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).

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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…

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.

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.

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.

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)

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.

MaRGEE: Move and Rotate Google Earth Elements

NASA Astrophysics Data System (ADS)

Dordevic, Mladen M.; Whitmeyer, Steven J.

2015-12-01

Google Earth is recognized as a highly effective visualization tool for geospatial information. However, there remain serious limitations that have hindered its acceptance as a tool for research and education in the geosciences. One significant limitation is the inability to translate or rotate geometrical elements on the Google Earth virtual globe. Here we present a new JavaScript web application to "Move and Rotate Google Earth Elements" (MaRGEE). MaRGEE includes tools to simplify, translate, and rotate elements, add intermediate steps to a transposition, and batch process multiple transpositions. The transposition algorithm uses spherical geometry calculations, such as the haversine formula, to accurately reposition groups of points, paths, and polygons on the Google Earth globe without distortion. Due to the imminent deprecation of the Google Earth API and browser plugin, MaRGEE uses a Google Maps interface to facilitate and illustrate the transpositions. However, the inherent spatial distortions that result from the Google Maps Web Mercator projection are not apparent once the transposed elements are saved as a KML file and opened in Google Earth. Potential applications of the MaRGEE toolkit include tectonic reconstructions, the movements of glaciers or thrust sheets, and time-based animations of other large- and small-scale geologic processes.

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.

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.

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.

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.

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

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.

OpenNEX, a private-public partnership in support of the national climate assessment

NASA Astrophysics Data System (ADS)

Nemani, R. R.; Wang, W.; Michaelis, A.; Votava, P.; Ganguly, S.

2016-12-01

The NASA Earth Exchange (NEX) is a collaborative computing platform that has been developed with the objective of bringing scientists together with the software tools, massive global datasets, and supercomputing resources necessary to accelerate research in Earth systems science and global change. NEX is funded as an enabling tool for sustaining the national climate assessment. Over the past five years, researchers have used the NEX platform and produced a number of data sets highly relevant to the National Climate Assessment. These include high-resolution climate projections using different downscaling techniques and trends in historical climate from satellite data. To enable a broader community in exploiting the above datasets, the NEX team partnered with public cloud providers to create the OpenNEX platform. OpenNEX provides ready access to NEX data holdings on a number of public cloud platforms along with pertinent analysis tools and workflows in the form of Machine Images and Docker Containers, lectures and tutorials by experts. We will showcase some of the applications of OpenNEX data and tools by the community on Amazon Web Services, Google Cloud and the NEX Sandbox.

Curating the Web: Building a Google Custom Search Engine for the Arts

ERIC Educational Resources Information Center

Hennesy, Cody; Bowman, John

2008-01-01

Google's first foray onto the web made search simple and results relevant. With its Co-op platform, Google has taken another step toward dramatically increasing the relevancy of search results, further adapting the World Wide Web to local needs. Google Custom Search Engine, a tool on the Co-op platform, puts one in control of his or her own search…

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

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)

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.

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

Towards Large-area Field-scale Operational Evapotranspiration for Water Use Mapping

NASA Astrophysics Data System (ADS)

Senay, G. B.; Friedrichs, M.; Morton, C.; Huntington, J. L.; Verdin, J.

2017-12-01

Field-scale evapotranspiration (ET) estimates are needed for improving surface and groundwater use and water budget studies. Ideally, field-scale ET estimates would be at regional to national levels and cover long time periods. As a result of large data storage and computational requirements associated with processing field-scale satellite imagery such as Landsat, numerous challenges remain to develop operational ET estimates over large areas for detailed water use and availability studies. However, the combination of new science, data availability, and cloud computing technology is enabling unprecedented capabilities for ET mapping. To demonstrate this capability, we used Google's Earth Engine cloud computing platform to create nationwide annual ET estimates with 30-meter resolution Landsat ( 16,000 images) and gridded weather data using the Operational Simplified Surface Energy Balance (SSEBop) model in support of the National Water Census, a USGS research program designed to build decision support capacity for water management agencies and other natural resource managers. By leveraging Google's Earth Engine Application Programming Interface (API) and developing software in a collaborative, open-platform environment, we rapidly advance from research towards applications for large-area field-scale ET mapping. Cloud computing of the Landsat image archive combined with other satellite, climate, and weather data, is creating never imagined opportunities for assessing ET model behavior and uncertainty, and ultimately providing the ability for more robust operational monitoring and assessment of water use at field-scales.

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)

GC31G-1182: Opennex, a Private-Public Partnership in Support of the National Climate Assessment

NASA Technical Reports Server (NTRS)

Nemani, Ramakrishna R.; Wang, Weile; Michaelis, Andrew; Votava, Petr; Ganguly, Sangram

2016-01-01

The NASA Earth Exchange (NEX) is a collaborative computing platform that has been developed with the objective of bringing scientists together with the software tools, massive global datasets, and supercomputing resources necessary to accelerate research in Earth systems science and global change. NEX is funded as an enabling tool for sustaining the national climate assessment. Over the past five years, researchers have used the NEX platform and produced a number of data sets highly relevant to the National Climate Assessment. These include high-resolution climate projections using different downscaling techniques and trends in historical climate from satellite data. To enable a broader community in exploiting the above datasets, the NEX team partnered with public cloud providers to create the OpenNEX platform. OpenNEX provides ready access to NEX data holdings on a number of public cloud platforms along with pertinent analysis tools and workflows in the form of Machine Images and Docker Containers, lectures and tutorials by experts. We will showcase some of the applications of OpenNEX data and tools by the community on Amazon Web Services, Google Cloud and the NEX Sandbox.

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.

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 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

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.

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.

Engaging Middle School Students with Google Earth Technology to Analyze Ocean Cores as Evidence for Sea Floor Spreading

NASA Astrophysics Data System (ADS)

Prouhet, T.; Cook, J.

2006-12-01

Google Earth's ability to captivate students' attention, its ease of use, and its high quality images give it the potential to be an extremely effective tool for earth science educators. The unique properties of Google Earth satisfy a growing demand to incorporate technology in science instruction. Google Earth is free and relatively easy to use unlike some other visualization software. Students often have difficulty conceptualizing and visualizing earth systems, such as deep-ocean basins, because of the complexity and dynamic nature of the processes associated with them (e.g. plate tectonics). Google Earth's combination of aerial photography, satellite images and remote sensing data brings a sense of realism to science concepts. The unobstructed view of the ocean floor provided by this technology illustrates three-dimensional subsurface features such as rift valleys, subduction zones, and sea-mounts enabling students to better understand the seafloor's dynamic nature. Students will use Google Earth to navigate the sea floor, and examine Deep Sea Drilling Project (DSDP) core locations the from the Glomar Challenger Leg 3 expedition. The lesson to be implemented was expanded upon and derived from the Joint Oceanographic Insitute (JOI) Learning exercise, Nannofossils Reveal Seafloor Spreading. In addition, students take on the role of scientists as they graph and analyze paleontological data against the distance from the Mid Ocean Ridge. The integration of ocean core data in this three-dimensional view aids students' ability to draw and communicate valid conclusions about their scientific observations. A pre and post survey will be given to examine attitudes, self-efficacy, achievement and content mastery to a sample of approximately 300 eighth grade science students. The hypothesis is that the integration of Google Earth will significantly improve all areas of focus as mentioned above.

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

Leveraging Google Geo Tools for Interactive STEM Education: Insights from the GEODE Project

NASA Astrophysics Data System (ADS)

Dordevic, M.; Whitmeyer, S. J.; De Paor, D. G.; Karabinos, P.; Burgin, S.; Coba, F.; Bentley, C.; St John, K. K.

2016-12-01

Web-based imagery and geospatial tools have transformed our ability to immerse students in global virtual environments. Google's suite of geospatial tools, such as Google Earth (± Engine), Google Maps, and Street View, allow developers and instructors to create interactive and immersive environments, where students can investigate and resolve common misconceptions in STEM concepts and natural processes. The GEODE (.net) project is developing digital resources to enhance STEM education. These include virtual field experiences (VFEs), such as an interactive visualization of the breakup of the Pangaea supercontinent, a "Grand Tour of the Terrestrial Planets," and GigaPan-based VFEs of sites like the Canadian Rockies. Web-based challenges, such as EarthQuiz (.net) and the "Fold Analysis Challenge," incorporate scaffolded investigations of geoscience concepts. EarthQuiz features web-hosted imagery, such as Street View, Photo Spheres, GigaPans, and Satellite View, as the basis for guided inquiry. In the Fold Analysis Challenge, upper-level undergraduates use Google Earth to evaluate a doubly-plunging fold at Sheep Mountain, WY. GEODE.net also features: "Reasons for the Seasons"—a Google Earth-based visualization that addresses misconceptions that abound amongst students, teachers, and the public, many of whom believe that seasonality is caused by large variations in Earth's distance from the Sun; "Plate Euler Pole Finder," which helps students understand rotational motion of tectonic plates on the globe; and "Exploring Marine Sediments Using Google Earth," an exercise that uses empirical data to explore the surficial distribution of marine sediments in the modern ocean. The GEODE research team includes the authors and: Heather Almquist, Cinzia Cervato, Gene Cooper, Helen Crompton, Terry Pavlis, Jen Piatek, Bill Richards, Jeff Ryan, Ron Schott, Barb Tewksbury, and their students and collaborating colleagues. We are supported by NSF DUE 1323419 and a Google Geo Curriculum Award.

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.

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.

Machine Learning for Flood Prediction in Google Earth Engine

NASA Astrophysics Data System (ADS)

Kuhn, C.; Tellman, B.; Max, S. A.; Schwarz, B.

2015-12-01

With the increasing availability of high-resolution satellite imagery, dynamic flood mapping in near real time is becoming a reachable goal for decision-makers. This talk describes a newly developed framework for predicting biophysical flood vulnerability using public data, cloud computing and machine learning. Our objective is to define an approach to flood inundation modeling using statistical learning methods deployed in a cloud-based computing platform. Traditionally, static flood extent maps grounded in physically based hydrologic models can require hours of human expertise to construct at significant financial cost. In addition, desktop modeling software and limited local server storage can impose restraints on the size and resolution of input datasets. Data-driven, cloud-based processing holds promise for predictive watershed modeling at a wide range of spatio-temporal scales. However, these benefits come with constraints. In particular, parallel computing limits a modeler's ability to simulate the flow of water across a landscape, rendering traditional routing algorithms unusable in this platform. Our project pushes these limits by testing the performance of two machine learning algorithms, Support Vector Machine (SVM) and Random Forests, at predicting flood extent. Constructed in Google Earth Engine, the model mines a suite of publicly available satellite imagery layers to use as algorithm inputs. Results are cross-validated using MODIS-based flood maps created using the Dartmouth Flood Observatory detection algorithm. Model uncertainty highlights the difficulty of deploying unbalanced training data sets based on rare extreme events.

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.

[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 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)

Visualizing Cross-sectional Data in a Real-World Context

NASA Astrophysics Data System (ADS)

Van Noten, K.; Lecocq, T.

2016-12-01

If you could fly around your research results in three dimensions, wouldn't you like to do it? Visualizing research results properly during scientific presentations already does half the job of informing the public on the geographic framework of your research. Many scientists use the Google Earth™ mapping service (V7.1.2.2041) because it's a great interactive mapping tool for assigning geographic coordinates to individual data points, localizing a research area, and draping maps of results over Earth's surface for 3D visualization. However, visualizations of research results in vertical cross-sections are often not shown simultaneously with the maps in Google Earth. A few tutorials and programs to display cross-sectional data in Google Earth do exist, and the workflow is rather simple. By importing a cross-sectional figure into in the open software SketchUp Make [Trimble Navigation Limited, 2016], any spatial model can be exported to a vertical figure in Google Earth. In this presentation a clear workflow/tutorial is presented how to image cross-sections manually in Google Earth. No software skills, nor any programming codes are required. It is very easy to use, offers great possibilities for teaching and allows fast figure manipulation in Google Earth. The full workflow can be found in "Van Noten, K. 2016. Visualizing Cross-Sectional Data in a Real-World Context. EOS, Transactions AGU, 97, 16-19".The video tutorial can be found here: https://www.youtube.com/watch?v=Tr8LwFJ4RYU&Figure: Cross-sectional Research Examples Illustrated in Google Earth

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.

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…

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.

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.

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)

Visualizing Dynamic Weather and Ocean Data in Google Earth

NASA Astrophysics Data System (ADS)

Castello, C.; Giencke, P.

2008-12-01

Katrina. Climate change. Rising sea levels. Low lake levels. These headliners, and countless others like them, underscore the need to better understand our changing oceans and lakes. Over the past decade, efforts such as the Global Ocean Observing System (GOOS) have added to this understanding, through the creation of interoperable ocean observing systems. These systems, including buoy networks, gliders, UAV's, etc, have resulted in a dramatic increase in the amount of Earth observation data available to the public. Unfortunately, these data tend to be restrictive to mass consumption, owing to large file sizes, incompatible formats, and/or a dearth of user friendly visualization software. Google Earth offers a flexible way to visualize Earth observation data. Marrying high resolution orthoimagery, user friendly query and navigation tools, and the power of OGC's KML standard, Google Earth can make observation data universally understandable and accessible. This presentation will feature examples of meteorological and oceanographic data visualized using KML and Google Earth, along with tools and tips for integrating other such environmental datasets.

