Abstract The central Appalachians form a classic orogen whose structural architecture developed during episodes of contractional, extensional, and transpressional deformation from the Proterozoic to the Mesozoic. These episodes include components of the Grenville orogenic cycle, the eastern breakup of Rodinia, Appalachian orogenic cycles, the breakup of Pangea, and the opening of the Atlantic Ocean basin. This field trip examines an array of rocks deformed via both ductile and brittle processes from the deep crust to the near-surface environment, and from the Mesoproterozoic to the present day. The trip commences in suspect terranes of the eastern Piedmont in central Virginia, and traverses northwestward across the Appalachian orogen through the thick-skinned Blue Ridge basement terrane, and into the thin-skinned fold-and-thrust belt of the Valley and Ridge geologic province. The traverse covers a range of deformation styles that developed over a vast span of geologic time: from high-grade metamorphic rocks deformed deep within the orogenic hinterland, to sedimentary rocks of the foreland that were folded, faulted, and cleaved in the late Paleozoic, to brittle extensional structures that overprint many of these rocks. Stops include: the damage zone of a major Mesozoic normal fault, composite fabrics in gneiss domes, transpressional mylonites that accommodated orogen-parallel elongation, contractional high-strain zones, and overpressured breccia zones in the Blue Ridge, as well as folds, thrusts, and back thrusts of the Alleghanian foreland.

Abstract This two-day trip highlights new findings from structural, stratigraphic, and petrologic research in the Valley and Ridge province of Highland, Bath, and Augusta Counties, Virginia, and Pendleton County, West Virginia. The structural emphasis on Days 1 and 2 will be at several scales, from the regional scale of folds and faults across the Valley and Ridge, to outcrop-and hand sample-scale structures. Stops will highlight deformation associated with previously unmapped faults and a second-order anticline in Silurian and Lower Devonian carbonate and siliciclastic strata, specifically the Silurian Tonoloway Limestone, the Silurian–Devonian Helderberg Group, and the Devonian Needmore Shale. The stops on Day 1 will also focus on facies changes in Silurian sandstones, the stratigraphy of the Keyser–Tonoloway formational contact, and new discoveries relevant to the depositional setting and regional facies of the McKenzie Formation in southern Highland County. The focus of the stops on Day 2 will be on the petrology and geochemistry of several exposures of the youngest known volcanic rocks (Eocene) in the eastern United States. Discussions will include the possible structural controls on emplacement of these igneous rocks, how these magmas and their xenoliths constrain the depth and temperature of the lower crust and mantle, and the tectonic environment that facilitated their emplacement.

The past decade has seen a rapid increase in the application of high-resolution imagery and geographic-based information systems across every segment of society from security intelligence to product marketing to scientific research. Google Earth has positioned itself at the forefront of this spatial information wave by providing free access to high-resolution imagery through a simple, user-friendly interface. Whereas Google Earth imagery has been widely exploited across the earth sciences for spatial visualization, education, and place-based searches, few studies have utilized the high-resolution imagery to yield quantitative insights about the processes and mechanisms acting at the earth's surface. In this paper, we detail the benefits of the underlying high-resolution imagery available within Google Earth, review the limited published research to date, and utilize this imagery to quantitatively illuminate previously difficult and unresolved questions within the discipline of geomorphology involving: (1) channel-width variability and scaling relations in the tectonically active Himalaya; (2) landslide characteristics related to large magnitude climatic and tectonic events in Haiti; and (3) identification and quantification of laterally offset geomorphic features within eastern California. In each example, we compare analyses using freely available Google Earth imagery with standard imagery and techniques (e.g., Landsat, ASTER, lidar) to demonstrate the potential benefits of using high-spatial resolution Google Earth imagery over established methodologies. In addition, we discuss the potential limitations and problems with using the imagery currently available in Google Earth and propose favorable future applications, namely studies in remote terrains and those requiring high-resolution imagery across a large spatial extent, where purchasing such imagery in an academic environment would be cost-prohibitive. Whether as a supplement, for reconnaissance, or as the primary data set, high-resolution Google Earth imagery, when properly applied, holds great promise for quantitatively tackling previously unresolved problems in the study of earth surface processes.

