Google Earth Engine

NASA Astrophysics Data System (ADS)

Gorelick, N.

2012-12-01

The Google Earth Engine platform is a system designed to enable petabyte-scale, scientific analysis and visualization of geospatial datasets. Earth Engine provides a consolidated environment including a massive data catalog co-located with thousands of computers for analysis. The user-friendly front-end provides a workbench environment to allow interactive data and algorithm development and exploration and provides a convenient mechanism for scientists to share data, visualizations and analytic algorithms via URLs. The Earth Engine data catalog contains a wide variety of popular, curated datasets, including the world's largest online collection of Landsat scenes (> 2.0M), numerous MODIS collections, and many vector-based data sets. The platform provides a uniform access mechanism to a variety of data types, independent of their bands, projection, bit-depth, resolution, etc..., facilitating easy multi-sensor analysis. Additionally, a user is able to add and curate their own data and collections. Using a just-in-time, distributed computation model, Earth Engine can rapidly process enormous quantities of geo-spatial data. All computation is performed lazily; nothing is computed until it's required either for output or as input to another step. This model allows real-time feedback and preview during algorithm development, supporting a rapid algorithm development, test, and improvement cycle that scales seamlessly to large-scale production data processing. Through integration with a variety of other services, Earth Engine is able to bring to bear considerable analytic and technical firepower in a transparent fashion, including: AI-based classification via integration with Google's machine learning infrastructure, publishing and distribution at Google scale through integration with the Google Maps API, Maps Engine and Google Earth, and support for in-the-field activities such as validation, ground-truthing, crowd-sourcing and citizen science though the Android Open Data Kit.

[Establishment of Oncomelania hupensis snail database based on smartphone and Google Earth].

PubMed

Wang, Wei-chun; Zhan, Ti; Zhu, Ying-fu

2015-02-01

To establish an Oncomelania hupensis snail database based on smartphone and Google Earth. The HEAD GPS software was loaded in the smartphone first. The GPS data of the snails were collected by the smartphone. The original data were exported to the computer with the format of KMIUKMZ. Then the data were converted into Excel file format by using some software. Finally, the results based on laboratory were filled, and the digital snail data were established. The data were converted into KML, and then were showed by Google Earth visually. The snail data of a 5 hm2-beach along the Yangtze River were collected and the distribution of the snails based on Google Earth was obtained. The database of the snails was built. The query function was implemented about the number of the total snails, the living snails and the schistosome infected snails of each survey frame. The digital management of the snail data is realized by using the smartphone and Google Earth.

Google Sky: A Digital View of the Night Sky

NASA Astrophysics Data System (ADS)

Connolly, A. Scranton, R.; Ornduff, T.

2008-11-01

From its inception Astronomy has been a visual science, from careful observations of the sky using the naked eye, to the use of telescopes and photographs to map the distribution of stars and galaxies, to the current era of digital cameras that can image the sky over many decades of the electromagnetic spectrum. Sky in Google Earth (http://earth.google.com) and Google Sky (http://www.google.com/sky) continue this tradition, providing an intuitive visual interface to some of the largest astronomical imaging surveys of the sky. Streaming multi-color imagery, catalogs, time domain data, as well as annotating interesting astronomical sources and events with placemarks, podcasts and videos, Sky provides a panchromatic view of the universe accessible to anyone with a computer. Beyond a simple exploration of the sky Google Sky enables users to create and share content with others around the world. With an open interface available on Linux, Mac OS X and Windows, and translations of the content into over 20 different languages we present Sky as the embodiment of a virtual telescope for discovery and sharing the excitement of astronomy and science as a whole.

Development of a Carbon Sequestration Visualization Tool using Google Earth Pro

NASA Astrophysics Data System (ADS)

Keating, G. N.; Greene, M. K.

2008-12-01

The Big Sky Carbon Sequestration Partnership seeks to prepare organizations throughout the western United States for a possible carbon-constrained economy. Through the development of CO2 capture and subsurface sequestration technology, the Partnership is working to enable the region to cleanly utilize its abundant fossil energy resources. The intent of the Los Alamos National Laboratory Big Sky Visualization tool is to allow geochemists, geologists, geophysicists, project managers, and other project members to view, identify, and query the data collected from CO2 injection tests using a single data source platform, a mission to which Google Earth Pro is uniquely and ideally suited . The visualization framework enables fusion of data from disparate sources and allows investigators to fully explore spatial and temporal trends in CO2 fate and transport within a reservoir. 3-D subsurface wells are projected above ground in Google Earth as the KML anchor points for the presentation of various surface subsurface data. This solution is the most integrative and cost-effective possible for the variety of users in the Big Sky community.

Getting Your GIS Data into Google Earth: Data Conversion Tools and Tips

NASA Astrophysics Data System (ADS)

Nurik, R.; Marks, M.

2009-12-01

Google Earth is a powerful platform for displaying your data. You can easily visualize content using the Keyhole Markup Language (KML). But what if you don't have your data in KML format? GIS data comes in a wide variety of formats, including .shp files, CSV, and many others. What can you do? This session will walk you through some of the tools for converting data to KML format. We will explore a variety of tools, including: Google Earth Pro, GDAL/OGR, KML2KML, etc. This session will be paced so that you can follow along on your laptop if you wish. Should you want to follow along, bring a laptop, and install the trial versions of Google Earth Pro and KML2KML. It is also recommended that you download GDAL from gdal.org and install it on your system.

Interfaces Visualize Data for Airline Safety, Efficiency

NASA Technical Reports Server (NTRS)

2014-01-01

As the A-Train Constellation orbits Earth to gather data, NASA scientists and partners visualize, analyze, and communicate the information. To this end, Langley Research Center awarded SBIR funding to Fairfax, Virginia-based WxAnalyst Ltd. to refine the company's existing user interface for Google Earth to visualize data. Hawaiian Airlines is now using the technology to help manage its flights.

Leveraging Earth and Planetary Datasets to Support Student Investigations in an Introductory Geoscience Course

NASA Astrophysics Data System (ADS)

Ryan, Jeffrey; De Paor, Declan

2016-04-01

Engaging undergraduates in discovery-based research during their first two years of college was a listed priority in the 2012 Report of the USA President's Council of Advisors on Science and Technology (PCAST), and has been the focus of events and publications sponsored by the National Academies (NAS, 2015). Challenges faced in moving undergraduate courses and curricula in this direction are the paired questions of how to effectively provide such experiences to large numbers of students, and how to do so in ways that are cost- and time-effiicient for institutions and instructional faculty. In the geosciences, free access to of a growing number of global earth and planetary data resources and associated visualization tools permits one to build into introductory-level courses straightforward data interrogation and analysis activities that provide students with valuable experiences with the compilation and critical investigation of earth and planetary data. Google Earth provides global Earth and planetary imagery databases that span large ranges in resolution and in time, permitting easy examination of earth surface features and surface features on Mars or the Moon. As well, "community" data sources (i.e., Gigapan photographic collections and 3D visualizations of geologic features, as are supported by the NSF GEODE project) allow for intensive interrogation of specific geologic phenomena. Google Earth Engine provides access to rich satellite-based earth observation data, supporting studies of weather and related student efforts. GeoMapApp, the freely available visualization tool of the Interdisciplinary Earth Data Alliance (IEDA), permits examination of the seafloor and the integration of a range of third-party data. The "Earth" meteorological website (earth.nullschool.net) provides near real-time visualization of global weather and oceanic conditions, which in combination with weather option data from Google Earth permits a deeper interrogation of atmospheric conditions. In combination, these freely accessible data resources permit one to transform general- audience geoscience courses into extended investigations, in which students discover key information about the workings of our planet.

How Would You Move Mount Fuji - And Why Would You Want To?

NASA Astrophysics Data System (ADS)

de Paor, D. G.

2008-12-01

According to author William Poundstone, "How Would You Move Mt Fuji?" typifies the kind of question that corporations such as Microsoft are wont to ask job applicants in order to test their lateral thinking skills. One answer (albeit not one that would necessarily secure a job at Microsoft) is: "With Google Earth and a Macintosh or PC." The answer to the more profound follow-up question "Why Would You Want To?" is hinted at by one of the great quotations of earth science, namely Charles Lyell's proposition that "The Present Is Key to the Past." Google Earth is a phenomenally powerful tool for visualizing today's earth, ocean, and atmosphere. With the aid of Google SketchUp, that visualization can be extended to reconstruct the past using relocated samples of present-day landscapes and environments as models of paleo-DEM and paleogeography. Volcanoes are particularly useful models because their self similar growth can be simulated by changing KML altitude tags within a timespan, but numerous other landforms and geologic structures serve as useful keys to the past. Examples range in scale from glaciers and fault scarps to island arcs and mountain ranges. The ability to generate a paleo-terrain model in Google Earth brings us one step closer to a truly four- dimensional, interactive geological map of the world throughout time.

State of the Oceans: A Satellite Data Processing System for Visualizing Near Real-Time Imagery on Google Earth

NASA Astrophysics Data System (ADS)

Thompson, C. K.; Bingham, A. W.; Hall, J. R.; Alarcon, C.; Plesea, L.; Henderson, M. L.; Levoe, S.

2011-12-01

The State of the Oceans (SOTO) web tool was developed at NASA's Physical Oceanography Distributed Active Archive Center (PO.DAAC) at the Jet Propulsion Laboratory (JPL) as an interactive means for users to visually explore and assess ocean-based geophysical parameters extracted from the latest archived data products. The SOTO system consists of four extensible modules, a data polling tool, a preparation and imaging package, image server software, and the graphical user interface. Together, these components support multi-resolution visualization of swath (Level 2) and gridded Level 3/4) data products as either raster- or vector- based KML layers on Google Earth. These layers are automatically updated periodically throughout the day. Current parameters available include sea surface temperature, chlorophyll concentration, ocean winds, sea surface height anomaly, and sea surface temperature anomaly. SOTO also supports mash-ups, allowing KML feeds from other sources to be overlaid directly onto Google Earth such as hurricane tracks and buoy data. A version of the SOTO software has also been installed at Goddard Space Flight Center (GSFC) to support the Land Atmosphere Near real-time Capability for EOS (LANCE). The State of the Earth (SOTE) has similar functionality to SOTO but supports different data sets, among them the MODIS 250m data product.

Spatiotemporal Visualization of Tsunami Waves Using Kml on Google Earth

NASA Astrophysics Data System (ADS)

Mohammadi, H.; Delavar, M. R.; Sharifi, M. A.; Pirooz, M. D.

2017-09-01

Disaster risk is a function of hazard and vulnerability. Risk is defined as the expected losses, including lives, personal injuries, property damages, and economic disruptions, due to a particular hazard for a given area and time period. Risk assessment is one of the key elements of a natural disaster management strategy as it allows for better disaster mitigation and preparation. It provides input for informed decision making, and increases risk awareness among decision makers and other stakeholders. Virtual globes such as Google Earth can be used as a visualization tool. Proper spatiotemporal graphical representations of the concerned risk significantly reduces the amount of effort to visualize the impact of the risk and improves the efficiency of the decision-making process to mitigate the impact of the risk. The spatiotemporal visualization of tsunami waves for disaster management process is an attractive topic in geosciences to assist investigation of areas at tsunami risk. In this paper, a method for coupling virtual globes with tsunami wave arrival time models is presented. In this process we have shown 2D+Time of tsunami waves for propagation and inundation of tsunami waves, both coastal line deformation, and the flooded areas. In addition, the worst case scenario of tsunami on Chabahar port derived from tsunami modelling is also presented using KML on google earth.

Wind Wake Watcher v. 1.0

DOE Office of Scientific and Technical Information (OSTI.GOV)

Martin, Shawn

This software enables the user to produce Google Earth visualizations of turbine wake effects for wind farms. The visualizations are based on computations of statistical quantities that vary with wind direction and help quantify the effects on power production of upwind turbines on turbines in their wakes. The results of the software are plot images and kml files that can be loaded into Google Earth. The statistics computed are described in greater detail in the paper: S. Martin, C. H. Westergaard, and J. White (2016), Visualizing Wind Farm Wakes Using SCADA Data, in Wither Turbulence and Big Data in themore » 21st Century? Eds. A. Pollard, L. Castillo, L. Danaila, and M. Glauser. Springer, pgs. 231-254.« less

Earth Adventure: Virtual Globe-based Suborbital Atmospheric Greenhouse Gases Exploration

NASA Astrophysics Data System (ADS)

Wei, Y.; Landolt, K.; Boyer, A.; Santhana Vannan, S. K.; Wei, Z.; Wang, E.

2016-12-01

The Earth Venture Suborbital (EVS) mission is an important component of NASA's Earth System Science Pathfinder program that aims at making substantial advances in Earth system science through measurements from suborbital platforms and modeling researches. For example, the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) project of EVS-1 collected measurements of greenhouse gases (GHG) on local to regional scales in the Alaskan Arctic. The Atmospheric Carbon and Transport - America (ACT-America) project of EVS-2 will provide advanced, high-resolution measurements of atmospheric profiles and horizontal gradients of CO2 and CH4.As the long-term archival center for CARVE and the future ACT-America data, the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC) has been developing a versatile data management system for CARVE data to maximize their usability. One of these efforts is the virtual globe-based Suborbital Atmospheric GHG Exploration application. It leverages Google Earth to simulate the 185 flights flew by the C-23 Sherpa aircraft in 2012-2015 for the CARVE project. Based on Google Earth's 3D modeling capability and the precise coordinates, altitude, pitch, roll, and heading info of the aircraft recorded in every second during each flight, the application provides users accurate and vivid simulation of flight experiences, with an active 3D visualization of a C-23 Sherpa aircraft in view. This application provides dynamic visualization of GHG, including CO2, CO, H2O, and CH4 captured during the flights, at the same pace of the flight simulation in Google Earth. Photos taken during those flights are also properly displayed along the flight paths. In the future, this application will be extended to incorporate more complicated GHG measurements (e.g. vertical profiles) from the ACT-America project. This application leverages virtual globe technology to provide users an integrated framework to interactively explore information about GHG measurements and to link scientific measurements to the rich virtual planet environment provided by Google Earth. Positive feedbacks have been received from users. It provides a good example of extending basic data visualization into a knowledge discovery experience and maximizing the usability of Earth science observations.

Visualizing spatio-temporal war casualty data in Google Earth - A case study of Map the Fallen (Invited)

NASA Astrophysics Data System (ADS)

Askay, S.

2009-12-01

Published on Memorial Day 2009, Map the Fallen is a Google Earth visualization of the 5500+ US and international soldiers that have died in Iraq and Afghanistan since 2001. In addition to providing photos, stories and links for each solider, the time-animated map visually connects hometowns to places of death. This novel way of representing casualty data brings the geographic reach and magnitude of the issue into focus together with the very personal nature of individual stories. Innovative visualizations techniques were used that illustrate the spatio-temporal nature of this information and to show the global reach and interconnectivity of this issue. Several of advanced KML techniques employed to create this engaging and performance-conscious map will be discussed during this session. These include: 1) the use of HTML iframes and javascript to minimize the KML size, and extensive cross-linking throughout content; 2) the creation of a time-animated, on-screen casualty counter; 3) the use of parabolic arcs to connect each hometown to place of death; 4) the use of concentric spirals to represent chronological data; and 5) numerous performance optimizations to ensure the 23K placemarks, 2500 screen overlays and nearly 250k line vertices performed well in Google Earth. This session will include a demonstration of the map, conceptual discussions of the techniques used, and some in-depth technical explanation of the KML code.

Flying across Galaxy Clusters with Google Earth: additional imagery from SDSS co-added data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hao, Jiangang; Annis, James; /Fermilab

2010-10-01

Galaxy clusters are spectacular. We provide a Google Earth compatible imagery for the deep co-added images from the Sloan Digital Sky Survey and make it a tool for examing galaxy clusters. Google Earth (in sky mode) provides a highly interactive environment for visualizing the sky. By encoding the galaxy cluster information into a kml/kmz file, one can use Google Earth as a tool for examining galaxy clusters and fly across them freely. However, the resolution of the images provided by Google Earth is not very high. This is partially because the major imagery google earth used is from Sloan Digitalmore » Sky Survey (SDSS) (SDSS collaboration 2000) and the resolutions have been reduced to speed up the web transferring. To have higher resolution images, you need to add your own images in a way that Google Earth can understand. The SDSS co-added data are the co-addition of {approx}100 scans of images from SDSS stripe 82 (Annis et al. 2010). It provides the deepest images based on SDSS and reach as deep as about redshift 1.0. Based on the co-added images, we created color images in a way as described by Lupton et al. (2004) and convert the color images to Google Earth compatible images using wcs2kml (Brewer et al. 2007). The images are stored at a public server at Fermi National Accelerator Laboratory and can be accessed by the public. To view those images in Google Earth, you need to download a kmz file, which contains the links to the color images, and then open the kmz file with your Google Earth. To meet different needs for resolutions, we provide three kmz files corresponding to low, medium and high resolution images. We recommend the high resolution one as long as you have a broadband Internet connection, though you should choose to download any of them, depending on your own needs and Internet speed. After you open the downloaded kmz file with Google Earth (in sky mode), it takes about 5 minutes (depending on your Internet connection and the resolution of images you want) to get some initial images loaded. Then, additional images corresponding to the region you are browsing will be loaded automatically. So far, you have access to all the co-added images. But you still do not have the galaxy cluster position information to look at. In order to see the galaxy clusters, you need to download another kmz file that tell Google Earth where to find the galaxy clusters in the co-added data region. We provide a kmz file for a few galaxy clusters in the stripe 82 region and you can download and open it with Google Earth. In the SDSS co-added region (stripe 82 region), the imagery from Google Earth itself is from the Digitized Sky Survey (2007), which is in very poor quality. In Figure1 and Figure2, we show screenshots of a cluster with and without the new co-added imagery in Google Earth. Much more details have been revealed with the deep images.« less

Integration of Geophysical and Geochemical Data

NASA Astrophysics Data System (ADS)

Yamagishi, Y.; Suzuki, K.; Tamura, H.; Nagao, H.; Yanaka, H.; Tsuboi, S.

2006-12-01

Integration of geochemical and geophysical data would give us a new insight to the nature of the Earth. It should advance our understanding for the dynamics of the Earth's interior and surface processes. Today various geochemical and geophysical data are available on Internet. These data are stored in various database systems. Each system is isolated and provides own format data. The goal of this study is to display both the geochemical and geophysical data obtained from such databases together visually. We adopt Google Earth as the presentation tool. Google Earth is virtual globe software and is provided free of charge by Google, Inc. Google Earth displays the Earth's surface using satellite images with mean resolution of ~15m. We display any graphical features on Google Earth by KML format file. We have developed softwares to convert geochemical and geophysical data to KML file. First of all, we tried to overlay data from Georoc and PetDB and seismic tomography data on Google Earth. Georoc and PetDB are both online database systems for geochemical data. The data format of Georoc is CSV and that of PetDB is Microsoft Excel. The format of tomography data we used is plain text. The conversion software can process these different file formats. The geochemical data (e. g. compositional abundance) is displayed as a three-dimensional column on the Earth's surface. The shape and color of the column mean the element type. The size and color tone vary according to the abundance of the element. The tomography data can be converted into a KML file for each depth. This overlay plot of geochemical data and tomography data should help us to correlate internal temperature anomalies to geochemical anomalies, which are observed at the surface of the Earth. Our tool can convert any geophysical and geochemical data to a KML as long as the data is associated with longitude and latitude. We are going to support more geophysical data formats. In addition, we are currently trying to obtain scientific insights for the Earth's interior based on the view of both geophysical and geochemical data on Google Earth.

Learning GIS and exploring geolocated data with the all-in-one Geolokit toolbox for Google Earth

NASA Astrophysics Data System (ADS)

Watlet, A.; Triantafyllou, A.; Bastin, C.

2016-12-01

GIS software are today's essential tools to gather and visualize geological data, to apply spatial and temporal analysis and finally, to create and share interactive maps for further investigations in geosciences. Such skills are especially essential to learn for students who go through fieldtrips, samples collections or field experiments. However, time is generally missing to teach in detail all the aspects of visualizing geolocated geoscientific data. For these purposes, we developed Geolokit: a lightweight freeware dedicated to geodata visualization and written in Python, a high-level, cross-platform programming language. Geolokit software is accessible through a graphical user interface, designed to run in parallel with Google Earth, benefitting from the numerous interactive capabilities. It is designed as a very user-friendly toolbox that allows `geo-users' to import their raw data (e.g. GPS, sample locations, structural data, field pictures, maps), to use fast data analysis tools and to visualize these into the Google Earth environment using KML code; with no require of third party software, except Google Earth itself. Geolokit comes with a large number of geosciences labels, symbols, colours and placemarks and is applicable to display several types of geolocated data, including: Multi-points datasets Automatically computed contours of multi-points datasets via several interpolation methods Discrete planar and linear structural geology data in 2D or 3D supporting large range of structures input format Clustered stereonets and rose diagrams 2D cross-sections as vertical sections Georeferenced maps and grids with user defined coordinates Field pictures using either geo-tracking metadata from a camera built-in GPS module, or the same-day track of an external GPS In the end, Geolokit is helpful for quickly visualizing and exploring data without losing too much time in the numerous capabilities of GIS software suites. We are looking for students and teachers to discover all the functionalities of Geolokit. As this project is under development and planned to be open source, we are definitely looking to discussions regarding particular needs or ideas, and to contributions in the Geolokit project.

Graphical overview and navigation of electronic health records in a prototyping environment using Google Earth and openEHR archetypes.

PubMed

Sundvall, Erik; Nyström, Mikael; Forss, Mattias; Chen, Rong; Petersson, Håkan; Ahlfeldt, Hans

2007-01-01

This paper describes selected earlier approaches to graphically relating events to each other and to time; some new combinations are also suggested. These are then combined into a unified prototyping environment for visualization and navigation of electronic health records. Google Earth (GE) is used for handling display and interaction of clinical information stored using openEHR data structures and 'archetypes'. The strength of the approach comes from GE's sophisticated handling of detail levels, from coarse overviews to fine-grained details that has been combined with linear, polar and region-based views of clinical events related to time. The system should be easy to learn since all the visualization styles can use the same navigation. The structured and multifaceted approach to handling time that is possible with archetyped openEHR data lends itself well to visualizing and integration with openEHR components is provided in the environment.

Case study of visualizing global user download patterns using Google Earth and NASA World Wind

NASA Astrophysics Data System (ADS)

Zong, Ziliang; Job, Joshua; Zhang, Xuesong; Nijim, Mais; Qin, Xiao

2012-01-01

Geo-visualization is significantly changing the way we view spatial data and discover information. On the one hand, a large number of spatial data are generated every day. On the other hand, these data are not well utilized due to the lack of free and easily used data-visualization tools. This becomes even worse when most of the spatial data remains in the form of plain text such as log files. This paper describes a way of visualizing massive plain-text spatial data at no cost by utilizing Google Earth and NASA World Wind. We illustrate our methods by visualizing over 170,000 global download requests for satellite images maintained by the Earth Resources Observation and Science (EROS) Center of U.S. Geological Survey (USGS). Our visualization results identify the most popular satellite images around the world and discover the global user download patterns. The benefits of this research are: 1. assisting in improving the satellite image downloading services provided by USGS, and 2. providing a proxy for analyzing the "hot spot" areas of research. Most importantly, our methods demonstrate an easy way to geo-visualize massive textual spatial data, which is highly applicable to mining spatially referenced data and information on a wide variety of research domains (e.g., hydrology, agriculture, atmospheric science, natural hazard, and global climate change).

3D Visualization of near real-time remote-sensing observation for hurricanes field campaign using Google Earth API

NASA Astrophysics Data System (ADS)

Li, P.; Turk, J.; Vu, Q.; Knosp, B.; Hristova-Veleva, S. M.; Lambrigtsen, B.; Poulsen, W. L.; Licata, S.

2009-12-01

NASA is planning a new field experiment, the Genesis and Rapid Intensification Processes (GRIP), in the summer of 2010 to better understand how tropical storms form and develop into major hurricanes. The DC-8 aircraft and the Global Hawk Unmanned Airborne System (UAS) will be deployed loaded with instruments for measurements including lightning, temperature, 3D wind, precipitation, liquid and ice water contents, aerosol and cloud profiles. During the field campaign, both the spaceborne and the airborne observations will be collected in real-time and integrated with the hurricane forecast models. This observation-model integration will help the campaign achieve its science goals by allowing team members to effectively plan the mission with current forecasts. To support the GRIP experiment, JPL developed a website for interactive visualization of all related remote-sensing observations in the GRIP’s geographical domain using the new Google Earth API. All the observations are collected in near real-time (NRT) with 2 to 5 hour latency. The observations include a 1KM blended Sea Surface Temperature (SST) map from GHRSST L2P products; 6-hour composite images of GOES IR; stability indices, temperature and vapor profiles from AIRS and AMSU-B; microwave brightness temperature and rain index maps from AMSR-E, SSMI and TRMM-TMI; ocean surface wind vectors, vorticity and divergence of the wind from QuikSCAT; the 3D precipitation structure from TRMM-PR and vertical profiles of cloud and precipitation from CloudSAT. All the NRT observations are collected from the data centers and science facilities at NASA and NOAA, subsetted, re-projected, and composited into hourly or daily data products depending on the frequency of the observation. The data products are then displayed on the 3D Google Earth plug-in at the JPL Tropical Cyclone Information System (TCIS) website. The data products offered by the TCIS in the Google Earth display include image overlays, wind vectors, clickable placemarks with vertical profiles for temperature and water vapors and curtain plots along the satellite tracks. Multiple products can be overlaid with individual adjustable opacity control. The time sequence visualization is supported by calendar and Google Earth time animation. The work described here was performed at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.

An overview of the web-based Google Earth coincident imaging tool

USGS Publications Warehouse

Chander, Gyanesh; Kilough, B.; Gowda, S.

2010-01-01

The Committee on Earth Observing Satellites (CEOS) Visualization Environment (COVE) tool is a browser-based application that leverages Google Earth web to display satellite sensor coverage areas. The analysis tool can also be used to identify near simultaneous surface observation locations for two or more satellites. The National Aeronautics and Space Administration (NASA) CEOS System Engineering Office (SEO) worked with the CEOS Working Group on Calibration and Validation (WGCV) to develop the COVE tool. The CEOS member organizations are currently operating and planning hundreds of Earth Observation (EO) satellites. Standard cross-comparison exercises between multiple sensors to compare near-simultaneous surface observations and to identify corresponding image pairs are time-consuming and labor-intensive. COVE is a suite of tools that have been developed to make such tasks easier.

Google Earth-Based Grand Tours of the World's Ocean Basins and Marine Sediments

NASA Astrophysics Data System (ADS)

St John, K. K.; De Paor, D. G.; Suranovic, B.; Robinson, C.; Firth, J. V.; Rand, C.

2016-12-01

The GEODE project has produced a collection of Google Earth-based marine geology teaching resources that offer grand tours of the world's ocean basins and marine sediments. We use a map of oceanic crustal ages from Müller et al (2008; doi:10.1029/2007GC001743), and a set of emergent COLLADA models of IODP drill core data as a basis for a Google Earth tour introducing students to the world's ocean basins. Most students are familiar with basic seafloor spreading patterns but teaching experience suggests that few students have an appreciation of the number of abandoned ocean basins on Earth. Students also lack a valid visualization of the west Pacific where the oldest crust forms an isolated triangular patch and the ocean floor becomes younger towards the subduction zones. Our tour links geographic locations to mechanical models of rifting, seafloor spreading, subduction, and transform faulting. Google Earth's built-in earthquake and volcano data are related to ocean floor patterns. Marine sediments are explored in a Google Earth tour that draws on exemplary IODP core samples of a range of sediment types (e.g., turbidites, diatom ooze). Information and links are used to connect location to sediment type. This tour compliments a physical core kit of core catcher sections that can be employed for classroom instruction (geode.net/marine-core-kit/). At a larger scale, we use data from IMLGS to explore the distribution of the marine sediments types in the modern global ocean. More than 2,500 sites are plotted with access to original data. Students are guided to compare modern "type sections" of primary marine sediment lithologies, as well as examine site transects to address questions of bathymetric setting, ocean circulation, chemistry (e.g., CCD), and bioproductivity as influences on modern seafloor sedimentation. KMZ files, student exercises, and tips for instructors are available at geode.net/exploring-marine-sediments-using-google-earth.

Measuring the Carolina Bays Using Archetype Template Overlays on the Google Earth Virtual Globe; Planform Metrics for 25,000 Bays Extracted from LiDAR and Satellite Imagery

NASA Astrophysics Data System (ADS)

Davias, M. E.; Gilbride, J. L.

2011-12-01

Aerial photographs of Carolina bays taken in the 1930's sparked the initial research into their geomorphology. Satellite Imagery available today through the Google Earth Virtual Globe facility expands the regions available for interrogation, but reveal only part of their unique planforms. Digital Elevation Maps (DEMs), using Light Detection And Ranging (LiDAR) remote sensing data, accentuate the visual presentation of these aligned ovoid shallow basins by emphasizing their robust circumpheral rims. To support a geospatial survey of Carolina bay landforms in the continental USA, 400,000 km2 of hsv-shaded DEMs were created as KML-JPEG tile sets. A majority of these DEMs were generated with LiDAR-derived data. We demonstrate the tile generation process and their integration into Google Earth, where the DEMs augment available photographic imagery for the visualization of bay planforms. While the generic Carolina bay planform is considered oval, we document subtle regional variations. Using a small set of empirically derived planform shapes, we created corresponding Google Earth overlay templates. We demonstrate the analysis of an individual Carolina bay by placing an appropriate overlay onto the virtually globe, then orientating, sizing and rotating it by edit handles such that it satisfactorily represents the bay's rim. The resulting overlay data element is extracted from Google Earth's object directory and programmatically processed to generate metrics such as geographic location, elevation, major and minor axis and inferred orientation. Utilizing a virtual globe facility for data capture may result in higher quality data compared to methods that reference flat maps, where geospatial shape and orientation of the bays could be skewed and distorted in the orthographic projection process. Using the methodology described, we have measured over 25k distinct Carolina bays. We discuss the Google Fusion geospatial data repository facility, through which these data have been assembled and made web-accessible to other researchers. Preliminary findings from the survey are discussed, such as how bay surface area, eccentricity and orientation vary across ~800 1/4° × 1/4° grid elements. Future work includes measuring 25k additional bays, as well as interrogation of the orientation data to identify any possible systematic geospatial relationships.

Utilization of Google Earth for Distribution Mapping of Cholangiocarcinoma: a Case Study in Satuek District, Buriram, Thailand.

PubMed

Rattanasing, Wannaporn; Kaewpitoon, Soraya J; Loyd, Ryan A; Rujirakul, Ratana; Yodkaw, Eakachai; Kaewpitoon, Natthawut

2015-01-01

Cholangiocarcinoma (CCA) is a serious public health problem in the Northeast of Thailand. CCA is considered to be an incurable and rapidly lethal disease. Knowledge of the distribution of CCA patients is necessary for management strategies. This study aimed to utilize the Geographic Information System and Google EarthTM for distribution mapping of cholangiocarcinoma in Satuek District, Buriram, Thailand, during a 5-year period (2008-2012). In this retrospective study data were collected and reviewed from the OPD cards, definitive cases of CCA were patients who were treated in Satuek hospital and were diagnosed with CCA or ICD-10 code C22.1. CCA cases were used to analyze and calculate with ArcGIS 9.2, all of data were imported into Google Earth using the online web page www.earthpoint.us. Data were displayed at village points. A total of 53 cases were diagnosed and identified as CCA. The incidence was 53.57 per 100,000 population (65.5 for males and 30.8 for females) and the majority of CCA cases were in stages IV and IIA. The average age was 67 years old. The highest attack rate was observed in Thung Wang sub-district (161.4 per 100,000 population). The map display at village points for CCA patients based on Google Earth gave a clear visual deistribution. CCA is still a major problem in Satuek district, Buriram province of Thailand. The Google Earth production process is very simple and easy to learn. It is suitable for the use in further development of CCA management strategies.

Sally Ride EarthKAM - Automated Image Geo-Referencing Using Google Earth Web Plug-In

NASA Technical Reports Server (NTRS)

Andres, Paul M.; Lazar, Dennis K.; Thames, Robert Q.

2013-01-01

Sally Ride EarthKAM is an educational program funded by NASA that aims to provide the public the ability to picture Earth from the perspective of the International Space Station (ISS). A computer-controlled camera is mounted on the ISS in a nadir-pointing window; however, timing limitations in the system cause inaccurate positional metadata. Manually correcting images within an orbit allows the positional metadata to be improved using mathematical regressions. The manual correction process is time-consuming and thus, unfeasible for a large number of images. The standard Google Earth program allows for the importing of KML (keyhole markup language) files that previously were created. These KML file-based overlays could then be manually manipulated as image overlays, saved, and then uploaded to the project server where they are parsed and the metadata in the database is updated. The new interface eliminates the need to save, download, open, re-save, and upload the KML files. Everything is processed on the Web, and all manipulations go directly into the database. Administrators also have the control to discard any single correction that was made and validate a correction. This program streamlines a process that previously required several critical steps and was probably too complex for the average user to complete successfully. The new process is theoretically simple enough for members of the public to make use of and contribute to the success of the Sally Ride EarthKAM project. Using the Google Earth Web plug-in, EarthKAM images, and associated metadata, this software allows users to interactively manipulate an EarthKAM image overlay, and update and improve the associated metadata. The Web interface uses the Google Earth JavaScript API along with PHP-PostgreSQL to present the user the same interface capabilities without leaving the Web. The simpler graphical user interface will allow the public to participate directly and meaningfully with EarthKAM. The use of similar techniques is being investigated to place ground-based observations in a Google Mars environment, allowing the MSL (Mars Science Laboratory) Science Team a means to visualize the rover and its environment.

Wallace Creek Virtual Field Trip: Teaching Geoscience Concepts with LiDAR

NASA Astrophysics Data System (ADS)

Robinson, S. E.; Arrowsmith, R.; Crosby, C. J.

2009-12-01

Recently available data such as LiDAR (Light Detection and Ranging) high-resolution topography can assist students to better visualize and understand geosciences concepts. It is important to bring these data into geosciences curricula as teaching aids while ensuring that the visualization tools, virtual environments, etc. do not serve as barriers to student learning. As a Southern California Earthquake Center ACCESS-G intern, I am creating a “virtual field trip” to Wallace Creek along the San Andreas Fault (SAF) using Google Earth as a platform and the B4 project LiDAR data. Wallace Creek is an excellent site for understanding the centennial-to-millennial record of SAF slip because of its dramatic stream offsets. Using the LiDAR data instead of, or alongside, traditional visualizations and teaching methods enhances a student’s ability to understand plate tectonics, the earthquake cycle, strike-slip faults, and geomorphology. Viewing a high-resolution representation of the topography in Google Earth allows students to analyze the landscape and answer questions about the behavior of the San Andreas Fault. The activity guides students along the fault allowing them to measure channel offsets using the Google Earth measuring tool. Knowing the ages of channels, they calculate slip rate. They look for the smallest channel offsets around Wallace Creek in order to determine the slip per event. At both a “LiDAR and Education” workshop and the Cyberinfrastructure Summer Institute for Geoscientists (CSIG), I presented the Wallace Creek activity to high school and college earth science teachers. The teachers were positive in their responses and had numerous important suggestions including the need for a teacher’s manual for instruction and scientific background, and that the student goals and science topics should be specific and well-articulated for the sake of both the teacher and the student. The teachers also noted that the technology in classrooms varies significantly. Some do not have computers available for students or do not have access to the internet or certain software licenses. For this reason, I am also creating a paper-based version of the same exercise. After a usable activity is developed I plan to make it available online through the OpenTopography portal (www.opentopography.com) using a format similar to the online teaching boxes seen at DLESE (www.dlese.org). The final version will facilitate visual student learning through the popular Google Earth platform along with student guides and a teacher’s manual.

Climate Engine - Monitoring Drought with Google Earth Engine

NASA Astrophysics Data System (ADS)

Hegewisch, K.; Daudert, B.; Morton, C.; McEvoy, D.; Huntington, J. L.; Abatzoglou, J. T.

2016-12-01

Drought has adverse effects on society through reduced water availability and agricultural production and increased wildfire risk. An abundance of remotely sensed imagery and climate data are being collected in near-real time that can provide place-based monitoring and early warning of drought and related hazards. However, in an era of increasing wealth of earth observations, tools that quickly access, compute, and visualize archives, and provide answers at relevant scales to better inform decision-making are lacking. We have developed ClimateEngine.org, a web application that uses Google's Earth Engine platform to enable users to quickly compute and visualize real-time observations. A suite of drought indices allow us to monitor and track drought from local (30-meters) to regional scales and contextualize current droughts within the historical record. Climate Engine is currently being used by U.S. federal agencies and researchers to develop baseline conditions and impact assessments related to agricultural, ecological, and hydrological drought. Climate Engine is also working with the Famine Early Warning Systems Network (FEWS NET) to expedite monitoring agricultural drought over broad areas at risk of food insecurity globally.

Google Earth and Geo Applications: A Toolset for Viewing Earth's Geospatial Information

NASA Astrophysics Data System (ADS)

Tuxen-Bettman, K.

2016-12-01

Earth scientists measure and derive fundamental data that can be of broad general interest to the public and policy makers. Yet, one of the challenges that has always faced the Earth science community is how to present their data and findings in an easy-to-use and compelling manner. Google's Geo Tools offer an efficient and dynamic way for scientists, educators, journalists and others to both access data and view or tell stories in a dynamic three-dimensional geospatial context. Google Earth in particular provides a dense canvas of satellite imagery on which can be viewed rich vector and raster datasets using the medium of Keyhole Markup Language (KML). Through KML, Google Earth can combine the analytical capabilities of Earth Engine, collaborative mapping of My Maps, and storytelling of Tour Builder and more to make Google's Geo Applications a coherent suite of tools for exploring our planet.https://earth.google.com/https://earthengine.google.com/https://mymaps.google.com/https://tourbuilder.withgoogle.com/https://www.google.com/streetview/

Google Earth: A Virtual Globe for Elementary Geography

ERIC Educational Resources Information Center

Britt, Judy; LaFontaine, Gus

2009-01-01

Originally called Earth Viewer in 2004, Google Earth was the first virtual globe easily available to the ordinary user of the Internet. Google Earth, at earth.google.com, is a free, 3-dimensional computer model of Earth, but that means more than just a large collection of pretty pictures. It allows the viewer to "fly" anywhere on Earth "to view…

Jupyter meets Earth: Creating Comprehensible and Reproducible Scientific Workflows with Jupyter Notebooks and Google Earth Engine

NASA Astrophysics Data System (ADS)

Erickson, T.

2016-12-01

Deriving actionable information from Earth observation data obtained from sensors or models can be quite complicated, and sharing those insights with others in a form that they can understand, reproduce, and improve upon is equally difficult. Journal articles, even if digital, commonly present just a summary of an analysis that cannot be understood in depth or reproduced without major effort on the part of the reader. Here we show a method of improving scientific literacy by pairing a recently developed scientific presentation technology (Jupyter Notebooks) with a petabyte-scale platform for accessing and analyzing Earth observation and model data (Google Earth Engine). Jupyter Notebooks are interactive web documents that mix live code with annotations such as rich-text markup, equations, images, videos, hyperlinks and dynamic output. Notebooks were first introduced as part of the IPython project in 2011, and have since gained wide acceptance in the scientific programming community, initially among Python programmers but later by a wide range of scientific programming languages. While Jupyter Notebooks have been widely adopted for general data analysis, data visualization, and machine learning, to date there have been relatively few examples of using Jupyter Notebooks to analyze geospatial datasets. Google Earth Engine is cloud-based platform for analyzing geospatial data, such as satellite remote sensing imagery and/or Earth system model output. Through its Python API, Earth Engine makes petabytes of Earth observation data accessible, and provides hundreds of algorithmic building blocks that can be chained together to produce high-level algorithms and outputs in real-time. We anticipate that this technology pairing will facilitate a better way of creating, documenting, and sharing complex analyses that derive information on our Earth that can be used to promote broader understanding of the complex issues that it faces. http://jupyter.orghttps://earthengine.google.com

Kinematics with the assistance of smartphones: Measuring data via GPS - Visualizing data with Google Earth

NASA Astrophysics Data System (ADS)

Gabriel, Patrik; Backhaus, Udo

2013-04-01

Nearly every smartphone is now GPS capable. The widespread use of GPS navigation has developed alongside less expensive hardware and user-friendly software interfaces, which may help to bring scientific research and teaching closer to real life.

BErkeley Atmospheric CO2 Network (BEACON) - Bringing Measurements of CO2 Emissions to a School Near You

NASA Astrophysics Data System (ADS)

Teige, V. E.; Havel, E.; Patt, C.; Heber, E.; Cohen, R. C.

2011-12-01

The University of California at Berkeley in collaboration with the Chabot Space and Science Center describe a set of educational programs, workshops, and exhibits based on a multi-node greenhouse gas and air quality monitoring network being deployed over Oakland, California. Examining raw numerical data using highly engaging and effective geo-data visualization tools like Google Earth can make the science come alive for students, and provide a hook for drawing them into deeper investigations. The Climate Science Investigations teacher workshop at the Chabot Space and Science Center will make use of Google Earth, Excel, and other geo-data visualization tools to step students through the process from data acquisition to discovery. Using multiple data sources, including output from the BErkeley Atmospheric CO2 Network (BEACON) project, participants will be encouraged to explore a variety of different modes of data display toward producing a unique, and ideally insightful, illumination of the data.

Authoring Tours of Geospatial Data With KML and Google Earth

NASA Astrophysics Data System (ADS)

Barcay, D. P.; Weiss-Malik, M.

2008-12-01

As virtual globes become widely adopted by the general public, the use of geospatial data has expanded greatly. With the popularization of Google Earth and other platforms, GIS systems have become virtual reality platforms. Using these platforms, a casual user can easily explore the world, browse massive data-sets, create powerful 3D visualizations, and share those visualizations with millions of people using the KML language. This technology has raised the bar for professionals and academics alike. It is now expected that studies and projects will be accompanied by compelling, high-quality visualizations. In this new landscape, a presentation of geospatial data can be the most effective form of advertisement for a project: engaging both the general public and the scientific community in a unified interactive experience. On the other hand, merely dumping a dataset into a virtual globe can be a disorienting, alienating experience for many users. To create an effective, far-reaching presentation, an author must take care to make their data approachable to a wide variety of users with varying knowledge of the subject matter, expertise in virtual globes, and attention spans. To that end, we present techniques for creating self-guided interactive tours of data represented in KML and visualized in Google Earth. Using these methods, we provide the ability to move the camera through the world while dynamically varying the content, style, and visibility of the displayed data. Such tours can automatically guide users through massive, complex datasets: engaging a broad user-base, and conveying subtle concepts that aren't immediately apparent when viewing the raw data. To the casual user these techniques result in an extremely compelling experience similar to watching video. Unlike video though, these techniques maintain the rich interactive environment provided by the virtual globe, allowing users to explore the data in detail and to add other data sources to the presentation.

An Interactive Visual Analytics Framework for Multi-Field Data in a Geo-Spatial Context

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Zhiyuan; Tong, Xiaonan; McDonnell, Kevin T.

2013-04-01

Climate research produces a wealth of multivariate data. These data often have a geospatial reference and so it is of interest to show them within their geospatial context. One can consider this configuration as a multi field visualization problem, where the geospace provides the expanse of the field. However, there is a limit on the amount of multivariate information that can be fit within a certain spatial location, and the use of linked multivari ate information displays has previously been devised to bridge this gap. In this paper we focus on the interactions in the geographical display, present an implementationmore » that uses Google Earth, and demonstrate it within a tightly linked parallel coordinates display. Several other visual representations, such as pie and bar charts are integrated into the Google Earth display and can be interactively manipulated. Further, we also demonstrate new brushing and visualization techniques for parallel coordinates, such as fixedwindow brushing and correlationenhanced display. We conceived our system with a team of climate researchers, who already made a few important discov eries using it. This demonstrates our system’s great potential to enable scientific discoveries, possibly also in oth er domains where data have a geospatial reference.« less

Development of a Web-Based Visualization Platform for Climate Research Using Google Earth

NASA Technical Reports Server (NTRS)

Sun, Xiaojuan; Shen, Suhung; Leptoukh, Gregory G.; Wang, Panxing; Di, Liping; Lu, Mingyue

2011-01-01

Recently, it has become easier to access climate data from satellites, ground measurements, and models from various data centers, However, searching. accessing, and prc(essing heterogeneous data from different sources are very tim -consuming tasks. There is lack of a comprehensive visual platform to acquire distributed and heterogeneous scientific data and to render processed images from a single accessing point for climate studies. This paper. documents the design and implementation of a Web-based visual, interoperable, and scalable platform that is able to access climatological fields from models, satellites, and ground stations from a number of data sources using Google Earth (GE) as a common graphical interface. The development is based on the TCP/IP protocol and various data sharing open sources, such as OPeNDAP, GDS, Web Processing Service (WPS), and Web Mapping Service (WMS). The visualization capability of integrating various measurements into cE extends dramatically the awareness and visibility of scientific results. Using embedded geographic information in the GE, the designed system improves our understanding of the relationships of different elements in a four dimensional domain. The system enables easy and convenient synergistic research on a virtual platform for professionals and the general public, gr$tly advancing global data sharing and scientific research collaboration.

Playing with Satellite Data

NASA Astrophysics Data System (ADS)

Beitler, J.; Truex, S.

2008-12-01

Would you like to see your science on the evening news? On everyone's mobile device? How hard is it to make one of those cool Google Earth files so people can explore your world? Do you need to be a programmer, or could most any person with a little motivation and a few inexpensive tools do it? Find out what it takes to get started with these technologies--it may be easier than you think--and how they can give your data more legs. I will demonstrate some of the ways that the National Snow and Ice Data Center has been successful in reaching the public and educators with visualized and animated data about the Earth's frozen regions, and talk about some of the how-to. In particular, see what we have done with QuickTime, Google Earth, YouTube, and the iPhone. I'll also talk about how we've assessed the reach and success of these efforts.

Do Interactive Globes and Games Help Students Learn Planetary Science?

NASA Astrophysics Data System (ADS)

Coba, Filis; Burgin, Stephen; De Paor, Declan; Georgen, Jennifer

2016-01-01

The popularity of animations and interactive visualizations in undergraduate science education might lead one to assume that these teaching aids enhance student learning. We tested this assumption for the case of the Google Earth virtual globe with a comparison of control and treatment student groups in a general education class of over 370 students at a large public university. Earth and Planetary Science course content was developed in two formats: using Keyhole Markup Language (KML) to create interactive tours in Google Earth (the treatment group) and Portable Document Format (PDF) for on-screen reading (the control group). The PDF documents contained identical text and images to the placemark balloons or "tour stops" in the Google Earth version. Some significant differences were noted between the two groups based on the immediate post-questionnaire with the KML students out-performing the PDF students, but not on the delayed measure. In a separate but related project, we undertake preliminary investigations into methods of teaching basic concepts in planetary mantle convection using numerical simulations. The goal of this project is to develop an interface with a two-dimensional finite element model that will allow students to vary parameters such as the temperatures assigned to the boundaries of the model domain, to help them actively explore important variables that control convection.

Google Moon Press Conference

NASA Image and Video Library

2009-07-19

Michael Weiss-Malik, Product Manager for Moon in Google Earth, Google, Inc., speaks during a press conference, Monday, July 20, 2009, announcing the launch of Moon in Google Earth, an immersive 3D atlas of the Moon, accessible within Google Earth 5.0, Monday, July 20, 2009, at the Newseum in Washington. Photo Credit: (NASA/Bill Ingalls)

Analyst Performance Measures. Volume 1: Persistent Surveillance Data Processing, Storage and Retrieval

DTIC Science & Technology

2011-09-01

solutions to address these important challenges . The Air Force is seeking innovative architectures to process and store massive data sets in a flexible...Google Earth, the Video LAN Client ( VLC ) media player, and the Environmental Systems Research Institute corporation‘s (ESRI) ArcGIS product — to...Earth, Quantum GIS, VLC Media Player, NASA WorldWind, ESRI ArcGIS and many others. Open source GIS and media visualization software can also be

Vizualization of Arctic Landscapes in the Geoinformation System

NASA Astrophysics Data System (ADS)

Panidi, E. A.; Tsepelev, V. Yu.; Bobkov, A. A.

2010-12-01

In order to investigate the long-scale dynamics of an ice cover, authors suggest to use the geoinformation system (GIS) which allows to conduct the operative and historical analysis of the Polar Region water-ice landscapes variability. Such GIS should include longterm monthly average fields of sea ice, hydrological and atmospheric characters. All collected data and results of their processing have been structured in ArcGISTM . For presentation in the INTERNET resources all datasets were transformed to the open format KML for using in the virtual reality of Google EarthTM . The double component system elaborating on the base of ArcGIS and Google Earth allows to make accumulation, processing and joint synchronous and asynchronous analysis of data and provide wide circle of remote users with accessibility of visual datasets analysis.

Building a Dashboard of the Planet with Google Earth and Earth Engine

NASA Astrophysics Data System (ADS)

Moore, R. T.; Hancher, M.

2016-12-01

In 2005 Google Earth, a popular 3-D virtual globe, was first released. Scientists immediately recognized how it could be used to tell stories about the Earth. From 2006 to 2009, the "Virtual Globes" sessions of AGU included innovative examples of scientists and educators using Google Earth, and since that time it has become a commonplace tool for communicating scientific results. In 2009 Google Earth Engine, a cloud-based platform for planetary-scale geospatial analysis, was first announced. Earth Engine was initially used to extract information about the world's forests from raw Landsat data. Since then, the platform has proven highly effective for general analysis of georeferenced data, and users have expanded the list of use cases to include high-impact societal issues such as conservation, drought, disease, food security, water management, climate change and environmental monitoring. To support these use cases, the platform has continuously evolved with new datasets, analysis functions, and user interface tools. This talk will give an overview of the latest Google Earth and Earth Engine functionality that allow partners to understand, monitor and tell stories about of our living, breathing Earth. https://earth.google.com https://earthengine.google.com

Using NASA's Giovanni Web Portal to Access and Visualize Satellite-based Earth Science Data in the Classroom

NASA Technical Reports Server (NTRS)

Lloyd, Steven; Acker, James G.; Prados, Ana I.; Leptoukh, Gregory G.

2008-01-01

One of the biggest obstacles for the average Earth science student today is locating and obtaining satellite-based remote sensing data sets in a format that is accessible and optimal for their data analysis needs. At the Goddard Earth Sciences Data and Information Services Center (GES-DISC) alone, on the order of hundreds of Terabytes of data are available for distribution to scientists, students and the general public. The single biggest and time-consuming hurdle for most students when they begin their study of the various datasets is how to slog through this mountain of data to arrive at a properly sub-setted and manageable data set to answer their science question(s). The GES DISC provides a number of tools for data access and visualization, including the Google-like Mirador search engine and the powerful GES-DISC Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) web interface.

Google earth as a source of ancillary material in a history of psychology class.

PubMed

Stevison, Blake K; Biggs, Patrick T; Abramson, Charles I

2010-06-01

This article discusses the use of Google Earth to visit significant geographical locations associated with events in the history of psychology. The process of opening files, viewing content, adding placemarks, and saving customized virtual tours on Google Earth are explained. Suggestions for incorporating Google Earth into a history of psychology course are also described.

Enhancing Geographic and Digital Literacy with a Student-Generated Course Portfolio in Google Earth

ERIC Educational Resources Information Center

Guertin, Laura; Stubbs, Christopher; Millet, Christopher; Lee, Tsan-Kuang; Bodek, Matthew

2012-01-01

Google Earth can serve as a platform for students to construct a course ePortfolio. By having students construct their own placemarks in a customized Google Earth file, students document their learning in a geospatial context, learn an innovative use of Google Earth, and have the opportunity for creativity and flexibility with disseminating their…

New Techniques for Deep Learning with Geospatial Data using TensorFlow, Earth Engine, and Google Cloud Platform

NASA Astrophysics Data System (ADS)

Hancher, M.

2017-12-01

Recent years have seen promising results from many research teams applying deep learning techniques to geospatial data processing. In that same timeframe, TensorFlow has emerged as the most popular framework for deep learning in general, and Google has assembled petabytes of Earth observation data from a wide variety of sources and made them available in analysis-ready form in the cloud through Google Earth Engine. Nevertheless, developing and applying deep learning to geospatial data at scale has been somewhat cumbersome to date. We present a new set of tools and techniques that simplify this process. Our approach combines the strengths of several underlying tools: TensorFlow for its expressive deep learning framework; Earth Engine for data management, preprocessing, postprocessing, and visualization; and other tools in Google Cloud Platform to train TensorFlow models at scale, perform additional custom parallel data processing, and drive the entire process from a single familiar Python development environment. These tools can be used to easily apply standard deep neural networks, convolutional neural networks, and other custom model architectures to a variety of geospatial data structures. We discuss our experiences applying these and related tools to a range of machine learning problems, including classic problems like cloud detection, building detection, land cover classification, as well as more novel problems like illegal fishing detection. Our improved tools will make it easier for geospatial data scientists to apply modern deep learning techniques to their own problems, and will also make it easier for machine learning researchers to advance the state of the art of those techniques.

GeolOkit 1.0: a new Open Source, Cross-Platform software for geological data visualization in Google Earth environment

NASA Astrophysics Data System (ADS)

Triantafyllou, Antoine; Bastin, Christophe; Watlet, Arnaud

2016-04-01

GIS software suites are today's essential tools to gather and visualise geological data, to apply spatial and temporal analysis and in fine, to create and share interactive maps for further geosciences' investigations. For these purposes, we developed GeolOkit: an open-source, freeware and lightweight software, written in Python, a high-level, cross-platform programming language. GeolOkit software is accessible through a graphical user interface, designed to run in parallel with Google Earth. It is a super user-friendly toolbox that allows 'geo-users' to import their raw data (e.g. GPS, sample locations, structural data, field pictures, maps), to use fast data analysis tools and to plot these one into Google Earth environment using KML code. This workflow requires no need of any third party software, except Google Earth itself. GeolOkit comes with large number of geosciences' labels, symbols, colours and placemarks and may process : (i) multi-points data, (ii) contours via several interpolations methods, (iii) discrete planar and linear structural data in 2D or 3D supporting large range of structures input format, (iv) clustered stereonets and rose diagram, (v) drawn cross-sections as vertical sections, (vi) georeferenced maps and vectors, (vii) field pictures using either geo-tracking metadata from a camera built-in GPS module, or the same-day track of an external GPS. We are looking for you to discover all the functionalities of GeolOkit software. As this project is under development, we are definitely looking to discussions regarding your proper needs, your ideas and contributions to GeolOkit project.

Supporting our scientists with Google Earth-based UIs.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Scott, Janine

2010-10-01

Google Earth and Google Maps are incredibly useful for researchers looking for easily-digestible displays of data. This presentation will provide a step-by-step tutorial on how to begin using Google Earth to create tools that further the mission of the DOE national lab complex.

Integrating and Visualizing Tropical Cyclone Data Using the Real Time Mission Monitor

NASA Technical Reports Server (NTRS)

Goodman, H. Michael; Blakeslee, Richard; Conover, Helen; Hall, John; He, Yubin; Regner, Kathryn

2009-01-01

The Real Time Mission Monitor (RTMM) is a visualization and information system that fuses multiple Earth science data sources, to enable real time decision-making for airborne and ground validation experiments. Developed at the NASA Marshall Space Flight Center, RTMM is a situational awareness, decision-support system that integrates satellite imagery, radar, surface and airborne instrument data sets, model output parameters, lightning location observations, aircraft navigation data, soundings, and other applicable Earth science data sets. The integration and delivery of this information is made possible using data acquisition systems, network communication links, network server resources, and visualizations through the Google Earth virtual globe application. RTMM is extremely valuable for optimizing individual Earth science airborne field experiments. Flight planners, scientists, and managers appreciate the contributions that RTMM makes to their flight projects. A broad spectrum of interdisciplinary scientists used RTMM during field campaigns including the hurricane-focused 2006 NASA African Monsoon Multidisciplinary Analyses (NAMMA), 2007 NOAA-NASA Aerosonde Hurricane Noel flight, 2007 Tropical Composition, Cloud, and Climate Coupling (TC4), plus a soil moisture (SMAP-VEX) and two arctic research experiments (ARCTAS) in 2008. Improving and evolving RTMM is a continuous process. RTMM recently integrated the Waypoint Planning Tool, a Java-based application that enables aircraft mission scientists to easily develop a pre-mission flight plan through an interactive point-and-click interface. Individual flight legs are automatically calculated "on the fly". The resultant flight plan is then immediately posted to the Google Earth-based RTMM for interested scientists to view the planned flight track and subsequently compare it to the actual real time flight progress. We are planning additional capabilities to RTMM including collaborations with the Jet Propulsion Laboratory in the joint development of a Tropical Cyclone Integrated Data Exchange and Analysis System (TC IDEAS) which will serve as a web portal for access to tropical cyclone data, visualizations and model output.

A method for vreating a three dimensional model from published geologic maps and cross sections

USGS Publications Warehouse

Walsh, Gregory J.

2009-01-01

This brief report presents a relatively inexpensive and rapid method for creating a 3D model of geology from published quadrangle-scale maps and cross sections using Google Earth and Google SketchUp software. An example from the Green Mountains of Vermont, USA, is used to illustrate the step by step methods used to create such a model. A second example is provided from the Jebel Saghro region of the Anti-Atlas Mountains of Morocco. The report was published to help enhance the public?s ability to use and visualize geologic map data.

Quantifying Urban Texture in Nairobi, Kenya and its Implications for Understanding Natural Hazard Impact

NASA Astrophysics Data System (ADS)

Taylor, Faith E.; Malamud, Bruce D.; Millington, James D. A.

2016-04-01

The configuration of infrastructure networks such as roads, drainage and power lines can both affect and be affected by natural hazards such as earthquakes, intense rain, wildfires and extreme temperatures. In this paper, we present and compare two methods to quantify urban topology on approximate scales of 0.0005 km2 to 10 km2 and create classifications of different 'urban textures' that relate to risk of natural hazard impact in an area. The methods we use focus on applicability in urban developing country settings, where access to high resolution and high quality data may be difficult. We use the city of Nairobi, Kenya to trial these methods. Nairobi has a population >3 million, and is a mix of informal settlements, residential and commercial development. The city and its immediate surroundings are subject to a variety of natural hazards such as floods, landslides, fires, drought, hail, heavy wind and extreme temperatures; all of these hazards can occur singly, but also have the potential for one to trigger another, thus providing a 'cascade' of hazards, or for two of the hazards to occur spatially and temporally near each other and interact. We use two measures of urban texture: (i) Street block textures, (ii) Google Earth land cover textures. Street block textures builds on the methodology of Louf and Barthelemy (2014) and uses Open Street Map data to analyse the shape, size, complexity and pattern of individual blocks of land created by fully enclosed loops of the major and minor road network of Nairobi. We find >4000 of these blocks ranging in size from approximately 0.0005 km2 to 10 km2, with approximately 5 classifications of urban texture. Google Earth land cover texture is a visual classification of homogeneous parcels of land performed in Google Earth using high-resolution airborne imagery and a qualitative criteria for each land cover type. Using the Google Earth land cover texture method, we identify >40 'urban textures' based on visual characteristics such as colour, texture, shadow and setting and have created a clear criteria for classifying an area based on its visual characteristics. These two methods for classifying urban texture in Nairobi are compared in a GIS and in the field to investigate whether there is a link between the visual appearance of an area and its network topology. From these urban textures, we may start to identify areas where (a) urban texture types may indicate a relative propensity to certain hazards and their interactions and (b) urban texture types that may increase or decrease the impact of a hazard that occurs in that area.

Development of Visualizations and Loggable Activities for the Geosciences. Results from Recent TUES Sponsored Projects

NASA Astrophysics Data System (ADS)

De Paor, D. G.; Bailey, J. E.; Whitmeyer, S. J.

2012-12-01

Our TUES research centers on the role of digital data, visualizations, animations, and simulations in undergraduate geoscience education. Digital hardware (smartphones, tablets, GPSs, GigaPan robotic camera mounts, etc.) are revolutionizing field data collection. Software products (GIS, 3-D scanning and modeling programs, virtual globes, etc.) have truly transformed the way geoscientists teach, learn, and do research. Whilst Google-Earth-style visualizations are famously user-friend for the person browsing, they can be notoriously unfriendly for the content creator. Therefore, we developed tools to help educators create and share visualizations as easily as if posting on Facebook. Anyone whoIf you wish to display geological cross sections on Google Earth, go to digitalplanet.org, upload image files, position them on a line of section, and share with the world through our KMZ hosting service. Other tools facilitate screen overlay and 3-D map symbol generation. We advocate use of such technology to enable undergraduate students to 'publish' their first mapping efforts even while they are working in the field. A second outcome of our TUES projects merges Second-Life-style interaction with Google Earth. We created games in which students act as first responders for natural hazard mitigation, prospectors for natural resource explorations, and structural geologist for map-making. Students are represented by avatars and collaborate by exchange of text messages - the natural mode of communication for the current generation. Teachers view logs showing student movements as well as transcripts of text messages and can scaffold student learning and geofence students to prevent wandering. Early results of in-class testing show positive learning outcomes. The third aspect of our program emphasizes dissemination. Experience shows that great effort is required to overcome activation energy and ensure adoption of new technology into the curriculum. We organized a GSA Penrose Conference, a GSA Pardee Keynote Symposium, and AGU Townhall Meeting, and numerous workshops at annual and regional meetings, and set up a web site dedicated to dissemination of program products. Future plans include development of augmented reality teaching resources, hosting of community mapping services, and creation of a truly 4-D virtual globe.;

Google Earth Visualizations of the Marine Automatic Identification System (AIS): Monitoring Ship Traffic in National Marine Sanctuaries

NASA Astrophysics Data System (ADS)

Schwehr, K.; Hatch, L.; Thompson, M.; Wiley, D.

2007-12-01

The Automatic Identification System (AIS) is a new technology that provides ship position reports with location, time, and identity information without human intervention from ships carrying the transponders to any receiver listening to the broadcasts. In collaboration with the USCG's Research and Development Center, NOAA's Stellwagen Bank National Marine Sanctuary (SBNMS) has installed 3 AIS receivers around Massachusetts Bay to monitor ship traffic transiting the sanctuary and surrounding waters. The SBNMS and the USCG also worked together propose the shifting the shipping lanes (termed the traffic separation scheme; TSS) that transit the sanctuary slightly to the north to reduce the probability of ship strikes of whales that frequent the sanctuary. Following approval by the United Nation's International Maritime Organization, AIS provided a means for NOAA to assess changes in the distribution of shipping traffic caused by formal change in the TSS effective July 1, 2007. However, there was no easy way to visualize this type of time series data. We have created a software package called noaadata-py to process the AIS ship reports and produce KML files for viewing in Google Earth. Ship tracks can be shown changing over time to allow the viewer to feel the motion of traffic through the sanctuary. The ship tracks can also be gridded to create ship traffic density reports for specified periods of time. The density is displayed as map draped on the sea surface or as vertical histogram columns. Additional visualizations such as bathymetry images, S57 nautical charts, and USCG Marine Information for Safety and Law Enforcement (MISLE) can be combined with the ship traffic visualizations to give a more complete picture of the maritime environment. AIS traffic analyses have the potential to give managers throughout NOAA's National Marine Sanctuaries an improved ability to assess the impacts of ship traffic on the marine resources they seek to protect. Viewing ship traffic data through Google Earth provides ease and efficiency for people not trained in GIS data processing.

Positional Accuracy Assessment of Googleearth in Riyadh

NASA Astrophysics Data System (ADS)

Farah, Ashraf; Algarni, Dafer

2014-06-01

Google Earth is a virtual globe, map and geographical information program that is controlled by Google corporation. It maps the Earth by the superimposition of images obtained from satellite imagery, aerial photography and GIS 3D globe. With millions of users all around the globe, GoogleEarth® has become the ultimate source of spatial data and information for private and public decision-support systems besides many types and forms of social interactions. Many users mostly in developing countries are also using it for surveying applications, the matter that raises questions about the positional accuracy of the Google Earth program. This research presents a small-scale assessment study of the positional accuracy of GoogleEarth® Imagery in Riyadh; capital of Kingdom of Saudi Arabia (KSA). The results show that the RMSE of the GoogleEarth imagery is 2.18 m and 1.51 m for the horizontal and height coordinates respectively.

GeoDash: Assisting Visual Image Interpretation in Collect Earth Online by Leveraging Big Data on Google Earth Engine

NASA Technical Reports Server (NTRS)

Markert, Kel; Ashmall, William; Johnson, Gary; Saah, David; Mollicone, Danilo; Diaz, Alfonso Sanchez-Paus; Anderson, Eric; Flores, Africa; Griffin, Robert

2017-01-01

Collect Earth Online (CEO) is a free and open online implementation of the FAO Collect Earth system for collaboratively collecting environmental data through the visual interpretation of Earth observation imagery. The primary collection mechanism in CEO is human interpretation of land surface characteristics in imagery served via Web Map Services (WMS). However, interpreters may not have enough contextual information to classify samples by only viewing the imagery served via WMS, be they high resolution or otherwise. To assist in the interpretation and collection processes in CEO, SERVIR, a joint NASA-USAID initiative that brings Earth observations to improve environmental decision making in developing countries, developed the GeoDash system, an embedded and critical component of CEO. GeoDash leverages Google Earth Engine (GEE) by allowing users to set up custom browser-based widgets that pull from GEE's massive public data catalog. These widgets can be quick looks of other satellite imagery, time series graphs of environmental variables, and statistics panels of the same. Users can customize widgets with any of GEE's image collections, such as the historical Landsat collection with data available since the 1970s, select date ranges, image stretch parameters, graph characteristics, and create custom layouts, all on-the-fly to support plot interpretation in CEO. This presentation focuses on the implementation and potential applications, including the back-end links to GEE and the user interface with custom widget building. GeoDash takes large data volumes and condenses them into meaningful, relevant information for interpreters. While designed initially with national and global forest resource assessments in mind, the system will complement disaster assessments, agriculture management, project monitoring and evaluation, and more.

GeoDash: Assisting Visual Image Interpretation in Collect Earth Online by Leveraging Big Data on Google Earth Engine

NASA Astrophysics Data System (ADS)

Markert, K. N.; Ashmall, W.; Johnson, G.; Saah, D. S.; Anderson, E.; Flores Cordova, A. I.; Díaz, A. S. P.; Mollicone, D.; Griffin, R.

2017-12-01

Collect Earth Online (CEO) is a free and open online implementation of the FAO Collect Earth system for collaboratively collecting environmental data through the visual interpretation of Earth observation imagery. The primary collection mechanism in CEO is human interpretation of land surface characteristics in imagery served via Web Map Services (WMS). However, interpreters may not have enough contextual information to classify samples by only viewing the imagery served via WMS, be they high resolution or otherwise. To assist in the interpretation and collection processes in CEO, SERVIR, a joint NASA-USAID initiative that brings Earth observations to improve environmental decision making in developing countries, developed the GeoDash system, an embedded and critical component of CEO. GeoDash leverages Google Earth Engine (GEE) by allowing users to set up custom browser-based widgets that pull from GEE's massive public data catalog. These widgets can be quick looks of other satellite imagery, time series graphs of environmental variables, and statistics panels of the same. Users can customize widgets with any of GEE's image collections, such as the historical Landsat collection with data available since the 1970s, select date ranges, image stretch parameters, graph characteristics, and create custom layouts, all on-the-fly to support plot interpretation in CEO. This presentation focuses on the implementation and potential applications, including the back-end links to GEE and the user interface with custom widget building. GeoDash takes large data volumes and condenses them into meaningful, relevant information for interpreters. While designed initially with national and global forest resource assessments in mind, the system will complement disaster assessments, agriculture management, project monitoring and evaluation, and more.

A Knowledge Portal and Collaboration Environment for the Earth Sciences

NASA Astrophysics Data System (ADS)

D'Agnese, F. A.

2008-12-01

Earth Knowledge is developing a web-based 'Knowledge Portal and Collaboration Environment' that will serve as the information-technology-based foundation of a modular Internet-based Earth-Systems Monitoring, Analysis, and Management Tool. This 'Knowledge Portal' is essentially a 'mash- up' of web-based and client-based tools and services that support on-line collaboration, community discussion, and broad public dissemination of earth and environmental science information in a wide-area distributed network. In contrast to specialized knowledge-management or geographic-information systems developed for long- term and incremental scientific analysis, this system will exploit familiar software tools using industry standard protocols, formats, and APIs to discover, process, fuse, and visualize existing environmental datasets using Google Earth and Google Maps. An early form of these tools and services is being used by Earth Knowledge to facilitate the investigations and conversations of scientists, resource managers, and citizen-stakeholders addressing water resource sustainability issues in the Great Basin region of the desert southwestern United States. These ongoing projects will serve as use cases for the further development of this information-technology infrastructure. This 'Knowledge Portal' will accelerate the deployment of Earth- system data and information into an operational knowledge management system that may be used by decision-makers concerned with stewardship of water resources in the American Desert Southwest.

The World in Spatial Terms: Mapmaking and Map Reading

ERIC Educational Resources Information Center

Ekiss, Gale Olp; Trapido-Lurie, Barbara; Phillips, Judy; Hinde, Elizabeth

2007-01-01

Maps and mapping activities are essential in the primary grades. Maps are truly ubiquitous today, as evidenced by the popularity of websites such as Google Earth and Mapquest, and by devices such as Global Positioning System (GPS) units in cars, planes, and boats. Maps can give visual settings to travel stories and historical narratives and can…

Global Coastal and Marine Spatial Planning (CMSP) from Space Based AIS Ship Tracking

NASA Astrophysics Data System (ADS)

Schwehr, K. D.; Foulkes, J. A.; Lorenzini, D.; Kanawati, M.

2011-12-01

All nations need to be developing long term integrated strategies for how to use and preserve our natural resources. As a part of these strategies, we must evalutate how communities of users react to changes in rules and regulations of ocean use. Global characterization of the vessel traffic on our Earth's oceans is essential to understanding the existing uses to develop international Coast and Marine Spatial Planning (CMSP). Ship traffic within 100-200km is beginning to be effectively covered in low latitudes by ground based receivers collecting position reports from the maritime Automatic Identification System (AIS). Unfortunately, remote islands, high latitudes, and open ocean Marine Protected Areas (MPA) are not covered by these ground systems. Deploying enough autonomous airborne (UAV) and surface (USV) vessels and buoys to provide adequate coverage is a difficult task. While the individual device costs are plummeting, a large fleet of AIS receivers is expensive to maintain. The global AIS coverage from SpaceQuest's low Earth orbit satellite receivers combined with the visualization and data storage infrastructure of Google (e.g. Maps, Earth, and Fusion Tables) provide a platform that enables researchers and resource managers to begin answer the question of how ocean resources are being utilized. Near real-time vessel traffic data will allow managers of marine resources to understand how changes to education, enforcement, rules, and regulations alter usage and compliance patterns. We will demonstrate the potential for this system using a sample SpaceQuest data set processed with libais which stores the results in a Fusion Table. From there, the data is imported to PyKML and visualized in Google Earth with a custom gx:Track visualization utilizing KML's extended data functionality to facilitate ship track interrogation. Analysts can then annotate and discuss vessel tracks in Fusion Tables.

A Virtual Tour of the 1868 Hayward Earthquake in Google EarthTM

NASA Astrophysics Data System (ADS)

Lackey, H. G.; Blair, J. L.; Boatwright, J.; Brocher, T.

2007-12-01

The 1868 Hayward earthquake has been overshadowed by the subsequent 1906 San Francisco earthquake that destroyed much of San Francisco. Nonetheless, a modern recurrence of the 1868 earthquake would cause widespread damage to the densely populated Bay Area, particularly in the east Bay communities that have grown up virtually on top of the Hayward fault. Our concern is heightened by paleoseismic studies suggesting that the recurrence interval for the past five earthquakes on the southern Hayward fault is 140 to 170 years. Our objective is to build an educational web site that illustrates the cause and effect of the 1868 earthquake drawing on scientific and historic information. We will use Google EarthTM software to visually illustrate complex scientific concepts in a way that is understandable to a non-scientific audience. This web site will lead the viewer from a regional summary of the plate tectonics and faulting system of western North America, to more specific information about the 1868 Hayward earthquake itself. Text and Google EarthTM layers will include modeled shaking of the earthquake, relocations of historic photographs, reconstruction of damaged buildings as 3-D models, and additional scientific data that may come from the many scientific studies conducted for the 140th anniversary of the event. Earthquake engineering concerns will be stressed, including population density, vulnerable infrastructure, and lifelines. We will also present detailed maps of the Hayward fault, measurements of fault creep, and geologic evidence of its recurrence. Understanding the science behind earthquake hazards is an important step in preparing for the next significant earthquake. We hope to communicate to the public and students of all ages, through visualizations, not only the cause and effect of the 1868 earthquake, but also modern seismic hazards of the San Francisco Bay region.

Google Moon Press Conference

NASA Image and Video Library

2009-07-19

Tiffany Montague, Technical Program Manager for NASA and Google Lunar X PRIZE, Google, Inc., speaks during a press conference, Monday, July 20, 2009, announcing the launch of Moon in Google Earth, an immersive 3D atlas of the Moon, accessible within Google Earth 5.0, Monday, July 20, 2009, at the Newseum in Washington. Photo Credit: (NASA/Bill Ingalls)

The 2nd Generation Real Time Mission Monitor (RTMM) Development

NASA Technical Reports Server (NTRS)

Blakeslee, Richard; Goodman, Michael; Meyer, Paul; Hardin, Danny; Hall, John; He, Yubin; Regner, Kathryn; Conover, Helen; Smith, Tammy; Lu, Jessica;

Google Earth as a method for connecting scientific research with the World

NASA Astrophysics Data System (ADS)

Graham, J. R.

2012-12-01

Google Earth has proven itself to be an exceptionally successful and ambitious application: fully capable as a scientific tool, yet able to also satisfy the intellectual and virtual touristic needs of students, educators and the general public. It is difficult to overstate Google Earth's impact on our understanding of the World we inhabit, and yet there is also considerable potential that remains unexplored. This paper will discuss Google Earth's potential as a social network for the science community - connecting the general public with scientists, and scientists with their research. This paper will look at the University of Lethbridge's RAVE (Reaching Audiences through Virtual Entryways) project as a model for how this social network can function within the Google Earth environment.

Geospatial Visualization of Scientific Data Through Keyhole Markup Language

NASA Astrophysics Data System (ADS)

Wernecke, J.; Bailey, J. E.

2008-12-01

The development of virtual globes has provided a fun and innovative tool for exploring the surface of the Earth. However, it has been the paralleling maturation of Keyhole Markup Language (KML) that has created a new medium and perspective through which to visualize scientific datasets. Originally created by Keyhole Inc., and then acquired by Google in 2004, in 2007 KML was given over to the Open Geospatial Consortium (OGC). It became an OGC international standard on 14 April 2008, and has subsequently been adopted by all major geobrowser developers (e.g., Google, Microsoft, ESRI, NASA) and many smaller ones (e.g., Earthbrowser). By making KML a standard at a relatively young stage in its evolution, developers of the language are seeking to avoid the issues that plagued the early World Wide Web and development of Hypertext Markup Language (HTML). The popularity and utility of Google Earth, in particular, has been enhanced by KML features such as the Smithsonian volcano layer and the dynamic weather layers. Through KML, users can view real-time earthquake locations (USGS), view animations of polar sea-ice coverage (NSIDC), or read about the daily activities of chimpanzees (Jane Goodall Institute). Perhaps even more powerful is the fact that any users can create, edit, and share their own KML, with no or relatively little knowledge of manipulating computer code. We present an overview of the best current scientific uses of KML and a guide to how scientists can learn to use KML themselves.

Cloud Geospatial Analysis Tools for Global-Scale Comparisons of Population Models for Decision Making

NASA Astrophysics Data System (ADS)

Hancher, M.; Lieber, A.; Scott, L.

2017-12-01

The volume of satellite and other Earth data is growing rapidly. Combined with information about where people are, these data can inform decisions in a range of areas including food and water security, disease and disaster risk management, biodiversity, and climate adaptation. Google's platform for planetary-scale geospatial data analysis, Earth Engine, grants access to petabytes of continually updating Earth data, programming interfaces for analyzing the data without the need to download and manage it, and mechanisms for sharing the analyses and publishing results for data-driven decision making. In addition to data about the planet, data about the human planet - population, settlement and urban models - are now available for global scale analysis. The Earth Engine APIs enable these data to be joined, combined or visualized with economic or environmental indicators such as nighttime lights trends, global surface water, or climate projections, in the browser without the need to download anything. We will present our newly developed application intended to serve as a resource for government agencies, disaster response and public health programs, or other consumers of these data to quickly visualize the different population models, and compare them to ground truth tabular data to determine which model suits their immediate needs. Users can further tap into the power of Earth Engine and other Google technologies to perform a range of analysis from simple statistics in custom regions to more complex machine learning models. We will highlight case studies in which organizations around the world have used Earth Engine to combine population data with multiple other sources of data, such as water resources and roads data, over deep stacks of temporal imagery to model disease risk and accessibility to inform decisions.

GeneOnEarth: fitting genetic PC plots on the globe.

PubMed

Torres-Sánchez, Sergio; Medina-Medina, Nuria; Gignoux, Chris; Abad-Grau, María M; González-Burchard, Esteban

2013-01-01

Principal component (PC) plots have become widely used to summarize genetic variation of individuals in a sample. The similarity between genetic distance in PC plots and geographical distance has shown to be quite impressive. However, in most situations, individual ancestral origins are not precisely known or they are heterogeneously distributed; hence, they are hardly linked to a geographical area. We have developed GeneOnEarth, a user-friendly web-based tool to help geneticists to understand whether a linear isolation-by-distance model may apply to a genetic data set; thus, genetic distances among a set of individuals resemble geographical distances among their origins. Its main goal is to allow users to first apply a by-view Procrustes method to visually learn whether this model holds. To do that, the user can choose the exact geographical area from an on line 2D or 3D world map by using, respectively, Google Maps or Google Earth, and rotate, flip, and resize the images. GeneOnEarth can also compute the optimal rotation angle using Procrustes analysis and assess statistical evidence of similarity when a different rotation angle has been chosen by the user. An online version of GeneOnEarth is available for testing and using purposes at http://bios.ugr.es/GeneOnEarth.