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.

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.

Information Technology Infusion Case Study: Integrating Google Earth(Trademark) into the A-Train Data Depot

NASA Technical Reports Server (NTRS)

Smith, Peter; Kempler, Steven; Leptoukh, Gregory; Chen, Aijun

2010-01-01

This poster paper represents the NASA funded project that was to employ the latest three dimensional visualization technology to explore and provide direct data access to heterogeneous A-Train datasets. Google Earth (tm) provides foundation for organizing, visualizing, publishing and synergizing Earth science data .

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.

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…

A mangrove forest map of China in 2015: Analysis of time series Landsat 7/8 and Sentinel-1A imagery in Google Earth Engine cloud computing platform

NASA Astrophysics Data System (ADS)

Chen, Bangqian; Xiao, Xiangming; Li, Xiangping; Pan, Lianghao; Doughty, Russell; Ma, Jun; Dong, Jinwei; Qin, Yuanwei; Zhao, Bin; Wu, Zhixiang; Sun, Rui; Lan, Guoyu; Xie, Guishui; Clinton, Nicholas; Giri, Chandra

2017-09-01

Due to rapid losses of mangrove forests caused by anthropogenic disturbances and climate change, accurate and contemporary maps of mangrove forests are needed to understand how mangrove ecosystems are changing and establish plans for sustainable management. In this study, a new classification algorithm was developed using the biophysical characteristics of mangrove forests in China. More specifically, these forests were mapped by identifying: (1) greenness, canopy coverage, and tidal inundation from time series Landsat data, and (2) elevation, slope, and intersection-with-sea criterion. The annual mean Normalized Difference Vegetation Index (NDVI) was found to be a key variable in determining the classification thresholds of greenness, canopy coverage, and tidal inundation of mangrove forests, which are greatly affected by tide dynamics. In addition, the integration of Sentinel-1A VH band and modified Normalized Difference Water Index (mNDWI) shows great potential in identifying yearlong tidal and fresh water bodies, which is related to mangrove forests. This algorithm was developed using 6 typical Regions of Interest (ROIs) as algorithm training and was run on the Google Earth Engine (GEE) cloud computing platform to process 1941 Landsat images (25 Path/Row) and 586 Sentinel-1A images circa 2015. The resultant mangrove forest map of China at 30 m spatial resolution has an overall/users/producer's accuracy greater than 95% when validated with ground reference data. In 2015, China's mangrove forests had a total area of 20,303 ha, about 92% of which was in the Guangxi Zhuang Autonomous Region, Guangdong, and Hainan Provinces. This study has demonstrated the potential of using the GEE platform, time series Landsat and Sentine-1A SAR images to identify and map mangrove forests along the coastal zones. The resultant mangrove forest maps are likely to be useful for the sustainable management and ecological assessments of mangrove forests in China.

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.

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 Geographic Data in Google Earth for Education and Outreach

NASA Astrophysics Data System (ADS)

Martin, D. J.; Treves, R.

2008-12-01

Google Earth is an excellent tool to help students and the public visualize scientific data as with low technical skill scientific content can be shown in three dimensions against a background of remotely sensed imagery. It therefore has a variety of uses in university education and as a tool for public outreach. However, in both situations it is of limited value if it is only used to attract attention with flashy three dimensional animations. In this poster we shall illustrate several applications that represent what we believe is good educational practice. The first example shows how the combination of a floor map and a projection of Google Earth on a screen can be used to produce active learning. Students are asked to imagine where they would build a house on Big Island Hawaii in order to avoid volcanic hazards. In the second example Google Earth is used to illustrate evidence over a range of scales in a description of Lake Agassiz flood events which would be more difficult to comprehend in a traditional paper based format. In the final example a simple text manipulation application "TMapper" is used to change the color palette of a thematic map generated by the students in Google Earth to teach them about the use of color in map design.

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.

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.

Using Social Media, Online Social Networks, and Internet Search as Platforms for Public Health Interventions: A Pilot Study.

PubMed

Huesch, Marco D; Galstyan, Aram; Ong, Michael K; Doctor, Jason N

2016-06-01

To pilot public health interventions at women potentially interested in maternity care via campaigns on social media (Twitter), social networks (Facebook), and online search engines (Google Search). Primary data from Twitter, Facebook, and Google Search on users of these platforms in Los Angeles between March and July 2014. Observational study measuring the responses of targeted users of Twitter, Facebook, and Google Search exposed to our sponsored messages soliciting them to start an engagement process by clicking through to a study website containing information on maternity care quality information for the Los Angeles market. Campaigns reached a little more than 140,000 consumers each day across the three platforms, with a little more than 400 engagements each day. Facebook and Google search had broader reach, better engagement rates, and lower costs than Twitter. Costs to reach 1,000 targeted users were approximately in the same range as less well-targeted radio and TV advertisements, while initial engagements-a user clicking through an advertisement-cost less than $1 each. Our results suggest that commercially available online advertising platforms in wide use by other industries could play a role in targeted public health interventions. © Health Research and Educational Trust.

Visualizing Moon Data and Imagery with Google Earth

NASA Astrophysics Data System (ADS)

Weiss-Malik, M.; Scharff, T.; Nefian, A.; Moratto, Z.; Kolb, E.; Lundy, M.; Hancher, M.; Gorelick, N.; Broxton, M.; Beyer, R. A.

2009-12-01

There is a vast store of planetary geospatial data that has been collected by NASA but is difficult to access and visualize. Virtual globes have revolutionized the way we visualize and understand the Earth, but other planetary bodies including Mars and the Moon can be visualized in similar ways. Extraterrestrial virtual globes are poised to revolutionize planetary science, bring an exciting new dimension to science education, and allow ordinary users to explore imagery being sent back to Earth by planetary science satellites. The original Google Moon Web site was a limited series of maps and Apollo content. The new Moon in Google Earth feature provides a similar virtual planet experience for the Moon as we have for the Earth and Mars. We incorporated existing Clementine and Lunar Orbiter imagery for the basemaps and a combination of Kaguya LALT topography and some terrain created from Apollo Metric and Panoramic images. We also have information about the Apollo landings and other robotic landers on the surface, as well as historic maps and charts, and guided tours. Some of the first-released LROC imagery of the Apollo landing sites has been put in place, and we look forward to incorporating more data as it is released from LRO, Chandraayan-1, and Kaguya. These capabilities have obvious public outreach and education benefits, but the potential benefits of allowing planetary scientists to rapidly explore these large and varied data collections — in geological context and within a single user interface — are also becoming evident. Because anyone can produce additional KML content for use in Google Earth, scientists can customize the environment to their needs as well as publish their own processed data and results for others to use. Many scientists and organizations have begun to do this already, resulting in a useful and growing collection of planetary-science-oriented Google Earth layers. Screen shot of Moon in Google Earth, a freely downloadable application for visualizing Moon imagery and data.

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…

Google Earth Mapping Exercises for Structural Geology Students--A Promising Intervention for Improving Penetrative Visualization Ability

ERIC Educational Resources Information Center

Giorgis, Scott

2015-01-01

Three-dimensional thinking skills are extremely useful for geoscientists, and at the undergraduate level, these skills are often emphasized in structural geology courses. Google Earth is a powerful tool for visualizing the three-dimensional nature of data collected on the surface of Earth. The results of a 5 y pre- and posttest study of the…

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

The extent of forest in dryland biomes.

PubMed

Bastin, Jean-François; Berrahmouni, Nora; Grainger, Alan; Maniatis, Danae; Mollicone, Danilo; Moore, Rebecca; Patriarca, Chiara; Picard, Nicolas; Sparrow, Ben; Abraham, Elena Maria; Aloui, Kamel; Atesoglu, Ayhan; Attore, Fabio; Bassüllü, Çağlar; Bey, Adia; Garzuglia, Monica; García-Montero, Luis G; Groot, Nikée; Guerin, Greg; Laestadius, Lars; Lowe, Andrew J; Mamane, Bako; Marchi, Giulio; Patterson, Paul; Rezende, Marcelo; Ricci, Stefano; Salcedo, Ignacio; Diaz, Alfonso Sanchez-Paus; Stolle, Fred; Surappaeva, Venera; Castro, Rene

2017-05-12

Dryland biomes cover two-fifths of Earth's land surface, but their forest area is poorly known. Here, we report an estimate of global forest extent in dryland biomes, based on analyzing more than 210,000 0.5-hectare sample plots through a photo-interpretation approach using large databases of satellite imagery at (i) very high spatial resolution and (ii) very high temporal resolution, which are available through the Google Earth platform. We show that in 2015, 1327 million hectares of drylands had more than 10% tree-cover, and 1079 million hectares comprised forest. Our estimate is 40 to 47% higher than previous estimates, corresponding to 467 million hectares of forest that have never been reported before. This increases current estimates of global forest cover by at least 9%. Copyright © 2017, American Association for the Advancement of Science.

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…

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.

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…

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…

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.

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.

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.

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…

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.

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.

A Java-based tool for creating KML files from GPS waypoints

NASA Astrophysics Data System (ADS)

Kinnicutt, P. G.; Rivard, C.; Rimer, S.

2008-12-01

Google Earth provides a free tool with powerful capabilities for visualizing geoscience images and data. Commercial software tools exist for doing sophisticated digitizing and spatial modeling , but for the purposes of presentation, visualization and overlaying aerial images with data Google Earth provides much of the functionality. Likewise, with current technologies in GPS (Global Positioning System) systems and with Google Earth Plus, it is possible to upload GPS waypoints, tracks and routes directly into Google Earth for visualization. However, older technology GPS units and even low-cost GPS units found today may lack the necessary communications interface to a computer (e.g. no Bluetooth, no WiFi, no USB, no Serial, etc.) or may have an incompatible interface, such as a Serial port but no USB adapter available. In such cases, any waypoints, tracks and routes saved in the GPS unit or recorded in a field notebook must be manually transferred to a computer for use in a GIS system or other program. This presentation describes a Java-based tool developed by the author which enables users to enter GPS coordinates in a user-friendly manner, then save these coordinates in a Keyhole MarkUp Language (KML) file format, for visualization in Google Earth. This tool either accepts user-interactive input or accepts input from a CSV (Comma Separated Value) file, which can be generated from any spreadsheet program. This tool accepts input in the form of lat/long or UTM (Universal Transverse Mercator) coordinates. This presentation describes this system's applicability through several small case studies. This free and lightweight tool simplifies the task of manually inputting GPS data into Google Earth for people working in the field without an automated mechanism for uploading the data; for instance, the user may not have internet connectivity or may not have the proper hardware or software. Since it is a Java application and not a web- based tool, it can be installed on one's field laptop and the GPS data can be manually entered without the need for internet connectivity. This tool provides a table view of the GPS data, but lacks a KML viewer to view the data overlain on top of an aerial view, as this viewer functionality is provided in Google Earth. The tool's primary contribution lies in its more convenient method for entering the GPS data manually when automated technologies are not available.

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…

Visualizing Mars data and imagery with Google Earth

NASA Astrophysics Data System (ADS)

Beyer, R. A.; Broxton, M.; Gorelick, N.; Hancher, M.; Lundy, M.; Kolb, E.; Moratto, Z.; Nefian, A.; Scharff, T.; Weiss-Malik, M.

2009-12-01

There is a vast store of planetary geospatial data that has been collected by NASA but is difficult to access and visualize. Virtual globes have revolutionized the way we visualize and understand the Earth, but other planetary bodies including Mars and the Moon can be visualized in similar ways. Extraterrestrial virtual globes are poised to revolutionize planetary science, bring an exciting new dimension to science education, and allow ordinary users to explore imagery being sent back to Earth by planetary science satellites. The original Google Mars Web site allowed users to view base maps of Mars via the Web, but it did not have the full features of the 3D Google Earth client. We have previously demonstrated the use of Google Earth to display Mars imagery, but now with the launch of Mars in Google Earth, there is a base set of Mars data available for anyone to work from and add to. There are a variety of global maps to choose from and display. The Terrain layer has the MOLA gridded data topography, and where available, HRSC terrain models are mosaicked into the topography. In some locations there is also meter-scale terrain derived from HiRISE stereo imagery. There is rich information in the form of the IAU nomenclature database, data for the rovers and landers on the surface, and a Spacecraft Imagery layer which contains the image outlines for all HiRISE, CTX, CRISM, HRSC, and MOC image data released to the PDS and links back to their science data. There are also features like the Traveler's Guide to Mars, Historic Maps, Guided Tours, as well as the 'Live from Mars' feature, which shows the orbital tracks of both the Mars Odyssey and Mars Reconnaissance Orbiter for a few days in the recent past. It shows where they have acquired imagery, and also some preview image data. These capabilities have obvious public outreach and education benefits, but the potential benefits of allowing planetary scientists to rapidly explore these large and varied data collections—in geological context and within a single user interface—are also becoming evident. Because anyone can produce additional KML content for use in Google Earth, scientists can customize the environment to their needs as well as publish their own processed data and results for others to use. Many scientists and organizations have begun to do this already, resulting in a useful and growing collection of planetary-science-oriented Google Earth layers.

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.

Immunochromatographic diagnostic test analysis using Google Glass.

