The Volcano Sensor Web (VSW) is a globe-spanning net of sensors and applications for detecting volcanic activity. Alerts from the VSW are used to trigger observations from space using the Earth Observing-1 (EO-1) spacecraft. Onboard EO-1 is the Autonomous Sciencecraft Experiment (ASE) advanced autonomy software. Using ASE has streamlined spacecraft operations and has enabled the rapid delivery of high-level products to end-users. The entire process, from initial alert to product delivery, is autonomous. This facility is of great value as a rapid response is vital during a volcanic crisis. ASE consists of three parts: (1) Science Data Classifiers, which process EO-1 Hyperion data to identify anomalous thermal signals; (2) a Spacecraft Command Language; and (3) the Continuous Activity Scheduling Planning Execution and Replanning (CASPER) software that plans and replans activities, including downlinks, based on available resources and operational constraints. For each eruption detected, thermal emission maps and estimates of eruption parameters are posted to a website at the Jet Propulsion Laboratory, California Institute of Technology, in Pasadena, CA. Selected products are emailed to end-users. The VSW uses software agents to detect volcanic activity alerts generated from a wide variety of sources on the ground and in space, and can also be easily triggered manually.

The HOTSAT multiplatform system for the analysis of infrared data from satellites provides a framework that allows the detection of volcanic hotspots and an output of their associated radiative power. This multiplatform system can operate on both Moderate Resolution Imaging Spectroradiometer and Spinning Enhanced Visible and Infrared Imager data. The new version of the system is now implemented on graphics processing units and its interface is available on the internet under restricted access conditions. Combining the estimation of time-varying discharge rates using HOTSAT with the MAGFLOW physics-based model to simulate lava flow paths resulted in the first operational system in which satellite observations drive the modelling of lava flow emplacement. This allows the timely definition of the parameters and maps essential for hazard assessment, including the propagation time of lava flows and the maximum run-out distance. The system was first used in an operational context during the paroxysmal episode at Mt Etna on 12–13 January 2011, when we produced real-time predictions of the areas likely to be inundated by lava flows while the eruption was still ongoing. This allowed key at-risk areas to be rapidly and appropriately identified.

DOWNFLOW is a probabilistic code for the simulation of the area covered by lava flows. This code has been used extensively for several basaltic volcanoes in the last decade, and a review of some applications is presented. DOWNFLOW is based on the simple principle that a lava flow tends to follow the steepest descent path downhill from the vent. DOWNFLOW computes the area possibly inundated by lava flows by deriving a number, N, of steepest descent paths, each path being calculated over a randomly perturbed topography. The perturbation is applied at each point of the topography, and ranges within the interval ±Δh. N and Δh are the two basic parameters of the code. The expected flow length is constrained by statistical weighting based on the past activity of the volcano. The strength of the code is that: (i) only limited volcanological knowledge is necessary to apply the code at a given volcano; (ii) there are only two (easily tunable) input parameters; and (iii) computational requirements are very low. However, DOWNFLOW does not provide the progression of the lava emplacement over time. The use of DOWNFLOW is ideal when a large number of simulations are necessary: for example, to compile maps for hazard and risk-assessment purposes.

FLOWGO is a one-dimensional model that tracks the thermorheological evolution of lava flowing down a channel. The model does not spread the lava but, instead, follows a control volume as it descends a line of steepest descent centred on the channel axis. The model basis is the Jeffreys equation for Newtonian flow, modified for a Bingham fluid, and a series of heat loss equations. Adjustable relationships are used to calculate cooling, crystallization and down-channel increases in viscosity and yield strength, as well as the resultant decrease in velocity. Here we provide a guide that allows FLOWGO to be set up in Excel. In doing so, we show how the model can be executed using a slope profile derived from Google™ Earth. Model simplicity and ease of source-term input from Google™ Earth means that this exercise allows (i) easy access to the model, (ii) quick, global application and (iii) use in a teaching role. Output is tested using measurements made for the 2010 eruption of Piton de la Fournaise (La Réunion Island). The model is also set up for rapid syneruptive hazard assessment at Piton de la Fournaise, as we show using the example of the response to the June 2014 eruption.