Visualization of the NASA ICON mission in 3d

NASA Astrophysics Data System (ADS)

Mendez, R. A., Jr.; Immel, T. J.; Miller, N.

2016-12-01

The ICON Explorer mission (http://icon.ssl.berkeley.edu) will provide several data products for the atmosphere and ionosphere after its launch in 2017. This project will support the mission by investigating the capability of these tools for visualization of current and predicted observatory characteristics and data acquisition. Visualization of this mission can be accomplished using tools like Google Earth or CesiumJS, as well assistance from Java or Python. Ideally we will bring this visualization into the homes of people without the need of additional software. The path of launching a standalone website, building this environment, and a full toolkit will be discussed. Eventually, the initial work could lead to the addition of a downloadable visualization packages for mission demonstration or science visualization.

Overcoming Assessment Problems in Google Earth-Based Assignments

ERIC Educational Resources Information Center

Johnson, Nicholas D.; Lang, Nicholas P.; Zophy, Kelley T.

2011-01-01

Educational technologies such as Google Earth have the potential to increase student learning and participation in geoscience classrooms. However, little has been written about tying the use of such software with effective assessment. To maximize Google Earth's learning potential for students, educators need to craft appropriate, research-based…

A Google Earth Grand Tour of the Terrestrial Planets

ERIC Educational Resources Information Center

De Paor, Declan; Coba, Filis; Burgin, Stephen

2016-01-01

Google Earth is a powerful instructional resource for geoscience education. We have extended the virtual globe to include all terrestrial planets. Downloadable Keyhole Markup Language (KML) files (Google Earth's scripting language) associated with this paper include lessons about Mercury, Venus, the Moon, and Mars. We created "grand…

Teaching Waves with Google Earth

ERIC Educational Resources Information Center

Logiurato, Fabrizio

2012-01-01

Google Earth is a huge source of interesting illustrations of various natural phenomena. It can represent a valuable tool for science education, not only for teaching geography and geology, but also physics. Here we suggest that Google Earth can be used for introducing in an attractive way the physics of waves. (Contains 9 figures.)

Google Earth for Landowners: Insights from Hands-on Workshops

ERIC Educational Resources Information Center

Huff, Tristan

2014-01-01

Google Earth is an accessible, user-friendly GIS that can help landowners in their management planning. I offered hands-on Google Earth workshops to landowners to teach skills, including mapmaking, length and area measurement, and database management. Workshop participants were surveyed at least 6 months following workshop completion, and learning…

Web GIS in practice III: creating a simple interactive map of England's Strategic Health Authorities using Google Maps API, Google Earth KML, and MSN Virtual Earth Map Control

PubMed Central

Boulos, Maged N Kamel

2005-01-01

This eye-opener article aims at introducing the health GIS community to the emerging online consumer geoinformatics services from Google and Microsoft (MSN), and their potential utility in creating custom online interactive health maps. Using the programmable interfaces provided by Google and MSN, we created three interactive demonstrator maps of England's Strategic Health Authorities. These can be browsed online at – Google Maps API (Application Programming Interface) version, – Google Earth KML (Keyhole Markup Language) version, and – MSN Virtual Earth Map Control version. Google and MSN's worldwide distribution of "free" geospatial tools, imagery, and maps is to be commended as a significant step towards the ultimate "wikification" of maps and GIS. A discussion is provided of these emerging online mapping trends, their expected future implications and development directions, and associated individual privacy, national security and copyrights issues. Although ESRI have announced their planned response to Google (and MSN), it remains to be seen how their envisaged plans will materialize and compare to the offerings from Google and MSN, and also how Google and MSN mapping tools will further evolve in the near future. PMID:16176577

Google Moon Press Conference

NASA Image and Video Library

2009-07-19

Brian McLendon, VP of Engineering, Google, Inc., speaks during a press conference, Monday, July 20, 2009, announcing the launch of Moon in Google Earth, an immersive 3D atlas of the Moon, accessible within Google Earth 5.0, Monday, July 20, 2009, at the Newseum in Washington. Photo Credit: (NASA/Bill Ingalls)

Google Moon Press Conference

NASA Image and Video Library

2009-07-19

Alan Eustace, Senior VP of Engineering and Research, Google, Inc., speaks during a press conference, Monday, July 20, 2009, announcing the launch of Moon in Google Earth, an immersive 3D atlas of the Moon, accessible within Google Earth 5.0, Monday, July 20, 2009, at the Newseum in Washington. Photo Credit: (NASA/Bill Ingalls)

Creating User-Friendly Tools for Data Analysis and Visualization in K-12 Classrooms: A Fortran Dinosaur Meets Generation Y

NASA Technical Reports Server (NTRS)

Chambers, L. H.; Chaudhury, S.; Page, M. T.; Lankey, A. J.; Doughty, J.; Kern, Steven; Rogerson, Tina M.

2008-01-01

During the summer of 2007, as part of the second year of a NASA-funded project in partnership with Christopher Newport University called SPHERE (Students as Professionals Helping Educators Research the Earth), a group of undergraduate students spent 8 weeks in a research internship at or near NASA Langley Research Center. Three students from this group formed the Clouds group along with a NASA mentor (Chambers), and the brief addition of a local high school student fulfilling a mentorship requirement. The Clouds group was given the task of exploring and analyzing ground-based cloud observations obtained by K-12 students as part of the Students' Cloud Observations On-Line (S'COOL) Project, and the corresponding satellite data. This project began in 1997. The primary analysis tools developed for it were in FORTRAN, a computer language none of the students were familiar with. While they persevered through computer challenges and picky syntax, it eventually became obvious that this was not the most fruitful approach for a project aimed at motivating K-12 students to do their own data analysis. Thus, about halfway through the summer the group shifted its focus to more modern data analysis and visualization tools, namely spreadsheets and Google(tm) Earth. The result of their efforts, so far, is two different Excel spreadsheets and a Google(tm) Earth file. The spreadsheets are set up to allow participating classrooms to paste in a particular dataset of interest, using the standard S'COOL format, and easily perform a variety of analyses and comparisons of the ground cloud observation reports and their correspondence with the satellite data. This includes summarizing cloud occurrence and cloud cover statistics, and comparing cloud cover measurements from the two points of view. A visual classification tool is also provided to compare the cloud levels reported from the two viewpoints. This provides a statistical counterpart to the existing S'COOL data visualization tool, which is used for individual ground-to-satellite correspondences. The Google(tm) Earth file contains a set of placemarks and ground overlays to show participating students the area around their school that the satellite is measuring. This approach will be automated and made interactive by the S'COOL database expert and will also be used to help refine the latitude/longitude location of the participating schools. Once complete, these new data analysis tools will be posted on the S'COOL website for use by the project participants in schools around the US and the world.

Using Google Earth as an innovative tool for community mapping.

PubMed

Lefer, Theodore B; Anderson, Matthew R; Fornari, Alice; Lambert, Anastasia; Fletcher, Jason; Baquero, Maria

2008-01-01

Maps are used to track diseases and illustrate the social context of health problems. However, commercial mapping software requires special training. This article illustrates how nonspecialists used Google Earth, a free program, to create community maps. The Bronx, New York, is characterized by high levels of obesity and diabetes. Residents and medical students measured the variety and quality of food and exercise sources around a residency training clinic and a student-run free clinic, using Google Earth to create maps with minimal assistance. Locations were identified using street addresses or simply by pointing to them on a map. Maps can be shared via e-mail, viewed online with Google Earth or Google Maps, and the data can be incorporated into other mapping software.

Integrating Socioeconomic and Earth Science Data Using Geobrowsers and Web Services: A Demonstration

NASA Astrophysics Data System (ADS)

Schumacher, J. A.; Yetman, G. G.

2007-12-01

The societal benefit areas identified as the focus for the Global Earth Observing System of Systems (GEOSS) 10- year implementation plan are an indicator of the importance of integrating socioeconomic data with earth science data to support decision makers. To aid this integration, CIESIN is delivering its global and U.S. demographic data to commercial and open source Geobrowsers and providing open standards based services for data access. Currently, data on population distribution, poverty, and detailed census data for the U.S. are available for visualization and access in Google Earth, NASA World Wind, and a browser-based 2-dimensional mapping client. The mapping client allows for the creation of web map documents that pull together layers from distributed servers and can be saved and shared. Visualization tools with Geobrowsers, user-driven map creation and sharing via browser-based clients, and a prototype for characterizing populations at risk to predicted precipitation deficits will be demonstrated.

Presenting Big Data in Google Earth with KML

NASA Astrophysics Data System (ADS)

Hagemark, B.

2006-12-01

KML 2.1 and Google Earth 4 provides support to enable streaming of very large datasets, with "smart" loading of data at multiple levels of resolution and incremental update to previously loaded data. This presentation demonstrates this technology for use with the Google Earth KML geometry and image primitives and shows some techniques and tools for creating this KML.

Cultural Adventures for the Google[TM] Generation

ERIC Educational Resources Information Center

Dann, Tammy

2010-01-01

Google Earth is a computer program that allows users to view the Earth through satellite imagery and maps, to see cities from above and through street views, and to search for addresses and browse locations. Many famous buildings and structures from around the world have detailed 3D views accessible on Google Earth. It is possible to explore the…

Google Mercury: The Launch of a New Planet

NASA Astrophysics Data System (ADS)

Hirshon, B.; Chapman, C. R.; Edmonds, J.; Goldstein, J.; Hallau, K. G.; Solomon, S. C.; Vanhala, H.; Weir, H. M.; Messenger Education; Public Outreach Epo Team

2010-12-01

The NASA MESSENGER mission’s Education and Public Outreach (EPO) Team, in cooperation with Google, Inc., has launched Google Mercury, an immersive new environment on the Google Earth platform. Google Mercury features hundreds of surface features, most of them newly revealed by the three flybys of the innermost planet by the MESSENGER spacecraft. As with Google Earth, Google Mercury is available on line at no cost. This presentation will demonstrate how our team worked with Google staff, features we incorporated, how games can be developed within the Google Earth platform, and how others can add tours, games, and other educational features. Finally, we will detail new enhancements to be added once MESSENGER enters into orbit about Mercury in March 2011 and begins sending back compelling images and other global data sets on a daily basis. The MESSENGER EPO Team comprises individuals from the American Association for the Advancement of Science (AAAS); Carnegie Academy for Science Education (CASE); Center for Educational Resources (CERES) at Montana State University (MSU) - Bozeman; National Center for Earth and Space Science Education (NCESSE); Johns Hopkins University Applied Physics Laboratory (JHU/APL); National Air and Space Museum (NASM); Science Systems and Applications, Inc. (SSAI); and Southwest Research Institute (SwRI). Screen shot of Google Mercury as a work in progress

Visualization of Wind Data on Google Earth for the Three-dimensional Wind Field (3DWF) Model

DTIC Science & Technology

2012-09-01

ActiveX components or XPCOM extensions can be used by JavaScript to write data to the local file system. Since there is an inherent risk, it is very...important to only use these types of objects ( ActiveX or XPCOM) from a trusted source in order to minimize the exposure of a computer system to malware

Cross-disciplinary Undergraduate Research: A Case Study in Digital Mapping, western Ireland

NASA Astrophysics Data System (ADS)

Whitmeyer, S. J.; de Paor, D. G.; Nicoletti, J.; Rivera, M.; Santangelo, B.; Daniels, J.

2008-12-01

As digital mapping technology becomes ever more advanced, field geologists spend a greater proportion of time learning digital methods relative to analyzing rocks and structures. To explore potential solutions to the time commitment implicit in learning digital field methods, we paired James Madison University (JMU) geology majors (experienced in traditional field techniques) with Worcester Polytechnic Institute (WPI) engineering students (experienced in computer applications) during a four week summer mapping project in Connemara, western Ireland. The project consisted of approximately equal parts digital field mapping (directed by the geology students), and lab-based map assembly, evaluation and formatting for virtual 3D terrains (directed by the engineering students). Students collected geologic data in the field using ruggedized handheld computers (Trimble GeoExplorer® series) with ArcPAD® software. Lab work initially focused on building geologic maps in ArcGIS® from the digital field data and then progressed to developing Google Earth-based visualizations of field data and maps. Challenges included exporting GIS data, such as locations and attributes, to KML tags for viewing in Google Earth, which we accomplished using a Linux bash script written by one of our engineers - a task outside the comfort zone of the average geology major. We also attempted to expand the scope of Google Earth by using DEMs of present-day geologically-induced landforms as representative models for paleo-geographic reconstructions of the western Ireland field area. As our integrated approach to digital field work progressed, we found that our digital field mapping produced data at a faster rate than could be effectively managed during our allotted time for lab work. This likely reflected the more developed methodology for digital field data collection, as compared with our lab-based attempts to develop new methods for 3D visualization of geologic maps. However, this experiment in cross-disciplinary undergraduate research was a big success, with an enthusiastic interchange of expertise between undergraduate geology and engineering students that produced new, cutting-edge methods for visualizing geologic data and maps.

Spatial Distribution of the Population at Risk of Cholangiocarcinoma in Chum Phaung District, Nakhon Ratchasima Province of Thailand.

PubMed

Kaewpitoon, Soraya J; Rujirakul, Ratana; Loyd, Ryan A; Matrakool, Likit; Sangkudloa, Amnat; Kaewthani, Sarochinee; Khemplila, Kritsakorn; Eaksanti, Thawatchai; Phatisena, Tanida; Kujapun, Jirawoot; Norkaew, Jun; Joosiri, Apinya; Kaewpitoon, Natthawut

2016-01-01

Cholangiocarcinoma (CCA) is a serious health problem in Thailand, particularly in northeastern and northern regions, but epidemiological studies are scarce and the spatial distribution of CCA remains to be determined. A database for the population at risk is required for monitoring, surveillance and organization of home health care. This study aim was to geo-visually display the distribution of CCA in northeast Thailand, using a geographic information system and Google Earth. A cross-sectional survey was carried out in 9 sub-districts and 133 villages in Chum Phuang district, Nakhon Ratchasima province during June and October 2015. Data on demography, and the population at risk for CCA were combined with the points of villages, sub-district boundaries, district boundaries, and points of hospitals in districts, then fed into a geographical information system. After the conversion, all of the data were imported into Google Earth for geo-visualization. A total of 11,960 from 83,096 population were included in this study. Females and male were 52.5%, and 47.8%, the age group 41-50 years old 33.3%. Individual risk for CCA was identifed and classified by using the Korat CCA verbal screening test as low (92.8%), followed by high risk (6.74%), and no (0.49%), respectively. Gender (X2-test=1143.63, p-value= 0.001), age group (X2-test==211.36, p-value=0.0001), and sub-district (X2-test=1471.858, p-value=0.0001) were significantly associated with CCA risk. Spatial distribution of the population at risk for CCA in Chum Phuang district was viewed with Google Earth. Geo-visual display followed Layer 1: District, Layer 2: Sub-district, Layer 3: Number of low risk in village, Layer 4: Number of high risk in village, and Layer 5: Hospital in Chum Phuang District and their related catchment areas. We present the first risk geo-visual display of CCA in this rural community, which is important for spatial targeting of control efforts. Risk appears to be strongly associated with gender, age group, and sub-district. Therefor, spatial distribution is suitable for the use in the further monitoring, surveillance, and home health care for CCA.

CEOS visualization environment (COVE) tool for intercalibration of satellite instruments

USGS Publications Warehouse

Kessler, P.D.; Killough, B.D.; Gowda, S.; Williams, B.R.; Chander, G.; Qu, Min

2013-01-01

Increasingly, data from multiple instruments are used to gain a more complete understanding of land surface processes at a variety of scales. Intercalibration, comparison, and coordination of satellite instrument coverage areas is a critical effort of international and domestic space agencies and organizations. The Committee on Earth Observation Satellites Visualization Environment (COVE) is a suite of browser-based applications that leverage Google Earth to display past, present, and future satellite instrument coverage areas and coincident calibration opportunities. This forecasting and ground coverage analysis and visualization capability greatly benefits the remote sensing calibration community in preparation for multisatellite ground calibration campaigns or individual satellite calibration studies. COVE has been developed for use by a broad international community to improve the efficiency and efficacy of such calibration planning efforts, whether those efforts require past, present, or future predictions. This paper provides a brief overview of the COVE tool, its validation, accuracies, and limitations with emphasis on the applicability of this visualization tool for supporting ground field campaigns and intercalibration of satellite instruments.

CEOS Visualization Environment (COVE) Tool for Intercalibration of Satellite Instruments

NASA Technical Reports Server (NTRS)

Kessler, Paul D.; Killough, Brian D.; Gowda, Sanjay; Williams, Brian R.; Chander, Gyanesh; Qu, Min

2013-01-01

Increasingly, data from multiple instruments are used to gain a more complete understanding of land surface processes at a variety of scales. Intercalibration, comparison, and coordination of satellite instrument coverage areas is a critical effort of space agencies and of international and domestic organizations. The Committee on Earth Observation Satellites Visualization Environment (COVE) is a suite of browser-based applications that leverage Google Earth to display past, present, and future satellite instrument coverage areas and coincident calibration opportunities. This forecasting and ground coverage analysis and visualization capability greatly benefits the remote sensing calibration community in preparation for multisatellite ground calibration campaigns or individual satellite calibration studies. COVE has been developed for use by a broad international community to improve the efficiency and efficacy of such calibration efforts. This paper provides a brief overview of the COVE tool, its validation, accuracies and limitations with emphasis on the applicability of this visualization tool for supporting ground field campaigns and intercalibration of satellite instruments.

Google earth mapping of damage from the Nigata-Ken-Chuetsu M6.6 earthquake of 16 July 2007

USGS Publications Warehouse

Kayen, Robert E.; Steele, WM. Clint; Collins, Brian; Walker, Kevin

2008-01-01

We describe the use of Google Earth during and after a large damaging earthquake thatstruck the central Japan coast on 16 July 2007 to collect and organize damage information and guide the reconnaissance activities. This software enabled greater real-time collaboration among scientists and engineers. After the field investigation, the Google Earth map is used as a final reporting product that was directly linked to the more traditional research report document. Finally, we analyze the use of the software within the context of a post-disaster reconnaissance investigation, and link it to student use of GoogleEarth in field situations

UNAVCO Software and Services for Visualization and Exploration of Geoscience Data

NASA Astrophysics Data System (ADS)

Meertens, C.; Wier, S.

2007-12-01

UNAVCO has been involved in visualization of geoscience data to support education and research for several years. An early and ongoing service is the Jules Verne Voyager, a web browser applet built on the GMT that displays any area on Earth, with many data set choices, including maps, satellite images, topography, geoid heights, sea-floor ages, strain rates, political boundaries, rivers and lakes, earthquake and volcano locations, focal mechanisms, stress axes, and observed and modeled plate motion and deformation velocity vectors from geodetic measurements around the world. As part of the GEON project, UNAVCO has developed the GEON IDV, a research-level, 4D (earth location, depth and/or altitude, and time), Java application for interactive display and analysis of geoscience data. The GEON IDV is designed to meet the challenge of investigating complex, multi-variate, time-varying, three-dimensional geoscience data anywhere on earth. The GEON IDV supports simultaneous displays of data sets from differing sources, with complete control over colors, time animation, map projection, map area, point of view, and vertical scale. The GEON IDV displays gridded and point data, images, GIS shape files, and several other types of data. The GEON IDV has symbols and displays for GPS velocity vectors, seismic tomography, earthquake focal mechanisms, earthquake locations with magnitude or depth, seismic ray paths in 3D, seismic anisotropy, convection model visualization, earth strain axes and strain field imagery, and high-resolution 3D topographic relief maps. Multiple data sources and display types may appear in one view. As an example of GEON IDV utility, it can display hypocenters under a volcano, a surface geology map of the volcano draped over 3D topographic relief, town locations and political boundaries, and real-time 3D weather radar clouds of volcanic ash in the atmosphere, with time animation. The GEON IDV can drive a GeoWall or other 3D stereo system. IDV output includes imagery, movies, and KML files for Google Earth use of IDV static images, where Google Earth can handle the display. The IDV can be scripted to create display images on user request or automatically on data arrival, offering the use of the IDV as a back end to support a data web site. We plan to extend the power of the IDV by accepting new data types and data services, such as GeoSciML. An active program of online and video training in GEON IDV use is planned. UNAVCO will support users who need assistance converting their data to the standard formats used by the GEON IDV. The UNAVCO Facility provides web-accessible support for Google Earth and Google Maps display of any of more than 9500 GPS stations and survey points, including metadata for each installation. UNAVCO provides corresponding Open Geospatial Consortium (OGC) web services with the same data. UNAVCO's goal is to facilitate data access, interoperability, and efficient searches, exploration, and use of data by promoting web services, standards for GEON IDV data formats and metadata, and software able to simultaneously read and display multiple data sources, formats, and map locations or projections. Retention and propagation of semantics and metadata with observational and experimental values is essential for interoperability and understanding diverse data sources.

Leveraging Global Geo-Data and Information Technologies to Bring Authentic Research Experiences to Students in Introductory Geosciences Courses

NASA Astrophysics Data System (ADS)

Ryan, J. G.

2014-12-01

The 2012 PCAST report identified the improvement of "gateway" science courses as critical to increasing the number of STEM graduates to levels commensurate with national needs. The urgent need to recruit/ retain more STEM graduates is particularly acute in the geosciences, where growth in employment opportunities, an aging workforce and flat graduation rates are leading to substantial unmet demand for geoscience-trained STEM graduates. The need to increase the number of Bachelors-level geoscience graduates was an identified priority at the Summit on the Future of Undergraduate Geoscience Education (http://www.jsg.utexas.edu/events/future-of-geoscience-undergraduateeducation/), as was the necessity of focusing on 2-year colleges, where a growing number of students are being introduced to geosciences. Undergraduate research as an instructional tool can help engage and retain students, but has largely not been part of introductory geoscience courses because of the challenge of scaling such activities for large student numbers. However, burgeoning information technology resources, including publicly available earth and planetary data repositories and freely available, intuitive data visualization platforms makes structured, in-classroom investigations of geoscience questions tractable, and open-ended student inquiry possible. Examples include "MARGINS Mini-Lessons", instructional resources developed with the support of two NSF-DUE grant awards that involve investigations of marine geosciences data resources (overseen by the Integrated Earth Data Applications (IEDA) portal: www.iedadata.org) and data visualization using GeoMapApp (www.geomapapp.org); and the growing suite of Google-Earth based data visualization and exploration activities overseen by the Google Earth in Onsite and Distance Education project (geode.net). Sample-based investigations are also viable in introductory courses, thanks to remote instrument operations technologies that allow real student participation in instrument-based data collection and interpretation. It is thus possible to model for students nearly the entire scientific process in introductory geoscience courses, allowing them to experience the excitement of "doing" science and thereby enticing more of them into the field.

NASA Google+ Hangout: 'Earthrise' A New Visualization - 45th Anniversary of Apollo 8 Viewing Earth from Space

NASA Image and Video Library

2013-12-19

Join NASA's Google+ Hangout on Friday, December 20th 2:00 - 3:00 PM (EST) at go.nasa.gov/18S2TbC It was 45 years ago, on December 24, 1968 when Apollo 8 astronauts captured 'Earthrise' – the first color photograph of Earth taken by a person in lunar orbit. NASA announces a new simulation of the events leading to the creation of 'Earthrise,' one of the iconic photographs of the 20th Century – Earth seen from the moon captured by the crew of Apollo 8. This new simulation allows anyone to virtually ride with the astronauts and experience the awe they felt at the vista in front of them. Apollo 8 Commander Frank Borman and crew members William A. Anders and James A. Lovell photographed the stunning scene as their spacecraft orbited the moon on December 24, 1968. The new computer simulation was created using data from NASA's Lunar Reconnaissance Orbiter, or LRO, spacecraft and includes details not seen in the previous visualization released last year. Participants in this Hangout include: * John Keller, project scientist for the Lunar Reconnaissance Orbiter project * Ernie Wright, project lead with the Scientific Visualization Studio at NASA Goddard Space Flight Center * Andrew Chaikin, space historian, author of the book A Man on the Moon "This will also be the first time we've released a video that's synchronized with the onboard audio recording of the astronauts,", says Ernie Wright. "The new visualization tells us not only what time the photos were taken, but also exactly which way the spacecraft was pointing and therefore which window each photo was taken from." Earthrise is the cover photo of TIME's Great Images of the 20th Century and is among photos on the cover of LIFE's 100 Photographs That Changed the World. NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Three-dimensional visualization of geographical terrain data using temporal parallax difference induction

NASA Astrophysics Data System (ADS)

Mayhew, Christopher A.; Mayhew, Craig M.

2009-02-01

Vision III Imaging, Inc. (the Company) has developed Parallax Image Display (PIDTM) software tools to critically align and display aerial images with parallax differences. Terrain features are rendered obvious to the viewer when critically aligned images are presented alternately at 4.3 Hz. The recent inclusion of digital elevation models in geographic data browsers now allows true three-dimensional parallax to be acquired from virtual globe programs like Google Earth. The authors have successfully developed PID methods and code that allow three-dimensional geographical terrain data to be visualized using temporal parallax differences.

Google Moon Press Conference

NASA Image and Video Library

2009-07-19

NASA Deputy Administrator Lori Garver, speaks during a press conference, Monday, July 20, 2009, announcing the launch of Moon in Google Earth, an immersive 3D atlas of the Moon, accessible within Google Earth 5.0, Monday, July 20, 2009, at the Newseum in Washington. Photo Credit: (NASA/Bill Ingalls)

USGS Coastal and Marine Geology Survey Data in Google Earth

NASA Astrophysics Data System (ADS)

Reiss, C.; Steele, C.; Ma, A.; Chin, J.

2006-12-01

The U.S. Geological Survey (USGS) Coastal and Marine Geology (CMG) program has a rich data catalog of geologic field activities and metadata called InfoBank, which has been a standard tool for researchers within and outside of the agency. Along with traditional web maps, the data are now accessible in Google Earth, which greatly expands the possible user audience. The Google Earth interface provides geographic orientation and panning/zooming capabilities to locate data relative to topography, bathymetry, and coastal areas. Viewing navigation with Google Earth's background imagery allows queries such as, why areas were not surveyed (answer presence of islands, shorelines, cliffs, etc.). Detailed box core subsample photos from selected sampling activities, published geotechnical data, and sample descriptions are now viewable on Google Earth, (for example, M-1-95-MB, P-2-95-MB, and P-1-97- MB box core samples). One example of the use of Google Earth is CMG's surveys of San Francisco's Ocean Beach since 2004. The surveys are conducted with an all-terrain vehicle (ATV) and shallow-water personal watercraft (PWC) equipped with Global Positioning System (GPS), and elevation and echo sounder data collectors. 3D topographic models with centimeter accuracy have been produced from these surveys to monitor beach and nearshore processes, including sand transport, sedimentation patterns, and seasonal trends. Using Google Earth, multiple track line data (examples: OB-1-05-CA and OB-2-05-CA) can be overlaid on beach imagery. The images also help explain the shape of track lines as objects are encountered.

Results of new petrologic and remote sensing studies in the Big Bend region

NASA Astrophysics Data System (ADS)

Benker, Stevan Christian

The initial section of this manuscript involves the South Rim Formation, a series of 32.2-32 Ma comenditic quartz trachytic-rhyolitic volcanics and associated intrusives, erupted and was emplaced in Big Bend National Park, Texas. Magmatic parameters have only been interpreted for one of the two diverse petrogenetic suites comprising this formation. Here, new mineralogic data for the South Rim Formation rocks are presented. Magmatic parameters interpreted from these data assist in deciphering lithospheric characteristics during the mid-Tertiary. Results indicate low temperatures (< 750 °C), reduced conditions (generally below the FMQ buffer), and low pressures (≤ 100 MPa) associated with South Rim Formation magmatism with slight conditional differences between the two suites. Newly discovered fayalite microphenocrysts allowed determination of oxygen fugacity values (between -0.14 and -0.25 DeltaFMQ over temperature ranges of 680-700 °C), via mineral equilibria based QUILF95 calculations, for Emory Peak Suite. Petrologic information is correlated with structural evidence from Trans-Pecos Texas and adjacent regions to evaluate debated timing of tectonic transition (Laramide compression to Basin and Range extension) and onset of the southern Rio Grande Rift during the mid-Tertiary. The A-type and peralkaline characteristics of the South Rim Formation and other pre-31 Ma magmatism in Trans-Pecos Texas, in addition to evidence implying earlier Rio Grande Rift onset in Colorado and New Mexico, promotes a near-neutral to transtensional setting in Trans-Pecos Texas by 32 Ma. This idea sharply contrasts with interpretations of tectonic compression and arc-related magmatism until 31 Ma as suggested by some authors. However, evidence discussed cannot preclude a pre-36 Ma proposed by other authors. The later section of this manuscript involves research in the Big Bend area using Google Earth. At present there is high interest in using Google Earth in a variety of scientific investigations. However, program developers have disclosed limited information concerning the program and its accuracy. While some authors have attempted to independently constrain the accuracy of Google Earth, their results have potentially lost validity through time due to technological advances and updates to imagery archives. For this reason we attempt to constrain more current horizontal and vertical position accuracies for the Big Bend region of West Texas. In Google Earth a series of 268 data points were virtually traced along various early Tertiary unconformities in Big Bend National Park and Big Bend Ranch State Park. These data points were compared with high precision GPS measurements collected in field and yielded a horizontal position accuracy of 2.64 meters RMSE. Complications arose in determining vertical position accuracy for Google Earth because default keyhole markup language (.kml) files currently do not export elevation data. This drawback forces users to hand record and manually input elevation values listed on screen. This is a significant handicap rendering Google Earth data useless with larger datasets. However, in a workaround solution exempted elevation values can be replaced from other data sources based on Google Earth horizontal positioning. We used Fledermaus 3D three-dimensional visualization software to drape Google Earth horizontal positions over a National Elevation Dataset (NED) digital elevation map (DEM) in order to adopt a large set of elevation data. A vertical position accuracy of 1.63 meters RMSE was determined between 268 Google Earth data points and the NED. Since determined accuracies were considerably lower than those reported in previous investigations, we devoted a later portion of this investigation to testing Google Earth-NED data in paleo-surface modeling of the Big Bend region. An 18 x 30 kilometer area in easternmost Big Ranch State Park was selected to create a post-Laramide paleo-surface model via interpolation of approximately 2900 Google Earth-NED data points representing sections of an early Tertiary unconformity. The area proved difficult to model as unconformity tracing and interpolation were often hindered by surface inflation due to regional magmatism, burial of Laramide topography by subsequent volcanism and sedimentation, and overprinting of Basin & Range extensional features masking Laramide compressional features. Despite these difficulties, a model was created illustrating paleo-topographic highs in the southeastern Bofecillos Mountains and at Lajitas Mesa. Based on the amount of surface relief depicted, inconsistency with subsequent normal faulting, and distance from magmatic features capable of surface doming or inflation, we believe the paleo-topographic highs modeled legitimately reflect the post-Laramide surface. We interpret the paleo-surface in this area as reflecting a post-Laramide surface that has experienced significant erosion. We attribute the paleo-topographic highs as Laramide topography that was more resistant. The model also implies a southern paleo-drainage direction for the area and suggests the present day topographic low through which the Rio Grande flows may have formed very soon after the Laramide Orogeny. Based on the newly calculated horizontal and vertical position accuracies for the Big Bend region and results of modeled Google Earth-NED data in easternmost Big Bend Ranch State Park, it seems Google Earth can be effectively utilized for remote sensing and geologic studies, however we urge caution as developers remain reluctant to disclose detailed program information to the public.

Google Moon Press Conference

NASA Image and Video Library

2009-07-19

Andrew Chaikin, author of "A Man on the Moon" speaks during a press conference, Monday, July 20, 2009, announcing the launch of Moon in Google Earth, an immersive 3D atlas of the Moon, accessible within Google Earth 5.0, Monday, July 20, 2009, at the Newseum in Washington. Photo Credit: (NASA/Bill Ingalls)

Google Moon Press Conference

NASA Image and Video Library

2009-07-19

Buzz Aldrin, the second man to walk on the moon, speaks during a press conference, Monday, July 20, 2009, announcing the launch of Moon in Google Earth, an immersive 3D atlas of the Moon, accessible within Google Earth 5.0, Monday, July 20, 2009, at the Newseum in Washington. Photo Credit: (NASA/Bill Ingalls)

Factors Affecting Student Success with a Google Earth-Based Earth Science Curriculum

ERIC Educational Resources Information Center

Blank, Lisa M.; Almquist, Heather; Estrada, Jen; Crews, Jeff

2016-01-01

This study investigated to what extent the implementation of a Google Earth (GE)-based earth science curriculum increased students' understanding of volcanoes, earthquakes, plate tectonics, scientific reasoning abilities, and science identity. Nine science classrooms participated in the study. In eight of the classrooms, pre- and post-assessments…

Google Moon Press Conference

NASA Image and Video Library

2009-07-19

Apollo 11 astronaut Buzz Aldrin, the second man to walk on the Moon, speaks during a press conference, Monday, July 20, 2009, announcing the launch of Moon in Google Earth, an immersive 3D atlas of the Moon, accessible within Google Earth 5.0, Monday, July 20, 2009, at the Newseum in Washington. Photo Credit: (NASA/Bill Ingalls)

Google Moon Press Conference

NASA Image and Video Library

2009-07-19

Miles O'Brien, former chief science and tech correspondent for CNN, speaks during a press conference, Monday, July 20, 2009, announcing the launch of Moon in Google Earth, an immersive 3D atlas of the Moon, accessible within Google Earth 5.0, Monday, July 20, 2009, at the Newseum in Washington. Photo Credit: (NASA/Bill Ingalls)

Google Moon Press Conference

NASA Image and Video Library

2009-07-19

Yoshinori Yoshimura, a respresentative from the Japan Aerospace Exploration Agency (JAXA), speaks during a press conference, Monday, July 20, 2009, announcing the launch of Moon in Google Earth, an immersive 3D atlas of the Moon, accessible within Google Earth 5.0, Monday, July 20, 2009, at the Newseum in Washington. Photo Credit: (NASA/Bill Ingalls)

Low-cost Tools for Aerial Video Geolocation and Air Traffic Analysis for Delay Reduction Using Google Earth

NASA Astrophysics Data System (ADS)

Zetterlind, V.; Pledgie, S.

2009-12-01

Low-cost, low-latency, robust geolocation and display of aerial video is a common need for a wide range of earth observing as well as emergency response and security applications. While hardware costs for aerial video collection systems, GPS, and inertial sensors have been decreasing, software costs for geolocation algorithms and reference imagery/DTED remain expensive and highly proprietary. As part of a Federal Small Business Innovative Research project, MosaicATM and EarthNC, Inc have developed a simple geolocation system based on the Google Earth API and Google's 'built-in' DTED and reference imagery libraries. This system geolocates aerial video based on platform and camera position, attitude, and field-of-view metadata using geometric photogrammetric principles of ray-intersection with DTED. Geolocated video can be directly rectified and viewed in the Google Earth API during processing. Work is underway to extend our geolocation code to NASA World Wind for additional flexibility and a fully open-source platform. In addition to our airborne remote sensing work, MosaicATM has developed the Surface Operations Data Analysis and Adaptation (SODAA) tool, funded by NASA Ames, which supports analysis of airport surface operations to optimize aircraft movements and reduce fuel burn and delays. As part of SODAA, MosaicATM and EarthNC, Inc have developed powerful tools to display national airspace data and time-animated 3D flight tracks in Google Earth for 4D analysis. The SODAA tool can convert raw format flight track data, FAA National Flight Data (NFD), and FAA 'Adaptation' airport surface data to a spatial database representation and then to Google Earth KML. The SODAA client provides users with a simple graphical interface through which to generate queries with a wide range of predefined and custom filters, plot results, and export for playback in Google Earth in conjunction with NFD and Adaptation overlays.

A Web-based Google-Earth Coincident Imaging Tool for Satellite Calibration and Validation

NASA Astrophysics Data System (ADS)

Killough, B. D.; Chander, G.; Gowda, S.

2009-12-01

The Group on Earth Observations (GEO) is coordinating international efforts to build a Global Earth Observation System of Systems (GEOSS) to meet the needs of its nine “Societal Benefit Areas”, of which the most demanding, in terms of accuracy, is climate. To accomplish this vision, satellite on-orbit and ground-based data calibration and validation (Cal/Val) of Earth observation measurements are critical to our scientific understanding of the Earth system. Existing tools supporting space mission Cal/Val are often developed for specific campaigns or events with little desire for broad application. This paper describes a web-based Google-Earth based tool for the calculation of coincident satellite observations with the intention to support a diverse international group of satellite missions to improve data continuity, interoperability and data fusion. The Committee on Earth Observing Satellites (CEOS), which includes 28 space agencies and 20 other national and international organizations, are currently operating and planning over 240 Earth observation satellites in the next 15 years. The technology described here will better enable the use of multiple sensors to promote increased coordination toward a GEOSS. The CEOS Systems Engineering Office (SEO) and the Working Group on Calibration and Validation (WGCV) support the development of the CEOS Visualization Environment (COVE) tool to enhance international coordination of data exchange, mission planning and Cal/Val events. The objective is to develop a simple and intuitive application tool that leverages the capabilities of Google-Earth web to display satellite sensor coverage areas and for the identification of coincident scene locations along with dynamic menus for flexibility and content display. Key features and capabilities include user-defined evaluation periods (start and end dates) and regions of interest (rectangular areas) and multi-user collaboration. Users can select two or more CEOS missions from a database including Satellite Tool Kit (STK) generated orbit information and perform rapid calculations to identify coincident scenes where the groundtracks of the CEOS mission instrument fields-of-view intersect. Calculated results are displayed on a customized Google-Earth web interface to view location and time information along with optional output to EXCEL table format. In addition, multiple viewports can be used for comparisons. COVE was first introduced to the CEOS WGCV community in May 2009. Since that time, the development of a prototype version has progressed. It is anticipated that the capabilities and applications of COVE can support a variety of international Cal/Val activities as well as provide general information on Earth observation coverage for education and societal benefit. This project demonstrates the utility of a systems engineering tool with broad international appeal for enhanced communication and data evaluation opportunities among international CEOS agencies. The COVE tool is publicly accessible via NASA servers.

Exploring Visual Evidence of Human Impact on the Environment with Planetary-Scale Zoomable Timelapse Video

NASA Astrophysics Data System (ADS)

Sargent, R.; Egge, M.; Dille, P. S.; O'Donnell, G. D.; Herwig, C.

2016-12-01

Visual evidence ignites curiosity and inspires advocacy. Zoomable imagery and video on a planetary scale provides compelling evidence of human impact on the environment. Earth Timelapse places the observable impact of 30+ years of human activity into the hands of policy makers, scientists, and advocates, with fluidity and speed that supports inquiry and exploration. Zoomability enables compelling narratives and ready apprehension of environmental changes, connecting human-scale evidence to regional and ecosystem-wide trends and changes. Leveraging the power of Google Earth Engine, join us to explore 30+ years of Landset 30m RGB imagery showing glacial retreat, agricultural deforestation, irrigation expansion, and the disappearance of lakes. These narratives are enriched with datasets showing planetary forest gain/loss, annual cycles of agricultural fires, global changes in the health of coral reefs, trends in resource extraction, and of renewable energy development. We demonstrate the intuitive and inquiry-enabling power of these planetary visualizations, and provide instruction on how scientists and advocates can create and share or contribute visualizations of their own research or topics of interest.

What Google Maps can do for biomedical data dissemination: examples and a design study.

PubMed

Jianu, Radu; Laidlaw, David H

2013-05-04

Biologists often need to assess whether unfamiliar datasets warrant the time investment required for more detailed exploration. Basing such assessments on brief descriptions provided by data publishers is unwieldy for large datasets that contain insights dependent on specific scientific questions. Alternatively, using complex software systems for a preliminary analysis may be deemed as too time consuming in itself, especially for unfamiliar data types and formats. This may lead to wasted analysis time and discarding of potentially useful data. We present an exploration of design opportunities that the Google Maps interface offers to biomedical data visualization. In particular, we focus on synergies between visualization techniques and Google Maps that facilitate the development of biological visualizations which have both low-overhead and sufficient expressivity to support the exploration of data at multiple scales. The methods we explore rely on displaying pre-rendered visualizations of biological data in browsers, with sparse yet powerful interactions, by using the Google Maps API. We structure our discussion around five visualizations: a gene co-regulation visualization, a heatmap viewer, a genome browser, a protein interaction network, and a planar visualization of white matter in the brain. Feedback from collaborative work with domain experts suggests that our Google Maps visualizations offer multiple, scale-dependent perspectives and can be particularly helpful for unfamiliar datasets due to their accessibility. We also find that users, particularly those less experienced with computer use, are attracted by the familiarity of the Google Maps API. Our five implementations introduce design elements that can benefit visualization developers. We describe a low-overhead approach that lets biologists access readily analyzed views of unfamiliar scientific datasets. We rely on pre-computed visualizations prepared by data experts, accompanied by sparse and intuitive interactions, and distributed via the familiar Google Maps framework. Our contributions are an evaluation demonstrating the validity and opportunities of this approach, a set of design guidelines benefiting those wanting to create such visualizations, and five concrete example visualizations.

What google maps can do for biomedical data dissemination: examples and a design study

PubMed Central

2013-01-01

Background Biologists often need to assess whether unfamiliar datasets warrant the time investment required for more detailed exploration. Basing such assessments on brief descriptions provided by data publishers is unwieldy for large datasets that contain insights dependent on specific scientific questions. Alternatively, using complex software systems for a preliminary analysis may be deemed as too time consuming in itself, especially for unfamiliar data types and formats. This may lead to wasted analysis time and discarding of potentially useful data. Results We present an exploration of design opportunities that the Google Maps interface offers to biomedical data visualization. In particular, we focus on synergies between visualization techniques and Google Maps that facilitate the development of biological visualizations which have both low-overhead and sufficient expressivity to support the exploration of data at multiple scales. The methods we explore rely on displaying pre-rendered visualizations of biological data in browsers, with sparse yet powerful interactions, by using the Google Maps API. We structure our discussion around five visualizations: a gene co-regulation visualization, a heatmap viewer, a genome browser, a protein interaction network, and a planar visualization of white matter in the brain. Feedback from collaborative work with domain experts suggests that our Google Maps visualizations offer multiple, scale-dependent perspectives and can be particularly helpful for unfamiliar datasets due to their accessibility. We also find that users, particularly those less experienced with computer use, are attracted by the familiarity of the Google Maps API. Our five implementations introduce design elements that can benefit visualization developers. Conclusions We describe a low-overhead approach that lets biologists access readily analyzed views of unfamiliar scientific datasets. We rely on pre-computed visualizations prepared by data experts, accompanied by sparse and intuitive interactions, and distributed via the familiar Google Maps framework. Our contributions are an evaluation demonstrating the validity and opportunities of this approach, a set of design guidelines benefiting those wanting to create such visualizations, and five concrete example visualizations. PMID:23642009

GIS Database and Google Map of the Population at Risk of Cholangiocarcinoma in Mueang Yang District, Nakhon Ratchasima Province of Thailand.

PubMed

Kaewpitoon, Soraya J; Rujirakul, Ratana; Joosiri, Apinya; Jantakate, Sirinun; Sangkudloa, Amnat; Kaewthani, Sarochinee; Chimplee, Kanokporn; Khemplila, Kritsakorn; Kaewpitoon, Natthawut

2016-01-01

Cholangiocarcinoma (CCA) is a serious problem in Thailand, particularly in the northeastern and northern regions. Database of population at risk are need required for monitoring, surveillance, home health care, and home visit. Therefore, this study aimed to develop a geographic information system (GIS) database and Google map of the population at risk of CCA in Mueang Yang district, Nakhon Ratchasima province, northeastern Thailand during June to October 2015. Populations at risk were screened using the Korat CCA verbal screening test (KCVST). Software included Microsoft Excel, ArcGIS, and Google Maps. The secondary data included the point of villages, sub-district boundaries, district boundaries, point of hospital in Mueang Yang district, used for created the spatial databese. The populations at risk for CCA and opisthorchiasis were used to create an arttribute database. Data were tranfered to WGS84 UTM ZONE 48. After the conversion, all of the data were imported into Google Earth using online web pages www.earthpoint.us. Some 222 from a 4,800 population at risk for CCA constituted a high risk group. Geo-visual display available at following www.google.com/maps/d/u/0/ edit?mid=zPxtcHv_iDLo.kvPpxl5mAs90 and hl=th. Geo-visual display 5 layers including: layer 1, village location and number of the population at risk for CCA; layer 2, sub-district health promotion hospital in Mueang Yang district and number of opisthorchiasis; layer 3, sub-district district and the number of population at risk for CCA; layer 4, district hospital and the number of population at risk for CCA and number of opisthorchiasis; and layer 5, district and the number of population at risk for CCA and number of opisthorchiasis. This GIS database and Google map production process is suitable for further monitoring, surveillance, and home health care for CCA sufferers.

Analysis of the Global Maritime Transportation System and Its Resilience

DTIC Science & Technology

2017-06-01

shortest/cheapest available route. • We establish re-routing strategies that apply, if a part of a route becomes impassable for container ships. We...The currently available throughput data is mostly from 2011, with few exceptions of 2010 and 2012. In total, there are 94 container seaports from 58...port or to the next available container port for further transportation by sea. Figure 3.5. The road layer visualized in Google Earth. Because our

Virtual Globes, where we were, are and will be

NASA Astrophysics Data System (ADS)

Dehn, J.; Webley, P. W.; Worden, A. K.

2016-12-01

Ten years ago, Google Earth was new, and the first "Virtual Globes" session was held at AGU. Only a few of us realized the potential of this technology at the time, but the idea quickly caught on. At that time a virtual globe came in two flavors, first a complex GIS system that was utterly impenetrable for the public, or a more accessible version with limited functionality and layers that was available on a desktop computer with a good internet connection. Google Earth's use of the Keyhole Markup Language opened the door for scientists and the public to share data and visualizations across disciplines and revolutionized how everyone uses geographic data. In the following 10 years, KML became more advanced, virtual globes moved to mobile and handheld platforms, and the Google Earth engine allowed for more complex data sharing among scientists. Virtual globe images went from a rare commodity to being everywhere in our lives, from weather forecasts, in our cars, on our smart-phones and shape how we receive and process data. This is a fantastic tool for education and with newer technologies can reach the the remote corners of the world and developing countries. New and emerging technologies allow for augmented reality to be merged with the globes, and for real-time data integration with sensors built into mobile devices or add-ons. This presentation will follow the history of virtual globes in the geosciences, show how robust technologies can be used in the field and classroom today, and make some suggestions for the future.

Combining Google Earth and GIS mapping technologies in a dengue surveillance system for developing countries

PubMed Central

Chang, Aileen Y; Parrales, Maria E; Jimenez, Javier; Sobieszczyk, Magdalena E; Hammer, Scott M; Copenhaver, David J; Kulkarni, Rajan P

2009-01-01

Background Dengue fever is a mosquito-borne illness that places significant burden on tropical developing countries with unplanned urbanization. A surveillance system using Google Earth and GIS mapping technologies was developed in Nicaragua as a management tool. Methods and Results Satellite imagery of the town of Bluefields, Nicaragua captured from Google Earth was used to create a base-map in ArcGIS 9. Indices of larval infestation, locations of tire dumps, cemeteries, large areas of standing water, etc. that may act as larval development sites, and locations of the homes of dengue cases collected during routine epidemiologic surveying were overlaid onto this map. Visual imagery of the location of dengue cases, larval infestation, and locations of potential larval development sites were used by dengue control specialists to prioritize specific neighborhoods for targeted control interventions. Conclusion This dengue surveillance program allows public health workers in resource-limited settings to accurately identify areas with high indices of mosquito infestation and interpret the spatial relationship of these areas with potential larval development sites such as garbage piles and large pools of standing water. As a result, it is possible to prioritize control strategies and to target interventions to highest risk areas in order to eliminate the likely origin of the mosquito vector. This program is well-suited for resource-limited settings since it utilizes readily available technologies that do not rely on Internet access for daily use and can easily be implemented in many developing countries for very little cost. PMID:19627614

The ethics of Google Earth: crossing thresholds from spatial data to landscape visualisation.

PubMed

Sheppard, Stephen R J; Cizek, Petr

2009-05-01

'Virtual globe' software systems such as Google Earth are growing rapidly in popularity as a way to visualise and share 3D environmental data. Scientists and environmental professionals, many of whom are new to 3D modeling and visual communications, are beginning routinely to use such techniques in their work. While the appeal of these techniques is evident, with unprecedented opportunities for public access to data and collaborative engagement over the web, are there nonetheless risks in their widespread usage when applied in areas of the public interest such as planning and policy-making? This paper argues that the Google Earth phenomenon, which features realistic imagery of places, cannot be dealt with only as a question of spatial data and geographic information science. The virtual globe type of visualisation crosses several key thresholds in communicating scientific and environmental information, taking it well beyond the realm of conventional spatial data and geographic information science, and engaging more complex dimensions of human perception and aesthetic preference. The realism, perspective views, and social meanings of the landscape visualisations embedded in virtual globes invoke not only cognition but also emotional and intuitive responses, with associated issues of uncertainty, credibility, and bias in interpreting the imagery. This paper considers the types of risks as well as benefits that may exist with participatory uses of virtual globes by experts and lay-people. It is illustrated with early examples from practice and relevant themes from the literature in landscape visualisation and related disciplines such as environmental psychology and landscape planning. Existing frameworks and principles for the appropriate use of environmental visualisation methods are applied to the special case of widely accessible, realistic 3D and 4D visualisation systems such as Google Earth, in the context of public awareness-building and agency decision-making on environmental issues. Relevant principles are suggested which lend themselves to much-needed evaluation of risks and benefits of virtual globe systems. Possible approaches for balancing these benefits and risks include codes of ethics, software design, and metadata templates.

Student-Teachers' Use of "Google Earth" in Problem-Based Geology Learning

ERIC Educational Resources Information Center

Ratinen, Ilkka; Keinonen, Tuula

2011-01-01

Geographical Information Systems (GIS) are adequate for analyzing complex scientific and spatial phenomena in geography education. "Google Earth" is a geographic information tool for GIS-based learning. It allows students to engage in the lesson, explore the Earth, explain what they identify and evaluate the implications of what they are…

Visualization of seismic tomography on Google Earth: Improvement of KML generator and its web application to accept the data file in European standard format

NASA Astrophysics Data System (ADS)

Yamagishi, Y.; Yanaka, H.; Tsuboi, S.

2009-12-01

We have developed a conversion tool for the data of seismic tomography into KML, called KML generator, and made it available on the web site (http://www.jamstec.go.jp/pacific21/google_earth). The KML generator enables us to display vertical and horizontal cross sections of the model on Google Earth in three-dimensional manner, which would be useful to understand the Earth's interior. The previous generator accepts text files of grid-point data having longitude, latitude, and seismic velocity anomaly. Each data file contains the data for each depth. Metadata, such as bibliographic reference, grid-point interval, depth, are described in other information file. We did not allow users to upload their own tomographic model to the web application, because there is not standard format to represent tomographic model. Recently European seismology research project, NEIRES (Network of Research Infrastructures for European Seismology), advocates that the data of seismic tomography should be standardized. They propose a new format based on JSON (JavaScript Object Notation), which is one of the data-interchange formats, as a standard one for the tomography. This format consists of two parts, which are metadata and grid-point data values. The JSON format seems to be powerful to handle and to analyze the tomographic model, because the structure of the format is fully defined by JavaScript objects, thus the elements are directly accessible by a script. In addition, there exist JSON libraries for several programming languages. The International Federation of Digital Seismograph Network (FDSN) adapted this format as a FDSN standard format for seismic tomographic model. There might be a possibility that this format would not only be accepted by European seismologists but also be accepted as the world standard. Therefore we improve our KML generator for seismic tomography to accept the data file having also JSON format. We also improve the web application of the generator so that the JSON formatted data file can be uploaded. Users can convert any tomographic model data to KML. The KML obtained through the new generator should provide an arena to compare various tomographic models and other geophysical observations on Google Earth, which may act as a common platform for geoscience browser.

Infusion of a Gaming Paradigm into Computer-Aided Engineering Design Tools

DTIC Science & Technology

2012-05-03

Virtual Test Bed (VTB), and the gaming tool, Unity3D . This hybrid gaming environment coupled a three-dimensional (3D) multibody vehicle system model...from Google Earth to the 3D visual front-end fabricated around Unity3D . The hybrid environment was sufficiently developed to support analyses of the...ndFr Cti3r4 G’OjrdFr ctior-2 The VTB simulation of the vehicle dynamics ran concurrently with and interacted with the gaming engine, Unity3D which

Next-generation Digital Earth.

PubMed

Goodchild, Michael F; Guo, Huadong; Annoni, Alessandro; Bian, Ling; de Bie, Kees; Campbell, Frederick; Craglia, Max; Ehlers, Manfred; van Genderen, John; Jackson, Davina; Lewis, Anthony J; Pesaresi, Martino; Remetey-Fülöpp, Gábor; Simpson, Richard; Skidmore, Andrew; Wang, Changlin; Woodgate, Peter

2012-07-10

A speech of then-Vice President Al Gore in 1998 created a vision for a Digital Earth, and played a role in stimulating the development of a first generation of virtual globes, typified by Google Earth, that achieved many but not all the elements of this vision. The technical achievements of Google Earth, and the functionality of this first generation of virtual globes, are reviewed against the Gore vision. Meanwhile, developments in technology continue, the era of "big data" has arrived, the general public is more and more engaged with technology through citizen science and crowd-sourcing, and advances have been made in our scientific understanding of the Earth system. However, although Google Earth stimulated progress in communicating the results of science, there continue to be substantial barriers in the public's access to science. All these factors prompt a reexamination of the initial vision of Digital Earth, and a discussion of the major elements that should be part of a next generation.

KML-Based Access and Visualization of High Resolution LiDAR Topography

NASA Astrophysics Data System (ADS)

Crosby, C. J.; Blair, J. L.; Nandigam, V.; Memon, A.; Baru, C.; Arrowsmith, J. R.

2008-12-01

Over the past decade, there has been dramatic growth in the acquisition of LiDAR (Light Detection And Ranging) high-resolution topographic data for earth science studies. Capable of providing digital elevation models (DEMs) more than an order of magnitude higher resolution than those currently available, LiDAR data allow earth scientists to study the processes that contribute to landscape evolution at resolutions not previously possible yet essential for their appropriate representation. These datasets also have significant implications for earth science education and outreach because they provide an accurate representation of landforms and geologic hazards. Unfortunately, the massive volume of data produced by LiDAR mapping technology can be a barrier to their use. To make these data available to a larger user community, we have been exploring the use of Keyhole Markup Language (KML) and Google Earth to provide access to LiDAR data products and visualizations. LiDAR digital elevation models are typically delivered in a tiled format that lends itself well to a KML-based distribution system. For LiDAR datasets hosted in the GEON OpenTopography Portal (www.opentopography.org) we have developed KML files that show the extent of available LiDAR DEMs and provide direct access to the data products. Users interact with these KML files to explore the extent of the available data and are able to select DEMs that correspond to their area of interest. Selection of a tile loads a download that the user can then save locally for analysis in their software of choice. The GEON topography system also has tools available that allow users to generate custom DEMs from LiDAR point cloud data. This system is powerful because it enables users to access massive volumes of raw LiDAR data and to produce DEM products that are optimized to their science applications. We have developed a web service that converts the custom DEM models produced by the system to a hillshade that is delivered to the user as a KML groundoverlay. The KML product enables users to quickly and easily visualize the DEMs in Google Earth. By combining internet-based LiDAR data processing with KML visualization products, users are able to execute computationally intensive data sub-setting, processing and visualization without having local access to computing resources, GIS software, or data processing expertise. Finally, GEON has partnered with the US Geological Survey to generate region-dependant network linked KML visualizations for large volumes of LiDAR derived hillshades of the Northern San Andreas fault system. These data, acquired by the NSF-funded GeoEarthScope project, offer an unprecedented look at active faults in the northern portion of the San Andreas system. Through the region-dependant network linked KML, users can seamlessly access 1 meter hillshades (both 315 and 45 degree sun angles) for the full 1400 square kilometer dataset, without downloading huge volumes of data. This type of data access has great utility for users ranging from earthquake scientists to K-12 educators who wish to introduce cutting edge real world data into their earth science lessons.

EarthScope Plate Boundary Observatory Data in the College Classroom (Invited)

NASA Astrophysics Data System (ADS)

Eriksson, S. C.; Olds, S. E.

2009-12-01

The Plate Boundary Observatory (PBO) is the geodetic component of the EarthScope project, designed to study the 3-D strain field across the active boundary zone between the Pacific and North American tectonics plates in the western United States. All PBO data are freely available to scientific and educational communities and have been incorporated into a variety of activities for college and university classrooms. UNAVCO Education and Outreach program staff have worked closely with faculty users, scientific researchers, and facility staff to create materials that are scientifically and technically accurate as well as useful to the classroom user. Availability of processed GPS data is not new to the geoscience community. However, PBO data staff have worked with education staff to deliver data that are readily accessible to educators. The UNAVCO Data for Educators webpage, incorporating an embedded Google Map with PBO GPS locations and providing current GPS time series plots and downloadable data, extends and updates the datasets available to our community. Google Earth allows the visualization GPS data with other types of datasets, e.g. LiDAR, while maintaining the self-contained and easy-to-use interface of UNAVCO’s Jules Verne Voyager map tools, which have multiple sets of geological and geophysical data. Curricular materials provide scaffolds for using EarthScope data in a variety of forms for different learning goals. Simple visualization of earthquake epicenters and locations of volcanoes can be used with velocity vectors to make simple deductions of plate boundary behaviors. Readily available time series plots provide opportunities for additional science skills, and there are web and paper-based support materials for downloading data, manipulating tables, and using plotting programs for processed GPS data. Scientists have provided contextual materials to explore the importance of these data in interpreting the structure and dynamics of the Earth. These data and their scientific context are now incorporated into the Active Earth Display developed by IRIS. Formal and informal evaluations during the past five years have provided useful data for revision and on-line implementation.

Enhancements and Evolution of the Real Time Mission Monitor

NASA Astrophysics Data System (ADS)

Goodman, M.; Blakeslee, R.; Hardin, D.; Hall, J.; He, Y.; Regner, K.

2008-12-01

The Real Time Mission Monitor (RTMM) is a visualization and information system that fuses multiple Earth science data sources, to enable real time decision-making for airborne and ground validation experiments. Developed at the National Aeronautics and Space Administration (NASA) Marshall Space Flight Center, RTMM is a situational awareness, decision-support system that integrates satellite imagery, radar, surface and airborne instrument data sets, model output parameters, lightning location observations, aircraft navigation data, soundings, and other applicable Earth science data sets. The integration and delivery of this information is made possible using data acquisition systems, network communication links, network server resources, and visualizations through the Google Earth virtual earth application. RTMM has proven extremely valuable for optimizing individual Earth science airborne field experiments. Flight planners, mission scientists, instrument scientists and program managers alike appreciate the contributions that RTMM makes to their flight projects. RTMM has received numerous plaudits from a wide variety of scientists who used RTMM during recent field campaigns including the 2006 NASA African Monsoon Multidisciplinary Analyses (NAMMA), 2007 Tropical Composition, Cloud, and Climate Coupling (TC4), 2008 Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) missions, the 2007-2008 NOAA-NASA Aerosonde Hurricane flights and the 2008 Soil Moisture Active-Passive Validation Experiment (SMAP-VEX). Improving and evolving RTMM is a continuous process. RTMM recently integrated the Waypoint Planning Tool, a Java-based application that enables aircraft mission scientists to easily develop a pre-mission flight plan through an interactive point-and-click interface. Individual flight legs are automatically calculated for altitude, latitude, longitude, flight leg distance, cumulative distance, flight leg time, cumulative time, and satellite overpass intersections. The resultant flight plan is then generated in KML and quickly posted to the Google Earth-based RTMM for planning discussions, as well as comparisons to real time flight tracks in progress. A description of the system architecture, components, and applications along with reviews and animations of RTMM during the field campaigns, plus planned enhancements and future opportunities will be presented.

Learning to Map the Earth and Planets using a Google Earth - based Multi-student Game

NASA Astrophysics Data System (ADS)

De Paor, D. G.; Wild, S. C.; Dordevic, M.

2011-12-01

We report on progress in developing an interactive geological and geophysical mapping game employing the Google Earth, Google Moon, and Goole Mars virtual globes. Working in groups of four, students represent themselves on the Google Earth surface by selecting an avatar. One of the group drives to each field stop in a model vehicle using game-like controls. When they arrive at a field stop and get out of their field vehicle, students can control their own avatars' movements independently and can communicate with one another by text message. They are geo-fenced and receive automatic messages if they wander off target. Individual movements are logged and stored in a MySQL database for later analysis. Students collaborate on mapping decisions and submit a report to their instructor through a Javascript interface to the Google Earth API. Unlike real mapping, students are not restricted by geographic access and can engage in comparative mapping on different planets. Using newly developed techniques, they can also explore and map the sub-surface down to the core-mantle boundary. Virtual specimens created with a 3D scanner, Gigapan images of outcrops, and COLLADA models of mantle structures such as subducted lithospheric slabs all contribute to an engaging learning experience.

Near real-time qualitative monitoring of lake water chlorophyll globally using GoogleEarth Engine

NASA Astrophysics Data System (ADS)

Zlinszky, András; Supan, Peter; Koma, Zsófia

2017-04-01

Monitoring ocean chlorophyll and suspended sediment has been made possible using optical satellite imaging, and has contributed immensely to our understanding of the Earth and its climate. However, lake water quality monitoring has limitations due to the optical complexity of shallow, sediment- and organic matter-laden waters. Meanwhile, timely and detailed information on basic lake water quality parameters would be essential for sustainable management of inland waters. Satellite-based remote sensing can deliver area-covering, high resolution maps of basic lake water quality parameters, but scientific application of these datasets for lake monitoring has been hindered by limitations to calibration and accuracy evaluation, and therefore access to such data has been the privilege of scientific users. Nevertheless, since for many inland waters satellite imaging is the only source of monitoring data, we believe it is urgent to make map products of chlorophyll and suspended sediment concentrations available to a wide range of users. Even if absolute accuracy can not be validated, patterns, processes and qualitative information delivered by such datasets in near-real time can act as an early warning system, raise awareness to water quality processes and serve education, in addition to complementing local monitoring activities. By making these datasets openly available on the internet through an easy to use framework, dialogue between stakeholders, management and governance authorities can be facilitated. We use GoogleEarthEngine to access and process archive and current satellite data. GoogleEarth Engine is a development and visualization framework that provides access to satellite datasets and processing capacity for analysis at the Petabyte scale. Based on earlier investigations, we chose the fluorescence line height index to represent water chlorophyll concentration. This index relies on the chlorophyll fluorescence peak at 680 nm, and has been tested for open ocean but also inland lake situations for MODIS and MERIS satellite sensor data. In addition to being relatively robust and less sensitive to atmospheric influence, this algorithm is also very simple, being based on the height of the 680 nm peak above the linear interpolation of the two neighbouring bands. However, not all satellite datasets suitable for FLH are catalogued for GoogleEarth Engine. In the current testing phase, Landsat 7, Landsat 8 (30 m resolution), and Sentinel 2 (20 m) are being tested. Landsat 7 has suitable band configuration, but has a strip error due to a sensor problem. Landsat 8 and Sentinel 2 lack a single spectral optimal for FLH. Sentinel 3 would be an optimal data source and has shown good performace during small-scale initial tests, but is not distributed globally for GoogleEarth Engine. In addition to FLH data from these satellites, our system delivers cloud and ice masking, qualitative suspended sediment data (based on the band closest to 600 nm) and true colour images, all within an easy-to-use Google Maps background. This allows on-demand understanding and interpretation of water quality patterns and processes in near real time. While the system is still under development, we believe it could significantly contribute to lake water quality management and monitoring worldwide.

Data-Driven Geospatial Visual Analytics for Real-Time Urban Flooding Decision Support

NASA Astrophysics Data System (ADS)

Liu, Y.; Hill, D.; Rodriguez, A.; Marini, L.; Kooper, R.; Myers, J.; Wu, X.; Minsker, B. S.

2009-12-01

Urban flooding is responsible for the loss of life and property as well as the release of pathogens and other pollutants into the environment. Previous studies have shown that spatial distribution of intense rainfall significantly impacts the triggering and behavior of urban flooding. However, no general purpose tools yet exist for deriving rainfall data and rendering them in real-time at the resolution of hydrologic units used for analyzing urban flooding. This paper presents a new visual analytics system that derives and renders rainfall data from the NEXRAD weather radar system at the sewershed (i.e. urban hydrologic unit) scale in real-time for a Chicago stormwater management project. We introduce a lightweight Web 2.0 approach which takes advantages of scientific workflow management and publishing capabilities developed at NCSA (National Center for Supercomputing Applications), streaming data-aware semantic content management repository, web-based Google Earth/Map and time-aware KML (Keyhole Markup Language). A collection of polygon-based virtual sensors is created from the NEXRAD Level II data using spatial, temporal and thematic transformations at the sewershed level in order to produce persistent virtual rainfall data sources for the animation. Animated color-coded rainfall map in the sewershed can be played in real-time as a movie using time-aware KML inside the web browser-based Google Earth for visually analyzing the spatiotemporal patterns of the rainfall intensity in the sewershed. Such system provides valuable information for situational awareness and improved decision support during extreme storm events in an urban area. Our further work includes incorporating additional data (such as basement flooding events data) or physics-based predictive models that can be used for more integrated data-driven decision support.

Google Earth locations of USA and seafloor hydrothermal vents with associated rare earth element data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Andrew Fowler

Google Earth .kmz files that contain the locations of geothermal wells and thermal springs in the USA, and seafloor hydrothermal vents that have associated rare earth element data. The file does not contain the actual data, the actual data is available through the GDR website in two tier 3 data sets entitled "Compilation of Rare Earth Element Analyses from US Geothermal Fields and Mid Ocean Ridge (MOR) Hydrothermal Vents" and "Rare earth element content of thermal fluids from Surprise Valley, California"

Effects of Thinking Style and Spatial Ability on Anchoring Behavior in Geographic Information Systems

ERIC Educational Resources Information Center

Wang, Dai-Yi; Lee, Mei-Hsuan; Sun, Chuen-Tsai

2013-01-01

The authors propose an instructional use for Google Earth (a GIS application) as an anchoring tool for knowledge integration. Google Earth can be used to support student explorations of world geography based on Wikipedia articles on earth science and history topics. We asked 66 Taiwanese high-school freshmen to make place marks with explanatory…

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zong, Ziliang; Job, Joshua; Zhang, Xuesong

Geo-visualization is significantly changing the way we view spatial data and discover information. On the one hand, a large number of spatial data are generated every day. On the other hand, these data are not well utilized due to the lack of free and easily used data-visualization tools. This becomes even worse when most of the spatial data remains in the form of plain text such as log files. This paper describes a way of visualizing massive plain-text spatial data at no cost by utilizing Google Earth and NASAWorld Wind. We illustrate our methods by visualizing over 170,000 global downloadmore » requests for satellite images maintained by the Earth Resources Observation and Science (EROS) Center of U.S. Geological Survey (USGS). Our visualization results identify the most popular satellite images around the world and discover the global user download patterns. The benefits of this research are: 1. assisting in improving the satellite image downloading services provided by USGS, and 2. providing a proxy for analyzing the hot spot areas of research. Most importantly, our methods demonstrate an easy way to geovisualize massive textual spatial data, which is highly applicable to mining spatially referenced data and information on a wide variety of research domains (e.g., hydrology, agriculture, atmospheric science, natural hazard, and global climate change).« less

A Web Portal-Based Time-Aware KML Animation Tool for Exploring Spatiotemporal Dynamics of Hydrological Events

NASA Astrophysics Data System (ADS)

Bao, X.; Cai, X.; Liu, Y.

2009-12-01

Understanding spatiotemporal dynamics of hydrological events such as storms and droughts is highly valuable for decision making on disaster mitigation and recovery. Virtual Globe-based technologies such as Google Earth and Open Geospatial Consortium KML standards show great promises for collaborative exploration of such events using visual analytical approaches. However, currently there are two barriers for wider usage of such approaches. First, there lacks an easy way to use open source tools to convert legacy or existing data formats such as shapefiles, geotiff, or web services-based data sources to KML and to produce time-aware KML files. Second, an integrated web portal-based time-aware animation tool is currently not available. Thus users usually share their files in the portal but have no means to visually explore them without leaving the portal environment which the users are familiar with. We develop a web portal-based time-aware KML animation tool for viewing extreme hydrologic events. The tool is based on Google Earth JavaScript API and Java Portlet standard 2.0 JSR-286, and it is currently deployable in one of the most popular open source portal frameworks, namely Liferay. We have also developed an open source toolkit kml-soc-ncsa (http://code.google.com/p/kml-soc-ncsa/) to facilitate the conversion of multiple formats into KML and the creation of time-aware KML files. We illustrate our tool using some example cases, in which drought and storm events with both time and space dimension can be explored in this web-based KML animation portlet. The tool provides an easy-to-use web browser-based portal environment for multiple users to collaboratively share and explore their time-aware KML files as well as improving the understanding of the spatiotemporal dynamics of the hydrological events.

Next-generation Digital Earth

PubMed Central

Goodchild, Michael F.; Guo, Huadong; Annoni, Alessandro; Bian, Ling; de Bie, Kees; Campbell, Frederick; Craglia, Max; Ehlers, Manfred; van Genderen, John; Jackson, Davina; Lewis, Anthony J.; Pesaresi, Martino; Remetey-Fülöpp, Gábor; Simpson, Richard; Skidmore, Andrew; Wang, Changlin; Woodgate, Peter

2012-01-01

A speech of then-Vice President Al Gore in 1998 created a vision for a Digital Earth, and played a role in stimulating the development of a first generation of virtual globes, typified by Google Earth, that achieved many but not all the elements of this vision. The technical achievements of Google Earth, and the functionality of this first generation of virtual globes, are reviewed against the Gore vision. Meanwhile, developments in technology continue, the era of “big data” has arrived, the general public is more and more engaged with technology through citizen science and crowd-sourcing, and advances have been made in our scientific understanding of the Earth system. However, although Google Earth stimulated progress in communicating the results of science, there continue to be substantial barriers in the public’s access to science. All these factors prompt a reexamination of the initial vision of Digital Earth, and a discussion of the major elements that should be part of a next generation. PMID:22723346

Discovery of Marine Datasets and Geospatial Metadata Visualization

NASA Astrophysics Data System (ADS)

Schwehr, K. D.; Brennan, R. T.; Sellars, J.; Smith, S.

2009-12-01

NOAA's National Geophysical Data Center (NGDC) provides the deep archive of US multibeam sonar hydrographic surveys. NOAA stores the data as Bathymetric Attributed Grids (BAG; http://www.opennavsurf.org/) that are HDF5 formatted files containing gridded bathymetry, gridded uncertainty, and XML metadata. While NGDC provides the deep store and a basic ERSI ArcIMS interface to the data, additional tools need to be created to increase the frequency with which researchers discover hydrographic surveys that might be beneficial for their research. Using Open Source tools, we have created a draft of a Google Earth visualization of NOAA's complete collection of BAG files as of March 2009. Each survey is represented as a bounding box, an optional preview image of the survey data, and a pop up placemark. The placemark contains a brief summary of the metadata and links to directly download of the BAG survey files and the complete metadata file. Each survey is time tagged so that users can search both in space and time for surveys that meet their needs. By creating this visualization, we aim to make the entire process of data discovery, validation of relevance, and download much more efficient for research scientists who may not be familiar with NOAA's hydrographic survey efforts or the BAG format. In the process of creating this demonstration, we have identified a number of improvements that can be made to the hydrographic survey process in order to make the results easier to use especially with respect to metadata generation. With the combination of the NGDC deep archiving infrastructure, a Google Earth virtual globe visualization, and GeoRSS feeds of updates, we hope to increase the utilization of these high-quality gridded bathymetry. This workflow applies equally well to LIDAR topography and bathymetry. Additionally, with proper referencing and geotagging in journal publications, we hope to close the loop and help the community create a true “Geospatial Scholar” infrastructure.

Google Earth as a (Not Just) Geography Education Tool

ERIC Educational Resources Information Center

Patterson, Todd C.

2007-01-01

The implementation of Geographic Information Science (GIScience) applications and discussion of GIScience-related themes are useful for teaching fundamental geographic and technological concepts. As one of the newest geographic information tools available on the World Wide Web, Google Earth has considerable potential to enhance methods for…

Interactive Computing and Processing of NASA Land Surface Observations Using Google Earth Engine

NASA Technical Reports Server (NTRS)

Molthan, Andrew; Burks, Jason; Bell, Jordan

2016-01-01

Google's Earth Engine offers a "big data" approach to processing large volumes of NASA and other remote sensing products. h\\ps://earthengine.google.com/ Interfaces include a Javascript or Python-based API, useful for accessing and processing over large periods of record for Landsat and MODIS observations. Other data sets are frequently added, including weather and climate model data sets, etc. Demonstrations here focus on exploratory efforts to perform land surface change detection related to severe weather, and other disaster events.

A Land-Use-Planning Simulation Using Google Earth

ERIC Educational Resources Information Center

Bodzin, Alec M.; Cirucci, Lori

2009-01-01

Google Earth (GE) is proving to be a valuable tool in the science classroom for understanding the environment and making responsible environmental decisions (Bodzin 2008). GE provides learners with a dynamic mapping experience using a simple interface with a limited range of functions. This interface makes geospatial analysis accessible and…

Assessing Place Location Knowledge Using a Virtual Globe

ERIC Educational Resources Information Center

Zhu, Liangfeng; Pan, Xin; Gao, Gongcheng

2016-01-01

Advances in the Google Earth virtual globe and the concomitant Keyhole Markup Language (KML) are providing educators with a convenient platform to cultivate and assess one's place location knowledge (PLK). This article presents a general framework and associated implementation methods for the online testing of PLK using Google Earth. The proposed…

Teachable Moment: Google Earth Takes Us There

ERIC Educational Resources Information Center

Williams, Ann; Davinroy, Thomas C.

2015-01-01

In the current educational climate, where clearly articulated learning objectives are required, it is clear that the spontaneous teachable moment still has its place. Authors Ann Williams and Thomas Davinroy think that instructors from almost any discipline can employ Google Earth as a tool to take advantage of teachable moments through the…

Fast segmentation of satellite images using SLIC, WebGL and Google Earth Engine

NASA Astrophysics Data System (ADS)

Donchyts, Gennadii; Baart, Fedor; Gorelick, Noel; Eisemann, Elmar; van de Giesen, Nick

2017-04-01

Google Earth Engine (GEE) is a parallel geospatial processing platform, which harmonizes access to petabytes of freely available satellite images. It provides a very rich API, allowing development of dedicated algorithms to extract useful geospatial information from these images. At the same time, modern GPUs provide thousands of computing cores, which are mostly not utilized in this context. In the last years, WebGL became a popular and well-supported API, allowing fast image processing directly in web browsers. In this work, we will evaluate the applicability of WebGL to enable fast segmentation of satellite images. A new implementation of a Simple Linear Iterative Clustering (SLIC) algorithm using GPU shaders will be presented. SLIC is a simple and efficient method to decompose an image in visually homogeneous regions. It adapts a k-means clustering approach to generate superpixels efficiently. While this approach will be hard to scale, due to a significant amount of data to be transferred to the client, it should significantly improve exploratory possibilities and simplify development of dedicated algorithms for geoscience applications. Our prototype implementation will be used to improve surface water detection of the reservoirs using multispectral satellite imagery.

Mapping of Sample Collection Data: GIS Tools for the Natural Product Researcher

PubMed Central

Oberlies, Nicholas H.; Rineer, James I.; Alali, Feras Q.; Tawaha, Khaled; Falkinham, Joseph O.; Wheaton, William D.

2009-01-01

Scientists engaged in the research of natural products often either conduct field collections themselves or collaborate with partners who do, such as botanists, mycologists, or SCUBA divers. The information gleaned from such collecting trips (e.g. longitude/latitude coordinates, geography, elevation, and a multitude of other field observations) have provided valuable data to the scientific community (e.g., biodiversity), even if it is tangential to the direct aims of the natural products research, which are often focused on drug discovery and/or chemical ecology. Geographic Information Systems (GIS) have been used to display, manage, and analyze geographic data, including collection sites for natural products. However, to the uninitiated, these tools are often beyond the financial and/or computational means of the natural product scientist. With new, free, and easy-to-use geospatial visualization tools, such as Google Earth, mapping and geographic imaging of sampling data are now within the reach of natural products scientists. The goals of the present study were to develop simple tools that are tailored for the natural products setting, thereby presenting a means to map such information, particularly via open source software like Google Earth. PMID:20161345

A virtual, interactive and dynamic excursion in Google Earth on soil management and conservation (AgroGeovid)

NASA Astrophysics Data System (ADS)

Vanwalleghem, Tom; Giráldez, Juan Vicente

2013-04-01

Many courses on natural resources require hands-on practical knowledge and experience that students traditionally could only acquire by expensive and time-consuming field excursions. New technologies and social media however provide an interesting alternative to train students and help them improve their practical knowledge. AgroGeovid is a virtual excursion, based on Google Earth, Youtube, Facebook and Twitter that is aimed at agricultural engineering students, but equally useful for any student interested in soil management and conservation, e.g. geography, geology and environmental resources. Agrogeovid provides the framework for teachers and students to upload geotagged photos, comments and discussions. After the initial startup phase, where the teacher uploaded material on e.g. soil erosion phenomena, soil conservation structures and different soil management strategies under different agronomic systems, students contributed with their own material gathered throughout the academic year. All students decided to contribute via Facebook, in stead of Twitter, which was not known to most of them. The final result was a visual and dynamic tool which students could use to train and perfect skills adopted in the classroom using case-studies and examples from their immediate environment.