PubMed

Feng, Steve; Caire, Romain; Cortazar, Bingen; Turan, Mehmet; Wong, Andrew; Ozcan, Aydogan

2014-03-25

We demonstrate a Google Glass-based rapid diagnostic test (RDT) reader platform capable of qualitative and quantitative measurements of various lateral flow immunochromatographic assays and similar biomedical diagnostics tests. Using a custom-written Glass application and without any external hardware attachments, one or more RDTs labeled with Quick Response (QR) code identifiers are simultaneously imaged using the built-in camera of the Google Glass that is based on a hands-free and voice-controlled interface and digitally transmitted to a server for digital processing. The acquired JPEG images are automatically processed to locate all the RDTs and, for each RDT, to produce a quantitative diagnostic result, which is returned to the Google Glass (i.e., the user) and also stored on a central server along with the RDT image, QR code, and other related information (e.g., demographic data). The same server also provides a dynamic spatiotemporal map and real-time statistics for uploaded RDT results accessible through Internet browsers. We tested this Google Glass-based diagnostic platform using qualitative (i.e., yes/no) human immunodeficiency virus (HIV) and quantitative prostate-specific antigen (PSA) tests. For the quantitative RDTs, we measured activated tests at various concentrations ranging from 0 to 200 ng/mL for free and total PSA. This wearable RDT reader platform running on Google Glass combines a hands-free sensing and image capture interface with powerful servers running our custom image processing codes, and it can be quite useful for real-time spatiotemporal tracking of various diseases and personal medical conditions, providing a valuable tool for epidemiology and mobile health.

Immunochromatographic Diagnostic Test Analysis Using Google Glass

PubMed Central

2014-01-01

We demonstrate a Google Glass-based rapid diagnostic test (RDT) reader platform capable of qualitative and quantitative measurements of various lateral flow immunochromatographic assays and similar biomedical diagnostics tests. Using a custom-written Glass application and without any external hardware attachments, one or more RDTs labeled with Quick Response (QR) code identifiers are simultaneously imaged using the built-in camera of the Google Glass that is based on a hands-free and voice-controlled interface and digitally transmitted to a server for digital processing. The acquired JPEG images are automatically processed to locate all the RDTs and, for each RDT, to produce a quantitative diagnostic result, which is returned to the Google Glass (i.e., the user) and also stored on a central server along with the RDT image, QR code, and other related information (e.g., demographic data). The same server also provides a dynamic spatiotemporal map and real-time statistics for uploaded RDT results accessible through Internet browsers. We tested this Google Glass-based diagnostic platform using qualitative (i.e., yes/no) human immunodeficiency virus (HIV) and quantitative prostate-specific antigen (PSA) tests. For the quantitative RDTs, we measured activated tests at various concentrations ranging from 0 to 200 ng/mL for free and total PSA. This wearable RDT reader platform running on Google Glass combines a hands-free sensing and image capture interface with powerful servers running our custom image processing codes, and it can be quite useful for real-time spatiotemporal tracking of various diseases and personal medical conditions, providing a valuable tool for epidemiology and mobile health. PMID:24571349

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.

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.

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.

Googling in Anatomy Education: Can Google Trends Inform Educators of National Online Search Patterns of Anatomical Syllabi?

ERIC Educational Resources Information Center

Phelan, Nigel; Davy, Shane; O'Keeffe, Gerard W.; Barry, Denis S.

2017-01-01

The role of e-learning platforms in anatomy education continues to expand as self-directed learning is promoted in higher education. Although a wide range of e-learning resources are available, determining student use of non-academic internet resources requires novel approaches. One such approach that may be useful is the Google Trends© web…

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.

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.

Inspiring the Next Generation of Scientists: Building on 52 Years of Tradition in Diatom Research with Open-Source, Web-Based Collaboration Tools and Online Resources in a Field Course for High School Students

NASA Astrophysics Data System (ADS)

Howard, K. L.; Lee, S. S.

2015-12-01

Open-source, web-based forums and online resources can be used to develop a collaborative, active-learning approach for engaging and training students in the scientific process. We used the Diatoms of the United States website as an online resource for diatom taxonomy and developed a Google+ class community to serve as a platform for high school students to learn about research in diatom taxonomy, community ecology and diatom applications to the earth sciences. Ecology and Systematics of Diatoms is a field course that has been taught at the undergraduate and graduate levels at the Iowa Lakeside Lab field station for 52 years, beginning with the Diatom Clinic in 1963. Freshwater diatom education at Lakeside Lab has since evolved into a foundational training course attracting budding diatomists from all over the world, and has grown to include a week-long course for high school students. Successful since 2012, the high school course is now offered for college credit (University of Iowa), and covers methods of diatom specimen collection and preparation, microscopy, identification of diatom genera, diatom ecology, applications of diatom research, and an introduction to data analysis incorporating multivariate statistics (ordination) using the R statistical program, as well as primary scientific literature. During the 2015 course, students contributed to a Google+ class community where they posted images, data, and questions. The web-based platform allowed students to easily share information and to give and receive feedback from both peers and instructors. Students collaborated via the Google+ community and used the Diatoms of the United States website to develop a taxonomic reference for a field-based group research project, simulating how an actual diatom research program would develop a region or project-specific flora harmonized across analysts. Students investigated the taxonomy and ecology of diatom epiphytes on the green alga Cladophora from the littoral zone of West Lake Okoboji, Iowa. They found the epiphyte community went through a seasonal succession and developed hypotheses for the observed patterns by researching the ecology of diatoms in primary literature. These course activities may be used as a model for other field-based courses or educational programs in earth and environmental sciences.

3D Orbit Visualization for Earth-Observing Missions

NASA Technical Reports Server (NTRS)

Jacob, Joseph C.; Plesea, Lucian; Chafin, Brian G.; Weiss, Barry H.

2011-01-01

This software visualizes orbit paths for the Orbiting Carbon Observatory (OCO), but was designed to be general and applicable to any Earth-observing mission. The software uses the Google Earth user interface to provide a visual mechanism to explore spacecraft orbit paths, ground footprint locations, and local cloud cover conditions. In addition, a drill-down capability allows for users to point and click on a particular observation frame to pop up ancillary information such as data product filenames and directory paths, latitude, longitude, time stamp, column-average dry air mole fraction of carbon dioxide, and solar zenith angle. This software can be integrated with the ground data system for any Earth-observing mission to automatically generate daily orbit path data products in Google Earth KML format. These KML data products can be directly loaded into the Google Earth application for interactive 3D visualization of the orbit paths for each mission day. Each time the application runs, the daily orbit paths are encapsulated in a KML file for each mission day since the last time the application ran. Alternatively, the daily KML for a specified mission day may be generated. The application automatically extracts the spacecraft position and ground footprint geometry as a function of time from a daily Level 1B data product created and archived by the mission s ground data system software. In addition, ancillary data, such as the column-averaged dry air mole fraction of carbon dioxide and solar zenith angle, are automatically extracted from a Level 2 mission data product. Zoom, pan, and rotate capability are provided through the standard Google Earth interface. Cloud cover is indicated with an image layer from the MODIS (Moderate Resolution Imaging Spectroradiometer) aboard the Aqua satellite, which is automatically retrieved from JPL s OnEarth Web service.

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)...

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.

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.

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.

Enlisting User Community Perspectives to Inform Development of a Semantic Web Application for Discovery of Cross-Institutional Research Information and Data

NASA Astrophysics Data System (ADS)

Johns, E. M.; Mayernik, M. S.; Boler, F. M.; Corson-Rikert, J.; Daniels, M. D.; Gross, M. B.; Khan, H.; Maull, K. E.; Rowan, L. R.; Stott, D.; Williams, S.; Krafft, D. B.

2015-12-01

Researchers seek information and data through a variety of avenues: published literature, search engines, repositories, colleagues, etc. In order to build a web application that leverages linked open data to enable multiple paths for information discovery, the EarthCollab project has surveyed two geoscience user communities to consider how researchers find and share scholarly output. EarthCollab, a cross-institutional, EarthCube funded project partnering UCAR, Cornell University, and UNAVCO, is employing the open-source semantic web software, VIVO, as the underlying technology to connect the people and resources of virtual research communities. This study will present an analysis of survey responses from members of the two case study communities: (1) the Bering Sea Project, an interdisciplinary field program whose data archive is hosted by NCAR's Earth Observing Laboratory (EOL), and (2) UNAVCO, a geodetic facility and consortium that supports diverse research projects informed by geodesy. The survey results illustrate the types of research products that respondents indicate should be discoverable within a digital platform and the current methods used to find publications, data, personnel, tools, and instrumentation. The responses showed that scientists rely heavily on general purpose search engines, such as Google, to find information, but that data center websites and the published literature were also critical sources for finding collaborators, data, and research tools.The survey participants also identify additional features of interest for an information platform such as search engine indexing, connection to institutional web pages, generation of bibliographies and CVs, and outward linking to social media. Through the survey, the user communities prioritized the type of information that is most important to display and describe their work within a research profile. The analysis of this survey will inform our further development of a platform that will facilitate different types of information discovery strategies, and help researchers to find and use the associated resources of a research project.

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.

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.

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.

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

BioMon: A Google Earth Based Continuous Biomass Monitoring System (Demo Paper)

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

Vatsavai, Raju

2009-01-01

We demonstrate a Google Earth based novel visualization system for continuous monitoring of biomass at regional and global scales. This system is integrated with a back-end spatiotemporal data mining system that continuously detects changes using high temporal resolution MODIS images. In addition to the visualization, we demonstrate novel query features of the system that provides insights into the current conditions of the landscape.

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.

Development of Waypoint Planning Tool in Response to NASA Field Campaign Challenges

NASA Technical Reports Server (NTRS)

He, Matt; Hardin, Danny; Mayer, Paul; Blakeslee, Richard; Goodman, Michael

2012-01-01

Airborne real time observations are a major component of NASA 's Earth Science research and satellite ground validation studies. Multiple aircraft are involved in most NASA field campaigns. The coordination of the aircraft with satellite overpasses, other airplanes and the constantly evolving, dynamic weather conditions often determines the success of the campaign. Planning a research aircraft mission within the context of meeting the science objectives is a complex task because it requires real time situational awareness of the weather conditions that affect the aircraft track. A flight planning tools is needed to provide situational awareness information to the mission scientists, and help them plan and modify the flight tracks. Scientists at the University of Alabama ]Huntsville and the NASA Marshall Space Flight Center developed the Waypoint Planning Tool, an interactive software tool that enables scientists to develop their own flight plans (also known as waypoints) with point -and-click mouse capabilities on a digital map filled with real time raster and vector data. The development of this Waypoint Planning Tool demonstrates the significance of mission support in responding to the challenges presented during NASA field campaigns. Analysis during and after each campaign helped identify both issues and new requirements, and initiated the next wave of development. Currently the Waypoint Planning Tool has gone through three rounds of development and analysis processes. The development of this waypoint tool is directly affected by the technology advances on GIS/Mapping technologies. From the standalone Google Earth application and simple KML functionalities, to Google Earth Plugin on web platform, and to the rising open source GIS tools with New Java Script frameworks, the Waypoint Planning Tool has entered its third phase of technology advancement. Adapting new technologies for the Waypoint Planning Tool ensures its success in helping scientist reach their mission objectives.

Measuring river from the cloud - River width algorithm development on Google Earth Engine

NASA Astrophysics Data System (ADS)

Yang, X.; Pavelsky, T.; Allen, G. H.; Donchyts, G.

2017-12-01

Rivers are some of the most dynamic features of the terrestrial land surface. They help distribute freshwater, nutrients, sediment, and they are also responsible for some of the greatest natural hazards. Despite their importance, our understanding of river behavior is limited at the global scale, in part because we do not have a river observational dataset that spans both time and space. Remote sensing data represent a rich, largely untapped resource for observing river dynamics. In particular, publicly accessible archives of satellite optical imagery, which date back to the 1970s, can be used to study the planview morphodynamics of rivers at the global scale. Here we present an image processing algorithm developed using the Google Earth Engine cloud-based platform, that can automatically extracts river centerlines and widths from Landsat 5, 7, and 8 scenes at 30 m resolution. Our algorithm makes use of the latest monthly global surface water history dataset and an existing Global River Width from Landsat (GRWL) dataset to efficiently extract river masks from each Landsat scene. Then a combination of distance transform and skeletonization techniques are used to extract river centerlines. Finally, our algorithm calculates wetted river width at each centerline pixel perpendicular to its local centerline direction. We validated this algorithm using in situ data estimated from 16 USGS gauge stations (N=1781). We find that 92% of the width differences are within 60 m (i.e. the minimum length of 2 Landsat pixels). Leveraging Earth Engine's infrastructure of collocated data and processing power, our goal is to use this algorithm to reconstruct the morphodynamic history of rivers globally by processing over 100,000 Landsat 5 scenes, covering from 1984 to 2013.

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.

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.