Remote sensing is an important option for finding interesting research problems in remote regions of the world, but existing freely available imagery, such as Landsat imagery, has limitations in terms of resolution. In some remote areas, recently available high-resolution imagery in Google Earth has the potential to revolutionize the kind of research that can be initiated and carried out. This paper details an example from a remote region of Egypt's Western Desert. Work by others on Eocene carbonates of the Drunka and El Rufuf Formations has focused on lithologic and paleontologic aspects, and previous mapping of the contact between the two formations in the Western Desert using early Landsat imagery (69 m/pixel) shows a simple contact. High-resolution imagery in Google Earth (~1 m/pixel) shows, however, that the contact is both folded and faulted. We used high-resolution images in Google Earth to define mappable subunits and to do detailed mapping of folds and faults in a 400 km 2 study area. Subsequent field work confirmed the accuracy of lithologic and structural mapping in Google Earth, targeted critical areas for field data collection, and provided ground truth for extending mapping into remote areas. Freely available, high-resolution satellite imagery in Google Earth not only allows identification of research questions but is also critical in pre–field work mapping, targeting sites for field work, and disseminating research results in areas of the world where field work is difficult, funding is poor, and access to dissemination of research results outside the region is limited.

High-resolution topography data acquired with lidar (light detection and ranging) technology are revolutionizing the way we study Earth surface processes. These data permit analysis of the mechanisms that drive landscape evolution at resolutions not previously possible yet essential for their appropriate representation. Unfortunately, the volume of data produced by the technology, software requirements, and a steep learning curve are barriers to lidar utilization. To encourage access to these data we use Keyhole Markup Language (KML) and Google Earth to deliver lidar-derived visualizations of these data for research and educational purposes. Display of full-resolution images derived from lidar in the Google Earth virtual globe is a powerful way to view and explore these data. Through region-dependent network linked KML (a.k.a., super-overlay), users are able to access lidar-derived imagery stored on a remote server from within Google Earth. This method provides seamless, Internet-based access to imagery through the simple download of a small KML-format file from the OpenTopography Facility portal. Lidar-derived imagery in Google Earth is the most popular product available via OpenTopography and has greatly enhanced the usability and thus impact of these data. Users ranging from scientists to K–12 educators have downloaded KML files ~12,000 times during the first eight months of 2011. The overwhelming usage of these data products demonstrates the impact of this simple yet novel approach for delivering easy to use lidar data visualizations to Earth scientists, students, and the general public.

Conventional archaeological excavation methods are, by design, extremely invasive and result in culturally sensitive areas being irrevocably altered. For this reason, near-surface geophysical techniques have been incorporated into archaeological investigations to aid in locating buried features and developing specific excavation plans with minimal damage to the sites. The objective of our research was to conduct a geophysical surveying campaign at a test site in Knoxville, Tennessee, to develop a workflow for an improved data management methodology that would be applied to data acquired at an active archaeological site in Cyprus. A multi-tool geophysical survey was completed as a first case study at a control site with known subsurface features on the University of Tennessee Agricultural Campus using both ground penetrating radar and magnetic gradiometry. Using real-time differential corrected GPS data, we systematically imported the images into Google Earth as accurately georeferenced overlays on existing topographic maps and air photos. We added placemarks where we interpreted subsurface anomalies based on the data, exported waypoints for the features into spreadsheet software, and correlated the results to the known locations. We next tested this methodology with data from an active archaeological site in southern Cyprus. Data were displayed in Google Earth and accurate GPS coordinates for features were exported into a spreadsheet file. We were able to share a tested, easily accessible final product that was immediately useful and accessible to the archaeologists on the team and the broader archaeological community.

The Grenadine Islands and the marine environment surrounding the islands were mapped over a five-year span. The project—Grenadines Marine Resource and Space-Use Information System (MarSIS)—involved merging local knowledge with existing scientific data into a geographic information system (GIS). Located in the Caribbean, the Grenadines share an international boundary between Grenada and St. Vincent and the Grenadines, creating numerous challenges for not only collecting data but sharing those data with the residents of the islands. Project geospatial information was collected in a GIS, but Google Earth was used as a way to share the findings on the web and through a series of tutorials and workshops. Though project GIS shapefiles will be made available through the project website, Google Earth was used as a ready delivery tool because it is cross platform, easy to use, and free. Using aftermarket GIS extensions, shapefile layers were exported from ArcGIS into Keyhole Markup Language (KML) layers. Over 400 photographs and videos were geolocated in the project KML. Once the Grenadines marine map was assembled as a KML project, we gave workshops on various islands. From user feedback following the first series of tutorials, we modified the KML by fixing problems, correcting mistaken information, and making the KML project file more understandable. When the project was finalized we put the KML on the MarSIS project web page and sent it as an attachment to the project email list. We traveled a second time to the Grenadine Islands to give another series of tutorials and workshops. We also created a video to help users navigate the project KML.