Enhancements and Evolution of the Real Time Mission Monitor

NASA Technical Reports Server (NTRS)

Goodman, Michael; Blakeslee, Richard; Hardin, Danny; Hall, John; He, Yubin; Regner, Kathryn

2008-01-01

The Real Time Mission Monitor (RTMM) is a visualization and information system that fuses multiple Earth science data sources, to enable real time decision-making for airborne and ground validation experiments. Developed at the National Aeronautics and Space Administration (NASA) Marshall Space Flight Center, RTMM is a situational awareness, decision-support system that integrates satellite imagery, radar, surface and airborne instrument data sets, model output parameters, lightning location observations, aircraft navigation data, soundings, and other applicable Earth science data sets. The integration and delivery of this information is made possible using data acquisition systems, network communication links, network server resources, and visualizations through the Google Earth virtual globe application. RTMM has proven extremely valuable for optimizing individual Earth science airborne field experiments. Flight planners, mission scientists, instrument scientists and program managers alike appreciate the contributions that RTMM makes to their flight projects. We have received numerous plaudits from a wide variety of scientists who used RTMM during recent field campaigns including the 2006 NASA African Monsoon Multidisciplinary Analyses (NAMMA), 2007 Tropical Composition, Cloud, and Climate Coupling (TC4), 2008 Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) missions, the 2007-2008 NOAA-NASA Aerosonde Hurricane flights and the 2008 Soil Moisture Active-Passive Validation Experiment (SMAP-VEX). Improving and evolving RTMM is a continuous process. RTMM recently integrated the Waypoint Planning Tool, a Java-based application that enables aircraft mission scientists to easily develop a pre-mission flight plan through an interactive point-and-click interface. Individual flight legs are automatically calculated for altitude, latitude, longitude, flight leg distance, cumulative distance, flight leg time, cumulative time, and satellite overpass intersections. The resultant flight plan is then generated in KML and quickly posted to the Google Earth-based RTMM for interested scientists to view the planned flight track and then compare it to the actual real time flight progress. A description of the system architecture, components, and applications along with reviews and animations of RTMM during the field campaigns, plus planned enhancements and future opportunities will be presented.

Three-dimensional slum urban reconstruction in Envisat and Google Earth Egypt

NASA Astrophysics Data System (ADS)

Marghany, M.; Genderen, J. v.

2014-02-01

This study aims to aim to investigate the capability of ENVISAT ASAR satellite and Google Earth data for three-dimensional (3-D) slum urban reconstruction in developed country such as Egypt. The main objective of this work is to utilize 3-D automatic detection algorithm for urban slum in ENVISAT ASAR and Google Erath images were acquired in Cairo, Egypt using Fuzzy B-spline algorithm. The results show that fuzzy algorithm is the best indicator for chaotic urban slum as it can discriminate them from its surrounding environment. The combination of Fuzzy and B-spline then used to reconstruct 3-D of urban slam. The results show that urban slums, road network, and infrastructures are perfectly discriminated. It can therefore be concluded that fuzzy algorithm is an appropriate algorithm for chaotic urban slum automatic detection in ENVSIAT ASAR and Google Earth data.

Knowledge Discovery for Smart Grid Operation, Control, and Situation Awareness -- A Big Data Visualization Platform

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gu, Yi; Jiang, Huaiguang; Zhang, Yingchen

In this paper, a big data visualization platform is designed to discover the hidden useful knowledge for smart grid (SG) operation, control and situation awareness. The spawn of smart sensors at both grid side and customer side can provide large volume of heterogeneous data that collect information in all time spectrums. Extracting useful knowledge from this big-data poll is still challenging. In this paper, the Apache Spark, an open source cluster computing framework, is used to process the big-data to effectively discover the hidden knowledge. A high-speed communication architecture utilizing the Open System Interconnection (OSI) model is designed to transmitmore » the data to a visualization platform. This visualization platform uses Google Earth, a global geographic information system (GIS) to link the geological information with the SG knowledge and visualize the information in user defined fashion. The University of Denver's campus grid is used as a SG test bench and several demonstrations are presented for the proposed platform.« less

SCEC-VDO: A New 3-Dimensional Visualization and Movie Making Software for Earth Science Data

NASA Astrophysics Data System (ADS)

Milner, K. R.; Sanskriti, F.; Yu, J.; Callaghan, S.; Maechling, P. J.; Jordan, T. H.

2016-12-01

Researchers and undergraduate interns at the Southern California Earthquake Center (SCEC) have created a new 3-dimensional (3D) visualization software tool called SCEC Virtual Display of Objects (SCEC-VDO). SCEC-VDO is written in Java and uses the Visualization Toolkit (VTK) backend to render 3D content. SCEC-VDO offers advantages over existing 3D visualization software for viewing georeferenced data beneath the Earth's surface. Many popular visualization packages, such as Google Earth, restrict the user to views of the Earth from above, obstructing views of geological features such as faults and earthquake hypocenters at depth. SCEC-VDO allows the user to view data both above and below the Earth's surface at any angle. It includes tools for viewing global earthquakes from the U.S. Geological Survey, faults from the SCEC Community Fault Model, and results from the latest SCEC models of earthquake hazards in California including UCERF3 and RSQSim. Its object-oriented plugin architecture allows for the easy integration of new regional and global datasets, regardless of the science domain. SCEC-VDO also features rich animation capabilities, allowing users to build a timeline with keyframes of camera position and displayed data. The software is built with the concept of statefulness, allowing for reproducibility and collaboration using an xml file. A prior version of SCEC-VDO, which began development in 2005 under the SCEC Undergraduate Studies in Earthquake Information Technology internship, used the now unsupported Java3D library. Replacing Java3D with the widely supported and actively developed VTK libraries not only ensures that SCEC-VDO can continue to function for years to come, but allows for the export of 3D scenes to web viewers and popular software such as Paraview. SCEC-VDO runs on all recent 64-bit Windows, Mac OS X, and Linux systems with Java 8 or later. More information, including downloads, tutorials, and example movies created fully within SCEC-VDO is available here: http://scecvdo.usc.edu

Efficiently Communicating Rich Heterogeneous Geospatial Data from the FeMO2008 Dive Cruise with FlashMap on EarthRef.org

NASA Astrophysics Data System (ADS)

Minnett, R. C.; Koppers, A. A.; Staudigel, D.; Staudigel, H.

2008-12-01

EarthRef.org is comprehensive and convenient resource for Earth Science reference data and models. It encompasses four main portals: the Geochemical Earth Reference Model (GERM), the Magnetics Information Consortium (MagIC), the Seamount Biogeosciences Network (SBN), and the Enduring Resources for Earth Science Education (ERESE). Their underlying databases are publically available and the scientific community has contributed widely and is urged to continue to do so. However, the net result is a vast and largely heterogeneous warehouse of geospatial data ranging from carefully prepared maps of seamounts to geochemical data/metadata, daily reports from seagoing expeditions, large volumes of raw and processed multibeam data, images of paleomagnetic sampling sites, etc. This presents a considerable obstacle for integrating other rich media content, such as videos, images, data files, cruise tracks, and interoperable database results, without overwhelming the web user. The four EarthRef.org portals clearly lend themselves to a more intuitive user interface and has, therefore, been an invaluable test bed for the design and implementation of FlashMap, a versatile KML-driven geospatial browser written for reliability and speed in Adobe Flash. FlashMap allows layers of content to be loaded and displayed over a streaming high-resolution map which can be zoomed and panned similarly to Google Maps and Google Earth. Many organizations, from National Geographic to the USGS, have begun using Google Earth software to display geospatial content. However, Google Earth, as a desktop application, does not integrate cleanly with existing websites requiring the user to navigate away from the browser and focus on a separate application and Google Maps, written in Java Script, does not scale up reliably to large datasets. FlashMap remedies these problems as a web-based application that allows for seamless integration of the real-time display power of Google Earth and the flexibility of the web without losing scalability and control of the base maps. Our Flash-based application is fully compatible with KML (Keyhole Markup Language) 2.2, the most recent iteration of KML, allowing users with existing Google Earth KML files to effortlessly display their geospatial content embedded in a web page. As a test case for FlashMap, the annual Iron-Oxidizing Microbial Observatory (FeMO) dive cruise to the Loihi Seamount, in conjunction with data available from ongoing and published FeMO laboratory studies, showcases the flexibility of this single web-based application. With a KML 2.2 compatible web-service providing the content, any database can display results in FlashMap. The user can then hide and show multiple layers of content, potentially from several data sources, and rapidly digest a vast quantity of information to narrow the search results. This flexibility gives experienced users the ability to drill down to exactly the record they are looking for (SERC at Carleton College's educational application of FlashMap at http://serc.carleton.edu/sp/erese/activities/22223.html) and allows users familiar with Google Earth the ability to load and view geospatial data content within a browser from any computer with an internet connection.

Long-Term Audience Impacts of Live Fulldome Planetarium Lectures for Earth Science and Global Change Education

NASA Astrophysics Data System (ADS)

Yu, K. C.; Champlin, D. M.; Goldsworth, D. A.; Raynolds, R. G.; Dechesne, M.

2011-09-01

Digital Earth visualization technologies, from ArcGIS to Google Earth, have allowed for the integration of complex, disparate data sets to produce visually rich and compelling three-dimensional models of sub-surface and surface resource distribution patterns. The rendering of these models allows the public to quickly understand complicated geospatial relationships that would otherwise take much longer to explain using traditional media. At the Denver Museum of Nature & Science (DMNS), we have used such visualization technologies, including real-time virtual reality software running in the immersive digital "fulldome" Gates Planetarium, to impact the community through topical policy presentations. DMNS public lectures have covered regional issues like water resources, as well as global topics such as earthquakes, tsunamis, and resource depletion. The Gates Planetarium allows an audience to have an immersive experience-similar to virtual reality "CAVE" environments found in academia-that would otherwise not be available to the general public. Public lectures in the dome allow audiences of over 100 people to comprehend dynamically changing geospatial datasets in an exciting and engaging fashion. Surveys and interviews show that these talks are effective in heightening visitor interest in the subjects weeks or months after the presentation. Many visitors take additional steps to learn more, while one was so inspired that she actively worked to bring the same programming to her children's school. These preliminary findings suggest that fulldome real-time visualizations can have a substantial long-term impact on an audience's engagement and interest in science topics.

Google Earth Science

ERIC Educational Resources Information Center

Baird, William H.; Padgett, Clifford W.; Secrest, Jeffery A.

2015-01-01

Google Earth has made a wealth of aerial imagery available online at no cost to users. We examine some of the potential uses of that data in illustrating basic physics and astronomy, such as finding the local magnetic declination, using landmarks such as the Washington Monument and Luxor Obelisk as gnomons, and showing how airport runways get…

Using Geo-Spatial Technologies for Field Applications in Higher Geography Education

ERIC Educational Resources Information Center

Karatepe, Akif

2012-01-01

Today's important geo-spatial technologies, GIS (Geographic Information Systems), GPS (Global Positioning Systems) and Google Earth have been widely used in geography education. Transferring spatially oriented data taken by GPS to the GIS and Google Earth has provided great benefits in terms of showing the usage of spatial technologies for field…

Got the World on a Screen

ERIC Educational Resources Information Center

Adam, Anna; Mowers, Helen

2007-01-01

In this article, the authors discuss how Google Earth provides more than a geography lesson. For starters, Google Earth is perfect for teaching geography. Subscribe to Where in the World, for example, and have their students listen to podcast clues in a find-the-location game created by students worldwide. Clues relate to math (the population of…

A Virtual Tour of Plate Tectonics: Using Google Earth for Inquiry Investigations

ERIC Educational Resources Information Center

Mulvey, Bridget; Bell, Randy

2012-01-01

Google Earth is an exciting way to engage students in scientific inquiry--the foundation of science education standards and reforms. The National Science Education Standards identify inquiry as an active process that incorporates questioning, gathering and analyzing data, and thinking critically about the interplay of evidence and explanations.…

Teaching Topographic Map Skills and Geomorphology Concepts with Google Earth in a One-Computer Classroom

ERIC Educational Resources Information Center

Hsu, Hsiao-Ping; Tsai, Bor-Wen; Chen, Che-Ming

2018-01-01

Teaching high-school geomorphological concepts and topographic map reading entails many challenges. This research reports the applicability and effectiveness of Google Earth in teaching topographic map skills and geomorphological concepts, by a single teacher, in a one-computer classroom. Compared to learning via a conventional instructional…

A detailed view of Earth across space and time: our changing planet through a 32-year global Landsat and Sentinel-2 timelapse video

NASA Astrophysics Data System (ADS)

Herwig, C.

2017-12-01

The Landsat program offers an unparalleled record of our changing planet, with satellites that have been observing the Earth since 1972 to the present day. However, clouds, seasonal variation, and technical challenges around access to large volumes of data make it difficult for researchers and the public to understand global and regional scale changes across time through the planetary dataset. Earth Timelapse is a global, zoomable video that has helped revolutionize how users - millions of which have never been capable of utilizing Landsat data before - monitor and understand a changing planet. It is made from 33 cloud-free annual mosaics, one for each year from 1984 to 2016, which are made interactively explorable by Carnegie Mellon University CREATE Lab's Time Machine library, a technology for creating and viewing zoomable and pannable timelapses over space and time. Using Earth Engine, we combined over 5 million satellite images acquired over the past three decades by 5 different satellites. The majority of the images come from Landsat, a joint USGS/NASA Earth observation program that has observed the Earth since the 1970s. For 2015 and 2016, we combined Landsat 8 imagery with imagery from Sentinel-2A, part of the European Commission and European Space Agency's Copernicus Earth observation program. Along with the interactive desktop Timelapse application, we created a 200-video YouTube playlist highlighting areas across the world exhibiting change in the dataset.Earth Timelapse is an example that illustrates the power of Google Earth Engine's cloud-computing platform, which enables users such as scientists, researchers, and journalists to detect changes, map trends, and quantify differences on the Earth's surface using Google's computational infrastructure and the multi-petabyte Earth Engine data catalog. Earth Timelapse also highlights the value of data visualization to communicate with non-scientific audiences with varied technical and internet connectivity. Timelapse videos - as a global, zoomable and explorable web map across time as well as curated locations hosted on YouTube - can be effective at conveying large and medium scale land surface changes over time to diverse audiences.

Integrating Authentic Earth Science Data in Online Visualization Tools and Social Media Networking to Promote Earth Science Education

NASA Astrophysics Data System (ADS)

Carter, B. L.; Campbell, B.; Chambers, L.; Davis, A.; Riebeek, H.; Ward, K.

2008-12-01

The Goddard Space Flight Center (GSFC) is one of the largest Earth Science research-based institutions in the nation. Along with the research comes a dedicated group of people who are tasked with developing Earth science research-based education and public outreach materials to reach the broadest possible range of audiences. The GSFC Earth science education community makes use of a wide variety of platforms in order to reach their goals of communicating science. These platforms include using social media networking such as Twitter and Facebook, as well as geo-spatial tools such as MY NASA DATA, NASA World Wind, NEO, and Google Earth. Using a wide variety of platforms serves the dual purposes of promoting NASA Earth Science research and making authentic data available to educational communities that otherwise might not otherwise be granted access. Making data available to education communities promotes scientific literacy through the investigation of scientific phenomena using the same data that is used by the scientific community. Data from several NASA missions will be used to demonstrate the ways in which Earth science data are made available for the education community.

Generating and Visualizing Climate Indices using Google Earth Engine

NASA Astrophysics Data System (ADS)

Erickson, T. A.; Guentchev, G.; Rood, R. B.

2017-12-01

Climate change is expected to have largest impacts on regional and local scales. Relevant and credible climate information is needed to support the planning and adaptation efforts in our communities. The volume of climate projections of temperature and precipitation is steadily increasing, as datasets are being generated on finer spatial and temporal grids with an increasing number of ensembles to characterize uncertainty. Despite advancements in tools for querying and retrieving subsets of these large, multi-dimensional datasets, ease of access remains a barrier for many existing and potential users who want to derive useful information from these data, particularly for those outside of the climate modelling research community. Climate indices, that can be derived from daily temperature and precipitation data, such as annual number of frost days or growing season length, can provide useful information to practitioners and stakeholders. For this work the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset was loaded into Google Earth Engine, a cloud-based geospatial processing platform. Algorithms that use the Earth Engine API to generate several climate indices were written. The indices were chosen from the set developed by the joint CCl/CLIVAR/JCOMM Expert Team on Climate Change Detection and Indices (ETCCDI). Simple user interfaces were created that allow users to query, produce maps and graphs of the indices, as well as download results for additional analyses. These browser-based interfaces could allow users in low-bandwidth environments to access climate information. This research shows that calculating climate indices from global downscaled climate projection datasets and sharing them widely using cloud computing technologies is feasible. Further development will focus on exposing the climate indices to existing applications via the Earth Engine API, and building custom user interfaces for presenting climate indices to a diverse set of user groups.

Visualizing Glaciers and Sea Ice via Google Earth

NASA Astrophysics Data System (ADS)

Ballagh, L. M.; Fetterer, F.; Haran, T. M.; Pharris, K.

2006-12-01

The NOAA team at NSIDC manages over 60 distinct cryospheric and related data products. With an emphasis on data rescue and in situ data, these products hold value for both the scientific and non-scientific user communities. The overarching goal of this presentation is to promote products from two components of the cryosphere (glaciers and sea ice). Our Online Glacier Photograph Database contains approximately 3,000 photographs taken over many decades, exemplifying change in the glacier terminus over time. The sea ice product shows sea ice extent and concentration along with anomalies and trends. This Sea Ice Index product, which starts in 1979 and is updated monthly, provides visuals of the current state of sea ice in both hemispheres with trends and anomalies. The long time period covered by the data set means that many of the trends in ice extent and concentration shown in this product are statistically significant despite the large natural variability in sea ice. The minimum arctic sea ice extent has been a record low in September 2002 and 2005, contributing to an accelerated trend in sea ice reduction. With increasing world-wide interest in indicators of global climate change, and the upcoming International Polar Year, these data products are of interest to a broad audience. To further extend the impact of these data, we have made them viewable through Google Earth via the Keyhole Markup Language (KML). This presents an opportunity to branch out to a more diverse audience by using a new and innovative tool that allows spatial representation of data of significant scientific and educational interest.

MARs Tools for Interactive ANalysis (MARTIAN): Google Maps Tools for Visual Exploration of Geophysical Modeling on Mars

NASA Astrophysics Data System (ADS)

Dimitrova, L. L.; Haines, M.; Holt, W. E.; Schultz, R. A.; Richard, G.; Haines, A. J.

2006-12-01

Interactive maps of surface-breaking faults and stress models on Mars provide important tools to engage undergraduate students, educators, and scientists with current geological and geophysical research. We have developed a map based on the Google Maps API -- an Internet based tool combining DHTML and AJAX, -- which allows very large maps to be viewed over the World Wide Web. Typically, small portions of the maps are downloaded as needed, rather than the entire image at once. This set-up enables relatively fast access for users with low bandwidth. Furthermore, Google Maps provides an extensible interactive interface making it ideal for visualizing multiple data sets at the user's choice. The Google Maps API works primarily with data referenced to latitudes and longitudes, which is then mapped in Mercator projection only. We have developed utilities for general cylindrical coordinate systems by converting these coordinates into equivalent Mercator projection before including them on the map. The MARTIAN project is available at http://rock.geo.sunysb.edu/~holt/Mars/MARTIAN/. We begin with an introduction to the Martian surface using a topography model. Faults from several datasets are classified by type (extension vs. compression) and by time epoch. Deviatoric stresses due to gravitational potential energy differences, calculated from the topography and crustal thickness, can be overlain. Several quantitative measures for the fit of the stress field to the faults are also included. We provide introductory text and exercises spanning a range of topics: how are faults identified, what stress is and how it relates to faults, what gravitational potential energy is and how variations in it produce stress, how the models are created, and how these models can be evaluated and interpreted. The MARTIAN tool is used at Stony Brook University in GEO 310: Introduction to Geophysics, a class geared towards junior and senior geosciences majors. Although this project is in its early stages, high school and college teachers, as well as researchers have expressed interest in using and extending these tools for visualizing and interacting with data on Earth and other planetary bodies.

Creating a Geo-Referenced Bibliography with Google Earth and Geocommons: The Coos Bay Bibliography

ERIC Educational Resources Information Center

Schmitt, Jenni; Butler, Barb

2012-01-01

We compiled a geo-referenced bibliography of research including theses, peer-reviewed articles, agency literature, and books having sample collection sites in and around Coos Bay, Oregon. Using Google Earth and GeoCommons we created a map that allows users such as visiting researchers, faculty, students, and local agencies to identify previous…

Preparing Precipitation Data Access, Value-added Services and Scientific Exploration Tools for the Integrated Multi-satellitE Retrievals for GPM (IMERG)

NASA Astrophysics Data System (ADS)

Ostrenga, D.; Liu, Z.; Kempler, S. J.; Vollmer, B.; Teng, W. L.

2013-12-01

The Precipitation Data and Information Services Center (PDISC) (http://disc.gsfc.nasa.gov/precipitation or google: NASA PDISC), located at the NASA Goddard Space Flight Center (GSFC) Earth Sciences (GES) Data and Information Services Center (DISC), is home of the Tropical Rainfall Measuring Mission (TRMM) data archive. For over 15 years, the GES DISC has served not only TRMM, but also other space-based, airborne-based, field campaign and ground-based precipitation data products to the precipitation community and other disciplinary communities as well. The TRMM Multi-Satellite Precipitation Analysis (TMPA) products are the most popular products in the TRMM product family in terms of data download and access through Mirador, the GES-DISC Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) and other services. The next generation of TMPA, the Integrated Multi-satellitE Retrievals for GPM (IMERG) to be released in 2014 after the launch of GPM, will be significantly improved in terms of spatial and temporal resolutions. To better serve the user community, we are preparing data services and samples are listed below. To enable scientific exploration of Earth science data products without going through complicated and often time consuming processes, such as data downloading, data processing, etc., the GES DISC has developed Giovanni in consultation with members of the user community, requesting quick search, subset, analysis and display capabilities for their specific data of interest. For example, the TRMM Online Visualization and Analysis System (TOVAS, http://disc2.nascom.nasa.gov/Giovanni/tovas/) has proven extremely popular, especially as additional datasets have been added upon request. Giovanni will continue to evolve to accommodate GPM data and the multi-sensor data inter-comparisons that will be sure to follow. Additional PDISC tool and service capabilities being adapted for GPM data include: An on-line PDISC Portal (includes user guide, etc.); Data ingest, processing, distribution from on-line archive; Google-like Mirador data search and access engine; electronic distribution, Subscriptions; Uses semantic technology to help manage large amounts of multi-sensor data and their relationships; Data drill down and search capabilities; Data access through various web services, i.e., OPeNDAP, GDS, WMS, WCS; Conversion into various formats, e.g., netCDF, HDF, KML (for Google Earth), ascii; Exploration, visualization and statistical online analysis through Giovanni; Visualization and analysis of L2 data profiles and maps; Generation of derived products, such as, daily products; Parameter and spatial subsetting; Time and temporal aggregation; Regridding; Data version control and provenance; Data Stewardship - Continuous archive verification; Documentation; Science support for proper data usage, help desk; Monitoring services for applications; Expertise in data related standards and interoperability. This presentation will further describe the data services at the PDISC that are currently being utilized by precipitation science and application researchers, and the preparation plan for IMERG. Comments and feedback are welcome.

Visualize Your Data with Google Fusion Tables

NASA Astrophysics Data System (ADS)

Brisbin, K. E.

2011-12-01

Google Fusion Tables is a modern data management platform that makes it easy to host, manage, collaborate on, visualize, and publish tabular data online. Fusion Tables allows users to upload their own data to the Google cloud, which they can then use to create compelling and interactive visualizations with the data. Users can view data on a Google Map, plot data in a line chart, or display data along a timeline. Users can share these visualizations with others to explore and discover interesting trends about various types of data, including scientific data such as invasive species or global trends in disease. Fusion Tables has been used by many organizations to visualize a variety of scientific data. One example is the California Redistricting Map created by the LA Times: http://goo.gl/gwZt5 The Pacific Institute and Circle of Blue have used Fusion Tables to map the quality of water around the world: http://goo.gl/T4SX8 The World Resources Institute mapped the threat level of coral reefs using Fusion Tables: http://goo.gl/cdqe8 What attendees will learn in this session: This session will cover all the steps necessary to use Fusion Tables to create a variety of interactive visualizations. Attendees will begin by learning about the various options for uploading data into Fusion Tables, including Shapefile, KML file, and CSV file import. Attendees will then learn how to use Fusion Tables to manage their data by merging it with other data and controlling the permissions of the data. Finally, the session will cover how to create a customized visualization from the data, and share that visualization with others using both Fusion Tables and the Google Maps API.

Global positioning system & Google Earth in the investigation of an outbreak of cholera in a village of Bengaluru Urban district, Karnataka.

PubMed

Masthi, N R Ramesh; Madhusudan, M; Puthussery, Yannick P

2015-11-01

The global positioning system (GPS) technology along with Google Earth is used to measure (spatial map) the accurate distribution of morbidity, mortality and planning of interventions in the community. We used this technology to find out its role in the investigation of a cholera outbreak, and also to identify the cause of the outbreak. This study was conducted in a village near Bengaluru, Karnataka in June 2013 during a cholera outbreak. House-to-house survey was done to identify acute watery diarrhoea cases. A hand held GPS receiver was used to record north and east coordinates of the households of cases and these values were subsequently plotted on Google Earth map. Water samples were collected from suspected sources for microbiological analysis. A total of 27 cases of acute watery diarrhoea were reported. Fifty per cent of cases were in the age group of 14-44 yr and one death was reported. GPS technology and Google Earth described the accurate location of household of cases and spot map generated showed clustering of cases around the suspected water sources. The attack rate was 6.92 per cent and case fatality rate was 3.7 per cent. Water samples collected from suspected sources showed the presence of Vibrio cholera O1 Ogawa. GPS technology and Google Earth were easy to use, helpful to accurately pinpoint the location of household of cases, construction of spot map and follow up of cases. Outbreak was found to be due to contamination of drinking water sources.

Accuracy comparison in mapping water bodies using Landsat images and Google Earth Images

NASA Astrophysics Data System (ADS)

Zhou, Z.; Zhou, X.

2016-12-01

A lot of research has been done for the extraction of water bodies with multiple satellite images. The Water Indexes with the use of multi-spectral images are the mostly used methods for the water bodies' extraction. In order to extract area of water bodies from satellite images, accuracy may depend on the spatial resolution of images and relative size of the water bodies. To quantify the impact of spatial resolution and size (major and minor lengths) of the water bodies on the accuracy of water area extraction, we use Georgetown Lake, Montana and coalbed methane (CBM) water retention ponds in the Montana Powder River Basin as test sites to evaluate the impact of spatial resolution and the size of water bodies on water area extraction. Data sources used include Landsat images and Google Earth images covering both large water bodies and small ponds. Firstly we used water indices to extract water coverage from Landsat images for both large lake and small ponds. Secondly we used a newly developed visible-index method to extract water coverage from Google Earth images covering both large lake and small ponds. Thirdly, we used the image fusion method in which the Google Earth Images are fused with multi-spectral Landsat images to obtain multi-spectral images of the same high spatial resolution as the Google earth images. The actual area of the lake and ponds are measured using GPS surveys. Results will be compared and the optimal method will be selected for water body extraction.

The Effect of Google Earth and Wiki Models on Oral Presentation Skills of University EFL Learners

ERIC Educational Resources Information Center

Awada, Ghada; Diab, Hassan B.

2018-01-01

This article reports the results of an experimental study that investigated the effectiveness of Google Earth and Wiki tools in improving the oral presentation skills of English as a Foreign Language (EFL) learners and boosting their motivation for learning. The participants (n =81) are enrolled in writing classes at two English-medium…

Utilizing Google Earth to Teach Students about Global Oil Spill Disasters

ERIC Educational Resources Information Center

Guertin, Laura; Neville, Sara

2011-01-01

The United States is currently experiencing its worst man-made environmental disaster, the BP Deepwater Horizon oil leak. The Gulf of Mexico oil spill is severe in its impact, but it is only one of several global oil spill disasters in history. Students can utilize the technology of Google Earth to explore the spatial and temporal distribution of…

KML-based teaching lessons developed by Google in partnership with the University of Alaska.

NASA Astrophysics Data System (ADS)

Kolb, E. J.; Bailey, J.; Bishop, A.; Cain, J.; Goddard, M.; Hurowitz, K.; Kennedy, K.; Ornduff, T.; Sfraga, M.; Wernecke, J.

2008-12-01

The focus of Google's Geo Education outreach efforts (http://www.google.com/educators/geo.html) is on helping primary, secondary, and post-secondary educators incorporate Google Earth and Sky, Google Maps, and SketchUp into their classroom lessons. In this poster and demonstration, we will show our KML-based science lessons that were developed in partnership with the University of Alaska and used in classroom teachings by our team to Alaskan high-school students.

Using geovisual analytics in Google Earth to understand disease distribution: a case study of campylobacteriosis in the Czech Republic (2008-2012).

PubMed

Marek, Lukáš; Tuček, Pavel; Pászto, Vít

2015-01-28

Visual analytics aims to connect the processing power of information technologies and the user's ability of logical thinking and reasoning through the complex visual interaction. Moreover, the most of the data contain the spatial component. Therefore, the need for geovisual tools and methods arises. Either one can develop own system but the dissemination of findings and its usability might be problematic or the widespread and well-known platform can be utilized. The aim of this paper is to prove the applicability of Google Earth™ software as a tool for geovisual analytics that helps to understand the spatio-temporal patterns of the disease distribution. We combined the complex joint spatio-temporal analysis with comprehensive visualisation. We analysed the spatio-temporal distribution of the campylobacteriosis in the Czech Republic between 2008 and 2012. We applied three main approaches in the study: (1) the geovisual analytics of the surveillance data that were visualised in the form of bubble chart; (2) the geovisual analytics of the disease's weekly incidence surfaces computed by spatio-temporal kriging and (3) the spatio-temporal scan statistics that was employed in order to identify high or low rates clusters of affected municipalities. The final data are stored in Keyhole Markup Language files and visualised in Google Earth™ in order to apply geovisual analytics. Using geovisual analytics we were able to display and retrieve information from complex dataset efficiently. Instead of searching for patterns in a series of static maps or using numerical statistics, we created the set of interactive visualisations in order to explore and communicate results of analyses to the wider audience. The results of the geovisual analytics identified periodical patterns in the behaviour of the disease as well as fourteen spatio-temporal clusters of increased relative risk. We prove that Google Earth™ software is a usable tool for the geovisual analysis of the disease distribution. Google Earth™ has many indisputable advantages (widespread, freely available, intuitive interface, space-time visualisation capabilities and animations, communication of results), nevertheless it is still needed to combine it with pre-processing tools that prepare the data into a form suitable for the geovisual analytics itself.

Using NASA's Giovanni Web Portal to Access and Visualize Satellite-Based Earth Science Data in the Classroom

NASA Astrophysics Data System (ADS)

Lloyd, S. A.; Acker, J. G.; Prados, A. I.; Leptoukh, G. G.

2008-12-01

One of the biggest obstacles for the average Earth science student today is locating and obtaining satellite- based remote sensing datasets in a format that is accessible and optimal for their data analysis needs. At the Goddard Earth Sciences Data and Information Services Center (GES-DISC) alone, on the order of hundreds of Terabytes of data are available for distribution to scientists, students and the general public. The single biggest and time-consuming hurdle for most students when they begin their study of the various datasets is how to slog through this mountain of data to arrive at a properly sub-setted and manageable dataset to answer their science question(s). The GES DISC provides a number of tools for data access and visualization, including the Google-like Mirador search engine and the powerful GES-DISC Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) web interface. Giovanni provides a simple way to visualize, analyze and access vast amounts of satellite-based Earth science data. Giovanni's features and practical examples of its use will be demonstrated, with an emphasis on how satellite remote sensing can help students understand recent events in the atmosphere and biosphere. Giovanni is actually a series of sixteen similar web-based data interfaces, each of which covers a single satellite dataset (such as TRMM, TOMS, OMI, AIRS, MLS, HALOE, etc.) or a group of related datasets (such as MODIS and MISR for aerosols, SeaWIFS and MODIS for ocean color, and the suite of A-Train observations co-located along the CloudSat orbital path). Recently, ground-based datasets have been included in Giovanni, including the Northern Eurasian Earth Science Partnership Initiative (NEESPI), and EPA fine particulate matter (PM2.5) for air quality. Model data such as the Goddard GOCART model and MERRA meteorological reanalyses (in process) are being increasingly incorporated into Giovanni to facilitate model- data intercomparison. A full suite of data analysis and visualization tools is also available within Giovanni. The GES DISC is currently developing a systematic series of training modules for Earth science satellite data, associated with our development of additional datasets and data visualization tools for Giovanni. Training sessions will include an overview of the Earth science datasets archived at Goddard, an overview of terms and techniques associated with satellite remote sensing, dataset-specific issues, an overview of Giovanni functionality, and a series of examples of how data can be readily accessed and visualized.

From Analysis to Impact: Challenges and Outcomes from Google's Cloud-based Platforms for Analyzing and Leveraging Petapixels of Geospatial Data

NASA Astrophysics Data System (ADS)

Thau, D.

2017-12-01

For the past seven years, Google has made petabytes of Earth observation data, and the tools to analyze it, freely available to researchers around the world via cloud computing. These data and tools were initially available via Google Earth Engine and are increasingly available on the Google Cloud Platform. We have introduced a number of APIs for both the analysis and presentation of geospatial data that have been successfully used to create impactful datasets and web applications, including studies of global surface water availability, global tree cover change, and crop yield estimation. Each of these projects used the cloud to analyze thousands to millions of Landsat scenes. The APIs support a range of publishing options, from outputting imagery and data for inclusion in papers, to providing tools for full scale web applications that provide analysis tools of their own. Over the course of developing these tools, we have learned a number of lessons about how to build a publicly available cloud platform for geospatial analysis, and about how the characteristics of an API can affect the kinds of impacts a platform can enable. This study will present an overview of how Google Earth Engine works and how Google's geospatial capabilities are extending to Google Cloud Platform. We will provide a number of case studies describing how these platforms, and the data they host, have been leveraged to build impactful decision support tools used by governments, researchers, and other institutions, and we will describe how the available APIs have shaped (or constrained) those tools. [Image Credit: Tyler A. Erickson

Mean composite fire severity metrics computed with Google Earth engine offer improved accuracy and expanded mapping potential

Treesearch

Sean A. Parks; Lisa M. Holsinger; Morgan A. Voss; Rachel A. Loehman; Nathaniel P. Robinson

2018-01-01

Landsat-based fire severity datasets are an invaluable resource for monitoring and research purposes. These gridded fire severity datasets are generally produced with pre- and post-fire imagery to estimate the degree of fire-induced ecological change. Here, we introduce methods to produce three Landsat-based fire severity metrics using the Google Earth Engine (GEE)...

Elevation data fitting and precision analysis of Google Earth in road survey

NASA Astrophysics Data System (ADS)

Wei, Haibin; Luan, Xiaohan; Li, Hanchao; Jia, Jiangkun; Chen, Zhao; Han, Leilei

2018-05-01

Objective: In order to improve efficiency of road survey and save manpower and material resources, this paper intends to apply Google Earth to the feasibility study stage of road survey and design. Limited by the problem that Google Earth elevation data lacks precision, this paper is focused on finding several different fitting or difference methods to improve the data precision, in order to make every effort to meet the accuracy requirements of road survey and design specifications. Method: On the basis of elevation difference of limited public points, any elevation difference of the other points can be fitted or interpolated. Thus, the precise elevation can be obtained by subtracting elevation difference from the Google Earth data. Quadratic polynomial surface fitting method, cubic polynomial surface fitting method, V4 interpolation method in MATLAB and neural network method are used in this paper to process elevation data of Google Earth. And internal conformity, external conformity and cross correlation coefficient are used as evaluation indexes to evaluate the data processing effect. Results: There is no fitting difference at the fitting point while using V4 interpolation method. Its external conformity is the largest and the effect of accuracy improvement is the worst, so V4 interpolation method is ruled out. The internal and external conformity of the cubic polynomial surface fitting method both are better than those of the quadratic polynomial surface fitting method. The neural network method has a similar fitting effect with the cubic polynomial surface fitting method, but its fitting effect is better in the case of a higher elevation difference. Because the neural network method is an unmanageable fitting model, the cubic polynomial surface fitting method should be mainly used and the neural network method can be used as the auxiliary method in the case of higher elevation difference. Conclusions: Cubic polynomial surface fitting method can obviously improve data precision of Google Earth. The error of data in hilly terrain areas meets the requirement of specifications after precision improvement and it can be used in feasibility study stage of road survey and design.

Towards a geospatial wikipedia

NASA Astrophysics Data System (ADS)

Fritz, S.; McCallum, I.; Schill, C.; Perger, C.; Kraxner, F.; Obersteiner, M.

2009-04-01

Based on the Google Earth (http://earth.google.com) platform we have developed a geospatial Wikipedia (geo-wiki.org). The tool allows everybody in the world to contribute to spatial validation and is made available to the internet community interested in that task. We illustrate how this tool can be used for different applications. In our first application we combine uncertainty hotspot information from three global land cover datasets (GLC, MODIS, GlobCover). With an ever increasing amount of high resolution images available on Google Earth, it is becoming increasingly possible to distinguish land cover features with a high degree of accuracy. We first direct the land cover validation community to certain hotspots of land cover uncertainty and then ask them to fill in a small popup menu on type of land cover, possibly a picture at that location with the different cardinal points as well as date and what type of validation was chosen (google earth imagery/panoramio or if the person has ground truth data). We have implemented the tool via a land cover validation community at FACEBOOK which is based on a snowball system which allows the tracking of individuals and the possibility to ignore users which misuse the system. In a second application we illustrate how the tool could possibly be used for mapping malaria occurrence and small water bodies as well as overall malaria risk. For this application we have implemented a polygon as well as attribute function using Google maps as along with virtual earth using openlayers. The third application deals with illegal logging and how an alert system for illegal logging detection within a certain land tenure system could be implemented. Here we show how the tool can be used to document illegal logging via a YouTube video.

Visualization of Client-Side Web Browsing and Email Activity

DTIC Science & Technology

2009-06-01

mantenimiento the amazing race dustin & candice oskar schindler mythbusters femjoy 080814-kathi in peace anna_ac_-_elixia miley cyrus mapa linea 12 metro... mantenimiento www.google.com.mx alcohol isopropilico www.google.com.mx descargas rapidshare corta final firefox www.google.com.mx desactivar

Predicting the performance of local seismic networks using Matlab and Google Earth.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chael, Eric Paul

2009-11-01

We have used Matlab and Google Earth to construct a prototype application for modeling the performance of local seismic networks for monitoring small, contained explosions. Published equations based on refraction experiments provide estimates of peak ground velocities as a function of event distance and charge weight. Matlab routines implement these relations to calculate the amplitudes across a network of stations from sources distributed over a geographic grid. The amplitudes are then compared to ambient noise levels at the stations, and scaled to determine the smallest yield that could be detected at each source location by a specified minimum number ofmore » stations. We use Google Earth as the primary user interface, both for positioning the stations of a hypothetical local network, and for displaying the resulting detection threshold contours.« less

Finding the Shape of Space

DTIC Science & Technology

2011-07-01

currently valid OMB control number. 1. REPORT DATE JUL 2011 2. REPORT TYPE 3. DATES COVERED 00-00-2011 to 00-00-2011 4. TITLE AND SUBTITLE...1 Lt Col Christopher C. Shannon Maj Tosha N. Meredith 2 GOOGLE EARTH TUBE: PROSPECTS FOR FULL MOTION VIDEO FROM SPACE . . . . . . . 5...Google Earth Tube,” a virtual environment that provides an extraordinary amount of information to whoever accesses it, sets the stage for improved

Optimum Antenna Configuration for Maximizing Access Point Range of an IEEE 802.11 Wireless Mesh Network in Support of Multi-Mission Operations Relative to Hastily Formed Scalable Deployments

DTIC Science & Technology

2007-09-01

Configuration Consideration ...........................54 C. MAE NGAT DAM, CHIANG MAI , THAILAND, FIELD EXPERIMENT...2006 802.11 Network Topology Mae Ngat Dam, Chiang Mai , Thailand.......................39 Figure 31. View of COASTS 2006 802.11 Topology...Requirements (Background From Google Earth).....62 Figure 44. Mae Ngat Dam, Chiang Mai , Thailand (From Google Earth

Naive (commonsense) geography and geobrowser usability after ten years of Google Earth

NASA Astrophysics Data System (ADS)

Hamerlinck, J. D.

2016-04-01

In 1995, the concept of ‘naive geography’ was formally introduced as an area of cognitive geographic information science representing ‘the body of knowledge that people have about the surrounding geographic world’ and reflecting ‘the way people think and reason about geographic space and time, both consciously and subconsciously’. The need to incorporate such commonsense knowledge and reasoning into design of geospatial technologies was identified but faced challenges in formalizing these relationships and processes in software implementation. Ten years later, the Google Earth geobrowser was released, marking the beginning of a new era of open access to, and application of, geographic data and information in society. Fast-forward to today, and the opportunity presents itself to take stock of twenty years of naive geography and a decade of the ubiquitous virtual globe. This paper introduces an ongoing research effort to explore the integration of naive (or commonsense) geography concepts in the Google Earth geobrowser virtual globe and their possible impact on Google Earth's usability, utility, and usefulness. A multi-phase methodology is described, combining usability reviews and usability testing with use-case scenarios involving the U.S.-Canadian Yellowstone to Yukon Initiative. Initial progress on a usability review combining cognitive walkthroughs and heuristics evaluation is presented.

Copernicus Big Data and Google Earth Engine for Glacier Surface Velocity Field Monitoring: Feasibility Demonstration on San Rafael and San Quintin Glaciers

NASA Astrophysics Data System (ADS)

Di Tullio, M.; Nocchi, F.; Camplani, A.; Emanuelli, N.; Nascetti, A.; Crespi, M.

2018-04-01

The glaciers are a natural global resource and one of the principal climate change indicator at global and local scale, being influenced by temperature and snow precipitation changes. Among the parameters used for glacier monitoring, the surface velocity is a key element, since it is connected to glaciers changes (mass balance, hydro balance, glaciers stability, landscape erosion). The leading idea of this work is to continuously retrieve glaciers surface velocity using free ESA Sentinel-1 SAR imagery and exploiting the potentialities of the Google Earth Engine (GEE) platform. GEE has been recently released by Google as a platform for petabyte-scale scientific analysis and visualization of geospatial datasets. The algorithm of SAR off-set tracking developed at the Geodesy and Geomatics Division of the University of Rome La Sapienza has been integrated in a cloud based platform that automatically processes large stacks of Sentinel-1 data to retrieve glacier surface velocity field time series. We processed about 600 Sentinel-1 image pairs to obtain a continuous time series of velocity field measurements over 3 years from January 2015 to January 2018 for two wide glaciers located in the Northern Patagonian Ice Field (NPIF), the San Rafael and the San Quintin glaciers. Several results related to these relevant glaciers also validated with respect already available and renown software (i.e. ESA SNAP, CIAS) and with respect optical sensor measurements (i.e. LANDSAT8), highlight the potential of the Big Data analysis to automatically monitor glacier surface velocity fields at global scale, exploiting the synergy between GEE and Sentinel-1 imagery.

CloudSat Reflectivity Data Visualization Inside Hurricanes

NASA Technical Reports Server (NTRS)

Suzuki, Shigeru; Wright, John R.; Falcon, Pedro C.

2011-01-01

Animations and other outreach products have been created and released to the public quickly after the CloudSat spacecraft flew over hurricanes. The automated script scans through the CloudSat quicklook data to find significant atmospheric moisture content. Once such a region is found, data from multiple sources is combined to produce the data products and the animations. KMZ products are quickly generated from the quicklook data for viewing in Google Earth and other tools. Animations are also generated to show the atmospheric moisture data in context with the storm cloud imagery. Global images from GOES satellites are shown to give context. The visualization provides better understanding of the interior of the hurricane storm clouds, which is difficult to observe directly. The automated process creates the finished animation in the High Definition (HD) video format for quick release to the media and public.

Visualization and Ontology of Geospatial Intelligence

NASA Astrophysics Data System (ADS)

Chan, Yupo

Recent events have deepened our conviction that many human endeavors are best described in a geospatial context. This is evidenced in the prevalence of location-based services, as afforded by the ubiquitous cell phone usage. It is also manifested by the popularity of such internet engines as Google Earth. As we commute to work, travel on business or pleasure, we make decisions based on the geospatial information provided by such location-based services. When corporations devise their business plans, they also rely heavily on such geospatial data. By definition, local, state and federal governments provide services according to geographic boundaries. One estimate suggests that 85 percent of data contain spatial attributes.

IDP camp evolvement analysis in Darfur using VHSR optical satellite image time series and scientific visualization on virtual globes

NASA Astrophysics Data System (ADS)

Tiede, Dirk; Lang, Stefan

2010-11-01

In this paper we focus on the application of transferable, object-based image analysis algorithms for dwelling extraction in a camp for internally displaced people (IDP) in Darfur, Sudan along with innovative means for scientific visualisation of the results. Three very high spatial resolution satellite images (QuickBird: 2002, 2004, 2008) were used for: (1) extracting different types of dwellings and (2) calculating and visualizing added-value products such as dwelling density and camp structure. The results were visualized on virtual globes (Google Earth and ArcGIS Explorer) revealing the analysis results (analytical 3D views,) transformed into the third dimension (z-value). Data formats depend on virtual globe software including KML/KMZ (keyhole mark-up language) and ESRI 3D shapefiles streamed as ArcGIS Server-based globe service. In addition, means for improving overall performance of automated dwelling structures using grid computing techniques are discussed using examples from a similar study.

CEO Sites Mission Management System (SMMS)

NASA Technical Reports Server (NTRS)

Trenchard, Mike

2014-01-01

Late in fiscal year 2011, the Crew Earth Observations (CEO) team was tasked to upgrade its science site database management tool, which at the time was integrated with the Automated Mission Planning System (AMPS) originally developed for Earth Observations mission planning in the 1980s. Although AMPS had been adapted and was reliably used by CEO for International Space Station (ISS) payload operations support, the database structure was dated, and the compiler required for modifications would not be supported in the Windows 7 64-bit operating system scheduled for implementation the following year. The Sites Mission Management System (SMMS) is now the tool used by CEO to manage a heritage Structured Query Language (SQL) database of more than 2,000 records for Earth science sites. SMMS is a carefully designed and crafted in-house software package with complete and detailed help files available for the user and meticulous internal documentation for future modifications. It was delivered in February 2012 for test and evaluation. Following acceptance, it was implemented for CEO mission operations support in April 2012. The database spans the period from the earliest systematic requests for astronaut photography during the shuttle era to current ISS mission support of the CEO science payload. Besides logging basic image information (site names, locations, broad application categories, and mission requests), the upgraded database management tool now tracks dates of creation, modification, and activation; imagery acquired in response to requests; the status and location of ancillary site information; and affiliations with studies, their sponsors, and collaborators. SMMS was designed to facilitate overall mission planning in terms of site selection and activation and provide the necessary site parameters for the Satellite Tool Kit (STK) Integrated Message Production List Editor (SIMPLE), which is used by CEO operations to perform daily ISS mission planning. The CEO team uses the SMMS for three general functions - database queries of content and status, individual site creation and updates, and mission planning. The CEO administrator of the science site database is able to create or modify the content of sites and activate or deactivate them based on the requirements of the sponsors. The administrator supports and implements ISS mission planning by assembling, reporting, and activating mission-specific site selections for management; deactivating sites as requirements are met; and creating new sites, such as International Charter sites for disasters, as circumstances warrant. In addition to the above CEO internal uses, when site planning for a specific ISS mission is complete and approved, the SMMS can produce and export those essential site database elements for the mission into XML format for use by onboard Earth-location systems, such as Worldmap. The design, development, and implementation of the SMMS resulted in a superior database management system for CEO science sites by focusing on the functions and applications of the database alone instead of integrating the database with the multipurpose configuration of the AMPS. Unlike the AMPS, it can function and be modified within the existing Windows 7 environment. The functions and applications of the SMMS were expanded to accommodate more database elements, report products, and a streamlined interface for data entry and review. A particularly elegant enhancement in data entry was the integration of the Google Earth application for the visual display and definition of site coordinates for site areas defined by multiple coordinates. Transfer between the SMMS and Google Earth is accomplished with a Keyhole Markup Language (KML) expression of geographic data (see figures 3 and 4). Site coordinates may be entered into the SMMS panel directly for display in Google Earth, or the coordinates may be defined on the Google Earth display as a mouse-controlled polygonal definition and transferred back into the SMMS as KML input. This significantly reduces the possibility of errors in coordinate entries and provides visualization of the scale of the site being defined. CEO now has a powerful tool for managing and defining sites on the Earth's surface for both targets of astronaut photography or other onboard remote sensing systems. It can also record and track results by sponsor, collaborator, or type of study.

Virtual Observatories for Space Physics Observations and Simulations: New Routes to Efficient Access and Visualization

NASA Technical Reports Server (NTRS)

Roberts, Aaron

2005-01-01

New tools for data access and visualization promise to make the analysis of space plasma data both more efficient and more powerful, especially for answering questions about the global structure and dynamics of the Sun-Earth system. We will show how new existing tools (particularly the Virtual Space Physics Observatory-VSPO-and the Visual System for Browsing, Analysis and Retrieval of Data-ViSBARD; look for the acronyms in Google) already provide rapid access to such information as spacecraft orbits, browse plots, and detailed data, as well as visualizations that can quickly unite our view of multispacecraft observations. We will show movies illustrating multispacecraft observations of the solar wind and magnetosphere during a magnetic storm, and of simulations of 3 0-spacecraft observations derived from MHD simulations of the magnetosphere sampled along likely trajectories of the spacecraft for the MagCon mission. An important issue remaining to be solved is how best to integrate simulation data and services into the Virtual Observatory environment, and this talk will hopefully stimulate further discussion along these lines.

Web GIS in practice V: 3-D interactive and real-time mapping in Second Life

PubMed Central

Boulos, Maged N Kamel; Burden, David

2007-01-01

This paper describes technologies from Daden Limited for geographically mapping and accessing live news stories/feeds, as well as other real-time, real-world data feeds (e.g., Google Earth KML feeds and GeoRSS feeds) in the 3-D virtual world of Second Life, by plotting and updating the corresponding Earth location points on a globe or some other suitable form (in-world), and further linking those points to relevant information and resources. This approach enables users to visualise, interact with, and even walk or fly through, the plotted data in 3-D. Users can also do the reverse: put pins on a map in the virtual world, and then view the data points on the Web in Google Maps or Google Earth. The technologies presented thus serve as a bridge between mirror worlds like Google Earth and virtual worlds like Second Life. We explore the geo-data display potential of virtual worlds and their likely convergence with mirror worlds in the context of the future 3-D Internet or Metaverse, and reflect on the potential of such technologies and their future possibilities, e.g. their use to develop emergency/public health virtual situation rooms to effectively manage emergencies and disasters in real time. The paper also covers some of the issues associated with these technologies, namely user interface accessibility and individual privacy. PMID:18042275

Conceptual Learning Outcomes of Virtual Experiential Learning: Results of Google Earth Exploration in Introductory Geoscience Courses

NASA Astrophysics Data System (ADS)

Bitting, Kelsey S.; McCartney, Marsha J.; Denning, Kathy R.; Roberts, Jennifer A.

2018-06-01

Virtual globe programs such as Google Earth replicate real-world experiential learning of spatial and geographic concepts by allowing students to navigate across our planet without ever leaving campus. However, empirical evidence for the learning value of these technological tools and the experience students gain by exploration assignments framed within them remains to be quantified and compared by student demographics. This study examines the impact of a Google Earth-based exploration assignment on conceptual understanding in introductory geoscience courses at a research university in the US Midwest using predominantly traditional college-age students from a range of majors. Using repeated-measures ANOVA and paired-samples t tests, we test the significance of the activity using pretest and posttest scores on a subset of items from the Geoscience Concept Inventory, and the interactive effects of student gender and ethnicity on student score improvement. Analyses show that learning from the Google Earth exploration activity is highly significant overall and for all but one of the concept inventory items. Furthermore, we find no significant interactive effects of class format, student gender, or student ethnicity on the magnitude of the score increases. These results provide strong support for the use of experiential learning in virtual globe environments for students in introductory geoscience and perhaps other disciplines for which direct observation of our planet's surface is conceptually relevant.

Real-time bus location monitoring using Arduino

NASA Astrophysics Data System (ADS)

Ibrahim, Mohammad Y. M.; Audah, Lukman

2017-09-01

The Internet of Things (IoT) is the network of objects, such as a vehicles, mobile devices, and buildings that have electronic components, software, and network connectivity that enable them to collect data, run commands, and be controlled through the Internet. Controlling physical items from the Internet will increase efficiency and save time. The growing number of devices used by people increases the practicality of having IoT devices on the market. The IoT is also an opportunity to develop products that can save money and time and increase work efficiency. Initially, they need more efficiency for real-time bus location systems, especially in university campuses. This system can easily find the accurate locations of and distances between each bus stop and the estimated time to reach a new location. This system has been separated into two parts, which are the hardware and the software. The hardware parts are the Arduino Uno and the Global Positioning System (GPS), while Google Earth and GpsGate are the software parts. The GPS continuously takes input data from the satellite and stores the latitude and longitude values in the Arduino Uno. If we want to track the vehicle, we need to send the longitude and latitude as a message to the Google Earth software to convert these into maps for navigation. Once the Arduino Uno is activated, it takes the last received latitude and longitude positions' values from GpsGate and sends a message to Google Earth. Once the message has been sent to Google Earth, the current location will be shown, and navigation will be activated automatically. Then it will be broadcast using ManyCam, Google+ Hangouts, and YouTube, as well as Facebook, and appear to users. The additional features use Google Forms for determining problems faced by students, who can also take immediate action against the responsible department. Then after several successful simulations, the results will be shown in real time on a map.

Multi-source Geospatial Data Analysis with Google Earth Engine

NASA Astrophysics Data System (ADS)

Erickson, T.

2014-12-01

The Google Earth Engine platform is a cloud computing environment for data analysis that combines a public data catalog with a large-scale computational facility optimized for parallel processing of geospatial data. The data catalog is a multi-petabyte archive of georeferenced datasets that include images from Earth observing satellite and airborne sensors (examples: USGS Landsat, NASA MODIS, USDA NAIP), weather and climate datasets, and digital elevation models. Earth Engine supports both a just-in-time computation model that enables real-time preview and debugging during algorithm development for open-ended data exploration, and a batch computation mode for applying algorithms over large spatial and temporal extents. The platform automatically handles many traditionally-onerous data management tasks, such as data format conversion, reprojection, and resampling, which facilitates writing algorithms that combine data from multiple sensors and/or models. Although the primary use of Earth Engine, to date, has been the analysis of large Earth observing satellite datasets, the computational platform is generally applicable to a wide variety of use cases that require large-scale geospatial data analyses. This presentation will focus on how Earth Engine facilitates the analysis of geospatial data streams that originate from multiple separate sources (and often communities) and how it enables collaboration during algorithm development and data exploration. The talk will highlight current projects/analyses that are enabled by this functionality.https://earthengine.google.org

Moving beyond a Google Search: Google Earth, SketchUp, Spreadsheet, and More

ERIC Educational Resources Information Center

Siegle, Del

2007-01-01

Google has been the search engine of choice for most Web surfers for the past half decade. More recently, the creative founders of the popular search engine have been busily creating and testing a variety of useful products that will appeal to gifted learners of varying ages. The purpose of this paper is to share information about three of these…

Google Earth Engine: a new cloud-computing platform for global-scale earth observation data and analysis

NASA Astrophysics Data System (ADS)

Moore, R. T.; Hansen, M. C.

2011-12-01

Google Earth Engine is a new technology platform that enables monitoring and measurement of changes in the earth's environment, at planetary scale, on a large catalog of earth observation data. The platform offers intrinsically-parallel computational access to thousands of computers in Google's data centers. Initial efforts have focused primarily on global forest monitoring and measurement, in support of REDD+ activities in the developing world. The intent is to put this platform into the hands of scientists and developing world nations, in order to advance the broader operational deployment of existing scientific methods, and strengthen the ability for public institutions and civil society to better understand, manage and report on the state of their natural resources. Earth Engine currently hosts online nearly the complete historical Landsat archive of L5 and L7 data collected over more than twenty-five years. Newly-collected Landsat imagery is downloaded from USGS EROS Center into Earth Engine on a daily basis. Earth Engine also includes a set of historical and current MODIS data products. The platform supports generation, on-demand, of spatial and temporal mosaics, "best-pixel" composites (for example to remove clouds and gaps in satellite imagery), as well as a variety of spectral indices. Supervised learning methods are available over the Landsat data catalog. The platform also includes a new application programming framework, or "API", that allows scientists access to these computational and data resources, to scale their current algorithms or develop new ones. Under the covers of the Google Earth Engine API is an intrinsically-parallel image-processing system. Several forest monitoring applications powered by this API are currently in development and expected to be operational in 2011. Combining science with massive data and technology resources in a cloud-computing framework can offer advantages of computational speed, ease-of-use and collaboration, as well as transparency in data and methods. Methods developed for global processing of MODIS data to map land cover are being adopted for use with Landsat data. Specifically, the MODIS Vegetation Continuous Field product methodology has been applied for mapping forest extent and change at national scales using Landsat time-series data sets. Scaling this method to continental and global scales is enabled by Google Earth Engine computing capabilities. By combining the supervised learning VCF approach with the Landsat archive and cloud computing, unprecedented monitoring of land cover dynamics is enabled.

Using Google Earth in Marine Research and Operational Decision Support

NASA Astrophysics Data System (ADS)

Blower, J. D.; Bretherton, D.; Haines, K.; Liu, C.; Rawlings, C.; Santokhee, A.; Smith, I.

2006-12-01

A key advantage of Virtual Globes ("geobrowsers") such as Google Earth is that they can display many different geospatial data types at a huge range of spatial scales. In this demonstration and poster display we shall show how marine data from disparate sources can be brought together in a geobrowser in order to support both scientific research and operational search and rescue activities. We have developed the Godiva2 interactive website for browsing and exploring marine data, mainly output from supercomputer analyses and predictions of ocean circulation. The user chooses a number of parameters (e.g. sea temperature at 100m depth on 1st July 2006) and can load an image of the resulting data in Google Earth. Through the use of an automatically-refreshing NetworkLink the user can explore the whole globe at a very large range of spatial scales: the displayed data will automatically be refreshed to show data at increasingly fine resolution as the user zooms in. This is a valuable research tool for exploring these terabyte- scale datasets. Many coastguard organizations around the world use SARIS, a software application produced by BMT Cordah Ltd., to predict the drift pattern of objects in the sea in order to support search and rescue operations. Different drifting objects have different trajectories depending on factors such as their buoyancy and windage and so a computer model, supported by meteorological and oceanographic data, is needed to help rescuers locate their targets. We shall demonstrate how Google Earth is used to display output from the SARIS model (including the search target location and associated error polygon) alongside meteorological data (wind vectors) and oceanographic data (sea temperature, surface currents) from Godiva2 in order to support decision-making. We shall also discuss the limitations of using Google Earth in this context: these include the difficulties of working with time- dependent data and the need to access data securely. essc.ac.uk:8080/Godiva2

Regional early flood warning system: design and implementation

NASA Astrophysics Data System (ADS)

Chang, L. C.; Yang, S. N.; Kuo, C. L.; Wang, Y. F.

2017-12-01

This study proposes a prototype of the regional early flood inundation warning system in Tainan City, Taiwan. The AI technology is used to forecast multi-step-ahead regional flood inundation maps during storm events. The computing time is only few seconds that leads to real-time regional flood inundation forecasting. A database is built to organize data and information for building real-time forecasting models, maintaining the relations of forecasted points, and displaying forecasted results, while real-time data acquisition is another key task where the model requires immediately accessing rain gauge information to provide forecast services. All programs related database are constructed in Microsoft SQL Server by using Visual C# to extracting real-time hydrological data, managing data, storing the forecasted data and providing the information to the visual map-based display. The regional early flood inundation warning system use the up-to-date Web technologies driven by the database and real-time data acquisition to display the on-line forecasting flood inundation depths in the study area. The friendly interface includes on-line sequentially showing inundation area by Google Map, maximum inundation depth and its location, and providing KMZ file download of the results which can be watched on Google Earth. The developed system can provide all the relevant information and on-line forecast results that helps city authorities to make decisions during typhoon events and make actions to mitigate the losses.

Space-Based Identification of Archaeological Illegal Excavations and a New Automatic Method for Looting Feature Extraction in Desert Areas

NASA Astrophysics Data System (ADS)

Lasaponara, Rosa; Masini, Nicola

2018-06-01

The identification and quantification of disturbance of archaeological sites has been generally approached by visual inspection of optical aerial or satellite pictures. In this paper, we briefly summarize the state of the art of the traditionally satellite-based approaches for looting identification and propose a new automatic method for archaeological looting feature extraction approach (ALFEA). It is based on three steps: the enhancement using spatial autocorrelation, unsupervised classification, and segmentation. ALFEA has been applied to Google Earth images of two test areas, selected in desert environs in Syria (Dura Europos), and in Peru (Cahuachi-Nasca). The reliability of ALFEA was assessed through field surveys in Peru and visual inspection for the Syrian case study. Results from the evaluation procedure showed satisfactory performance from both of the two analysed test cases with a rate of success higher than 90%.

Geodynamics in Modular Course System at Vienna High School

NASA Astrophysics Data System (ADS)

Pitzl-Reinbacher, Robert

2017-04-01

In Austria there are currently some major reforms concerning high school education underway. At our school, the Bundesgymnasium and Bundesrealgymnasium Draschestrasse, a school belonging to the Vienna Bilingual Schooling branch, we have developed a course system in which pupils can select courses and determine individually which areas of study they want to focus on. Specially devised courses have been developed which fit within the framework of natural and applied sciences but go beyond the basic curriculum in physics. Geodynamics is the title of one of these courses, with an emphasis on weather, climate and geodynamic processes of the earth's crust. The course „The restless earth" deals specifically with plate tectonics, vulcanism, formation of mountains and processes such as ocean currents and the physics involved. Apart from theoretical basics we use manifold media and approaches concerning visualization: graphics, map data taken from Google Maps, satellite pictures, and others. The knowledge acquired in this course is broadened and consolidated by means of excursions to the Vienna Natural History Museum where additional instructional materials and visual aids are on display. Based on this experience pupils are requested to hold presentations (individually or in groups) at the end of the course.

Landsat Imagery Enables Global Studies of Surface Trends

NASA Technical Reports Server (NTRS)

2015-01-01

Landsat 8 is the latest in the NASA-developed series of satellites that have provided a continuous picture of Earth for more than 40 years. Mountain View, California-based Google has incorporated Landsat data into several products, most recently generating a cloud-free view of Earth. Google has also teamed up with researchers at the University of Maryland and Goddard Space Flight Center to create a global survey showing changes in forest cover over many years-the first of its kind.

Global Analysis of River Planform Change using the Google Earth Engine

NASA Astrophysics Data System (ADS)

Bryk, A.; Dietrich, W. E.; Gorelick, N.; Sargent, R.; Braudrick, C. A.

2014-12-01

Geomorphologists have historically tracked river dynamics using a combination of maps, aerial photographs, and the stratigraphic record. Although stratigraphic records can extend into deep time, maps and aerial photographs often confine our record of change to sparse measurements over the last ~80 years and in some cases much less time. For the first time Google's Earth Engine (GEE) cloud based platform allows researchers the means to analyze quantitatively the pattern and pace of river channel change over the last 30 years with high temporal resolution across the entire planet. The GEE provides an application programing interface (API) that enables quantitative analysis of various data sets including the entire Landsat L1T archive. This allows change detection for channels wider than about 150 m over 30 years of successive, georeferenced imagery. Qualitatively, it becomes immediately evident that the pace of channel morphodynamics for similar planforms varies by orders of magnitude across the planet and downstream along individual rivers. To quantify these rates of change and to explore their controls we have developed methods for differentiating channels from floodplain along large alluvial rivers. We introduce a new metric of morphodynamics: the ratio of eroded area to channel area per unit time, referred to as "M". We also keep track of depositional areas resulting from channel shifting. To date our quantitative analysis has focused on rivers in the Andean foreland. Our analysis shows channel bank erosion rates, M, varies by orders of magnitude for these rivers, from 0 to ~0.25 yr-1, yet these rivers have essentially identical curvature and sinuosity and are visually indistinguishable. By tracking both bank paths in time, we find that, for some meandering rivers, a significant fraction of new floodplain is produced through outer-bank accretion rather than point bar deposition. This process is perhaps more important in generating floodplain stratigraphy than previously recognized. These initial findings indicate a new set of quantitative observations will emerge to further test and advance morphodynamic theory. The Google Earth Engine offers the opportunity to explore river morphodynamics on an unprecedented scale and provides a powerful tool for addressing fundamental questions in river morphodynamics.

The Real Time Mission Monitor: A Platform for Real Time Environmental Data Integration and Display during NASA Field Campaigns

NASA Astrophysics Data System (ADS)

He, M.; Hardin, D. M.; Goodman, M.; Blakeslee, R.

2008-05-01

The Real Time Mission Monitor (RTMM) is an interactive visualization application based on Google Earth, that provides situational awareness and field asset management during NASA field campaigns. The RTMM can integrate data and imagery from numerous sources including GOES-12, GOES-10, and TRMM satellites. Simultaneously, it can display data and imagery from surface observations including Nexrad, NPOL and SMART- R radars. In addition to all these it can display output from models and real-time flight tracks of all aircraft involved in the experiment. In some instances the RTMM can also display measurements from scientific instruments as they are being flown. All data are recorded and archived in an on-line system enabling playback and review of all sorties. This is invaluable in preparing for future deployments and in exercising case studies. The RTMM facilitates pre-flight planning, in-flight monitoring, development of adaptive flight strategies and post- flight data analyses and assessments. Since the RTMM is available via the internet - during the actual experiment - project managers, scientists and mission planners can collaborate no matter where they are located as long as they have a viable internet connection. In addition, the system is open so that the general public can also view the experiment, in-progress, with Google Earth. Predecessors of RTMM were originally deployed in 2002 as part of the Altus Cumulus Electrification Study (ACES) to monitor uninhabited aerial vehicles near thunderstorms. In 2005 an interactive Java-based web prototype supported the airborne Lightning Instrument Package (LIP) during the Tropical Cloud Systems and Processes (TCSP) experiment. In 2006 the technology was adapted to the 3D Google Earth virtual globe and in 2007 its capabilities were extended to support multiple NASA aircraft (ER-2, WB-57, DC-8) during Tropical Composition, Clouds and Climate Coupling (TC4) experiment and 2007 Summer Aerosonde field study. In April 2008 the RTMM will be flown in the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) experiment to study the atmospheric composition in the Arctic.

Making a report of a short trip in an ophiolitic complex with Google Earth

NASA Astrophysics Data System (ADS)

Aubret, Marianne

2017-04-01

Plate tectonics is taught in French secondary school (lower and upper-sixth). According to the curriculum, the comprehension of plate-tectonic processes and concepts should be based on field data. For example, the Alpine's ocean history is studied to understand how mountain ranges are formed. In this context, Corsica is a great open-air laboratory, but unfortunately, the traffic conditions are very difficult in the island and despite the short distances, it's almost impossible for teachers to take their students to the remarkable geologic spots. The «défilé de l'Inzecca» is one of them: there you can see a part of the alpine's ophiolitic complex. The aim of this activity is to elaborate a « KMZ folder » in Google Earth as a report of a short trip thanks to the students' data field; it is also the occasion to enrich the Google Earth KMZ folder already available for our teaching.

The Palladiolibrary Geo-Models AN Open 3d Archive to Manage and Visualize Information-Communication Resources about Palladio

NASA Astrophysics Data System (ADS)

Apollonio, F. I.; Baldissini, S.; Clini, P.; Gaiani, M.; Palestini, C.; Trevisan, C.

2013-07-01

The paper describes objectives, methods, procedures and outcomes of the development of the digital archive of Palladio works and documentation: the PALLADIOLibrary of Centro Internazionale di Studi di Architettura Andrea Palladio di Vicenza (CISAAP). The core of the application consists of fifty-one reality-based 3D models usable and navigable within a system grounded on GoogleEarth. This information system, a collaboration of four universities bearers of specific skills returns a comprehensive, structured and coherent semantic interpretation of Palladian landscape through shapes realistically reconstructed from historical sources and surveys and treated for GE with Ambient Occlusion techniques, overcoming the traditional display mode.

NASA Earth Observations (NEO): Data Imagery for Education and Visualization

NASA Astrophysics Data System (ADS)

Ward, K.

2008-12-01

NASA Earth Observations (NEO) has dramatically simplified public access to georeferenced imagery of NASA remote sensing data. NEO targets the non-traditional data users who are currently underserved by functionality and formats available from the existing data ordering systems. These users include formal and informal educators, museum and science center personnel, professional communicators, and citizen scientists. NEO currently serves imagery from 45 different datasets with daily, weekly, and/or monthly temporal resolutions, with more datasets currently under development. The imagery from these datasets is produced in coordination with several data partners who are affiliated either with the instrument science teams or with the respective data processing center. NEO is a system of three components -- website, WMS (Web Mapping Service), and ftp archive -- which together are able to meet the wide-ranging needs of our users. Some of these needs include the ability to: view and manipulate imagery using the NEO website -- e.g., applying color palettes, resizing, exporting to a variety of formats including PNG, JPEG, KMZ (Google Earth), GeoTIFF; access the NEO collection via a standards-based API (WMS); and create customized exports for select users (ftp archive) such as Science on a Sphere, NASA's Earth Observatory, and others.

Google's Geo Education Outreach: Results and Discussion of Outreach Trip to Alaskan High Schools.

NASA Astrophysics Data System (ADS)

Kolb, E. J.; Bailey, J.; Bishop, A.; Cain, J.; Goddard, M.; Hurowitz, K.; Kennedy, K.; Ornduff, T.; Sfraga, M.; Wernecke, J.

2008-12-01

The focus of Google's Geo Education outreach efforts (http://www.google.com/educators/geo.html) is on helping primary, secondary, and post-secondary educators incorporate Google Earth and Sky, Google Maps, and SketchUp into their classroom lessons. In partnership with the University of Alaska, our Geo Education team members visited several remote Alaskan high schools during a one-week period in September. At each school, we led several 40-minute hands-on learning sessions in which Google products were used by the students to investigate local geologic and environmental processes. For the teachers, we provided several resources including follow-on lesson plans, example KML-based lessons, useful URL's, and website resources that multiple users can contribute to. This talk will highlight results of the trip and discuss how educators can access and use Google's Geo Education resources.

Known unknowns, Google Earth, plate tectonics and Mt Bellenden Ker: some thoughts on locality data.

PubMed

Mesibov, Robert

2012-01-01

Latitude/longitude data in locality records should be published with spatial uncertainties, datum(s) used and indications of how the data were obtained. Google Earth can be used to locate sampling sites, but the underlying georegistration of the satellite image should be checked. The little-known relabelling of a set of landmarks on Mt Bellenden Ker, a scientifically important collecting locality in tropical north Queensland, Australia, is documented as an example of the importance of checking records not accompanied by appropriately accurate latitude/longitude data.

Community-Based Services that Facilitate Interoperability and Intercomparison of Precipitation Datasets from Multiple Sources

NASA Technical Reports Server (NTRS)

Liu, Zhong; Kempler, Steven; Teng, William; Leptoukh, Gregory; Ostrenga, Dana

2010-01-01

Over the past 12 years, large volumes of precipitation data have been generated from space-based observatories (e.g., TRMM), merging of data products (e.g., gridded 3B42), models (e.g., GMAO), climatologies (e.g., Chang SSM/I derived rain indices), field campaigns, and ground-based measuring stations. The science research, applications, and education communities have greatly benefited from the unrestricted availability of these data from the Goddard Earth Sciences Data and Information Services Center (GES DISC) and, in particular, the services tailored toward precipitation data access and usability. In addition, tools and services that are responsive to the expressed evolving needs of the precipitation data user communities have been developed at the Precipitation Data and Information Services Center (PDISC) (http://disc.gsfc.nasa.gov/precipitation or google NASA PDISC), located at the GES DISC, to provide users with quick data exploration and access capabilities. In recent years, data management and access services have become increasingly sophisticated, such that they now afford researchers, particularly those interested in multi-data set science analysis and/or data validation, the ability to homogenize data sets, in order to apply multi-variant, comparison, and evaluation functions. Included in these services is the ability to capture data quality and data provenance. These interoperability services can be directly applied to future data sets, such as those from the Global Precipitation Measurement (GPM) mission. This presentation describes the data sets and services at the PDISC that are currently used by precipitation science and applications researchers, and which will be enhanced in preparation for GPM and associated multi-sensor data research. Specifically, the GES-DISC Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) will be illustrated. Giovanni enables scientific exploration of Earth science data without researchers having to perform the complicated data access and match-up processes. In addition, PDISC tool and service capabilities being adapted for GPM data will be described, including the Google-like Mirador data search and access engine; semantic technology to help manage large amounts of multi-sensor data and their relationships; data access through various Web services (e.g., OPeNDAP, GDS, WMS, WCS); conversion to various formats (e.g., netCDF, HDF, KML (for Google Earth)); visualization and analysis of Level 2 data profiles and maps; parameter and spatial subsetting; time and temporal aggregation; regridding; data version control and provenance; continuous archive verification; and expertise in data-related standards and interoperability. The goal of providing these services is to further the progress towards a common framework by which data analysis/validation can be more easily accomplished.

Global Precipitation Measurement (GPM) Mission Products and Services at the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC)

NASA Technical Reports Server (NTRS)

Liu, Z.; Ostrenga, D.; Vollmer, B.; Kempler, S.; Deshong, B.; Greene, M.

2015-01-01

The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) hosts and distributes GPM data within the NASA Earth Observation System Data Information System (EOSDIS). The GES DISC is also home to the data archive for the GPM predecessor, the Tropical Rainfall Measuring Mission (TRMM). Over the past 17 years, the GES DISC has served the scientific as well as other communities with TRMM data and user-friendly services. During the GPM era, the GES DISC will continue to provide user-friendly data services and customer support to users around the world. GPM products currently and to-be available: -Level-1 GPM Microwave Imager (GMI) and partner radiometer products, DPR products -Level-2 Goddard Profiling Algorithm (GPROF) GMI and partner products, DPR products -Level-3 daily and monthly products, DPR products -Integrated Multi-satellitE Retrievals for GPM (IMERG) products (early, late, and final) A dedicated Web portal (including user guides, etc.) has been developed for GPM data (http://disc.sci.gsfc.nasa.gov/gpm). Data services that are currently and to-be available include Google-like Mirador (http://mirador.gsfc.nasa.gov/) for data search and access; data access through various Web services (e.g., OPeNDAP, GDS, WMS, WCS); conversion into various formats (e.g., netCDF, HDF, KML (for Google Earth), ASCII); exploration, visualization, and statistical online analysis through Giovanni (http://giovanni.gsfc.nasa.gov); generation of value-added products; parameter and spatial subsetting; time aggregation; regridding; data version control and provenance; documentation; science support for proper data usage, FAQ, help desk; monitoring services (e.g. Current Conditions) for applications. The United User Interface (UUI) is the next step in the evolution of the GES DISC web site. It attempts to provide seamless access to data, information and services through a single interface without sending the user to different applications or URLs (e.g., search, access, subset, Giovanni, documents).

Urban topography for flood modeling by fusion of OpenStreetMap, SRTM and local knowledge

NASA Astrophysics Data System (ADS)

Winsemius, Hessel; Donchyts, Gennadii; Eilander, Dirk; Chen, Jorik; Leskens, Anne; Coughlan, Erin; Mawanda, Shaban; Ward, Philip; Diaz Loaiza, Andres; Luo, Tianyi; Iceland, Charles

2016-04-01

Topography data is essential for understanding and modeling of urban flood hazard. Within urban areas, much of the topography is defined by highly localized man-made features such as roads, channels, ditches, culverts and buildings. This results in the requirement that urban flood models require high resolution topography, and water conveying connections within the topography are considered. In recent years, more and more topography information is collected through LIDAR surveys however there are still many cities in the world where high resolution topography data is not available. Furthermore, information on connectivity is required for flood modelling, even when LIDAR data are used. In this contribution, we demonstrate how high resolution terrain data can be synthesized using a fusion between features in OpenStreetMap (OSM) data (including roads, culverts, channels and buildings) and existing low resolution and noisy SRTM elevation data using the Google Earth Engine platform. Our method uses typical existing OSM properties to estimate heights and topology associated with the features, and uses these to correct noise and burn features on top of the existing low resolution SRTM elevation data. The method has been setup in the Google Earth Engine platform so that local stakeholders and mapping teams can on-the-fly propose, include and visualize the effect of additional features and properties of features, which are deemed important for topography and water conveyance. These features can be included in a workshop environment. We pilot our tool over Dar Es Salaam.

Leveraging Open Standards and Technologies to Search and Display Planetary Image Data

NASA Astrophysics Data System (ADS)

Rose, M.; Schauer, C.; Quinol, M.; Trimble, J.

2011-12-01

Mars and the Moon have both been visited by multiple NASA spacecraft. A large number of images and other data have been gathered by the spacecraft and are publicly available in NASA's Planetary Data System. Through a collaboration with Google, Inc., the User Centered Technologies group at NASA Ames Resarch Center has developed at tool for searching and browsing among images from multiple Mars and Moon missions. Development of this tool was facilitated by the use of several open technologies and standards. First, an open-source full-text search engine is used to search both place names on the target and to find images matching a geographic region. Second, the published API of the Google Earth browser plugin is used to geolocate the images on a virtual globe and allow the user to navigate on the globe to see related images. The structure of the application also employs standard protocols and services. The back-end is exposed as RESTful APIs, which could be reused by other client systems in the future. Further, the communication between the front- and back-end portions of the system utilizes open data standards including XML and KML (Keyhole Markup Language) for representation of textual and geographic data. The creation of the search index was facilitated by reuse of existing, publicly available metadata, including the Gazetteer of Planetary Nomenclature from the USGS, available in KML format. And the image metadata was reused from standards-compliant archives in the Planetary Data System. The system also supports collaboration with other tools by allowing export of search results in KML, and the ability to display those results in the Google Earth desktop application. We will demonstrate the search and visualization capabilities of the system, with emphasis on how the system facilitates reuse of data and services through the adoption of open standards.