Visualization of High-Resolution LiDAR Topography in Google Earth

NASA Astrophysics Data System (ADS)

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

2009-12-01

The growing availability of high-resolution LiDAR (Light Detection And Ranging) topographic data has proven to be revolutionary for Earth science research. These data allow scientists to study the processes acting on the Earth’s surfaces at resolutions not previously possible yet essential for their appropriate representation. In addition to their utility for research, the data have also been recognized as powerful tools for communicating earth science concepts for education and outreach purposes. Unfortunately, the massive volume of data produced by LiDAR mapping technology can be a barrier to their use. To facilitate access to these powerful data for research and educational purposes, we have been exploring the use of Keyhole Markup Language (KML) and Google Earth to deliver LiDAR-derived visualizations. The OpenTopography Portal (http://www.opentopography.org/) is a National Science Foundation-funded facility designed to provide access to Earth science-oriented LiDAR data. OpenTopography hosts a growing collection of LiDAR data for a variety of geologic domains, including many of the active faults in the western United States. We have found that the wide spectrum of LiDAR users have variable scientific applications, computing resources, and technical experience and thus require a data distribution system that provides various levels of access to the data. For users seeking a synoptic view of the data, and for education and outreach purposes, delivering full-resolution images derived from LiDAR topography into the Google Earth virtual globe is powerful. The virtual globe environment provides a freely available and easily navigated viewer and enables quick integration of the LiDAR visualizations with imagery, geographic layers, and other relevant data available in KML format. Through region-dependant network linked KML, OpenTopography currently delivers over 20 GB of LiDAR-derived imagery to users via simple, easily downloaded KMZ files hosted at the Portal. This method provides seamlessly access to hillshaded imagery for both bare earth and first return terrain models with various angles of illumination. Seamless access to LiDAR-derived imagery in Google Earth has proven to be the most popular product available in the OpenTopography Portal. The hillshade KMZ files have been downloaded over 3000 times by users ranging from earthquake scientists to K-12 educators who wish to introduce cutting edge real world data into their earth science lessons. OpenTopography also provides dynamically generated KMZ visualizations of LiDAR data products produced when users choose to use the OpenTopography point cloud access and processing system. These Google Earth compatible products allow users to quickly visualize the custom terrain products they have generated without the burden of loading the data into a GIS environment. For users who have installed the Google Earth browser plug-in, these visualizations can be launched directly from the OpenTopography results page and viewed directly in the browser.

3D Online Visualization and Synergy of NASA A-Train Data Using Google Earth

NASA Technical Reports Server (NTRS)

Chen, Aijun; Kempler, Steven; Leptoukh, Gregory; Smith, Peter

2010-01-01

This poster presentation reviews the use of Google Earth to assist in three dimensional online visualization of NASA Earth science and geospatial data. The NASA A-Train satellite constellation is a succession of seven sun-synchronous orbit satellites: (1) OCO-2 (Orbiting Carbon Observatory) (will launch in Feb. 2013), (2) GCOM-W1 (Global Change Observation Mission), (3) Aqua, (4) CloudSat, (5) CALIPSO (Cloud-Aerosol Lidar & Infrared Pathfinder Satellite Observations), (6) Glory, (7) Aura. The A-Train makes possible synergy of information from multiple resources, so more information about earth condition is obtained from the combined observations than would be possible from the sum of the observations taken independently

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.

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…

Digimarc Discover on Google Glass

NASA Astrophysics Data System (ADS)

Rogers, Eliot; Rodriguez, Tony; Lord, John; Alattar, Adnan

2015-03-01

This paper reports on the implementation of the Digimarc® Discover platform on Google Glass, enabling the reading of a watermark embedded in a printed material or audio. The embedded watermark typically contains a unique code that identifies the containing media or object and a synchronization signal that allows the watermark to be read robustly. The Digimarc Discover smartphone application can read the watermark from a small portion of printed image presented at any orientation or reasonable distance. Likewise, Discover can read the recently introduced Digimarc Barcode to identify and manage consumer packaged goods in the retail channel. The Digimarc Barcode has several advantages over the traditional barcode and is expected to save the retail industry millions of dollars when deployed at scale. Discover can also read an audio watermark from ambient audio captured using a microphone. The Digimarc Discover platform has been widely deployed on the iPad, iPhone and many Android-based devices, but it has not yet been implemented on a head-worn wearable device, such as Google Glass. Implementing Discover on Google Glass is a challenging task due to the current hardware and software limitations of the device. This paper identifies the challenges encountered in porting Discover to the Google Glass and reports on the solutions created to deliver a prototype implementation.

Critical assessment of pediatric neurosurgery patient/parent educational information obtained via the Internet.

PubMed

Garcia, Michael; Daugherty, Christopher; Ben Khallouq, Bertha; Maugans, Todd

2018-05-01

OBJECTIVE The Internet is used frequently by patients and family members to acquire information about pediatric neurosurgical conditions. The sources, nature, accuracy, and usefulness of this information have not been examined recently. The authors analyzed the results from searches of 10 common pediatric neurosurgical terms using a novel scoring test to assess the value of the educational information obtained. METHODS Google and Bing searches were performed for 10 common pediatric neurosurgical topics (concussion, craniosynostosis, hydrocephalus, pediatric brain tumor, pediatric Chiari malformation, pediatric epilepsy surgery, pediatric neurosurgery, plagiocephaly, spina bifida, and tethered spinal cord). The first 10 "hits" obtained with each search engine were analyzed using the Currency, Relevance, Authority, Accuracy, and Purpose (CRAAP) test, which assigns a numerical score in each of 5 domains. Agreement between results was assessed for 1) concurrent searches with Google and Bing; 2) Google searches over time (6 months apart); 3) Google searches using mobile and PC platforms concurrently; and 4) searches using privacy settings. Readability was assessed with an online analytical tool. RESULTS Google and Bing searches yielded information with similar CRAAP scores (mean 72% and 75%, respectively), but with frequently differing results (58% concordance/matching results). There was a high level of agreement (72% concordance) over time for Google searches and also between searches using general and privacy settings (92% concordance). Government sources scored the best in both CRAAP score and readability. Hospitals and universities were the most prevalent sources, but these sources had the lowest CRAAP scores, due in part to an abundance of self-marketing. The CRAAP scores for mobile and desktop platforms did not differ significantly (p = 0.49). CONCLUSIONS Google and Bing searches yielded useful educational information, using either mobile or PC platforms. Most information was relevant and accurate; however, the depth and breadth of information was variable. Search results over a 6-month period were moderately stable. Pediatric neurosurgery practices and neurosurgical professional organization websites were inferior (less current, less accurate, less authoritative, and less purposeful) to governmental and encyclopedia-type resources such as Wikipedia. This presents an opportunity for pediatric neurosurgeons to participate in the creation of better online patient/parent educational material.

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

Development of Waypoint Planning Tool in Response to NASA Field Campaign Challenges

NASA Technical Reports Server (NTRS)

He, Matt; Hardin, Danny; Conover, Helen; Graves, Sara; Meyer, Paul; Blakeslee, Richard; Goodman, Michael

2012-01-01

Airborne real time observations are a major component of NASA's Earth Science research and satellite ground validation studies. For mission scientists, planning a research aircraft mission within the context of meeting the science objectives is a complex task because it requires real time situational awareness of the weather conditions that affect the aircraft track. Multiple aircrafts are often involved in NASA field campaigns. The coordination of the aircrafts with satellite overpasses, other airplanes and the constantly evolving, dynamic weather conditions often determines the success of the campaign. A flight planning tool is needed to provide situational awareness information to the mission scientists, and help them plan and modify the flight tracks. Scientists at the University of Alabama-Huntsville and the NASA Marshall Space Flight Center developed the Waypoint Planning Tool, an interactive software tool that enables scientists to develop their own flight plans (also known as waypoints) with point -and-click mouse capabilities on a digital map filled with real time raster and vector data. The development of this Waypoint Planning Tool demonstrates the significance of mission support in responding to the challenges presented during NASA field campaigns. Analysis during and after each campaign helped identify both issues and new requirements, and initiated the next wave of development. Currently the Waypoint Planning Tool has gone through three rounds of development and analysis processes. The development of this waypoint tool is directly affected by the technology advances on GIS/Mapping technologies. From the standalone Google Earth application and simple KML functionalities, to Google Earth Plugin and Java Web Start/Applet on web platform, and to the rising open source GIS tools with new JavaScript frameworks, the Waypoint Planning Tool has entered its third phase of technology advancement. The newly innovated, cross ]platform, modular designed JavaScript ]controlled Way Point Tool is planned to be integrated with NASA Airborne Science Mission Tool Suite. Adapting new technologies for the Waypoint Planning Tool ensures its success in helping scientists reach their mission objectives. This presentation will discuss the development processes of the Waypoint Planning Tool in responding to field campaign challenges, identify new information technologies, and describe the capabilities and features of the Waypoint Planning Tool with the real time aspect, interactive nature, and the resultant benefits to the airborne science community.

The Way Point Planning Tool: Real Time Flight Planning for Airborne Science

NASA Technical Reports Server (NTRS)

He, Yubin; Blakeslee, Richard; Goodman, Michael; Hall, John

2012-01-01

Airborne real time observation are a major component of NASA's Earth Science research and satellite ground validation studies. For mission scientist, planning a research aircraft mission within the context of meeting the science objective is a complex task because it requires real time situational awareness of the weather conditions that affect the aircraft track. Multiple aircraft are often involved in the NASA field campaigns the coordination of the aircraft with satellite overpasses, other airplanes and the constantly evolving dynamic weather conditions often determine the success of the campaign. A flight planning tool is needed to provide situational awareness information to the mission scientist and help them plan and modify the flight tracks successfully. Scientists at the University of Alabama Huntsville and the NASA Marshal Space Flight Center developed the Waypoint Planning Tool (WPT), an interactive software tool that enables scientist to develop their own flight plans (also known as waypoints), with point and click mouse capabilities on a digital map filled with time raster and vector data. The development of this Waypoint Planning Tool demonstrates the significance of mission support in responding to the challenges presented during NASA field campaigns. Analyses during and after each campaign helped identify both issues and new requirements, initiating the next wave of development. Currently the Waypoint Planning Tool has gone through three rounds of development and analysis processes. The development of this waypoint tool is directly affected by the technology advances on GIS/Mapping technologies. From the standalone Google Earth application and simple KML functionalities to the Google Earth Plugin and Java Web Start/Applet on web platform, as well as to the rising open source GIS tools with new JavaScript frameworks, the Waypoint planning Tool has entered its third phase of technology advancement. The newly innovated, cross-platform, modular designed JavaScript-controled Waypoint tool is planned to be integrated with the NASA Airborne Science Mission Tool Suite. Adapting new technologies for the Waypoint Planning Tool ensures its success in helping scientist reach their mission objectives. This presentation will discuss the development process of the Waypoint Planning Tool in responding to field campaign challenges, identifying new information technologies, and describing the capabilities and features of the Waypoint Planning Tool with the real time aspect, interactive nature, and the resultant benefits to the airborne science community.

Development of Way Point Planning Tool in Response to NASA Field Campaign Challenges

NASA Astrophysics Data System (ADS)

He, M.; Hardin, D. M.; Conover, H.; Graves, S. J.; Meyer, P.; Blakeslee, R. J.; Goodman, M. L.

2012-12-01

Airborne real time observations are a major component of NASA's Earth Science research and satellite ground validation studies. For mission scientists, planning a research aircraft mission within the context of meeting the science objectives is a complex task because it requires real time situational awareness of the weather conditions that affect the aircraft track. Multiple aircrafts are often involved in NASA field campaigns. The coordination of the aircrafts with satellite overpasses, other airplanes and the constantly evolving, dynamic weather conditions often determines the success of the campaign. A flight planning tool is needed to provide situational awareness information to the mission scientists, and help them plan and modify the flight tracks. Scientists at the University of Alabama-Huntsville and the NASA Marshall Space Flight Center developed the Waypoint Planning Tool, an interactive software tool that enables scientists to develop their own flight plans (also known as waypoints) with point-and-click mouse capabilities on a digital map filled with real time raster and vector data. The development of this Waypoint Planning Tool demonstrates the significance of mission support in responding to the challenges presented during NASA field campaigns. Analysis during and after each campaign helped identify both issues and new requirements, and initiated the next wave of development. Currently the Waypoint Planning Tool has gone through three rounds of development and analysis processes. The development of this waypoint tool is directly affected by the technology advances on GIS/Mapping technologies. From the standalone Google Earth application and simple KML functionalities, to Google Earth Plugin and Java Web Start/Applet on web platform, and to the rising open source GIS tools with new JavaScript frameworks, the Waypoint Planning Tool has entered its third phase of technology advancement. The newly innovated, cross-platform, modular designed JavaScript-controlled Way Point Tool is planned to be integrated with NASA Airborne Science Mission Tool Suite. Adapting new technologies for the Waypoint Planning Tool ensures its success in helping scientists reach their mission objectives. This presentation will discuss the development processes of the Waypoint Planning Tool in responding to field campaign challenges, identify new information technologies, and describe the capabilities and features of the Waypoint Planning Tool with the real time aspect, interactive nature, and the resultant benefits to the airborne science community.

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.

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.