Keyhole Markup Language (KML)—a type of extensible markup language (XML)—is the key to the extensibility of Google Earth for geoscience applications. Static KML code may be saved to a file from the Google Earth desktop application, handwritten with a text editor, or generated by running a custom computer program. Many Google Earth visualizations are limited to static KML developed with the desktop application's user interface. The purpose of this paper is to highlight how much more is possible with the implementation of additional applications. Geoscience learning resources may be taken to the next level with the interactive generation and animation of graphics and models both in the desktop application and using the Google Earth web browser plug-in and its JavaScript application programing interface. Dynamic KML may be generated on-the-fly by means of client-side or server-side scripts, or with the aid of Google Fusion Tables and network links.

The effectiveness of a computer application depends on, among other things, an efficient user interface. In order to visualize subsurface geologic phenomena using the Google Earth™ application, we initially employed the built-in Google Earth time slider. Dragging the slider's right thumb elevated a COLLADA model that initially loads at a subsurface altitude. However, the double-thumb feature of the time slide caused users some difficulties. It is not possible to turn off this feature when not required, so it can be misleading to users. Because of this and because of the need for more control, we transitioned from the stand-alone Google Earth application to the web-based Google Earth plug-in. To overcome some of the limitation for the existing user interface, such as the inability to make controls appear semitransparent, we designed and implemented a screen overlay using the plug-in's application programming interface. This approach opened new possibilities to build more customizable user interfaces. A demonstration of the approach and sample usage of JavaScript to create buttons, draggable images, slides, and slider controls is presented.

Although the evolution of Brazilian coastal depositional systems in the Quaternary has been studied in past decades, it is only in the last couple of years that it has been possible to incorporate the latest remote sensing databases available to help understand their development. In comparison to other freely accessible imagery, high-resolution images available on Google Earth are advantageous when undertaking local coastal analysis. In some instances, it is possible to differentiate geomorphologic features such as tidal deltas, beach ridges, and dunes. Also, the monitoring of small-scale features allows evaluation of the sensitivity of coastal zones to high-frequency and low-intensity processes. Thus, the downscaling description of coastal zones is now easily accessible, permitting the analysis of the extensive Brazilian coastal depositional systems. On the regional scale, a quick glance of a coastal setting may help frame the sedimentary characteristics of the depositional system. Coastal areas in the States of Santa Catarina and São Paulo are taken into consideration in this study. These areas illustrate representative prograded barrier formations from Middle to Late Holocene with dunes formed at a later development stage. A comparison is made in the use of Google Earth and its historic images with aerial photographs and Landsat images. In the past, small-scale features of these regions were evaluated in aerial photographs, while regional features were studied by low-resolution satellite images. Accordingly, integration of these two products was difficult. In this work, we show that Google Earth facilitates the analysis as a whole. Furthermore, comparison of Google Earth images with aerial photographs from 1938 onward allowed the study of short-term migration and deflation of the dunefields probably accelerated in recent years by human interference. In addition, Keyhole Markup Language (KML) files were saved from Google Earth placemarks to facilitate georeferencing raster images on GIS programs. Finally, information available from previous local studies, such as luminescence dating, geomorphology of the costal system, grain size, heavy minerals, pollen, and carbon isotope analyses, was gathered into a Google Fusion Table database making data retrieval and parsing easily accessible. This database provides information that can be shared with other researchers and may be used to address important questions about the development of Brazil's coastal system in the past, present, and future.

Data on ground-water and surface-water use in Louisiana are available online in tabular form from the U.S. Geological Survey. Data are categorized by parish and by type of usage (e.g., public supply, irrigation, industry, and power generation) from 1960 to 2005. Water usage in Louisiana has complicated spatial and temporal trends which are not readily apparent in static tables. For example, ground-water usage varies from more than 200 million gallons a day in some rice farming parishes to less than 40,000 gallons a day in coastal parishes where most ground water is not potable. Baton Rouge Parish uses mostly ground water even though it is on the Mississippi River because the ground water is high quality. Orleans Parish uses almost exclusively river water because most ground water is brackish. Significant temporal trends include the rapid rise of water use for power generation since 1960, a drop in overall water usage during the economic downturn following the oil bust of the 1980s, and the switch from surface to ground water in some areas due to decadal droughts or pollution of surface water. Google Fusion Tables represent a rapid and effective way to visualize water usage trends for K–16 education, research, and public policy. Using Google API (application programming interface), we have developed intensity maps that illustrate quantity and category of both surface-water and ground-water use by parish. Each parish within an intensity map has a pop-up bar chart that shows total water usage from 1960 to 2005 in five-year increments. We also have included versions of intensity maps that have pop-up pie/line charts that show the distribution of usage in each parish among public supply, agriculture, industry, and power generation. The dynamic feature of Fusion Tables allows students, researchers, and policy makers to clearly see temporal trends as well as illustrate connections among water usage and other factors. For examples, most students falsely assume that the steady rise in water use for public supply is related to population increase whereas it is primarily due to a substantial increase in per capita usage. These tables will be made available on the web.