Google Earth in the middle school geography classroom: Its impact on spatial literacy and place geography understanding of students

NASA Astrophysics Data System (ADS)

Westgard, Kerri S. W.

Success in today's globalized, multi-dimensional, and connected world requires individuals to have a variety of skill sets -- i.e. oracy, numeracy, literacy, as well as the ability to think spatially. Student's spatial literacy, based on various national and international assessment results, indicates that even though there have been gains in U.S. scores over the past decade, overall performance, including those specific to spatial skills, are still below proficiency. Existing studies focused on the potential of virtual learning environment technology to reach students in a variety of academic areas, but a need still exists to study specifically the phenomenon of using Google Earth as a potentially more useful pedagogical tool to develop spatial literacy than the currently employed methods. The purpose of this study was to determine the extent to which graphicacy achievement scores of students who were immersed in a Google Earth environment were different from students who were provided with only two-dimensional instruction for developing spatial skills. Situated learning theory and the work of Piaget and Inhelder's Child's Conception of Space provided the theoretical grounding from which this study evolved. The National Research Council's call to develop spatial literacy, as seen in Learning to Think Spatially , provided the impetus to begin research. The target population (N = 84) for this study consisted of eighth grade geography students at an upper Midwest Jr. High School during the 2009-2010 academic year. Students were assigned to the control or experimental group based on when they had geography class. Control group students ( n = 44) used two-dimensional PowerPoint images to complete activities, while experimental group students (n = 40) were immersed in the three-dimensional Google Earth world for activity completion. Research data was then compiled and statistically analyzed to answer five research questions developed for this study. One-way ANOVAs were run on data collected and no statistically significant difference was found between the control and experimental group. However, two of the five research questions yielded practically significant data that indicates students who used Google Earth outperformed their counterparts who used PowerPoint on pattern prediction and spatial relationship understanding.

Public Use of Online Hydrology Information for Harris County and Houston, Texas, during Hurricane Harvey and Suggested Improvement for Future Flood Events

NASA Astrophysics Data System (ADS)

Lilly, M. R.; Feditova, A.; Levine, K.; Giardino, J. R.

2017-12-01

The Harris County Flood Control District has an impressive amount of information available for the public related to flood management and response. During Hurricane Harvey, this information was used by the authors to help address daily questions from family and friends living in the Houston area. Common near-real-time reporting data included precipitation and water levels. Maps included locations of data stations, stream or bayou conditions (in bank, out of bank) and watershed or drainage boundaries. In general, the data station reporting and online information was updating well throughout the hurricane and post-flooding period. Only a few of the data reporting stations had problems with water level sensor measurements. The overall information was helpful to hydrologists and floodplain managers. The online information could not easily answer all common questions residents may have during a flood event. Some of the more common questions were how to use the water-level information to know the potential extent of flooding and relative location of flooding to the location of residents. To help address the questions raised during the flooding on how to use the available water level data, we used Google Earth to get lot and intersection locations to help show the relative differences between nearby water-level stations and residences of interest. The reported resolution of the Google Earth elevation data is 1-foot. To help confirm the use of this data, we compared Google Earth approximate elevations with reported Harris County Floodplain Reference Mark individual reports. This method helped verify we could use the Google Earth information for approximate comparisons. We also faced questions on what routes to take if evacuation was needed, and where to go to get to higher ground elevations. Google Earth again provided a helpful and easy to use interface to look at road and intersection elevations and develop suggested routes for family and friends to take to avoid low areas that may be subject to flooding. These and other recommendations that helped answer common questions by residents reacting to the hurricane and subsequent flooding conditions are summarized with examples.

Development, Deployment, and Assessment of Dynamic Geological and Geophysical Models Using the Google Earth APP and API: Implications for Undergraduate Education in the Earth and Planetary Sciences

NASA Astrophysics Data System (ADS)

de Paor, D. G.; Whitmeyer, S. J.; Gobert, J.

2009-12-01

We previously reported on innovative techniques for presenting data on virtual globes such as Google Earth using emergent Collada models that reveal subsurface geology and geophysics. We here present several new and enhanced models and linked lesson plans to aid deployment in undergraduate geoscience courses, along with preliminary results from our assessment of their effectiveness. The new Collada models are created with Google SketchUp, Bonzai3D, and MeshLab software, and are grouped to cover (i) small scale field mapping areas; (ii) regional scale studies of the North Atlantic Ocean Basin, the Appalachian Orogen, and the Pacific Ring of Fire; and (iii) global scale studies of terrestrial planets, moons, and asteroids. Enhancements include emergent block models with three-dimensional surface topography; models that conserve structural orientation data; interactive virtual specimens; models that animate plate movements on the virtual globe; exploded 3-D views of planetary mantles and cores; and server-generated dynamic KML. We tested volunteer students and professors using Silverback monitoring software, think-aloud verbalizations, and questionnaires designed to assess their understanding of the underlying geo-scientific phenomena. With the aid of a cohort of instructors across the U.S., we are continuing to assess areas in which users encounter difficulties with both the software and geoscientific concepts. Preliminary results suggest that it is easy to overestimate the computer expertise of novice users even when they are content knowledge experts (i.e., instructors), and that a detailed introduction to virtual globe manipulation is essential before moving on to geoscience applications. Tasks that seem trivial to developers may present barriers to non-technical users and technicalities that challenge instructors may block adoption in the classroom. We have developed new models using the Google Earth API which permits enhanced interaction and dynamic feedback and are assessing their relative merits versus the Google Earth APP. Overall, test students and professors value the models very highly. There are clear pedagogical opportunities for using materials such as these to create engaging in-course research opportunities for undergraduates.

Using Google Earth to Assess Shade for Sun Protection in Urban Recreation Spaces: Methods and Results.

PubMed

Gage, R; Wilson, N; Signal, L; Barr, M; Mackay, C; Reeder, A; Thomson, G

2018-05-16

Shade in public spaces can lower the risk of and sun burning and skin cancer. However, existing methods of auditing shade require travel between sites, and sunny weather conditions. This study aimed to evaluate the feasibility of free computer software-Google Earth-for assessing shade in urban open spaces. A shade projection method was developed that uses Google Earth street view and aerial images to estimate shade at solar noon on the summer solstice, irrespective of the date of image capture. Three researchers used the method to separately estimate shade cover over pre-defined activity areas in a sample of 45 New Zealand urban open spaces, including 24 playgrounds, 12 beaches and 9 outdoor pools. Outcome measures included method accuracy (assessed by comparison with a subsample of field observations of 10 of the settings) and inter-rater reliability. Of the 164 activity areas identified in the 45 settings, most (83%) had no shade cover. The method identified most activity areas in playgrounds (85%) and beaches (93%) and was accurate for assessing shade over these areas (predictive values of 100%). Only 8% of activity areas at outdoor pools were identified, due to a lack of street view images. Reliability for shade cover estimates was excellent (intraclass correlation coefficient of 0.97, 95% CI 0.97-0.98). Google Earth appears to be a reasonably accurate and reliable and shade audit tool for playgrounds and beaches. The findings are relevant for programmes focused on supporting the development of healthy urban open spaces.

Transforming Polar Research with Google Glass Augmented Reality (Invited)

NASA Astrophysics Data System (ADS)

Ruthkoski, T.

2013-12-01

Augmented reality is a new technology with the potential to accelerate the advancement of science, particularly in geophysical research. Augmented reality is defined as a live, direct or indirect, view of a physical, real-world environment whose elements are augmented (or supplemented) by computer-generated sensory input such as sound, video, graphics or GPS data. When paired with advanced computing techniques on cloud resources, augmented reality has the potential to improve data collection techniques, visualizations, as well as in-situ analysis for many areas of research. Google is currently a pioneer of augmented reality technology and has released beta versions of their wearable computing device, Google Glass, to a select number of developers and beta testers. This community of 'Glass Explorers' is the vehicle from which Google shapes the future of their augmented reality device. Example applications of Google Glass in geophysical research range from use as a data gathering interface in harsh climates to an on-site visualization and analysis tool. Early participation in the shaping of the Google Glass device is an opportunity for researchers to tailor this new technology to their specific needs. The purpose of this presentation is to provide geophysical researchers with a hands-on first look at Google Glass and its potential as a scientific tool. Attendees will be given an overview of the technical specifications as well as a live demonstration of the device. Potential applications to geophysical research in polar regions will be the primary focus. The presentation will conclude with an open call to participate, during which attendees may indicate interest in developing projects that integrate Google Glass into their research. Application Mockup: Penguin Counter Google Glass Augmented Reality Device

Transforming Polar Research with Google Glass Augmented Reality (Invited)

NASA Astrophysics Data System (ADS)

Ramachandran, R.; McEniry, M.; Maskey, M.

2011-12-01

Augmented reality is a new technology with the potential to accelerate the advancement of science, particularly in geophysical research. Augmented reality is defined as a live, direct or indirect, view of a physical, real-world environment whose elements are augmented (or supplemented) by computer-generated sensory input such as sound, video, graphics or GPS data. When paired with advanced computing techniques on cloud resources, augmented reality has the potential to improve data collection techniques, visualizations, as well as in-situ analysis for many areas of research. Google is currently a pioneer of augmented reality technology and has released beta versions of their wearable computing device, Google Glass, to a select number of developers and beta testers. This community of 'Glass Explorers' is the vehicle from which Google shapes the future of their augmented reality device. Example applications of Google Glass in geophysical research range from use as a data gathering interface in harsh climates to an on-site visualization and analysis tool. Early participation in the shaping of the Google Glass device is an opportunity for researchers to tailor this new technology to their specific needs. The purpose of this presentation is to provide geophysical researchers with a hands-on first look at Google Glass and its potential as a scientific tool. Attendees will be given an overview of the technical specifications as well as a live demonstration of the device. Potential applications to geophysical research in polar regions will be the primary focus. The presentation will conclude with an open call to participate, during which attendees may indicate interest in developing projects that integrate Google Glass into their research. Application Mockup: Penguin Counter Google Glass Augmented Reality Device

Comparison of User Performance with Interactive and Static 3d Visualization - Pilot Study

NASA Astrophysics Data System (ADS)

Herman, L.; Stachoň, Z.

2016-06-01

Interactive 3D visualizations of spatial data are currently available and popular through various applications such as Google Earth, ArcScene, etc. Several scientific studies have focused on user performance with 3D visualization, but static perspective views are used as stimuli in most of the studies. The main objective of this paper is to try to identify potential differences in user performance with static perspective views and interactive visualizations. This research is an exploratory study. An experiment was designed as a between-subject study and a customized testing tool based on open web technologies was used for the experiment. The testing set consists of an initial questionnaire, a training task and four experimental tasks. Selection of the highest point and determination of visibility from the top of a mountain were used as the experimental tasks. Speed and accuracy of each task performance of participants were recorded. The movement and actions in the virtual environment were also recorded within the interactive variant. The results show that participants deal with the tasks faster when using static visualization. The average error rate was also higher in the static variant. The findings from this pilot study will be used for further testing, especially for formulating of hypotheses and designing of subsequent experiments.

Interacting with Petabytes of Earth Science Data using Jupyter Notebooks, IPython Widgets and Google Earth Engine

NASA Astrophysics Data System (ADS)

Erickson, T. A.; Granger, B.; Grout, J.; Corlay, S.

2017-12-01

The volume of Earth science data gathered from satellites, aircraft, drones, and field instruments continues to increase. For many scientific questions in the Earth sciences, managing this large volume of data is a barrier to progress, as it is difficult to explore and analyze large volumes of data using the traditional paradigm of downloading datasets to a local computer for analysis. Furthermore, methods for communicating Earth science algorithms that operate on large datasets in an easily understandable and reproducible way are needed. Here we describe a system for developing, interacting, and sharing well-documented Earth Science algorithms that combines existing software components: Jupyter Notebook: An open-source, web-based environment that supports documents that combine code and computational results with text narrative, mathematics, images, and other media. These notebooks provide an environment for interactive exploration of data and development of well documented algorithms. Jupyter Widgets / ipyleaflet: An architecture for creating interactive user interface controls (such as sliders, text boxes, etc.) in Jupyter Notebooks that communicate with Python code. This architecture includes a default set of UI controls (sliders, dropboxes, etc.) as well as APIs for building custom UI controls. The ipyleaflet project is one example that offers a custom interactive map control that allows a user to display and manipulate geographic data within the Jupyter Notebook. Google Earth Engine: A cloud-based geospatial analysis platform that provides access to petabytes of Earth science data via a Python API. The combination of Jupyter Notebooks, Jupyter Widgets, ipyleaflet, and Google Earth Engine makes it possible to explore and analyze massive Earth science datasets via a web browser, in an environment suitable for interactive exploration, teaching, and sharing. Using these environments can make Earth science analyses easier to understand and reproducible, which may increase the rate of scientific discoveries and the transition of discoveries into real-world impacts.

International Ocean Discovery Program U.S. Implementing Organization

Science.gov Websites

coordinates seagoing expeditions to study the history of the Earth recorded in sediments and rocks beneath the Internship :: Minorities in Scientific Ocean Drilling Fellowship Education Deep Earth Academy logo :: joidesresolution.org :: For students :: For teachers :: For scientists :: View drill sites in Google Earth Export

Dynamic Server-Based KML Code Generator Method for Level-of-Detail Traversal of Geospatial Data

NASA Technical Reports Server (NTRS)

Baxes, Gregory; Mixon, Brian; Linger, TIm

2013-01-01

Web-based geospatial client applications such as Google Earth and NASA World Wind must listen to data requests, access appropriate stored data, and compile a data response to the requesting client application. This process occurs repeatedly to support multiple client requests and application instances. Newer Web-based geospatial clients also provide user-interactive functionality that is dependent on fast and efficient server responses. With massively large datasets, server-client interaction can become severely impeded because the server must determine the best way to assemble data to meet the client applications request. In client applications such as Google Earth, the user interactively wanders through the data using visually guided panning and zooming actions. With these actions, the client application is continually issuing data requests to the server without knowledge of the server s data structure or extraction/assembly paradigm. A method for efficiently controlling the networked access of a Web-based geospatial browser to server-based datasets in particular, massively sized datasets has been developed. The method specifically uses the Keyhole Markup Language (KML), an Open Geospatial Consortium (OGS) standard used by Google Earth and other KML-compliant geospatial client applications. The innovation is based on establishing a dynamic cascading KML strategy that is initiated by a KML launch file provided by a data server host to a Google Earth or similar KMLcompliant geospatial client application user. Upon execution, the launch KML code issues a request for image data covering an initial geographic region. The server responds with the requested data along with subsequent dynamically generated KML code that directs the client application to make follow-on requests for higher level of detail (LOD) imagery to replace the initial imagery as the user navigates into the dataset. The approach provides an efficient data traversal path and mechanism that can be flexibly established for any dataset regardless of size or other characteristics. The method yields significant improvements in userinteractive geospatial client and data server interaction and associated network bandwidth requirements. The innovation uses a C- or PHP-code-like grammar that provides a high degree of processing flexibility. A set of language lexer and parser elements is provided that offers a complete language grammar for writing and executing language directives. A script is wrapped and passed to the geospatial data server by a client application as a component of a standard KML-compliant statement. The approach provides an efficient means for a geospatial client application to request server preprocessing of data prior to client delivery. Data is structured in a quadtree format. As the user zooms into the dataset, geographic regions are subdivided into four child regions. Conversely, as the user zooms out, four child regions collapse into a single, lower-LOD region. The approach provides an efficient data traversal path and mechanism that can be flexibly established for any dataset regardless of size or other characteristics.

Google Haul Out: Earth Observation Imagery and Digital Aerial Surveys in Coastal Wildlife Management and Abundance Estimation

PubMed Central

Moxley, Jerry H.; Bogomolni, Andrea; Hammill, Mike O.; Moore, Kathleen M. T.; Polito, Michael J.; Sette, Lisa; Sharp, W. Brian; Waring, Gordon T.; Gilbert, James R.; Halpin, Patrick N.; Johnston, David W.

2017-01-01

Abstract As the sampling frequency and resolution of Earth observation imagery increase, there are growing opportunities for novel applications in population monitoring. New methods are required to apply established analytical approaches to data collected from new observation platforms (e.g., satellites and unmanned aerial vehicles). Here, we present a method that estimates regional seasonal abundances for an understudied and growing population of gray seals (Halichoerus grypus) in southeastern Massachusetts, using opportunistic observations in Google Earth imagery. Abundance estimates are derived from digital aerial survey counts by adapting established correction-based analyses with telemetry behavioral observation to quantify survey biases. The result is a first regional understanding of gray seal abundance in the northeast US through opportunistic Earth observation imagery and repurposed animal telemetry data. As species observation data from Earth observation imagery become more ubiquitous, such methods provide a robust, adaptable, and cost-effective solution to monitoring animal colonies and understanding species abundances. PMID:29599542

Google Haul Out: Earth Observation Imagery and Digital Aerial Surveys in Coastal Wildlife Management and Abundance Estimation.

PubMed

Moxley, Jerry H; Bogomolni, Andrea; Hammill, Mike O; Moore, Kathleen M T; Polito, Michael J; Sette, Lisa; Sharp, W Brian; Waring, Gordon T; Gilbert, James R; Halpin, Patrick N; Johnston, David W

2017-08-01

As the sampling frequency and resolution of Earth observation imagery increase, there are growing opportunities for novel applications in population monitoring. New methods are required to apply established analytical approaches to data collected from new observation platforms (e.g., satellites and unmanned aerial vehicles). Here, we present a method that estimates regional seasonal abundances for an understudied and growing population of gray seals (Halichoerus grypus) in southeastern Massachusetts, using opportunistic observations in Google Earth imagery. Abundance estimates are derived from digital aerial survey counts by adapting established correction-based analyses with telemetry behavioral observation to quantify survey biases. The result is a first regional understanding of gray seal abundance in the northeast US through opportunistic Earth observation imagery and repurposed animal telemetry data. As species observation data from Earth observation imagery become more ubiquitous, such methods provide a robust, adaptable, and cost-effective solution to monitoring animal colonies and understanding species abundances.

Geolokit: An interactive tool for visualising and exploring geoscientific data in Google Earth

NASA Astrophysics Data System (ADS)

Triantafyllou, Antoine; Watlet, Arnaud; Bastin, Christophe

2017-10-01

Virtual globes have been developed to showcase different types of data combining a digital elevation model and basemaps of high resolution satellite imagery. Hence, they became a standard to share spatial data and information, although they suffer from a lack of toolboxes dedicated to the formatting of large geoscientific dataset. From this perspective, we developed Geolokit: a free and lightweight software that allows geoscientists - and every scientist working with spatial data - to import their data (e.g., sample collections, structural geology, cross-sections, field pictures, georeferenced maps), to handle and to transcribe them to Keyhole Markup Language (KML) files. KML files are then automatically opened in the Google Earth virtual globe and the spatial data accessed and shared. Geolokit comes with a large number of dedicated tools that can process and display: (i) multi-points data, (ii) scattered data interpolations, (iii) structural geology features in 2D and 3D, (iv) rose diagrams, stereonets and dip-plunge polar histograms, (v) cross-sections and oriented rasters, (vi) georeferenced field pictures, (vii) georeferenced maps and projected gridding. Therefore, together with Geolokit, Google Earth becomes not only a powerful georeferenced data viewer but also a stand-alone work platform. The toolbox (available online at http://www.geolokit.org) is written in Python, a high-level, cross-platform programming language and is accessible through a graphical user interface, designed to run in parallel with Google Earth, through a workflow that requires no additional third party software. Geolokit features are demonstrated in this paper using typical datasets gathered from two case studies illustrating its applicability at multiple scales of investigation: a petro-structural investigation of the Ile d'Yeu orthogneissic unit (Western France) and data collection of the Mariana oceanic subduction zone (Western Pacific).

Multi-temporal Land Use Mapping of Coastal Wetlands Area using Machine Learning in Google Earth Engine

NASA Astrophysics Data System (ADS)

Farda, N. M.

2017-12-01

Coastal wetlands provide ecosystem services essential to people and the environment. Changes in coastal wetlands, especially on land use, are important to monitor by utilizing multi-temporal imagery. The Google Earth Engine (GEE) provides many machine learning algorithms (10 algorithms) that are very useful for extracting land use from imagery. The research objective is to explore machine learning in Google Earth Engine and its accuracy for multi-temporal land use mapping of coastal wetland area. Landsat 3 MSS (1978), Landsat 5 TM (1991), Landsat 7 ETM+ (2001), and Landsat 8 OLI (2014) images located in Segara Anakan lagoon are selected to represent multi temporal images. The input for machine learning are visible and near infrared bands, PCA band, invers PCA bands, bare soil index, vegetation index, wetness index, elevation from ASTER GDEM, and GLCM (Harralick) texture, and also polygon samples in 140 locations. There are 10 machine learning algorithms applied to extract coastal wetlands land use from Landsat imagery. The algorithms are Fast Naive Bayes, CART (Classification and Regression Tree), Random Forests, GMO Max Entropy, Perceptron (Multi Class Perceptron), Winnow, Voting SVM, Margin SVM, Pegasos (Primal Estimated sub-GrAdient SOlver for Svm), IKPamir (Intersection Kernel Passive Aggressive Method for Information Retrieval, SVM). Machine learning in Google Earth Engine are very helpful in multi-temporal land use mapping, the highest accuracy for land use mapping of coastal wetland is CART with 96.98 % Overall Accuracy using K-Fold Cross Validation (K = 10). GEE is particularly useful for multi-temporal land use mapping with ready used image and classification algorithms, and also very challenging for other applications.

Assessing species distribution using Google Street View: a pilot study with the Pine Processionary Moth.

PubMed

Rousselet, Jérôme; Imbert, Charles-Edouard; Dekri, Anissa; Garcia, Jacques; Goussard, Francis; Vincent, Bruno; Denux, Olivier; Robinet, Christelle; Dorkeld, Franck; Roques, Alain; Rossi, Jean-Pierre

2013-01-01

Mapping species spatial distribution using spatial inference and prediction requires a lot of data. Occurrence data are generally not easily available from the literature and are very time-consuming to collect in the field. For that reason, we designed a survey to explore to which extent large-scale databases such as Google maps and Google Street View could be used to derive valid occurrence data. We worked with the Pine Processionary Moth (PPM) Thaumetopoea pityocampa because the larvae of that moth build silk nests that are easily visible. The presence of the species at one location can therefore be inferred from visual records derived from the panoramic views available from Google Street View. We designed a standardized procedure allowing evaluating the presence of the PPM on a sampling grid covering the landscape under study. The outputs were compared to field data. We investigated two landscapes using grids of different extent and mesh size. Data derived from Google Street View were highly similar to field data in the large-scale analysis based on a square grid with a mesh of 16 km (96% of matching records). Using a 2 km mesh size led to a strong divergence between field and Google-derived data (46% of matching records). We conclude that Google database might provide useful occurrence data for mapping the distribution of species which presence can be visually evaluated such as the PPM. However, the accuracy of the output strongly depends on the spatial scales considered and on the sampling grid used. Other factors such as the coverage of Google Street View network with regards to sampling grid size and the spatial distribution of host trees with regards to road network may also be determinant.

Assessing Species Distribution Using Google Street View: A Pilot Study with the Pine Processionary Moth

PubMed Central

Dekri, Anissa; Garcia, Jacques; Goussard, Francis; Vincent, Bruno; Denux, Olivier; Robinet, Christelle; Dorkeld, Franck; Roques, Alain; Rossi, Jean-Pierre

2013-01-01

Mapping species spatial distribution using spatial inference and prediction requires a lot of data. Occurrence data are generally not easily available from the literature and are very time-consuming to collect in the field. For that reason, we designed a survey to explore to which extent large-scale databases such as Google maps and Google street view could be used to derive valid occurrence data. We worked with the Pine Processionary Moth (PPM) Thaumetopoea pityocampa because the larvae of that moth build silk nests that are easily visible. The presence of the species at one location can therefore be inferred from visual records derived from the panoramic views available from Google street view. We designed a standardized procedure allowing evaluating the presence of the PPM on a sampling grid covering the landscape under study. The outputs were compared to field data. We investigated two landscapes using grids of different extent and mesh size. Data derived from Google street view were highly similar to field data in the large-scale analysis based on a square grid with a mesh of 16 km (96% of matching records). Using a 2 km mesh size led to a strong divergence between field and Google-derived data (46% of matching records). We conclude that Google database might provide useful occurrence data for mapping the distribution of species which presence can be visually evaluated such as the PPM. However, the accuracy of the output strongly depends on the spatial scales considered and on the sampling grid used. Other factors such as the coverage of Google street view network with regards to sampling grid size and the spatial distribution of host trees with regards to road network may also be determinant. PMID:24130675

Planetary-Scale Geospatial Data Analysis Techniques in Google's Earth Engine Platform (Invited)

NASA Astrophysics Data System (ADS)

Hancher, M.

2013-12-01

Geoscientists have more and more access to new tools for large-scale computing. With any tool, some tasks are easy and other tasks hard. It is natural to look to new computing platforms to increase the scale and efficiency of existing techniques, but there is a more exiting opportunity to discover and develop a new vocabulary of fundamental analysis idioms that are made easy and effective by these new tools. Google's Earth Engine platform is a cloud computing environment for earth data analysis that combines a public data catalog with a large-scale computational facility optimized for parallel processing of geospatial data. The data catalog includes a nearly complete archive of scenes from Landsat 4, 5, 7, and 8 that have been processed by the USGS, as well as a wide variety of other remotely-sensed and ancillary data products. Earth Engine supports a just-in-time computation model that enables real-time preview during algorithm development and debugging as well as during experimental data analysis and open-ended data exploration. Data processing operations are performed in parallel across many computers in Google's datacenters. The platform automatically handles many traditionally-onerous data management tasks, such as data format conversion, reprojection, resampling, and associating image metadata with pixel data. Early applications of Earth Engine have included the development of Google's global cloud-free fifteen-meter base map and global multi-decadal time-lapse animations, as well as numerous large and small experimental analyses by scientists from a range of academic, government, and non-governmental institutions, working in a wide variety of application areas including forestry, agriculture, urban mapping, and species habitat modeling. Patterns in the successes and failures of these early efforts have begun to emerge, sketching the outlines of a new set of simple and effective approaches to geospatial data analysis.

Using Immersive Visualizations to Improve Decision Making and Enhancing Public Understanding of Earth Resource and Climate Issues

NASA Astrophysics Data System (ADS)

Yu, K. C.; Raynolds, R. G.; Dechesne, M.

2008-12-01

New visualization technologies, from ArcGIS to Google Earth, have allowed for the integration of complex, disparate data sets to produce visually rich and compelling three-dimensional models of sub-surface and surface resource distribution patterns. The rendering of these models allows the public to quickly understand complicated geospatial relationships that would otherwise take much longer to explain using traditional media. We have impacted the community through topical policy presentations at both state and city levels, adult education classes at the Denver Museum of Nature and Science (DMNS), and public lectures at DMNS. We have constructed three-dimensional models from well data and surface observations which allow policy makers to better understand the distribution of groundwater in sandstone aquifers of the Denver Basin. Our presentations to local governments in the Denver metro area have allowed resource managers to better project future ground water depletion patterns, and to encourage development of alternative sources. DMNS adult education classes on water resources, geography, and regional geology, as well as public lectures on global issues such as earthquakes, tsunamis, and resource depletion, have utilized the visualizations developed from these research models. In addition to presenting GIS models in traditional lectures, we have also made use of the immersive display capabilities of the digital "fulldome" Gates Planetarium at DMNS. The real-time Uniview visualization application installed at Gates was designed for teaching astronomy, but it can be re-purposed for displaying our model datasets in the context of the Earth's surface. The 17-meter diameter dome of the Gates Planetarium allows an audience to have an immersive experience---similar to virtual reality CAVEs employed by the oil exploration industry---that would otherwise not be available to the general public. Public lectures in the dome allow audiences of over 100 people to comprehend dynamically- changing geospatial datasets in an exciting and engaging fashion. In our presentation, we will demonstrate how new software tools like Uniview can be used to dramatically enhance and accelerate public comprehension of complex, multi-scale geospatial phenomena.

Digital surveying and mapping of forest road network for development of a GIS tool for the effective protection and management of natural ecosystems

NASA Astrophysics Data System (ADS)

Drosos, Vasileios C.; Liampas, Sarantis-Aggelos G.; Doukas, Aristotelis-Kosmas G.

2014-08-01

In our time, the Geographic Information Systems (GIS) have become important tools, not only in the geosciences and environmental sciences, as well as virtually for all researches that require monitoring, planning or land management. The purpose of this paper was to develop a planning tool and decision making tool using AutoCAD Map software, ArcGIS and Google Earth with emphasis on the investigation of the suitability of forest roads' mapping and the range of its implementation in Greece in prefecture level. Integrating spatial information into a database makes data available throughout the organization; improving quality, productivity, and data management. Also working in such an environment, you can: Access and edit information, integrate and analyze data and communicate effectively. To select desirable information such as forest road network in a very early stage in the planning of silviculture operations, for example before the planning of the harvest is carried out. The software programs that were used were AutoCAD Map for the export in shape files for the GPS data, and ArcGIS in shape files (ArcGlobe), while Google Earth with KML files (Keyhole Markup Language) in order to better visualize and evaluate existing conditions, design in a real-world context and exchange information with government agencies, utilities, and contractors in both CAD and GIS data formats. The automation of the updating procedure and transfer of any files between agencies-departments is one of the main tasks of the integrated GIS-tool among the others should be addressed.

NASA Radar Images Show Continued Deformation from Mexico Quake

NASA Image and Video Library

2010-08-04

This image shows a UAVSAR interferogram swath overlaid atop a Google Earth image. New NASA airborne radar images show the continuing deformation in Earth surface resulting from the magnitude 7.2 temblor in Baja California on April 4, 2010.

An Hour of Spectacular Visualization

NASA Technical Reports Server (NTRS)

Hasler, Arthur F.

2005-01-01

The NASA/NOAA Electronic Theater presents Earth science observations and visualizations from space in a historical perspective. Fly in from outer space to Athens and site of the 2004 Summer Olympics and the Far East using 1 m IKONOS "Spy Satellite" data. Contrast the 1972 Apollo 17 "Blue Marble" image of the Earth with the latest US and International global satellite images that allow us to view our Planet from any vantage point. See the latest spectacular images from NASA/NOAA/Commercial remote sensing missions like Terra, GOES, TRMM, SeaWiFS, & Landsat 7, QuickBird of the SE Asia Tsunami, devastation of Hurricane Katrina this year in New Orleans, and the LA/San Diego Fires of 2003. See how High Definition Television (HDTV) is revolutionizing the way we do science communication. Take the pulse of the planet on a daily, annual and 30-year time scale. See daily thunderstorms, the annual blooming of the northern hemisphere land masses and oceans, fires in Africa, dust storms in Iraq, and carbon monoxide exhaust from global burning. See visualizations featured on Newsweek, TIME, National Geographic, Popular Science covers & National & International Network TV. Spectacular new global visualizations of the observed and simulated atmosphere & oceans are shown. See the currents and vortexes in the oceans that bring up the nutrients to feed tiny plankton and draw the fish, whales and fishermen. See the how the ocean blooms in response to El Nino/La Nina climate changes. The Etheater will be presented using the latest High Definition TV (HDTV) and video projection technology on a large screen. See city lights around the globe and in your area observed by the "night-vision" DMSP satellite, Also see how Keyhole and Google Maps are using satellite and aerial photography to help you find your house and plan your vacation.

Monitoring Urban Heat Island Through Google Earth Engine: Potentialities and Difficulties in Different Cities of the United States

NASA Astrophysics Data System (ADS)

Ravanelli, R.; Nascetti, A.; Cirigliano, R. V.; Di Rico, C.; Monti, P.; Crespi, M.

2018-04-01

The aim of this work is to exploit the large-scale analysis capabilities of the innovative Google Earth Engine platform in order to investigate the temporal variations of the Urban Heat Island phenomenon as a whole. A intuitive methodology implementing a largescale correlation analysis between the Land Surface Temperature and Land Cover alterations was thus developed.The results obtained for the Phoenix MA are promising and show how the urbanization heavily affects the magnitude of the UHI effects with significant increases in LST. The proposed methodology is therefore able to efficiently monitor the UHI phenomenon.

Changes of Earthquake Vulnerability of Marunouchi and Ginza Area in Tokyo and Urban Recovery Digital Archives on Google Earth

NASA Astrophysics Data System (ADS)

Igarashi, Masayasu; Murao, Osamu

In this paper, the authors develop a multiple regression model which estimates urban earthquake vulnerability (building collapse risk and conflagration risk) for different eras, and clarify the historical changes of urban risk in Marunouchi and Ginza Districts in Tokyo, Japan using old maps and contemporary geographic information data. Also, we compare the change of urban vulnerability of the districts with the significant historical events in Tokyo. Finally, the results are loaded onto Google Earth with timescale extension to consider the possibility of urban recovery digital archives in the era of the recent geoinformatic technologies.

Using ArcMap, Google Earth, and Global Positioning Systems to select and locate random households in rural Haiti.

PubMed

Wampler, Peter J; Rediske, Richard R; Molla, Azizur R

2013-01-18

A remote sensing technique was developed which combines a Geographic Information System (GIS); Google Earth, and Microsoft Excel to identify home locations for a random sample of households in rural Haiti. The method was used to select homes for ethnographic and water quality research in a region of rural Haiti located within 9 km of a local hospital and source of health education in Deschapelles, Haiti. The technique does not require access to governmental records or ground based surveys to collect household location data and can be performed in a rapid, cost-effective manner. The random selection of households and the location of these households during field surveys were accomplished using GIS, Google Earth, Microsoft Excel, and handheld Garmin GPSmap 76CSx GPS units. Homes were identified and mapped in Google Earth, exported to ArcMap 10.0, and a random list of homes was generated using Microsoft Excel which was then loaded onto handheld GPS units for field location. The development and use of a remote sensing method was essential to the selection and location of random households. A total of 537 homes initially were mapped and a randomized subset of 96 was identified as potential survey locations. Over 96% of the homes mapped using Google Earth imagery were correctly identified as occupied dwellings. Only 3.6% of the occupants of mapped homes visited declined to be interviewed. 16.4% of the homes visited were not occupied at the time of the visit due to work away from the home or market days. A total of 55 households were located using this method during the 10 days of fieldwork in May and June of 2012. The method used to generate and field locate random homes for surveys and water sampling was an effective means of selecting random households in a rural environment lacking geolocation infrastructure. The success rate for locating households using a handheld GPS was excellent and only rarely was local knowledge required to identify and locate households. This method provides an important technique that can be applied to other developing countries where a randomized study design is needed but infrastructure is lacking to implement more traditional participant selection methods.

Landforms in Lidar: Building a Catalog of Digital Landforms for Education and Outreach

NASA Astrophysics Data System (ADS)

Kleber, E.; Crosby, C.; Olds, S. E.; Arrowsmith, R.

2012-12-01

Lidar (Light Detection and Ranging) has emerged as a fundamental tool in the earth sciences. The collection of high-resolution lidar topography from an airborne or terrestrial platform allows landscapes and landforms to be spatially represented in at sub-meter resolution and in three dimensions. While the growing availability of lidar has led to numerous new scientific findings, these data also have tremendous value for earth science education. The study of landforms is an essential and basic element of earth science education that helps students to grasp fundamental earth system processes and how they manifest themselves in the world around us. Historically students are introduced to landforms and related processes through diagrams and images seen in earth science textbooks. Lidar data, coupled with free tools such as Google Earth, provide a means to allow students and the interested public to visualize, explore, and interrogate these same landforms in an interactive manner not possible in two-dimensional remotely sensed imagery. The NSF-funded OpenTopography facility hosts data collected for geologic, hydrologic, and biological research, covering a diverse range of landscapes, and thus provides a wealth of data that could be incorporated into educational materials. OpenTopography, in collaboration with UNAVCO, are developing a catalog of classic geologic landforms depicted in lidar. Beginning with textbook-examples of features such as faults and tectonic landforms, dunes, fluvial and glacial geomorphology, and natural hazards such as landslides and volcanoes, the catalog will be an online resource for educators and the interested public. Initially, the landforms will be sourced from pre-existing datasets hosted by OpenTopography. Users will see an image representative of the landform then have the option to download the data in Google Earth KMZ format, as a digital elevation model, or the original lidar point cloud file. By providing the landform in a range of data types, educators can choose to load the image into a presentation, work with the data in a GIS, or do more advanced data analysis on the original point cloud data. In addition, for each landform, links to additional online resources and a bibliography of select publications will be provided. OpenTopography will initially seed the lidar landform catalog, but ultimately the goal is to solicit community contributions as well. We envision the catalog development as the first phase of this activity, and hope that later activities will focus on building curriculum that leverages the catalog and lidar data to teach earth system processes.

Web-based visualization of gridded dataset usings OceanBrowser

NASA Astrophysics Data System (ADS)

Barth, Alexander; Watelet, Sylvain; Troupin, Charles; Beckers, Jean-Marie

2015-04-01

OceanBrowser is a web-based visualization tool for gridded oceanographic data sets. Those data sets are typically four-dimensional (longitude, latitude, depth and time). OceanBrowser allows one to visualize horizontal sections at a given depth and time to examine the horizontal distribution of a given variable. It also offers the possibility to display the results on an arbitrary vertical section. To study the evolution of the variable in time, the horizontal and vertical sections can also be animated. Vertical section can be generated by using a fixed distance from coast or fixed ocean depth. The user can customize the plot by changing the color-map, the range of the color-bar, the type of the plot (linearly interpolated color, simple contours, filled contours) and download the current view as a simple image or as Keyhole Markup Language (KML) file for visualization in applications such as Google Earth. The data products can also be accessed as NetCDF files and through OPeNDAP. Third-party layers from a web map service can also be integrated. OceanBrowser is used in the frame of the SeaDataNet project (http://gher-diva.phys.ulg.ac.be/web-vis/) and EMODNET Chemistry (http://oceanbrowser.net/emodnet/) to distribute gridded data sets interpolated from in situ observation using DIVA (Data-Interpolating Variational Analysis).

Cartographic analyses of geographic information available on Google Earth Images

NASA Astrophysics Data System (ADS)

Oliveira, J. C.; Ramos, J. R.; Epiphanio, J. C.

2011-12-01

The propose was to evaluate planimetric accuracy of satellite images available on database of Google Earth. These images are referents to the vicinities of the Federal Univertisity of Viçosa, Minas Gerais - Brazil. The methodology developed evaluated the geographical information of three groups of images which were in accordance to the level of detail presented in the screen images (zoom). These groups of images were labeled to Zoom 1000 (a single image for the entire study area), Zoom 100 (formed by a mosaic of 73 images) and Zoom 100 with geometric correction (this mosaic is like before, however, it was applied a geometric correction through control points). In each group of image was measured the Cartographic Accuracy based on statistical analyses and brazilian's law parameters about planimetric mapping. For this evaluation were identified 22 points in each group of image, where the coordinates of each point were compared to the coordinates of the field obtained by GPS (Global Positioning System). The Table 1 show results related to accuracy (based on a threshold equal to 0.5 mm * mapping scale) and tendency (abscissa and ordinate) between the coordinates of the image and the coordinates of field. Table 1 The geometric correction applied to the Group Zoom 100 reduced the trends identified earlier, and the statistical tests pointed a usefulness of the data for a mapping at a scale of 1/5000 with error minor than 0.5 mm * scale. The analyses proved the quality of cartographic data provided by Google, as well as the possibility of reduce the divergences of positioning present on the data. It can be concluded that it is possible to obtain geographic information database available on Google Earth, however, the level of detail (zoom) used at the time of viewing and capturing information on the screen influences the quality cartographic of the mapping. Although cartographic and thematic potential present in the database, it is important to note that both the software as data distributed by Google Earth has policies for use and distribution.
Table 1 - PLANIMETRIC ANALYSIS

Towards the Geospatial Web: Media Platforms for Managing Geotagged Knowledge Repositories

NASA Astrophysics Data System (ADS)

Scharl, Arno

International media have recognized the visual appeal of geo-browsers such as NASA World Wind and Google Earth, for example, when Web and television coverage on Hurricane Katrina used interactive geospatial projections to illustrate its path and the scale of destruction in August 2005. Yet these early applications only hint at the true potential of geospatial technology to build and maintain virtual communities and to revolutionize the production, distribution and consumption of media products. This chapter investigates this potential by reviewing the literature and discussing the integration of geospatial and semantic reference systems, with an emphasis on extracting geospatial context from unstructured text. A content analysis of news coverage based on a suite of text mining tools (webLyzard) sheds light on the popularity and adoption of geospatial platforms.

Satellite Imagery Assisted Road-Based Visual Navigation System

NASA Astrophysics Data System (ADS)

Volkova, A.; Gibbens, P. W.

2016-06-01

There is a growing demand for unmanned aerial systems as autonomous surveillance, exploration and remote sensing solutions. Among the key concerns for robust operation of these systems is the need to reliably navigate the environment without reliance on global navigation satellite system (GNSS). This is of particular concern in Defence circles, but is also a major safety issue for commercial operations. In these circumstances, the aircraft needs to navigate relying only on information from on-board passive sensors such as digital cameras. An autonomous feature-based visual system presented in this work offers a novel integral approach to the modelling and registration of visual features that responds to the specific needs of the navigation system. It detects visual features from Google Earth* build a feature database. The same algorithm then detects features in an on-board cameras video stream. On one level this serves to localise the vehicle relative to the environment using Simultaneous Localisation and Mapping (SLAM). On a second level it correlates them with the database to localise the vehicle with respect to the inertial frame. The performance of the presented visual navigation system was compared using the satellite imagery from different years. Based on comparison results, an analysis of the effects of seasonal, structural and qualitative changes of the imagery source on the performance of the navigation algorithm is presented. * The algorithm is independent of the source of satellite imagery and another provider can be used

Multi-Instrument Tools and Services to Access NASA Earth Science Data from the GSFC Earth Sciences Data and Information Services Center

NASA Technical Reports Server (NTRS)

Kempler, Steve; Leptoukh, Greg; Lynnes, Chris

2010-01-01

The presentation purpose is to describe multi-instrument tools and services that facilitate access and usability of NASA Earth science data at Goddard Space Flight Center (GSFC). NASA's Earth observing system includes 14 satellites. Topics include EOSDIS facilities and system architecture, and overview of GSFC Earth Science Data and Information Services Center (GES DISC) mission, Mirador data search, Giovanni, multi-instrument data exploration, Google Earth[TM], data merging, and applications.

Using Google Streetview Panoramic Imagery for Geoscience Education

NASA Astrophysics Data System (ADS)

De Paor, D. G.; Dordevic, M. M.

2014-12-01

Google Streetview is a feature of Google Maps and Google Earth that allows viewers to switch from map or satellite view to 360° panoramic imagery recorded close to the ground. Most panoramas are recorded by Google engineers using special cameras mounted on the roofs of cars. Bicycles, snowmobiles, and boats have also been used and sometimes the camera has been mounted on a backpack for off-road use by hikers and skiers or attached to scuba-diving gear for "Underwater Streetview (sic)." Streetview panoramas are linked together so that the viewer can change viewpoint by clicking forward and reverse buttons. They therefore create a 4-D touring effect. As part of the GEODE project ("Google Earth for Onsite and Distance Education"), we are experimenting with the use of Streetview imagery for geoscience education. Our web-based test application allows instructors to select locations for students to study. Students are presented with a set of questions or tasks that they must address by studying the panoramic imagery. Questions include identification of rock types, structures such as faults, and general geological setting. The student view is locked into Streetview mode until they submit their answers, whereupon the map and satellite views become available, allowing students to zoom out and verify their location on Earth. Student learning is scaffolded by automatic computerized feedback. There are lots of existing Streetview panoramas with rich geological content. Additionally, instructors and members of the general public can create panoramas, including 360° Photo Spheres, by stitching images taken with their mobiles devices and submitting them to Google for evaluation and hosting. A multi-thousand-dollar, multi-directional camera and mount can be purchased from DIY-streetview.com. This allows power users to generate their own high-resolution panoramas. A cheaper, 360° video camera is soon to be released according to geonaute.com. Thus there are opportunities for geoscience educators both to use existing Streetview imagery and to generate new imagery for specific locations of geological interest. The GEODE team includes the authors and: H. Almquist, C. Bentley, S. Burgin, C. Cervato, G. Cooper, P. Karabinos, T. Pavlis, J. Piatek, B. Richards, J. Ryan, R. Schott, K. St. John, B. Tewksbury, and S. Whitmeyer.

Exploring Research Contributions of the North American Carbon Program using Google Earth and Google Map

NASA Astrophysics Data System (ADS)

Griffith, P. C.; Wilcox, L. E.; Morrell, A.

2009-12-01

The central objective of the North American Carbon Program (NACP), a core element of the US Global Change Research Program, is to quantify the sources and sinks of carbon dioxide, carbon monoxide, and methane in North America and adjacent ocean regions. The NACP consists of a wide range of investigators at universities and federal research centers. Although many of these investigators have worked together in the past, many have had few prior interactions and may not know of similar work within knowledge domains, much less across the diversity of environments and scientific approaches in the Program. Coordinating interactions and sharing data are major challenges in conducting NACP. The Google Earth and Google Map Collections on the NACP website (www.nacarbon.org) provide a geographical view of the research products contributed by each core and affiliated NACP project. Other relevant data sources (e.g. AERONET, LVIS) can also be browsed in spatial context with NACP contributions. Each contribution links to project-oriented metadata, or “project profiles”, that provide a greater understanding of the scientific and social context of each dataset and are an important means of communicating within the NACP and to the larger carbon cycle science community. Project profiles store information such as a project's title, leaders, participants, an abstract, keywords, funding agencies, associated intensive campaigns, expected data products, data needs, publications, and URLs to associated data centers, datasets, and metadata. Data products are research contributions that include biometric inventories, flux tower estimates, remote sensing land cover products, tools, services, and model inputs / outputs. Project leaders have been asked to identify these contributions to the site level whenever possible, either through simple latitude/longitude pair, or by uploading a KML, KMZ, or shape file. Project leaders may select custom icons to graphically categorize their contributions; for example, a ship for oceanographic samples, a tower for tower measurements. After post-processing, research contributions are added to the NACP Google Earth and Google Map Collection to facilitate discovery and use in synthesis activities of the Program.

Design and Deployment of a General Purpose, Open Source LoRa to Wi-Fi Hub and Data Logger

NASA Astrophysics Data System (ADS)

DeBell, T. C.; Udell, C.; Kwon, M.; Selker, J. S.; Lopez Alcala, J. M.

2017-12-01

Methods and technologies facilitating internet connectivity and near-real-time status updates for in site environmental sensor data are of increasing interest in Earth Science. However, Open Source, Do-It-Yourself technologies that enable plug and play functionality for web-connected sensors and devices remain largely inaccessible for typical researchers in our community. The Openly Published Environmental Sensing Lab at Oregon State University (OPEnS Lab) constructed an Open Source 900 MHz Long Range Radio (LoRa) receiver hub with SD card data logger, Ethernet and Wi-Fi shield, and 3D printed enclosure that dynamically uploads transmissions from multiple wirelessly-connected environmental sensing devices. Data transmissions may be received from devices up to 20km away. The hub time-stamps, saves to SD card, and uploads all transmissions to a Google Drive spreadsheet to be accessed in near-real-time by researchers and GeoVisualization applications (such as Arc GIS) for access, visualization, and analysis. This research expands the possibilities of scientific observation of our Earth, transforming the technology, methods, and culture by combining open-source development and cutting edge technology. This poster details our methods and evaluates the application of using 3D printing, Arduino Integrated Development Environment (IDE), Adafruit's Open-Hardware Feather development boards, and the WIZNET5500 Ethernet shield for designing this open-source, general purpose LoRa to Wi-Fi data logger.

Global Precipitation Measurement (GPM) Mission Products and Services at the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC)

NASA Technical Reports Server (NTRS)

Ostrenga, D.; Liu, Z.; Vollmer, B.; Teng, W.; Kempler, S.

2014-01-01

On February 27, 2014, the NASA Global Precipitation Measurement (GPM) mission was launched to provide the next-generation global observations of rain and snow (http:pmm.nasa.govGPM). The GPM mission consists of an international network of satellites in which a GPM Core Observatory satellite carries both active and passive microwave instruments to measure precipitation and serve as a reference standard, to unify precipitation measurements from a constellation of other research and operational satellites. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) hosts and distributes GPM data within the NASA Earth Observation System Data Information System (EOSDIS). The GES DISC is home to the data archive for the GPM predecessor, the Tropical Rainfall Measuring Mission (TRMM). Over the past 16 years, the GES DISC has served the scientific as well as other communities with TRMM data and user-friendly services. During the GPM era, the GES DISC will continue to provide user-friendly data services and customer support to users around the world. GPM products currently and to-be available include the following:Level-1 GPM Microwave Imager (GMI) and partner radiometer productsLevel-2 Goddard Profiling Algorithm (GPROF) GMI and partner productsLevel-3 daily and monthly productsIntegrated Multi-satellitE Retrievals for GPM (IMERG) products (early, late, and final) A dedicated Web portal (including user guides, etc.) has been developed for GPM data (http:disc.sci.gsfc.nasa.govgpm). Data services that are currently and to-be available include Google-like Mirador (http:mirador.gsfc.nasa.gov) for data search and access; data access through various Web services (e.g., OPeNDAP, GDS, WMS, WCS); conversion into various formats (e.g., netCDF, HDF, KML (for Google Earth), ASCII); exploration, visualization, and statistical online analysis through Giovanni (http:giovanni.gsfc.nasa.gov); generation of value-added products; parameter and spatial subsetting; time aggregation; regridding; data version control and provenance; documentation; science support for proper data usage, FAQ, help desk; monitoring services (e.g. Current Conditions) for applications.

Global Precipitation Measurement (GPM) Mission Products and Services at the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC)

NASA Technical Reports Server (NTRS)

Liu, Zhong; Ostrenga, D.; Vollmer, B.; Deshong, B.; Greene, M.; Teng, W.; Kempler, S. J.

2015-01-01

On February 27, 2014, the NASA Global Precipitation Measurement (GPM) mission was launched to provide the next-generation global observations of rain and snow (http:pmm.nasa.govGPM). The GPM mission consists of an international network of satellites in which a GPM Core Observatory satellite carries both active and passive microwave instruments to measure precipitation and serve as a reference standard, to unify precipitation measurements from a constellation of other research and operational satellites. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) hosts and distributes GPM data within the NASA Earth Observation System Data Information System (EOSDIS). The GES DISC is home to the data archive for the GPM predecessor, the Tropical Rainfall Measuring Mission (TRMM). Over the past 16 years, the GES DISC has served the scientific as well as other communities with TRMM data and user-friendly services. During the GPM era, the GES DISC will continue to provide user-friendly data services and customer support to users around the world. GPM products currently and to-be available include the following: 1. Level-1 GPM Microwave Imager (GMI) and partner radiometer products. 2. Goddard Profiling Algorithm (GPROF) GMI and partner products. 3. Integrated Multi-satellitE Retrievals for GPM (IMERG) products. (early, late, and final)A dedicated Web portal (including user guides, etc.) has been developed for GPM data (http:disc.sci.gsfc.nasa.govgpm). Data services that are currently and to-be available include Google-like Mirador (http:mirador.gsfc.nasa.gov) for data search and access; data access through various Web services (e.g., OPeNDAP, GDS, WMS, WCS); conversion into various formats (e.g., netCDF, HDF, KML (for Google Earth), ASCII); exploration, visualization, and statistical online analysis through Giovanni (http:giovanni.gsfc.nasa.gov); generation of value-added products; parameter and spatial subsetting; time aggregation; regridding; data version control and provenance; documentation; science support for proper data usage, FAQ, help desk; monitoring services (e.g. Current Conditions) for applications.In this presentation, we will present GPM data products and services with examples.

Global Precipitation Measurement (GPM) Mission Products and Services at the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC)

NASA Astrophysics Data System (ADS)

Ostrenga, D.; Liu, Z.; Vollmer, B.; Teng, W. L.; Kempler, S. J.

2014-12-01

On February 27, 2014, the NASA Global Precipitation Measurement (GPM) mission was launched to provide the next-generation global observations of rain and snow (http://pmm.nasa.gov/GPM). The GPM mission consists of an international network of satellites in which a GPM "Core Observatory" satellite carries both active and passive microwave instruments to measure precipitation and serve as a reference standard, to unify precipitation measurements from a constellation of other research and operational satellites. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) hosts and distributes GPM data within the NASA Earth Observation System Data Information System (EOSDIS). The GES DISC is home to the data archive for the GPM predecessor, the Tropical Rainfall Measuring Mission (TRMM). Over the past 16 years, the GES DISC has served the scientific as well as other communities with TRMM data and user-friendly services. During the GPM era, the GES DISC will continue to provide user-friendly data services and customer support to users around the world. GPM products currently and to-be available include the following: Level-1 GPM Microwave Imager (GMI) and partner radiometer products Goddard Profiling Algorithm (GPROF) GMI and partner products Integrated Multi-satellitE Retrievals for GPM (IMERG) products (early, late, and final) A dedicated Web portal (including user guides, etc.) has been developed for GPM data (http://disc.sci.gsfc.nasa.gov/gpm). Data services that are currently and to-be available include Google-like Mirador (http://mirador.gsfc.nasa.gov/) for data search and access; data access through various Web services (e.g., OPeNDAP, GDS, WMS, WCS); conversion into various formats (e.g., netCDF, HDF, KML (for Google Earth), ASCII); exploration, visualization, and statistical online analysis through Giovanni (http://giovanni.gsfc.nasa.gov); generation of value-added products; parameter and spatial subsetting; time aggregation; regridding; data version control and provenance; documentation; science support for proper data usage, FAQ, help desk; monitoring services (e.g. Current Conditions) for applications. In this presentation, we will present GPM data products and services with examples.

Integrated visualization of remote sensing data using Google Earth

NASA Astrophysics Data System (ADS)

Castella, M.; Rigo, T.; Argemi, O.; Bech, J.; Pineda, N.; Vilaclara, E.

2009-09-01

The need for advanced visualization tools for meteorological data has lead in the last years to the development of sophisticated software packages either by observing systems manufacturers or by third-party solution providers. For example, manufacturers of remote sensing systems such as weather radars or lightning detection systems include zoom, product selection, archive access capabilities, as well as quantitative tools for data analysis, as standard features which are highly appreciated in weather surveillance or post-event case study analysis. However, the fact that each manufacturer has its own visualization system and data formats hampers the usability and integration of different data sources. In this context, Google Earth (GE) offers the possibility of combining several graphical information types in a unique visualization system which can be easily accessed by users. The Meteorological Service of Catalonia (SMC) has been evaluating the use of GE as a visualization platform for surveillance tasks in adverse weather events. First experiences are related to the integration in real-time of remote sensing data: radar, lightning, and satellite. The tool shows the animation of the combined products in the last hour, giving a good picture of the meteorological situation. One of the main advantages of this product is that is easy to be installed in many computers and does not need high computational requirements. Besides this, the capability of GE provides information about the most affected areas by heavy rain or other weather phenomena. On the opposite, the main disadvantage is that the product offers only qualitative information, and quantitative data is only available though the graphical display (i.e. trough color scales but not associated to physical values that can be accessed by users easily). The procedure developed to run in real time is divided in three parts. First of all, a crontab file launches different applications, depending on the data type (satellite, radar, or lightning) to be treated. For each type of data, the time of launching is different, and goes from 5 (satellite and lightning) to 6 minutes (radar). The second part is the use of IDL and ENVI programs, which search in each archive file the last images in one hour. In the case of lightning data, the files are generated for the procedure, while for the others the procedure searches for existing imagery. Finally, the procedure generates metadata information required by GE, kml files, and sends them to the internal server. At the same time, in the local computer where GE is running, there exists kml files which update the information referring to the server ones. Another application that has been evaluated is the analysis of past events. In this sense, further work is devoted to develop access procedures to archived data via cgi scripts in order to retrieve and convert the information in a format suitable for GE. The presentation includes examples of the evaluation of the use of GE, and a brief comparison with other existing visualization systems available within the SMC.

New Tools for Viewing Spectrally and Temporally-Rich Remote Sensing Imagery

NASA Astrophysics Data System (ADS)

Bradley, E. S.; Toomey, M. P.; Roberts, D. A.; Still, C. J.

2010-12-01

High frequency, temporally extensive remote sensing datasets (GOES: 30 minutes, Santa Cruz Island webcam: nearly 5 years at every 10 min.) and airborne imaging spectrometry (AVIRIS with 224 spectral bands), present exciting opportunities for education, synthesis, and analysis. However, the large file volume / size can make holistic review and exploration difficult. In this research, we explore two options for visualization (1) a web-based portal for time-series analysis, PanOpt, and (2) Google Earth-based timestamped image overlays. PanOpt is an interactive website (http://zulu.geog.ucsb.edu/panopt/), which integrates high frequency (GOES) and multispectral (MODIS) satellite imagery with webcam ground-based repeat photography. Side-by-side comparison of satellite imagery with webcam images supports analysis of atmospheric and environmental phenomena. In this proof of concept, we have integrated four years of imagery for a multi-view FogCam on Santa Cruz Island off the coast of Southern California with two years of GOES-11 and four years of MODIS Aqua imagery subsets for the area (14,000 km2). From the PHP-based website, users can search the data (date, time of day, etc.) and specify timestep and display size; and then view the image stack as animations or in a matrix form. Extracted metrics for regions of interest (ROIs) can be viewed in different formats, including time-series and scatter plots. Through click and mouseover actions over the hyperlink-enabled data points, users can view the corresponding images. This directly melds the quantitative and qualitative aspects and could be particularly effective for both education as well as anomaly interpretation. We have also extended this project to Google Earth with timestamped GOES and MODIS image overlays, which can be controlled using the temporal slider and linked to a screen chart of ancillary meteorological data. The automated ENVI/IDL script for generating KMZ overlays was also applied for generating same-day visualization of AVIRIS acquisitions as part of the Gulf of Mexico oil spill response. This supports location-focused imagery review and synthesis, which is critical for successfully imaging moving targets, such as oil slicks.

Interactive Visualization of Near Real-Time and Production Global Precipitation Mission Data Online Using CesiumJS

NASA Astrophysics Data System (ADS)

Lammers, M.

2016-12-01

Advancements in the capabilities of JavaScript frameworks and web browsing technology make online visualization of large geospatial datasets viable. Commonly this is done using static image overlays, pre-rendered animations, or cumbersome geoservers. These methods can limit interactivity and/or place a large burden on server-side post-processing and storage of data. Geospatial data, and satellite data specifically, benefit from being visualized both on and above a three-dimensional surface. The open-source JavaScript framework CesiumJS, developed by Analytical Graphics, Inc., leverages the WebGL protocol to do just that. It has entered the void left by the abandonment of the Google Earth Web API, and it serves as a capable and well-maintained platform upon which data can be displayed. This paper will describe the technology behind the two primary products developed as part of the NASA Precipitation Processing System STORM website: GPM Near Real Time Viewer (GPMNRTView) and STORM Virtual Globe (STORM VG). GPMNRTView reads small post-processed CZML files derived from various Level 1 through 3 near real-time products. For swath-based products, several brightness temperature channels or precipitation-related variables are available for animating in virtual real-time as the satellite observed them on and above the Earth's surface. With grid-based products, only precipitation rates are available, but the grid points are visualized in such a way that they can be interactively examined to explore raw values. STORM VG reads values directly off the HDF5 files, converting the information into JSON on the fly. All data points both on and above the surface can be examined here as well. Both the raw values and, if relevant, elevations are displayed. Surface and above-ground precipitation rates from select Level 2 and 3 products are shown. Examples from both products will be shown, including visuals from high impact events observed by GPM constellation satellites.

Interactive Visualization of Near Real Time and Production Global Precipitation Measurement (GPM) Mission Data Online Using CesiumJS

NASA Technical Reports Server (NTRS)

Lammers, Matthew

2016-01-01

Advancements in the capabilities of JavaScript frameworks and web browsing technology make online visualization of large geospatial datasets viable. Commonly this is done using static image overlays, prerendered animations, or cumbersome geoservers. These methods can limit interactivity andor place a large burden on server-side post-processing and storage of data. Geospatial data, and satellite data specifically, benefit from being visualized both on and above a three-dimensional surface. The open-source JavaScript framework CesiumJS, developed by Analytical Graphics, Inc., leverages the WebGL protocol to do just that. It has entered the void left by the abandonment of the Google Earth Web API, and it serves as a capable and well-maintained platform upon which data can be displayed. This paper will describe the technology behind the two primary products developed as part of the NASA Precipitation Processing System STORM website: GPM Near Real Time Viewer (GPMNRTView) and STORM Virtual Globe (STORM VG). GPMNRTView reads small post-processed CZML files derived from various Level 1 through 3 near real-time products. For swath-based products, several brightness temperature channels or precipitation-related variables are available for animating in virtual real-time as the satellite-observed them on and above the Earths surface. With grid-based products, only precipitation rates are available, but the grid points are visualized in such a way that they can be interactively examined to explore raw values. STORM VG reads values directly off the HDF5 files, converting the information into JSON on the fly. All data points both on and above the surface can be examined here as well. Both the raw values and, if relevant, elevations are displayed. Surface and above-ground precipitation rates from select Level 2 and 3 products are shown. Examples from both products will be shown, including visuals from high impact events observed by GPM constellation satellites.

Resources for Designing, Selecting and Teaching with Visualizations in the Geoscience Classroom

NASA Astrophysics Data System (ADS)

Kirk, K. B.; Manduca, C. A.; Ormand, C. J.; McDaris, J. R.

2009-12-01

Geoscience is a highly visual field, and effective use of visualizations can enhance student learning, appeal to students’ emotions and help them acquire skills for interpreting visual information. The On the Cutting Edge website, “Teaching Geoscience with Visualizations” presents information of interest to faculty who are teaching with visualizations, as well as those who are designing visualizations. The website contains best practices for effective visualizations, drawn from the educational literature and from experts in the field. For example, a case is made for careful selection of visualizations so that faculty can align the correct visualization with their teaching goals and audience level. Appropriate visualizations will contain the desired geoscience content without adding extraneous information that may distract or confuse students. Features such as labels, arrows and contextual information can help guide students through imagery and help to explain the relevant concepts. Because students learn by constructing their own mental image of processes, it is helpful to select visualizations that reflect the same type of mental picture that students should create. A host of recommended readings and presentations from the On the Cutting Edge visualization workshops can provide further grounding for the educational uses of visualizations. Several different collections of visualizations, datasets with visualizations and visualization tools are available on the website. Examples include animations of tsunamis, El Nino conditions, braided stream formation and mountain uplift. These collections are grouped by topic and range from simple animations to interactive models. A series of example activities that incorporate visualizations into classroom and laboratory activities illustrate various tactics for using these materials in different types of settings. Activities cover topics such as ocean circulation, land use changes, earthquake simulations and the use of Google Earth to explore geologic processes. These materials can be found at http://serc.carleton.edu/NAGTWorkshops/visualization. Faculty and developers of visualization tools are encouraged to submit teaching activities, references or visualizations to the collections.

Virtual Field Trips: Using Google Maps to Support Online Learning and Teaching of the History of Astronomy

ERIC Educational Resources Information Center

Fluke, Christopher J.

2009-01-01

I report on a pilot study on the use of Google Maps to provide virtual field trips as a component of a wholly online graduate course on the history of astronomy. The Astronomical Tourist Web site (http://astronomy.swin.edu.au/sao/tourist), themed around the role that specific locations on Earth have contributed to the development of astronomical…

An Interactive Web System for Field Data Sharing and Collaboration

NASA Astrophysics Data System (ADS)

Weng, Y.; Sun, F.; Grigsby, J. D.

2010-12-01

A Web 2.0 system is designed and developed to facilitate data collection for the field studies in the Geological Sciences department at Ball State University. The system provides a student-centered learning platform that enables the users to first upload their collected data in various formats, interact and collaborate dynamically online, and ultimately create a shared digital repository of field experiences. The data types considered for the system and their corresponding format and requirements are listed in the table below. The system has six main functionalities as follows. (1) Only the registered users can access the system with confidential identification and password. (2) Each user can upload/revise/delete data in various formats such as image, audio, video, and text files to the system. (3) Interested users are allowed to co-edit the contents and join the collaboration whiteboard for further discussion. (4) The system integrates with Google, Yahoo, or Flickr to search for similar photos with same tags. (5) Users can search the web system according to the specific key words. (6) Photos with recorded GPS readings can be mashed and mapped to Google Maps/Earth for visualization. Application of the system to geology field trips at Ball State University will be demonstrated to assess the usability of the system.Data Requirements

Using 3D Printers to Model Earth Surface Topography for Increased Student Understanding and Retention

NASA Astrophysics Data System (ADS)

Thesenga, David; Town, James

2014-05-01

In February 2000, the Space Shuttle Endeavour flew a specially modified radar system during an 11-day mission. The purpose of the multinational Shuttle Radar Topography Mission (SRTM) was to "obtain elevation data on a near-global scale to generate the most complete high-resolution digital topographic database of Earth" by using radar interferometry. The data and resulting products are now publicly available for download and give a view of the landscape removed of vegetation, buildings, and other structures. This new view of the Earth's topography allows us to see previously unmapped or poorly mapped regions of the Earth as well as providing a level of detail that was previously unknown using traditional topographic mapping techniques. Understanding and appreciating the geographic terrain is a complex but necessary requirement for middle school aged (11-14yo) students. Abstract in nature, topographic maps and other 2D renderings of the Earth's surface and features do not address the inherent spatial challenges of a concrete-learner and traditional methods of teaching can at times exacerbate the problem. Technological solutions such as 3D-imaging in programs like Google Earth are effective but lack the tactile realness that can make a large difference in learning comprehension and retention for these young students. First developed in the 1980's, 3D printers were not commercial reality until recently and the rapid rise in interest has driven down the cost. With the advent of sub US1500 3D printers, this technology has moved out of the high-end marketplace and into the local office supply store. Schools across the US and elsewhere in the world are adding 3D printers to their technological workspaces and students have begun rapid-prototyping and manufacturing a variety of projects. This project attempted to streamline the process of transforming SRTM data from a GeoTIFF format by way of Python code. The resulting data was then inputted into a CAD-based program for visualization and exporting as a .stl file for 3D printing. A proposal for improving the method and making it more accessible to middle school aged students is provided. Using the SRTM data to print a hand-held visual representation of a portion of the Earth's surface would utilize existing technology in the school and alter how topography can be taught in the classroom. Combining methods of 2D paper representations, on-screen 3D visualizations, and 3D hand-held models, give students the opportunity to truly grasp and retain the information being provided.

Using Google Earth to Explore Strain Rate Models of Southern California

NASA Astrophysics Data System (ADS)

Richard, G. A.; Bell, E. A.; Holt, W. E.

2007-12-01

A series of strain rate models for the Transverse Ranges of southern California were developed based on Quaternary fault slip data and geodetic data from high precision GPS stations in southern California. Pacific-North America velocity boundary conditions are applied for all models. Topography changes are calculated using the model dilatation rates, which predict crustal thickness changes under the assumption of Airy isostasy and a specified rate of crustal volume loss through erosion. The models were designed to produce graphical and numerical output representing the configuration of the region from 3 million years ago to 3 million years into the future at intervals of 50 thousand years. Using a North American reference frame, graphical output for the topography and faults and numerical output for locations of faults and points on the crust marked by the locations on cities were used to create data in KML format that can be used in Google Earth to represent time intervals of 50 thousand years. As markers familiar to students, the cities provide a geographic context that can be used to quantify crustal movement, using the Google Earth ruler tool. By comparing distances that markers for selected cities have moved in various parts of the region, students discover that the greatest amount of crustal deformation has occurred in the vicinity of the boundary between the North American and Pacific plates. Students can also identify areas of compression or extension by finding pairs of city markers that have converged or diverged, respectively, over time. The Google Earth layers also reveal that faults that are not parallel to the plate boundary have tended to rotate clockwise due to the right lateral motion along the plate boundary zone. KML TimeSpan markup was added to two versions of the model, enabling the layers to be displayed in an automatic sequenced loop for a movie effect. The data is also available as QuickTime (.mov) and Graphics Interchange Format (.gif) animations and in ESRI Shapefile format.

Interactive Volcano Studies and Education Using Virtual Globes

NASA Astrophysics Data System (ADS)

Dehn, J.; Bailey, J. E.; Webley, P.

2006-12-01

Internet-based virtual globe programs such as Google Earth provide a spatial context for visualization of monitoring and geophysical data sets. At the Alaska Volcano Observatory, Google Earth is being used to integrate satellite imagery, modeling of volcanic eruption clouds and seismic data sets to build new monitoring and reporting tools. However, one of the most useful information sources for environmental monitoring is under utilized. Local populations, who have lived near volcanoes for decades are perhaps one of the best gauges for changes in activity. Much of the history of the volcanoes is only recorded through local legend. By utilizing the high level of internet connectivity in Alaska, and the interest of secondary education in environmental science and monitoring, it is proposed to build a network of observation nodes around local schools in Alaska and along the Aleutian Chain. A series of interactive web pages with observations on a volcano's condition, be it glow at night, puffs of ash, discolored snow, earthquakes, sounds, and even current weather conditions can be recorded, and the users will be able to see their reports in near real time. The database will create a KMZ file on the fly for upload into the virtual globe software. Past observations and legends could be entered to help put a volcano's long-term activity in perspective. Beyond the benefit to researchers and emergency managers, students and teachers in the rural areas will be involved in volcano monitoring, and gain an understanding of the processes and hazard mitigation efforts in their community. K-12 students will be exposed to the science, and encouraged to participate in projects at the university. Infrastructure at the university can be used by local teachers to augment their science programs, hopefully encouraging students to continue their education at the university level.

NARSTO EPA SS PITTSBURGH GAS PM PROPERTY DATA

Atmospheric Science Data Center

2018-04-09

... Sizer Nephelometer Aerosol Collector SMPS - Scanning Mobility Particle Sizer Fluorescence Spectroscopy ... Get Google Earth Related Data:  Environmental Protection Agency Supersites Pittsburgh, Pennsylvania ...

[Establishment of malaria early warning system in Jiangsu Province II application of digital earth system in malaria epidemic management and surveillance].

PubMed

Wang, Wei-Ming; Zhou, Hua-Yun; Liu, Yao-Bao; Li, Ju-Lin; Cao, Yuan-Yuan; Cao, Jun

2013-04-01

To explore a new mode of malaria elimination through the application of digital earth system in malaria epidemic management and surveillance. While we investigated the malaria cases and deal with the epidemic areas in Jiangsu Province in 2011, we used JISIBAO UniStrong G330 GIS data acquisition unit (GPS) to collect the latitude and longitude of the cases located, and then established a landmark library about early-warning areas and an image management system by using Google Earth Free 6.2 and its image processing software. A total of 374 malaria cases were reported in Jiangsu Province in 2011. Among them, there were 13 local vivax malaria cases, 11 imported vivax malaria cases from other provinces, 20 abroad imported vivax malaria cases, 309 abroad imported falciparum malaria cases, 7 abroad imported quartan malaria cases (Plasmodium malaria infection), and 14 abroad imported ovale malaria cases (P. ovale infection). Through the analysis of Google Earth Mapping system, these malaria cases showed a certain degree of aggregation except the abroad imported quartan malaria cases which were highly sporadic. The local vivax malaria cases mainly concentrated in Sihong County, the imported vivax malaria cases from other provinces mainly concentrated in Suzhou City and Wuxi City, the abroad imported vivax malaria cases concentrated in Nanjing City, the abroad imported falciparum malaria cases clustered in the middle parts of Jiangsu Province, and the abroad imported ovale malaria cases clustered in Liyang City. The operation of Google Earth Free 6.2 is simple, convenient and quick, which could help the public health authority to make the decision of malaria prevention and control, including the use of funds and other health resources.

PsyGlass: Capitalizing on Google Glass for naturalistic data collection.

PubMed

Paxton, Alexandra; Rodriguez, Kevin; Dale, Rick

2015-09-01

As commercial technology moves further into wearable technologies, cognitive and psychological scientists can capitalize on these devices to facilitate naturalistic research designs while still maintaining strong experimental control. One such wearable technology is Google Glass (Google, Inc.: www.google.com/glass), which can present wearers with audio and visual stimuli while tracking a host of multimodal data. In this article, we introduce PsyGlass, a framework for incorporating Google Glass into experimental work that is freely available for download and community improvement over time (www.github.com/a-paxton/PsyGlass). As a proof of concept, we use this framework to investigate dual-task pressures on naturalistic interaction. The preliminary study demonstrates how designs from classic experimental psychology may be integrated in naturalistic interactive designs with emerging technologies. We close with a series of recommendations for using PsyGlass and a discussion of how wearable technology more broadly may contribute to new or adapted naturalistic research designs.

A System for Traffic Violation Detection

PubMed Central

Aliane, Nourdine; Fernandez, Javier; Mata, Mario; Bemposta, Sergio

2014-01-01

This paper describes the framework and components of an experimental platform for an advanced driver assistance system (ADAS) aimed at providing drivers with a feedback about traffic violations they have committed during their driving. The system is able to detect some specific traffic violations, record data associated to these faults in a local data-base, and also allow visualization of the spatial and temporal information of these traffic violations in a geographical map using the standard Google Earth tool. The test-bed is mainly composed of two parts: a computer vision subsystem for traffic sign detection and recognition which operates during both day and nighttime, and an event data recorder (EDR) for recording data related to some specific traffic violations. The paper covers firstly the description of the hardware architecture and then presents the policies used for handling traffic violations. PMID:25421737

A system for traffic violation detection.

PubMed

Aliane, Nourdine; Fernandez, Javier; Mata, Mario; Bemposta, Sergio

2014-11-24

This paper describes the framework and components of an experimental platform for an advanced driver assistance system (ADAS) aimed at providing drivers with a feedback about traffic violations they have committed during their driving. The system is able to detect some specific traffic violations, record data associated to these faults in a local data-base, and also allow visualization of the spatial and temporal information of these traffic violations in a geographical map using the standard Google Earth tool. The test-bed is mainly composed of two parts: a computer vision subsystem for traffic sign detection and recognition which operates during both day and nighttime, and an event data recorder (EDR) for recording data related to some specific traffic violations. The paper covers firstly the description of the hardware architecture and then presents the policies used for handling traffic violations.

Leveraging High Resolution Topography for Education and Outreach: Updates to OpenTopography to make EarthScope and Other Lidar Datasets more Prominent in Geoscience Education

NASA Astrophysics Data System (ADS)

Kleber, E.; Crosby, C. J.; Arrowsmith, R.; Robinson, S.; Haddad, D. E.

2013-12-01

The use of Light Detection and Ranging (lidar) derived topography has become an indispensable tool in Earth science research. The collection of high-resolution lidar topography from an airborne or terrestrial platform allows landscapes and landforms to be represented at sub-meter resolution and in three dimensions. In addition to its high value for scientific research, lidar derived topography has tremendous potential as a tool for Earth science education. Recent science education initiatives and a community call for access to research-level data make the time ripe to expose lidar data and derived data products as a teaching tool. High resolution topographic data fosters several Disciplinary Core Ideas (DCIs) of the Next Generation Science Standards (NGS, 2013), presents respective Big Ideas of the new community-driven Earth Science Literacy Initiative (ESLI, 2009), teaches to a number National Science Education Standards (NSES, 1996), and Benchmarks for Science Literacy (AAAS, 1993) for science education for undergraduate physical and environmental earth science classes. The spatial context of lidar data complements concepts like visualization, place-based learning, inquiry based teaching and active learning essential to teaching in the geosciences. As official host to EarthScope lidar datasets for tectonically active areas in the western United States, the NSF-funded OpenTopography facility provides user-friendly access to a wealth of data that is easily incorporated into Earth science educational materials. OpenTopography (www.opentopography.org), in collaboration with EarthScope, has developed education and outreach activities to foster teacher, student and researcher utilization of lidar data. These educational resources use lidar data coupled with free tools such as Google Earth to provide a means for students and the interested public to visualize and explore Earth's surface in an interactive manner not possible with most other remotely sensed imagery. The education section of the OpenTopography portal has recently been strengthened with the addition of several new resources and the re-organization of existing content for easy discovery. New resources include a detailed frequently asked questions (FAQ) section, updated 'How-to' videos for downloading data from OpenTopography and additional webpages aimed at students, educators and researchers leveraging existing and updated resources from OpenTopography, EarthScope and other organizations. In addition, the OpenLandform catalog, an online collection of classic geologic landforms depicted in lidar, has been updated to include additional tectonic landforms from EarthScope lidar datasets.

The GPlates Portal: Cloud-based interactive 3D and 4D visualization of global geological and geophysical data and models in a browser

NASA Astrophysics Data System (ADS)

Müller, Dietmar; Qin, Xiaodong; Sandwell, David; Dutkiewicz, Adriana; Williams, Simon; Flament, Nicolas; Maus, Stefan; Seton, Maria

2017-04-01

The pace of scientific discovery is being transformed by the availability of 'big data' and open access, open source software tools. These innovations open up new avenues for how scientists communicate and share data and ideas with each other, and with the general public. Here, we describe our efforts to bring to life our studies of the Earth system, both at present day and through deep geological time. The GPlates Portal (portal.gplates.org) is a gateway to a series of virtual globes based on the Cesium Javascript library. The portal allows fast interactive visualization of global geophysical and geological data sets, draped over digital terrain models. The globes use WebGL for hardware-accelerated graphics and are cross-platform and cross-browser compatible with complete camera control. The globes include a visualization of a high-resolution global digital elevation model and the vertical gradient of the global gravity field, highlighting small-scale seafloor fabric such as abyssal hills, fracture zones and seamounts in unprecedented detail. The portal also features globes portraying seafloor geology and a global data set of marine magnetic anomaly identifications. The portal is specifically designed to visualize models of the Earth through geological time. These space-time globes include tectonic reconstructions of the Earth's gravity and magnetic fields, and several models of long-wavelength surface dynamic topography through time, including the interactive plotting of vertical motion histories at selected locations. The portal has been visited over half a million times since its inception in October 2015, as tracked by google analytics, and the globes have been featured in numerous media articles around the world. This demonstrates the high demand for fast visualization of global spatial big data, both for the present-day as well as through geological time. The globes put the on-the-fly visualization of massive data sets at the fingertips of end-users to stimulate teaching and learning and novel avenues of inquiry. This technology offers many future opportunities for providing additional functionality, especially on-the-fly big data analytics. Müller, R.D., Qin, X., Sandwell, D.T., Dutkiewicz, A., Williams, S.E., Flament, N., Maus, S. and Seton, M, 2016, The GPlates Portal: Cloud-based interactive 3D visualization of global geophysical and geological data in a web browser, PLoS ONE 11(3): e0150883. doi:10.1371/ journal.pone.0150883

NASA's Earth Science Gateway: A Platform for Interoperable Services in Support of the GEOSS Architecture

NASA Astrophysics Data System (ADS)

Alameh, N.; Bambacus, M.; Cole, M.