Assessing Google Cardboard Virtual Reality as a Content Delivery System in Business Classrooms

ERIC Educational Resources Information Center

Lee, Seung Hwan; Sergueeva, Ksenia; Catangui, Mathew; Kandaurova, Maria

2017-01-01

In the past, researchers have explored virtual reality (VR) as an educational tool primarily for training or therapeutic purposes. In this research, the authors examine the potential for using Google Cardboard VR in business classrooms as a content delivery platform. They specifically investigate how VR (viewing a 3-dimensional, 360° video)…

piBox: A Platform for Privacy-Preserving Apps

DTIC Science & Technology

2012-10-03

media Arcade/Action! Books! Brain/Puzzles! Business! Cards/Casino! Casual! Comics! Communication! Education ! Entertainment! Finance! Health/Fitness... Lifestyle ! Live Wallpaper! Media/Video! Medical! Music/Audio! News/Magazines! Personalization! Photography! Productivity! Racing! Shopping! Social! Sports...Cells: A virtual mobile smartphone architecture. In SOSP, 2011. [4] Google App Engine. https://developers. google.com/appengine. [5] M. Backes, A. Kate

Access High Quality Imagery from the NOAA View Portal

NASA Astrophysics Data System (ADS)

Pisut, D.; Powell, A. M.; Loomis, T.; Goel, V.; Mills, B.; Cowan, D.

2013-12-01

NOAA curates a vast treasure trove of environmental data, but one that is sometimes not easily accessed, especially for education, outreach, and media purposes. Traditional data portals in NOAA require extensive knowledge of the specific names of observation platforms, models, and analyses, along with nomenclature for variable outputs. A new website and web mapping service (WMS) from NOAA attempts to remedy such issues. The NOAA View data imagery portal provides a seamless entry point into data from across the agency: satellite, models, in-situ analysis, etc. The system provides the user with ability to browse, animate, and download high resolution (e.g., 4,000 x 2,000 pixel) imagery, Google Earth, and even proxy data files. The WMS architecture also allows the resources to be ingested into other software systems or applications.

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.

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.

Harvesting rockfall hazard evaluation parameters from Google Earth Street View

NASA Astrophysics Data System (ADS)

Partsinevelos, Panagiotis; Agioutantis, Zacharias; Tripolitsiotis, Achilles; Steiakakis, Chrysanthos; Mertikas, Stelios

2015-04-01

Rockfall incidents along highways and railways prove extremely dangerous for properties, infrastructures and human lives. Several qualitative metrics such as the Rockfall Hazard Rating System (RHRS) and the Colorado Rockfall Hazard Rating System (CRHRS) have been established to estimate rockfall potential and provide risk maps in order to control and monitor rockfall incidents. The implementation of such metrics for efficient and reliable risk modeling require accurate knowledge of multi-parametric attributes such as the geological, geotechnical, topographic parameters of the study area. The Missouri Rockfall Hazard Rating System (MORH RS) identifies the most potentially problematic areas using digital video logging for the determination of parameters like slope height and angle, face irregularities, etc. This study aims to harvest in a semi-automated approach geometric and qualitative measures through open source platforms that may provide 3-dimensional views of the areas of interest. More specifically, the Street View platform from Google Maps, is hereby used to provide essential information that can be used towards 3-dimensional reconstruction of slopes along highways. The potential of image capturing along a programmable virtual route to provide the input data for photogrammetric processing is also evaluated. Moreover, qualitative characterization of the geological and geotechnical status, based on the Street View images, is performed. These attributes are then integrated to deliver a GIS-based rockfall hazard map. The 3-dimensional models are compared to actual photogrammetric measures in a rockfall prone area in Crete, Greece while in-situ geotechnical characterization is also used to compare and validate the hazard risk. This work is considered as the first step towards the exploitation of open source platforms to improve road safety and the development of an operational system where authorized agencies (i.e., civil protection) will be able to acquire near-real time hazard maps based on video images retrieved either by open source platforms, operational unmanned aerial vehicles, and/or simple video recordings from users. This work has been performed under the framework of the "Cooperation 2011" project ISTRIA (11_SYN_9_13989) funded from the Operational Program "Competitiveness and Entrepreneurship" (co-funded by the European Regional Development Fund (ERDF)) and managed by the Greek General Secretariat for Research and Technology.

Geospatial analysis of land use change in the Savannah River Basin using Google Earth Engine

NASA Astrophysics Data System (ADS)

Zurqani, Hamdi A.; Post, Christopher J.; Mikhailova, Elena A.; Schlautman, Mark A.; Sharp, Julia L.

2018-07-01

Climate and land use/cover change are among the most pervasive issues facing the Southeastern United States, including the Savannah River basin in South Carolina and Georgia. Land use directly affects the natural environment across the Savannah River basin and it is important to analyze these impacts. The objectives of this study are to: 1) determine the classes and the distribution of land cover in the Savannah River basin; 2) identify the spatial and the temporal change of the land cover that occurs as a consequence of land use change in the area; and 3) discuss the potential effects of land use change in the Savannah River basin. The land cover maps were produced using random forest supervised classification at four time periods for a total of thirteen common land cover classes with overall accuracy assessments of 79.18% (1999), 79.41% (2005), 76.04% (2009), and 76.11% (2015). The major land use change observed was due to the deforestation and reforestation of forest areas during the entire study period. The change detection results using the normalized difference vegetation index (NDVI) indicated that the proportion areas of the deforestation were 5.93% (1999-2005), 4.63% (2005-2009), and 3.76% (2009-2015), while the proportion areas of the reforestation were 1.57% (1999-2005), 0.44% (2005-2009), and 1.53% (2009-2015). These results not only indicate land use change, but also demonstrate the advantage of utilizing Google Earth Engine and the public archive database in its platform to track and monitor this change over time.

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.

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.

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.

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.

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.

Using Google Docs to Enhance the Teacher Work Sample: Building e-Portfolios for Learning and Practice

ERIC Educational Resources Information Center

Gugino, Jessica

2018-01-01

The use of teaching portfolios in teacher education programs is a widely accepted practice. This article describes how a traditional teacher work sample was transformed using the online platform, Google Docs. The use of online digital portfolios may help to satisfy both the need to evaluate teacher candidates' performance in special education…

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.

Big Data Sensors of Organic Advocacy: The Case of Leonardo DiCaprio and Climate Change.

PubMed

Leas, Eric C; Althouse, Benjamin M; Dredze, Mark; Obradovich, Nick; Fowler, James H; Noar, Seth M; Allem, Jon-Patrick; Ayers, John W

2016-01-01

The strategies that experts have used to share information about social causes have historically been top-down, meaning the most influential messages are believed to come from planned events and campaigns. However, more people are independently engaging with social causes today than ever before, in part because online platforms allow them to instantaneously seek, create, and share information. In some cases this "organic advocacy" may rival or even eclipse top-down strategies. Big data analytics make it possible to rapidly detect public engagement with social causes by analyzing the same platforms from which organic advocacy spreads. To demonstrate this claim we evaluated how Leonardo DiCaprio's 2016 Oscar acceptance speech citing climate change motivated global English language news (Bloomberg Terminal news archives), social media (Twitter postings) and information seeking (Google searches) about climate change. Despite an insignificant increase in traditional news coverage (54%; 95%CI: -144 to 247), tweets including the terms "climate change" or "global warming" reached record highs, increasing 636% (95%CI: 573-699) with more than 250,000 tweets the day DiCaprio spoke. In practical terms the "DiCaprio effect" surpassed the daily average effect of the 2015 Conference of the Parties (COP) and the Earth Day effect by a factor of 3.2 and 5.3, respectively. At the same time, Google searches for "climate change" or "global warming" increased 261% (95%CI, 186-335) and 210% (95%CI 149-272) the day DiCaprio spoke and remained higher for 4 more days, representing 104,190 and 216,490 searches. This increase was 3.8 and 4.3 times larger than the increases observed during COP's daily average or on Earth Day. Searches were closely linked to content from Dicaprio's speech (e.g., "hottest year"), as unmentioned content did not have search increases (e.g., "electric car"). Because these data are freely available in real time our analytical strategy provides substantial lead time for experts to detect and participate in organic advocacy while an issue is salient. Our study demonstrates new opportunities to detect and aid agents of change and advances our understanding of communication in the 21st century media landscape.

Using Social Media Activity to Identify Personality Characteristics of Navy Personnel

DTIC Science & Technology

2016-03-01

1]. The list of social media platforms is constantly growing. The most commonly used platforms are YouTube , Facebook, Google+, and Twitter; others...such as anxiety, anger, depression , self- consciousness, impulsiveness, and vulnerability • Openness to Experience, described with terms such as fantasy

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.

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.

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.

Space Situational Awareness Data Processing Scalability Utilizing Google Cloud Services

NASA Astrophysics Data System (ADS)

Greenly, D.; Duncan, M.; Wysack, J.; Flores, F.

Space Situational Awareness (SSA) is a fundamental and critical component of current space operations. The term SSA encompasses the awareness, understanding and predictability of all objects in space. As the population of orbital space objects and debris increases, the number of collision avoidance maneuvers grows and prompts the need for accurate and timely process measures. The SSA mission continually evolves to near real-time assessment and analysis demanding the need for higher processing capabilities. By conventional methods, meeting these demands requires the integration of new hardware to keep pace with the growing complexity of maneuver planning algorithms. SpaceNav has implemented a highly scalable architecture that will track satellites and debris by utilizing powerful virtual machines on the Google Cloud Platform. SpaceNav algorithms for processing CDMs outpace conventional means. A robust processing environment for tracking data, collision avoidance maneuvers and various other aspects of SSA can be created and deleted on demand. Migrating SpaceNav tools and algorithms into the Google Cloud Platform will be discussed and the trials and tribulations involved. Information will be shared on how and why certain cloud products were used as well as integration techniques that were implemented. Key items to be presented are: 1.Scientific algorithms and SpaceNav tools integrated into a scalable architecture a) Maneuver Planning b) Parallel Processing c) Monte Carlo Simulations d) Optimization Algorithms e) SW Application Development/Integration into the Google Cloud Platform 2. Compute Engine Processing a) Application Engine Automated Processing b) Performance testing and Performance Scalability c) Cloud MySQL databases and Database Scalability d) Cloud Data Storage e) Redundancy and Availability

Taking Science On-air with Google+

NASA Astrophysics Data System (ADS)

Gay, P.

2014-01-01

Cost has long been a deterrent when trying to stream live events to large audiences. While streaming providers like UStream have free options, they include advertising and typically limit broadcasts to originating from a single location. In the autumn of 2011, Google premiered a new, free, video streaming tool -- Hangouts on Air -- as part of their Google+ social network. This platform allows up to ten different computers to stream live content to an unlimited audience, and automatically archives that content to YouTube. In this article we discuss best practices for using this technology to stream events over the internet.

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.

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.

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.

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.

Tracking the polio virus down the Congo River: a case study on the use of Google Earth™ in public health planning and mapping

PubMed Central

Kamadjeu, Raoul

2009-01-01

Background The use of GIS in public health is growing, a consequence of a rapidly evolving technology and increasing accessibility to a wider audience. Google Earth™ (GE) is becoming an important mapping infrastructure for public health. However, generating traditional public health maps for GE is still beyond the reach of most public health professionals. In this paper, we explain, through the example of polio eradication activities in the Democratic Republic of Congo, how we used GE Earth as a planning tool and we share the methods used to generate public health maps. Results The use of GE improved field operations and resulted in better dispatch of vaccination teams and allocation of resources. It also allowed the creation of maps of high quality for advocacy, training and to help understand the spatiotemporal relationship between all the entities involved in the polio outbreak and response. Conclusion GE has the potential of making mapping available to a new set of public health users in developing countries. High quality and free satellite imagery, rich features including Keyhole Markup Language or image overlay provide a flexible but yet powerful platform that set it apart from traditional GIS tools and this power is still to be fully harnessed by public health professionals. PMID:19161606

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

Recruiting a Diverse Set of Future Geoscientists through Outreach to Middle and High School Students and Teachers in Miami, Florida

NASA Astrophysics Data System (ADS)

Whitman, D.; Hickey-Vargas, R.; Draper, G.; Rego, R.; Gebelein, J.

2014-12-01

Florida International University (FIU), the State University of Florida in Miami is a large enrollment, federally recognized Minority Serving Institution with over 70% of the undergraduate population coming from groups underrepresented in the geoscience workforce. Recruiting local students into the geosciences is challenging because geology is not well integrated into the local school curriculum, the geology is poorly exposed in the low-relief south Florida region and many first generation college students are reluctant to enter unfamiliar fields. We describe and present preliminary findings from Growing Community Roots for the Geosciences in Miami, FL, a 2-year, NSF funded project run by the Department of Earth and Environment at FIU which aims to inform students enrolled in the local middle and high schools to educational and career opportunities in the geosciences. The project takes a multi-faceted approach which includes direct outreach through social media platforms and school visits, a 1-week workshop for middle school teachers and a 2-week summer camp aimed at high school students. An outreach team of undergraduate geoscience majors were recruited to build and maintain informational resources on Facebook, Instagram, Twitter and Google Plus and to accompany FIU faculty on visits to local middle schools and high schools. Both the teacher workshop and the summer camp included lectures on geoscience careers, fundamental concepts of solid earth and atmospheric science, hands on exercises with earth materials, fossils and microscopy, exercises with Google Earth imagery and GIS, and field trips to local geological sites and government facilities. Participants were surveyed at the beginning of the programs on their general educational background in math and science and their general attitudes of and interest in geoscience careers. Post program surveys showed significant increases in the comfort of teaching topics in geoscience among teachers and an increased interest in majoring in geoscience among students. On the final day of the programs, participants were queried on better ways of interesting high school to major in geoscience. Suggestions included visits by faculty and college students to high schools and using social media to promote events and activities.