Animal tracking data are routinely delivered in the form of e-mail messages with an attachment or in the main text of an e-mail that includes satellite-telemetry data provided by Argos services. Downloading these data onto a computer, transferring them into shapefiles, filtering, processing, and displaying them consumes considerable end-user time and energy. In this paper, we demonstrate that freely available “Cloud”-based services are sufficient to take over this workload and fast enough to deliver spatial data to an end-user without a considerable investment of time. The animal-generated spatial data we present come in two forms: satellite data from the Argos service and GPS data delivered as text messages using a Short Message Service (SMS). We suggest a simple mail-to-map system, which automatically archives data (coordinates, time, telemetry) and displays it dynamically on various Internet applications such as Google Maps/Google Earth or Google Graphs. We use the Gmail service to filter messages, a free blog service (e.g., blogger.com or wordpress.com) for unlimited-time data storage and the Google spreadsheets to dynamically assemble the KML (Keyhole Markup Language) files. To demonstrate the utility of our mail-to-map system, we apply the approach to two contrasting wildlife case studies—the highly endangered Steller's Sea Eagle ( Haliaetus pelagicus ) of northeast Asia and White-tailed Deer ( Odolescens virginianus ), which is ubiquitous in the eastern United States—and discuss conservation implications of the near-real-time data publication opportunities that our system provides.

Digital geologic maps that use a virtual globe interface, like Google Earth (GE), are a relatively new medium for presenting geologic data and interpretations. This format incorporates significant advantages over traditional paper geologic maps and cross sections, including: A user-friendly and intuitive interface for novice users, which enhances the utility of geologic information for students and the general public; The ability to view multiple maps simultaneously and seamlessly transition between maps by zooming or panning; The option of displaying cross sections in situ on geologic maps as vertical interpretations of above ground or subsurface geology; and A facility for integrating map interpretations with individual outcrop and field data, which traditionally has been relegated to field books. This paper outlines a digital maps package, composed of geologic maps of regions of Virginia, as a proof of concept and template for possible future expansion beyond state boundaries or into the realm of soils, geomorphological, or hydrological maps. Through collaboration amoung universities, state agencies, and federal organizations we have assembled a multi-layered, fully interactive map accessible through two portals: the stand-alone Google Earth application, and as a web page using the GE web browser plug-in (GE API). All maps within this package have selectable polygons, polylines (“paths”), and points (“placemarks”), many of which contain associated metadata, such as lithologic descriptions, fault information, outcrop orientation data, etc. At the smallest scale, a generalized geologic map of Virginia is displayed with a selectable overlay of regional physiographic provinces. As users pan and zoom, the maps automatically transition from generalized statewide maps to more refined regional maps and 1:24,000 scale quadrangle maps. Many of the map components (cross sections, explanations, and orientation symbols) cannot be created directly in GE but are added to the digital maps using KML scripts derived from an HTML-based toolkit. Challenges related to the method of digital map development described herein include: effective importation of vector data from other GIS databases, style limitations inherent in GE, and time-consuming labor associated with the digitization of polygons and polylines in GE. There are also conceptual challenges at the user interface level, including possible misconceptions with the display of vertical cross sections due to the inability to look below the GE digital elevation model and associated surface imagery.

Google Earth offers an excellent example of software design balancing enough power while retaining a simple and intuitive interface, and provides tremendous capabilities both for teaching and research interaction. It displays data with a well-documented, standard keyhole markup language (KML) format on generally high resolution base imagery, with roads, borders and other relevant layers which can be turned on and off, and allows easy combination of multiple data sets. Google Earth lacks the analysis capabilities of geographical information system (GIS) software, but is outstanding for visualization and dissemination of results. Users can zoom in and out and view animations or 3-D displays of the data. The freeware MICRODEM program allows easy export of GIS data to KML and linking of text and graphics to an icon on the map, and it facilitates registration of maps. Examples of this usage include student projects, animations used for teaching, sharing data among research groups, and interactive display of published maps. For the earth sciences, where almost all data has a geographic component, virtual globes provide an integrated way to interact with information.