2006-12-01

Nasa's Earth Science as well as interdisciplinary research and applications activities require access to earth observations, analytical models and specialized tools and services, from diverse distributed sources. Interoperability and open standards for geospatial data access and processing greatly facilitate such access among the information and processing compo¬nents related to space¬craft, airborne, and in situ sensors; predictive models; and decision support tools. To support this mission, NASA's Geosciences Interoperability Office (GIO) has been developing the Earth Science Gateway (ESG; online at http://esg.gsfc.nasa.gov) by adapting and deploying a standards-based commercial product. Thanks to extensive use of open standards, ESG can tap into a wide array of online data services, serve a variety of audiences and purposes, and adapt to technology and business changes. Most importantly, the use of open standards allow ESG to function as a platform within a larger context of distributed geoscience processing, such as the Global Earth Observing System of Systems (GEOSS). ESG shares the goals of GEOSS to ensure that observations and products shared by users will be accessible, comparable, and understandable by relying on common standards and adaptation to user needs. By maximizing interoperability, modularity, extensibility and scalability, ESG's architecture fully supports the stated goals of GEOSS. As such, ESG's role extends beyond that of a gateway to NASA science data to become a shared platform that can be leveraged by GEOSS via: A modular and extensible architecture Consensus and community-based standards (e.g. ISO and OGC standards) A variety of clients and visualization techniques, including WorldWind and Google Earth A variety of services (including catalogs) with standard interfaces Data integration and interoperability Mechanisms for user involvement and collaboration Mechanisms for supporting interdisciplinary and domain-specific applications ESG has played a key role in recent GEOSS Service Network (GSN) demos and workshops, acting not only as a service and data catalog and discovery client, but also as a portrayal and visualization client to distributed data.

Mash-up of techniques between data crawling/transfer, data preservation/stewardship and data processing/visualization technologies on a science cloud system designed for Earth and space science: a report of successful operation and science projects of the NICT Science Cloud

NASA Astrophysics Data System (ADS)

Murata, K. T.

2014-12-01

Data-intensive or data-centric science is 4th paradigm after observational and/or experimental science (1st paradigm), theoretical science (2nd paradigm) and numerical science (3rd paradigm). Science cloud is an infrastructure for 4th science methodology. The NICT science cloud is designed for big data sciences of Earth, space and other sciences based on modern informatics and information technologies [1]. Data flow on the cloud is through the following three techniques; (1) data crawling and transfer, (2) data preservation and stewardship, and (3) data processing and visualization. Original tools and applications of these techniques have been designed and implemented. We mash up these tools and applications on the NICT Science Cloud to build up customized systems for each project. In this paper, we discuss science data processing through these three steps. For big data science, data file deployment on a distributed storage system should be well designed in order to save storage cost and transfer time. We developed a high-bandwidth virtual remote storage system (HbVRS) and data crawling tool, NICTY/DLA and Wide-area Observation Network Monitoring (WONM) system, respectively. Data files are saved on the cloud storage system according to both data preservation policy and data processing plan. The storage system is developed via distributed file system middle-ware (Gfarm: GRID datafarm). It is effective since disaster recovery (DR) and parallel data processing are carried out simultaneously without moving these big data from storage to storage. Data files are managed on our Web application, WSDBank (World Science Data Bank). The big-data on the cloud are processed via Pwrake, which is a workflow tool with high-bandwidth of I/O. There are several visualization tools on the cloud; VirtualAurora for magnetosphere and ionosphere, VDVGE for google Earth, STICKER for urban environment data and STARStouch for multi-disciplinary data. There are 30 projects running on the NICT Science Cloud for Earth and space science. In 2003 56 refereed papers were published. At the end, we introduce a couple of successful results of Earth and space sciences using these three techniques carried out on the NICT Sciences Cloud. [1] http://sc-web.nict.go.jp

Earthquakes in Action: Incorporating Multimedia, Internet Resources, Large-scale Seismic Data, and 3-D Visualizations into Innovative Activities and Research Projects for Today's High School Students

NASA Astrophysics Data System (ADS)

Smith-Konter, B.; Jacobs, A.; Lawrence, K.; Kilb, D.

2006-12-01

The most effective means of communicating science to today's "high-tech" students is through the use of visually attractive and animated lessons, hands-on activities, and interactive Internet-based exercises. To address these needs, we have developed Earthquakes in Action, a summer high school enrichment course offered through the California State Summer School for Mathematics and Science (COSMOS) Program at the University of California, San Diego. The summer course consists of classroom lectures, lab experiments, and a final research project designed to foster geophysical innovations, technological inquiries, and effective scientific communication (http://topex.ucsd.edu/cosmos/earthquakes). Course content includes lessons on plate tectonics, seismic wave behavior, seismometer construction, fault characteristics, California seismicity, global seismic hazards, earthquake stress triggering, tsunami generation, and geodetic measurements of the Earth's crust. Students are introduced to these topics through lectures-made-fun using a range of multimedia, including computer animations, videos, and interactive 3-D visualizations. These lessons are further enforced through both hands-on lab experiments and computer-based exercises. Lab experiments included building hand-held seismometers, simulating the frictional behavior of faults using bricks and sandpaper, simulating tsunami generation in a mini-wave pool, and using the Internet to collect global earthquake data on a daily basis and map earthquake locations using a large classroom map. Students also use Internet resources like Google Earth and UNAVCO/EarthScope's Jules Verne Voyager Jr. interactive mapping tool to study Earth Science on a global scale. All computer-based exercises and experiments developed for Earthquakes in Action have been distributed to teachers participating in the 2006 Earthquake Education Workshop, hosted by the Visualization Center at Scripps Institution of Oceanography (http://siovizcenter.ucsd.edu/workshop). In addition to daily lecture and lab exercises, COSMOS students also conduct a mini-research project of their choice that uses data ranging from the 2004 Parkfield Earthquake, to Southern California seismicity, to global seismicity. Students collect seismic data from the Internet and evaluate earthquake locations, magnitudes, temporal sequence of seismic activity, active fault planes, and plate tectonic boundaries using research quality techniques. Students are given the opportunity to build 3-D visualizations of their research data sets and archive these at the SIO Visualization Center's online library, which is globally accessible to students, teachers, researchers, and the general public (http://www.siovizcenter.ucsd.edu/library.php). These student- generated visualizations have become a practical resource for not only students and teachers, but also geophysical researchers that use the visual objects as research tools to better explore and understand their data. Through Earthquakes in Action, we offer both the tools for scientific exploration and the thrills of scientific discovery, providing students with valuable knowledge, novel research experience, and a unique sense of scientific contribution.

D Visualization of Mangrove and Aquaculture Conversion in Banate Bay, Iloilo

NASA Astrophysics Data System (ADS)

Domingo, G. A.; Mallillin, M. M.; Perez, A. M. C.; Claridades, A. R. C.; Tamondong, A. M.

2017-10-01

Studies have shown that mangrove forests in the Philippines have been drastically reduced due to conversion to fishponds, salt ponds, reclamation, as well as other forms of industrial development and as of 2011, Iloilo's 95 % mangrove forest was converted to fishponds. In this research, six (6) Landsat images acquired on the years 1973, 1976, 2000, 2006, 2010, and 2016, were classified using Support Vector Machine (SVM) Classification to determine land cover changes, particularly the area change of mangrove and aquaculture from 1976 to 2016. The results of the classification were used as layers for the generation of 3D visualization models using four (4) platforms namely Google Earth, ArcScene, Virtual Terrain Project, and Terragen. A perception survey was conducted among respondents with different levels of expertise in spatial analysis, 3D visualization, as well as in forestry, fisheries, and aquatic resources to assess the usability, effectiveness, and potential of the various platforms used. Change detection showed that largest negative change for mangrove areas happened from 1976 to 2000, with the mangrove area decreasing from 545.374 hectares to 286.935 hectares. Highest increase in fishpond area occurred from 1973 to 1976 rising from 2,930.67 hectares to 3,441.51 hectares. Results of the perception survey showed that ArcScene is preferred for spatial analysis while respondents favored Terragen for 3D visualization and for forestry, fishery and aquatic resources applications.

An Information Infrastructure for Coastal Models and Data

NASA Astrophysics Data System (ADS)

Hardin, D.; Keiser, K.; Conover, H.; Graves, S.

2007-12-01

Advances in semantics and visualization have given rise to new capabilities for the location, manipulation, integration, management and display of data and information in and across domains. An example of these capabilities is illustrated by a coastal restoration project that utilizes satellite, in-situ data and hydrodynamic model output to address seagrass habitat restoration in the Northern Gulf of Mexico. In this project a standard stressor conceptual model was implemented as an ontology in addition to the typical CMAP diagram. The ontology captures the elements of the seagrass conceptual model as well as the relationships between them. Noesis, developed by the University of Alabama in Huntsville, is an application that provides a simple but powerful way to search and organize data and information represented by ontologies. Noesis uses domain ontologies to help scope search queries to ensure that search results are both accurate and complete. Semantics are captured by refining the query terms to cover synonyms, specializations, generalizations and related concepts. As a resource aggregator Noesis categorizes search results returned from multiple, concurrent search engines such as Google, Yahoo, and Ask.com. Search results are further directed by accessing domain specific catalogs that include outputs from hydrodynamic and other models. Embedded within the search results are links that invoke applications such as web map displays, animation tools and virtual globe applications such as Google Earth. In the seagrass prioritization project Noesis is used to locate information that is vital to understanding the impact of stressors on the habitat. This presentation will show how the intelligent search capabilities of Noesis are coupled with visualization tools and model output to investigate the restoration of seagrass habitat.

Generating Southern Africa Precipitation Forecast Using the FEWS Engine, a New Application for the Google Earth Engine

NASA Astrophysics Data System (ADS)

Landsfeld, M. F.; Hegewisch, K.; Daudert, B.; Morton, C.; Husak, G. J.; Friedrichs, M.; Funk, C. C.; Huntington, J. L.; Abatzoglou, J. T.; Verdin, J. P.

2016-12-01

The Famine Early Warning Systems Network (FEWS NET) focuses on food insecurity in developing nations and provides objective, evidence-based analysis to help government decision-makers and relief agencies plan for and respond to humanitarian emergencies. The network of FEWS NET analysts and scientists require flexible, interactive tools to aid in their monitoring and research efforts. Because they often work in bandwidth-limited regions, lightweight Internet tools and services that bypass the need for downloading massive datasets are preferred for their work. To support food security analysis FEWS NET developed a custom interface for the Google Earth Engine (GEE). GEE is a platform developed by Google to support scientific analysis of environmental data in their cloud computing environment. This platform allows scientists and independent researchers to mine massive collections of environmental data, leveraging Google's vast computational resources for purposes of detecting changes and monitoring the Earth's surface and climate. GEE hosts an enormous amount of satellite imagery and climate archives, one of which is the Climate Hazards Group Infrared Precipitation with Stations dataset (CHIRPS). CHIRPS precipitation dataset is a key input for FEWS NET monitoring and forecasting efforts. In this talk we introduce the FEWS Engine interface. We present an application that highlights the utility of FEWS Engine for forecasting the upcoming seasonal precipitation of southern Africa. Specifically, the current state of ENSO is assessed and used to identify similar historical seasons. The FEWS Engine compositing tool is used to examine rainfall and other environmental data for these analog seasons. The application illustrates the unique benefits of using FEWS Engine for on-the-fly food security scenario development.

Using Google Earth to Study the Basic Characteristics of Volcanoes

ERIC Educational Resources Information Center

Schipper, Stacia; Mattox, Stephen

2010-01-01

Landforms, natural hazards, and the change in the Earth over time are common material in state and national standards. Volcanoes exemplify these standards and readily capture the interest and imagination of students. With a minimum of training, students can recognize erupted materials and types of volcanoes; in turn, students can relate these…

Active Fire Mapping Program

MedlinePlus

Active Fire Mapping Program Current Large Incidents (Home) New Large Incidents Fire Detection Maps MODIS Satellite Imagery VIIRS Satellite Imagery Fire Detection GIS Data Fire Data in Google Earth ...

NARSTO EPA SS LOS ANGELES SMPS DATA

Atmospheric Science Data Center

2018-04-09

... Ground Station Instrument:  SMPS - Scanning Mobility Particle Sizer Location:  Los Angeles, ... Get Google Earth Related Data:  Environmental Protection Agency Supersites Los Angeles, California ...

Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing.

PubMed

Midekisa, Alemayehu; Holl, Felix; Savory, David J; Andrade-Pacheco, Ricardo; Gething, Peter W; Bennett, Adam; Sturrock, Hugh J W

2017-01-01

Quantifying and monitoring the spatial and temporal dynamics of the global land cover is critical for better understanding many of the Earth's land surface processes. However, the lack of regularly updated, continental-scale, and high spatial resolution (30 m) land cover data limit our ability to better understand the spatial extent and the temporal dynamics of land surface changes. Despite the free availability of high spatial resolution Landsat satellite data, continental-scale land cover mapping using high resolution Landsat satellite data was not feasible until now due to the need for high-performance computing to store, process, and analyze this large volume of high resolution satellite data. In this study, we present an approach to quantify continental land cover and impervious surface changes over a long period of time (15 years) using high resolution Landsat satellite observations and Google Earth Engine cloud computing platform. The approach applied here to overcome the computational challenges of handling big earth observation data by using cloud computing can help scientists and practitioners who lack high-performance computational resources.

The Use of LANCE Imagery Products to Investigate Hazards and Disasters

NASA Astrophysics Data System (ADS)

Schmaltz, J. E.; Teague, M.; Conover, H.; Regner, K.; Masuoka, E.; Vollmer, B. E.; Durbin, P.; Murphy, K. J.; Boller, R. A.; Davies, D.; Ilavajhala, S.; Thompson, C. K.; Bingham, A.; Rao, S.

2011-12-01

The NASA/GSFC Land Atmospheres Near-real time Capability for EOS (LANCE) has endeavored to integrate a variety of products from the Terra, Aqua, and Aura missions to assist in meeting the needs of the applications user community. This community has a need for imagery products to support the investigation of a wide variety of phenomena including hazards and disasters. The Evjafjallajokull eruption, the tsunamis/flood in Japan, and the Gulf of Mexico oil spill are recent examples of applications benefiting from the timely and synoptic view afforded by LANCE data. Working with the instrument science teams and the applications community, LANCE has identified 14 applications categories and the LANCE products that will support their investigation. The categories are: Smoke Plumes, Ash Plumes, Dust Storms, Pollution, Severe Storms, Shipping hazards, Fishery hazards, Land Transportation, Fires, Floods, Drought, Vegetation, Agriculture, and Oil Spills. Forty products from AMSR-E, MODIS, AIRS, and OMI have been identified to support analyses and investigations of these phenomena. In each case multiple products from two or more instruments are available which gives a more complete picture of the evolving hazard or disaster. All Level 2 (L2) products are available within 2.5 hours of observation at the spacecraft and the daily L3 products are updated incrementally as new data become available. LANCE provides user access to imagery using two systems: a Web Mapping Service (WMS) and a Google Earth-based interface known as the State of the Earth (SOTE). The latter has resulted from a partnership between LANCE and the Physical Oceanography Distributed Active Archive Center (PO DAAC). When the user selects one of the 14 categories, the relevant products are established within the WMS (http://lance2.modaps.eosdis.nasa.gov/wms/). For each application, population density data are available for densities in excess of 100 people/sqkm with user-defined opacity. These data are provided by the EOSDIS Socio-Economic Data and Applications Center (SEDAC). Certain users may not want to be constrained by the pre-defined categories and related products and all 40 products may be added as potential overlays. The most recent 10 days of near-real time data are available through the WMS. The SOTE provides an interface to the products grouped in the same fashion as the WMS. The SOTE servers stream imagery and data in the OGC KML format and these feeds can be visualized through the Google Earth browser plug-in. SOTE provides visualization through a virtual globe environment by allowing users to interact with the globe via zooming, rotating, and tilting.

The implementation of a modernized Dynamic Digital Map on Gale Crater, Mars

NASA Astrophysics Data System (ADS)

McBeck, J.; Condit, C. D.

2012-12-01

Currently, geology instructors present information to students via PowerPoint, Word, Excel and other programs that are not designed to parse or present geologic data. More tech-savvy, and perhaps better-funded, instructors use Google Earth or ArcGIS to display geologic maps and other visual information. However, Google Earth lacks the ability to present large portions of text, and ArcGIS restricts such functionality to labels and annotations. The original Dynamic Digital Map, which we have renamed Dynamic Digital Map Classic (DDMC), allows instructors to represent both visual and large portions of textual information to students. This summer we generalized the underlying architecture of DDMC, redesigned the user interface, modernized the analytical functionality, renamed the older version and labeled this new creature Dynamic Digital Map Extended (DDME). With the new DDME instructors can showcase maps, images, articles and movies, and create digital field trips. They can set the scale, coordinate system and caption of maps and images, add symbol links to maps and images that can transport the user to any specified destination—either internally (to data contained within the DDME) or externally (to a website address). Instructors and students can also calculate non-linear distances and irregular areas of maps and images, and create digital field trips with any number of stops—complete with notes and driving directions. DDMEs are perhaps best described as a sort of computerized, self-authored, interactive textbook. To display the vast capabilities of DDME, we created a DDME of Gale Crater (DDME-GC), which is the landing site of the most sophisticated NASA Mars Rover—Curiosity. DDME-GC hosts six thematic maps: a detailed geologic map provided by Brad Thompson of the Boston University Center for Remote Sensing (Thompson, et al., 2010), and five maps maintained in ASU's JMARS system, including global mosaics from Mars Global Surveyor's Mars Orbiter Laser Altimeter (MOLA), Mars Odyssey's Thermal Emission Imaging System (THEMIS), and the Mars Digital Image Model. DDME-GC offers a diverse suite of images, with over 40 images captured in the High Resolution Imaging Science Experiment (HiRISE), as well as several global mosaics created from Viking Orbiter, Hubble Telescope, THEMIS, MOLA and HiRISE data. DDME-GC also provides more than 25 articles that span subjects from the possible origins of the mound located in Gale Crater to the goals of NASA's Mars Exploration Program. The movies hosted by DDME-GC describe the difficulties of selecting a landing site for Curiosity, landing Curiosity on Mars and several other dynamic topics. The most significant advantage of the modernized DDME is its easily augmented functionality. In the future, DDME will be able to communicate with databases, import Keyhole Markup Language (KML) files from Google Earth, and be available on iOS and Android operating system. (Imagine: a field trip without the burden of notebooks, pens or pencils, paper or clipboards, with this information maintained on a mobile device.) The most recent DDME is a mere skeleton of its full capabilities—a robust architecture upon which myriad functionality can be supplemented.

Relevant Links

Atmospheric Science Data Center

2018-06-15

... Theoretical Basis Document (ATBD) ADAM-M ADAM-M Information AirMISR AirMISR Home Page MISR Home Page Feature Article: Fiery Temperament KONVEX Information SAFARI Home Page AirMSPI Get Google Earth ...

Mars @ ASDC

NASA Astrophysics Data System (ADS)

Carraro, Francesco

"Mars @ ASDC" is a project born with the goal of using the new web technologies to assist researches involved in the study of Mars. This project employs Mars map and javascript APIs provided by Google to visualize data acquired by space missions on the planet. So far, visualization of tracks acquired by MARSIS and regions observed by VIRTIS-Rosetta has been implemented. The main reason for the creation of this kind of tool is the difficulty in handling hundreds or thousands of acquisitions, like the ones from MARSIS, and the consequent difficulty in finding observations related to a particular region. This led to the development of a tool which allows to search for acquisitions either by defining the region of interest through a set of geometrical parameters or by manually selecting the region on the map through a few mouse clicks The system allows the visualization of tracks (acquired by MARSIS) or regions (acquired by VIRTIS-Rosetta) which intersect the user defined region. MARSIS tracks can be visualized both in Mercator and polar projections while the regions observed by VIRTIS can presently be visualized only in Mercator projection. The Mercator projection is the standard map provided by Google. The polar projections are provided by NASA and have been developed to be used in combination with APIs provided by Google The whole project has been developed following the "open source" philosophy: the client-side code which handles the functioning of the web page is written in javascript; the server-side code which executes the searches for tracks or regions is written in PHP and the DB which undergoes the system is MySQL.

Feasibility of external rhythmic cueing with the Google Glass for improving gait in people with Parkinson's disease.

PubMed

Zhao, Yan; Nonnekes, Jorik; Storcken, Erik J M; Janssen, Sabine; van Wegen, Erwin E H; Bloem, Bastiaan R; Dorresteijn, Lucille D A; van Vugt, Jeroen P P; Heida, Tjitske; van Wezel, Richard J A

2016-06-01

New mobile technologies like smartglasses can deliver external cues that may improve gait in people with Parkinson's disease in their natural environment. However, the potential of these devices must first be assessed in controlled experiments. Therefore, we evaluated rhythmic visual and auditory cueing in a laboratory setting with a custom-made application for the Google Glass. Twelve participants (mean age = 66.8; mean disease duration = 13.6 years) were tested at end of dose. We compared several key gait parameters (walking speed, cadence, stride length, and stride length variability) and freezing of gait for three types of external cues (metronome, flashing light, and optic flow) and a control condition (no-cue). For all cueing conditions, the subjects completed several walking tasks of varying complexity. Seven inertial sensors attached to the feet, legs and pelvis captured motion data for gait analysis. Two experienced raters scored the presence and severity of freezing of gait using video recordings. User experience was evaluated through a semi-open interview. During cueing, a more stable gait pattern emerged, particularly on complicated walking courses; however, freezing of gait did not significantly decrease. The metronome was more effective than rhythmic visual cues and most preferred by the participants. Participants were overall positive about the usability of the Google Glass and willing to use it at home. Thus, smartglasses like the Google Glass could be used to provide personalized mobile cueing to support gait; however, in its current form, auditory cues seemed more effective than rhythmic visual cues.

Google Earth Engine derived areal extents to infer elevation variation of lakes and reservoirs

NASA Astrophysics Data System (ADS)

Nguy-Robertson, Anthony; May, Jack; Dartevelle, Sebastien; Griffin, Sean; Miller, Justin; Tetrault, Robert; Birkett, Charon; Lucero, Eileen; Russo, Tess; Zentner, Matthew

2017-04-01

Monitoring water supplies is important for identifying potential national security issues before they begin. As a means to estimate lake and reservoir storage for sites without reliable water stage data, this study defines correlations between water body levels from hypsometry curves based on in situ gauge station and altimeter data (i.e. TOPEX/Poseidon, Jason series) and sensor areal extents observed in historic multispectral (i.e. MODIS and Landsat TM/ETM+/OLI) imagery. Water levels measured using in situ observations and altimeters, when in situ data were unavailable, were used to estimate the relationship between water elevation and surface area for 18 sites globally. Altimeters were generally more accurate (RMSE: 0.40 - 0.49 m) for estimating in situ lake elevations from Iraq and Afghanistan than the modeled elevation data using multispectral sensor areal extents: Landsat (RMSE: 0.25 - 1.5 m) and MODIS (RMSE 0.53 - 3.0 m). Correlations between altimeter data and Landsat imagery processed with Google Earth Engine confirmed similar relationships exists for a broader range of lakes without reported in situ data across the globe (RMSE: 0.24 - 1.6 m). Thus, while altimetry is still preferred to an areal extent model, lake surface area derived with Google Earth Engine can be used as a reasonable proxy for lake storage, expanding the number of observable lakes beyond the current constellation of altimeters and in situ gauges.

Improved discrimination among similar agricultural plots using red-and-green-based pseudo-colour imaging

NASA Astrophysics Data System (ADS)

Doi, Ryoichi

2016-04-01

The effects of a pseudo-colour imaging method were investigated by discriminating among similar agricultural plots in remote sensing images acquired using the Airborne Visible/Infrared Imaging Spectrometer (Indiana, USA) and the Landsat 7 satellite (Fergana, Uzbekistan), and that provided by GoogleEarth (Toyama, Japan). From each dataset, red (R)-green (G)-R-G-blue yellow (RGrgbyB), and RGrgby-1B pseudo-colour images were prepared. From each, cyan, magenta, yellow, key black, L*, a*, and b* derivative grayscale images were generated. In the Airborne Visible/Infrared Imaging Spectrometer image, pixels were selected for corn no tillage (29 pixels), corn minimum tillage (27), and soybean (34) plots. Likewise, in the Landsat 7 image, pixels representing corn (73 pixels), cotton (110), and wheat (112) plots were selected, and in the GoogleEarth image, those representing soybean (118 pixels) and rice (151) were selected. When the 14 derivative grayscale images were used together with an RGB yellow grayscale image, the overall classification accuracy improved from 74 to 94% (Airborne Visible/Infrared Imaging Spectrometer), 64 to 83% (Landsat), or 77 to 90% (GoogleEarth). As an indicator of discriminatory power, the kappa significance improved 1018-fold (Airborne Visible/Infrared Imaging Spectrometer) or greater. The derivative grayscale images were found to increase the dimensionality and quantity of data. Herein, the details of the increases in dimensionality and quantity are further analysed and discussed.

Feature Positioning on Google Street View Panoramas

NASA Astrophysics Data System (ADS)

Tsai, V. J. D.; Chang, C.-T.

2012-07-01

Location-based services (LBS) on web-based maps and images have come into real-time since Google launched its Street View imaging services in 2007. This research employs Google Maps API and Web Service, GAE for JAVA, AJAX, Proj4js, CSS and HTML in developing an internet platform for accessing the orientation parameters of Google Street View (GSV) panoramas in order to determine the three dimensional position of interest features that appear on two overlapping panoramas by geometric intersection. A pair of GSV panoramas was examined using known points located on the Library Building of National Chung Hsing University (NCHU) with the root-mean-squared errors of ±0.522m, ±1.230m, and ±5.779m for intersection and ±0.142m, ±1.558m, and ±5.733m for resection in X, Y, and h (elevation), respectively. Potential error sources in GSV positioning were analyzed and illustrated that the errors in Google provided GSV positional parameters dominate the errors in geometric intersection. The developed system is suitable for data collection in establishing LBS applications integrated with Google Maps and Google Earth in traffic sign and infrastructure inventory by adding automatic extraction and matching techniques for points of interest (POI) from GSV panoramas.

Streets? Where We're Going, We Don't Need Streets

NASA Astrophysics Data System (ADS)

Bailey, J.

2017-12-01

In 2007 Google Street View started as a project to provide 360-degree imagery along streets, but in the decade since has evolved into a platform through which to explore everywhere from the slope of everest, to the middle of the Amazon rainforest to under the ocean. As camera technology has evolved it has also become a tool for ground truthing maps, and provided scientific observations, storytelling and education. The Google Street View "special collects" team has undertaken increasingly more challenging projects across 80+ countries and every continent. All of which culminated in possibly the most ambitious collection yet, the capture of Street View on board the International Space Station. Learn about the preparation and obstacles behind this and other special collects. Explore these datasets through both Google Earth and Google Expeditions VR, an educational tool to take students on virtual field trips using 360 degree imagery.

Accelerating North American rangeland conservation with earth observation data and user driven web applications.

NASA Astrophysics Data System (ADS)

Allred, B. W.; Naugle, D.; Donnelly, P.; Tack, J.; Jones, M. O.

2016-12-01

In 2010, the USDA Natural Resources Conservation Service (NRCS) launched the Sage Grouse Initiative (SGI) to voluntarily reduce threats facing sage-grouse and rangelands on private lands. Over the past five years, SGI has matured into a primary catalyst for rangeland and wildlife conservation across the North American west, focusing on the shared vision of wildlife conservation through sustainable working landscapes and providing win-win solutions for producers, sage grouse, and 350 other sagebrush obligate species. SGI and its partners have invested a total of $750 million into rangeland and wildlife conservation. Moving forward, SGI continues to focus on rangeland conservation. Partnering with Google Earth Engine, SGI has developed outcome monitoring and conservation planning tools at continental scales. The SGI science team is currently developing assessment and monitoring algorithms of key conservation indicators. The SGI web application utilizes Google Earth Engine for user defined analysis and planning, putting the appropriate information directly into the hands of managers and conservationists.

The use of Web-based GIS data technologies in the construction of geoscience instructional materials: examples from the MARGINS Data in the Classroom project

NASA Astrophysics Data System (ADS)

Ryan, J. G.; McIlrath, J. A.

2008-12-01

Web-accessible geospatial information system (GIS) technologies have advanced in concert with an expansion of data resources that can be accessed and used by researchers, educators and students. These resources facilitate the development of data-rich instructional resources and activities that can be used to transition seamlessly into undergraduate research projects. MARGINS Data in the Classroom (http://serc.carleton.edu/ margins/index.html) seeks to engage MARGINS researchers and educators in using the images, datasets, and visualizations produced by NSF-MARGINS Program-funded research and related efforts to create Web-deliverable instructional materials for use in undergraduate-level geoscience courses (MARGINS Mini-Lessons). MARGINS science data is managed by the Marine Geosciences Data System (MGDS), and these and all other MGDS-hosted data can be accessed, manipulated and visualized using GeoMapApp (www.geomapapp.org; Carbotte et al, 2004), a freely available geographic information system focused on the marine environment. Both "packaged" MGDS datasets (i.e., global earthquake foci, volcanoes, bathymetry) and "raw" data (seismic surveys, magnetics, gravity) are accessible via GeoMapApp, with WFS linkages to other resources (geodesy from UNAVCO; seismic profiles from IRIS; geochemical and drillsite data from EarthChem, IODP, and others), permitting the comprehensive characterization of many regions of the ocean basins. Geospatially controlled datasets can be imported into GeoMapApp visualizations, and these visualizations can be exported into Google Earth as .kmz image files. Many of the MARGINS Mini-Lessons thus far produced use (or have studentss use the varied capabilities of GeoMapApp (i.e., constructing topographic profiles, overlaying varied geophysical and bathymetric datasets, characterizing geochemical data). These materials are available for use and testing from the project webpage (http://serc.carleton.edu/margins/). Classroom testing and assessment of the Mini- Lessons begins this Fall.

Public-Private Partnership: Joint recommendations to improve downloads of large Earth observation data

NASA Astrophysics Data System (ADS)

Ramachandran, R.; Murphy, K. J.; Baynes, K.; Lynnes, C.

2016-12-01

With the volume of Earth observation data expanding rapidly, cloud computing is quickly changing the way Earth observation data is processed, analyzed, and visualized. The cloud infrastructure provides the flexibility to scale up to large volumes of data and handle high velocity data streams efficiently. Having freely available Earth observation data collocated on a cloud infrastructure creates opportunities for innovation and value-added data re-use in ways unforeseen by the original data provider. These innovations spur new industries and applications and spawn new scientific pathways that were previously limited due to data volume and computational infrastructure issues. NASA, in collaboration with Amazon, Google, and Microsoft, have jointly developed a set of recommendations to enable efficient transfer of Earth observation data from existing data systems to a cloud computing infrastructure. The purpose of these recommendations is to provide guidelines against which all data providers can evaluate existing data systems and be used to improve any issues uncovered to enable efficient search, access, and use of large volumes of data. Additionally, these guidelines ensure that all cloud providers utilize a common methodology for bulk-downloading data from data providers thus preventing the data providers from building custom capabilities to meet the needs of individual cloud providers. The intent is to share these recommendations with other Federal agencies and organizations that serve Earth observation to enable efficient search, access, and use of large volumes of data. Additionally, the adoption of these recommendations will benefit data users interested in moving large volumes of data from data systems to any other location. These data users include the cloud providers, cloud users such as scientists, and other users working in a high performance computing environment who need to move large volumes of data.

Windows Into the Real World From a Virtual Globe

NASA Astrophysics Data System (ADS)

Rich, J.; Urban-Rich, J.

2007-12-01

Virtual globes such as Google Earth can be great tools for learning about the geographical variation of the earth. The key to virtual globes is the use of satellite imagery to provide a highly accurate view of the earth's surface. However, because the images are not updated regularly, variations in climate and vegetation over time can not be easily seen. In order to enhance the view of the earth and observe these changes by region and over time we are working to add near real time "windows" into the real world from a virtual globe. For the past 4 years we have been installing web cameras in areas of the world that will provide long term monitoring of global changes. By archiving hourly images from arctic, temperate and tropical regions we are creating a visual data set that is already beginning to tell the story of climate variability. The cameras are currently installed in 10 elementary schools in 3 countries and show the student's view out each window. The Windows Around the World program (http://www.WindowsAroundTheWorld.org) uses the images from these cameras to help students gain a better understanding of earth process and variability in climate and vegetation between different regions and over time. Previously we have used standard web based technologies such as DHTML and AJAX to provide near real-time access to these images and also provide enhanced functionality such as dynamic time lapse movies that allow users to see changes over months, days or hours up to the current hour (http://www.windowsaroundtheworld.org/north_america.aspx). We have integrated the camera images from Windows Around the World into Google Earth. Through network links and models we are creating a way for students to "fly" to another school in the program and see what the current view is out the window. By using a model as a screen, the image can be viewed from the same direction as the students who are sitting in a classroom at the participating school. Once at the school, visiting students can move around the area in three dimensions and gain a better understanding of what they are seeing out the window. Currently time-lapse images can be viewed at a lower resolution for all schools on the globe or when flying into an individual school, higher resolution time-lapse images can be seen. The observation of shadows, precipitation, movement of the sun and changes in vegetation allows the viewer to gain a better understanding of how the earth works and how the environment changes between regions and over time. World.org

Comparing the demands of destination entry using Google Glass and the Samsung Galaxy S4 during simulated driving.

PubMed

Beckers, Niek; Schreiner, Sam; Bertrand, Pierre; Mehler, Bruce; Reimer, Bryan

2017-01-01

The relative impact of using a Google Glass based voice interface to enter a destination address compared to voice and touch-entry methods using a handheld Samsung Galaxy S4 smartphone was assessed in a driving simulator. Voice entry (Google Glass and Samsung) had lower subjective workload ratings, lower standard deviation of lateral lane position, shorter task durations, faster remote Detection Response Task (DRT) reaction times, lower DRT miss rates, and resulted in less time glancing off-road than the primary visual-manual interaction with the Samsung Touch interface. Comparing voice entry methods, using Google Glass took less time, while glance metrics and reaction time to DRT events responded to were similar. In contrast, DRT miss rate was higher for Google Glass, suggesting that drivers may be under increased distraction levels but for a shorter period of time; whether one or the other equates to an overall safer driving experience is an open question. Copyright © 2016 Elsevier Ltd. All rights reserved.

Steno Google doodle

NASA Astrophysics Data System (ADS)

Showstack, Randy

2012-01-01

Nicolas Steno, a seventeenth-century Danish Catholic bishop and scientist, is considered a founder of modern stratigraphy and geology for his work on linking modern shark teeth to objects found in rock formations, among many other studies and writings. Steno, whose non-Latinized name was Niels Stensen, gained newfound fame as the inspiration for a Google doodle published on 11 January to mark his 374th birthday. The doodle of the Google logo is a rainbow-colored block letter formation that suggests karst stratigraphic layers chock with fossils and shells. How did Steno end up being honored in this way? “The criteria for selecting a doodle subject are pretty simple: We like to celebrate anything that is geeky, quirky, and artistic,” Google's Jennifer Hom, who drew the doodle, told Eos. “Nicholas Steno happened to be a really geeky and innovative thinker whose work on stratigraphy is also visually interesting. Not only does he relate to our Google culture in that he was a groundbreaking (no pun intended) scientist, his work is also very artistically inspiring.”

Disaster medicine through Google Glass.

PubMed

Carenzo, Luca; Barra, Federico Lorenzo; Ingrassia, Pier Luigi; Colombo, Davide; Costa, Alessandro; Della Corte, Francesco

2015-06-01

Nontechnical skills can make a difference in the management of disasters and mass casualty incidents and any tool helping providers in action might improve their ability to respond to such events. Google Glass, released by Google as a new personal communication device, could play a role in this field. We recently tested Google Glass during a full-scale exercise to perform visually guided augmented-reality Simple Triage and Rapid Treatment triage using a custom-made application and to identify casualties and collect georeferenced notes, photos, and videos to be incorporated into the debriefing. Despite some limitations (battery life and privacy concerns), Glass is a promising technology both for telemedicine applications and augmented-reality disaster response support to increase operators' performance, helping them to make better choices on the field; to optimize timings; and finally represents an excellent option to take professional education to a higher level.

Google Earth as a Vehicle to Integrating Multiple Layers of Environmental Satellite Data for Weather and Science Applications

NASA Astrophysics Data System (ADS)

Turk, F. J.; Miller, S. D.

2007-12-01

One of the main challenges facing current and future environmental satellite systems (e.g, the future National Polar Orbiting Environmental Satellite System (NPOESS)) is reaching and entraining the diverse user community via communication of how these systems address their particular needs. A necessary element to meeting this challenge is effective data visualization: facilitating the display, animation and layering of multiple satellite imaging and sounding sensors (providing complementary information) in a user-friendly and intuitive fashion. In light of the fact that these data are rapidly making their way into the classroom owing to efficient and timely data archival systems and dissemination over the Internet, there is a golden opportunity to leverage existing technology to introduce environmental science to wide spectrum of users. Google Earth's simplified interface and underlying markup language enables access to detailed global geographic information, and contains features which are both desirable and advantageous for geo-referencing and combining a wide range of environmental satellite data types. Since these satellite data are available with a variety of horizontal spatial resolutions (tens of km down to hundreds of meters), the imagery can be sub-setted (tiled) at a very small size. This allows low-bandwidth users to efficiently view and animate a sequence of imagery while zoomed out from the surface, whereas high-bandwidth users can efficiently zoom into the finest image resolution when viewing fine-scale phenomena such as fires, volcanic activity, as well as the details of meteorological phenomena such as hurricanes, rainfall, lightning, winds, etc. Dynamically updated network links allow for near real-time updates such that these data can be integrated with other Earth-hosted applications and exploited not only in the teaching environment, but also for operational users in the government and private industry sectors. To conceptualize how environmental satellite data would be utilized within a geobrowser in a near real-time setting, we present a demonstration from the 2007 hurricane season, developed within the Google Earth framework. A menu of imagery based sequential satellite overpasses (GOES and other geostationary satellites, TRMM, CloudSat, Terra, Aqua, DMSP, NOAA, QuikScat) during the storm lifecycle, are presented to the Earth client in an structured folder format. The remapping of these satellite data follows the hurricane track, enabling the user to view, animate, zoom, overlay and combine visible, infrared and passive microwave imagery and combine with other data (surface reports, forecasts, surface winds, ground and spaceborne radars, etc.) at various stages of the hurricane lifecycle. Pop-up balloons provide training that explains the properties and capabilities of the satellite datasets and what components of the underlying weather are represented. Future satellite overpass tracks are provided so that the user can anticipate imagery updates several days in advance (e.g., as a hurricane approaches landfall). This combination of geo-navigable data provides a convenient framework for efficiently demonstrating meteorological, oceanographic and weather and climate concepts to students, planners, and the public at large.

The Use of Virtual Globes as a Spatial Teaching Tool with Suggestions for Metadata Standards

ERIC Educational Resources Information Center

Schultz, Richard B.; Kerski, Joseph J.; Patterson, Todd C.

2008-01-01

Virtual Globe software has become extremely popular both inside and outside of educational settings. This software allows users to explore the Earth in three dimensions while streaming satellite imagery, elevation, and other data from the Internet. Virtual Globes, such as Google Earth, NASA World Wind, and ESRI's ArcGIS Explorer can be effectively…

Spatio-temporal Change Patterns of Tropical Forests from 2000 to 2014 Using MOD09A1 Dataset

NASA Astrophysics Data System (ADS)

Qin, Y.; Xiao, X.; Dong, J.

2016-12-01

Large-scale deforestation and forest degradation in the tropical region have resulted in extensive carbon emissions and biodiversity loss. However, restricted by the availability of good-quality observations, large uncertainty exists in mapping the spatial distribution of forests and their spatio-temporal changes. In this study, we proposed a pixel- and phenology-based algorithm to identify and map annual tropical forests from 2000 to 2014, using the 8-day, 500-m MOD09A1 (v005) product, under the support of Google cloud computing (Google Earth Engine). A temporal filter was applied to reduce the random noises and to identify the spatio-temporal changes of forests. We then built up a confusion matrix and assessed the accuracy of the annual forest maps based on the ground reference interpreted from high spatial resolution images in Google Earth. The resultant forest maps showed the consistent forest/non-forest, forest loss, and forest gain in the pan-tropical zone during 2000 - 2014. The proposed algorithm showed the potential for tropical forest mapping and the resultant forest maps are important for the estimation of carbon emission and biodiversity loss.

Airborne single particle mass spectrometers (SPLAT II & miniSPLAT) and new software for data visualization and analysis in a geo-spatial context.

PubMed

Zelenyuk, Alla; Imre, Dan; Wilson, Jacqueline; Zhang, Zhiyuan; Wang, Jun; Mueller, Klaus

2015-02-01

Understanding the effect of aerosols on climate requires knowledge of the size and chemical composition of individual aerosol particles-two fundamental properties that determine an aerosol's optical properties and ability to serve as cloud condensation or ice nuclei. Here we present our aircraft-compatible single particle mass spectrometers, SPLAT II and its new, miniaturized version, miniSPLAT that measure in-situ and in real-time the size and chemical composition of individual aerosol particles with extremely high sensitivity, temporal resolution, and sizing precision on the order of a monolayer. Although miniSPLAT's size, weight, and power consumption are significantly smaller, its performance is on par with SPLAT II. Both instruments operate in dual data acquisition mode to measure, in addition to single particle size and composition, particle number concentrations, size distributions, density, and asphericity with high temporal resolution. We also present ND-Scope, our newly developed interactive visual analytics software package. ND-Scope is designed to explore and visualize the vast amount of complex, multidimensional data acquired by our single particle mass spectrometers, along with other aerosol and cloud characterization instruments on-board aircraft. We demonstrate that ND-Scope makes it possible to visualize the relationships between different observables and to view the data in a geo-spatial context, using the interactive and fully coupled Google Earth and Parallel Coordinates displays. Here we illustrate the utility of ND-Scope to visualize the spatial distribution of atmospheric particles of different compositions, and explore the relationship between individual particle compositions and their activity as cloud condensation nuclei.

Local Air Quality Conditions and Forecasts

MedlinePlus

... Monitor Location Archived Maps by Region Canada Air Quality Air Quality on Google Earth Links A-Z About AirNow AirNow International Air Quality Action Days / Alerts AirCompare Air Quality Index (AQI) ...

Web GIS in practice X: a Microsoft Kinect natural user interface for Google Earth navigation

PubMed Central

2011-01-01

This paper covers the use of depth sensors such as Microsoft Kinect and ASUS Xtion to provide a natural user interface (NUI) for controlling 3-D (three-dimensional) virtual globes such as Google Earth (including its Street View mode), Bing Maps 3D, and NASA World Wind. The paper introduces the Microsoft Kinect device, briefly describing how it works (the underlying technology by PrimeSense), as well as its market uptake and application potential beyond its original intended purpose as a home entertainment and video game controller. The different software drivers available for connecting the Kinect device to a PC (Personal Computer) are also covered, and their comparative pros and cons briefly discussed. We survey a number of approaches and application examples for controlling 3-D virtual globes using the Kinect sensor, then describe Kinoogle, a Kinect interface for natural interaction with Google Earth, developed by students at Texas A&M University. Readers interested in trying out the application on their own hardware can download a Zip archive (included with the manuscript as additional files 1, 2, &3) that contains a 'Kinnogle installation package for Windows PCs'. Finally, we discuss some usability aspects of Kinoogle and similar NUIs for controlling 3-D virtual globes (including possible future improvements), and propose a number of unique, practical 'use scenarios' where such NUIs could prove useful in navigating a 3-D virtual globe, compared to conventional mouse/3-D mouse and keyboard-based interfaces. PMID:21791054

What's New in the Ocean in Google Earth and Maps

NASA Astrophysics Data System (ADS)

Austin, J.; Sandwell, D. T.

2014-12-01

Jenifer Austin, Jamie Adams, Kurt Schwehr, Brian Sullivan, David Sandwell2, Walter Smith3, Vicki Ferrini4, and Barry Eakins5, 1 Google Inc., 1600 Amphitheatre Parkway, Mountain View, California, USA 2 University of California-San Diego, Scripps Institute of Oceanography, La Jolla, California ,USA3 NOAA Laboratory for Satellite Altimetry, College Park, Maryland, USA4 Lamont Doherty, Columbia University5 NOAAMore than two-thirds of Earth is covered by oceans. On the almost 6 year anniversary of launching an explorable ocean seafloor in Google Earth and Maps, we updated our global underwater terrain dataset in partnership with Lamont-Doherty at Columbia, the Scripps Institution of Oceanography, and NOAA. With this update to our ocean map, we'll reveal an additional 2% of the ocean in high resolution representing 2 years of work by Columbia, pulling in data from numerous institutions including the Campeche Escarpment in the Gulf of Mexico in partnership with Charlie Paul at MBARI and the Schmidt Ocean Institute. The Scripps Institution of Oceanography at UCSD has curated 30 years of data from more than 8,000 ship cruises and 135 different institutions to reveal 15 percent of the seafloor at 1 km resolution. In addition, explore new data from an automated pipeline built to make updates to our Ocean Map more scalable in partnership with NOAA's National Geophysical Data Center (link to http://www.ngdc.noaa.gov/mgg/bathymetry/) and the University of Colorado CIRES program (link to http://cires.colorado.edu/index.html).

Web GIS in practice X: a Microsoft Kinect natural user interface for Google Earth navigation.

PubMed

Boulos, Maged N Kamel; Blanchard, Bryan J; Walker, Cory; Montero, Julio; Tripathy, Aalap; Gutierrez-Osuna, Ricardo

2011-07-26

This paper covers the use of depth sensors such as Microsoft Kinect and ASUS Xtion to provide a natural user interface (NUI) for controlling 3-D (three-dimensional) virtual globes such as Google Earth (including its Street View mode), Bing Maps 3D, and NASA World Wind. The paper introduces the Microsoft Kinect device, briefly describing how it works (the underlying technology by PrimeSense), as well as its market uptake and application potential beyond its original intended purpose as a home entertainment and video game controller. The different software drivers available for connecting the Kinect device to a PC (Personal Computer) are also covered, and their comparative pros and cons briefly discussed. We survey a number of approaches and application examples for controlling 3-D virtual globes using the Kinect sensor, then describe Kinoogle, a Kinect interface for natural interaction with Google Earth, developed by students at Texas A&M University. Readers interested in trying out the application on their own hardware can download a Zip archive (included with the manuscript as additional files 1, 2, &3) that contains a 'Kinnogle installation package for Windows PCs'. Finally, we discuss some usability aspects of Kinoogle and similar NUIs for controlling 3-D virtual globes (including possible future improvements), and propose a number of unique, practical 'use scenarios' where such NUIs could prove useful in navigating a 3-D virtual globe, compared to conventional mouse/3-D mouse and keyboard-based interfaces.

Vulnerability of the Nigerian coast: An insight into sea level rise owing to climate change and anthropogenic activities

NASA Astrophysics Data System (ADS)

Danladi, Iliya Bauchi; Kore, Basiru Mohammed; Gül, Murat

2017-10-01

Coastal areas are important regions in the world as they host huge population, diverse ecosystems and natural resources. However, owing to their settings, elevations and proximities to the sea, climate change (global warming) and human activities are threatening issues. Herein, we report the coastline changes and possible future threats related to sea level rise owing to global warming and human activities in the coastal region of Nigeria. Google earth images, Digital Elevation Model (DEM) and geological maps were used. Using google earth images, coastal changes for the past 43 years, 3 years prior to and after the construction of breakwaters along Goshen Beach Estate (Lekki) were examined. Additionally, coastline changes along Lekki Phase I from 2013 to 2016 were evaluated. The DEM map was used to delineate 0-2 m, 2-5 m and 5-10 m asl which correspond to undifferentiated sands and gravels to clays on the geological map. The results of the google earth images revealed remarkable erosion along both Lekki and Lekki Phase I, with the destruction of a lagoon in Lekki Phase I. Based on the result of the DEM map and geology, elevations of 0-2 m, 2-5 m and 5-10 m asl were interpreted as highly risky, moderately risky and risky respectively. Considering factors threatening coastal regions, the erosion and destruction of the lagoon along the Nigerian coast may be ascribed to sea level rise as a result of global warming and intense human activities respectively.

PHYLOGEOrec: A QGIS plugin for spatial phylogeographic reconstruction from phylogenetic tree and geographical information data

NASA Astrophysics Data System (ADS)

Nashrulloh, Maulana Malik; Kurniawan, Nia; Rahardi, Brian

2017-11-01

The increasing availability of genetic sequence data associated with explicit geographic and environment (including biotic and abiotic components) information offers new opportunities to study the processes that shape biodiversity and its patterns. Developing phylogeography reconstruction, by integrating phylogenetic and biogeographic knowledge, provides richer and deeper visualization and information on diversification events than ever before. Geographical information systems such as QGIS provide an environment for spatial modeling, analysis, and dissemination by which phylogenetic models can be explicitly linked with their associated spatial data, and subsequently, they will be integrated with other related georeferenced datasets describing the biotic and abiotic environment. We are introducing PHYLOGEOrec, a QGIS plugin for building spatial phylogeographic reconstructions constructed from phylogenetic tree and geographical information data based on QGIS2threejs. By using PHYLOGEOrec, researchers can integrate existing phylogeny and geographical information data, resulting in three-dimensional geographic visualizations of phylogenetic trees in the Keyhole Markup Language (KML) format. Such formats can be overlaid on a map using QGIS and finally, spatially viewed in QGIS by means of a QGIS2threejs engine for further analysis. KML can also be viewed in reputable geobrowsers with KML-support (i.e., Google Earth).

Imaging 50,000 Oriented Ovoid Depressions Using LiDAR Elevation Data Elucidates the Enigmatic Character of The Carolina Bays: Wind & Wave, Or Cosmic Impact Detritus?

NASA Astrophysics Data System (ADS)

Davias, M. E.; Harris, T. H. S.

2017-12-01

80 years after aerial photography revealed thousands of aligned oval depressions on the USA's Atlantic Coastal Plain, the geomorphology of the "Carolina bays" remains enigmatic. Geologists and astronomers alike hold that invoking a cosmic impact for their genesis is indefensible. Rather, the bays are commonly attributed to gradualistic fluvial, marine and/or aeolian processes operating during the Pleistocene era. The major axis orientations of Carolina bays are noted for varying statistically by latitude, suggesting that, should there be any merit to a cosmic hypothesis, a highly accurate triangulation network and suborbital analysis would yield a locus and allow for identification of a putative impact site. Digital elevation maps using LiDAR technology offer the precision necessary to measure their exquisitely-carved circumferential rims and orientations reliably. To support a comprehensive geospatial survey of Carolina bay landforms (Survey) we generated about a million km2 of false-color hsv-shaded bare-earth topographic maps as KML-JPEG tile sets for visualization on virtual globes. Considering the evidence contained in the Survey, we maintain that interdisciplinary research into a possible cosmic origin should be encouraged. Consensus opinion does hold a cosmic impact accountable for an enigmatic Pleistocene event - the Australasian tektite strewn field - despite the failure of a 60-year search to locate the causal astroblem. Ironically, a cosmic link to the Carolina bays is considered soundly falsified by the identical lack of a causal impact structure. Our conjecture suggests both these events are coeval with a cosmic impact into the Great Lakes area during the Mid-Pleistocene Transition, at 786 ka ± 5 k. All Survey data and imagery produced for the Survey are available on the Internet to support independent research. A table of metrics for 50,000 bays examined for the Survey is available from an on-line Google Fusion Table: https://goo.gl/XTHKC4 . Each bay is also geospatially referenceable through a map containing clickable placemarks that provide information windows displaying that bay's measurements as well as further links which allows visualization of the associated LiDAR imagery and the bay's planform measurement overlay within the Google Earth virtual globe: https://goo.gl/EHR4Lf .

Strengthened IAEA Safeguards-Imagery Analysis: Geospatial Tools for Nonproliferation Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pabian, Frank V

2012-08-14

This slide presentation focuses on the growing role and importance of imagery analysis for IAEA safeguards applications and how commercial satellite imagery, together with the newly available geospatial tools, can be used to promote 'all-source synergy.' As additional sources of openly available information, satellite imagery in conjunction with the geospatial tools can be used to significantly augment and enhance existing information gathering techniques, procedures, and analyses in the remote detection and assessment of nonproliferation relevant activities, facilities, and programs. Foremost of the geospatial tools are the 'Digital Virtual Globes' (i.e., GoogleEarth, Virtual Earth, etc.) that are far better than previouslymore » used simple 2-D plan-view line drawings for visualization of known and suspected facilities of interest which can be critical to: (1) Site familiarization and true geospatial context awareness; (2) Pre-inspection planning; (3) Onsite orientation and navigation; (4) Post-inspection reporting; (5) Site monitoring over time for changes; (6) Verification of states site declarations and for input to State Evaluation reports; and (7) A common basis for discussions among all interested parties (Member States). Additionally, as an 'open-source', such virtual globes can also provide a new, essentially free, means to conduct broad area search for undeclared nuclear sites and activities - either alleged through open source leads; identified on internet BLOGS and WIKI Layers, with input from a 'free' cadre of global browsers and/or by knowledgeable local citizens (a.k.a.: 'crowdsourcing'), that can include ground photos and maps; or by other initiatives based on existing information and in-house country knowledge. They also provide a means to acquire ground photography taken by locals, hobbyists, and tourists of the surrounding locales that can be useful in identifying and discriminating between relevant and non-relevant facilities and their associated infrastructure. The digital globes also provide highly accurate terrain mapping for better geospatial context and allow detailed 3-D perspectives of all sites or areas of interest. 3-D modeling software (i.e., Google's SketchUp6 newly available in 2007) when used in conjunction with these digital globes can significantly enhance individual building characterization and visualization (including interiors), allowing for better assessments including walk-arounds or fly-arounds and perhaps better decision making on multiple levels (e.g., the best placement for International Atomic Energy Agency (IAEA) video monitoring cameras).« less

Mapping and Modeling Web Portal to Advance Global Monitoring and Climate Research

NASA Astrophysics Data System (ADS)

Chang, G.; Malhotra, S.; Bui, B.; Sadaqathulla, S.; Goodale, C. E.; Ramirez, P.; Kim, R. M.; Rodriguez, L.; Law, E.

2011-12-01

Today, the principal investigators of NASA Earth Science missions develop their own software to manipulate, visualize, and analyze the data collected from Earth, space, and airborne observation instruments. There is very little, if any, collaboration among these principal investigators due to the lack of collaborative tools, which would allow these scientists to share data and results. At NASA's Jet Propulsion Laboratory (JPL), under the Lunar Mapping and Modeling Project (LMMP), we have built a web portal that exposes a set of common services to users to allow search, visualization, subset, and download lunar science data. Users also have access to a set of tools that visualize, analyze and annotate the data. These services are developed according to industry standards for data access and manipulation, such REST and Open Geospatial Consortium (OGC) web services. As a result, users can access the datasets through custom written applications or off-the-shelf applications such as Google Earth. Even though it's currently used to store and process lunar data, this web portal infrastructure has been designed to support other solar system bodies such as asteroids and planets, including Earth. The infrastructure uses a combination of custom, commercial, and open-source software as well as off-the-shelf hardware and pay-by-use cloud computing services. The use of standardized web service interfaces facilitates platform and application-independent access to the services and data. For instance, we have software clients for the LMMP portal that provide a rich browsing and analysis experience from a variety of platforms including iOS and Android mobile platforms and large screen multi-touch displays with 3-D terrain viewing functions. The service-oriented architecture and design principles utilized in the implementation of the portal lends itself to be reusable and scalable and could naturally be extended to include a collaborative environment that enables scientists and principal investigators to share their research and analysis seamlessly. In addition, this extension will allow users to easily share their tools and data, and to enrich their mapping and analysis experiences. In this talk, we will describe the advanced data management and portal technologies used to power this collaborative environment. We will further illustrate how this environment can enable, enhance and advance global monitoring and climate research.

An Agro-Climatological Early Warning Tool Based on the Google Earth Engine to Support Regional Food Security Analysis

NASA Astrophysics Data System (ADS)

Landsfeld, M. F.; Daudert, B.; Friedrichs, M.; Morton, C.; Hegewisch, K.; Husak, G. J.; Funk, C. C.; Peterson, P.; Huntington, J. L.; Abatzoglou, J. T.; Verdin, J. P.; Williams, E. L.

2015-12-01

The Famine Early Warning Systems Network (FEWS NET) focuses on food insecurity in developing nations and provides objective, evidence based analysis to help government decision-makers and relief agencies plan for and respond to humanitarian emergencies. The Google Earth Engine (GEE) is a platform provided by Google Inc. to support scientific research and analysis of environmental data in their cloud environment. The intent is to allow scientists and independent researchers to mine massive collections of environmental data and leverage Google's vast computational resources to detect changes and monitor the Earth's surface and climate. GEE hosts an enormous amount of satellite imagery and climate archives, one of which is the Climate Hazards Group Infrared Precipitation with Stations dataset (CHIRPS). The CHIRPS dataset is land based, quasi-global (latitude 50N-50S), 0.05 degree resolution, and has a relatively long term period of record (1981-present). CHIRPS is on a continuous monthly feed into the GEE as new data fields are generated each month. This precipitation dataset is a key input for FEWS NET monitoring and forecasting efforts. FEWS NET intends to leverage the GEE in order to provide analysts and scientists with flexible, interactive tools to aid in their monitoring and research efforts. These scientists often work in bandwidth limited regions, so lightweight Internet tools and services that bypass the need for downloading massive datasets to analyze them, are preferred for their work. The GEE provides just this type of service. We present a tool designed specifically for FEWS NET scientists to be utilized interactively for investigating and monitoring for agro-climatological issues. We are able to utilize the enormous GEE computing power to generate on-the-fly statistics to calculate precipitation anomalies, z-scores, percentiles and band ratios, and allow the user to interactively select custom areas for statistical time series comparisons and predictions.

Fostering Inquiry and Scientific Investigation in Students by Using GPS Data to Explore Plate Tectonics and Volcanic Deformation

NASA Astrophysics Data System (ADS)

Olds, S. E.; Eriksson, S.

2007-12-01

The Education and Outreach program at UNAVCO has developed free instructional materials using authentic high-precision GPS data for secondary education and undergraduate students in Earth science courses. Using inquiry-based, data-rich activities, students investigate crustal deformation and plate motion using GPS data and learn how these measurements are important to scientific discovery and understanding natural hazards and the current state of prediction. Because this deformation is expressed on Earth's surface over familiar time scales and on easily visualized orders of magnitude, GPS data represent an effective method for illustrating the geomorphic effects of plate tectonics and, in essence, allow students to 'see' plates move and volcanoes deform. The activities foster student skills to critically assess different forms of data, to visualize abstract concepts, and to evaluate multiple lines of evidence to analyze scientific problems. The activities are scaffolded to begin with basic concepts about GPS data and analyzing simple plate motion and move towards data analyses for more complex motion and crustal deformation. As part of assessment, students can apply new knowledge to explore other geographic regions independently. Learning activities currently include exploring motion along the San Andreas Fault, monitoring volcano deformation and ground movement at the Yellowstone Caldera, and analyzing ground motion along the subduction zone in the Cascadia region. To support educators and their students in their investigations, UNAVCO has developed the Data for Educators portal; http://www.unavco.org/edu_outreach/data.html. This portal provides a Google-map displaying the locations of GPS stations, web links to numerical GPS data that illustrate specific Earth processes, and educational activities that incorporate this data. The GPS data is freely available in a format compatible with standard spreadsheet and graphing programs as well as visualization and analysis tools such as the Integrated Data Viewer (IDV). After becoming familiar with the data available through the Data for Educators portal, students are more prepared to use the full UNAVCO data archive to conduct their own independent investigations.

Data visualization in interactive maps and time series

NASA Astrophysics Data System (ADS)

Maigne, Vanessa; Evano, Pascal; Brockmann, Patrick; Peylin, Philippe; Ciais, Philippe

2014-05-01

State-of-the-art data visualization has nothing to do with plots and maps we used few years ago. Many opensource tools are now available to provide access to scientific data and implement accessible, interactive, and flexible web applications. Here we will present a web site opened November 2013 to create custom global and regional maps and time series from research models and datasets. For maps, we explore and get access to data sources from a THREDDS Data Server (TDS) with the OGC WMS protocol (using the ncWMS implementation) then create interactive maps with the OpenLayers javascript library and extra information layers from a GeoServer. Maps become dynamic, zoomable, synchroneaously connected to each other, and exportable to Google Earth. For time series, we extract data from a TDS with the Netcdf Subset Service (NCSS) then display interactive graphs with a custom library based on the Data Driven Documents javascript library (D3.js). This time series application provides dynamic functionalities such as interpolation, interactive zoom on different axes, display of point values, and export to different formats. These tools were implemented for the Global Carbon Atlas (http://www.globalcarbonatlas.org): a web portal to explore, visualize, and interpret global and regional carbon fluxes from various model simulations arising from both human activities and natural processes, a work led by the Global Carbon Project.

Tracing Forest Change through 40 Years on Two Continents with the BULC Algorithm and Google Earth Engine

NASA Astrophysics Data System (ADS)

Cardille, J. A.; Crowley, M.; Fortin, J. A.; Lee, J.; Perez, E.; Sleeter, B. M.; Thau, D.

2016-12-01

With the opening of the Landsat archive, researchers have a vast new data source teeming with imagery and potential. Beyond Landsat, data from other sensors is newly available as well: these include ALOS/PALSAR, Sentinel-1 and -2, MERIS, and many more. Google Earth Engine, developed to organize and provide analysis tools for these immense data sets, is an ideal platform for researchers trying to sift through huge image stacks. It offers nearly unlimited processing power and storage with a straightforward programming interface. Yet labeling land-cover change through time remains challenging given the current state of the art for interpreting remote sensing image sequences. Moreover, combining data from very different image platforms remains quite difficult. To address these challenges, we developed the BULC algorithm (Bayesian Updating of Land Cover), designed for the continuous updating of land-cover classifications through time in large data sets. The algorithm ingests data from any of the wide variety of earth-resources sensors; it maintains a running estimate of land-cover probabilities and the most probable class at all time points along a sequence of events. Here we compare BULC results from two study sites that witnessed considerable forest change in the last 40 years: the Pacific Northwest of the United States and the Mato Grosso region of Brazil. In Brazil, we incorporated rough classifications from more than 100 images of varying quality, mixing imagery from more than 10 different sensors. In the Pacific Northwest, we used BULC to identify forest changes due to logging and urbanization from 1973 to the present. Both regions had classification sequences that were better than many of the component days, effectively ignoring clouds and other unwanted noise while fusing the information contained on several platforms. As we leave remote sensing's data-poor era and enter a period with multiple looks at Earth's surface from multiple sensors over a short period of time, the BULC algorithm can help to sift through images of varying quality in Google Earth Engine to extract the most useful information for mapping the state and history of Earth's land cover.

Garver Google+ Hangout

NASA Image and Video Library

2013-05-31

NASA Deputy Administrator Lori Garver participates in a live "We The Geeks" Google+ Hangout hosted by the White House to talk about asteroids, Friday, May 31, 2013 at NASA Headquarters in Washington. An asteroid nearly three kilometers wide will pass by the Earth today at 3.6 million miles away. Garver is joined in the conversation by Bill Nye, Executive Director, Planetary Society; Ed Lu, former astronaut and CEO, B612 Foundation; Peter Diamandis, Co-Founder and Co-Chairman, Planetary Resources and Jose Luis Galache, Astronomer at the International Astronomical Unions's Minor Planet Center. Photo Credit: (NASA/Carla Cioffi)

3D Viewer Platform of Cloud Clustering Management System: Google Map 3D

NASA Astrophysics Data System (ADS)

Choi, Sung-Ja; Lee, Gang-Soo

The new management system of framework for cloud envrionemnt is needed by the platfrom of convergence according to computing environments of changes. A ISV and small business model is hard to adapt management system of platform which is offered from super business. This article suggest the clustering management system of cloud computing envirionments for ISV and a man of enterprise in small business model. It applies the 3D viewer adapt from map3D & earth of google. It is called 3DV_CCMS as expand the CCMS[1].

Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing

PubMed Central

Holl, Felix; Savory, David J.; Andrade-Pacheco, Ricardo; Gething, Peter W.; Bennett, Adam; Sturrock, Hugh J. W.

2017-01-01

Quantifying and monitoring the spatial and temporal dynamics of the global land cover is critical for better understanding many of the Earth’s land surface processes. However, the lack of regularly updated, continental-scale, and high spatial resolution (30 m) land cover data limit our ability to better understand the spatial extent and the temporal dynamics of land surface changes. Despite the free availability of high spatial resolution Landsat satellite data, continental-scale land cover mapping using high resolution Landsat satellite data was not feasible until now due to the need for high-performance computing to store, process, and analyze this large volume of high resolution satellite data. In this study, we present an approach to quantify continental land cover and impervious surface changes over a long period of time (15 years) using high resolution Landsat satellite observations and Google Earth Engine cloud computing platform. The approach applied here to overcome the computational challenges of handling big earth observation data by using cloud computing can help scientists and practitioners who lack high-performance computational resources. PMID:28953943

Exploratory Visual Analytics of a Dynamically Built Network of Nodes in a WebGL-Enabled Browser

DTIC Science & Technology

2014-01-01

dimensionality reduction, feature extraction, high-dimensional data, t-distributed stochastic neighbor embedding, neighbor retrieval visualizer, visual...WebGL-enabled rendering is supported natively by browsers such as the latest Mozilla Firefox , Google Chrome, and Microsoft Internet Explorer 11. At the...appropriate names. The resultant 26-node network is displayed in a Mozilla Firefox browser in figure 2 (also see appendix B). 3 Figure 1. The

A regional inventory of the landslide processes and the elements at risk on the Rift flanks west of Lake Kivu (DRC)

NASA Astrophysics Data System (ADS)

Maki Mateso, Jean-Claude; Monsieurs, Elise; Jacobs, Liesbet; Bagalwa Mateso, Luc; Fiama Bondo, Silvanos; Delvaux, Damien; Albino, Fabien; Kervyn, François; Dewitte, Olivier

2016-04-01

The Rift flanks west of Lake Kivu (DRC) are one of the Congolese regions most affected by fatal landslides. However, information on the distribution of these processes and their impact on society is still lacking. Here we present a first regional landslide inventory and the associated elements at risk. The inventory was conducted in an area of 5,700 km² in three administrative territories between the cities of Bukavu and Goma. The region is one of the most densely populated area of DRC with a density of up to 200 persons/km². The approach for the inventory relies on visual analysis of Google Earth imagery and a 5 m resolution DEM that we produced from TanDEM-X interferometry. Field validation was performed in target places accounting for 5% of the study area. More than 2,000 landslides were mapped and distinction was made between deep and shallow, and slide and flow processes. Average landslide area is 6 ha (max. = 430 ha). Geomorphological analysis of landslide distribution shows topographic, lithologic, climatic and seismic controls. For 600 randomly-selected landslides, elements at risk (house, road, cultivated land, river) were inventoried in the areas affected and potentially affected by the instabilities; 10% of the landslides are inhabited and 25% do not present any risk. Numerous landslides have caused direct and indirect damage in recent years. In some places, the impact of mining activities on slope stability can be important. Google Earth was the only way to locate the recent shallow failures triggered by known extreme rainfall events. This inventory is a first step towards the understanding of the landslide processes in the region. Further studies are needed to complete and validate the information, to better infer about the triggers, and to compute susceptibility and risk maps.

Google Scholar as replacement for systematic literature searches: good relative recall and precision are not enough.

PubMed

Boeker, Martin; Vach, Werner; Motschall, Edith

2013-10-26

Recent research indicates a high recall in Google Scholar searches for systematic reviews. These reports raised high expectations of Google Scholar as a unified and easy to use search interface. However, studies on the coverage of Google Scholar rarely used the search interface in a realistic approach but instead merely checked for the existence of gold standard references. In addition, the severe limitations of the Google Search interface must be taken into consideration when comparing with professional literature retrieval tools.The objectives of this work are to measure the relative recall and precision of searches with Google Scholar under conditions which are derived from structured search procedures conventional in scientific literature retrieval; and to provide an overview of current advantages and disadvantages of the Google Scholar search interface in scientific literature retrieval. General and MEDLINE-specific search strategies were retrieved from 14 Cochrane systematic reviews. Cochrane systematic review search strategies were translated to Google Scholar search expression as good as possible under consideration of the original search semantics. The references of the included studies from the Cochrane reviews were checked for their inclusion in the result sets of the Google Scholar searches. Relative recall and precision were calculated. We investigated Cochrane reviews with a number of included references between 11 and 70 with a total of 396 references. The Google Scholar searches resulted in sets between 4,320 and 67,800 and a total of 291,190 hits. The relative recall of the Google Scholar searches had a minimum of 76.2% and a maximum of 100% (7 searches). The precision of the Google Scholar searches had a minimum of 0.05% and a maximum of 0.92%. The overall relative recall for all searches was 92.9%, the overall precision was 0.13%. The reported relative recall must be interpreted with care. It is a quality indicator of Google Scholar confined to an experimental setting which is unavailable in systematic retrieval due to the severe limitations of the Google Scholar search interface. Currently, Google Scholar does not provide necessary elements for systematic scientific literature retrieval such as tools for incremental query optimization, export of a large number of references, a visual search builder or a history function. Google Scholar is not ready as a professional searching tool for tasks where structured retrieval methodology is necessary.

Use of Google Earth to strengthen public health capacity and facilitate management of vector-borne diseases in resource-poor environments.

PubMed

Lozano-Fuentes, Saul; Elizondo-Quiroga, Darwin; Farfan-Ale, Jose Arturo; Loroño-Pino, Maria Alba; Garcia-Rejon, Julian; Gomez-Carro, Salvador; Lira-Zumbardo, Victor; Najera-Vazquez, Rosario; Fernandez-Salas, Ildefonso; Calderon-Martinez, Joaquin; Dominguez-Galera, Marco; Mis-Avila, Pedro; Morris, Natashia; Coleman, Michael; Moore, Chester G; Beaty, Barry J; Eisen, Lars

2008-09-01

Novel, inexpensive solutions are needed for improved management of vector-borne and other diseases in resource-poor environments. Emerging free software providing access to satellite imagery and simple editing tools (e.g. Google Earth) complement existing geographic information system (GIS) software and provide new opportunities for: (i) strengthening overall public health capacity through development of information for city infrastructures; and (ii) display of public health data directly on an image of the physical environment. We used freely accessible satellite imagery and a set of feature-making tools included in the software (allowing for production of polygons, lines and points) to generate information for city infrastructure and to display disease data in a dengue decision support system (DDSS) framework. Two cities in Mexico (Chetumal and Merida) were used to demonstrate that a basic representation of city infrastructure useful as a spatial backbone in a DDSS can be rapidly developed at minimal cost. Data layers generated included labelled polygons representing city blocks, lines representing streets, and points showing the locations of schools and health clinics. City blocks were colour-coded to show presence of dengue cases. The data layers were successfully imported in a format known as shapefile into a GIS software. The combination of Google Earth and free GIS software (e.g. HealthMapper, developed by WHO, and SIGEpi, developed by PAHO) has tremendous potential to strengthen overall public health capacity and facilitate decision support system approaches to prevention and control of vector-borne diseases in resource-poor environments.

Crop classification and mapping based on Sentinel missions data in cloud environment

NASA Astrophysics Data System (ADS)

Lavreniuk, M. S.; Kussul, N.; Shelestov, A.; Vasiliev, V.

2017-12-01

Availability of high resolution satellite imagery (Sentinel-1/2/3, Landsat) over large territories opens new opportunities in agricultural monitoring. In particular, it becomes feasible to solve crop classification and crop mapping task at country and regional scale using time series of heterogenous satellite imagery. But in this case, we face with the problem of Big Data. Dealing with time series of high resolution (10 m) multispectral imagery we need to download huge volumes of data and then process them. The solution is to move "processing chain" closer to data itself to drastically shorten time for data transfer. One more advantage of such approach is the possibility to parallelize data processing workflow and efficiently implement machine learning algorithms. This could be done with cloud platform where Sentinel imagery are stored. In this study, we investigate usability and efficiency of two different cloud platforms Amazon and Google for crop classification and crop mapping problems. Two pilot areas were investigated - Ukraine and England. Google provides user friendly environment Google Earth Engine for Earth observation applications with a lot of data processing and machine learning tools already deployed. At the same time with Amazon one gets much more flexibility in implementation of his own workflow. Detailed analysis of pros and cons will be done in the presentation.

Assessment of the detectability of geo-hazards using Google Earth applied to the Three Parallel Rivers Area, Yunnan province of China

NASA Astrophysics Data System (ADS)

Voermans, Michiel; Mao, Zhun; Baartman, Jantiene EM; Stokes, Alexia

2017-04-01

Anthropogenic activities such as hydropower, mining and road construction in mountainous areas can induce and intensify mass wasting geo-hazards (e.g. landslides, gullies, rockslides). This represses local safety and socio-economic development, and endangers biodiversity at larger scale. Until today, data and knowledge to construct geo-hazard databases for further assessments are lacking. This applies in particular to countries with a recently emerged rapid economic growth, where there are no previous hazard documentations and where means to gain data from e.g. intensive fieldwork or VHR satellite imagery and DEM processing are lacking. Google Earth (GE, https://www.google.com/earth/) is a freely available and relatively simple virtual globe, map and geographical information program, which is potentially useful in detecting geo-hazards. This research aimed at (i) testing the capability of Google Earth to detect locations of geo-hazards and (ii) identifying factors affecting the diagnosing quality of the detection, including effects of geo-hazard dimensions, environs setting and professional background and effort of GE users. This was tested on nine geo-hazard sites following road segments in the Three Parallel Rivers Area in the Yunnan province of China, where geo-hazards are frequently occurring. Along each road site, the position and size of each geo-hazard was measured in situ. Next, independent diagnosers with varying professional experience (students, researchers, engineers etc.) were invited to detect geo-hazard occurrence along each of the eight sites via GE. Finally, the inventory and diagnostic data were compared to validate the objectives. Rates of detected geo-hazards from 30 diagnosers ranged from 10% to 48%. No strong correlations were found between the type and size of the geo-hazards and their detection rates. Also the years of expertise of the diagnosers proved not to make a difference, opposite to what may be expected. Meanwhile the amount of time spent by the diagnoser proved to be positively influencing the detectability. GE showed to be a useful tool in detecting mainly larger geo-hazards if diligently applied, and is therefore applicable to identify geo-hazard hotspots. The usability for further assessments such as sediment delivery estimations is questionable and further research should be carried out to give insight to its full potential.

Airborne Single Particle Mass Spectrometers (SPLAT II & miniSPLAT) and New Software for Data Visualization and Analysis in a Geo-Spatial Context

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zelenyuk, Alla; Imre, D.; Wilson, Jacqueline M.

2015-02-01

Understanding the effect of aerosols on climate requires knowledge of the size and chemical composition of individual aerosol particles - two fundamental properties that determine an aerosol’s optical properties and ability to serve as cloud condensation or ice nuclei. Here we present miniSPLAT, our new aircraft compatible single particle mass spectrometer, that measures in-situ and in real-time size and chemical composition of individual aerosol particles with extremely high sensitivity, temporal resolution, and sizing precision on the order of a monolayer. miniSPLAT operates in dual data acquisition mode to measure, in addition to single particle size and composition, particle number concentrations,more » size distributions, density, and asphericity with high temporal resolution. When compared to our previous instrument, SPLAT II, miniSPLAT has been significantly reduced in size, weight, and power consumption without loss in performance. We also present ND-Scope, our newly developed interactive visual analytics software package. ND-Scope is designed to explore and visualize the vast amount of complex, multidimensional data acquired by our single particle mass spectrometers, along with other aerosol and cloud characterization instruments on-board aircraft. We demonstrate that ND-Scope makes it possible to visualize the relationships between different observables and to view the data in a geo-spatial context, using the interactive and fully coupled Google Earth and Parallel Coordinates displays. Here we illustrate the utility of ND-Scope to visualize the spatial distribution of atmospheric particles of different compositions, and explore the relationship between individual particle composition and their activity as cloud condensation nuclei.« less

Using Google Maps to Access USGS Volcano Hazards Information

NASA Astrophysics Data System (ADS)

Venezky, D. Y.; Snedigar, S.; Guffanti, M.; Bailey, J. E.; Wall, B. G.

2006-12-01

The U.S. Geological Survey (USGS) Volcano Hazard Program (VHP) is revising the information architecture of our website to provide data within a geospatial context for emergency managers, educators, landowners in volcanic areas, researchers, and the general public. Using a map-based interface for displaying hazard information provides a synoptic view of volcanic activity along with the ability to quickly ascertain where hazards are in relation to major population and infrastructure centers. At the same time, the map interface provides a gateway for educators and the public to find information about volcanoes in their geographic context. A plethora of data visualization solutions are available that are flexible, customizable, and can be run on individual websites. We are currently using a Google map interface because it can be accessed immediately from a website (a downloadable viewer is not required), and it provides simple features for moving around and zooming within the large map area that encompasses U.S. volcanism. A text interface will also be available. The new VHP website will serve as a portal to information for each volcano the USGS monitors with icons for alert levels and aviation color codes. When a volcano is clicked, a window will provide additional information including links to maps, images, and real-time data, thereby connecting information from individual observatories, the Smithsonian Institution, and our partner universities. In addition to the VHP home page, many observatories and partners have detailed graphical interfaces to data and images that include the activity pages for the Alaska Volcano Observatory, the Smithsonian Google Earth files, and Yellowstone Volcano Observatory pictures and data. Users with varied requests such as raw data, scientific papers, images, or brief overviews expect to be able to quickly access information for their specialized needs. Over the next few years we will be gathering, cleansing, reorganizing, and posting data in multiple formats to meet these needs.