VolcFlow is a finite-difference Eulerian code based on the depth-averaged approach and developed for the simulation of isothermal geophysical flows. Its capability for reproducing lava flows is tested here for the first time. The field example chosen is the 2010 lava flow of Tungurahua volcano (Ecuador), the emplacement of which is tracked by projecting thermal images onto a georeferenced digital topography. Results show that, at least for this case study, the isothermal approach of VolcFlow is able to simulate the velocity of the lava through time, as well as the extent of the solidified lava. However, the good fit between the modelled and the natural flow may be explained by the short emplacement time (c. 20 h) of a thick lava (c. 5 m), which could limit the influence of cooling on the flow dynamics, thus favouring the use of an isothermal rheology.

The MAGFLOW model for lava-flow simulations is based on the cellular automaton (CA) approach, and uses a physical model for the thermal and rheological evolution of the flowing lava. We discuss the potential of MAGFLOW to improve our understanding of the dynamics of lava-flow emplacement and our ability to assess lava-flow hazards. Sensitivity analysis of the input parameters controlling the evolution function of the automaton demonstrates that water content and solidus temperatures are the parameters to which MAGFLOW is most sensitive. Additional tests also indicate that temporal changes in effusion rate strongly influence the accuracy of the predictive modelling of lava-flow paths. The parallel implementation of MAGFLOW on graphic processing units (GPUs) can achieve speed-ups of two orders of magnitude relative to the corresponding serial implementation, providing a lava-flow simulation spanning several days of eruption in just a few minutes. We describe and demonstrate the operation of MAGFLOW using two case studies from Mt Etna: one is a reconstruction of the detailed chronology of the lava-flow emplacement during the 2006 flank eruption; and the other is the production of the lava-flow hazard map of the persistent eruptive activity at the summit craters.

Understanding the magmatic processes that drive unrest at silicic calderas remains a major goal in Volcanology. Rabaul in Papua New Guinea is an exceptional location because after two decades of unrest and a peak in seismicity and deformation in 1983–85, eruptive activity began in 1994 and is still ongoing. A particularly large sub-Plinian eruption occurred from Tavurvur in October 2006. Whole-rock compositions are andesitic and reflect mixing/mingling between basaltic and dacitic magmas from the same system. The magmas that fed the 2006 eruption were stored at about 930°C, with 1–3 wt% H2O, 25–520 ppm CO2, and 50–2500 ppm SO2 in the melt. Melt inclusions hosted in pyroxene, and plagioclase phenocrysts record fractional crystallization at ≤200 MPa under relatively dry and poorly oxidizing conditions. Magma mixing/mingling is expressed as heterogeneous glass compositions, strongly zoned phenocrysts, and mafic crystal aggregates. A textural maturation from fine, acicular to large, blocky crystal clots implies different relative ages of formation. Modelling the chemical zoning of plagioclase shows that mafic–silicic interactions started a couple of decades prior to the 2006 eruption and continued until days to weeks prior to eruption. Basaltic replenishments have been driving unrest and eruption at the Rabaul caldera since the 1970s.Supplementary material:Tables and figures reporting the composition of the Tavurvur 2006, Kombiu and 1.4 ka BP caldera samples and showing thermodynamic modelling with MELTS are available at http://www.geolsoc.org.uk/SUP18816

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.

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.

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.

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.