Googling your hand hygiene data: Using Google Forms, Google Sheets, and R to collect and automate analysis of hand hygiene compliance monitoring.

PubMed

Wiemken, Timothy L; Furmanek, Stephen P; Mattingly, William A; Haas, Janet; Ramirez, Julio A; Carrico, Ruth M

2018-06-01

Hand hygiene is one of the most important interventions in the quest to eliminate healthcare-associated infections, and rates in healthcare facilities are markedly low. Since hand hygiene observation and feedback are critical to improve adherence, we created an easy-to-use, platform-independent hand hygiene data collection process and an automated, on-demand reporting engine. A 3-step approach was used for this project: 1) creation of a data collection form using Google Forms, 2) transfer of data from the form to a spreadsheet using Google Spreadsheets, and 3) creation of an automated, cloud-based analytics platform for report generation using R and RStudio Shiny software. A video tutorial of all steps in the creation and use of this free tool can be found on our YouTube channel: https://www.youtube.com/watch?v=uFatMR1rXqU&t. The on-demand reporting tool can be accessed at: https://crsp.louisville.edu/shiny/handhygiene. This data collection and automated analytics engine provides an easy-to-use environment for evaluating hand hygiene data; it also provides rapid feedback to healthcare workers. By reducing some of the data management workload required of the infection preventionist, more focused interventions may be instituted to increase global hand hygiene rates and reduce infection. Copyright © 2018 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.

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

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.

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.

Estimating Water Levels with Google Earth Engine

NASA Astrophysics Data System (ADS)

Lucero, E.; Russo, T. A.; Zentner, M.; May, J.; Nguy-Robertson, A. L.

2016-12-01

Reservoirs serve multiple functions and are vital for storage, electricity generation, and flood control. For many areas, traditional ground-based reservoir measurements may not be available or data dissemination may be problematic. Consistent monitoring of reservoir levels in data-poor areas can be achieved through remote sensing, providing information to researchers and the international community. Estimates of trends and relative reservoir volume can be used to identify water supply vulnerability, anticipate low power generation, and predict flood risk. Image processing with automated cloud computing provides opportunities to study multiple geographic areas in near real-time. We demonstrate the prediction capability of a cloud environment for identifying water trends at reservoirs in the US, and then apply the method to data-poor areas in North Korea, Iran, Azerbaijan, Zambia, and India. The Google Earth Engine cloud platform hosts remote sensing data and can be used to automate reservoir level estimation with multispectral imagery. We combine automated cloud-based analysis from Landsat image classification to identify reservoir surface area trends and radar altimetry to identify reservoir level trends. The study estimates water level trends using three years of data from four domestic reservoirs to validate the remote sensing method, and five foreign reservoirs to demonstrate the method application. We report correlations between ground-based reservoir level measurements in the US and our remote sensing methods, and correlations between the cloud analysis and altimetry data for reservoirs in data-poor areas. The availability of regular satellite imagery and an automated, near real-time application method provides the necessary datasets for further temporal analysis, reservoir modeling, and flood forecasting. All statements of fact, analysis, or opinion are those of the author and do not reflect the official policy or position of the Department of Defense or any of its components or the U.S. Government

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.

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.

U.S. Army Public Affairs Officers and Social Media Training Requirements

DTIC Science & Technology

2016-06-10

media platforms include Facebook, Twitter, LinkedIn, Google, YouTube, Pinterest, Instagram , and Slideshare.15 According to the Decidedly Social...includes a list of social media platforms that include: Facebook, Twitter, YouTube, Instagram , Tumblr, and private messaging as part of the social...2.62 Using two or more social or sharing media platforms in one campaign 4.72 Instagram 2.37 Print magazines 4.70 Crowdsourcing 2.19 Sharing of

Public health practice course using Google Plus.

PubMed

Wu, Ting-Ting; Sung, Tien-Wen

2014-03-01

In recent years, mobile device-assisted clinical education has become popular among nursing school students. The introduction of mobile devices saves manpower and reduces errors while enhancing nursing students' professional knowledge and skills. To respond to the demands of various learning strategies and to maintain existing systems of education, the concept of Cloud Learning is gradually being introduced to instructional environments. Cloud computing facilitates learning that is personalized, diverse, and virtual. This study involved assessing the advantages of mobile devices and Cloud Learning in a public health practice course, in which Google+ was used as the learning platform, integrating various application tools. Users could save and access data by using any wireless Internet device. The platform was student centered and based on resource sharing and collaborative learning. With the assistance of highly flexible and convenient technology, certain obstacles in traditional practice training can be resolved. Our findings showed that the students who adopted Google+ were learned more effectively compared with those who were limited to traditional learning systems. Most students and the nurse educator expressed a positive attitude toward and were satisfied with the innovative learning method.

Getting the Most from Google Classroom: A Pedagogical Framework for Tertiary Educators

ERIC Educational Resources Information Center

Heggart, Keith R.; Yoo, Joanne

2018-01-01

Many tertiary institutions have embraced digital learning through the use of online learning platforms and social networks. However, the research about the efficacy of such platforms is confused, as is the field itself, in part because of the rapidly evolving technology, and also because of a lack of clarity about what constitutes a learning…

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.

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.

Google-Earth Based Visualizations for Environmental Flows and Pollutant Dispersion in Urban Areas

PubMed Central

Liu, Daoming; Kenjeres, Sasa

2017-01-01

In the present study, we address the development and application of an efficient tool for conversion of results obtained by an integrated computational fluid dynamics (CFD) and computational reaction dynamics (CRD) approach and their visualization in the Google Earth. We focus on results typical for environmental fluid mechanics studies at a city scale that include characteristic wind flow patterns and dispersion of reactive scalars. This is achieved by developing a code based on the Java language, which converts the typical four-dimensional structure (spatial and temporal dependency) of data results in the Keyhole Markup Language (KML) format. The visualization techniques most often used are revisited and implemented into the conversion tool. The potential of the tool is demonstrated in a case study of smog formation due to an intense traffic emission in Rotterdam (The Netherlands). It is shown that the Google Earth can provide a computationally efficient and user-friendly means of data representation. This feature can be very useful for visualization of pollution at street levels, which is of great importance for the city residents. Various meteorological and traffic emissions can be easily visualized and analyzed, providing a powerful, user-friendly tool for traffic regulations and urban climate adaptations. PMID:28257078

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.

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.

Investigating Public Perception of Occupational Therapy: An Environmental Scan of Three Media Outlets.

PubMed

Walsh, Wendy E

Using a phenomenological approach, this study investigated visibility and perception of the profession of occupational therapy in three media outlets. Content analysis occurred on LexisNexis Academic (LNA), Google Images, and Twitter platforms. Analysis of LNA identified the prevalence of articles about occupational therapy in domestic newspapers and similar media avenues, MaxQDA qualitative software coded Google Images from a search on occupational therapy, and AnalyzeWords evaluated Twitter feeds of four health care professions for presence and tone in a social media context. Results indicate that although occupational therapy is 100 years old, its presence in news and online platforms could be stronger. This study suggests that a clear professional identity for occupational therapy practitioners must be strategically communicated through academic and social platforms. Such advocacy promotes the profession, meets the next iteration of occupational therapy's professional vision, and allows occupational therapy to remain a prominent and formidable stakeholder in today's health care marketplace. Copyright © 2018 by the American Occupational Therapy Association, Inc.

Map of Life - A Dashboard for Monitoring Planetary Species Distributions

NASA Astrophysics Data System (ADS)

Jetz, W.

2016-12-01

Geographic information about biodiversity is vital for understanding the many services nature provides and their potential changes, yet remains unreliable and often insufficient. By integrating a wide range of knowledge about species distributions and their dynamics over time, Map of Life supports global biodiversity education, monitoring, research and decision-making. Built on a scalable web platform geared for large biodiversity and environmental data, Map of Life endeavors provides species range information globally and species lists for any area. With data and technology provided by NASA and Google Earth Engine, tools under development use remote sensing-based environmental layers to enable on-the-fly predictions of species distributions, range changes, and early warning signals for threatened species. The ultimate vision is a globally connected, collaborative knowledge- and tool-base for regional and local biodiversity decision-making, education, monitoring, and projection. For currently available tools, more information and to follow progress, go to MOL.org.

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.

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

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.

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.

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 the Spatial Representativeness of NAAQS and Near Roadway Sites Using High-Spatial Resolution Air Pollution Maps Produced by A Mobile Mapping Platform

EPA Science Inventory

In the current study, three Google Street View cars were equipped with the Aclima Environmental Intelligence ™ Platform. The air pollutants of interest, including O3, NO, NO2, CO2, black carbon, and particle number in several size ranges, were measured using a suite of fast...

The Hybrid Studio--Introducing Google+ as a Blended Learning Platform for Architectural Design Studio Teaching

ERIC Educational Resources Information Center

Steinø, Nicolai; Khalid, Md. Saufuddin

2017-01-01

Much architecture and design teaching is based on the studio format, where the co-presence in time and space of students, instructors and physical learning artefacts form a triangle from which the learning emerges. Yet with the advent of online communication platforms and learning management systems (LMS), there is reason to study how these…

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.

Big Data Sensors of Organic Advocacy: The Case of Leonardo DiCaprio and Climate Change

PubMed Central

Althouse, Benjamin M.; Dredze, Mark; Obradovich, Nick; Fowler, James H.; Noar, Seth M.; Allem, Jon-Patrick

2016-01-01

The strategies that experts have used to share information about social causes have historically been top-down, meaning the most influential messages are believed to come from planned events and campaigns. However, more people are independently engaging with social causes today than ever before, in part because online platforms allow them to instantaneously seek, create, and share information. In some cases this “organic advocacy” may rival or even eclipse top-down strategies. Big data analytics make it possible to rapidly detect public engagement with social causes by analyzing the same platforms from which organic advocacy spreads. To demonstrate this claim we evaluated how Leonardo DiCaprio’s 2016 Oscar acceptance speech citing climate change motivated global English language news (Bloomberg Terminal news archives), social media (Twitter postings) and information seeking (Google searches) about climate change. Despite an insignificant increase in traditional news coverage (54%; 95%CI: -144 to 247), tweets including the terms “climate change” or “global warming” reached record highs, increasing 636% (95%CI: 573–699) with more than 250,000 tweets the day DiCaprio spoke. In practical terms the “DiCaprio effect” surpassed the daily average effect of the 2015 Conference of the Parties (COP) and the Earth Day effect by a factor of 3.2 and 5.3, respectively. At the same time, Google searches for “climate change” or “global warming” increased 261% (95%CI, 186–335) and 210% (95%CI 149–272) the day DiCaprio spoke and remained higher for 4 more days, representing 104,190 and 216,490 searches. This increase was 3.8 and 4.3 times larger than the increases observed during COP’s daily average or on Earth Day. Searches were closely linked to content from Dicaprio’s speech (e.g., “hottest year”), as unmentioned content did not have search increases (e.g., “electric car”). Because these data are freely available in real time our analytical strategy provides substantial lead time for experts to detect and participate in organic advocacy while an issue is salient. Our study demonstrates new opportunities to detect and aid agents of change and advances our understanding of communication in the 21st century media landscape. PMID:27482907

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.

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.

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.

Feasibility and Efficacy of a Urologic Profession Campaign on Cryptorchidism Using Internet and Social Media.

PubMed

Borgmann, Hendrik; Kliesch, Sabine; Roth, Stephan; Roth, Mael; Degener, Stephan

2017-01-01

We performed a professional campaign in Germany intending to establish the urologic profession as a competent and helpful point of contact for patients with cryptorchidism. The aim of this study was to assess the feasibility of this campaign and to quantify the efficacy of using Internet vs. social media. The strategic design of the campaign comprised a strategy meeting, creation of a landing page, and targeted advertisements on Google in the form of Adwords and on Facebook in the form of sidebar ads and sponsored posts. Outcome measurements were number of impressions, homepage sessions, and downloads of an information brochure. The campaign generated 2,511,923 impressions, 7,369 homepage sessions and 1,086 downloads of information brochures using a total investment budget of 7,500€. Use of Google Adwords was more efficient on outcome measurements than Facebook. A subanalysis of Facebook advertisements showed that sidebar ads and sponsored posts were equally efficient. New media are an effective platform for a profession campaign. Google Adwords is a more effective and cost-efficient platform than Facebook for a targeted campaign. © 2016 S. Karger AG, Basel.

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…

What Is Being Played in the World? Mobile eSport Applications

ERIC Educational Resources Information Center

Atalay, Ahmet; Topuz, Arif Cem

2018-01-01

In this study, the aim is to examine the most popular eSport applications at a global scale. In this context, the App Store and Google Play Store application platforms which have the highest number of users at a global scale were focused on. For this reason, the eSport applications included in these two platforms constituted the sampling of the…

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.

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.

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.

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

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.

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 ...

Use of Real Time Satellite Infrared and Ocean Color to Produce Ocean Products

NASA Astrophysics Data System (ADS)

Roffer, M. A.; Muller-Karger, F. E.; Westhaver, D.; Gawlikowski, G.; Upton, M.; Hall, C.

