACH) research field have been published. Most of these concern specific ACH investigations with a wide spatial coverage. GE can often be used to survey and document ACH so that both skilled archaeologists and the public can more easily and intuitively understand the results. Based on geographical tools and multi-temporal very high-resolution (VHR) satellite imagery, GE has been shown to provide spatio-temporal change information that has a bearing on the physical, environmental, and geographical character of ACH. In this review, in order to discuss the huge potential of GE, a comprehensive review of GE and its applications to ACH in the published scientific literature is first presented; case studies in five main research fields demonstrating how GE can be deployed as a key tool for studying ACH are then described. The selected case studies illustrate how GE can be used effectively to investigate ACH at multiple scales, discover new archaeological sites in remote regions, monitor historical sites, and assess damage in areas of conflict, and promote virtual tourism. These examples form the basis for highlighting current trends in remote sensing archaeology based on the GE platform, which could provide access to a low-cost and easy-to-use tool for communicating and sharing ACH geospatial data more effectively to the general public in the era of Digital Earth. Finally, a discussion of the merits and limitations of GE is presented along with conclusions and remaining challenges. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]