Geologic maps and cross-sections effectively summarize the structural geology of a region, but they can be difficult for non-geologists to interpret. Textbooks and interpretive guides commonly integrate maps and cross-sections into static perspective block diagrams to help novices visualize basic concepts in geology. The inherent power of block diagrams, however, is dramatically increased by software such as Google SketchUp, a free downloadable program, which can create interactive 3-D models of a region. The stand-alone models can be Rotated, Panned, and Zoomed by the user and exported for animations. An efficient way to create block diagrams is to combine the individual strengths of dedicated GIS software with SketchUp, and merge the results into a single 3-D model. Effective 3-D block diagrams drape a geologic map on a digital elevation model and show how the map and cross-sections connect at the topographic surface. Creating block diagrams in such a way that portions of the map between cross-section planes are independent segments gives the user flexibility to make portions of the map invisible. By “turning off” parts of the surface, it is possible to sequentially reveal multiple cross-sections. 3-D block diagrams help students and non-specialists visualize geologic structures. Once created, the 3-D block diagrams can be quickly edited by substituting alternate images of geologic maps and cross-sections. Thus they provide an elegant approach for comparing different interpretations of a region. Combined with tools available in SketchUp, they also provide geologists with a valuable resource for assessing the geometric plausibility of geologic cross-sections.

The creation of new outcrops through construction is an important source of field data for geologists, especially in parts of the Appalachians with limited rock exposure. Users of Google Earth for field research often encounter disparities between the digital topography and the current-day Earth's surface, as newly formed outcrops may not be represented in the topography. Such is the case along sections of the I-26 corridor in Unicoi County, northeastern Tennessee. Twenty-four kilometers of U.S. 23 (future I-26) was widened to four lanes from Sams Gap at the North Carolina–Tennessee line to the Nolichucky River near Erwin, Tennessee, in the early 1990s. The series of outcrops created along the corridor provide an exceptional traverse through Grenvillian-age basement and cover strata which contain numerous stacked Alleghanian thrust sheets and shear zones. Near mile marker 44 along I-26, an ~250 m-long and 65 m-high outcrop was formed as part of the early 1990s construction. Google Earth satellite and Street View images show the outcrop, but the digital terrain in Google Earth does not reflect the approximate 150,000 m3 of rock removed to form this roadcut. To correct for this, terrain modifications were made with Sketch-Up by copying and virtually excavating the landscape. The SketchUp model was then imported into Google Earth to show the outcrop and interstate as it looks today, with the interstate passing uninterrupted through a ridge rather than draping over hilly topography. This technique can be applied to any area in Google Earth where a mismatch exists between real and virtual topography.

Utilizing 3D photorealistic outcrop models for research and education is becoming more and more common in industry and academia. A system is presented for annotating on preloaded distortion-free photos used for model construction while in front of a real outcrop or a virtual 3D model in the lab or classroom. This interaction is accomplished through tracing geologic boundaries, writing notes and recording locations using an applet on an iPad. These geologic tracings are sent to a PC where 3D geometric information is extracted with a provided MatLab program. Annotations on the photo can then be visualized on the 3D model because control points from the model building process link 2D pixels on the photo with the 3D mesh by six transformation coefficients. The MatLab Program separates meaningful geological information based on pixel value defined by geologists for further analysis (strike/dip, rock type, etc.). Therefore geological features can be attributed, annotated, quantitatively analyzed and visualized in 3D or 3D stereo with available software. The University of Texas at Dallas as well as other groups have been creating such 3D models with laser scanning, GNSS (Global Navigation Satellite Systems) and digital photography since 1998. This approach can be used on any photorealistic model built based on the transformation correlation between imagery and 3D geometry. The website www.utdallas.edu/iGeology provides access to several such models of road cuts across the Arbuckle Anticline, Oklahoma. An instructor or project leader can access and set up the environment for students or users. This is not a field geologic logging/mapping system but is designed for interacting with and extracting quantitative from existing virtual models for research and education. Computations taking place on the PC are transparent to the user, and therefore the system can be readily used in academia and industry at many different levels of expertise. The tablet's portability enables users to interact with the outcrop in the field or with a 3D display in the lab. Similar applications can be built on android tablets. The system is provided in detail in three appendices.