2014-12-01

Real-time data products derived from infrared and ocean color satellites are useful for several types of users around the world. Highly relevant applications include recreational and commercial fisheries, commercial towing vessel and other maritime and navigation operations, and other scientific and applied marine research. Uses of the data include developing sampling strategies for research programs, tracking of water masses and ocean fronts, optimizing ship routes, evaluating water quality conditions (coastal, estuarine, oceanic), and developing fisheries and essential fish habitat indices. Important considerations for users are data access and delivery mechanisms, and data formats. At this time, the data are being generated in formats increasingly available on mobile computing platforms, and are delivered through popular interfaces including social media (Facebook, Linkedin, Twitter and others), Google Earth and other online Geographical Information Systems, or are simply distributed via subscription by email. We review 30 years of applications and describe how we develop customized products and delivery mechanisms working directly with users. We review benefits and issues of access to government databases (NOAA, NASA, ESA), standard data products, and the conversion to tailored products for our users. We discuss advantages of different product formats and of the platforms used to display and to manipulate the data.

Steam distribution and energy delivery optimization using wireless sensors

NASA Astrophysics Data System (ADS)

Olama, Mohammed M.; Allgood, Glenn O.; Kuruganti, Teja P.; Sukumar, Sreenivas R.; Djouadi, Seddik M.; Lake, Joe E.

2011-05-01

The Extreme Measurement Communications Center at Oak Ridge National Laboratory (ORNL) explores the deployment of a wireless sensor system with a real-time measurement-based energy efficiency optimization framework in the ORNL campus. With particular focus on the 12-mile long steam distribution network in our campus, we propose an integrated system-level approach to optimize the energy delivery within the steam distribution system. We address the goal of achieving significant energy-saving in steam lines by monitoring and acting on leaking steam valves/traps. Our approach leverages an integrated wireless sensor and real-time monitoring capabilities. We make assessments on the real-time status of the distribution system by mounting acoustic sensors on the steam pipes/traps/valves and observe the state measurements of these sensors. Our assessments are based on analysis of the wireless sensor measurements. We describe Fourier-spectrum based algorithms that interpret acoustic vibration sensor data to characterize flows and classify the steam system status. We are able to present the sensor readings, steam flow, steam trap status and the assessed alerts as an interactive overlay within a web-based Google Earth geographic platform that enables decision makers to take remedial action. We believe our demonstration serves as an instantiation of a platform that extends implementation to include newer modalities to manage water flow, sewage and energy consumption.

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 ...

Landsat Time-series for the Masses: Predicting Wood Biomass Growth from Tree-rings Using Departures from Mean Phenology in Google Earth Engine

NASA Astrophysics Data System (ADS)

Foster, J. R.; D'Amato, A. W.; Itter, M.; Reinikainen, M.; Curzon, M.

2017-12-01

The terrestrial carbon cycle is perturbed when disturbances remove leaf biomass from the forest canopy during the growing season. Changes in foliar biomass arise from defoliation caused by insects, disease, drought, frost or human management. As ephemeral disturbances, these often go undetected and their significance to models that predict forest growth from climatic drivers remains unknown. Here, we seek to distinguish the roles of weather vs. canopy disturbance on forest growth by using dense Landsat time-series to quantify departures in mean phenology that in turn predict changes in leaf biomass. We estimated a foliar biomass index (FBMI) from 1984-2016, and predict plot-level wood growth over 28 years on 156 tree-ring monitoring plots in Minnesota, USA. We accessed the entire Landsat archive (sensors 4, 5 & 7) to compute FBMI using Google Earth Engine's cloud computing platform (GEE). GEE allows this pixel-level approach to be applied at any location; a feature we demonstrate with published wood-growth data from flux tower sites. Our Bayesian models predicted biomass changes from tree-ring plots as a function of Landsat FBMI and annual climate data. We expected model parameters to vary by tree functional groups defined by differences in xylem anatomy and leaf longevity, two traits with linkages to phenology, as reported in a recent review. We found that Landsat FBMI was a surprisingly strong predictor of aggregate wood-growth, explaining up to 80% of annual growth variation for some deciduous plots. Growth responses to canopy disturbance varied among tree functional groups, and the importance of some seasonal climate metrics diminished or changed sign when FBMI was included (e.g. fall and spring climatic water deficit), while others remained unchanged (current and lagged summer deficit). Insights emerging from these models can clear up sources of persistent uncertainty and open a new frontier for models of forest productivity.

A pan-Arctic Assessment of Hydraulic Geometry

NASA Astrophysics Data System (ADS)

Chen, H. Z. D.; Gleason, C. J.

2016-12-01

Arctic Rivers are a crucial part of the global hydrologic cycle, especially as our climate system alters toward an uncertain future. These rivers have many ecological and societal functions, such as funneling meltwater to the ocean and act as critical winter transport for arctic communities. Despite this importance, their fluvial geomorphology, in particular their hydraulic geometry (HG) is not fully understood due to their often remote locations. HG, including at-a-station (AHG), downstream (DHG), and the recently discovered At-many-stations (AMHG), provides the empirical basis between gauging measurements and how rivers respond to varying flow conditions, serving as an indicator to the critical functions mentioned above. Hence, a systematic cataloging of the AHG, DHG, and AMHG, of Arctic rivers is needed for a pan-Arctic view of fluvial geomorphic behavior. This study will document the width-based AHG, DHG, and AMHG for rivers wider than 120m with an Arctic Ocean drainage and gauge data with satellite records. First, we will make time-series width measurements from classified imagery at locations along all such rivers from Landsat archive since 1984, accessed within the Google Earth Engine cloud computing environment. Second, we will run available gauge data for width-based AHG, DHG, and AMHG over large river reaches. Lastly, we will assess these empirical relationships, seek regional trends, and changes in HG over time as climate change has on the Arctic system. This is part of an ongoing process in the larger scope of data calibration/validation for the Surface Water and Ocean Topography (SWOT) satellite planned for 2020, and HG mapping will aid the selection of field validation sites. The work showcase an unprecedented opportunity to process and retrieve scientifically significant HG data in the often inaccessible Arctic via Google Earth Engine. This unique platform makes such broad scale study possible, providing a blueprint for future large-area HG research.

Virtual Reality as a Story Telling Platform for Geoscience Communication

NASA Astrophysics Data System (ADS)

Lazar, K.; Moysey, S. M.

2017-12-01

Capturing the attention of students and the public is a critical step for increasing societal interest and literacy in earth science issues. Virtual reality (VR) provides a means for geoscience engagement that is well suited to place-based learning through exciting and immersive experiences. One approach is to create fully-immersive virtual gaming environments where players interact with physical objects, such as rock samples and outcrops, to pursue geoscience learning goals. Developing an experience like this, however, can require substantial programming expertise and resources. At the other end of the development spectrum, it is possible for anyone to create immersive virtual experiences with 360-degree imagery, which can be made interactive using easy to use VR editing software to embed videos, audio, images, and other content within the 360-degree image. Accessible editing tools like these make the creation of VR experiences something that anyone can tackle. Using the VR editor ThingLink and imagery from Google Maps, for example, we were able to create an interactive tour of the Grand Canyon, complete with embedded assessments, in a matter of hours. The true power of such platforms, however, comes from the potential to engage students as content authors to create and share stories of place that explore geoscience issues from their personal perspective. For example, we have used combinations of 360-degree images with interactive mapping and web platforms to enable students with no programming experience to create complex web apps as highly engaging story telling platforms. We highlight here examples of how we have implemented such story telling approaches with students to assess learning in courses, to share geoscience research outcomes, and to communicate issues of societal importance.

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.

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.

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.

The AppScale Cloud Platform

PubMed Central

Krintz, Chandra

2013-01-01

AppScale is an open source distributed software system that implements a cloud platform as a service (PaaS). AppScale makes cloud applications easy to deploy and scale over disparate cloud fabrics, implementing a set of APIs and architecture that also makes apps portable across the services they employ. AppScale is API-compatible with Google App Engine (GAE) and thus executes GAE applications on-premise or over other cloud infrastructures, without modification. PMID:23828721

The Snow Data System at NASA JPL

NASA Astrophysics Data System (ADS)

Laidlaw, R.; Painter, T. H.; Mattmann, C. A.; Ramirez, P.; Bormann, K.; Brodzik, M. J.; Burgess, A. B.; Rittger, K.; Goodale, C. E.; Joyce, M.; McGibbney, L. J.; Zimdars, P.

2014-12-01

NASA JPL's Snow Data System has a data-processing pipeline powered by Apache OODT, an open source software tool. The pipeline has been running for several years and has successfully generated a significant amount of cryosphere data, including MODIS-based products such as MODSCAG, MODDRFS and MODICE, with historical and near-real time windows and covering regions such as the Artic, Western US, Alaska, Central Europe, Asia, South America, Australia and New Zealand. The team continues to improve the pipeline, using monitoring tools such as Ganglia to give an overview of operations, and improving fault-tolerance with automated recovery scripts. Several alternative adaptations of the Snow Covered Area and Grain size (SCAG) algorithm are being investigated. These include using VIIRS and Landsat TM/ETM+ satellite data as inputs. Parallel computing techniques are being considered for core SCAG processing, such as using the PyCUDA Python API to utilize multi-core GPU architectures. An experimental version of MODSCAG is also being developed for the Google Earth Engine platform, a cloud-based service.

Planetary-scale surface water detection from space

NASA Astrophysics Data System (ADS)

Donchyts, G.; Baart, F.; Winsemius, H.; Gorelick, N.

2017-12-01

Accurate, efficient and high-resolution methods of surface water detection are needed for a better water management. Datasets on surface water extent and dynamics are crucial for a better understanding of natural and human-made processes, and as an input data for hydrological and hydraulic models. In spite of considerable progress in the harmonization of freely available satellite data, producing accurate and efficient higher-level surface water data products remains very challenging. This presentation will provide an overview of existing methods for surface water extent and change detection from multitemporal and multi-sensor satellite imagery. An algorithm to detect surface water changes from multi-temporal satellite imagery will be demonstrated as well as its open-source implementation (http://aqua-monitor.deltares.nl). This algorithm was used to estimate global surface water changes at high spatial resolution. These changes include climate change, land reclamation, reservoir construction/decommissioning, erosion/accretion, and many other. This presentation will demonstrate how open satellite data and open platforms such as Google Earth Engine have helped with this research.

Vulnerable transportation and utility assets near actively migrating streams in Indiana

USGS Publications Warehouse

Sperl, Benjamin J.

2017-11-02

An investigation was completed by the U.S. Geological Survey in cooperation with the Indiana Office of Community and Rural Affairs that found 1,132 transportation and utility assets in Indiana are vulnerable to fluvial erosion hazards due to close proximity to actively migrating streams. Locations of transportation assets (bridges, roadways, and railroad lines) and selected utility assets (high-capacity overhead power-transmission lines, underground pipelines, water treatment facilities, and in-channel dams) were determined using aerial imagery hosted by the Google Earth platform. Identified assets were aggregated by stream reach, county, and class. Accompanying the report is a polyline shapefile of the stream reaches documented by Robinson. The shapefile, derived from line work in the National Hydrography Dataset and attributed with channel migration rates, is released with complete Federal Geographic Data Committee metadata. The data presented in this report are intended to help stakeholders and others identify high-risk areas where transportation and utility assets may be threatened by fluvial erosion hazards thus warranting consideration for mitigation strategies.

Using a digital marketing platform for the promotion of an internet based health encyclopedia in saudi arabia.

PubMed

Al Ateeq, Asma; Al Moamary, Eman; Daghestani, Tahani; Al Muallem, Yahya; Al Dogether, Majed; Alsughayr, Abdulrahman; Altuwaijri, Majid; Househ, Mowafa

2015-01-01

The objective of this paper is to investigate the experiences of using a digital marketing platform to promote the use of an internet based health encyclopedia in Saudi Arabia. Key informant interviews, meeting documentation, and Google Analytics were the data collection sources used in the study. Findings show that using a digital marketing platform led to a significant increase in the number of visitors to the health encyclopedia. The results demonstrate that digital marketing platforms are effective tools to be used for promoting internet based health education interventions. Future work will examine long-term educational impacts and costs in using digital marketing platforms to promote online healthcare sites in Saudi Arabia.

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.

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.

Moon-based Earth Observation for Large Scale Geoscience Phenomena

NASA Astrophysics Data System (ADS)

Guo, Huadong; Liu, Guang; Ding, Yixing

2016-07-01

The capability of Earth observation for large-global-scale natural phenomena needs to be improved and new observing platform are expected. We have studied the concept of Moon as an Earth observation in these years. Comparing with manmade satellite platform, Moon-based Earth observation can obtain multi-spherical, full-band, active and passive information,which is of following advantages: large observation range, variable view angle, long-term continuous observation, extra-long life cycle, with the characteristics of longevity ,consistency, integrity, stability and uniqueness. Moon-based Earth observation is suitable for monitoring the large scale geoscience phenomena including large scale atmosphere change, large scale ocean change,large scale land surface dynamic change,solid earth dynamic change,etc. For the purpose of establishing a Moon-based Earth observation platform, we already have a plan to study the five aspects as follows: mechanism and models of moon-based observing earth sciences macroscopic phenomena; sensors' parameters optimization and methods of moon-based Earth observation; site selection and environment of moon-based Earth observation; Moon-based Earth observation platform; and Moon-based Earth observation fundamental scientific framework.