College geoscience departments keep archives of student research ranging from senior theses to master's and Ph.D. dissertations. In field geology, these archives often include maps, cross sections, stereographic projections, field notes and photographs, hand specimens, and thin sections. Subsequent publications may result from the thesis work, but much of this valuable legacy data is difficult to access and assess. Here we describe the conversion of a pre–digital-era thesis on the Vredefort Rim Synclinorium in South Africa from hard copy to digital format using Keyhole Markup Language (KML) to drape maps and inset photographs, and COLLADA (COLLAborative Design Activity) models to create stereographic projections, emergent cross sections, and virtual specimens. In addition to using the Google Earth terrain to fine-tune draped map locations, errors in field locations arising from pace and compass or bearing methods of geo-location that preceded the availability of Global Positioning Systems (GPS) were recognized and corrected. At 2.023 billion years in age and an estimated 300 km in original diameter, the Vredefort Dome is the world's oldest and largest known impact structure. The Vredefort region has been designated a World Heritage Site and specimen collection is prohibited. Only a few geologists are ever likely to visit the region, so geo-referenced field photography, specimens, and structural data are irreplaceable. An interpretative center is being planned for the Vredefort structure by South African authorities and our interactive Google Earth resources will be made available to the visiting public as well as those browsing over the Internet. Thus draped maps and scanned models provide an invaluable opportunity for enhanced instruction, continued research, and public outreach.

This paper focuses on the potential for developing geologic maps using high-resolution aerial imagery and digital elevation data. A key component of geologic mapping discussed herein addresses the determination of geologic layer orientation using a planar approximation (also known as the three-point method). An analytical solution is presented which can be readily implemented in a spreadsheet. The path from initial data collection in a GIS to spreadsheet computation and back to GIS is outlined. The Mecca Hills in southern California serve as a test case, as there is good coverage with high-resolution aerial imagery, a variety of elevation data including airborne LiDAR, and a published geologic map for the area. The comparison between vector-derived strike and dip and traditional field measured strike and dip suggests that remote mapping can successfully capture the regional aspects of the geology in an area. Estimates of rock orientation can be made if the elevation data is accurate and sufficient visual contrast exists in aerial imagery to define mappable features. A comparison shows that United States Geological Survey's National Elevation Data sets and airborne LiDAR can identify regional geologic structures, while Shuttle Radar Topography Mission and ASTER GDEM data yield results that diverge substantially from higher resolution elevation data. Remote mapping using the vector form of the three-point method offers a promising tool for geologic exploration as data sets continue to improve in quality and resolution.

Google Earth Pro imagery was used by graduate students for a course project to identify, describe, and interpret lineament patterns on two oil-producing anticlines in Wyoming, one in the northwest Wind River Basin and the other in the southern Bighorn Basin (Maverick Springs and Thermopolis anticlines, respectively). These anticlines lie on opposite sides of the east-west–trending Owl Creek arch, which is a sinistral, transpressive array of en echelon, basement-involved thrust blocks. Both anticlines are well-exposed and display extensive near-surface fracturing and faulting, making them ideal candidates for a study of fold-related lineament patterns. Google Earth Pro was used to map and measure the orientation of lineaments and faults in a digital format. The lineaments identified include a set parallel to dip (A–C), a set parallel to strike (B–C), and two sets oblique to strike. Lineament orientation data were analyzed using length-weighted rose diagrams, whereas fold geometry and plunge were evaluated using equal-area (lower hemisphere) stereonets. Although the study was limited in scope to a computer-based geometric analysis and did not include outcrop-based kinematic data, the lineament/fracture data derived from Google Earth mapping are nevertheless compatible with published studies that demonstrate regional NE-SW shortening along the western Owl Creek transpressive zone during the Laramide orogeny. Google Earth Pro proved to be a highly effective tool for gathering lineament orientation and spatial distribution data across these well-exposed anticlines.

A workflow for digital geological mapping, from fieldwork to multidimensional digital map, has been designed and tested in a sector of the Northern Apennines (Furlo Anticline). Using digital tools, a field mapping campaign was conducted after the organization of conceptual schemas for data capture, storage, and management. Once the data and schemas had been tested to enable a map to be drawn using GIS tools, they were almost ready to be imported into modeling tools for maps, sections, and 3D models. Moreover, we believe that web visualization and distribution using Google Earth is a further step in the direction of knowledge transfer to a greater number of people.