An augmented-reality edge enhancement application for Google Glass.

PubMed

Hwang, Alex D; Peli, Eli

2014-08-01

Google Glass provides a platform that can be easily extended to include a vision enhancement tool. We have implemented an augmented vision system on Glass, which overlays enhanced edge information over the wearer's real-world view, to provide contrast-improved central vision to the Glass wearers. The enhanced central vision can be naturally integrated with scanning. Google Glass' camera lens distortions were corrected by using an image warping. Because the camera and virtual display are horizontally separated by 16 mm, and the camera aiming and virtual display projection angle are off by 10°, the warped camera image had to go through a series of three-dimensional transformations to minimize parallax errors before the final projection to the Glass' see-through virtual display. All image processes were implemented to achieve near real-time performance. The impacts of the contrast enhancements were measured for three normal-vision subjects, with and without a diffuser film to simulate vision loss. For all three subjects, significantly improved contrast sensitivity was achieved when the subjects used the edge enhancements with a diffuser film. The performance boost is limited by the Glass camera's performance. The authors assume that this accounts for why performance improvements were observed only with the diffuser filter condition (simulating low vision). Improvements were measured with simulated visual impairments. With the benefit of see-through augmented reality edge enhancement, natural visual scanning process is possible and suggests that the device may provide better visual function in a cosmetically and ergonomically attractive format for patients with macular degeneration.

Making Your Tools Useful to a Broader Audience

NASA Astrophysics Data System (ADS)

Lyness, M. D.; Broten, M. J.

2006-12-01

With the increasing growth of Web Services and SOAP the ability to connect and reuse computational and also visualization tools from all over the world via Web Interfaces that can be easily displayed in any current browser has provided the means to construct an ideal online research environment. The age-old question of usability is a major determining factor whether a particular tool would find great success in its community. An interface that can be understood purely by a user's intuition is desirable and more closely obtainable than ever before. Through the use of increasingly sophisticated web-oriented technologies including JavaScript, AJAX, and the DOM, web interfaces are able to harness the advantages of the Internet along with the functional capabilities of native applications such as menus, partial page changes, background processing, and visual effects to name a few. Also, with computers becoming a normal part of the educational process companies, such as Google and Microsoft, give us a synthetic intuition as a foundation for new designs. Understanding the way earth science researchers know how to use computers will allow the VLab portal (http://vlab.msi.umn.edu) and other projects to create interfaces that will get used. To provide detailed communication with the users of VLab's computational tools, projects like the Porky Portlet (http://www.gorerle.com/vlab-wiki/index.php?title=Porky_Portlet) spawned to empower users with a fully- detailed, interactive visual representation of progressing workflows. With the well-thought design of such tools and interfaces, researchers around the world will become accustomed to new highly engaging, visual web- based research environments.

GeoMapApp, Virtual Ocean, and other Free Data Resources for the 21st Century Classroom

NASA Astrophysics Data System (ADS)

Goodwillie, A. M.; Ryan, W.; Carbotte, S.; Melkonian, A.; Coplan, J.; Arko, R.; Ferrini, V.; O'Hara, S.; Leung, A.; Bonckzowski, J.

2008-12-01

With funding from the U.S. National Science Foundation, the Marine Geoscience Data System (MGDS) (http://www.marine-geo.org/) is developing GeoMapApp (http://www.geomapapp.org) - a computer application that provides wide-ranging map-based visualization and manipulation options for interdisciplinary geosciences research and education. The novelty comes from the use of this visual tool to discover and explore data, with seamless links to further discovery using traditional text-based approaches. Users can generate custom maps and grids and import their own data sets. Built-in functionality allows users to readily explore a broad suite of interactive data sets and interfaces. Examples include multi-resolution global digital models of topography, gravity, sediment thickness, and crustal ages; rock, fluid, biology and sediment sample information; research cruise underway geophysical and multibeam data; earthquake events; submersible dive photos of hydrothermal vents; geochemical analyses; DSDP/ODP core logs; seismic reflection profiles; contouring, shading, profiling of grids; and many more. On-line audio-visual tutorials lead users step-by-step through GeoMapApp functionality (http://www.geomapapp.org/tutorials/). Virtual Ocean (http://www.virtualocean.org/) integrates GeoMapApp with a 3-D earth browser based upon NASA WorldWind, providing yet more powerful capabilities. The searchable MGDS Media Bank (http://media.marine-geo.org/) supports viewing of remarkable images and video from the NSF Ridge 2000 and MARGINS programs. For users familiar with Google Earth (tm), KML files are available for viewing several MGDS data sets (http://www.marine-geo.org/education/kmls.php). Examples of accessing and manipulating a range of geoscience data sets from various NSF-funded programs will be shown. GeoMapApp, Virtual Ocean, the MGDS Media Bank and KML files are free MGDS data resources and work on any type of computer. They are currently used by educators, researchers, school teachers and the general public.

VIP Data Explorer: A Tool for Exploring 30 years of Vegetation Index and Phenology Observations

NASA Astrophysics Data System (ADS)

Barreto-munoz, A.; Didan, K.; Rivera-Camacho, J.; Yitayew, M.; Miura, T.; Tsend-Ayush, J.

2011-12-01

Continuous acquisition of global satellite imagery over the years has contributed to the creation of long term data records from AVHRR, MODIS, TM, SPOT-VGT and other sensors. These records account for 30+ years, as these archives grow, they become invaluable tools for environmental, resources management, and climate studies dealing with trends and changes from local, regional to global scale. In this project, the Vegetation Index and Phenology Lab (VIPLab) is processing 30 years of daily global surface reflectance data into an Earth Science Data Record of Vegetation Index and Phenology metrics. Data from AVHRR (N07,N09,N11 and N14) and MODIS (AQUA and TERRA collection 5) for the periods 1981-1999 and 2000-2010, at CMG resolution were processed into one seamless and sensor independent data record using various filtering, continuity and gap filling techniques (Tsend-Ayush et al., AGU 2011, Rivera-Camacho et al, AGU 2011). An interactive online tool (VIP Data Explorer) was developed to support the visualization, qualitative and quantitative exploration, distribution, and documentation of these records using a simple web 2.0 interface. The VIP Data explorer (http://vip.arizona.edu/viplab_data_explorer) can display any combination of multi temporal and multi source data, enable the quickly exploration and cross comparison of the various levels of processing of this data. It uses the Google Earth (GE) model and was developed using the GE API for images rendering, manipulation and geolocation. These ESDRs records can be quickly animated in this environment and explored for visual trends and anomalies detection. Additionally the tool enables extracting and visualizing any land pixel time series while showing the different levels of processing it went through. User can explore this ESDR database within this data explorer GUI environment, and any desired data can be placed into a dynamic "cart" to be ordered and downloaded later. More functionalities are planned and will be added to this data explorer tool as the project progresses.

Teaching Young Adults with Intellectual and Developmental Disabilities Community-Based Navigation Skills to Take Public Transportation.

PubMed

Price, Richard; Marsh, Abbie J; Fisher, Marisa H

2018-03-01

Facilitating the use of public transportation enhances opportunities for independent living and competitive, community-based employment for individuals with intellectual and developmental disabilities (IDD). Four young adults with IDD were taught through total-task chaining to use the Google Maps application, a self-prompting, visual navigation system, to take the bus to locations around a college campus and the community. Three of four participants learned to use Google Maps to independently navigate public transportation. Google Maps may be helpful in supporting independent travel, highlighting the importance of future research in teaching navigation skills. Learning to independently use public transportation increases access to autonomous activities, such as opportunities to work and to attend postsecondary education programs on large college campuses.Individuals with IDD can be taught through chaining procedures to use the Google Maps application to navigate public transportation.Mobile map applications are an effective and functional modern tool that can be used to teach community navigation.

The impact of geo-tagging on the photo industry and creating revenue streams

NASA Astrophysics Data System (ADS)

Richter, Rolf; Böge, Henning; Weckmann, Christoph; Schloen, Malte

2010-02-01

Internet geo and mapping services like Google Maps, Google Earth and Microsoft Bing Maps have reinvented the use of geographical information and have reached an enormous popularity. Besides that, location technologies like GPS have become affordable and are now being integrated in many camera phones. GPS is also available for standalone cameras as add on products or integrated in cameras. These developments are the enabler for new products for the photo industry or they enhance existing products. New commercial opportunities have been identified in the areas of photo hardware, internet/software and photo finishing.

Data are from Mars, Tools are from Venus

NASA Technical Reports Server (NTRS)

Lee, H. Joe

2017-01-01

Although during the data production phase, the data producers will usually ensure the products to be easily used by the specific power users the products serve. However, most data products are also posted for general public to use. It is not straightforward for data producers to anticipate what tools that these general end-data users are likely to use. In this talk, we will try to help fill in the gap by going over various tools related to Earth Science and how they work with the existing NASA HDF (Hierarchical Data Format) data products and the reasons why some products cannot be visualized or analyzed by existing tools. One goal is for to give insights for data producers on how to make their data product more interoperable. On the other hand, we also provide some hints for end users on how to make tools work with existing HDF data products. (tool category list: check the comments) HDF-EOS tools: HDFView HDF-EOS Plugin, HEG, h4tonccf, hdf-eos2 dumper, NCL, MATLAB, IDL, etc.net; CDF-Java tools: Panoply, IDV, toosUI, NcML, etc.net; CDF-C tools: ArcGIS Desktop, GrADS, NCL, NCO, etc.; GDAL tools: ArcGIS Desktop, QGIS, Google Earth, etc.; CSV tools: ArcGIS Online, MS Excel, Tableau, etc.

Relevancy 101

NASA Technical Reports Server (NTRS)

Lynnes, Chris; Newman, Doug

2016-01-01

Where we present an overview on why relevancy is a problem, how important it is and how we can improve it. The topic of relevancy is becoming increasingly important in earth data discovery as our audience is tuned to the accuracy of standard search engines like Google.

A New More Accurate Calibration for TIMED/GUVI

NASA Astrophysics Data System (ADS)

Schaefer, R. K.; Aiello, J.; Wolven, B. C.; Paxton, L. J.; Romeo, G.; Zhang, Y.

2017-12-01

The Global UltraViolet Imager (GUVI - http://guvi.jhuapl.edu) on NASA's TIMED spacecraft has the longest continuous set of observations of the Earth's ionosphere and thermosphere, spanning more than one solar cycle (2001-2017). As such, it represents an important dataset for understanding the dynamics of the Ionosphere-Thermosphere system. The entire dataset has been reprocessed and released as a new version (13) of GUVI data products. This is a complete re-examination of the calibration elements, including better calibrated radiances, better geolocation, and better background subtraction. Details can be found on the GUVI website: http://guvitimed.jhuapl.edu/guvi-Calib_Prod The radiances (except for the LBH long band) in version 13 are within 10% of the original archival radiances and so most of the derived products are little changed from their original versions. The LBH long band was redefined in on-board instrument color tables on Nov., 2, 2004 to better limit contamination from Nitric Oxide emission but this was not updated in ground processing until now. Version 13 LBH Long has 19% smaller radiances than the old calibrated products for post 11/2/2004 data. GUVI auroral products are the only ones that use LBHL - (LBH long)/(LBH short) is used to gauge the amount of intervening oxygen absorption. We will show several examples of the difference between new and old auroral products. Overall version 13 represents a big improvement in the calibration, geolocation, and background of the GUVI UV data products, allowing for the cleanest UV data for analysis of the ionosphere-thermosphere-aurora. An updated "Using GUVI Data Tutorial" will be available from the GUVI webpage to help you navigate to the data you need. Data products are displayed as daily summary and Google Earth files that can be browsed through the Cesium tool on the GUVI website or the image files can be downloaded and viewed through the Google Earth app. The image below shows gridded 135.6 nm radiances from March 27, 2003 displayed in Google Earth.

Tracing Forest Change through 40 Years on Two Continents with the BULC Algorithm and Google Earth Engine

NASA Astrophysics Data System (ADS)

Cardille, J. A.

2015-12-01

With the opening of the Landsat archive, researchers have a vast new data source teeming with imagery and potential. Beyond Landsat, data from other sensors is newly available as well: these include ALOS/PALSAR, Sentinel-1 and -2, MERIS, and many more. Google Earth Engine, developed to organize and provide analysis tools for these immense data sets, is an ideal platform for researchers trying to sift through huge image stacks. It offers nearly unlimited processing power and storage with a straightforward programming interface. Yet labeling forest change through time remains challenging given the current state of the art for interpreting remote sensing image sequences. Moreover, combining data from very different image platforms remains quite difficult. To address these challenges, we developed the BULC algorithm (Bayesian Updating of Land Cover), designed for the continuous updating of land-cover classifications through time in large data sets. The algorithm ingests data from any of the wide variety of earth-resources sensors; it maintains a running estimate of land-cover probabilities and the most probable class at all time points along a sequence of events. Here we compare BULC results from two study sites that witnessed considerable forest change in the last 40 years: the Pacific Northwest of the United States and the Mato Grosso region of Brazil. In Brazil, we incorporated rough classifications from more than 100 images of varying quality, mixing imagery from more than 10 different sensors. In the Pacific Northwest, we used BULC to identify forest changes due to logging and urbanization from 1973 to the present. Both regions had classification sequences that were better than many of the component days, effectively ignoring clouds and other unwanted signal while fusing the information contained on several platforms. As we leave remote sensing's data-poor era and enter a period with multiple looks at Earth's surface from multiple sensors over a short period of time, this algorithm may help to sift through images of varying quality in Google Earth Engine to extract the most useful information for mapping.

Large Scale Crop Mapping in Ukraine Using Google Earth Engine

NASA Astrophysics Data System (ADS)

Shelestov, A.; Lavreniuk, M. S.; Kussul, N.

2016-12-01

There are no globally available high resolution satellite-derived crop specific maps at present. Only coarse-resolution imagery (> 250 m spatial resolution) has been utilized to derive global cropland extent. In 2016 we are going to carry out a country level demonstration of Sentinel-2 use for crop classification in Ukraine within the ESA Sen2-Agri project. But optical imagery can be contaminated by cloud cover that makes it difficult to acquire imagery in an optimal time range to discriminate certain crops. Due to the Copernicus program since 2015, a lot of Sentinel-1 SAR data at high spatial resolution is available for free for Ukraine. It allows us to use the time series of SAR data for crop classification. Our experiment for one administrative region in 2015 showed much higher crop classification accuracy with SAR data than with optical only time series [1, 2]. Therefore, in 2016 within the Google Earth Engine Research Award we use SAR data together with optical ones for large area crop mapping (entire territory of Ukraine) using cloud computing capabilities available at Google Earth Engine (GEE). This study compares different classification methods for crop mapping for the whole territory of Ukraine using data and algorithms from GEE. Classification performance assessed using overall classification accuracy, Kappa coefficients, and user's and producer's accuracies. Also, crop areas from derived classification maps compared to the official statistics [3]. S. Skakun et al., "Efficiency assessment of multitemporal C-band Radarsat-2 intensity and Landsat-8 surface reflectance satellite imagery for crop classification in Ukraine," IEEE Journal of Selected Topics in Applied Earth Observ. and Rem. Sens., 2015, DOI: 10.1109/JSTARS.2015.2454297. N. Kussul, S. Skakun, A. Shelestov, O. Kussul, "The use of satellite SAR imagery to crop classification in Ukraine within JECAM project," IEEE International Geoscience and Remote Sensing Symposium (IGARSS), pp.1497-1500, 13-18 July 2014, Quebec City, Canada. F.J. Gallego, N. Kussul, S. Skakun, O. Kravchenko, A. Shelestov, O. Kussul, "Efficiency assessment of using satellite data for crop area estimation in Ukraine," International Journal of Applied Earth Observation and Geoinformation vol. 29, pp. 22-30, 2014.

Data to Pictures to Data: Outreach Imaging Software and Metadata

NASA Astrophysics Data System (ADS)

Levay, Z.

2011-07-01

A convergence between astronomy science and digital photography has enabled a steady stream of visually rich imagery from state-of-the-art data. The accessibility of hardware and software has facilitated an explosion of astronomical images for outreach, from space-based observatories, ground-based professional facilities and among the vibrant amateur astrophotography community. Producing imagery from science data involves a combination of custom software to understand FITS data (FITS Liberator), off-the-shelf, industry-standard software to composite multi-wavelength data and edit digital photographs (Adobe Photoshop), and application of photo/image-processing techniques. Some additional effort is needed to close the loop and enable this imagery to be conveniently available for various purposes beyond web and print publication. The metadata paradigms in digital photography are now complying with FITS and science software to carry information such as keyword tags and world coordinates, enabling these images to be usable in more sophisticated, imaginative ways exemplified by Sky in Google Earth and World Wide Telescope.

Juicebox.js Provides a Cloud-Based Visualization System for Hi-C Data.

PubMed

Robinson, James T; Turner, Douglass; Durand, Neva C; Thorvaldsdóttir, Helga; Mesirov, Jill P; Aiden, Erez Lieberman

2018-02-28

Contact mapping experiments such as Hi-C explore how genomes fold in 3D. Here, we introduce Juicebox.js, a cloud-based web application for exploring the resulting datasets. Like the original Juicebox application, Juicebox.js allows users to zoom in and out of such datasets using an interface similar to Google Earth. Juicebox.js also has many features designed to facilitate data reproducibility and sharing. Furthermore, Juicebox.js encodes the exact state of the browser in a shareable URL. Creating a public browser for a new Hi-C dataset does not require coding and can be accomplished in under a minute. The web app also makes it possible to create interactive figures online that can complement or replace ordinary journal figures. When combined with Juicer, this makes the entire process of data analysis transparent, insofar as every step from raw reads to published figure is publicly available as open source code. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Environmental Remote Sensing Analysis Using Open Source Virtual Earths and Public Domain Imagery

NASA Astrophysics Data System (ADS)

Pilant, A. N.; Worthy, L. D.

2008-12-01

Human activities increasingly impact natural environments. Globally, many ecosystems are stressed to unhealthy limits, leading to loss of valuable ecosystem services- economic, ecologic and intrinsic. Virtual earths (virtual globes) (e.g., NASA World Wind, ossimPlanet, ArcGIS Explorer, Google Earth, Microsoft Virtual Earth) are geospatial data integration tools that can aid our efforts to understand and protect the environment. Virtual earths provide unprecedented desktop views of our planet, not only to professional scientists, but also to citizen scientists, students, environmental stewards, decision makers, urban developers and planners. Anyone with a broadband internet connection can explore the planet virtually, due in large part to freely available open source software and public domain imagery. This has at least two important potential benefits. One, individuals can study the planet from the visually intuitive perspective of the synoptic aerial view, promoting environmental awareness and stewardship. Two, it opens up the possibility of harnessing the in situ knowledge and observations of citizen scientists familiar with landscape conditions in their locales. Could this collective knowledge be harnessed (crowd sourcing) to validate and quality assure land cover and other maps? In this presentation we present examples using public domain imagery and two open source virtual earths to highlight some of the functionalities currently available. OssimPlanet is used to view aerial data from the USDA Geospatial Data Gateway. NASA World Wind is used to extract georeferenced high resolution USGS urban area orthoimagery. ArcGIS Explorer is used to demonstrate an example of image analysis using web processing services. The research presented here was conducted under the Environmental Feature Finder project of the Environmental Protection Agency's Advanced Monitoring Initiative. Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect official Agency policy. Use of trade names does not imply endorsement by the authors or the EPA.

Google Scholar as replacement for systematic literature searches: good relative recall and precision are not enough

PubMed Central

2013-01-01

Background Recent research indicates a high recall in Google Scholar searches for systematic reviews. These reports raised high expectations of Google Scholar as a unified and easy to use search interface. However, studies on the coverage of Google Scholar rarely used the search interface in a realistic approach but instead merely checked for the existence of gold standard references. In addition, the severe limitations of the Google Search interface must be taken into consideration when comparing with professional literature retrieval tools. The objectives of this work are to measure the relative recall and precision of searches with Google Scholar under conditions which are derived from structured search procedures conventional in scientific literature retrieval; and to provide an overview of current advantages and disadvantages of the Google Scholar search interface in scientific literature retrieval. Methods General and MEDLINE-specific search strategies were retrieved from 14 Cochrane systematic reviews. Cochrane systematic review search strategies were translated to Google Scholar search expression as good as possible under consideration of the original search semantics. The references of the included studies from the Cochrane reviews were checked for their inclusion in the result sets of the Google Scholar searches. Relative recall and precision were calculated. Results We investigated Cochrane reviews with a number of included references between 11 and 70 with a total of 396 references. The Google Scholar searches resulted in sets between 4,320 and 67,800 and a total of 291,190 hits. The relative recall of the Google Scholar searches had a minimum of 76.2% and a maximum of 100% (7 searches). The precision of the Google Scholar searches had a minimum of 0.05% and a maximum of 0.92%. The overall relative recall for all searches was 92.9%, the overall precision was 0.13%. Conclusion The reported relative recall must be interpreted with care. It is a quality indicator of Google Scholar confined to an experimental setting which is unavailable in systematic retrieval due to the severe limitations of the Google Scholar search interface. Currently, Google Scholar does not provide necessary elements for systematic scientific literature retrieval such as tools for incremental query optimization, export of a large number of references, a visual search builder or a history function. Google Scholar is not ready as a professional searching tool for tasks where structured retrieval methodology is necessary. PMID:24160679

Results of Prospecting of Impact Craters in Morocco

NASA Astrophysics Data System (ADS)

Chaabout, S.; Chennaoui Aoudjehane, H.; Reimold, W. U.; Baratoux, D.

2014-09-01

This work is based to use satellite images of Google Earth and Yahoo-Maps scenes; we examined the surface of our country to be able to locate the structures that have a circular morphology such as impact craters, which potentially could be.

Exploring Google Earth Engine platform for big data processing: classification of multi-temporal satellite imagery for crop mapping

NASA Astrophysics Data System (ADS)

Shelestov, Andrii; Lavreniuk, Mykola; Kussul, Nataliia; Novikov, Alexei; Skakun, Sergii

2017-02-01

Many applied problems arising in agricultural monitoring and food security require reliable crop maps at national or global scale. Large scale crop mapping requires processing and management of large amount of heterogeneous satellite imagery acquired by various sensors that consequently leads to a “Big Data” problem. The main objective of this study is to explore efficiency of using the Google Earth Engine (GEE) platform when classifying multi-temporal satellite imagery with potential to apply the platform for a larger scale (e.g. country level) and multiple sensors (e.g. Landsat-8 and Sentinel-2). In particular, multiple state-of-the-art classifiers available in the GEE platform are compared to produce a high resolution (30 m) crop classification map for a large territory ( 28,100 km2 and 1.0 M ha of cropland). Though this study does not involve large volumes of data, it does address efficiency of the GEE platform to effectively execute complex workflows of satellite data processing required with large scale applications such as crop mapping. The study discusses strengths and weaknesses of classifiers, assesses accuracies that can be achieved with different classifiers for the Ukrainian landscape, and compares them to the benchmark classifier using a neural network approach that was developed in our previous studies. The study is carried out for the Joint Experiment of Crop Assessment and Monitoring (JECAM) test site in Ukraine covering the Kyiv region (North of Ukraine) in 2013. We found that Google Earth Engine (GEE) provides very good performance in terms of enabling access to the remote sensing products through the cloud platform and providing pre-processing; however, in terms of classification accuracy, the neural network based approach outperformed support vector machine (SVM), decision tree and random forest classifiers available in GEE.

Stories from dynamic Earth: developing your sense of place through Landsat-based citizen science

NASA Astrophysics Data System (ADS)

Nelson, P.; Kennedy, R. E.; Nolin, A. W.; Hughes, J.; Bianchetti, R. A.; O'Connell, K.; Morrell, P.

2016-12-01

Many citizen science activities provide opportunities to understand a specific location on Earth at human scale and to collect local ecological knowledge that can improve the scientific endeavor of monitoring Earth. However, it can be challenging to comprehend ecological changes occurring at larger spatial and temporal scales. Based on the results of two professional development workshops designed for Oregon middle school science teachers in 2011-2013 and 2013-2016, we describe how working with multi-decade Landsat imagery transformed participants and students. Collaborating with scientists, the teachers used 30 years of time-series Landsat imagery with LandTrendr and IceTrendr algorithms to distill several study sites in Oregon, Washington, and Alaska (U.S) into periods of consistent long or short-duration landscape dynamics (e.g. stable areas, forestry activities, flooding, urbanization, tree growth). Using the spatial, tabular, and graphic outputs from this process, the teachers created climate change curriculum aligned to state and national standards. Web-enabled visualization tools, such as Google Earth, provided a platform that engaged students in understanding the drivers of their local landscape changes. Students and teachers reported increased interest in and understanding of their landscape. In addition to fulfilling classroom needs, the activities contributed data used in regional carbon modeling and land cover monitoring throughout California, Oregon, and Washington (U.S). We will discuss strategies and challenges to translating expert-level scientific data, models, methods, vocabulary, and conclusions into citizen science materials that support place-based climate change education across age ranges and educational disciplines. Finally, we share ways you can deepen your own sense of place while participating in citizen science activities that improve land cover and land use monitoring at local, regional, and global scales.

Assessing and Minimizing Adversarial Risk in a Nuclear Material Transportation Network

DTIC Science & Technology

2013-09-01

0704-0188) Washington DC 20503. 1. AGENCY USE ONLY (Leave Blank) 2. REPORT DATE 09-27-2013 3. REPORT TYPE AND DATES COVERED Master’s Thesis 4. TITLE AND...U.S. as of July 2013. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Figure A.1 Google Earth routing from Areva to Arkansas Nuclear...Uranium ore is mined or removed from the earth in a leaching process. 2. Conversion (1). Triuranium octoxide (U3O8, “yellowcake”) is converted into ura

Geospatial Data Science Applications and Visualizations | Geospatial Data

Science.gov Websites

. Since before the time of Google Maps, NREL has used the internet to allow stakeholders to view and world, these maps drive understanding. See our collection of key maps for examples. Featured Analysis

Using Google Earth for Submarine Operations at Pavilion Lake

NASA Astrophysics Data System (ADS)

Deans, M. C.; Lees, D. S.; Fong, T.; Lim, D. S.

2009-12-01

During the July 2009 Pavilion Lake field test, we supported submarine "flight" operations using Google Earth. The Intelligent Robotics Group at NASA Ames has experience with ground data systems for NASA missions, earth analog field tests, disaster response, and the Gigapan camera system. Leveraging this expertise and existing software, we put together a set of tools to support sub tracking and mapping, called the "Surface Data System." This system supports flight planning, real time flight operations, and post-flight analysis. For planning, we make overlays of the regional bedrock geology, sonar bathymetry, and sonar backscatter maps that show geology, depth, and structure of the bottom. Placemarks show the mooring locations for start and end points. Flight plans are shown as polylines with icons for waypoints. Flight tracks and imagery from previous field seasons are embedded in the map for planning follow-on activities. These data provide context for flight planning. During flights, sub position is updated every 5 seconds from the nav computer on the chase boat. We periodically update tracking KML files and refresh them with network links. A sub icon shows current location of the sub. A compass rose shows bearings to indicate heading to the next waypoint. A "Science Stenographer" listens on the voice loop and transcribes significant observations in real time. Observations called up to the surface immediately appear on the map as icons with date, time, position, and what was said. After each flight, the science back room immediately has the flight track and georeferenced notes from the pilots. We add additional information in post-processing. The submarines record video continuously, with "event" timestamps marked by the pilot. We cross-correlate the event timestamps with position logs to geolocate events and put a preview image and compressed video clip into the map. Animated flight tracks are also generated, showing timestamped position and providing timelapse playback of the flight. Neogeography tools are increasing in popularity and offer an excellent platform for geoinformatics. The scientists on the team are already familiar with Google Earth, eliminating up-front training on new tools. The flight maps and archived data are available immediately and in a usable format. Google Earth provides lots of measurement tools, annotation tools, and other built-in functions that we can use to create and analyze the map. All of this information is saved to a shared filesystem so that everyone on the team has access to all of the same map data. After the field season, the map data will be used by the team to analyse and correlate information from across the lake and across different flights to support their research, and to plan next year's activities.

Integrated Web-Based Access to and use of Satellite Remote Sensing Data for Improved Decision Making in Hydrologic Applications

NASA Astrophysics Data System (ADS)

Teng, W.; Chiu, L.; Kempler, S.; Liu, Z.; Nadeau, D.; Rui, H.

2006-12-01

Using NASA satellite remote sensing data from multiple sources for hydrologic applications can be a daunting task and requires a detailed understanding of the data's internal structure and physical implementation. Gaining this understanding and applying it to data reduction is a time-consuming task that must be undertaken before the core investigation can begin. In order to facilitate such investigations, the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has developed the GES-DISC Interactive Online Visualization ANd aNalysis Infrastructure or "Giovanni," which supports a family of Web interfaces (instances) that allow users to perform interactive visualization and analysis online without downloading any data. Two such Giovanni instances are particularly relevant to hydrologic applications: the Tropical Rainfall Measuring Mission (TRMM) Online Visualization and Analysis System (TOVAS) and the Agricultural Online Visualization and Analysis System (AOVAS), both highly popular and widely used for a variety of applications, including those related to several NASA Applications of National Priority, such as Agricultural Efficiency, Disaster Management, Ecological Forecasting, Homeland Security, and Public Health. Dynamic, context- sensitive Web services provided by TOVAS and AOVAS enable users to seamlessly access NASA data from within, and deeply integrate the data into, their local client environments. One example is between TOVAS and Florida International University's TerraFly, a Web-enabled system that serves a broad segment of the research and applications community, by facilitating access to various textual, remotely sensed, and vector data. Another example is between AOVAS and the U.S. Department of Agriculture Foreign Agricultural Service (USDA FAS)'s Crop Explorer, the primary decision support tool used by FAS to monitor the production, supply, and demand of agricultural commodities worldwide. AOVAS is also part of GES DISC's Agricultural Information System (AIS), which can operationally provide satellite remote sensing data products (e.g., near- real-time rainfall) and analysis services to agricultural users. AIS enables the remote, interoperable access to distributed data, by using the GrADS-Data Server (GDS) and the Open Geospatial Consortium (OGC)- compliant MapServer. The latter allows the access of AIS data from any OGC-compliant client, such as the Earth-Sun System Gateway (ESG) or Google Earth. The Giovanni system is evolving towards a Service- Oriented Architecture and is highly customizable (e.g., adding new products or services), thus availing the hydrologic applications user community of Giovanni's simple-to-use and powerful capabilities to improve decision-making.

A Web-Based Earth-Systems Knowledge Portal and Collaboration Platform

NASA Astrophysics Data System (ADS)

D'Agnese, F. A.; Turner, A. K.

2010-12-01

In support of complex water-resource sustainability projects in the Great Basin region of the United States, Earth Knowledge, Inc. has developed several web-based data management and analysis platforms that have been used by its scientists, clients, and public to facilitate information exchanges, collaborations, and decision making. These platforms support accurate water-resource decision-making by combining second-generation internet (Web 2.0) technologies with traditional 2D GIS and web-based 2D and 3D mapping systems such as Google Maps, and Google Earth. Most data management and analysis systems use traditional software systems to address the data needs and usage behavior of the scientific community. In contrast, these platforms employ more accessible open-source and “off-the-shelf” consumer-oriented, hosted web-services. They exploit familiar software tools using industry standard protocols, formats, and APIs to discover, process, fuse, and visualize earth, engineering, and social science datasets. Thus, they respond to the information needs and web-interface expectations of both subject-matter experts and the public. Because the platforms continue to gather and store all the contributions of their broad-spectrum of users, each new assessment leverages the data, information, and expertise derived from previous investigations. In the last year, Earth Knowledge completed a conceptual system design and feasibility study for a platform, which has a Knowledge Portal providing access to users wishing to retrieve information or knowledge developed by the science enterprise and a Collaboration Environment Module, a framework that links the user-access functions to a Technical Core supporting technical and scientific analyses including Data Management, Analysis and Modeling, and Decision Management, and to essential system administrative functions within an Administrative Module. The over-riding technical challenge is the design and development of a single technical platform that is accessed through a flexible series of knowledge portal and collaboration environment styles reflecting the information needs and user expectations of a diverse community of users. Recent investigations have defined the information needs and expectations of the major end-users and also have reviewed and assessed a wide variety of modern web-based technologies. Combining these efforts produced design specifications and recommendations for the selection and integration of web- and client-based tools. When fully developed, the resulting platform will: -Support new, advanced information systems and decision environments that take full advantage of multiple data sources and platforms; -Provide a distribution network tailored to the timely delivery of products to a broad range of users that are needed to support applications in disaster management, resource management, energy, and urban sustainability; -Establish new integrated multiple-user requirements and knowledge databases that support researchers and promote infusion of successful technologies into existing processes; and -Develop new decision support strategies and presentation methodologies for applied earth science applications to reduce risk, cost, and time.

Internet-Based Software Tools for Analysis and Processing of LIDAR Point Cloud Data via the OpenTopography Portal

NASA Astrophysics Data System (ADS)

Nandigam, V.; Crosby, C. J.; Baru, C.; Arrowsmith, R.

2009-12-01

LIDAR is an excellent example of the new generation of powerful remote sensing data now available to Earth science researchers. Capable of producing digital elevation models (DEMs) more than an order of magnitude higher resolution than those currently available, LIDAR data allows earth scientists to study the processes that contribute to landscape evolution at resolutions not previously possible, yet essential for their appropriate representation. Along with these high-resolution datasets comes an increase in the volume and complexity of data that the user must efficiently manage and process in order for it to be scientifically useful. Although there are expensive commercial LIDAR software applications available, processing and analysis of these datasets are typically computationally inefficient on the conventional hardware and software that is currently available to most of the Earth science community. We have designed and implemented an Internet-based system, the OpenTopography Portal, that provides integrated access to high-resolution LIDAR data as well as web-based tools for processing of these datasets. By using remote data storage and high performance compute resources, the OpenTopography Portal attempts to simplify data access and standard LIDAR processing tasks for the Earth Science community. The OpenTopography Portal allows users to access massive amounts of raw point cloud LIDAR data as well as a suite of DEM generation tools to enable users to generate custom digital elevation models to best fit their science applications. The Cyberinfrastructure software tools for processing the data are freely available via the portal and conveniently integrated with the data selection in a single user-friendly interface. The ability to run these tools on powerful Cyberinfrastructure resources instead of their own labs provides a huge advantage in terms of performance and compute power. The system also encourages users to explore data processing methods and the variations in algorithm parameters since all of the processing is done remotely and numerous jobs can be submitted in sequence. The web-based software also eliminates the need for users to deal with the hassles and costs associated with software installation and licensing while providing adequate disk space for storage and personal job archival capability. Although currently limited to data access and DEM generation tasks, the OpenTopography system is modular in design and can be modified to accommodate new processing tools as they become available. We are currently exploring implementation of higher-level DEM analysis tasks in OpenTopography, since such processing is often computationally intensive and thus lends itself to utilization of cyberinfrastructure. Products derived from OpenTopography processing are available in a variety of formats ranging from simple Google Earth visualizations of LIDAR-derived hillshades to various GIS-compatible grid formats. To serve community users less interested in data processing, OpenTopography also hosts 1 km^2 digital elevation model tiles as well as Google Earth image overlays for a synoptic view of the data.

Power Plants Likely Covered by the Mercury and Air Toxics Standards (MATS)

EPA Pesticide Factsheets

The U.S. Environmental Protection Agency (EPA) has proposed Mercury and Air Toxics Standards (MATS) for power plants to limit mercury, acid gases and other toxic pollution from power plants. Using Google Earth, this page locates power plants in your state.

A Geospatial Scavenger Hunt

ERIC Educational Resources Information Center

Martinez, Adriana E.; Williams, Nikki A.; Metoyer, Sandra K.; Morris, Jennifer N.; Berhane, Stephen A.

2009-01-01

With the use of technology such as Global Positioning System (GPS) units and Google Earth for a simple-machine scavenger hunt, you will transform a standard identification activity into an exciting learning experience that motivates students, incorporates practical skills in technology, and enhances students' spatial-thinking skills. In the…

Teaching Genocide through GIS: A Transformative Approach

ERIC Educational Resources Information Center

Fitchett, Paul G.; Good, Amy J.

2012-01-01

The utilization of Geographical Information Systems (GIS) and geobrowsers (Google Earth) have become increasingly prevalent in the study of genocide. These applications offer teachers and students the opportunity to analyze historical and contemporary genocidal acts from a critical geographic perspective in which the confluence of historical…

Digital field mapping for stimulating Secondary School students in the recognition of geological features and landforms

NASA Astrophysics Data System (ADS)

Giardino, Marco; Magagna, Alessandra; Ferrero, Elena; Perrone, Gianluigi

2015-04-01

Digital field mapping has certainly provided geoscientists with the opportunity to map and gather data in the field directly using digital tools and software rather than using paper maps, notebooks and analogue devices and then subsequently transferring the data to a digital format for subsequent analysis. But, the same opportunity has to be recognized for Geoscience education, as well as for stimulating and helping students in the recognition of landforms and interpretation of the geological and geomorphological components of a landscape. More, an early exposure to mapping during school and prior to university can optimise the ability to "read" and identify uncertainty in 3d models. During 2014, about 200 Secondary School students (aged 12-15) of the Piedmont region (NW Italy) participated in a research program involving the use of mobile devices (smartphone and tablet) in the field. Students, divided in groups, used the application Trimble Outdoors Navigators for tracking a geological trail in the Sangone Valley and for taking georeferenced pictures and notes. Back to school, students downloaded the digital data in a .kml file for the visualization on Google Earth. This allowed them: to compare the hand tracked trail on a paper map with the digital trail, and to discuss about the functioning and the precision of the tools; to overlap a digital/semitransparent version of the 2D paper map (a Regional Technical Map) used during the field trip on the 2.5D landscape of Google Earth, as to help them in the interpretation of conventional symbols such as contour lines; to perceive the landforms seen during the field trip as a part of a more complex Pleistocene glacial landscape; to understand the classical and innovative contributions from different geoscientific disciplines to the generation of a 3D structural geological model of the Rivoli-Avigliana Morainic Amphitheatre. In 2013 and 2014, some other pilot projects have been carried out in different areas of the Piedmont region, and in the Sesia Val Grande Geopark, for testing the utility of digital field mapping in Geoscience education. Feedback from students are positive: they are stimulated and involved by the use of ICT for learning Geoscience, and they voluntary choose to work with their personal mobile device (more than 90% of them own a smartphone); they are interested in knowing the features of GPS, and of software for the visualization of satellite and aerial images, but they recognize the importance of integrating and comparing traditional and innovative methods in the field.

Mobile membrane introduction tandem mass spectrometry for on-the-fly measurements and adaptive sampling of VOCs around oil and gas projects in Alberta, Canada

NASA Astrophysics Data System (ADS)

Krogh, E.; Gill, C.; Bell, R.; Davey, N.; Martinsen, M.; Thompson, A.; Simpson, I. J.; Blake, D. R.

2012-12-01

The release of hydrocarbons into the environment can have significant environmental and economic consequences. The evolution of smaller, more portable mass spectrometers to the field can provide spatially and temporally resolved information for rapid detection, adaptive sampling and decision support. We have deployed a mobile platform membrane introduction mass spectrometer (MIMS) for the in-field simultaneous measurement of volatile and semi-volatile organic compounds. In this work, we report instrument and data handling advances that produce geographically referenced data in real-time and preliminary data where these improvements have been combined with high precision ultra-trace VOCs analysis to adaptively sample air plumes near oil and gas operations in Alberta, Canada. We have modified a commercially available ion-trap mass spectrometer (Griffin ICX 400) with an in-house temperature controlled capillary hollow fibre polydimethylsiloxane (PDMS) polymer membrane interface and in-line permeation tube flow cell for a continuously infused internal standard. The system is powered by 24 VDC for remote operations in a moving vehicle. Software modifications include the ability to run continuous, interlaced tandem mass spectrometry (MS/MS) experiments for multiple contaminants/internal standards. All data are time and location stamped with on-board GPS and meteorological data to facilitate spatial and temporal data mapping. Tandem MS/MS scans were employed to simultaneously monitor ten volatile and semi-volatile analytes, including benzene, toluene, ethylbenzene and xylene (BTEX), reduced sulfur compounds, halogenated organics and naphthalene. Quantification was achieved by calibrating against a continuously infused deuterated internal standard (toluene-d8). Time referenced MS/MS data were correlated with positional data and processed using Labview and Matlab to produce calibrated, geographical Google Earth data-visualizations that enable adaptive sampling protocols. This real-time approach has been employed in a moving vehicle to identify and track downwind plumes of fugitive VOC emissions near hydrocarbon upgrading and chemical processing facilities in Fort Saskatchewan, Alberta. This information was relayed to a trailing vehicle, which collected stationary grab samples in evacuated canisters for ultra trace analysis of over seventy VOC analytes. In addition, stationary time series data were collected and compared with grab samples co-located with our sampling line. Spatially and temporally resolved, time referenced MS/MS data for several air contaminants associated with oil and gas processing were processed in real time to produce geospatial data for visualization in Google Earth. This information was used to strategically locate grab samples for high precision, ultra trace analysis.

Fuzzy B-spline optimization for urban slum three-dimensional reconstruction using ENVISAT satellite data

NASA Astrophysics Data System (ADS)

Marghany, Maged

2014-06-01

A critical challenges in urban aeras is slums. In fact, they are considered a source of crime and disease due to poor-quality housing, unsanitary conditions, poor infrastructures and occupancy security. The poor in the dense urban slums are the most vulnerable to infection due to (i) inadequate and restricted access to safety, drinking water and sufficient quantities of water for personal hygiene; (ii) the lack of removal and treatment of excreta; and (iii) the lack of removal of solid waste. This study aims to investigate the capability of ENVISAT ASAR satellite and Google Earth data for three-dimensional (3-D) slum urban reconstruction in developed countries such as Egypt. The main objective of this work is to utilize some 3-D automatic detection algorithm for urban slum in ENVISAT ASAR and Google Erath images were acquired in Cairo, Egypt using Fuzzy B-spline algorithm. The results show that the fuzzy algorithm is the best indicator for chaotic urban slum as it can discriminate between them from its surrounding environment. The combination of Fuzzy and B-spline then used to reconstruct 3-D of urban slum. The results show that urban slums, road network, and infrastructures are perfectly discriminated. It can therefore be concluded that the fuzzy algorithm is an appropriate algorithm for chaotic urban slum automatic detection in ENVSIAT ASAR and Google Earth data.

A comparison of Google Glass and traditional video vantage points for bedside procedural skill assessment.

PubMed

Evans, Heather L; O'Shea, Dylan J; Morris, Amy E; Keys, Kari A; Wright, Andrew S; Schaad, Douglas C; Ilgen, Jonathan S

2016-02-01

This pilot study assessed the feasibility of using first person (1P) video recording with Google Glass (GG) to assess procedural skills, as compared with traditional third person (3P) video. We hypothesized that raters reviewing 1P videos would visualize more procedural steps with greater inter-rater reliability than 3P rating vantages. Seven subjects performed simulated internal jugular catheter insertions. Procedures were recorded by both Google Glass and an observer's head-mounted camera. Videos were assessed by 3 expert raters using a task-specific checklist (CL) and both an additive- and summative-global rating scale (GRS). Mean scores were compared by t-tests. Inter-rater reliabilities were calculated using intraclass correlation coefficients. The 1P vantage was associated with a significantly higher mean CL score than the 3P vantage (7.9 vs 6.9, P = .02). Mean GRS scores were not significantly different. Mean inter-rater reliabilities for the CL, additive-GRS, and summative-GRS were similar between vantages. 1P vantage recordings may improve visualization of tasks for behaviorally anchored instruments (eg, CLs), whereas maintaining similar global ratings and inter-rater reliability when compared with conventional 3P vantage recordings. Copyright © 2016 Elsevier Inc. All rights reserved.

Google Glass Glare: disability glare produced by a head-mounted visual display.

PubMed

Longley, Chris; Whitaker, David

2016-03-01

Head mounted displays are a type of wearable technology - a market that is projected to expand rapidly over the coming years. Probably the most well known example is the device Google Glass (or 'Glass'). Here we investigate the extent to which the device display can interfere with normal visual function by producing monocular disability glare. Contrast sensitivity was measured in two normally sighted participants, 32 and 52 years of age. Data were recorded for the right eye, the left eye and then again in a binocular condition. Measurements were taken both with and without the Glass in place, across a range of stimulus luminance levels using a two-alternative forced-choice methodology. The device produced a significant reduction in contrast sensitivity in the right eye (>0.5 log units). The level of disability glare increased as stimulus luminance was reduced in a manner consistent with intraocular light scatter, resulting in a veiling retinal illuminance. Sensitivity in the left eye was unaffected. A significant reduction in binocular contrast sensitivity occurred at lower luminance levels due to a loss of binocular summation, although binocular sensitivity was not found to fall below the sensitivity of the better monocular level (binocular inhibition). Head mounted displays such as Google Glass have the potential to cause significant disability glare in the eye exposed to the visual display, particularly under conditions of low luminance. They can also cause a more modest binocular reduction in sensitivity by eliminating the benefits of binocular summation. © 2015 The Authors Ophthalmic & Physiological Optics © 2015 The College of Optometrists.

The community-driven BiG CZ software system for integration and analysis of bio- and geoscience data in the critical zone

NASA Astrophysics Data System (ADS)

Aufdenkampe, A. K.; Mayorga, E.; Horsburgh, J. S.; Lehnert, K. A.; Zaslavsky, I.; Valentine, D. W., Jr.; Richard, S. M.; Cheetham, R.; Meyer, F.; Henry, C.; Berg-Cross, G.; Packman, A. I.; Aronson, E. L.

2014-12-01

Here we present the prototypes of a new scientific software system designed around the new Observations Data Model version 2.0 (ODM2, https://github.com/UCHIC/ODM2) to substantially enhance integration of biological and Geological (BiG) data for Critical Zone (CZ) science. The CZ science community takes as its charge the effort to integrate theory, models and data from the multitude of disciplines collectively studying processes on the Earth's surface. The central scientific challenge of the CZ science community is to develop a "grand unifying theory" of the critical zone through a theory-model-data fusion approach, for which the key missing need is a cyberinfrastructure for seamless 4D visual exploration of the integrated knowledge (data, model outputs and interpolations) from all the bio and geoscience disciplines relevant to critical zone structure and function, similar to today's ability to easily explore historical satellite imagery and photographs of the earth's surface using Google Earth. This project takes the first "BiG" steps toward answering that need. The overall goal of this project is to co-develop with the CZ science and broader community, including natural resource managers and stakeholders, a web-based integration and visualization environment for joint analysis of cross-scale bio and geoscience processes in the critical zone (BiG CZ), spanning experimental and observational designs. We will: (1) Engage the CZ and broader community to co-develop and deploy the BiG CZ software stack; (2) Develop the BiG CZ Portal web application for intuitive, high-performance map-based discovery, visualization, access and publication of data by scientists, resource managers, educators and the general public; (3) Develop the BiG CZ Toolbox to enable cyber-savvy CZ scientists to access BiG CZ Application Programming Interfaces (APIs); and (4) Develop the BiG CZ Central software stack to bridge data systems developed for multiple critical zone domains into a single metadata catalog. The entire BiG CZ Software system is being developed on public repositories as a modular suite of open source software projects. It will be built around a new Observations Data Model Version 2.0 (ODM2) that has been developed by members of the BiG CZ project team, with community input, under separate funding.

Using open-source programs to create a web-based portal for hydrologic information

NASA Astrophysics Data System (ADS)

Kim, H.

2013-12-01

Some hydrologic data sets, such as basin climatology, precipitation, and terrestrial water storage, are not easily obtainable and distributable due to their size and complexity. We present a Hydrologic Information Portal (HIP) that has been implemented at the University of California for Hydrologic Modeling (UCCHM) and that has been organized around the large river basins of North America. This portal can be easily accessed through a modern web browser that enables easy access and visualization of such hydrologic data sets. Some of the main features of our HIP include a set of data visualization features so that users can search, retrieve, analyze, integrate, organize, and map data within large river basins. Recent information technologies such as Google Maps, Tornado (Python asynchronous web server), NumPy/SciPy (Scientific Library for Python) and d3.js (Visualization library for JavaScript) were incorporated into the HIP to create ease in navigating large data sets. With such open source libraries, HIP can give public users a way to combine and explore various data sets by generating multiple chart types (Line, Bar, Pie, Scatter plot) directly from the Google Maps viewport. Every rendered object such as a basin shape on the viewport is clickable, and this is the first step to access the visualization of data sets.

Get Connected

ERIC Educational Resources Information Center

Horton, Jessica; Hagevik, Rita; Adkinson, Bennett; Parmly, Jilynn

2013-01-01

Technology can be both a blessing and a curse in the classroom. Although technology can provide greater access to information and increase student engagement, if screen time replaces time spent outside, then students stand to lose awareness and connectivity to the surrounding natural environment. This article describes how Google Earth can foster…

Cornerstone: Foundational Models and Services for Integrated Battle Planning

DTIC Science & Technology

2012-06-01

We close with a summary of future planned research. 3 Cross-Domain Knowledge Representation One of the primary reasons behind the...mission data using Google Earth to display the results of a Keyhole Markup Language (KML) mission data translator. Finally, we successfully ran Thread 1

An Integrated Approach for Accessing Multiple Datasets through LANCE

NASA Astrophysics Data System (ADS)

Murphy, K. J.; Teague, M.; Conover, H.; Regner, K.; Beaumont, B.; Masuoka, E.; Vollmer, B.; Theobald, M.; Durbin, P.; Michael, K.; Boller, R. A.; Schmaltz, J. E.; Davies, D.; Horricks, K.; Ilavajhala, S.; Thompson, C. K.; Bingham, A.

2011-12-01

The NASA/GSFC Land Atmospheres Near-real time Capability for EOS (LANCE) provides imagery for approximately 40 data products from MODIS, AIRS, AMSR-E and OMI to support the applications community in the study of a variety of phenomena. Thirty-six of these products are available within 2.5 hours of observation at the spacecraft. The data set includes the population density data provided by the EOSDIS Socio-Economic Data and Applications Center (SEDAC). The purpose of this paper is to describe the variety of tools that have been developed by LANCE to support user access to the imagery. The long-standing Rapid Response system has been integrated into LANCE and is a major vehicle for the distribution of the imagery to end users. There are presently approximately 10,000 anonymous users per month accessing these imagery. The products are grouped into 14 applications categories such as Smoke Plumes, Pollution, Fires, Agriculture and the selection of any category will make relevant subsets of the 40 products available as possible overlays in an interactive Web Client utilizing Web Mapping Service (WMS) to support user investigations (http://lance2.modaps.eosdis.nasa.gov/wms/). For example, selecting Severe Storms will include 6 products for MODIS, OMI, AIRS, and AMSR-E plus the SEDAC population density data. The client and WMS were developed using open-source technologies such as OpenLayers and MapServer and provides a uniform, browser-based access to data products. All overlays are downloadable in PNG, JPEG, or GeoTiff form up to 200MB per request. The WMS was beta-tested with the user community and substantial performance improvements were made through the use of such techniques as tile-caching. LANCE established a partnership with Physical Oceanography Distributed Active Archive Center (PO DAAC) to develop an alternative presentation for the 40 data products known as the State of the Earth (SOTE). This provides a Google Earth-based interface to the products grouped in the same fashion as the WMS. The SOTE servers stream imagery and data in the OGC KML format and these feeds can be visualized through the Google Earth browser plug-in. SOTE provides visualization through a virtual globe environment by allowing users to interact with the globe via zooming, rotating, and tilting. In addition, SOTE also allows adding custom KML feeds. LANCE also provides datacasting feeds to facilitate user access to imagery for the 40 products and the related HDF-EOS products (available in a variety of formats). These XML-based data feeds contain data attribute and geolocation information, and metadata including an identification of the related application category. Users can subscribe to any feeds through the LANCE web site and use the PO DAAC Feed Reader to filter and view the content. The WMS, SOTE, and datacasting tools can be accessed through http://lance.nasa.gov.

Technical Aspects for the Creation of a Multi-Dimensional Land Information System

NASA Astrophysics Data System (ADS)

Ioannidis, Charalabos; Potsiou, Chryssy; Soile, Sofia; Verykokou, Styliani; Mourafetis, George; Doulamis, Nikolaos

2016-06-01

The complexity of modern urban environments and civil demands for fast, reliable and affordable decision-making requires not only a 3D Land Information System, which tends to replace traditional 2D LIS architectures, but also the need to address the time and scale parameters, that is, the 3D geometry of buildings in various time instances (4th dimension) at various levels of detail (LoDs - 5th dimension). This paper describes and proposes solutions for technical aspects that need to be addressed for the 5D modelling pipeline. Such solutions include the creation of a 3D model, the application of a selective modelling procedure between various time instances and at various LoDs, enriched with cadastral and other spatial data, and a procedural modelling approach for the representation of the inner parts of the buildings. The methodology is based on automatic change detection algorithms for spatial-temporal analysis of the changes that took place in subsequent time periods, using dense image matching and structure from motion algorithms. The selective modelling approach allows a detailed modelling only for the areas where spatial changes are detected. The procedural modelling techniques use programming languages for the textual semantic description of a building; they require the modeller to describe its part-to-whole relationships. Finally, a 5D viewer is developed, in order to tackle existing limitations that accompany the use of global systems, such as the Google Earth or the Google Maps, as visualization software. An application based on the proposed methodology in an urban area is presented and it provides satisfactory results.

Building Opportunities for Environmental Education Through Student Development of Cyberinfrastructure

NASA Astrophysics Data System (ADS)

Moysey, S. M.; Boyer, D. M.; Mobley, C.; Byrd, V. L.

2014-12-01

It is increasingly common to utilize simulations and games in the classroom, but learning opportunities can also be created by having students construct these cyberinfrastructure resources themselves. We outline two examples of such projects completed during the summer of 2014 within the NSF ACI sponsored REU Site: Research Experiences for Undergraduates in Collaborative Data Visualization Applications at Clemson University (Award 1359223). The first project focuses on the development of immersive virtual reality field trips of geologic sites using the Oculus Rift headset. This project developed a platform which will allow users to navigate virtual terrains derived from real-world data obtained from the US Geological Survey and Google Earth. The system provides users with the ability to partake in an interactive first-person exploration of a region, such as the Grand Canyon, and thus makes an important educational contribution for students without access to these environmental assets in the real world. The second project focused on providing players visual feedback about the sustainability of their practices within the web-based, multiplayer watershed management game Naranpur Online. Identifying sustainability indicators that communicate meaningful information to players and finding an effective way to visualize these data were a primary challenge faced by the student researcher working on this project. To solve this problem the student translated findings from the literature to the context of the game to develop a hierarchical set of relative sustainability criteria to be accessed by players within a sustainability dashboard. Though the REU focused on visualization, both projects forced the students to transform their thinking to address higher-level questions regarding the utilization and communication of environmental data or concepts, thus enhancing the educational experience for themselves and future students.

Integrating Geospatial Technologies to Examine Urban Land Use Change: A Design Partnership

ERIC Educational Resources Information Center

Bodzin, Alec M.; Cirucci, Lori

2009-01-01

This article describes a design partnership that investigated how to integrate Google Earth, remotely sensed satellite and aerial imagery, with other instructional resources to investigate ground cover and land use in diverse middle school classrooms. Data analysis from the implementation study revealed that students acquired skills for…

Learning Geomorphology Using Aerial Photography in a Web-Facilitated Class

ERIC Educational Resources Information Center

Palmer, R. Evan

2013-01-01

General education students taking freshman-level physical geography and geomorphology classes at Arizona State University completed an online laboratory whose main tool was Google Earth. Early in the semester, oblique and planimetric views introduced students to a few volcanic, tectonic, glacial, karst, and coastal landforms. Semi-quantitative…

Understanding "Change" through Spatial Thinking Using Google Earth in Secondary Geography

ERIC Educational Resources Information Center

Xiang, X.; Liu, Y.

2017-01-01

Understanding geographic changes has become an indispensable element in geography education. Describing and analyzing changes in space require spatial thinking skills emphasized in geography curriculum but often pose challenges for secondary school students. This school-based research targets a specific strand of spatial thinking skills and…

Earthdata 3.0: A Unified Experience and Platform for Earth Science Discovery

NASA Astrophysics Data System (ADS)

Plofchan, P.; McLaughlin, B. D.

2015-12-01

NASA's EOSDIS (Earth Observing System Data and Information System) as a multitude of websites and applications focused on serving the Earth Science community's extensive data needs. With no central user interface, theme, or mechanism for accessing that data, interrelated systems are confusing and potentially disruptive in users' searches for EOSDIS data holdings. In an effort to bring consistency across these systems, an effort was undertaken to develop Earthdata 3.0: a complete information architecture overhaul of the Earthdata website, a significant update to the Earthdata user experience and user interface, and an increased focus on searching across EOSDIS data holdings, including those housed and made available through DAAC websites. As part of this effort, and in a desire to unify the user experience across related websites, the Earthdata User Interface (EUI) was developed. The EUI is a collection of responsive design components and layouts geared toward creating websites and applications within the Earthdata ecosystem. Each component and layout has been designed specifically for Earth science-related projects which eliminates some of the complexities of building a website or application from the ground up. Its adoption will ensure both consistent markup and a unified look and feel for end users, thereby increasing usability and accessibility. Additionally, through the user of a Google Search Appliance, custom Clojure code, and in cooperation with DAACs, Earthdata 3.0 presents a variety of search results upon a user's keyword(s) entry. These results are not just textual links, but also direct links to downloadable datasets, visualizations of datasets and collections of data, and related articles and videos for further research. The end result of the development of the EUI and the enhanced multi-response type search is a consistent and usable platform for Earth scientists and users to navigate and locate data to further their research.

Common Ground: An Interactive Visual Exploration and Discovery for Complex Health Data

DTIC Science & Technology

2014-04-01

annotate other ontologies for the visual interface client. Finally, we are actively working on software development of both a backend server and the...the following infrastructure and resources. For the development and management of the ontologies, we installed a framework consisting of a server...that is being developed by Google. Using these 9 technologies, we developed an HTML5 client that runs on Windows, Mac OSX, Linux and mobile systems

Operational Monitoring of Volcanoes Using Keyhole Markup Language

NASA Astrophysics Data System (ADS)

Dehn, J.; Bailey, J. E.; Webley, P.

2007-12-01

Volcanoes are some of the most geologically powerful, dynamic, visually appealing structures on the Earth's landscape. Volcanic eruptions are hard to predict, difficult to quantify and impossible to prevent, making effective monitoring a difficult proposition. In Alaska, volcanoes are an intrinsic part of the culture, with over 100 volcanoes and volcanic fields that have been active in historic time monitored by the Alaska Volcano Observatory (AVO). Observations and research are performed using a suite of methods and tools in the fields of remote sensing, seismology, geodesy and geology, producing large volumes of geospatial data. Keyhole Markup Language (KML) offers a context in which these different, and in the past disparate, data can be displayed simultaneously. Dynamic links keep these data current, allowing it to be used in an operational capacity. KML is used to display information from the aviation color codes and activity alert levels for volcanoes to locations of thermal anomalies, earthquake locations and ash plume modeling. The dynamic refresh and time primitive are used to display volcano webcam and satellite image overlays in near real-time. In addition a virtual globe browser using KML, such as Google Earth, provides an interface to further information using the hyperlink, rich- text and flash-embedding abilities supported within object description balloons. By merging these data sets in an easy to use interface, a virtual globe browser provides a better tool for scientists and emergency managers alike to mitigate volcanic crises.

From data to information: Tools and techniques educators can use to enhance Google Earth imagery with geographic information systems data and three dimensional models

NASA Astrophysics Data System (ADS)

Simms, M.

2007-12-01

As with any educational technology, moving beyond basic information delivery to dynamic use can be a challenge and Google Earth (GE) is no exception. Moving beyond annotated placemarks and pictures, educators can utilize free, free-to-educators, and low cost tools to develop learning experiences within GE to facilitate dynamic interaction with real world data in the form of three dimensional models (3D) and geographic information systems data (GIS). Students take an active role in knowledge construction through self-directed navigation in 3D, seeing features of the landscape not in snapshot views found in textbooks, but in situ and in context. By incorporating categorized data, such as what is commonly found in GIS, an added dimension of human interaction can be incorporated. For example, GIS layers such as landuse, soil type, etc. provide students with data tools for investigating the role their community plays in supporting migrating Monarch butterfly habitat. Functionality for changing the appearance of layers in GE facilitates interaction with geospatial data in a manner that creates a type of "visual" GIS and can serve as an advanced organizer for later use of more powerful GIS software. GE can also be used as a metaphor to create a new context for an otherwise abstract concept, for example, scaling 3D models of the sun and planets to the size of a well known football stadium and placing each planet at the corresponding scaled distances from that location. Photorealistic 3D models created using SketchUp and Anim8or may help students relate to an otherwise abstract concept of planetary size and distances. Finally, digital elevation models (DEM) draped with imagery not available in GE or with GIS data can be used to make topic-specific 3D models either used within GE or in a 3D model viewer embedded in a website or email. With a little instruction, students can quickly learn how to make their own models as well. Procedures and software to accomplish each of these examples will be demonstrated.

An Object-Based Machine Learning Classification Procedure for Mapping Impoundments in Brazil's Amazon-Cerrado Agricultural Frontier

NASA Astrophysics Data System (ADS)

Solvik, K.; Macedo, M.; Graesser, J.; Lathuilliere, M. J.

2017-12-01

Large-scale agriculture and cattle ranching in Brazil has driving the creation of tens of thousands of small stream impoundments to provide water for crops and livestock. These impoundments are a source of methane emissions and have significant impacts on stream temperature, connectivity, and water use over a large region. Due to their large numbers and small size, they are difficult to map using conventional methods. Here, we present a two-stage object-based supervised classification methodology for identifying man-made impoundments in Brazil. First, in Google Earth Engine pixels are classified as water or non-water using satellite data and HydroSHEDS products as predictors. Second, using Python's scikit-learn and scikit-image modules the water objects are classified as man-made or natural based on a variety of shape and spectral properties. Both classifications are performed by a random forest classifier. Training data is acquired by visually identifying impoundments and natural water bodies using high resolution satellite imagery from Google Earth.This methodology was applied to the state of Mato Grosso using a cloud-free mosaic of Sentinel 1 (10m resolution) radar and Sentinel 2 (10-20m) multispectral data acquired during the 2016 dry season. Independent test accuracy was estimated at 95% for the first stage and 93% for the second. We identified 54,294 man-made impoundments in Mato Grosso in 2016. The methodology is generalizable to other high resolution satellite data and has been tested on Landsat 5 and 8 imagery. Applying the same approach to Landsat 8 images (30 m), we identified 35,707 impoundments in the 2015 dry season. The difference in number is likely because the coarser-scale imagery fails to detect small (< 900 m2) objects. On-going work will apply this approach to satellite time series for the entire Amazon-Cerrado frontier, allowing us to track changes in the number, size, and distribution of man-made impoundments. Automated impoundment mapping over large areas may help with management of streams in agricultural landscapes in Brazil and other tropical regions.

Semantic Web Data Discovery of Earth Science Data at NASA Goddard Earth Sciences Data and Information Services Center (GES DISC)

NASA Technical Reports Server (NTRS)

Hegde, Mahabaleshwara; Strub, Richard F.; Lynnes, Christopher S.; Fang, Hongliang; Teng, William

2008-01-01

Mirador is a web interface for searching Earth Science data archived at the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). Mirador provides keyword-based search and guided navigation for providing efficient search and access to Earth Science data. Mirador employs the power of Google's universal search technology for fast metadata keyword searches, augmented by additional capabilities such as event searches (e.g., hurricanes), searches based on location gazetteer, and data services like format converters and data sub-setters. The objective of guided data navigation is to present users with multiple guided navigation in Mirador is an ontology based on the Global Change Master directory (GCMD) Directory Interchange Format (DIF). Current implementation includes the project ontology covering various instruments and model data. Additional capabilities in the pipeline include Earth Science parameter and applications ontologies.

Application of Deep Learning in GLOBELAND30-2010 Product Refinement

NASA Astrophysics Data System (ADS)

Liu, T.; Chen, X.

2018-04-01

GlobeLand30, as one of the best Global Land Cover (GLC) product at 30-m resolution, has been widely used in many research fields. Due to the significant spectral confusion among different land cover types and limited textual information of Landsat data, the overall accuracy of GlobeLand30 is about 80 %. Although such accuracy is much higher than most other global land cover products, it cannot satisfy various applications. There is still a great need of an effective method to improve the quality of GlobeLand30. The explosive high-resolution satellite images and remarkable performance of Deep Learning on image classification provide a new opportunity to refine GlobeLand30. However, the performance of deep leaning depends on quality and quantity of training samples as well as model training strategy. Therefore, this paper 1) proposed an automatic training sample generation method via Google earth to build a large training sample set; and 2) explore the best training strategy for land cover classification using GoogleNet (Inception V3), one of the most widely used deep learning network. The result shows that the fine-tuning from first layer of Inception V3 using rough large sample set is the best strategy. The retrained network was then applied in one selected area from Xi'an city as a case study of GlobeLand30 refinement. The experiment results indicate that the proposed approach with Deep Learning and google earth imagery is a promising solution for further improving accuracy of GlobeLand30.

JPL Earth Science Center Visualization Multitouch Table

NASA Astrophysics Data System (ADS)

Kim, R.; Dodge, K.; Malhotra, S.; Chang, G.

2014-12-01

JPL Earth Science Center Visualization table is a specialized software and hardware to allow multitouch, multiuser, and remote display control to create seamlessly integrated experiences to visualize JPL missions and their remote sensing data. The software is fully GIS capable through time aware OGC WMTS using Lunar Mapping and Modeling Portal as the GIS backend to continuously ingest and retrieve realtime remote sending data and satellite location data. 55 inch and 82 inch unlimited finger count multitouch displays allows multiple users to explore JPL Earth missions and visualize remote sensing data through very intuitive and interactive touch graphical user interface. To improve the integrated experience, Earth Science Center Visualization Table team developed network streaming which allows table software to stream data visualization to near by remote display though computer network. The purpose of this visualization/presentation tool is not only to support earth science operation, but specifically designed for education and public outreach and will significantly contribute to STEM. Our presentation will include overview of our software, hardware, and showcase of our system.

How scary! An analysis of visual communication concerning genetically modified organisms in Italy.

PubMed

Ventura, Vera; Frisio, Dario G; Ferrazzi, Giovanni; Siletti, Elena

2017-07-01

Several studies provide evidence of the role of written communication in influencing public perception towards genetically modified organisms, whereas visual communication has been sparsely investigated. This article aims to evaluate the exposure of the Italian population to scary genetically modified organism-related images. A set of 517 images collected through Google are classified considering fearful attributes, and an index that accounts for the scary impact of these images is built. Then, through an ordinary least-squares regression, we estimate the relationship between the Scary Impact Index and a set of variables that describes the context in which the images appear. The results reveal that the first (and most viewed) Google result images contain the most frightful contents. In addition, the agri-food sector in Italy is strongly oriented towards offering a negative representation of genetically modified organisms. Exposure to scary images could be a factor that affects the negative perception of genetically modified organisms in Italy.

Development and Deployment of the Computer Assisted Neighborhood Visual Assessment System (CANVAS) to Measure Health-Related Neighborhood Conditions

PubMed Central

Bader, Michael D. M.; Mooney, Stephen J.; Lee, Yeon Jin; Sheehan, Daniel; Neckerman, Kathryn M.; Rundle, Andrew G.; Teitler, Julien O.

2014-01-01

Public health research has shown that neighborhood conditions are associated with health behaviors and outcomes. Systematic neighborhood audits have helped researchers measure neighborhood conditions that they deem theoretically relevant but not available in existing administrative data. Systematic audits, however, are expensive to conduct and rarely comparable across geographic regions. We describe the development of an online application, the Computer Assisted Neighborhood Visual Assessment System (CANVAS), that uses Google Street View to conduct virtual audits of neighborhood environments. We use this system to assess the inter-rater reliability of 187 items related to walkability and physical disorder on a national sample of 150 street segments in the United States. We find that many items are reliably measured across auditors using CANVAS and that agreement between auditors appears to be uncorrelated with neighborhood demographic characteristics. Based on our results we conclude that Google Street View and CANVAS offer opportunities to develop greater comparability across neighborhood audit studies. PMID:25545769

Using the Browser for Science: A Collaborative Toolkit for Astronomy

NASA Astrophysics Data System (ADS)

Connolly, A. J.; Smith, I.; Krughoff, K. S.; Gibson, R.

2011-07-01

Astronomical surveys have yielded hundreds of terabytes of catalogs and images that span many decades of the electromagnetic spectrum. Even when observatories provide user-friendly web interfaces, exploring these data resources remains a complex and daunting task. In contrast, gadgets and widgets have become popular in social networking (e.g. iGoogle, Facebook). They provide a simple way to make complex data easily accessible that can be customized based on the interest of the user. With ASCOT (an AStronomical COllaborative Toolkit) we expand on these concepts to provide a customizable and extensible gadget framework for use in science. Unlike iGoogle, where all of the gadgets are independent, the gadgets we develop communicate and share information, enabling users to visualize and interact with data through multiple, simultaneous views. With this approach, web-based applications for accessing and visualizing data can be generated easily and, by linking these tools together, integrated and powerful data analysis and discovery tools can be constructed.

The Dimensions of the Solar System

ERIC Educational Resources Information Center

Schneider, Stephen E.; Davis, Kathleen S.

2007-01-01

A few new wrinkles have been added to the popular activity of building a scale model of the solar system. Students can learn about maps and scaling using easily accessible online resources that include satellite images. This is accomplished by taking advantage of some of the special features of Google Earth. This activity gives students a much…

Crowdfunding Astronomy Research with Google Sky

ERIC Educational Resources Information Center

Metcalfe, Travis S.

2015-01-01

For nearly four years, NASA's Kepler space telescope searched for planets like Earth around more than 150,000 stars similar to the Sun. In 2008 with in-kind support from several technology companies, our non-profit organization established the Pale Blue Dot Project, an adopt-a-star program that supports scientific research on the stars observed by…

Using Google Earth to Teach Plate Tectonics and Science Explanations

ERIC Educational Resources Information Center

Blank, Lisa M.; Plautz, Mike; Almquist, Heather; Crews, Jeff; Estrada, Jen

2012-01-01

"A Framework for K-12 Science Education: Practices, Crosscutting Concepts, and Core Ideas" emphasizes that the practice of science is inherently a model-building activity focused on constructing explanations using evidence and reasoning (NRC 2012). Because building and refining is an iterative process, middle school students may view this practice…

Drawing the Line with Google Earth: The Place of Digital Mapping outside of Geography

ERIC Educational Resources Information Center

Mercier, O. Ripeka; Rata, Arama

2017-01-01

The "Te Kawa a Maui Atlas" project explores how mapping activities support undergraduate student engagement and learning in Maori studies. This article describes two specific assignments, which used online mapping allowing students to engage with the work of their peers. By analysing student evaluations of these activities, we identify…

Map Scale, Proportion, and Google[TM] Earth

ERIC Educational Resources Information Center

Roberge, Martin C.; Cooper, Linda L.

2010-01-01

Aerial imagery has a great capacity to engage and maintain student interest while providing a contextual setting to strengthen their ability to reason proportionally. Free, on-demand, high-resolution, large-scale aerial photography provides both a bird's eye view of the world and a new perspective on one's own community. This article presents an…

Cloud-based Computing and Applications of New Snow Metrics for Societal Benefit

NASA Astrophysics Data System (ADS)

Nolin, A. W.; Sproles, E. A.; Crumley, R. L.; Wilson, A.; Mar, E.; van de Kerk, M.; Prugh, L.

2017-12-01

Seasonal and interannual variability in snow cover affects socio-environmental systems including water resources, forest ecology, freshwater and terrestrial habitat, and winter recreation. We have developed two new seasonal snow metrics: snow cover frequency (SCF) and snow disappearance date (SDD). These metrics are calculated at 500-m resolution using NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover data (MOD10A1). SCF is the number of times snow is observed in a pixel over the user-defined observation period. SDD is the last date of observed snow in a water year. These pixel-level metrics are calculated rapidly and globally in the Google Earth Engine cloud-based environment. SCF and SDD can be interactively visualized in a map-based interface, allowing users to explore spatial and temporal snowcover patterns from 2000-present. These metrics are especially valuable in regions where snow data are sparse or non-existent. We have used these metrics in several ongoing projects. When SCF was linked with a simple hydrologic model in the La Laguna watershed in northern Chile, it successfully predicted summer low flows with a Nash-Sutcliffe value of 0.86. SCF has also been used to help explain changes in Dall sheep populations in Alaska where sheep populations are negatively impacted by late snow cover and low snowline elevation during the spring lambing season. In forest management, SCF and SDD appear to be valuable predictors of post-wildfire vegetation growth. We see a positive relationship between winter SCF and subsequent summer greening for several years post-fire. For western US winter recreation, we are exploring trends in SDD and SCF for regions where snow sports are economically important. In a world with declining snowpacks and increasing uncertainty, these metrics extend across elevations and fill data gaps to provide valuable information for decision-making. SCF and SDD are being produced so that anyone with Internet access and a Google account can access, visualize, and download the data with a minimum of technical expertise and no need for proprietary software.

Tethys: A Platform for Water Resources Modeling and Decision Support Apps

NASA Astrophysics Data System (ADS)

Swain, N. R.; Christensen, S. D.; Jones, N.; Nelson, E. J.

2014-12-01

Cloud-based applications or apps are a promising medium through which water resources models and data can be conveyed in a user-friendly environment—making them more accessible to decision-makers and stakeholders. In the context of this work, a water resources web app is a web application that exposes limited modeling functionality for a scenario exploration activity in a structured workflow (e.g.: land use change runoff analysis, snowmelt runoff prediction, and flood potential analysis). The technical expertise required to develop water resources web apps can be a barrier to many potential developers of water resources apps. One challenge that developers face is in providing spatial storage, analysis, and visualization for the spatial data that is inherent to water resources models. The software projects that provide this functionality are non-standard to web development and there are a large number of free and open source software (FOSS) projects to choose from. In addition, it is often required to synthesize several software projects to provide all of the needed functionality. Another challenge for the developer will be orchestrating the use of several software components. Consequently, the initial software development investment required to deploy an effective water resources cloud-based application can be substantial. The Tethys Platform has been developed to lower the technical barrier and minimize the initial development investment that prohibits many scientists and engineers from making use of the web app medium. Tethys synthesizes several software projects including PostGIS for spatial storage, 52°North WPS for spatial analysis, GeoServer for spatial publishing, Google Earth™, Google Maps™ and OpenLayers for spatial visualization, and Highcharts for plotting tabular data. The software selection came after a literature review of software projects being used to create existing earth sciences web apps. All of the software is linked via a Python-powered software development kit (SDK). Tethys developers use the SDK to build their apps and incorporate the needed functionality from the software suite. The presentation will include several apps that have been developed using Tethys to demonstrate its capabilities. Based upon work supported by the National Science Foundation under Grant No. 1135483.

Measurable realistic image-based 3D mapping

NASA Astrophysics Data System (ADS)

Liu, W.; Wang, J.; Wang, J. J.; Ding, W.; Almagbile, A.

2011-12-01

Maps with 3D visual models are becoming a remarkable feature of 3D map services. High-resolution image data is obtained for the construction of 3D visualized models.The3D map not only provides the capabilities of 3D measurements and knowledge mining, but also provides the virtual experienceof places of interest, such as demonstrated in the Google Earth. Applications of 3D maps are expanding into the areas of architecture, property management, and urban environment monitoring. However, the reconstruction of high quality 3D models is time consuming, and requires robust hardware and powerful software to handle the enormous amount of data. This is especially for automatic implementation of 3D models and the representation of complicated surfacesthat still need improvements with in the visualisation techniques. The shortcoming of 3D model-based maps is the limitation of detailed coverage since a user can only view and measure objects that are already modelled in the virtual environment. This paper proposes and demonstrates a 3D map concept that is realistic and image-based, that enables geometric measurements and geo-location services. Additionally, image-based 3D maps provide more detailed information of the real world than 3D model-based maps. The image-based 3D maps use geo-referenced stereo images or panoramic images. The geometric relationships between objects in the images can be resolved from the geometric model of stereo images. The panoramic function makes 3D maps more interactive with users but also creates an interesting immersive circumstance. Actually, unmeasurable image-based 3D maps already exist, such as Google street view, but only provide virtual experiences in terms of photos. The topographic and terrain attributes, such as shapes and heights though are omitted. This paper also discusses the potential for using a low cost land Mobile Mapping System (MMS) to implement realistic image 3D mapping, and evaluates the positioning accuracy that a measureable realistic image-based (MRI) system can produce. The major contribution here is the implementation of measurable images on 3D maps to obtain various measurements from real scenes.

Detecting Potential Water Quality Issues by Mapping Trophic Status Using Google Earth Engine

NASA Astrophysics Data System (ADS)

Nguy-Robertson, A. L.; Harvey, K.; Huening, V.; Robinson, H.

2017-12-01

The identification, timing, and spatial distribution of recurrent algal blooms and aquatic vegetation can help water managers and policy makers make better water resource decisions. In many parts of the world there is little monitoring or reporting of water quality due to the required costs and effort to collect and process water samples. We propose to use Google Earth Engine to quickly identify the recurrence of trophic states in global inland water systems. Utilizing Landsat and Sentinel multispectral imagery, inland water quality parameters (i.e. chlorophyll a concentration) can be estimated and waters can be classified by trophic state; oligotrophic, mesotrophic, eutrophic, and hypereutrophic. The recurrence of eutrophic and hypereutrophic observations can highlight potentially problematic locations where algal blooms or aquatic vegetation occur routinely. Eutrophic and hypereutrophic waters commonly include many harmful algal blooms and waters prone to fish die-offs from hypoxia. While these maps may be limited by the accuracy of the algorithms utilized to estimate chlorophyll a; relative comparisons at a local scale can help water managers to focus limited resources.

