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.

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.

The region near Dujiangyan City and Wenchuan County, Sichuan China, including significant giant panda habitats, was severely impacted by the Wenchuan earthquake. Large-area landslides occurred and seriously threatened the lives of people and giant pandas. In this paper, we report the development of an enhanced multi-temporal interferometric synthetic aperture radar (MTInSAR) methodology to monitor potential post-seismic landslides by analyzing coherent scatterers (CS) and distributed scatterers (DS) points extracted from multi-temporal l-band ALOS/PALSAR data in an integrated manner. Through the integration of phase optimization and mitigation of the orbit and topography-related phase errors, surface deformations in the study area were derived: the rates in the line of sight (LOS) direction ranged from −7 to 1.5 cm/a. Dozens of potential landslides, distributed mainly along the Minjiang River, Longmenshan Fault, and in other the high-altitude areas were detected. These findings matched the distribution of previous landslides. InSAR-derived results demonstrated that some previous landslides were still active; many unstable slopes have developed, and there are significant probabilities of future massive failures. The impact of landslides on the giant panda habitat, however ranged from low to moderate, would continue to be a concern for conservationists for some time in the future.

Asia, Europe, and Africa, connected by the maritime silk road (MSR) and the land silk road (LSR), as the cradle of ancient civilizations, contain rich cultural heritage resources. While aiming to achieve differentiated and targeted application, protection, and development of world cultural heritage (WCHS), it is essential to identify the temporal-spatial distribution features of WCHS on these three continents. For these WCHS elements, based on big earth data, we semi-quantitatively describe the features of spatial-temporal distribution, material types, civilization and religion characters, capital investment capacity, and risks by data cleaning, spatial analysis, and risk assessment. Our findings reveal features in these WCHS elements, including temporal and spatial distribution, the amount of different ancient civilizations and cultural diversity, and the need for preservation and funding capacity. Finally, this study’s results indicate that we should take full advantage of the potential of cultural heritage, digital technologies, and the scientific protection of cultural heritage along with the MSR and LSR. Moreover, declarations of heritage in Africa and Central Asia should be extended to realize the precise “poverty alleviation” of WCHS protection in these regions. For further planning of WCHS sites along the Silk Road, we propose countermeasures to protect the global cultural heritage in the future and also provide theoretical guidance and specific scientific implementation directions to “strengthen efforts to protect and safeguard the world’s cultural and natural heritage,” as proposed by the United Nations.

This study mainly focuses on revealing an ancient water landscape at the Longcheng site in the northern Chaohu Lake Basin using very high-resolution (VHR) GeoEye-1 imagery. First, prior to classification, the GeoEye-1 image was processed following atmospheric and geometric correction. The supervised classification was carried out in order to show the land-cover situation in the Longcheng area. The overall classification accuracy was 89.98%, with a kappa coefficient of 0.87. The moat system around the city walls was discovered by using rule-based object-oriented segmentation of the postclassified image, and the other walls of ancient Longcheng were manually identified from the pansharpened VHR GeoEye-1 image. Finally, a map of the ancient water landscape containing the ancient city, wall and moat at the Longcheng site was produced. This paper demonstrates that VHR remote sensing has the ability to uncover an ancient water landscape and provide new insights for archaeological and paleoenvironmental studies.