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.

With improvements in synthetic aperture radar (SAR) image resolutions and multitemporal SAR interferometry (MTInSAR) algorithms, it becomes feasible to generate 3D point clouds with millimeter deformation accuracy to monitor urban infrastructure health in detail. This article reviews the progress and challenges of MT interferometric SAR (InSAR) techniques for infrastructure deformation monitoring, with an emphasis on refinement performance. After a brief overview of literature statistics, we examine characteristics of the main MTInSAR algorithms. We demonstrate performance refinement in terms of point density, height accuracy, and deformation accuracy, using a comparative study of the reclaimed Hong Kong International Airport (HKIA). A series of typical infrastructure dynamic behaviors in urban areas revealed by MTInSAR is then illustrated. This article also describes key issues that remain to be addressed to facilitate operational fine surveillance. Finally, we go beyond MTInSAR to illustrate intelligent infrastructure diagnosis systems applicable to city-scale and even infrastructural component-scale analysis. It is our expectation that this review will provide a reference and guidance for future research and applications of MTInSAR in urban infrastructure monitoring.