Undergraduate Course on Global Concerns

NASA Astrophysics Data System (ADS)

Richard, G. A.; Weidner, D. J.

2008-12-01

GEO 311: Geoscience and Global Concerns is an undergraduate course taught at Stony Brook University during each fall semester. The class meets twice per week, with one session consisting of a lecture and the other, an interactive activity in a computer laboratory that engages the students in exploring real world problems. A specific concern or issue serves as a focus during each session. The students are asked to develop answers to a series of questions that engage them in identifying causes of the problem, connections with the Earth system, relationships to other problems, and possible solutions on both a global and local scale. The questions are designed to facilitate an integrated view of the Earth system. Examples of topics that the students explore during the laboratory sessions are: 1) fossil fuel reserves and consumption rates and the effect of their use on climate, 2) alternative sources of energy and associated technologies, such as solar photovoltaics, nuclear energy, tidal power, geothermal energy, and wind power, 3) effects of tsunamis and earthquakes on human populations and infrastructure, 4) climate change, and 5) hurricanes and storms. The selection and scheduling of topics often takes advantage of the occurrence of media attention or events that can serve as case studies. Tools used during the computer sessions include Google Earth, ArcGIS, spreadsheets, and web sites that offer data and maps. The students use Google Earth or ArcGIS to map events such as earthquakes, storms, tsunamis, and changes in the extent of polar ice. Spreadsheets are employed to discern trends in fossil fuel supply and consumption, and to experiment with models that make predictions for the future. We present examples of several of these activities and discuss how they facilitate an understanding of interrelationships within the Earth system.

Yet More Visualized JAMSTEC Cruise and Dive Information

NASA Astrophysics Data System (ADS)

Tomiyama, T.; Hase, H.; Fukuda, K.; Saito, H.; Kayo, M.; Matsuda, S.; Azuma, S.

2014-12-01

Every year, JAMSTEC performs about a hundred of research cruises and numerous dive surveys using its research vessels and submersibles. JAMSTEC provides data and samples obtained during these cruises and dives to international users through a series of data sites on the Internet. The "DARWIN (http://www.godac.jamstec.go.jp/darwin/e)" data site disseminates cruise and dive information. On DARWIN, users can search interested cruises and dives with a combination search form or an interactive tree menu, and find lists of observation data as well as links to surrounding databases. Document catalog, physical sample databases, and visual archive of dive surveys (e. g. in http://www.godac.jamstec.go.jp/jmedia/portal/e) are directly accessible from the lists. In 2014, DARWIN experienced an update, which was arranged mainly for enabling on-demand data visualization. Using　login users' functions, users can put listed data items into the virtual basket and then trim, plot and download the data. The visualization tools help users to quickly grasp the quality and characteristics of observation data. Meanwhile, JAMSTEC launched a new data site named "JDIVES (http://www.godac.jamstec.go.jp/jdives/e)"　to visualize data and sample information obtained by dive surveys. JDIVES shows tracks of dive surveys on the "Google Earth Plugin" and diagrams of deep-sea environmental data such as temperature, salinity, and depth. Submersible camera images and links to associated databases are placed along the dive tracks. The JDVIES interface enables users to perform so-called virtual dive surveys, which can help users to understand local geometries of dive spots and geological settings of associated data and samples. It is not easy for individual researchers to organize a huge amount of information recovered from each cruise and dive. The improved visibility and accessibility of JAMSTEC databases are advantageous not only for second-hand users, but also for on-board researchers themselves.

NASA's Global Imagery Browse Services - Technologies for Visualizing Earth Science Data

NASA Astrophysics Data System (ADS)

Cechini, M. F.; Boller, R. A.; Baynes, K.; Schmaltz, J. E.; Thompson, C. K.; Roberts, J. T.; Rodriguez, J.; Wong, M. M.; King, B. A.; King, J.; De Luca, A. P.; Pressley, N. N.

2017-12-01

For more than 20 years, the NASA Earth Observing System (EOS) has collected earth science data for thousands of scientific parameters now totaling nearly 15 Petabytes of data. In 2013, NASA's Global Imagery Browse Services (GIBS) formed its vision to "transform how end users interact and discover [EOS] data through visualizations." This vision included leveraging scientific and community best practices and standards to provide a scalable, compliant, and authoritative source for EOS earth science data visualizations. Since that time, GIBS has grown quickly and now services millions of daily requests for over 500 imagery layers representing hundreds of earth science parameters to a broad community of users. For many of these parameters, visualizations are available within hours of acquisition from the satellite. For others, visualizations are available for the entire mission of the satellite. The GIBS system is built upon the OnEarth and MRF open source software projects, which are provided by the GIBS team. This software facilitates standards-based access for compliance with existing GIS tools. The GIBS imagery layers are predominantly rasterized images represented in two-dimensional coordinate systems, though multiple projections are supported. The OnEarth software also supports the GIBS ingest pipeline to facilitate low latency updates to new or updated visualizations. This presentation will focus on the following topics: Overview of GIBS visualizations and user community Current benefits and limitations of the OnEarth and MRF software projects and related standards GIBS access methods and their in/compatibilities with existing GIS libraries and applications Considerations for visualization accuracy and understandability Future plans for more advanced visualization concepts including Vertical Profiles and Vector-Based Representations Future plans for Amazon Web Service support and deployments

Google Glass-Directed Monitoring and Control of Microfluidic Biosensors and Actuators

PubMed Central

Zhang, Yu Shrike; Busignani, Fabio; Ribas, João; Aleman, Julio; Rodrigues, Talles Nascimento; Shaegh, Seyed Ali Mousavi; Massa, Solange; Rossi, Camilla Baj; Taurino, Irene; Shin, Su-Ryon; Calzone, Giovanni; Amaratunga, Givan Mark; Chambers, Douglas Leon; Jabari, Saman; Niu, Yuxi; Manoharan, Vijayan; Dokmeci, Mehmet Remzi; Carrara, Sandro; Demarchi, Danilo; Khademhosseini, Ali

2016-01-01

Google Glass is a recently designed wearable device capable of displaying information in a smartphone-like hands-free format by wireless communication. The Glass also provides convenient control over remote devices, primarily enabled by voice recognition commands. These unique features of the Google Glass make it useful for medical and biomedical applications where hands-free experiences are strongly preferred. Here, we report for the first time, an integral set of hardware, firmware, software, and Glassware that enabled wireless transmission of sensor data onto the Google Glass for on-demand data visualization and real-time analysis. Additionally, the platform allowed the user to control outputs entered through the Glass, therefore achieving bi-directional Glass-device interfacing. Using this versatile platform, we demonstrated its capability in monitoring physical and physiological parameters such as temperature, pH, and morphology of liver- and heart-on-chips. Furthermore, we showed the capability to remotely introduce pharmaceutical compounds into a microfluidic human primary liver bioreactor at desired time points while monitoring their effects through the Glass. We believe that such an innovative platform, along with its concept, has set up a premise in wearable monitoring and controlling technology for a wide variety of applications in biomedicine. PMID:26928456

Google Glass-Directed Monitoring and Control of Microfluidic Biosensors and Actuators

NASA Astrophysics Data System (ADS)

Zhang, Yu Shrike; Busignani, Fabio; Ribas, João; Aleman, Julio; Rodrigues, Talles Nascimento; Shaegh, Seyed Ali Mousavi; Massa, Solange; Rossi, Camilla Baj; Taurino, Irene; Shin, Su-Ryon; Calzone, Giovanni; Amaratunga, Givan Mark; Chambers, Douglas Leon; Jabari, Saman; Niu, Yuxi; Manoharan, Vijayan; Dokmeci, Mehmet Remzi; Carrara, Sandro; Demarchi, Danilo; Khademhosseini, Ali

2016-03-01

Google Glass is a recently designed wearable device capable of displaying information in a smartphone-like hands-free format by wireless communication. The Glass also provides convenient control over remote devices, primarily enabled by voice recognition commands. These unique features of the Google Glass make it useful for medical and biomedical applications where hands-free experiences are strongly preferred. Here, we report for the first time, an integral set of hardware, firmware, software, and Glassware that enabled wireless transmission of sensor data onto the Google Glass for on-demand data visualization and real-time analysis. Additionally, the platform allowed the user to control outputs entered through the Glass, therefore achieving bi-directional Glass-device interfacing. Using this versatile platform, we demonstrated its capability in monitoring physical and physiological parameters such as temperature, pH, and morphology of liver- and heart-on-chips. Furthermore, we showed the capability to remotely introduce pharmaceutical compounds into a microfluidic human primary liver bioreactor at desired time points while monitoring their effects through the Glass. We believe that such an innovative platform, along with its concept, has set up a premise in wearable monitoring and controlling technology for a wide variety of applications in biomedicine.

Google Glass-Directed Monitoring and Control of Microfluidic Biosensors and Actuators.

PubMed

Zhang, Yu Shrike; Busignani, Fabio; Ribas, João; Aleman, Julio; Rodrigues, Talles Nascimento; Shaegh, Seyed Ali Mousavi; Massa, Solange; Baj Rossi, Camilla; Taurino, Irene; Shin, Su-Ryon; Calzone, Giovanni; Amaratunga, Givan Mark; Chambers, Douglas Leon; Jabari, Saman; Niu, Yuxi; Manoharan, Vijayan; Dokmeci, Mehmet Remzi; Carrara, Sandro; Demarchi, Danilo; Khademhosseini, Ali

2016-03-01

Google Glass is a recently designed wearable device capable of displaying information in a smartphone-like hands-free format by wireless communication. The Glass also provides convenient control over remote devices, primarily enabled by voice recognition commands. These unique features of the Google Glass make it useful for medical and biomedical applications where hands-free experiences are strongly preferred. Here, we report for the first time, an integral set of hardware, firmware, software, and Glassware that enabled wireless transmission of sensor data onto the Google Glass for on-demand data visualization and real-time analysis. Additionally, the platform allowed the user to control outputs entered through the Glass, therefore achieving bi-directional Glass-device interfacing. Using this versatile platform, we demonstrated its capability in monitoring physical and physiological parameters such as temperature, pH, and morphology of liver- and heart-on-chips. Furthermore, we showed the capability to remotely introduce pharmaceutical compounds into a microfluidic human primary liver bioreactor at desired time points while monitoring their effects through the Glass. We believe that such an innovative platform, along with its concept, has set up a premise in wearable monitoring and controlling technology for a wide variety of applications in biomedicine.

The SPURS Data Management System: Real-time Situational Awareness at Sea

NASA Astrophysics Data System (ADS)

Bingham, F.; Chao, Y.; Li, P.; Vu, Q. A.

2012-12-01

SPURS (Salinity Processes in the Upper ocean Regional Study) is a field program in the North Atlantic to study the subtropical surface salinity maximum. It is a heterogeneous array consisting of research ships, profiling floats, surface drifters, gliders, microstructure profilers and moorings, as well as satellite observations and models. The SPURS Data Management System aims to capture the status of the observing system in near-real time and allow SPURS science team members to deploy observational assets "on the fly". At the heart of this is a visualization system that tracks the positions of the various assets and displays them in a an interface using Google Earth. The interface was used by program participants on land and at sea to coordinate the deployment of instrumentation. Before the Fall AGU, SPURS will have completed the first part of its mission with a 6-week cruise to the study area. This poster presents some of the highlights of the field campaign, and details the lessons learned in doing real-time oceanography on the high seas.

Two NextGen Air Safety Tools: An ADS-B Equipped UAV and a Wake Turbulence Estimator

NASA Astrophysics Data System (ADS)

Handley, Ward A.

Two air safety tools are developed in the context of the FAA's NextGen program. The first tool addresses the alarming increase in the frequency of near-collisions between manned and unmanned aircraft by equipping a common hobby class UAV with an ADS-B transponder that broadcasts its position, speed, heading and unique identification number to all local air traffic. The second tool estimates and outputs the location of dangerous wake vortex corridors in real time based on the ADS-B data collected and processed using a custom software package developed for this project. The TRansponder based Position Information System (TRAPIS) consists of data packet decoders, an aircraft database, Graphical User Interface (GUI) and the wake vortex extension application. Output from TRAPIS can be visualized in Google Earth and alleviates the problem of pilots being left to imagine where invisible wake vortex corridors are based solely on intuition or verbal warnings from ATC. The result of these two tools is the increased situational awareness, and hence safety, of human pilots in the National Airspace System (NAS).

A database for the monitoring of thermal anomalies over the Amazon forest and adjacent intertropical oceans

PubMed Central

Jiménez-Muñoz, Juan C.; Mattar, Cristian; Sobrino, José A.; Malhi, Yadvinder

2015-01-01

Advances in information technologies and accessibility to climate and satellite data in recent years have favored the development of web-based tools with user-friendly interfaces in order to facilitate the dissemination of geo/biophysical products. These products are useful for the analysis of the impact of global warming over different biomes. In particular, the study of the Amazon forest responses to drought have recently received attention by the scientific community due to the occurrence of two extreme droughts and sustained warming over the last decade. Thermal Amazoni@ is a web-based platform for the visualization and download of surface thermal anomalies products over the Amazon forest and adjacent intertropical oceans using Google Earth as a baseline graphical interface (http://ipl.uv.es/thamazon/web). This platform is currently operational at the servers of the University of Valencia (Spain), and it includes both satellite (MODIS) and climatic (ERA-Interim) datasets. Thermal Amazoni@ is composed of the viewer system and the web and ftp sites with ancillary information and access to product download. PMID:26029379

A database for the monitoring of thermal anomalies over the Amazon forest and adjacent intertropical oceans.

PubMed

Jiménez-Muñoz, Juan C; Mattar, Cristian; Sobrino, José A; Malhi, Yadvinder

2015-01-01

Advances in information technologies and accessibility to climate and satellite data in recent years have favored the development of web-based tools with user-friendly interfaces in order to facilitate the dissemination of geo/biophysical products. These products are useful for the analysis of the impact of global warming over different biomes. In particular, the study of the Amazon forest responses to drought have recently received attention by the scientific community due to the occurrence of two extreme droughts and sustained warming over the last decade. Thermal Amazoni@ is a web-based platform for the visualization and download of surface thermal anomalies products over the Amazon forest and adjacent intertropical oceans using Google Earth as a baseline graphical interface (http://ipl.uv.es/thamazon/web). This platform is currently operational at the servers of the University of Valencia (Spain), and it includes both satellite (MODIS) and climatic (ERA-Interim) datasets. Thermal Amazoni@ is composed of the viewer system and the web and ftp sites with ancillary information and access to product download.

Color and temperature of the crater lakes at Kelimutu volcano through time

NASA Astrophysics Data System (ADS)

Murphy, Sam; Wright, Robert; Rouwet, Dmitri

2018-01-01

We investigated the color and temperature of three volcanic crater lakes that co-exist at Kelimutu volcano (Indonesia) using 30 years of Landsat data. These satellite data were obtained through Google Earth Engine. Time series of surface reflectance (visible wavelengths) and brightness temperature above background (thermal infrared wavelengths) were calculated. Color was defined in the RGB (red-green-blue) and HSV (hue-saturation-value) color spaces, and we introduce a visualization concept called "hue stretch" to consistently represent hue through time. These parameters display long-term trends, seasonal cycles and short duration bursts of activity at the lakes. We demonstrate that the color of the lakes are related over a period of months to years and discovered a previously unreported but significant episode around 1997, which included large agglomerations of floating elemental sulfur. Globally speaking, these techniques could reveal trends at any of the 100 crater lakes on active volcanoes. Furthermore, they could apply to any target whose color changes through time (e.g., forests, crops, and non-volcanic water bodies). We have open-sourced the code necessary to perform these analyses.

red - an R package to facilitate species red list assessments according to the IUCN criteria

PubMed Central

2017-01-01

Abstract The International Union for the Conservation of Nature Red List is the most useful database of species that are at risk of extinction worldwide, as it relies on a number of objective criteria and is now widely adopted. The R package red – IUCN Redlisting Tools - performs a number of spatial analyses based on either observed occurrences or estimated ranges. Functions include calculating Extent of Occurrence (EOO), Area of Occupancy (AOO), mapping species ranges, species distribution modelling using climate and land cover and calculating the Red List Index for groups of species. The package allows the calculation of confidence limits for all measures. Spatial data of species occurrences, environmental or land cover variables can be either given by the user or automatically extracted from several online databases. It outputs geographical range, elevation and country values, maps in several formats and vectorial data for visualization in Google Earth. Several examples are shown demonstrating the usefulness of the different methods. The red package constitutes an open platform for further development of new tools to facilitate red list assessments. PMID:29104439

A virtual tour of geological heritage: Valourising geodiversity using Google Earth and QR code

NASA Astrophysics Data System (ADS)

Martínez-Graña, A. M.; Goy, J. L.; Cimarra, C. A.

2013-12-01

When making land-use plans, it is necessary to inventory and catalogue the geological heritage and geodiversity of a site to establish an apolitical conservation protection plan to meet the educational and social needs of society. New technologies make it possible to create virtual databases using virtual globes - e.g., Google Earth - and other personal-use geomatics applications (smartphones, tablets, PDAs) for accessing geological heritage information in “real time” for scientific, educational, and cultural purposes via a virtual geological itinerary. Seventeen mapped and georeferenced geosites have been created in Keyhole Markup Language for use in map layers used in geological itinerary stops for different applications. A virtual tour has been developed for Las Quilamas Natural Park, which is located in the Spanish Central System, using geological layers and topographic and digital terrain models that can be overlaid in a 3D model. The Google Earth application was used to import the geosite placemarks. For each geosite, a tab has been developed that shows a description of the geology with photographs and diagrams and that evaluates the scientific, educational, and tourism quality. Augmented reality allows the user to access these georeferenced thematic layers and overlay data, images, and graphics in real time on their mobile devices. These virtual tours can be incorporated into subject guides designed by public. Seven educational and interpretive panels describing some of the geosites were designed and tagged with a QR code that could be printed at each stop or in the printed itinerary. These QR codes can be scanned with the camera found on most mobile devices, and video virtual tours can be viewed on these devices. The virtual tour of the geological heritage can be used to show tourists the geological history of the Las Quilamas Natural Park using new geomatics technologies (virtual globes, augmented reality, and QR codes).

Google Earth Grand Tour Themes

NASA Astrophysics Data System (ADS)

De Paor, D. G.; Whitmeyer, S. J.; Bentley, C.; Dordevic, M. M.

2014-12-01

As part of an NSF TUES Type 3 project entitled "Google Earth for Onsite and Distance Education (GEODE)," we are assembling a "Grand Tour" of locations on Earth and other terrestrial bodies that every geoscience student should know about and visit at least in virtual reality. Based on feedback from colleagues at previous meetings, we have identified nine Grand Tour themes: "Plates and Plumes," "Rocks and Regions," "Geology Through Time," "The Mapping Challenge*," "U.S. National Parks*," "The Magical Mystery Tour*," "Resources and Hazards," "Planets and Moons," and "Top of the Pops." Themes marked with an asterisk are most developed at this stage and will be demonstrated in real time. The Mapping Challenge invites students to trace geological contacts, measure bedding strike and dip and the plunge, trend, and facing of a fold. There is an advanced tool for modeling periclinal folds. The challenge is presented in a game-like format with an emphasis on puzzle-solving that will appeal to students regardless of gender. For the tour of U.S. national parks, we divided the most geologically important parks into four groups—Western Pacific, West Coast, Rockies, and East Coast. We are combining our own team's GigaPan imagery with imagery already available on the Internet. There is a great deal of imagery just waiting to be annotated for geological education purposes. The Magical Mystery Tour takes students to Google Streetview locations selected by instructors. Students are presented with questions or tasks and are given automatic feedback. Other themes are under development. Within each theme, we are crowd-sourcing contributions from colleagues and inviting colleagues to vote for or against proposed locations and student interactions. The GEODE team includes the authors and: Heather Almquist, Stephen Burgin, Cinzia Cervato, Gene Cooper, Paul Karabinos, Terry Pavlis, Jen Piatek, Bill Richards, Jeff Ryan, Ron Schott, Kristen St. John, and Barb Tewksbury.

Dagik: A Quick Look System of the Geospace Data in KML format

NASA Astrophysics Data System (ADS)

Yoshida, D.; Saito, A.

2007-12-01

Dagik (Daily Geospace data in KML) is a quick look plot sharing system using Google Earth as a data browser. It provides daily data lists that contain network links to the KML/KMZ files of various geospace data. KML is a markup language to display data on Google Earth, and KMZ is a compressed file of KML. Users can browse the KML/KMZ files with the following procedures: 1) download "dagik.kml" from Dagik homepage (http://www- step.kugi.kyoto-u.ac.jp/dagik/), and open it with Google Earth, 2) select date, 3) select data type to browse. Dagik is a collection of network links to KML/KMZ files. The daily Dagik files are available since 1957, though they contain only the geomagnetic index data in the early periods. There are three activities of Dagik. The first one is the generation of the daily data lists, the second is to provide several useful tools, such as observatory lists, and the third is to assist researchers to make KML/KMZ data plots. To make the plot browsing easy, there are three rules for Dagik plot format: 1) one file contains one UT day data, 2) use common plot panel size, 3) share the data list. There are three steps to join Dagik as a plot provider: 1) make KML/KMZ files of the data, 2) put the KML/KMZ files on Web, 3) notice Dagik group the URL address and description of the files. The KML/KMZ files will be included in Dagik data list. As of September 2007, quick looks of several geosphace data, such as GPS total electron content data, ionosonde data, magnetometer data, FUV imaging data by a satellite, ground-based airglow data, and satellite footprint data, are available. The system of Dagik is introduced in the presentation. u.ac.jp/dagik/

Next Generation Landsat Products Delivered Using Virtual Globes and OGC Standard Services

NASA Astrophysics Data System (ADS)

Neiers, M.; Dwyer, J.; Neiers, S.

2008-12-01

The Landsat Data Continuity Mission (LDCM) is the next in the series of Landsat satellite missions and is tasked with the objective of delivering data acquired by the Operational Land Imager (OLI). The OLI instrument will provide data continuity to over 30 years of global multispectral data collected by the Landsat series of satellites. The U.S. Geological Survey Earth Resources Observation and Science (USGS EROS) Center has responsibility for the development and operation of the LDCM ground system. One of the mission objectives of the LDCM is to distribute OLI data products electronically over the Internet to the general public on a nondiscriminatory basis and at no cost. To ensure the user community and general public can easily access LDCM data from multiple clients, the User Portal Element (UPE) of the LDCM ground system will use OGC standards and services such as Keyhole Markup Language (KML), Web Map Service (WMS), Web Coverage Service (WCS), and Geographic encoding of Really Simple Syndication (GeoRSS) feeds for both access to and delivery of LDCM products. The USGS has developed and tested the capabilities of several successful UPE prototypes for delivery of Landsat metadata, full resolution browse, and orthorectified (L1T) products from clients such as Google Earth, Google Maps, ESRI ArcGIS Explorer, and Microsoft's Virtual Earth. Prototyping efforts included the following services: using virtual globes to search the historical Landsat archive by dynamic generation of KML; notification of and access to new Landsat acquisitions and L1T downloads from GeoRSS feeds; Google indexing of KML files containing links to full resolution browse and data downloads; WMS delivery of reduced resolution browse, full resolution browse, and cloud mask overlays; and custom data downloads using WCS clients. These various prototypes will be demonstrated and LDCM service implementation plans will be discussed during this session.

GeoSearch: a new virtual globe application for the submission, storage, and sharing of point-based ecological data

NASA Astrophysics Data System (ADS)

Cardille, J. A.; Gonzales, R.; Parrott, L.; Bai, J.

2009-12-01

How should researchers store and share data? For most of history, scientists with results and data to share have been mostly limited to books and journal articles. In recent decades, the advent of personal computers and shared data formats has made it feasible, though often cumbersome, to transfer data between individuals or among small groups. Meanwhile, the use of automatic samplers, simulation models, and other data-production techniques has increased greatly. The result is that there is more and more data to store, and a greater expectation that they will be available at the click of a button. In 10 or 20 years, will we still send emails to each other to learn about what data exist? The development and widespread familiarity with virtual globes like Google Earth and NASA WorldWind has created the potential, in just the last few years, to revolutionize the way we share data, search for and search through data, and understand the relationship between individual projects in research networks, where sharing and dissemination of knowledge is encouraged. For the last two years, we have been building the GeoSearch application, a cutting-edge online resource for the storage, sharing, search, and retrieval of data produced by research networks. Linking NASA’s WorldWind globe platform, the data browsing toolkit prefuse, and SQL databases, GeoSearch’s version 1.0 enables flexible searches and novel geovisualizations of large amounts of related scientific data. These data may be submitted to the database by individual researchers and processed by GeoSearch’s data parser. Ultimately, data from research groups gathered in a research network would be shared among users via the platform. Access is not limited to the scientists themselves; administrators can determine which data can be presented publicly and which require group membership. Under the auspices of the Canada’s Sustainable Forestry Management Network of Excellence, we have created a moderate-sized database of ecological measurements in forests; we expect to extend the approach to a Quebec lake research network encompassing decades of lake measurements. In this session, we will describe and present four related components of the new system: GeoSearch’s globe-based searching and display of scientific data; prefuse-based visualization of social connections among members of a scientific research network; geolocation of research projects using Google Spreadsheets, KML, and Google Earth/Maps; and collaborative construction of a geolocated database of research articles. Each component is designed to have applications for scientists themselves as well as the general public. Although each implementation is in its infancy, we believe they could be useful to other researcher networks.

WebViz:A Web-based Collaborative Interactive Visualization System for large-Scale Data Sets

NASA Astrophysics Data System (ADS)

Yuen, D. A.; McArthur, E.; Weiss, R. M.; Zhou, J.; Yao, B.

2010-12-01

WebViz is a web-based application designed to conduct collaborative, interactive visualizations of large data sets for multiple users, allowing researchers situated all over the world to utilize the visualization services offered by the University of Minnesota’s Laboratory for Computational Sciences and Engineering (LCSE). This ongoing project has been built upon over the last 3 1/2 years .The motivation behind WebViz lies primarily with the need to parse through an increasing amount of data produced by the scientific community as a result of larger and faster multicore and massively parallel computers coming to the market, including the use of general purpose GPU computing. WebViz allows these large data sets to be visualized online by anyone with an account. The application allows users to save time and resources by visualizing data ‘on the fly’, wherever he or she may be located. By leveraging AJAX via the Google Web Toolkit (http://code.google.com/webtoolkit/), we are able to provide users with a remote, web portal to LCSE's (http://www.lcse.umn.edu) large-scale interactive visualization system already in place at the University of Minnesota. LCSE’s custom hierarchical volume rendering software provides high resolution visualizations on the order of 15 million pixels and has been employed for visualizing data primarily from simulations in astrophysics to geophysical fluid dynamics . In the current version of WebViz, we have implemented a highly extensible back-end framework built around HTTP "server push" technology. The web application is accessible via a variety of devices including netbooks, iPhones, and other web and javascript-enabled cell phones. Features in the current version include the ability for users to (1) securely login (2) launch multiple visualizations (3) conduct collaborative visualization sessions (4) delegate control aspects of a visualization to others and (5) engage in collaborative chats with other users within the user interface of the web application. These features are all in addition to a full range of essential visualization functions including 3-D camera and object orientation, position manipulation, time-stepping control, and custom color/alpha mapping.

3D Immersive Visualization with Astrophysical Data

NASA Astrophysics Data System (ADS)

Kent, Brian R.

2017-01-01

We present the refinement of a new 3D immersion technique for astrophysical data visualization.Methodology to create 360 degree spherical panoramas is reviewed. The 3D software package Blender coupled with Python and the Google Spatial Media module are used together to create the final data products. Data can be viewed interactively with a mobile phone or tablet or in a web browser. The technique can apply to different kinds of astronomical data including 3D stellar and galaxy catalogs, images, and planetary maps.

Spherical Panoramas for Astrophysical Data Visualization

NASA Astrophysics Data System (ADS)

Kent, Brian R.

2017-05-01

Data immersion has advantages in astrophysical visualization. Complex multi-dimensional data and phase spaces can be explored in a seamless and interactive viewing environment. Putting the user in the data is a first step toward immersive data analysis. We present a technique for creating 360° spherical panoramas with astrophysical data. The three-dimensional software package Blender and the Google Spatial Media module are used together to immerse users in data exploration. Several examples employing these methods exhibit how the technique works using different types of astronomical data.

Injury surveillance in low-resource settings using Geospatial and Social Web technologies

PubMed Central

2010-01-01

Background Extensive public health gains have benefited high-income countries in recent decades, however, citizens of low and middle-income countries (LMIC) have largely not enjoyed the same advancements. This is in part due to the fact that public health data - the foundation for public health advances - are rarely collected in many LMIC. Injury data are particularly scarce in many low-resource settings, despite the huge associated burden of morbidity and mortality. Advances in freely-accessible and easy-to-use information and communication (ICT) technology may provide the impetus for increased public health data collection in settings with limited financial and personnel resources. Methods and Results A pilot study was conducted at a hospital in Cape Town, South Africa to assess the utility and feasibility of using free (non-licensed), and easy-to-use Social Web and GeoWeb tools for injury surveillance in low-resource settings. Data entry, geocoding, data exploration, and data visualization were successfully conducted using these technologies, including Google Spreadsheet, Mapalist, BatchGeocode, and Google Earth. Conclusion This study examined the potential for Social Web and GeoWeb technologies to contribute to public health data collection and analysis in low-resource settings through an injury surveillance pilot study conducted in Cape Town, South Africa. The success of this study illustrates the great potential for these technologies to be leveraged for public health surveillance in resource-constrained environments, given their ease-of-use and low-cost, and the sharing and collaboration capabilities they afford. The possibilities and potential limitations of these technologies are discussed in relation to the study, and to the field of public health in general. PMID:20497570

Free Global Dsm Assessment on Large Scale Areas Exploiting the Potentialities of the Innovative Google Earth Engine Platform

NASA Astrophysics Data System (ADS)

Nascetti, A.; Di Rita, M.; Ravanelli, R.; Amicuzi, M.; Esposito, S.; Crespi, M.

2017-05-01

The high-performance cloud-computing platform Google Earth Engine has been developed for global-scale analysis based on the Earth observation data. In particular, in this work, the geometric accuracy of the two most used nearly-global free DSMs (SRTM and ASTER) has been evaluated on the territories of four American States (Colorado, Michigan, Nevada, Utah) and one Italian Region (Trentino Alto- Adige, Northern Italy) exploiting the potentiality of this platform. These are large areas characterized by different terrain morphology, land covers and slopes. The assessment has been performed using two different reference DSMs: the USGS National Elevation Dataset (NED) and a LiDAR acquisition. The DSMs accuracy has been evaluated through computation of standard statistic parameters, both at global scale (considering the whole State/Region) and in function of the terrain morphology using several slope classes. The geometric accuracy in terms of Standard deviation and NMAD, for SRTM range from 2-3 meters in the first slope class to about 45 meters in the last one, whereas for ASTER, the values range from 5-6 to 30 meters. In general, the performed analysis shows a better accuracy for the SRTM in the flat areas whereas the ASTER GDEM is more reliable in the steep areas, where the slopes increase. These preliminary results highlight the GEE potentialities to perform DSM assessment on a global scale.

Developing a Global Database of Historic Flood Events to Support Machine Learning Flood Prediction in Google Earth Engine

NASA Astrophysics Data System (ADS)

Tellman, B.; Sullivan, J.; Kettner, A.; Brakenridge, G. R.; Slayback, D. A.; Kuhn, C.; Doyle, C.

2016-12-01

There is an increasing need to understand flood vulnerability as the societal and economic effects of flooding increases. Risk models from insurance companies and flood models from hydrologists must be calibrated based on flood observations in order to make future predictions that can improve planning and help societies reduce future disasters. Specifically, to improve these models both traditional methods of flood prediction from physically based models as well as data-driven techniques, such as machine learning, require spatial flood observation to validate model outputs and quantify uncertainty. A key dataset that is missing for flood model validation is a global historical geo-database of flood event extents. Currently, the most advanced database of historical flood extent is hosted and maintained at the Dartmouth Flood Observatory (DFO) that has catalogued 4320 floods (1985-2015) but has only mapped 5% of these floods. We are addressing this data gap by mapping the inventory of floods in the DFO database to create a first-of- its-kind, comprehensive, global and historical geospatial database of flood events. To do so, we combine water detection algorithms on MODIS and Landsat 5,7 and 8 imagery in Google Earth Engine to map discrete flood events. The created database will be available in the Earth Engine Catalogue for download by country, region, or time period. This dataset can be leveraged for new data-driven hydrologic modeling using machine learning algorithms in Earth Engine's highly parallelized computing environment, and we will show examples for New York and Senegal.

High Resolution Land Use Land Cover Classification using Landsat Earth Observation Data for the Continental Africa

NASA Astrophysics Data System (ADS)

Midekisa, A.; Bennet, A.; Gething, P. W.; Holl, F.; Andrade-Pacheco, R.; Savory, D. J.; Hugh, S. J.

2016-12-01

Spatially detailed and temporally dynamic land use land cover data is necessary to monitor the state of the land surface for various applications. Yet, such data at a continental to global scale is lacking. Here, we developed high resolution (30 meter) annual land use land cover layers for the continental Africa using Google Earth Engine. To capture ground truth training data, high resolution satellite imageries were visually inspected and used to identify 7, 212 sample Landsat pixels that were comprised entirely of one of seven land use land cover classes (water, man-made impervious surface, high biomass, low biomass, rock, sand and bare soil). For model validation purposes, 80% of points from each class were used as training data, with 20% withheld as a validation dataset. Cloud free Landsat 7 annual composites for 2000 to 2015 were generated and spectral bands from the Landsat images were then extracted for each of the training and validation sample points. In addition to the Landsat spectral bands, spectral indices such as normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used as covariates in the model. Additionally, calibrated night time light imageries from the National Oceanic and Atmospheric Administration (NOAA) were included as a covariate. A decision tree classification algorithm was applied to predict the 7 land cover classes for the periods 2000 to 2015 using the training dataset. Using the validation dataset, classification accuracy including omission error and commission error were computed for each land cover class. Model results showed that overall accuracy of classification was high (88%). This high resolution land cover product developed for the continental Africa will be available for public use and can potentially enhance the ability of monitoring and studying the state of the Earth's surface.

Open Land-Use Map: A Regional Land-Use Mapping Strategy for Incorporating OpenStreetMap with Earth Observations

NASA Astrophysics Data System (ADS)

Yang, D.; Fu, C. S.; Binford, M. W.

2017-12-01

The southeastern United States has high landscape heterogeneity, withheavily managed forestlands, highly developed agriculture lands, and multiple metropolitan areas. Human activities are transforming and altering land patterns and structures in both negative and positive manners. A land-use map for at the greater scale is a heavy computation task but is critical to most landowners, researchers, and decision makers, enabling them to make informed decisions for varying objectives. There are two major difficulties in generating the classification maps at the regional scale: the necessity of large training point sets and the expensive computation cost-in terms of both money and time-in classifier modeling. Volunteered Geographic Information (VGI) opens a new era in mapping and visualizing our world, where the platform is open for collecting valuable georeferenced information by volunteer citizens, and the data is freely available to the public. As one of the most well-known VGI initiatives, OpenStreetMap (OSM) contributes not only road network distribution, but also the potential for using this data to justify land cover and land use classifications. Google Earth Engine (GEE) is a platform designed for cloud-based mapping with a robust and fast computing power. Most large scale and national mapping approaches confuse "land cover" and "land-use", or build up the land-use database based on modeled land cover datasets. Unlike most other large-scale approaches, we distinguish and differentiate land-use from land cover. By focusing our prime objective of mapping land-use and management practices, a robust regional land-use mapping approach is developed by incorporating the OpenstreepMap dataset into Earth observation remote sensing imageries instead of the often-used land cover base maps.

AFRC2016-0054-528

NASA Image and Video Library

2016-02-27

Sam Choi and Naiara Pinto observe Google Earth overlaid with in almost real time what the synthetic aperture radar is mapping from the C-20A aircraft. Researchers were in the sky and on the ground to take measurements of plant mass, distribution of trees, shrubs and ground cover and the diversity of plants and how much carbon is absorbed by them.

Smartphones and Time Zones

ERIC Educational Resources Information Center

Baird, William; Secrest, Jeffery; Padgett, Clifford; Johnson, Wayne; Hagrelius, Claire

2016-01-01

Using the Sun to tell time is an ancient idea, but we can take advantage of modern technology to bring it into the 21st century for students in astronomy, physics, or physical science classes. We have employed smartphones, Google Earth, and 3D printing to find the moment of local noon at two widely separated locations. By reviewing GPS…

Using Google Earth to Teach the Magnitude of Deep Time

ERIC Educational Resources Information Center

Parker, Joel D.

2011-01-01

Most timeline analogies of geologic and evolutionary time are fundamentally flawed. They trade off the problem of grasping very long times for the problem of grasping very short distances. The result is an understanding of relative time with little comprehension of absolute time. Earlier work has shown that the distances most easily understood by…

Content and Language Integrated Learning through an Online Game in Primary School: A Case Study

ERIC Educational Resources Information Center

Dourda, Kyriaki; Bratitsis, Tharrenos; Griva, Eleni; Papadopoulou, Penelope

2014-01-01

In this paper an educational design proposal is presented which combines two well established teaching approaches, that of Game-based Learning (GBL) and Content and Language Integrated Learning (CLIL). The context of the proposal was the design of an educational geography computer game, utilizing QR Codes and Google Earth for teaching English…

Using Google Earth and Satellite Imagery to Foster Place-Based Teaching in an Introductory Physical Geology Course

ERIC Educational Resources Information Center

Monet, Julie; Greene, Todd

2012-01-01

Students in an introductory physical geology course often have difficulty making connections between basic course topics and assembling key concepts (beyond textbook examples) to interpret how geologic processes shape the characteristics of the local and regional natural environment. As an approach to address these issues, we designed and…

Applying Modern Stage Theory to Mauritania: A Prescription to Encourage Entrepreneurship

DTIC Science & Technology

2014-12-01

entrepreneurship, stage theory, development, Africa , factor-driven, trade freedom, business freedom 15. NUMBER OF PAGES 77 16. PRICE CODE 17...SOUTH ASIA, SUB-SAHARAN AFRICA ) from the NAVAL POSTGRADUATE SCHOOL December 2014 Author: Jennifer M. Warren Approved by: Robert E...Notes, Coins) .......................................................................... 4  Figure 2.  Satellite map of West Africa (from Google Earth

Creating global comparative analyses of tectonic rifts, monogenetic volcanism and inverted relief

NASA Astrophysics Data System (ADS)

van Wyk de Vries, Benjamin

2016-04-01

I have been all around the world, and to other planets and have travelled from the present to the Archaean and back to seek out the most significant tectonic rifts, monogenetic volcanoes and examples of inverted relief. I have done this to provide a broad foundation of the comparative analysis for the Chaîne des Puys - Limagne fault nomination to UNESCO world Heritage. This would have been an impossible task, if not for the cooperation of the scientific community and for Google Earth, Google Maps and academic search engines. In preparing global comparisons of geological features, these quite recently developed tools provide a powerful way to find and describe geological features. The ability to do scientific crowd sourcing, rapidly discussing with colleagues about features, allows large numbers of areas to be checked and the open GIS tools (such as Google Earth) allow a standardised description. Search engines also allow the literature on areas to be checked and compared. I will present a comparative study of rifts of the world, monogenetic volcanic field and inverted relief, integrated to analyse the full geological system represented by the Chaîne des Puys - Limagne fault. The analysis confirms that the site is an exceptional example of the first steps of continental drift in a mountain rift setting, and that this is necessarily seen through the combined landscape of tectonic, volcanic and geomorphic features. The analysis goes further to deepen the understanding of geological systems and stresses the need for more study on geological heritage using such a global and broad systems approach.

In the eye of the beholder: A simulator study of the impact of Google Glass on driving performance.

PubMed

Young, Kristie L; Stephens, Amanda N; Stephan, Karen L; Stuart, Geoffrey W

2016-01-01

This study examined whether, and to what extent, driving is affected by reading text on Google Glass. Reading text requires a high level of visual resources and can interfere with safe driving. However, it is currently unclear if the impact of reading text on a head-mounted display, such as Google Glass (Glass), will differ from that found with more traditional head-down electronic devices, such as a dash-mounted smartphone. A total of 20 drivers (22-48 years) completed the Lane Change Test while driving undistracted and while reading text on Glass and on a smartphone. Measures of lateral vehicle control and event detection were examined along with subjective workload and secondary task performance. Results revealed that drivers' lane keeping ability was significantly impaired by reading text on both Glass and the smartphone. When using Glass, drivers also failed to detect a greater number of lane change signs compared to when using the phone or driving undistracted. In terms of subjective workload, drivers rated reading on Glass as subjectively easier than on the smartphone, which may possibly encourage greater use of this device while driving. Overall, the results suggest that, despite Glass allowing drivers to better maintain their visual attention on the forward scene, drivers are still not able to effectively divide their cognitive attention across the Glass display and the road environment, resulting in impaired driving performance. Copyright © 2015 Elsevier Ltd. All rights reserved.

New developments in super-resolution for GaoFen-4

NASA Astrophysics Data System (ADS)

Li, Feng; Fu, Jie; Xin, Lei; Liu, Yuhong; Liu, Zhijia

2017-10-01

In this paper, the application of super resolution (SR, restoring a high spatial resolution image from a series of low resolution images of the same scene) techniques to GaoFen(GF)-4, which is the most advanced geostationaryorbit earth observing satellite in China, remote sensing images is investigated and tested. SR has been a hot research area for decades, but one of the barriers of applying SR in remote sensing community is the time slot between those low resolution (LR) images acquisition. In general, the longer the time slot, the less reliable the reconstruction. GF-4 has the unique advantage of capturing a sequence of LR of the same region in minutes, i.e. working as a staring camera from the point view of SR. This is the first experiment of applying super resolution to a sequence of low resolution images captured by GF-4 within a short time period. In this paper, we use Maximum a Posteriori (MAP) to solve the ill-conditioned problem of SR. Both the wavelet transform and the curvelet transform are used to setup a sparse prior for remote sensing images. By combining several images of both the BeiJing and DunHuang regions captured by GF-4 our method can improve spatial resolution both visually and numerically. Experimental tests show that lots of detail cannot be observed in the captured LR images, but can be seen in the super resolved high resolution (HR) images. To help the evaluation, Google Earth image can also be referenced. Moreover, our experimental tests also show that the higher the temporal resolution, the better the HR images can be resolved. The study illustrates that the application for SR to geostationary-orbit based earth observation data is very feasible and worthwhile, and it holds the potential application for all other geostationary-orbit based earth observing systems.

Geonucleus, the freeware application for managing geological mapping data in GIS

NASA Astrophysics Data System (ADS)

Albert, Gáspár

2016-04-01

Geological mapping is the most traditional way of collecting information from the deposits and rocks. The traditional technique of the documentation was refined by generations of geologists. These traditions were implemented into Geonucleus to create a tool for precise data-recording after fieldwork, but giving the freedom of pondering the details of the observation as well. In 2012 a general xml-based data structure was worked out for storing field observations for the Geological Institute of Hungary (Albert et al. 2012). This structure was implemented into the desktop version of Geonucleus, which creates a database of the recorded data on the client computer. The application saves the complete database in one file, which can be loaded into a GIS. The observations can be saved in simple text format as well, but primarily the kml (Keyhole Markup Languege) is supported. This way, the observations are visualized in comprehensible forms (e.g. on a 3D surface model with satellite photos in Google Earth). If the kml is directly visualized in Google Earth, an info-bubble will appear via clicking on a pinpoint. It displays all the metadata (e.g. index, coordinates, date, logger name, etc.), the descriptions and the photos of the observed site. If a more general GIS application is the aim (e.g. Global Mapper or QGIS), the file can be saved in a different format, but still in a kml-structure. The simple text format is recommended if the observations are to be imported in a user-defined relational database system (RDB). Report text-type is also available if a detailed description of one or more observed site is needed. Importing waypoint gpx-files can quicken the logging. The code was written in VisualBasic.Net. The app is freely accessible from the geonucleus.elte.hu site and it can be installed on any system, which has the .Net framework 4.0 or higher. The software is bilingual (English and Hungarian), and the app is designed for general geological mapping purposes (e.g. quick logging of field trips). The layout of the GUI has three components: 1) metadata area, 2) general description area with unlimited storing capacity, 3) switchable panels for observations, measurements, photos and notes. The latter includes panels for stratigraphy, structures, fossils, samples, photo uploads and general notes. Details like the sequence and contact type of layers, the parameters of structures and slickensides, name and condition of fossils and purpose of sampling are also available to log (but not compulsorily). It is also a tool for teaching geological mapping, since the available parameters - listed in the app - draws attention to the details, which are to be observed on the field. Reference: Albert G, Csillag G, Fodor L, Zentai L. 2012: Visualisation of Geological Observations on Web 2.0 Based Maps, in: Zentai, L. and Reyes-Nunez, J (eds.): Maps for the Future - Children, Education and Internet, Series: Lecture Notes in Geoinformation and Cartography, Tentative volume 5 - Springer, pp. 165-178.

Reusable Client-Side JavaScript Modules for Immersive Web-Based Real-Time Collaborative Neuroimage Visualization.

PubMed

Bernal-Rusiel, Jorge L; Rannou, Nicolas; Gollub, Randy L; Pieper, Steve; Murphy, Shawn; Robertson, Richard; Grant, Patricia E; Pienaar, Rudolph

2017-01-01

In this paper we present a web-based software solution to the problem of implementing real-time collaborative neuroimage visualization. In both clinical and research settings, simple and powerful access to imaging technologies across multiple devices is becoming increasingly useful. Prior technical solutions have used a server-side rendering and push-to-client model wherein only the server has the full image dataset. We propose a rich client solution in which each client has all the data and uses the Google Drive Realtime API for state synchronization. We have developed a small set of reusable client-side object-oriented JavaScript modules that make use of the XTK toolkit, a popular open-source JavaScript library also developed by our team, for the in-browser rendering and visualization of brain image volumes. Efficient realtime communication among the remote instances is achieved by using just a small JSON object, comprising a representation of the XTK image renderers' state, as the Google Drive Realtime collaborative data model. The developed open-source JavaScript modules have already been instantiated in a web-app called MedView , a distributed collaborative neuroimage visualization application that is delivered to the users over the web without requiring the installation of any extra software or browser plugin. This responsive application allows multiple physically distant physicians or researchers to cooperate in real time to reach a diagnosis or scientific conclusion. It also serves as a proof of concept for the capabilities of the presented technological solution.

NASA GIBS Use in Live Planetarium Shows

NASA Astrophysics Data System (ADS)

Emmart, C. B.

2015-12-01

The American Museum of Natural History's Hayden Planetarium was rebuilt in year 2000 as an immersive theater for scientific data visualization to show the universe in context to our planet. Specific astrophysical movie productions provide the main daily programming, but interactive control software, developed at AMNH allows immersive presentation within a data aggregation of astronomical catalogs called the Digital Universe 3D Atlas. Since 2006, WMS globe browsing capabilities have been built into a software development collaboration with Sweden's Linkoping University (LiU). The resulting Uniview software, now a product of the company SCISS, is operated by about fifty planetariums around that world with ability to network amongst the sites for global presentations. Public presentation of NASA GIBS has allowed authoritative narratives to be presented within the range of data available in context to other sources such as Science on a Sphere, NASA Earth Observatory and Google Earth KML resources. Specifically, the NOAA supported World Views Network conducted a series of presentations across the US that focused on local ecological issues that could then be expanded in the course of presentation to national and global scales of examination. NASA support of for GIBS resources in an easy access multi scale streaming format like WMS has tremendously enabled particularly facile presentations of global monitoring like never before. Global networking of theaters for distributed presentations broadens out the potential for impact of this medium. Archiving and refinement of these presentations has already begun to inform new types of documentary productions that examine pertinent, global interdependency topics.

Visualization of Coastal Data Through KML

NASA Astrophysics Data System (ADS)

Damsma, T.; Baart, F.; de Boer, G.; van Koningsveld, M.; Bruens, A.

2009-12-01

As a country that lies mostly below sea level, the Netherlands has a history of coastal engineering, and is world renowned for its leading role in Integrated Coastal Zone Management (ICZM). Within the framework of Building with Nature (a Dutch ICZM research program) an OPeNDAP server is used to host several datasets of the Dutch coast. Among these sets are bathymetric data, cross-shore profiles, water level time series of which some date back to the eighteenth century. The challenge with hosting this amount of data is more in dissemination and accessibility rather than a technical one (tracing, accessing, gathering, unifying and storing). With so many data in different sets, how can one easily know when and where data is available, and of what quality it is? Recent work using Google Earth as a visual front-end for this database has proven very encouraging. Taking full advantage of the four dimensional (3D+time) visualization capabilities allows researchers, consultants and the general public to view, access and interact with the data. Within MATLAB a set of generic tools are developed for easy creation of among others:

• A high resolution, time animated, historic bathymetry of the entire Dutch coast.
• 3D curvilinear computation grids.
• A 3D contour plot of the Westerschelde Estuary.
• Time animated wind and water flow fields, both with traditional quiver diagrams and arrows that move with the flow field.
• Various overviews of markers containing direct web links to data and metadata on OPeNDAP server. Wind field (arrows) and water level elevation for model calculations of Katrina (animated over 14 days) Coastal cross sections (with exaggerated hight) and 2D positions of high and low water lines (animated over 40 years)

• Gravity as a Strong Prior: Implications for Perception and Action.

  PubMed

  Jörges, Björn; López-Moliner, Joan

  2017-01-01

  In the future, humans are likely to be exposed to environments with altered gravity conditions, be it only visually (Virtual and Augmented Reality), or visually and bodily (space travel). As visually and bodily perceived gravity as well as an interiorized representation of earth gravity are involved in a series of tasks, such as catching, grasping, body orientation estimation and spatial inferences, humans will need to adapt to these new gravity conditions. Performance under earth gravity discrepant conditions has been shown to be relatively poor, and few studies conducted in gravity adaptation are rather discouraging. Especially in VR on earth, conflicts between bodily and visual gravity cues seem to make a full adaptation to visually perceived earth-discrepant gravities nearly impossible, and even in space, when visual and bodily cues are congruent, adaptation is extremely slow. We invoke a Bayesian framework for gravity related perceptual processes, in which earth gravity holds the status of a so called "strong prior". As other strong priors, the gravity prior has developed through years and years of experience in an earth gravity environment. For this reason, the reliability of this representation is extremely high and overrules any sensory information to its contrary. While also other factors such as the multisensory nature of gravity perception need to be taken into account, we present the strong prior account as a unifying explanation for empirical results in gravity perception and adaptation to earth-discrepant gravities.

• Tracking changes of river morphology in Ayeyarwady River in Myanmar using earth observations and surface water mapping tool

  NASA Astrophysics Data System (ADS)

  Piman, T.; Schellekens, J.; Haag, A.; Donchyts, G.; Apirumanekul, C.; Hlaing, K. T.

  2017-12-01

  River morphology changes is one of the key issues in Ayeyarwady River in Myanmar which cause impacts on navigation, riverine habitats, agriculture lands, communities and livelihoods near the bank of the river. This study is aimed to track the changes in river morphology in the middle reach of Ayeyarwady River over last 30 years from 1984-2014 to improve understanding of riverbank dynamic, erosion and deposition procress. Earth observations including LandSat-7, LandSat-8, Digital Elevation Model from SRTM Plus and, ASTER-2 GoogleMap and Open Street Map were obtained for the study. GIS and remote sensing tools were used to analyze changes in river morphology while surface water mapping tool was applied to determine how the dynamic behaviour of the surface river and effect of river morphology changes. The tool consists of two components: (1) a Google Earth Engine (GEE) javascript or python application that performs image analysis and (2) a user-friendly site/app using Google's appspot.com that exposes the application to the users. The results of this study shown that the fluvial morphology in the middle reach of Ayeyarwady River is continuously changing under the influence of high water flows in particularly from extreme flood events and land use change from mining and deforestation. It was observed that some meandering sections of the riverbank were straightened, which results in the movement of sediment downstream and created new sections of meandering riverbank. Several large islands have formed due to the stabilization by vegetation and is enforced by sedimentation while many small bars were formed and migrated dynamically due to changes in water levels and flow velocity in the wet and dry seasons. The main channel was changed to secondary channel in some sections of the river. This results a constant shift of the navigation route. We also found that some villages were facing riverbank erosion which can force villagers to relocate. The study results demonstrated that the products from earth observations and the surface water mapping tool could detect dynamic changes of river morphology in the Ayeyarwady River. This information is useful to support navigation and riverbank protection planning and formulating mitigation measures for local communities that are affecting by riverbank erosion.

• Addressing key concepts in physical geography through interactive learning activities in an online geo-ICT environment

  NASA Astrophysics Data System (ADS)

  Verstraeten, Gert; Steegen, An; Martens, Lotte

  2016-04-01

  The increasing number of geospatial datasets and free online geo-ICT tools offers new opportunities for education in Earth Sciences. Geospatial technology indeed provides an environment through which interactive learning can be introduced in Earth Sciences curricula. However, the effectiveness of such e-learning approaches in terms of learning outcomes has rarely been addressed. Here, we present our experience with the implementation of digital interactive learning activities within an introductory Physical Geography course attended by 90 undergraduate students in Geography, Geology, Biology and Archaeology. Two traditional lectures were replaced by interactive sessions (each 2 h) in a flexible classroom where students had to work both in team and individually in order to explore some key concepts through the integrated use of geospatial data within Google EarthTM. A first interactive lesson dealt with the classification of river systems and aimed to examine the conditions under which rivers tend to meander or to develop a braided pattern. Students were required to collect properties of rivers (river channel pattern, channel slope, climate, discharge, lithology, vegetation, etc). All these data are available on a global scale and have been added as separate map layers in Google EarthTM. Each student collected data for at least two rivers and added this information to a Google Drive Spreadsheet accessible to the entire group. This resulted in a database of more than one hundred rivers spread over various environments worldwide. In a second phase small groups of students discussed the potential relationships between river channel pattern and its controlling factors. Afterwards, the findings of each discussion group were presented to the entire audience. The same set-up was followed in a second interactive session to explore spatial variations in ecosystem properties such as net primary production and soil carbon content. The qualitative evaluation of both interactive sessions showed that the majority of students perceive these as very useful and inspiring. Students were more capable in exploring the spatial linkages between various environmental variables and processes compared to traditional lectures. Furthermore, the format of the sessions offered a forum in which undergraduate students from a variety of disciplines discussed the learning content in mixed groups. The success of interactive learning activities, however, strongly depends on the quality of the educational infrastructure (flexible spaces, wireless connections with sufficient broadband capacity).

• Geospatial Services in Special Libraries: A Needs Assessment Perspective

  ERIC Educational Resources Information Center

  Barnes, Ilana

  2013-01-01

  Once limited to geographers and mapmakers, Geographic Information Systems (GIS) has taken a growing central role in information management and visualization. Geospatial services run a gamut of different products and services from Google maps to ArcGIS servers to Mobile development. Geospatial services are not new. Libraries have been writing about…

• Post-Nor'Ida coastal oblique aerial photographs collected from Ocean City, Maryland, to Hatteras, North Carolina, December 4, 2009

  USGS Publications Warehouse

  Morgan, Karen L. M.; Krohn, M. Dennis; Guy, Kristy K.

  2015-01-01

  In addition to the photographs, a Google Earth Keyhole Markup Language (KML) file is provided and can be used to view the images by clicking on the marker and then clicking on either the thumbnail or the link above the thumbnail. The KML files were created using the photographic navigation files.

• Baseline Coastal Oblique Aerial Photographs Collected from Navarre Beach, Florida, to Breton Island, Louisiana, September 1, 2014

  USGS Publications Warehouse

  Morgan, Karen L. M.

  2015-08-31

  In addition to the photographs, a Google Earth Keyhole Markup Language (KML) file is provided and can be used to view the images by clicking on the marker and then clicking on either the thumbnail or the link above the thumbnail. The KML files were created using the photographic navigation files.

• Pinpointing Watershed Pollution on a Virtual Globe

  ERIC Educational Resources Information Center

  Saunders, Cheston; Taylor, Amy

  2014-01-01

  Pollution is not a problem we just read about anymore. It affects the air we breathe, the land we live on, and the water we consume. After noticing a lack of awareness in students, a lesson was developed that used Google Earth to pinpoint sources of pollution in the local area and in others across the country, and their effects on the surrounding…

• Automatic building detection based on Purposive FastICA (PFICA) algorithm using monocular high resolution Google Earth images

  NASA Astrophysics Data System (ADS)

  Ghaffarian, Saman; Ghaffarian, Salar

  2014-11-01

  This paper proposes an improved FastICA model named as Purposive FastICA (PFICA) with initializing by a simple color space transformation and a novel masking approach to automatically detect buildings from high resolution Google Earth imagery. ICA and FastICA algorithms are defined as Blind Source Separation (BSS) techniques for unmixing source signals using the reference data sets. In order to overcome the limitations of the ICA and FastICA algorithms and make them purposeful, we developed a novel method involving three main steps: 1-Improving the FastICA algorithm using Moore-Penrose pseudo inverse matrix model, 2-Automated seeding of the PFICA algorithm based on LUV color space and proposed simple rules to split image into three regions; shadow + vegetation, baresoil + roads and buildings, respectively, 3-Masking out the final building detection results from PFICA outputs utilizing the K-means clustering algorithm with two number of clusters and conducting simple morphological operations to remove noises. Evaluation of the results illustrates that buildings detected from dense and suburban districts with divers characteristics and color combinations using our proposed method have 88.6% and 85.5% overall pixel-based and object-based precision performances, respectively.

• Assessment of rainwater harvesting potential using GIS

  NASA Astrophysics Data System (ADS)

  Hari, Durgasrilakshmi; Ramamohan Reddy, K.; Vikas, Kola; Srinivas, N.; Vikas, G.

  2018-03-01

  Rainwater harvesting (RWH) is one of the best practices to overcome the scarcity of water. Rainwater harvesting involves collection and storage of rainwater locally through different technologies, for future use. It is also useful for livestock, groundwater recharge and for irrigation practices. Potential of rainwater harvesting refers to the capacity of an individual catchment that harnesses the water falling on the catchment during a particular year considering all rainy days. The present study deals with the identification of the study area boundary and marking it as a Polygon in Google Earth Pro Later, Rooftops of various house entities and roads were digitized using the Polygon command in Google Earth Pro. GIS technique is employed for locating boundaries of the study area and for calculating the areas of various types of rooftops and roads. With the application of GIS, it is possible to assess the total potential of water that can be harvested. The present study will enable us to identify the suitable type of water harvesting structure along with the number of structures required. It is extremely an ideal and effective solution to overcome the water crisis through water conservation in the study area.

• The CRUTEM4 land-surface air temperature data set: construction, previous versions and dissemination via Google Earth

  NASA Astrophysics Data System (ADS)

  Osborn, T. J.; Jones, P. D.

  2014-02-01

  The CRUTEM4 (Climatic Research Unit Temperature, version 4) land-surface air temperature data set is one of the most widely used records of the climate system. Here we provide an important additional dissemination route for this data set: online access to monthly, seasonal and annual data values and time series graphs via Google Earth. This is achieved via an interface written in Keyhole Markup Language (KML) and also provides access to the underlying weather station data used to construct the CRUTEM4 data set. A mathematical description of the construction of the CRUTEM4 data set (and its predecessor versions) is also provided, together with an archive of some previous versions and a recommendation for identifying the precise version of the data set used in a particular study. The CRUTEM4 data set used here is available from doi:10.5285/EECBA94F-62F9-4B7C-88D3-482F2C93C468.

• Analyzing Earth Science Research Networking through Visualizations

  NASA Astrophysics Data System (ADS)

  Hasnain, S.; Stephan, R.; Narock, T.

  2017-12-01

  Using D3.js we visualize collaboration amongst several geophysical science organizations, such as the American Geophysical Union (AGU) and the Federation of Earth Science Information Partners (ESIP). We look at historical trends in Earth Science research topics, cross-domain collaboration, and topics of interest to the general population. The visualization techniques used provide an effective way for non-experts to easily explore distributed and heterogeneous Big Data. Analysis of these visualizations provides stakeholders with insights into optimizing meetings, performing impact evaluation, structuring outreach efforts, and identifying new opportunities for collaboration.

• Web GIS in practice VII: stereoscopic 3-D solutions for online maps and virtual globes

  PubMed Central

  Boulos, Maged N Kamel; Robinson, Larry R

  2009-01-01

  Because our pupils are about 6.5 cm apart, each eye views a scene from a different angle and sends a unique image to the visual cortex, which then merges the images from both eyes into a single picture. The slight difference between the right and left images allows the brain to properly perceive the 'third dimension' or depth in a scene (stereopsis). However, when a person views a conventional 2-D (two-dimensional) image representation of a 3-D (three-dimensional) scene on a conventional computer screen, each eye receives essentially the same information. Depth in such cases can only be approximately inferred from visual clues in the image, such as perspective, as only one image is offered to both eyes. The goal of stereoscopic 3-D displays is to project a slightly different image into each eye to achieve a much truer and realistic perception of depth, of different scene planes, and of object relief. This paper presents a brief review of a number of stereoscopic 3-D hardware and software solutions for creating and displaying online maps and virtual globes (such as Google Earth) in "true 3D", with costs ranging from almost free to multi-thousand pounds sterling. A practical account is also given of the experience of the USGS BRD UMESC (United States Geological Survey's Biological Resources Division, Upper Midwest Environmental Sciences Center) in setting up a low-cost, full-colour stereoscopic 3-D system. PMID:19849837

• Web GIS in practice VII: stereoscopic 3-D solutions for online maps and virtual globes.

  PubMed

  Boulos, Maged N Kamel; Robinson, Larry R

  2009-10-22

  Because our pupils are about 6.5 cm apart, each eye views a scene from a different angle and sends a unique image to the visual cortex, which then merges the images from both eyes into a single picture. The slight difference between the right and left images allows the brain to properly perceive the 'third dimension' or depth in a scene (stereopsis). However, when a person views a conventional 2-D (two-dimensional) image representation of a 3-D (three-dimensional) scene on a conventional computer screen, each eye receives essentially the same information. Depth in such cases can only be approximately inferred from visual clues in the image, such as perspective, as only one image is offered to both eyes. The goal of stereoscopic 3-D displays is to project a slightly different image into each eye to achieve a much truer and realistic perception of depth, of different scene planes, and of object relief. This paper presents a brief review of a number of stereoscopic 3-D hardware and software solutions for creating and displaying online maps and virtual globes (such as Google Earth) in "true 3D", with costs ranging from almost free to multi-thousand pounds sterling. A practical account is also given of the experience of the USGS BRD UMESC (United States Geological Survey's Biological Resources Division, Upper Midwest Environmental Sciences Center) in setting up a low-cost, full-colour stereoscopic 3-D system.

• Web GIS in practice VII: stereoscopic 3-D solutions for online maps and virtual globes

  USGS Publications Warehouse

  Boulos, Maged N.K.; Robinson, Larry R.

  2009-01-01

  Because our pupils are about 6.5 cm apart, each eye views a scene from a different angle and sends a unique image to the visual cortex, which then merges the images from both eyes into a single picture. The slight difference between the right and left images allows the brain to properly perceive the 'third dimension' or depth in a scene (stereopsis). However, when a person views a conventional 2-D (two-dimensional) image representation of a 3-D (three-dimensional) scene on a conventional computer screen, each eye receives essentially the same information. Depth in such cases can only be approximately inferred from visual clues in the image, such as perspective, as only one image is offered to both eyes. The goal of stereoscopic 3-D displays is to project a slightly different image into each eye to achieve a much truer and realistic perception of depth, of different scene planes, and of object relief. This paper presents a brief review of a number of stereoscopic 3-D hardware and software solutions for creating and displaying online maps and virtual globes (such as Google Earth) in "true 3D", with costs ranging from almost free to multi-thousand pounds sterling. A practical account is also given of the experience of the USGS BRD UMESC (United States Geological Survey's Biological Resources Division, Upper Midwest Environmental Sciences Center) in setting up a low-cost, full-colour stereoscopic 3-D system.

• The Climate-G testbed: towards a large scale data sharing environment for climate change

  NASA Astrophysics Data System (ADS)

  Aloisio, G.; Fiore, S.; Denvil, S.; Petitdidier, M.; Fox, P.; Schwichtenberg, H.; Blower, J.; Barbera, R.

  2009-04-01

  The Climate-G testbed provides an experimental large scale data environment for climate change addressing challenging data and metadata management issues. The main scope of Climate-G is to allow scientists to carry out geographical and cross-institutional climate data discovery, access, visualization and sharing. Climate-G is a multidisciplinary collaboration involving both climate and computer scientists and it currently involves several partners such as: Centro Euro-Mediterraneo per i Cambiamenti Climatici (CMCC), Institut Pierre-Simon Laplace (IPSL), Fraunhofer Institut für Algorithmen und Wissenschaftliches Rechnen (SCAI), National Center for Atmospheric Research (NCAR), University of Reading, University of Catania and University of Salento. To perform distributed metadata search and discovery, we adopted a CMCC metadata solution (which provides a high level of scalability, transparency, fault tolerance and autonomy) leveraging both on P2P and grid technologies (GRelC Data Access and Integration Service). Moreover, data are available through OPeNDAP/THREDDS services, Live Access Server as well as the OGC compliant Web Map Service and they can be downloaded, visualized, accessed into the proposed environment through the Climate-G Data Distribution Centre (DDC), the web gateway to the Climate-G digital library. The DDC is a data-grid portal allowing users to easily, securely and transparently perform search/discovery, metadata management, data access, data visualization, etc. Godiva2 (integrated into the DDC) displays 2D maps (and animations) and also exports maps for display on the Google Earth virtual globe. Presently, Climate-G publishes (through the DDC) about 2TB of data related to the ENSEMBLES project (also including distributed replicas of data) as well as to the IPCC AR4. The main results of the proposed work are: wide data access/sharing environment for climate change; P2P/grid metadata approach; production-level Climate-G DDC; high quality tools for data visualization; metadata search/discovery across several countries/institutions; open environment for climate change data sharing.

• Managed Clearings: an Unaccounted Land-cover in Urbanizing Regions

  NASA Astrophysics Data System (ADS)

  Singh, K. K.; Madden, M.; Meentemeyer, R. K.

  2016-12-01

  Managed clearings (MC), such as lawns, public parks and grassy transportation medians, are a common and ecologically important land cover type in urbanizing regions, especially those characterized by sprawl. We hypothesize that MC is underrepresented in land cover classification schemes and data products such as NLCD (National Land Cover Database) data, which may impact environmental assessments and models of urban ecosystems. We visually interpreted and mapped fine scale land cover with special attention to MC using 2012 NAIP (National Agriculture Imagery Program) images and compared the output with NLCD data. Areas sampled were 50 randomly distributed 1*1km blocks of land in three cities of the Char-lanta mega-region (Atlanta, Charlotte, and Raleigh). We estimated the abundance of MC relative to other land cover types, and the proportion of land-cover types in NLCD data that are similar to MC. We also assessed if the designations of recreation, transportation, and utility in MC inform the problem differently than simply tallying MC as a whole. 610 ground points, collected using the Google Earth, were used to evaluate accuracy of NLCD data and visual interpretation for consistency. Overall accuracy of visual interpretation and NLCD data was 78% and 58%, respectively. NLCD data underestimated forest and MC by 14.4km2 and 6.4km2, respectively, while overestimated impervious surfaces by 10.2km2 compared to visual interpretation. MC was the second most dominant land cover after forest (40.5%) as it covered about 28% of the total area and about 13% higher than impervious surfaces. Results also suggested that recreation in MC constitutes up to 90% of area followed by transportation and utility. Due to the prevalence of MC in urbanizing regions, the addition of MC to the synthesis of land-cover data can help delineate realistic cover types and area proportions that could inform ecologic/hydrologic models, and allow for accurate prediction of ecological phenomena.

• Evolution of errors in the altimetric bathymetry model used by Google Earth and GEBCO

  NASA Astrophysics Data System (ADS)

  Marks, K. M.; Smith, W. H. F.; Sandwell, D. T.

  2010-09-01

  We analyze errors in the global bathymetry models of Smith and Sandwell that combine satellite altimetry with acoustic soundings and shorelines to estimate depths. Versions of these models have been incorporated into Google Earth and the General Bathymetric Chart of the Oceans (GEBCO). We use Japan Agency for Marine-Earth Science and Technology (JAMSTEC) multibeam surveys not previously incorporated into the models as "ground truth" to compare against model versions 7.2 through 12.1, defining vertical differences as "errors." Overall error statistics improve over time: 50th percentile errors declined from 57 to 55 to 49 m, and 90th percentile errors declined from 257 to 235 to 219 m, in versions 8.2, 11.1 and 12.1. This improvement is partly due to an increasing number of soundings incorporated into successive models, and partly to improvements in the satellite gravity model. Inspection of specific sites reveals that changes in the algorithms used to interpolate across survey gaps with altimetry have affected some errors. Versions 9.1 through 11.1 show a bias in the scaling from gravity in milliGals to topography in meters that affected the 15-160 km wavelength band. Regionally averaged (>160 km wavelength) depths have accumulated error over successive versions 9 through 11. These problems have been mitigated in version 12.1, which shows no systematic variation of errors with depth. Even so, version 12.1 is in some respects not as good as version 8.2, which employed a different algorithm.

• Gravity as a Strong Prior: Implications for Perception and Action

  PubMed Central

  Jörges, Björn; López-Moliner, Joan

  2017-01-01

  In the future, humans are likely to be exposed to environments with altered gravity conditions, be it only visually (Virtual and Augmented Reality), or visually and bodily (space travel). As visually and bodily perceived gravity as well as an interiorized representation of earth gravity are involved in a series of tasks, such as catching, grasping, body orientation estimation and spatial inferences, humans will need to adapt to these new gravity conditions. Performance under earth gravity discrepant conditions has been shown to be relatively poor, and few studies conducted in gravity adaptation are rather discouraging. Especially in VR on earth, conflicts between bodily and visual gravity cues seem to make a full adaptation to visually perceived earth-discrepant gravities nearly impossible, and even in space, when visual and bodily cues are congruent, adaptation is extremely slow. We invoke a Bayesian framework for gravity related perceptual processes, in which earth gravity holds the status of a so called “strong prior”. As other strong priors, the gravity prior has developed through years and years of experience in an earth gravity environment. For this reason, the reliability of this representation is extremely high and overrules any sensory information to its contrary. While also other factors such as the multisensory nature of gravity perception need to be taken into account, we present the strong prior account as a unifying explanation for empirical results in gravity perception and adaptation to earth-discrepant gravities. PMID:28503140

• Global Imagery Browse Services (GIBS) - Rapidly Serving NASA Imagery for Applications and Science Users

  NASA Astrophysics Data System (ADS)

  Schmaltz, J. E.; Ilavajhala, S.; Plesea, L.; Hall, J. R.; Boller, R. A.; Chang, G.; Sadaqathullah, S.; Kim, R.; Murphy, K. J.; Thompson, C. K.

  2012-12-01

  Expedited processing of imagery from NASA satellites for near-real time use by non-science applications users has a long history, especially since the beginning of the Terra and Aqua missions. Several years ago, the Land Atmosphere Near-real-time Capability for EOS (LANCE) was created to greatly expand the range of near-real time data products from a variety of Earth Observing System (EOS) instruments. NASA's Earth Observing System Data and Information System (EOSDIS) began exploring methods to distribute these data as imagery in an intuitive, geo-referenced format, which would be available within three hours of acquisition. Toward this end, EOSDIS has developed the Global Imagery Browse Services (GIBS, http://earthdata.nasa.gov/gibs) to provide highly responsive, scalable, and expandable imagery services. The baseline technology chosen for GIBS was a Tiled Web Mapping Service (TWMS) developed at the Jet Propulsion Laboratory. Using this, global images and mosaics are divided into tiles with fixed bounding boxes for a pyramid of fixed resolutions. Initially, the satellite imagery is created at the existing data systems for each sensor, ensuring the oversight of those most knowledgeable about the science. There, the satellite data is geolocated and converted to an image format such as JPEG, TIFF, or PNG. The GIBS ingest server retrieves imagery from the various data systems and converts them into image tiles, which are stored in a highly-optimized raster format named Meta Raster Format (MRF). The image tiles are then served to users via HTTP by means of an Apache module. Services are available for the entire globe (lat-long projection) and for both polar regions (polar stereographic projection). Requests to the services can be made with the non-standard, but widely known, TWMS format or via the well-known OGC Web Map Tile Service (WMTS) standard format. Standard OGC Web Map Service (WMS) access to the GIBS server is also available. In addition, users may request a KML pyramid. This variety of access methods allows stakeholders to develop visualization/browse clients for a diverse variety of specific audiences. Currently, EOSDIS is providing an OpenLayers web client, Worldview (http://earthdata.nasa.gov/worldview), as an interface to GIBS. A variety of other existing clients can also be developed using such tools as Google Earth, Google Earth browser Plugin, ESRI's Adobe Flash/Flex Client Library, NASA World Wind, Perceptive Pixel Client, Esri's iOS Client Library, and OpenLayers for Mobile. The imagery browse capabilities from GIBS can be combined with other EOSDIS services (i.e. ECHO OpenSearch) via a client that ties them both together to provide an interface that enables data download from the onscreen imagery. Future plans for GIBS include providing imagery based on science quality data from the entire data record of these EOS instruments.

Reaching the Next Generation of College Students via Their Digital Devices.

NASA Astrophysics Data System (ADS)

Whitmeyer, S. J.; De Paor, D. G.; Bentley, C.

2015-12-01

Current college students attended school during a decade in which many school districts banned cellphones from the classroom or even from school grounds. These students are used to being told to put away their mobile devices and concentrate on traditional classroom activities such as watching PowerPoint presentations or calculating with pencil and paper. However, due to a combination of parental security concerns and recent education research, schools are rapidly changing policy and embracing mobile devices for ubiquitous learning opportunities inside and outside of the classroom. Consequently, many of the next generation of college students will have expectations of learning via mobile technology. We have developed a range of digital geology resources to aid mobile-based geoscience education at college level, including mapping on iPads and other tablets, "crowd-sourced" field projects, augmented reality-supported asynchronous field classes, 3D and 4D split-screen virtual reality tours, macroscopic and microscopic gigapixel imagery, 360° panoramas, assistive devices for inclusive field education, and game-style educational challenges. Class testing of virtual planetary tours shows modest short-term learning gains, but more work is needed to ensure long-term retention. Many of our resources rely on the Google Earth browser plug-in and application program interface (API). Because of security concerns, browser plug-ins in general are being phased out and the Google Earth API will not be supported in future browsers. However, a new plug-in-free API is promised by Google and an alternative open-source virtual globe called Cesium is undergoing rapid development. It already supports the main aspects of Keyhole Markup Language and has features of significant benefit to geoscience, including full support on mobile devices and sub-surface viewing and touring. The research team includes: Heather Almquist, Stephen Burgin, Cinzia Cervato, Filis Coba, Chloe Constants, Gene Cooper, Mladen Dordevic, Marissa Dudek, Brandon Fitzwater, Bridget Gomez, Tyler Hansen, Paul Karabinos, Terry Pavlis, Jen Piatek, Alan Pitts, Robin Rohrback, Bill Richards, Caroline Robinson, Jeff Rollins, Jeff Ryan, Ron Schott, Kristen St. John, and Barb Tewksbury. Supported by NSF DUE 1323419 and by Google Geo Curriculum Awards.

Understanding Urban Watersheds through Digital Interactive Maps, San Francisco Bay Area, California

NASA Astrophysics Data System (ADS)

Sowers, J. M.; Ticci, M. G.; Mulvey, P.

2014-12-01

Dense urbanization has resulted in the "disappearance" of many local creeks in urbanized areas surrounding the San Francisco Bay. Long reaches of creeks now flow in underground pipes. Municipalities and water agencies trying to reduce non-point-source pollution are faced with a public that cannot see and therefore does not understand the interconnected nature of the drainage system or its ultimate discharge to the bay. Since 1993, we have collaborated with the Oakland Museum, the San Francisco Estuary Institute, public agencies, and municipalities to create creek and watershed maps to address the need for public understanding of watershed concepts. Fifteen paper maps are now published (www.museumca.org/creeks), which have become a standard reference for educators and anyone working on local creek-related issues. We now present digital interactive creek and watershed maps in Google Earth. Four maps are completed covering urbanized areas of Santa Clara and Alameda Counties. The maps provide a 3D visualization of the watersheds, with cartography draped over the landscape in transparent colors. Each mapped area includes both Present and Past (circa 1800s) layers which can be clicked on or off by the user. The Present layers include the modern drainage network, watershed boundaries, and reservoirs. The Past layers include the 1800s-era creek systems, tidal marshes, lagoons, and other habitats. All data are developed in ArcGIS software and converted to Google Earth format. To ensure the maps are interesting and engaging, clickable icons pop-up provide information on places to visit, restoration projects, history, plants, and animals. Maps of Santa Clara Valley are available at http://www.valleywater.org/WOW.aspx. Maps of western Alameda County will soon be available at http://acfloodcontrol.org/. Digital interactive maps provide several advantages over paper maps. They are seamless within each map area, and the user can zoom in or out, and tilt, and fly over to explore any area of interest. They can be easily customized, for example, adding placemarks or notes. Enrichment information can be added, using clickable icons, without cluttering the map. Best, the maps are fun to use. Digital interactive maps will be another effective tool for enhancing public understanding of urban creeks & watersheds.

Baseline coastal oblique aerial photographs collected from the Virginia/North Carolina border to Montauk Point, New York, October 5-6, 2014

USGS Publications Warehouse

Morgan, Karen L. M.

2015-10-02

In addition to the photographs, a Google Earth Keyhole Markup Language (KML) file is provided and can be used to view the images by clicking on the marker and then clicking on either the thumbnail or the link above the thumbnail. The KML files were created using the photographic navigation files.

Tactical Level Commander and Staff Toolkit

DTIC Science & Technology

2010-01-01

Sites Geodata.gov (for maps) http://gos2.geodata.gov Google Earth for .mil (United States Army Corps of Engineers (USACE) site) https...the eyes, ears, head, hands, back, and feet. When appropriate, personnel should wear protective lenses, goggles, or face shields . Leaders should...Typical hurricanes are about 300 miles wide, although they can vary considerably. Size is not necessarily an indication of hurricane intensity. The

From Geocaching to Virtual Reality: Technology tools that can transform courses into interactive learning expeditions

NASA Astrophysics Data System (ADS)

Moysey, S. M.; Lazar, K.; Boyer, D. M.; Mobley, C.; Sellers, V.

2016-12-01

Transforming classrooms into active learning environments is a key challenge in introductory-level courses. The technology explosion over the last decade, from the advent of mobile devices to virtual reality, is creating innumerable opportunities to engage students within and outside of traditional classroom settings. In particular, technology can be an effective tool for providing students with field experiences that would otherwise be logistically difficult in large, introductory earth science courses. For example, we have created an integrated platform for mobile devices using readily accessible "off the shelf" components (e.g., Google Apps, Geocaching.com, and Facebook) that allow individual students to navigate to geologically relevant sites, perform and report on activities at these locations, and share their findings through social media by posting "geoselfies". Students compete with their friends on a leaderboard, while earning incentives for completing extracurricular activities in courses. Thus in addition to exposing students to a wider range of meaningful and accessible geologic field experiences, they also build a greater sense of community and identity within the context of earth science classrooms. Rather than sending students to the field, we can also increasingly bring the field to students in classrooms using virtual reality. Ample mobile platforms are emerging that easily allow for the creation, curation, and viewing of photospheres (i.e., 360o images) with mobile phones and low-cost headsets; Google Street View, Earth, and Expeditions are leading the way in terms of ease of content creation and implementation in the classroom. While these tools are an excellent entry point to show students real-world sites, they currently lack the capacity for students to interact with the environment. We have therefore also developed an immersive virtual reality game that allows students to study the geology of the Grand Canyon using their smartphone and Google Cardboard viewer. Students navigate the terrain, collect rock samples, and investigate outcrops using a variety of tests and comparative analyses built into the game narrative. To enhance the realism of the game, real-world samples and outcrops from the Grand Canyon were scanned and embedded within the VR environment.

Mapping for the masses: using free remote sensing data for disaster management

NASA Astrophysics Data System (ADS)

Teeuw, R.; McWilliam, N.; Morris, N.; Saunders, C.

2009-04-01

We examine the uses of free satellite imagery and Digital Elevation Models (DEMs) for disaster management, targeting three data sources: the United Nations Charter on Space and Disasters, Google Earth and internet-based satellite data archives, such as the Global Land Cover Facility (GLCF). The research has assessed SRTM and ASTER DEM data, Landsat TM/ETM+ and ASTER imagery, as well as utilising datasets and basic GIS operations available via Google Earth. As an aid to Disaster Risk Reduction, four sets of maps can be produced from satellite data: (i) Multiple Geohazards: areas prone to slope instability, coastal inundation and fluvial flooding; (ii) Vulnerability: population density, habitation types, land cover types and infrastructure; (iii) Disaster Risk: produced by combining severity scores from (i) and (ii); (iv) Reconstruction: zones of rock/sediment with construction uses; areas of woodland (for fuel/construction) water sources; transport routes; zones suitable for re-settlement. This set of Disaster Risk Reduction maps are ideal for regional (1:50,000 to 1:250,000 scale) planning for in low-income countries: more detailed assessments require relatively expensive high resolution satellite imagery or aerial photography, although Google Earth has a good track record for posting high-res imagery of disaster zones (e.g. the 2008 Burma storm surge). The Disaster Risk maps highlight areas of maximum risk to a region's emergency planners and decision makers, enabling various types of public education and other disaster mitigation measures. The Reconstruction map also helps to save lives, by facilitating disaster recovery. Many problems have been identified. Access to the UN Charter imagery is fine after a disaster, but very difficult if assessing pre-disaster indicators: the data supplied also tends to be pre-processed, when some relief agencies would prefer to have raw data. The limited and expensive internet access in many developing countries limits access to archives of free satellite data, such as the GLCF. Finally, data integration, spatial/temporal analysis and map production are all hindered by the high price of most GIS software, making the development of suitable open-source software a priority.

Landsat Based Woody Vegetation Loss Detection in Queensland, Australia Using the Google Earth Engine

NASA Astrophysics Data System (ADS)

Johansen, K.; Phinn, S. R.; Taylor, M.

2014-12-01

Land clearing detection and woody Foliage Projective Cover (FPC) monitoring at the state and national level in Australia has mainly been undertaken by state governments and the Terrestrial Ecosystem Research Network (TERN) because of the considerable expense, expertise, sustained duration of activities and staffing levels needed. Only recently have services become available, providing low budget, generalized access to change detection tools suited to this task. The objective of this research was to examine if a globally available service, Google Earth Engine Beta, could be used to predict woody vegetation loss with accuracies approaching the methods used by TERN and the government of the state of Queensland, Australia. Two change detection approaches were investigated using Landsat Thematic Mapper time series and the Google Earth Engine Application Programming Interface: (1) CART and Random Forest classifiers; and (2) a normalized time series of Foliage Projective Cover (FPC) and NDVI combined with a spectral index. The CART and Random Forest classifiers produced high user's and producer's mapping accuracies of clearing (77-92% and 54-77%, respectively) when detecting change within epochs for which training data were available, but extrapolation to epochs without training data reduced the mapping accuracies. The use of FPC and NDVI time series provided a more robust approach for calculation of a clearing probability, as it did not rely on training data but instead on the difference of the normalized FPC / NDVI mean and standard deviation of a single year at the change point in relation to the remaining time series. However, the FPC and NDVI time series approach represented a trade-off between user's and producer's accuracies. Both change detection approaches explored in this research were sensitive to ephemeral greening and drying of the landscape. However, the developed normalized FPC and NDVI time series approach can be tuned to provide automated alerts for large woody vegetation clearing events by selecting suitable thresholds to identify very likely clearing. This research provides a comprehensive foundation to build further capacity to use globally accessible, free, online image datasets and processing tools to accurately detect woody vegetation clearing in an automated and rapid manner.

Assessing Coupled Social Ecological Flood Vulnerability from Uttarakhand, India, to the State of New York with Google Earth Engine

NASA Astrophysics Data System (ADS)

Tellman, B.; Schwarz, B.

2014-12-01

This talk describes the development of a web application to predict and communicate vulnerability to floods given publicly available data, disaster science, and geotech cloud capabilities. The proof of concept in Google Earth Engine API with initial testing on case studies in New York and Utterakhand India demonstrates the potential of highly parallelized cloud computing to model socio-ecological disaster vulnerability at high spatial and temporal resolution and in near real time. Cloud computing facilitates statistical modeling with variables derived from large public social and ecological data sets, including census data, nighttime lights (NTL), and World Pop to derive social parameters together with elevation, satellite imagery, rainfall, and observed flood data from Dartmouth Flood Observatory to derive biophysical parameters. While more traditional, physically based hydrological models that rely on flow algorithms and numerical methods are currently unavailable in parallelized computing platforms like Google Earth Engine, there is high potential to explore "data driven" modeling that trades physics for statistics in a parallelized environment. A data driven approach to flood modeling with geographically weighted logistic regression has been initially tested on Hurricane Irene in southeastern New York. Comparison of model results with observed flood data reveals a 97% accuracy of the model to predict flooded pixels. Testing on multiple storms is required to further validate this initial promising approach. A statistical social-ecological flood model that could produce rapid vulnerability assessments to predict who might require immediate evacuation and where could serve as an early warning. This type of early warning system would be especially relevant in data poor places lacking the computing power, high resolution data such as LiDar and stream gauges, or hydrologic expertise to run physically based models in real time. As the data-driven model presented relies on globally available data, the only real time data input required would be typical data from a weather service, e.g. precipitation or coarse resolution flood prediction. However, model uncertainty will vary locally depending upon the resolution and frequency of observed flood and socio-economic damage impact data.

Reusable Client-Side JavaScript Modules for Immersive Web-Based Real-Time Collaborative Neuroimage Visualization

PubMed Central

Bernal-Rusiel, Jorge L.; Rannou, Nicolas; Gollub, Randy L.; Pieper, Steve; Murphy, Shawn; Robertson, Richard; Grant, Patricia E.; Pienaar, Rudolph

2017-01-01

In this paper we present a web-based software solution to the problem of implementing real-time collaborative neuroimage visualization. In both clinical and research settings, simple and powerful access to imaging technologies across multiple devices is becoming increasingly useful. Prior technical solutions have used a server-side rendering and push-to-client model wherein only the server has the full image dataset. We propose a rich client solution in which each client has all the data and uses the Google Drive Realtime API for state synchronization. We have developed a small set of reusable client-side object-oriented JavaScript modules that make use of the XTK toolkit, a popular open-source JavaScript library also developed by our team, for the in-browser rendering and visualization of brain image volumes. Efficient realtime communication among the remote instances is achieved by using just a small JSON object, comprising a representation of the XTK image renderers' state, as the Google Drive Realtime collaborative data model. The developed open-source JavaScript modules have already been instantiated in a web-app called MedView, a distributed collaborative neuroimage visualization application that is delivered to the users over the web without requiring the installation of any extra software or browser plugin. This responsive application allows multiple physically distant physicians or researchers to cooperate in real time to reach a diagnosis or scientific conclusion. It also serves as a proof of concept for the capabilities of the presented technological solution. PMID:28507515

Ptolemy's Britain and Ireland: A New Digital Reconstruction

NASA Astrophysics Data System (ADS)

Abshire, Corey; Durham, Anthony; Gusev, Dmitri A.; Stafeyev, Sergey K.

2018-05-01

In this paper, we expand application of our mathematical methods for translating ancient coordinates from the classical Geography by Claudius Ptolemy into modern coordinates from India and Arabia to Britain and Ireland, historically important islands on the periphery of the ancient Roman Empire. The methods include triangulation and flocking with subsequent Bayesian correction. The results of our work can be conveniently visualized in modern GIS tools, such as ArcGIS, QGIS, and Google Earth. The enhancements we have made include a novel technique for handling tentatively identified points. We compare the precision of reconstruction achieved for Ptolemy's Britain and Ireland with the precisions that we had computed earlier for his India before the Ganges and three provinces of Arabia. We also provide improved validation and comparison amongst the methods applied. We compare our results with the prior work, while utilizing knowledge from such important ancient sources as the Antonine Itinerary, Tabula Peutingeriana, and the Ravenna Cosmography. The new digital reconstruction of Claudius Ptolemy's Britain and Ireland presented in this paper, along with the accompanying linguistic analysis of ancient toponyms, contributes to improvement of understanding of our cultural cartographic heritage by making it easier to study the ancient world using the popular and accessible GIS programs.

Accessing Earth Science Data Visualizations through NASA GIBS & Worldview

NASA Astrophysics Data System (ADS)

Cechini, M. F.; Boller, R. A.; Baynes, K.; Wong, M. M.; King, B. A.; Schmaltz, J. E.; De Luca, A. P.; King, J.; Roberts, J. T.; Rodriguez, J.; Thompson, C. K.; Pressley, N. N.

2017-12-01

For more than 20 years, the NASA Earth Observing System (EOS) has operated dozens of remote sensing satellites collecting nearly 15 Petabytes of data that span thousands of science parameters. Within these observations are keys the Earth Scientists have used to unlock many things that we understand about our planet. Also contained within these observations are a myriad of opportunities for learning and education. The trick is making them accessible to educators and students in convenient and simple ways so that effort can be spent on lesson enrichment and not overcoming technical hurdles. The NASA Global Imagery Browse Services (GIBS) system and NASA Worldview website provide a unique view into EOS data through daily full resolution visualizations of hundreds of earth science parameters. For many of these parameters, visualizations are available within hours of acquisition from the satellite. For others, visualizations are available for the entire mission of the satellite. Accompanying the visualizations are visual aids such as color legends, place names, and orbit tracks. By using these visualizations, educators and students can observe natural phenomena that enrich a scientific education. This poster will provide an overview of the visualizations available in NASA GIBS and Worldview and how they are accessed. We invite discussion on how the visualizations can be used or improved for educational purposes.

The OpenEarth Framework (OEF) for the 3D Visualization of Integrated Earth Science Data

NASA Astrophysics Data System (ADS)

Nadeau, David; Moreland, John; Baru, Chaitan; Crosby, Chris

2010-05-01

Data integration is increasingly important as we strive to combine data from disparate sources and assemble better models of the complex processes operating at the Earth's surface and within its interior. These data are often large, multi-dimensional, and subject to differing conventions for data structures, file formats, coordinate spaces, and units of measure. When visualized, these data require differing, and sometimes conflicting, conventions for visual representations, dimensionality, symbology, and interaction. All of this makes the visualization of integrated Earth science data particularly difficult. The OpenEarth Framework (OEF) is an open-source data integration and visualization suite of applications and libraries being developed by the GEON project at the University of California, San Diego, USA. Funded by the NSF, the project is leveraging virtual globe technology from NASA's WorldWind to create interactive 3D visualization tools that combine and layer data from a wide variety of sources to create a holistic view of features at, above, and beneath the Earth's surface. The OEF architecture is open, cross-platform, modular, and based upon Java. The OEF's modular approach to software architecture yields an array of mix-and-match software components for assembling custom applications. Available modules support file format handling, web service communications, data management, user interaction, and 3D visualization. File parsers handle a variety of formal and de facto standard file formats used in the field. Each one imports data into a general-purpose common data model supporting multidimensional regular and irregular grids, topography, feature geometry, and more. Data within these data models may be manipulated, combined, reprojected, and visualized. The OEF's visualization features support a variety of conventional and new visualization techniques for looking at topography, tomography, point clouds, imagery, maps, and feature geometry. 3D data such as seismic tomography may be sliced by multiple oriented cutting planes and isosurfaced to create 3D skins that trace feature boundaries within the data. Topography may be overlaid with satellite imagery, maps, and data such as gravity and magnetics measurements. Multiple data sets may be visualized simultaneously using overlapping layers within a common 3D coordinate space. Data management within the OEF handles and hides the inevitable quirks of differing file formats, web protocols, storage structures, coordinate spaces, and metadata representations. Heuristics are used to extract necessary metadata used to guide data and visual operations. Derived data representations are computed to better support fluid interaction and visualization while the original data is left unchanged in its original form. Data is cached for better memory and network efficiency, and all visualization makes use of 3D graphics hardware support found on today's computers. The OpenEarth Framework project is currently prototyping the software for use in the visualization, and integration of continental scale geophysical data being produced by EarthScope-related research in the Western US. The OEF is providing researchers with new ways to display and interrogate their data and is anticipated to be a valuable tool for future EarthScope-related research.

Artificial Intelligence and NASA Data Used to Discover Eighth Planet Circling Distant Star

NASA Image and Video Library

2017-12-12

Our solar system now is tied for most number of planets around a single star, with the recent discovery of an eighth planet circling Kepler-90, a Sun-like star 2,545 light years from Earth. The planet was discovered in data from NASA’s Kepler space telescope. The newly-discovered Kepler-90i -- a sizzling hot, rocky planet that orbits its star once every 14.4 days -- was found by researchers from Google and The University of Texas at Austin using machine learning. Machine learning is an approach to artificial intelligence in which computers “learn.” In this case, computers learned to identify planets by finding in Kepler data instances where the telescope recorded signals from planets beyond our solar system, known as exoplanets. Video Credit: NASA Ames Research Center / Google

The Use of Interactive Media Ispring Suite 8 Supported by Google SketchUp to Improve Students’ Geometry Skills Based on Hoffer’s Theory

NASA Astrophysics Data System (ADS)

Nurwijayanti, A.; Budiyono; Fitriana, L.

2018-04-01

The basic Geometry skills are needed by the students to solve the geometrical tasks in daily life. There are five aspects of the Geometry ability based on the Hoffer’s theory. They are visual, verbal, drawing, logical, and application. These are the abilities that the students in junior high school level need to master. The purpose of this study is to find out and describe the effectiveness of the interactive media supported by Google SketchUp to improve the students’ basic Geometry skills based on Hoffer’s theory. The subject in this research is 30 students from class 9E in Junior High School of Mojogedang 1, Karanganyar regency. This study uses a pre-test and post-test experiment and analyzed with the t-test hypothesis with the significant level of 5%. The result of this study can be seen from the diffeence average score between the pre-test and post-test, which shows a significance difference. It means that through the interactive media supported by Google SketchUp, the students’ five basic abilities are improved. Therefore, it can be concluded that the interactive media supported by Google SketchUp is potential and can be used to help the students in improving their basic Geometry skills based on Hoffer’s theory.

Inheriting the Learner's View: A Google Glass-Based Wearable Computing Platform for Improving Surgical Trainee Performance.

PubMed

Brewer, Zachary E; Fann, Hutchinson C; Ogden, W David; Burdon, Thomas A; Sheikh, Ahmad Y

2016-01-01

It is speculated that, in operative environments, real-time visualization of the trainee's viewpoint by the instructor may improve performance and teaching efficacy. We hypothesized that introduction of a wearable surgical visualization system allowing the instructor to visualize otherwise "blind" areas in the operative field could improve trainee performance in a simulated operative setting. A total of 11 surgery residents (4 in general surgery training and 7 in an integrated 6-year cardiothoracic surgery program) participated in the study. Google (Mountain View, CA) Glass hardware running proprietary software from CrowdOptic (San Francisco, CA) was utilized for creation of the wearable surgical visualization system. Both the learner and trainer wore the system, and video was streamed from the learner's system in real time to the trainer, who directed the learner to place needles in a simulated operative field. Subjects placed a total of 5 needles in each of 4 quadrants. A composite error score was calculated based on the accuracy of needle placement in relation to the intended needle trajectories as described by the trainer. Time to task completion (TTC) was also measured and participants completed an exit questionnaire. All residents completed the protocol tasks and the survey. Introduction of the wearable surgical visualization system did not affect mean time to task completion (278 ± 50 vs. 282 ± 69 seconds, p = NS). However, mean composite error score fell significantly once the wearable system was deployed (18 ± 5 vs. 15 ± 4, p < 0.05), demonstrating improved accuracy of needle placement. Most of the participants deemed the device unobtrusive, easy to operate, and useful for communication and instruction. This study suggests that wearable surgical visualization systems allowing for adoption of the learner's perspective may be a useful educational adjunct in the training of surgeons. Further evaluations of the efficacy of wearable technology in the operating room environment are warranted. Copyright © 2016 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Images of Earth and Space: The Role of Visualization in NASA Science

NASA Technical Reports Server (NTRS)

1996-01-01

Fly through the ocean at breakneck speed. Tour the moon. Even swim safely in the boiling sun. You can do these things and more in a 17 minute virtual journey through Earth and space. The trek is by way of colorful scientific visualizations developed by the NASA/Goddard Space Flight Center's Scientific Visualization Studio and the NASA HPCC Earth and Space Science Project investigators. Various styles of electronic music and lay-level narration provide the accompaniment.

Building Knowledge Graphs for NASA's Earth Science Enterprise

NASA Astrophysics Data System (ADS)

Zhang, J.; Lee, T. J.; Ramachandran, R.; Shi, R.; Bao, Q.; Gatlin, P. N.; Weigel, A. M.; Maskey, M.; Miller, J. J.

2016-12-01

Inspired by Google Knowledge Graph, we have been building a prototype Knowledge Graph for Earth scientists, connecting information and data in NASA's Earth science enterprise. Our primary goal is to advance the state-of-the-art NASA knowledge extraction capability by going beyond traditional catalog search and linking different distributed information (such as data, publications, services, tools and people). This will enable a more efficient pathway to knowledge discovery. While Google Knowledge Graph provides impressive semantic-search and aggregation capabilities, it is limited to search topics for general public. We use the similar knowledge graph approach to semantically link information gathered from a wide variety of sources within the NASA Earth Science enterprise. Our prototype serves as a proof of concept on the viability of building an operational "knowledge base" system for NASA Earth science. Information is pulled from structured sources (such as NASA CMR catalog, GCMD, and Climate and Forecast Conventions) and unstructured sources (such as research papers). Leveraging modern techniques of machine learning, information retrieval, and deep learning, we provide an integrated data mining and information discovery environment to help Earth scientists to use the best data, tools, methodologies, and models available to answer a hypothesis. Our knowledge graph would be able to answer questions like: Which articles discuss topics investigating similar hypotheses? How have these methods been tested for accuracy? Which approaches have been highly cited within the scientific community? What variables were used for this method and what datasets were used to represent them? What processing was necessary to use this data? These questions then lead researchers and citizen scientists to investigate the sources where data can be found, available user guides, information on how the data was acquired, and available tools and models to use with this data. As a proof of concept, we focus on a well-defined domain - Hurricane Science linking research articles and their findings, data, people and tools/services. Modern information retrieval, natural language processing machine learning and deep learning techniques are applied to build the knowledge network.

Identifying Severe Weather Impacts and Damage with Google Earth Engine

NASA Astrophysics Data System (ADS)

Molthan, A.; Burks, J. E.; Bell, J. R.

2015-12-01

Hazards associated with severe convective storms can lead to rapid changes in land surface vegetation. Depending upon the type of vegetation that has been impacted, their impacts can be relatively short lived, such as damage to seasonal crops that are eventually removed by harvest, or longer-lived, such as damage to a stand of trees or expanse of forest that require several years to recover. Since many remote sensing imagers provide their highest spatial resolution bands in the red and near-infrared to support monitoring of vegetation, these impacts can be readily identified as short-term and marked decreases in common vegetation indices such as NDVI, along with increases in land surface temperature that are observed at a reduced spatial resolution. The ability to identify an area of vegetation change is improved by understanding the conditions that are normal for a given time of year and location, along with a typical range of variability in a given parameter. This analysis requires a period of record well beyond the availability of near real-time data. These activities would typically require an analyst to download large volumes of data from sensors such as NASA's MODIS (aboard Terra and Aqua) or higher resolution imagers from the Landsat series of satellites. Google's Earth Engine offers a "big data" solution to these challenges, by providing a streamlined API and option to process the period of record of NASA MODIS and Landsat products through relatively simple Javascript coding. This presentation will highlight efforts to date in using Earth Engine holdings to produce vegetation and land surface temperature anomalies that are associated with damage to agricultural and other vegetation caused by severe thunderstorms across the Central and Southeastern United States. Earth Engine applications will show how large data holdings can be used to map severe weather damage, ascertain longer-term impacts, and share best practices learned and challenges with applying Earth Engine holdings to the analysis of severe weather damage. Other applications are also demonstrated, such as use of Earth Engine to prepare pre-event composites that can be used to subjectively identify other severe weather impacts. Future extension to flooding and wildfires is also proposed.

Researchermap: a tool for visualizing author locations using Google maps.

PubMed

Rastegar-Mojarad, Majid; Bales, Michael E; Yu, Hong

2013-01-01

We hereby present ResearcherMap, a tool to visualize locations of authors of scholarly papers. In response to a query, the system returns a map of author locations. To develop the system we first populated a database of author locations, geocoding institution locations for all available institutional affiliation data in our database. The database includes all authors of Medline papers from 1990 to 2012. We conducted a formative heuristic usability evaluation of the system and measured the system's accuracy and performance. The accuracy of finding the accurate address is 97.5% in our system.

compuGUT: An in silico platform for simulating intestinal fermentation

NASA Astrophysics Data System (ADS)

Moorthy, Arun S.; Eberl, Hermann J.

The microbiota inhabiting the colon and its effect on health is a topic of significant interest. In this paper, we describe the compuGUT - a simulation tool developed to assist in exploring interactions between intestinal microbiota and their environment. The primary numerical machinery is implemented in C, and the accessory scripts for loading and visualization are prepared in bash (LINUX) and R. SUNDIALS libraries are employed for numerical integration, and googleVis API for interactive visualization. Supplementary material includes a concise description of the underlying mathematical model, and detailed characterization of numerical errors and computing times associated with implementation parameters.

Timely Reporting and Interactive Visualization of Animal Health and Slaughterhouse Surveillance Data in Switzerland.

PubMed

Muellner, Ulrich J; Vial, Flavie; Wohlfender, Franziska; Hadorn, Daniela; Reist, Martin; Muellner, Petra

2015-01-01

The reporting of outputs from health surveillance systems should be done in a near real-time and interactive manner in order to provide decision makers with powerful means to identify, assess, and manage health hazards as early and efficiently as possible. While this is currently rarely the case in veterinary public health surveillance, reporting tools do exist for the visual exploration and interactive interrogation of health data. In this work, we used tools freely available from the Google Maps and Charts library to develop a web application reporting health-related data derived from slaughterhouse surveillance and from a newly established web-based equine surveillance system in Switzerland. Both sets of tools allowed entry-level usage without or with minimal programing skills while being flexible enough to cater for more complex scenarios for users with greater programing skills. In particular, interfaces linking statistical softwares and Google tools provide additional analytical functionality (such as algorithms for the detection of unusually high case occurrences) for inclusion in the reporting process. We show that such powerful approaches could improve timely dissemination and communication of technical information to decision makers and other stakeholders and could foster the early-warning capacity of animal health surveillance systems.

IRIS Earthquake Browser with Integration to the GEON IDV for 3-D Visualization of Hypocenters.

NASA Astrophysics Data System (ADS)

Weertman, B. R.

2007-12-01

We present a new generation of web based earthquake query tool - the IRIS Earthquake Browser (IEB). The IEB combines the DMC's large set of earthquake catalogs (provided by USGS/NEIC, ISC and the ANF) with the popular Google Maps web interface. With the IEB you can quickly and easily find earthquakes in any region of the globe. Using Google's detailed satellite images, earthquakes can be easily co-located with natural geographic features such as volcanoes as well as man made features such as commercial mines. A set of controls allow earthquakes to be filtered by time, magnitude, and depth range as well as catalog name, contributor name and magnitude type. Displayed events can be easily exported in NetCDF format into the GEON Integrated Data Viewer (IDV) where hypocenters may be visualized in three dimensions. Looking "under the hood", the IEB is based on AJAX technology and utilizes REST style web services hosted at the IRIS DMC. The IEB is part of a broader effort at the DMC aimed at making our data holdings available via web services. The IEB is useful both educationally and as a research tool.

Towards the Ubiquitous Deployment of DNSSEC

DTIC Science & Technology

2016-01-01

with other deployment partners around the world, there is now a significant and growing number of TLDs that have been signed, and a number of...as Google Earth, the Blackberry 10 operating system, and the entire set of K Desktop Environment (KDE) windowing system applications are based on...differentiate between transient errors and legitimate DNS spoofing attacks is likely going to be very important as deployment grows . The importance of

Reaching Forward in the War against the Islamic State

DTIC Science & Technology

2016-12-07

every week with U.S.- and Coalition-advised ISOF troops taking the lead in combat operations using cellular communications systems that link them...tions—Offline Maps, Google Earth , and Viber, to name a few—which allowed them to bring tablets and phones on their operations to help communicate ...provided an initial Remote Advise and Assist capability that enabled the special forces advisors to track, communicate , and share limited data with

Baseline coastal oblique aerial photographs collected from Navarre Beach, Florida, to Breton Island, Louisiana, September 18–19, 2015

USGS Publications Warehouse

Morgan, Karen L. M.

2016-08-01

In addition to the photographs, a Google Earth Keyhole Markup Language (KML) file is provided and can be used to view the images by clicking on the marker and then the thumbnail or the link below the thumbnail. The KML file was created using the photographic navigation files. This KML file can be found in the kml folder.

MATLAB® and Design Recipes for Earth Sciences: How to Collect, Process and Present Geoscientific Information

NASA Astrophysics Data System (ADS)

Trauth, M.; Sillmann, E.

2012-04-01

The overall aim of the class was to introduce undergraduate students to the typical course of a project. The project starts with searching of the relevant literature, reviewing and ranking of the published books and journal articles, extracting the relevant information as text, data or graphs from the literature, searching, processing and visualizing data, and compiling and presenting the results as posters, abstracts and oral presentations. In the first lecture, an unexpectedly-large number (ca. 65) of students subscribed to the course urging us to teach the course in a lecture hall with a projector, microphone and speaker system, a table for the teacher's laptop and equipment, private laptops of the students and wireless Internet. We used a MOODLE eLearning environment to handle the large number of participants in a highly interactive, tutorial-style course environment. Moreover, the students were organized in five GOOGLE groups not accessed by the course instructor, but led by elected student group leaders and their deputies. During the course, the instructor defined three principle topics for each of the groups within the overall theme Past Climate Changes. After having defined sub-themes within the groups for each student, the course culminated in the presentation of the project work as conference-style posters, 200-word abstracts and one-hour sessions with 10-15 two-minute presentations, chaired by the project leaders and their deputies. The course inspired a new textbook that will appear later this year, using a similar concept as its sister book MATLAB Recipes for Earth Sciences-3rd Edition (Trauth, Springer 2010).

Mapping erodibility in dust source regions based on geomorphology, meteorology, and remote sensing

NASA Astrophysics Data System (ADS)

Parajuli, Sagar Prasad; Yang, Zong-Liang; Kocurek, Gary

2014-09-01

Mineral dust in the atmosphere has implications for Earth's radiation budget, biogeochemical cycles, hydrological cycles, human health, and visibility. Currently, the simulated vertical mass flux of dust differs greatly among the existing dust models. While most of the models utilize an erodibility factor to characterize dust sources, this factor is assumed to be static, without sufficient characterization of the highly heterogeneous and dynamic nature of dust source regions. We present a high-resolution land cover map of the Middle East and North Africa (MENA) in which the terrain is classified by visually examining satellite images obtained from Google Earth Professional and Environmental Systems Research Institute Basemap. We show that the correlation between surface wind speed and Moderate Resolution Imaging Spectroradiometer deep blue aerosol optical depth (AOD) can be used as a proxy for erodibility, which satisfactorily represents the spatiotemporal distribution of soil-derived dust sources. This method also identifies agricultural dust sources and eliminates the satellite-observed dust component that arises from long-range transport, pollution, and biomass burning. The erodible land cover of the MENA region is grouped into nine categories: (1) bedrock: with sediment, (2) sand deposit, (3) sand deposit: on bedrock, (4) sand deposit: stabilized, (5) agricultural and urban area, (6) fluvial system, (7) stony surface, (8) playa/sabkha, and (9) savanna/grassland. Our results indicate that erodibility is linked to the land cover type and has regional variation. An improved land cover map, which explicitly accounts for sediment supply, availability, and transport capacity, may be necessary to represent the highly dynamic nature of dust sources in climate models.

Interpretation of earthquake-induced landslides triggered by the 12 May 2008, M7.9 Wenchuan earthquake in the Beichuan area, Sichuan Province, China using satellite imagery and Google Earth

USGS Publications Warehouse

Sato, H.P.; Harp, E.L.

2009-01-01

The 12 May 2008 M7.9 Wenchuan earthquake in the People's Republic of China represented a unique opportunity for the international community to use commonly available GIS (Geographic Information System) tools, like Google Earth (GE), to rapidly evaluate and assess landslide hazards triggered by the destructive earthquake and its aftershocks. In order to map earthquake-triggered landslides, we provide details on the applicability and limitations of publicly available 3-day-post- and pre-earthquake imagery provided by GE from the FORMOSAT-2 (formerly ROCSAT-2; Republic of China Satellite 2). We interpreted landslides on the 8-m-resolution FORMOSAT-2 image by GE; as a result, 257 large landslides were mapped with the highest concentration along the Beichuan fault. An estimated density of 0.3 landslides/km2 represents a minimum bound on density given the resolution of available imagery; higher resolution data would have identified more landslides. This is a preliminary study, and further study is needed to understand the landslide characteristics in detail. Although it is best to obtain landslide locations and measurements from satellite imagery having high resolution, it was found that GE is an effective and rapid reconnaissance tool. ?? 2009 Springer-Verlag.

Epidemiologic study of residential proximity to transmission lines and childhood cancer in California: description of design, epidemiologic methods and study population

PubMed Central

Kheifets, Leeka; Crespi, Catherine M; Hooper, Chris; Oksuzyan, Sona; Cockburn, Myles; Ly, Thomas; Mezei, Gabor

2015-01-01

We conducted a large epidemiologic case-control study in California to examine the association between childhood cancer risk and distance from the home address at birth to the nearest high-voltage overhead transmission line as a replication of the study of Draper et al. in the United Kingdom. We present a detailed description of the study design, methods of case ascertainment, control selection, exposure assessment and data analysis plan. A total of 5788 childhood leukemia cases and 3308 childhood central nervous system cancer cases (included for comparison) and matched controls were available for analysis. Birth and diagnosis addresses of cases and birth addresses of controls were geocoded. Distance from the home to nearby overhead transmission lines was ascertained on the basis of the electric power companies’ geographic information system (GIS) databases, additional Google Earth aerial evaluation and site visits to selected residences. We evaluated distances to power lines up to 2000 m and included consideration of lower voltages (60–69 kV). Distance measures based on GIS and Google Earth evaluation showed close agreement (Pearson correlation >0.99). Our three-tiered approach to exposure assessment allowed us to achieve high specificity, which is crucial for studies of rare diseases with low exposure prevalence. PMID:24045429

A two-stage cluster sampling method using gridded population data, a GIS, and Google Earth(TM) imagery in a population-based mortality survey in Iraq.

PubMed

Galway, Lp; Bell, Nathaniel; Sae, Al Shatari; Hagopian, Amy; Burnham, Gilbert; Flaxman, Abraham; Weiss, Wiliam M; Rajaratnam, Julie; Takaro, Tim K

2012-04-27

Mortality estimates can measure and monitor the impacts of conflict on a population, guide humanitarian efforts, and help to better understand the public health impacts of conflict. Vital statistics registration and surveillance systems are rarely functional in conflict settings, posing a challenge of estimating mortality using retrospective population-based surveys. We present a two-stage cluster sampling method for application in population-based mortality surveys. The sampling method utilizes gridded population data and a geographic information system (GIS) to select clusters in the first sampling stage and Google Earth TM imagery and sampling grids to select households in the second sampling stage. The sampling method is implemented in a household mortality study in Iraq in 2011. Factors affecting feasibility and methodological quality are described. Sampling is a challenge in retrospective population-based mortality studies and alternatives that improve on the conventional approaches are needed. The sampling strategy presented here was designed to generate a representative sample of the Iraqi population while reducing the potential for bias and considering the context specific challenges of the study setting. This sampling strategy, or variations on it, are adaptable and should be considered and tested in other conflict settings.

A two-stage cluster sampling method using gridded population data, a GIS, and Google EarthTM imagery in a population-based mortality survey in Iraq

PubMed Central

2012-01-01

Background Mortality estimates can measure and monitor the impacts of conflict on a population, guide humanitarian efforts, and help to better understand the public health impacts of conflict. Vital statistics registration and surveillance systems are rarely functional in conflict settings, posing a challenge of estimating mortality using retrospective population-based surveys. Results We present a two-stage cluster sampling method for application in population-based mortality surveys. The sampling method utilizes gridded population data and a geographic information system (GIS) to select clusters in the first sampling stage and Google Earth TM imagery and sampling grids to select households in the second sampling stage. The sampling method is implemented in a household mortality study in Iraq in 2011. Factors affecting feasibility and methodological quality are described. Conclusion Sampling is a challenge in retrospective population-based mortality studies and alternatives that improve on the conventional approaches are needed. The sampling strategy presented here was designed to generate a representative sample of the Iraqi population while reducing the potential for bias and considering the context specific challenges of the study setting. This sampling strategy, or variations on it, are adaptable and should be considered and tested in other conflict settings. PMID:22540266

a Map Mash-Up Application: Investigation the Temporal Effects of Climate Change on Salt Lake Basin

NASA Astrophysics Data System (ADS)

Kirtiloglu, O. S.; Orhan, O.; Ekercin, S.

2016-06-01

The main purpose of this paper is to investigate climate change effects that have been occurred at the beginning of the twenty-first century at the Konya Closed Basin (KCB) located in the semi-arid central Anatolian region of Turkey and particularly in Salt Lake region where many major wetlands located in and situated in KCB and to share the analysis results online in a Web Geographical Information System (GIS) environment. 71 Landsat 5-TM, 7-ETM+ and 8-OLI images and meteorological data obtained from 10 meteorological stations have been used at the scope of this work. 56 of Landsat images have been used for extraction of Salt Lake surface area through multi-temporal Landsat imagery collected from 2000 to 2014 in Salt lake basin. 15 of Landsat images have been used to make thematic maps of Normalised Difference Vegetation Index (NDVI) in KCB, and 10 meteorological stations data has been used to generate the Standardized Precipitation Index (SPI), which was used in drought studies. For the purpose of visualizing and sharing the results, a Web GIS-like environment has been established by using Google Maps and its useful data storage and manipulating product Fusion Tables which are all Google's free of charge Web service elements. The infrastructure of web application includes HTML5, CSS3, JavaScript, Google Maps API V3 and Google Fusion Tables API technologies. These technologies make it possible to make effective "Map Mash-Ups" involving an embedded Google Map in a Web page, storing the spatial or tabular data in Fusion Tables and add this data as a map layer on embedded map. The analysing process and map mash-up application have been discussed in detail as the main sections of this paper.

A Google Glass navigation system for ultrasound and fluorescence dual-mode image-guided surgery

NASA Astrophysics Data System (ADS)

Zhang, Zeshu; Pei, Jing; Wang, Dong; Hu, Chuanzhen; Ye, Jian; Gan, Qi; Liu, Peng; Yue, Jian; Wang, Benzhong; Shao, Pengfei; Povoski, Stephen P.; Martin, Edward W.; Yilmaz, Alper; Tweedle, Michael F.; Xu, Ronald X.

2016-03-01

Surgical resection remains the primary curative intervention for cancer treatment. However, the occurrence of a residual tumor after resection is very common, leading to the recurrence of the disease and the need for re-resection. We develop a surgical Google Glass navigation system that combines near infrared fluorescent imaging and ultrasonography for intraoperative detection of sites of tumor and assessment of surgical resection boundaries, well as for guiding sentinel lymph node (SLN) mapping and biopsy. The system consists of a monochromatic CCD camera, a computer, a Google Glass wearable headset, an ultrasonic machine and an array of LED light sources. All the above components, except the Google Glass, are connected to a host computer by a USB or HDMI port. Wireless connection is established between the glass and the host computer for image acquisition and data transport tasks. A control program is written in C++ to call OpenCV functions for image calibration, processing and display. The technical feasibility of the system is tested in both tumor simulating phantoms and in a human subject. When the system is used for simulated phantom resection tasks, the tumor boundaries, invisible to the naked eye, can be clearly visualized with the surgical Google Glass navigation system. This system has also been used in an IRB approved protocol in a single patient during SLN mapping and biopsy in the First Affiliated Hospital of Anhui Medical University, demonstrating the ability to successfully localize and resect all apparent SLNs. In summary, our tumor simulating phantom and human subject studies have demonstrated the technical feasibility of successfully using the proposed goggle navigation system during cancer surgery.

A Visual Analytics Paradigm Enabling Trillion-Edge Graph Exploration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wong, Pak C.; Haglin, David J.; Gillen, David S.

We present a visual analytics paradigm and a system prototype for exploring web-scale graphs. A web-scale graph is described as a graph with ~one trillion edges and ~50 billion vertices. While there is an aggressive R&D effort in processing and exploring web-scale graphs among internet vendors such as Facebook and Google, visualizing a graph of that scale still remains an underexplored R&D area. The paper describes a nontraditional peek-and-filter strategy that facilitates the exploration of a graph database of unprecedented size for visualization and analytics. We demonstrate that our system prototype can 1) preprocess a graph with ~25 billion edgesmore » in less than two hours and 2) support database query and visualization on the processed graph database afterward. Based on our computational performance results, we argue that we most likely will achieve the one trillion edge mark (a computational performance improvement of 40 times) for graph visual analytics in the near future.« less

Moon Color Visualizations

NASA Image and Video Library

1996-01-29

These color visualizations of the Moon were obtained by NASA Galileo spacecraft as it left the Earth after completing its first Earth Gravity Assist. The images were acquired Dec. 8-9, 1990. http://photojournal.jpl.nasa.gov/catalog/PIA00075

MARGINS mini-lessons: A tour of the Mariana Subduction System (Invited)

NASA Astrophysics Data System (ADS)

Goodliffe, A. M.; Oakley, A.

2009-12-01

MARGINS mini-lessons provide an efficient way to quickly move cutting edge MARGINS research into the university classroom. Instructors who are not necessarily familiar with the MARGINS program can easily use mini-lessons in a variety of educational settings. The mini-lesson described herein is centered on bathymetric and multi-channel seismic data collected during a 2003 NSF-MARGINS funded marine geophysical survey in the Mariana Basin. Designed as an approximately sixty minute lecture segment, the lesson covers both the techniques used to collect marine geophysical data and a description of the geology of the system. All geological provinces are included, from the subducting Pacific Plate in the east to the remnant arc in the west. Representative seismic lines and bathymetric images are presented for each province, along with a description of key processes including deformation of the subducting plate, serpentinite mud volcanism, forearc faulting, potentially tsunamigenic landslides, arc volcanism, and backarc spreading. The Mariana subduction system mini-lesson requires a computer with an internet connection, powerpoint, Google Earth, and a web-browser. Questions are embedded in the powerpoint presentation that can be adapted to a specific interactive response system as needed. Optimally the lesson should be used in parallel with a GeoWall. A 3-dimensional ArcScene visualization of the Mariana system is available for download through the MARGINS mini-lessons web site. Such visualizations are particularly effective in helping students understand complex three-dimensional systems. If presented in a computer lab students will benefit from being able to explore the Mariana system using tools such as GeoMapApp.

Customer-oriented Data Formats and Services for Global Land Data Assimilation System (GLDAS) Products at the NASA GES DISC

NASA Astrophysics Data System (ADS)

Fang, H.; Kato, H.; Rodell, M.; Teng, W. L.; Vollmer, B. E.

2008-12-01

The Global Land Data Assimilation System (GLDAS) has been generating a series of land surface state (e.g., soil moisture and surface temperature) and flux (e.g., evaporation and sensible heat flux) products, simulated by four land surface models (CLM, Mosaic, Noah and VIC). These products are now accessible at the Hydrology Data and Information Services Center (HDISC), a component of the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). Current GLDAS data hosted at HDISC include a set of 1.0° data products, covering 1979 to the present, from the four models and a 0.25° data product, covering 2000 to the present, from the Noah model. In addition to the basic anonymous ftp data downloading, users can avail themselves of several advanced data search and downloading services, such as Mirador and OPeNDAP. Mirador is a Google-based search tool that provides keywords searching, on-the-fly spatial and parameter subsetting of selected data. OPeNDAP (Open-source Project for a Network Data Access Protocol) enables remote OPeNDAP clients to access OPeNDAP served data regardless of local storage format. Additional data services to be available in the near future from HDISC include (1) on-the-fly converter of GLDAS to NetCDF and binary data formats; (2) temporal aggregation of GLDAS files; and (3) Giovanni, an online visualization and analysis tool that provides a simple way to visualize, analyze, and access vast amounts of data without having to download the data.

Science Center Public Forums: Engaging Lay-Publics in Resilience Deliberations Through Informal Science Education

NASA Astrophysics Data System (ADS)

Sittenfeld, D.; Choi, F.; Farooque, M.; Helmuth, B.

2017-12-01

Because climate hazards present a range of potential impacts and considerations for different kinds of stakeholders, community responses to increase resilience are best considered through the inclusion of diverse, informed perspectives. The Science Center Public Forums project has created multifaceted modules to engage diverse publics in substantive deliberations around four hazards: heat waves, drought, extreme precipitation, and sea level rise. Using a suite of background materials including visualization and narrative components, each of these daylong dialogues engage varied groups of lay-participants at eight US science centers in learning about hazard vulnerabilities and tradeoffs of proposed strategies for building resilience. Participants listen to and consider the priorities and perspectives of fellow residents and stakeholders, and work together to formulate detailed resilience plans reflecting both current science and informed public values. Deliverables for the project include visualizations of hazard vulnerabilities and strategies through immersive planetarium graphics and Google Earth, stakeholder perspective narratives, and detailed background materials for each project hazard. This session will: communicate the process for developing the hazard modules with input from subject matter experts, outline the process for iterative revisions based upon findings from formative focus groups, share results generated by participants of the project's first two pilot forums, and describe plans for broader implementation. These activities and outcomes could help to increase the capacity of informal science education institutions as trusted conveners for informed community dialogue by educating residents about vulnerabilities and engaging them in critical thinking about potential policy responses to critical climate hazards while sharing usable public values and priorities with civic planners.

Virtual Earth System Laboratory (VESL): Effective Visualization of Earth System Data and Process Simulations

NASA Astrophysics Data System (ADS)

Quinn, J. D.; Larour, E. Y.; Cheng, D. L. C.; Halkides, D. J.

2016-12-01

The Virtual Earth System Laboratory (VESL) is a Web-based tool, under development at the Jet Propulsion Laboratory and UC Irvine, for the visualization of Earth System data and process simulations. It contains features geared toward a range of applications, spanning research and outreach. It offers an intuitive user interface, in which model inputs are changed using sliders and other interactive components. Current capabilities include simulation of polar ice sheet responses to climate forcing, based on NASA's Ice Sheet System Model (ISSM). We believe that the visualization of data is most effective when tailored to the target audience, and that many of the best practices for modern Web design/development can be applied directly to the visualization of data: use of negative space, color schemes, typography, accessibility standards, tooltips, etc cetera. We present our prototype website, and invite input from potential users, including researchers, educators, and students.

Use of Openly Available Satellite Images for Remote Sensing Education

NASA Astrophysics Data System (ADS)

Wang, C.-K.

2011-09-01

With the advent of Google Earth, Google Maps, and Microsoft Bing Maps, high resolution satellite imagery are becoming more easily accessible than ever. It have been the case that the college students may already have wealth experiences with the high resolution satellite imagery by using these software and web services prior to any formal remote sensing education. It is obvious that the remote sensing education should be adjusted to the fact that the audience are already the customers of remote sensing products (through the use of the above mentioned services). This paper reports the use of openly available satellite imagery in an introductory-level remote sensing course in the Department of Geomatics of National Cheng Kung University as a term project. From the experience learned from the fall of 2009 and 2010, it shows that this term project has effectively aroused the students' enthusiastic toward Remote Sensing.

Assessing environmental features related to mental health: a reliability study of visual streetscape images.

PubMed

Wu, Yu-Tzu; Nash, Paul; Barnes, Linda E; Minett, Thais; Matthews, Fiona E; Jones, Andy; Brayne, Carol

2014-10-22

An association between depressive symptoms and features of built environment has been reported in the literature. A remaining research challenge is the development of methods to efficiently capture pertinent environmental features in relevant study settings. Visual streetscape images have been used to replace traditional physical audits and directly observe the built environment of communities. The aim of this work is to examine the inter-method reliability of the two audit methods for assessing community environments with a specific focus on physical features related to mental health. Forty-eight postcodes in urban and rural areas of Cambridgeshire, England were randomly selected from an alphabetical list of streets hosted on a UK property website. The assessment was conducted in July and August 2012 by both physical and visual image audits based on the items in Residential Environment Assessment Tool (REAT), an observational instrument targeting the micro-scale environmental features related to mental health in UK postcodes. The assessor used the images of Google Street View and virtually "walked through" the streets to conduct the property and street level assessments. Gwet's AC1 coefficients and Bland-Altman plots were used to compare the concordance of two audits. The results of conducting the REAT by visual image audits generally correspond to direct observations. More variations were found in property level items regarding physical incivilities, with broad limits of agreement which importantly lead to most of the variation in the overall REAT score. Postcodes in urban areas had lower consistency between the two methods than rural areas. Google Street View has the potential to assess environmental features related to mental health with fair reliability and provide a less resource intense method of assessing community environments than physical audits.

Stepping Into Science Data: Data Visualization in Virtual Reality

NASA Astrophysics Data System (ADS)

Skolnik, S.

2017-12-01

Have you ever seen people get really excited about science data? Navteca, along with the Earth Science Technology Office (ESTO), within the Earth Science Division of NASA's Science Mission Directorate have been exploring virtual reality (VR) technology for the next generation of Earth science technology information systems. One of their first joint experiments was visualizing climate data from the Goddard Earth Observing System Model (GEOS) in VR, and the resulting visualizations greatly excited the scientific community. This presentation will share the value of VR for science, such as the capability of permitting the observer to interact with data rendered in real-time, make selections, and view volumetric data in an innovative way. Using interactive VR hardware (headset and controllers), the viewer steps into the data visualizations, physically moving through three-dimensional structures that are traditionally displayed as layers or slices, such as cloud and storm systems from NASA's Global Precipitation Measurement (GPM). Results from displaying this precipitation and cloud data show that there is interesting potential for scientific visualization, 3D/4D visualizations, and inter-disciplinary studies using VR. Additionally, VR visualizations can be leveraged as 360 content for scientific communication and outreach and VR can be used as a tool to engage policy and decision makers, as well as the public.

Digital Earth reloaded - Beyond the next generation

NASA Astrophysics Data System (ADS)

Ehlers, M.; Woodgate, P.; Annoni, A.; Schade, S.

2014-02-01

Digital replicas (or 'mirror worlds') of complex entities and systems are now routine in many fields such as aerospace engineering; archaeology; medicine; or even fashion design. The Digital Earth (DE) concept as a digital replica of the entire planet occurs in Al Gore's 1992 book Earth in the Balance and was popularized in his speech at the California Science Center in January 1998. It played a pivotal role in stimulating the development of a first generation of virtual globes, typified by Google Earth that achieved many elements of this vision. Almost 15 years after Al Gore's speech, the concept of DE needs to be re-evaluated in the light of the many scientific and technical developments in the fields of information technology, data infrastructures, citizen?s participation, and earth observation that have taken place since. This paper intends to look beyond the next generation predominantly based on the developments of fields outside the spatial sciences, where concepts, software, and hardware with strong relationships to DE are being developed without referring to this term. It also presents a number of guiding criteria for future DE developments.

Enhancing Geologic Education in Grades 5-12: Creating Virtual Field Trips

NASA Astrophysics Data System (ADS)

Vitek, J. D.; Gamache, K. R.; Giardino, J. R.; Schroeder, C. E.

2011-12-01

New tools of technology enhance and facilitate the ability to bring the "field experience" into the classroom as part of the effort necessary to turn students onto the geosciences. The real key is high-speed computers and high-definition cameras with which to capture visual images. Still and movie data are easily obtained as are large and small-scale images from space, available through "Google Earth°". GPS information provides accurate location data to enhance mapping efforts. One no longer needs to rely on commercial ventures to show students any aspect of the "real" world. The virtual world is a viable replacement. The new cost-effective tools mean everyone can be a producer of information critical to understanding Earth. During the last four summers (2008-2011), Texas teachers have participated in G-Camp, an effort to instill geologic and geomorphic knowledge such that the information will make its way into classrooms. Teachers have acquired thousands of images and developed concepts that are being used to enhance their ability to promote geology in their classrooms. Texas will soon require four years of science at the high-school level, and we believe that geology or Earth science needs to be elevated to the required level of biology, chemistry and physics. Teachers need to be trained and methodology developed that is exciting to students. After all, everyone on Earth needs to be aware of the hazardous nature of geologic events not just to pass an exam, but for a lifetime. We use a video, which is a composite of our ventures, to show how data collected during these trips can be used in the classroom. . Social media, Facebook°, blogs, and email facilitate sharing information such that everyone can learn from each other about the best way to do things. New tools of technology are taking their place in every classroom to take advantage of the skills students bring to the learning environment. Besides many of these approaches are common to video gaming, and certainly, education cannot be too far behind.

Baseline coastal oblique aerial photographs collected from Key Largo, Florida, to the Florida/Georgia border, September 5-6, 2014

USGS Publications Warehouse

Morgan, Karen L. M.

2015-09-14

In addition to the photographs, a Google Earth Keyhole Markup Language (KML) file is provided and can be used to view the images by clicking on the marker and then clicking on either the thumbnail or the link above the thumbnail. The KML files were created using the photographic navigation files. These KML files can be found in the kml folder.

Isosurface Display of 3-D Scalar Fields from a Meteorological Model on Google Earth

DTIC Science & Technology

2013-07-01

facets to four, we have chosen to adopt and implement a revised method discussed and made available by Bourke (1994), which can accommodate up to...five facets for a given grid cube. While the published code from Bourke (1994) is in the public domain, it was originally implemented in the C...and atmospheric temperatures. 17 4. References Bourke , P. Polygonising a Scalar Field. http://paulbourke.net/geometry/polygonise

Effects of Spatial Ability, Gender Differences, and Pictorial Training on Children Using 2-D and 3-D Environments to Recall Landmark Locations from Memory

ERIC Educational Resources Information Center

Kopcha, Theodore J.; Otumfuor, Beryl A.; Wang, Lu

2015-01-01

This study examines the effects of spatial ability, gender differences, and pictorial training on fourth grade students' ability to recall landmark locations from memory. Ninety-six students used Google Earth over a 3-week period to locate landmarks (3-D) and mark their location on a 2-D topographical map. Analysis of covariance on posttest scores…

Too Cool for School? No Way! Using the TPACK Framework: You Can Have Your Hot Tools and Teach with Them, Too

ERIC Educational Resources Information Center

Mishra, Punya; Koehler, Matthew

2009-01-01

This is the age of cool tools. Facebook, iPhone, Flickr, blogs, cloud computing, Smart Boards, YouTube, Google Earth, and GPS are just a few examples of new technologies that bombard people from all directions. As individuals people see a new technology and can appreciate its coolness, but as educators they wonder how these tools can be used for…

The Feasibility and Acceptability of Google Glass for Teletoxicology Consults.

PubMed

Chai, Peter R; Babu, Kavita M; Boyer, Edward W

2015-09-01

Teletoxicology offers the potential for toxicologists to assist in providing medical care at remote locations, via remote, interactive augmented audiovisual technology. This study examined the feasibility of using Google Glass, a head-mounted device that incorporates a webcam, viewing prism, and wireless connectivity, to assess the poisoned patient by a medical toxicology consult staff. Emergency medicine residents (resident toxicology consultants) rotating on the toxicology service wore Glass during bedside evaluation of poisoned patients; Glass transmitted real-time video of patients' physical examination findings to toxicology fellows and attendings (supervisory consultants), who reviewed these findings. We evaluated the usability (e.g., quality of connectivity and video feeds) of Glass by supervisory consultants, as well as attitudes towards use of Glass. Resident toxicology consultants and supervisory consultants completed 18 consults through Glass. Toxicologists viewing the video stream found the quality of audio and visual transmission usable in 89 % of cases. Toxicologists reported their management of the patient changed after viewing the patient through Glass in 56 % of cases. Based on findings obtained through Glass, toxicologists recommended specific antidotes in six cases. Head-mounted devices like Google Glass may be effective tools for real-time teletoxicology consultation.

iAnn: an event sharing platform for the life sciences.

PubMed

Jimenez, Rafael C; Albar, Juan P; Bhak, Jong; Blatter, Marie-Claude; Blicher, Thomas; Brazas, Michelle D; Brooksbank, Cath; Budd, Aidan; De Las Rivas, Javier; Dreyer, Jacqueline; van Driel, Marc A; Dunn, Michael J; Fernandes, Pedro L; van Gelder, Celia W G; Hermjakob, Henning; Ioannidis, Vassilios; Judge, David P; Kahlem, Pascal; Korpelainen, Eija; Kraus, Hans-Joachim; Loveland, Jane; Mayer, Christine; McDowall, Jennifer; Moran, Federico; Mulder, Nicola; Nyronen, Tommi; Rother, Kristian; Salazar, Gustavo A; Schneider, Reinhard; Via, Allegra; Villaveces, Jose M; Yu, Ping; Schneider, Maria V; Attwood, Teresa K; Corpas, Manuel

2013-08-01

We present iAnn, an open source community-driven platform for dissemination of life science events, such as courses, conferences and workshops. iAnn allows automatic visualisation and integration of customised event reports. A central repository lies at the core of the platform: curators add submitted events, and these are subsequently accessed via web services. Thus, once an iAnn widget is incorporated into a website, it permanently shows timely relevant information as if it were native to the remote site. At the same time, announcements submitted to the repository are automatically disseminated to all portals that query the system. To facilitate the visualization of announcements, iAnn provides powerful filtering options and views, integrated in Google Maps and Google Calendar. All iAnn widgets are freely available. http://iann.pro/iannviewer manuel.corpas@tgac.ac.uk.

NASA's Earth Observations of the Global Environment

NASA Technical Reports Server (NTRS)

King, Michael D.

2005-01-01

A birds eye view of the Earth from afar and up close reveals the power and magnificence of the Earth and juxtaposes the simultaneous impacts and powerlessness of humankind. The NASA Electronic Theater presents Earth science observations and visualizations in an historical perspective. Fly in from outer space to Africa and Cape Town. See the latest spectacular images from NASA & NOAA remote sensing missions like Meteosat, TRMM, Landsat 7, and Terra, which will be visualized and explained in the context of global change. See visualizations of global data sets currently available from Earth orbiting satellites, including the Earth at night with its city lights, aerosols from biomass burning in the Middle East and Africa, and retreat of the glaciers on Mt. Kilimanjaro. See the dynamics of vegetation growth and decay over Africa over 17 years. New visualization tools allow us to roam & zoom through massive global mosaic images including Landsat and Terra tours of Africa and South America, showing land use and land cover change from Bolivian highlands. Spectacular new visualizations of the global atmosphere & oceans are shown. See massive dust storms sweeping across Africa and across the Atlantic to the Caribbean and Amazon basin. See ocean vortexes and currents that bring up the nutrients to feed tiny phytoplankton and draw the fish, pant whales and fisher- man. See how the ocean blooms in response to these currents and El Nino/La Nifia. We will illustrate these and other topics with a dynamic theater-style presentation, along with animations of satellite launch deployments and orbital mapping to highlight aspects of Earth observations from space.

Earth Science Multimedia Theater

NASA Technical Reports Server (NTRS)

Hasler, A. F.

1998-01-01

The presentation will begin with the latest 1998 NASA Earth Science Vision for the next 25 years. A compilation of the 10 days of animations of Hurricane Georges which were supplied daily on NASA to Network television will be shown. NASA's visualizations of Hurricane Bonnie which appeared in the Sept 7 1998 issue of TIME magazine. Highlights will be shown from the NASA hurricane visualization resource video tape that has been used repeatedly this season on network TV. Results will be presented from a new paper on automatic wind measurements in Hurricane Luis from 1 -min GOES images that will appear in the October BAMS. The visualizations are produced by the Goddard Visualization & Analysis Laboratory, and Scientific Visualization Studio, as well as other Goddard and NASA groups using NASA, NOAA, ESA, and NASDA Earth science datasets. Visualizations will be shown from the "Digital-HyperRes-Panorama" Earth Science ETheater'98 recently presented in Tokyo, Paris and Phoenix. The presentation in Paris used a SGI/CRAY Onyx Infinite Reality Super Graphics Workstation at 2560 X 1024 resolution with dual synchronized video Epson 71 00 projectors on a 20ft wide screen. Earth Science Electronic Theater '999 is being prepared for a December 1 st showing at NASA HQ in Washington and January presentation at the AMS meetings in Dallas. The 1999 version of the Etheater will be triple wide with at resolution of 3840 X 1024 on a 60 ft wide screen. Visualizations will also be featured from the new Earth Today Exhibit which was opened by Vice President Gore on July 2, 1998 at the Smithsonian Air & Space Museum in Washington, as well as those presented for possible use at the American Museum of Natural History (NYC), Disney EPCOT, and other venues. New methods are demonstrated for visualizing, interpreting, comparing, organizing and analyzing immense Hyperimage remote sensing datasets and three dimensional numerical model results. We call the data from many new Earth sensing satellites, Hyperimage datasets, because they have such high resolution in the spectral, temporal, spatial, and dynamic range domains. The traditional numerical spreadsheet paradigm has been extended to develop a scientific visualization approach for processing Hyperimage datasets and 3D model results interactively. The advantages of extending the powerful spreadsheet style of computation to multiple sets of images and organizing image processing were demonstrated using the Distributed Image SpreadSheet (DISS).

Illuminating Northern California’s Active Faults

USGS Publications Warehouse

Prentice, Carol S.; Crosby, Christopher J.; Whitehill, Caroline S.; Arrowsmith, J. Ramon; Furlong, Kevin P.; Philips, David A.

2009-01-01

Newly acquired light detection and ranging (lidar) topographic data provide a powerful community resource for the study of landforms associated with the plate boundary faults of northern California (Figure 1). In the spring of 2007, GeoEarthScope, a component of the EarthScope Facility construction project funded by the U.S. National Science Foundation, acquired approximately 2000 square kilometers of airborne lidar topographic data along major active fault zones of northern California. These data are now freely available in point cloud (x, y, z coordinate data for every laser return), digital elevation model (DEM), and KMZ (zipped Keyhole Markup Language, for use in Google EarthTM and other similar software) formats through the GEON OpenTopography Portal (http://www.OpenTopography.org/data). Importantly, vegetation can be digitally removed from lidar data, producing high-resolution images (0.5- or 1.0-meter DEMs) of the ground surface beneath forested regions that reveal landforms typically obscured by vegetation canopy (Figure 2)

Facilitating NASA Earth Science Data Processing Using Nebula Cloud Computing

NASA Astrophysics Data System (ADS)

Chen, A.; Pham, L.; Kempler, S.; Theobald, M.; Esfandiari, A.; Campino, J.; Vollmer, B.; Lynnes, C.

2011-12-01

Cloud Computing technology has been used to offer high-performance and low-cost computing and storage resources for both scientific problems and business services. Several cloud computing services have been implemented in the commercial arena, e.g. Amazon's EC2 & S3, Microsoft's Azure, and Google App Engine. There are also some research and application programs being launched in academia and governments to utilize Cloud Computing. NASA launched the Nebula Cloud Computing platform in 2008, which is an Infrastructure as a Service (IaaS) to deliver on-demand distributed virtual computers. Nebula users can receive required computing resources as a fully outsourced service. NASA Goddard Earth Science Data and Information Service Center (GES DISC) migrated several GES DISC's applications to the Nebula as a proof of concept, including: a) The Simple, Scalable, Script-based Science Processor for Measurements (S4PM) for processing scientific data; b) the Atmospheric Infrared Sounder (AIRS) data process workflow for processing AIRS raw data; and c) the GES-DISC Interactive Online Visualization ANd aNalysis Infrastructure (GIOVANNI) for online access to, analysis, and visualization of Earth science data. This work aims to evaluate the practicability and adaptability of the Nebula. The initial work focused on the AIRS data process workflow to evaluate the Nebula. The AIRS data process workflow consists of a series of algorithms being used to process raw AIRS level 0 data and output AIRS level 2 geophysical retrievals. Migrating the entire workflow to the Nebula platform is challenging, but practicable. After installing several supporting libraries and the processing code itself, the workflow is able to process AIRS data in a similar fashion to its current (non-cloud) configuration. We compared the performance of processing 2 days of AIRS level 0 data through level 2 using a Nebula virtual computer and a local Linux computer. The result shows that Nebula has significantly better performance than the local machine. Much of the difference was due to newer equipment in the Nebula than the legacy computer, which is suggestive of a potential economic advantage beyond elastic power, i.e., access to up-to-date hardware vs. legacy hardware that must be maintained past its prime to amortize the cost. In addition to a trade study of advantages and challenges of porting complex processing to the cloud, a tutorial was developed to enable further progress in utilizing the Nebula for Earth Science applications and understanding better the potential for Cloud Computing in further data- and computing-intensive Earth Science research. In particular, highly bursty computing such as that experienced in the user-demand-driven Giovanni system may become more tractable in a Cloud environment. Our future work will continue to focus on migrating more GES DISC's applications/instances, e.g. Giovanni instances, to the Nebula platform and making matured migrated applications to be in operation on the Nebula.

Using Google Glass in Nonsurgical Medical Settings: Systematic Review.

PubMed

Dougherty, Bryn; Badawy, Sherif M

2017-10-19

Wearable technologies provide users hands-free access to computer functions and are becoming increasingly popular on both the consumer market and in various industries. The medical industry has pioneered research and implementation of head-mounted wearable devices, such as Google Glass. Most of this research has focused on surgical interventions; however, other medical fields have begun to explore the potential of this technology to support both patients and clinicians. Our aim was to systematically evaluate the feasibility, usability, and acceptability of using Google Glass in nonsurgical medical settings and to determine the benefits, limitations, and future directions of its application. This review covers literature published between January 2013 and May 2017. Searches included PubMed MEDLINE, Embase, INSPEC (Ebsco), Cochrane Central Register of Controlled Trials (CENTRAL), IEEE Explore, Web of Science, Scopus, and Compendex. The search strategy sought all articles on Google Glass. Two reviewers independently screened titles and abstracts, assessed full-text articles, and extracted data from articles that met all predefined criteria. Any disagreements were resolved by discussion or consultation by the senior author. Included studies were original research articles that evaluated the feasibility, usability, or acceptability of Google Glass in nonsurgical medical settings. The preferred reporting results of systematic reviews and meta-analyses (PRISMA) guidelines were followed for reporting of results. Of the 852 records examined, 51 met all predefined criteria, including patient-centered (n=21) and clinician-centered studies (n=30). Patient-centered studies explored the utility of Google Glass in supporting patients with motor impairments (n=8), visual impairments (n=5), developmental and psychiatric disorders (n=2), weight management concerns (n=3), allergies (n=1), or other health concerns (n=2). Clinician-centered studies explored the utility of Google Glass in student training (n=9), disaster relief (n=4), diagnostics (n=2), nursing (n=1), autopsy and postmortem examination (n=1), wound care (n=1), behavioral sciences (n=1), and various medical subspecialties, including, cardiology (n=3), radiology (n=3), neurology (n=1), anesthesiology (n=1), pulmonology (n=1), toxicology (n=1), and dermatology (n=1). Most of the studies were conducted in the United States (40/51, 78%), did not report specific age information for participants (38/51, 75%), had sample size <30 participants (29/51, 57%), and were pilot or feasibility studies (31/51, 61%). Most patient-centered studies (19/21, 90%) demonstrated feasibility with high satisfaction and acceptability among participants, despite a few technical challenges with the device. A number of clinician-centered studies (11/30, 37%) reported low to moderate satisfaction among participants, with the most promising results being in the area of student training. Studies varied in sample size, approach for implementation of Google Glass, and outcomes assessment. The use of Google Glass in nonsurgical medical settings varied. More promising results regarding the feasibility, usability, and acceptability of using Google Glass were seen in patient-centered studies and student training settings. Further research evaluating the efficacy and cost-effectiveness of Google Glass as an intervention to improve important clinical outcomes is warranted. ©Bryn Dougherty, Sherif M Badawy. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 19.10.2017.

Using Google Glass in Nonsurgical Medical Settings: Systematic Review

PubMed Central

Dougherty, Bryn

2017-01-01

Background Wearable technologies provide users hands-free access to computer functions and are becoming increasingly popular on both the consumer market and in various industries. The medical industry has pioneered research and implementation of head-mounted wearable devices, such as Google Glass. Most of this research has focused on surgical interventions; however, other medical fields have begun to explore the potential of this technology to support both patients and clinicians. Objective Our aim was to systematically evaluate the feasibility, usability, and acceptability of using Google Glass in nonsurgical medical settings and to determine the benefits, limitations, and future directions of its application. Methods This review covers literature published between January 2013 and May 2017. Searches included PubMed MEDLINE, Embase, INSPEC (Ebsco), Cochrane Central Register of Controlled Trials (CENTRAL), IEEE Explore, Web of Science, Scopus, and Compendex. The search strategy sought all articles on Google Glass. Two reviewers independently screened titles and abstracts, assessed full-text articles, and extracted data from articles that met all predefined criteria. Any disagreements were resolved by discussion or consultation by the senior author. Included studies were original research articles that evaluated the feasibility, usability, or acceptability of Google Glass in nonsurgical medical settings. The preferred reporting results of systematic reviews and meta-analyses (PRISMA) guidelines were followed for reporting of results. Results Of the 852 records examined, 51 met all predefined criteria, including patient-centered (n=21) and clinician-centered studies (n=30). Patient-centered studies explored the utility of Google Glass in supporting patients with motor impairments (n=8), visual impairments (n=5), developmental and psychiatric disorders (n=2), weight management concerns (n=3), allergies (n=1), or other health concerns (n=2). Clinician-centered studies explored the utility of Google Glass in student training (n=9), disaster relief (n=4), diagnostics (n=2), nursing (n=1), autopsy and postmortem examination (n=1), wound care (n=1), behavioral sciences (n=1), and various medical subspecialties, including, cardiology (n=3), radiology (n=3), neurology (n=1), anesthesiology (n=1), pulmonology (n=1), toxicology (n=1), and dermatology (n=1). Most of the studies were conducted in the United States (40/51, 78%), did not report specific age information for participants (38/51, 75%), had sample size <30 participants (29/51, 57%), and were pilot or feasibility studies (31/51, 61%). Most patient-centered studies (19/21, 90%) demonstrated feasibility with high satisfaction and acceptability among participants, despite a few technical challenges with the device. A number of clinician-centered studies (11/30, 37%) reported low to moderate satisfaction among participants, with the most promising results being in the area of student training. Studies varied in sample size, approach for implementation of Google Glass, and outcomes assessment. Conclusions The use of Google Glass in nonsurgical medical settings varied. More promising results regarding the feasibility, usability, and acceptability of using Google Glass were seen in patient-centered studies and student training settings. Further research evaluating the efficacy and cost-effectiveness of Google Glass as an intervention to improve important clinical outcomes is warranted. PMID:29051136

A proposed-standard format to represent and distribute tomographic models and other earth spatial data

NASA Astrophysics Data System (ADS)

Postpischl, L.; Morelli, A.; Danecek, P.

2009-04-01

Formats used to represent (and distribute) tomographic earth models differ considerably and are rarely self-consistent. In fact, each earth scientist, or research group, uses specific conventions to encode the various parameterizations used to describe, e.g., seismic wave speed or density in three dimensions, and complete information is often found in related documents or publications (if available at all) only. As a consequence, use of various tomographic models from different authors requires considerable effort, is more cumbersome than it should be and prevents widespread exchange and circulation within the community. We propose a format, based on modern web standards, able to represent different (grid-based) model parameterizations within the same simple text-based environment, easy to write, to parse, and to visualise. The aim is the creation of self-describing data-structures, both human and machine readable, that are automatically recognised by general-purpose software agents, and easily imported in the scientific programming environment. We think that the adoption of such a representation as a standard for the exchange and distribution of earth models can greatly ease their usage and enhance their circulation, both among fellow seismologists and among a broader non-specialist community. The proposed solution uses semantic web technologies, fully fitting the current trends in data accessibility. It is based on Json (JavaScript Object Notation), a plain-text, human-readable lightweight computer data interchange format, which adopts a hierarchical name-value model for representing simple data structures and associative arrays (called objects). Our implementation allows integration of large datasets with metadata (authors, affiliations, bibliographic references, units of measure etc.) into a single resource. It is equally suited to represent other geo-referenced volumetric quantities — beyond tomographic models — as well as (structured and unstructured) computational meshes. This approach can exploit the capabilities of the web browser as a computing platform: a series of in-page quick tools for comparative analysis between models will be presented, as well as visualisation techniques for tomographic layers in Google Maps and Google Earth. We are working on tools for conversion into common scientific format like netCDF, to allow easy visualisation in GEON-IDV or gmt.

The GEON Integrated Data Viewer (IDV) for Exploration of Geoscience Data With Visualizations

NASA Astrophysics Data System (ADS)

Wier, S.; Meertens, C.

2008-12-01

The GEON Integrated Data Viewer (GEON IDV) is a fully interactive, research-level, true 3D and 4D (latitude, longitude, depth or altitude, and time) tool to display and explore almost any data located on the Earth, inside the Earth, or above the Earth's surface. Although the GEON IDV makes impressive 3D displays, it is primarily designed for data exploration and analysis. The GEON IDV is designed to meet the challenge of investigating complex, multi-variate, time-varying, three- dimensional geoscience questions anywhere on earth. The GEON IDV supports simultaneous displays of data sets of differing sources and data type or character, with complete control over map projection and area, time animation, vertical scale, and color schemes. The GEON IDV displays gridded and point data, images, GIS shape files, and other types of data, from files, HTTP servers, OPeNDAP catalogs, RSS feeds, and web map servers. GEON IDV displays include images and geology maps on 3D topographic relief surfaces, vertical geologic cross sections in their correct depth extent, tectonic plate boundaries and plate motion vectors including time animation, GPS velocity vectors and error ellipses, GPS time series at a station, earthquake locations in depth optionally colored and sized by magnitude, earthquake focal mechanisms 'beachballs,' 2D grids of gravity or magnetic anomalies, 2D grids of crustal strain imagery, seismic raypaths, seismic tomography model 3D grids as vertical and horizontal cross sections and isosurfaces, 3D grids of crust and mantle structure for any property, and time animation of 3D grids of mantle convection models as cross sections and isosurfaces. The IDV can also show tracks of aircraft, ships, drifting buoys and marine animals, colored observed values, borehole soundings, and vertical probes of 3D grids. The GEON IDV can drive a GeoWall or other 3D stereo system. IDV output files include imagery, movies, and KML files for Google Earth. The IDV has built in analysis capabilities with user-created Python language routines, and with automatic conversion of data sources with differing units and grid structures. The IDV can be scripted to create display images on user request or automatically on data arrival, offering the use of the IDV as a back end to support image generation in a data portal. Examples of GEON IDV use in seismology, geodesy, geodynamics and other fields will be shown.

Mapping rice extent map with crop intensity in south China through integration of optical and microwave images based on google earth engine

NASA Astrophysics Data System (ADS)

Zhang, X.; Wu, B.; Zhang, M.; Zeng, H.

2017-12-01

Rice is one of the main staple foods in East Asia and Southeast Asia, which has occupied more than half of the world's population with 11% of cultivated land. Study on rice can provide direct or indirect information on food security and water source management. Remote sensing has proven to be the most effective method to monitoring the cropland in large scale by using temporary and spectral information. There are two main kinds of satellite have been used to mapping rice including microwave and optical. Rice, as the main crop of paddy fields, the main feature different from other crops is flooding phenomenon at planning stage (Figure 1). Microwave satellites can penetrate through clouds and efficiency on monitoring flooding phenomenon. Meanwhile, the vegetation index based on optical satellite can well distinguish rice from other vegetation. Google Earth Engine is a cloud-based platform that makes it easy to access high-performance computing resources for processing very large geospatial datasets. Google has collected large number of remote sensing satellite data around the world, which providing researchers with the possibility of doing application by using multi-source remote sensing data in a large area. In this work, we map rice planting area in south China through integration of Landsat-8 OLI, Sentienl-2, and Sentinel-1 Synthetic Aperture Radar (SAR) images. The flowchart is shown in figure 2. First, a threshold method the VH polarized backscatter from SAR sensor and vegetation index including normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) from optical sensor were used the classify the rice extent map. The forest and water surface extent map provided by earth engine were used to mask forest and water. To overcome the problem of the "salt and pepper effect" by Pixel-based classification when the spatial resolution increased, we segment the optical image and use the pixel- based classification results to merge the object-oriented segmentation data, and finally get the rice extent map. At last, by using the time series analysis, the peak count was obtained for each rice area to ensure the crop intensity. In this work, the rice ground point from a GVG crowdsourcing smartphone and rice area statistical results from National Bureau of Statistics were used to validate and evaluate our result.

Modern Era Retrospective Restrospective-Analysis for Research and Applications (MERRA) Data and Services at the GES DISC

NASA Technical Reports Server (NTRS)

Berrick, Stephen W.; Shen, Suhung; Ostrenga, Dana

2008-01-01

The Modern Era Retrospective-analysis for Research and Applications (MERRA) dataset is a NASA satellite era, 30 year (1979 - present), reanalysis using the Goddard Earth Observing System Data Assimilation System, Version 5 (GEOS-5). The project, run out of NASA's Global Modeling and Assimilation Office at Goddard Space Flight Center, provides the science and application communities with a state-of-the-art global analysis with emphasis on improved estimates of the hydrological cycle over a broad range of weather and climate time scales. MERRA products are generated as a long-term synthesis that places the NASA EOS suite of observations in a climate context. The MERRA analysis is performed at a horizontal resolution of 2/3 longitude x 1/2 latitude (540x361 global gridpoints) with observational analyses every 6 hours. The MERRA output data will include 3 dimensional state fields for every 6 hourly analysis cycle on 42 pressure levels (or 72 terrain following model coordinate levels) from the surface through the stratosphere. Several data products are specifically designed to support chemistry and stratosphere transport modeling. The 2 dimensional surface and atmospheric diagnostics (numbering 259) are being stored on the native grid at 1 hourly intervals. These include radiation and vertical integrals of the atmosphere for water and energy budget studies and also surface diagnostics where the diurnal cycle is important. The one hourly surface and near surface data product will also facilitate research on the integrated analysis of Earth system observations in the land, ocean and cryosphere. The MERRA products are archived and distributed by the Goddard Earth Sciences Data and Information Services Center (GES DISC) through its Modeling DISC Web (MDISC) portal. Multiple data access methods and services are available for MERRA data through MDISC: (1) Mirador offers a quick, comprehensive search of MERRA and all GES DISC archived data holdings, allowing searches on keywords, location names or latitude/longitude box, and date/time, with responses within a few seconds. (2) Giovanni is a GES DISC developed Web application that provides data visualization and analysis online. Giovanni features popular visualizations such as latitude-longitude maps, animations, cross sections, profiles, time series, etc. and some basic statistical analysis functions such as scatter plots and correlation coefficient maps. Users are able to download results in several different formats, including Google Earth. (3) On-the-fly parameter subsetting of data within a spatial/temporal window is provided through a simple select and click Web page. (4) MERRA data are also available via OPeNDAP, GrADS Data Server (GDS) and can be converted to netCDF on the fly.