3D multiplayer virtual pets game using Google Card Board

NASA Astrophysics Data System (ADS)

Herumurti, Darlis; Riskahadi, Dimas; Kuswardayan, Imam

2017-08-01

Virtual Reality (VR) is a technology which allows user to interact with the virtual environment. This virtual environment is generated and simulated by computer. This technology can make user feel the sensation when they are in the virtual environment. The VR technology provides real virtual environment view for user and it is not viewed from screen. But it needs another additional device to show the view of virtual environment. This device is known as Head Mounted Device (HMD). Oculust Rift and Microsoft Hololens are the most famous HMD devices used in VR. And in 2014, Google Card Board was introduced at Google I/O developers conference. Google Card Board is VR platform which allows user to enjoy the VR with simple and cheap way. In this research, we explore Google Card Board to develop simulation game of raising pet. The Google Card Board is used to create view for the VR environment. The view and control in VR environment is built using Unity game engine. And the simulation process is designed using Finite State Machine (FSM). This FSM can help to design the process clearly. So the simulation process can describe the simulation of raising pet well. Raising pet is fun activity. But sometimes, there are many conditions which cause raising pet become difficult to do, i.e. environment condition, disease, high cost, etc. this research aims to explore and implement Google Card Board in simulation of raising pet.

Observation duration analysis for Earth surface features from a Moon-based platform

NASA Astrophysics Data System (ADS)

Ye, Hanlin; Guo, Huadong; Liu, Guang; Ren, Yuanzhen

2018-07-01

Earth System Science is a discipline that performs holistic and comprehensive research on various components of the Earth. One of a key issue for the Earth monitoring and observation is to enhance the observation duration, the time intervals during which the Earth surface features can be observed by sensors. In this work, we propose to utilise the Moon as an Earth observation platform. Thanks to the long distance between the Earth and the Moon, and the vast space on the lunar surface which is suitable for sensor installation, this Earth observation platform could have large spatial coverage, long temporal duration, and could perform multi-layer detection of the Earth. The line of sight between a proposed Moon-based platform and the Earth will change with different lunar surface positions; therefore, in this work, the position of the lunar surface was divided into four regions, including one full observation region and three incomplete observation regions. As existing methods are not able to perform global-scale observations, a Boolean matrix method was established to calculate the necessary observation durations from a Moon-based platform. Based on Jet Propulsion Laboratory (JPL) ephemerides and Earth Orientation Parameters (EOP), a formula was developed to describe the geometrical relationship between the Moon-based platform and Earth surface features in the unified spatial coordinate system and the unified time system. In addition, we compared the observation geometries at different positions on the lunar surface and two parameters that are vital to observation duration calculations were considered. Finally, an analysis method was developed. We found that the observation duration of a given Earth surface feature shows little difference regardless of sensor position within the full observation region. However, the observation duration for sensors in the incomplete observation regions is reduced by at least half. In summary, our results demonstrate the suitability of a Moon-based platform located in the full observation region.

Keemei: cloud-based validation of tabular bioinformatics file formats in Google Sheets.

PubMed

Rideout, Jai Ram; Chase, John H; Bolyen, Evan; Ackermann, Gail; González, Antonio; Knight, Rob; Caporaso, J Gregory

2016-06-13

Bioinformatics software often requires human-generated tabular text files as input and has specific requirements for how those data are formatted. Users frequently manage these data in spreadsheet programs, which is convenient for researchers who are compiling the requisite information because the spreadsheet programs can easily be used on different platforms including laptops and tablets, and because they provide a familiar interface. It is increasingly common for many different researchers to be involved in compiling these data, including study coordinators, clinicians, lab technicians and bioinformaticians. As a result, many research groups are shifting toward using cloud-based spreadsheet programs, such as Google Sheets, which support the concurrent editing of a single spreadsheet by different users working on different platforms. Most of the researchers who enter data are not familiar with the formatting requirements of the bioinformatics programs that will be used, so validating and correcting file formats is often a bottleneck prior to beginning bioinformatics analysis. We present Keemei, a Google Sheets Add-on, for validating tabular files used in bioinformatics analyses. Keemei is available free of charge from Google's Chrome Web Store. Keemei can be installed and run on any web browser supported by Google Sheets. Keemei currently supports the validation of two widely used tabular bioinformatics formats, the Quantitative Insights into Microbial Ecology (QIIME) sample metadata mapping file format and the Spatially Referenced Genetic Data (SRGD) format, but is designed to easily support the addition of others. Keemei will save researchers time and frustration by providing a convenient interface for tabular bioinformatics file format validation. By allowing everyone involved with data entry for a project to easily validate their data, it will reduce the validation and formatting bottlenecks that are commonly encountered when human-generated data files are first used with a bioinformatics system. Simplifying the validation of essential tabular data files, such as sample metadata, will reduce common errors and thereby improve the quality and reliability of research outcomes.

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.

Developing and Benchmarking Native Linux Applications on Android

NASA Astrophysics Data System (ADS)

Batyuk, Leonid; Schmidt, Aubrey-Derrick; Schmidt, Hans-Gunther; Camtepe, Ahmet; Albayrak, Sahin

Smartphones get increasingly popular where more and more smartphone platforms emerge. Special attention was gained by the open source platform Android which was presented by the Open Handset Alliance (OHA) hosting members like Google, Motorola, and HTC. Android uses a Linux kernel and a stripped-down userland with a custom Java VM set on top. The resulting system joins the advantages of both environments, while third-parties are intended to develop only Java applications at the moment.

Mapping snow cover using multi-source satellite data on big data platforms

NASA Astrophysics Data System (ADS)

Lhermitte, Stef

2017-04-01

Snowmelt is an important and dynamically changing water resource in mountainous regions around the world. In this framework, remote sensing data of snow cover data provides an essential input for hydrological models to model the water contribution from remote mountain areas and to understand how this water resource might alter as a result of climate change. Traditionally, however, many of these remote sensing products show a trade-off between spatial and temporal resolution (e.g., 16-day Landsat at 30m vs. daily MODIS at 500m resolution). With the advent of Sentinel-1 and 2 and the PROBA-V 100m products this trade-off can partially be tackled by having data that corresponds more closely to the spatial and temporal variations in snow cover typically observed over complex mountain areas. This study provides first a quantitative analysis of the trade-offs between the state-of-the-art snow cover mapping methodologies for Landsat, MODIS, PROBA-V, Sentinel-1 and 2 and applies them on big data platforms such as Google Earth Engine (GEE), RSS (ESA Research Service & Support) CloudToolbox, and the PROBA-V Mission Exploitation Platform (MEP). Second, it combines the different sensor data-cubes in one multi-sensor classification approach using newly developed spatio-temporal probability classifiers within the big data platform environments. Analysis of the spatio-temporal differences in derived snow cover areas from the different sensors reveals the importance of understanding the spatial and temporal scales at which variations occur. Moreover, it shows the importance of i) temporal resolution when monitoring highly dynamical properties such as snow cover and of ii) differences in satellite viewing angles over complex mountain areas. Finally, it highlights the potential and drawbacks of big data platforms for combining multi-source satellite data for monitoring dynamical processes such as snow cover.

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…

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.

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.

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.

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.

Interactive Mapping of the Planets: An Online Activity Using the Google Earth Platform

NASA Astrophysics Data System (ADS)

Osinski, G. R.; Gilbert, A.; Harrison, T. N.; Mader, M. M.; Shankar, B.; Tornabene, L. L.

2013-12-01

With funding from the Natural Sciences and Engineering Research Council of Canada's PromoScience program and support from the Department of Earth Sciences at The University of Western Ontario, the Centre for Planetary Science and Exploration (CPSX) has developed a new web-based initiative called Interactive Mapping of the Planets (IMAPS). Additional components include in person school visits to deliver inquiry-based workshops, week-long summer camps, and pre-prepared impact rock lending kits, all framed around the IMAPS activity. IMAPS will is now in beta testing mode and will be demonstrated in this session. The general objective of the online activity is for participants to plan and design a rover mission to Mars based on a given mission goal - e.g., to find evidence for past water flow. The activity begins with participants receiving image-analysis training to learn about the different landforms on Mars and which ones are potentially caused by water flow. They then need to pass a short test to show they can consistently identify Martian landforms. From there, the participants choose a landing site and plan a traverse - utilizing the free Google Earth plug-in - and taking into account factors such as hazards and their sites of interest. A mission control blog will provide updates on the status of their mission and a 'choose your rover' option provides the opportunity to unlock more advanced rovers by collaborating with other scientists and rating their missions. Indeed, evaluation of missions will be done using a crowd-sourcing method. In addition to being fully accessible online, CPSX will also target primary- and secondary-school grades in which astronomy and space science is taught. Teachers in K-12 classrooms will be able to sign-up for the activity ahead of time in order to receive a workshop package, which will guide them on how to use the IMAPS online activity with their class. Teachers will be able to set up groups for their classroom so that they can evaluate their students based on pre-determined criteria. The IMAPS activities are developed in partnerships with the Department of Earth Sciences at Western University, Sports Western, the Thames Valley District School Board, and Dimentians Web Marketing and Design. We are continually looking for new collaborators to help design or test our inquiry- and web-based activities, provide feedback on our programs, or volunteer with us. Please contact cpsxoutreach@uwo.ca if you are interested.

Mobile Device Management

DTIC Science & Technology

2012-01-01

password policies (or smart card authentication), disabling compo- nents of the operating system that were deemed unsafe, allowing users to only install...written nearly 100 applications for the iOS and Android platforms with over 1,500,000 downloads on iTunes and Google Play. CPT Braunstein is a

Surgical smartphone applications across different platforms: their evolution, uses, and users.

PubMed

Kulendran, Myutan; Lim, Marcus; Laws, Georgia; Chow, Andre; Nehme, Jean; Darzi, Ara; Purkayastha, Sanjay

2014-08-01

There are a vast array of smartphone applications that could benefit both surgeons and their patients. To review and identify all relevant surgical smartphone applications available for the Apple iPhone iOS and Google Android platform based on their user group and subspecialty for which they were designed. Both the literature using PubMed and Google Scholar were searched using the following terms: application$, smartphone$, app$, app*, surgery, surgical, surg*, general surgery, general surg*, bariatric$, urology and plastic surgery, ortho*, orthop(a)edic, cardiac surgery, cardiothoracic, neurosurgery, and ophthalmology. The search yielded 38 articles of which 23 were eligible. Each of the key specialties was searched in the Apple iTunes App Store for iPhone iOS and the Google Play Android application store. In total, there were 621 surgical applications for Apple iPhone iOS and 97 identified on Android's Google Play. There has been a 9-fold increase in the number of surgical applications available for the Apple iPhone iOS from 2009 to 2012. Of these applications there were 126 dedicated to plastic surgery, 79 to orthopedics, 41 to neurosurgical, 180 to general surgery, 36 to cardiac surgery, 121 to ophthalmology, and 44 to urology. There was a wide range of applications ranging from simple flashcards to be used for revision to virtual surgery applications that provided surgical exposure and familiarization with common operative procedures. Despite the plethora of surgical applications available for smartphones, there is no taxonomy for medical applications. Only 12% were affiliated with an academic institution or association, which highlights the need for greater regulation of surgical applications. © The Author(s) 2014.

Seismicity map tools for earthquake studies

NASA Astrophysics Data System (ADS)

Boucouvalas, Anthony; Kaskebes, Athanasios; Tselikas, Nikos

2014-05-01

We report on the development of new and online set of tools for use within Google Maps, for earthquake research. We demonstrate this server based and online platform (developped with PHP, Javascript, MySQL) with the new tools using a database system with earthquake data. The platform allows us to carry out statistical and deterministic analysis on earthquake data use of Google Maps and plot various seismicity graphs. The tool box has been extended to draw on the map line segments, multiple straight lines horizontally and vertically as well as multiple circles, including geodesic lines. The application is demonstrated using localized seismic data from the geographic region of Greece as well as other global earthquake data. The application also offers regional segmentation (NxN) which allows the studying earthquake clustering, and earthquake cluster shift within the segments in space. The platform offers many filters such for plotting selected magnitude ranges or time periods. The plotting facility allows statistically based plots such as cumulative earthquake magnitude plots and earthquake magnitude histograms, calculation of 'b' etc. What is novel for the platform is the additional deterministic tools. Using the newly developed horizontal and vertical line and circle tools we have studied the spatial distribution trends of many earthquakes and we here show for the first time the link between Fibonacci Numbers and spatiotemporal location of some earthquakes. The new tools are valuable for examining visualizing trends in earthquake research as it allows calculation of statistics as well as deterministic precursors. We plan to show many new results based on our newly developed platform.

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.

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)

Using Multi-Temporal Remote Sensing Data to Analyze the Spatio-Temporal Patterns of Dry Season Rice Production in Bangladesh

NASA Astrophysics Data System (ADS)

Shew, A. M.; Ghosh, A.

2017-10-01

Remote sensing in the optical domain is widely used in agricultural monitoring; however, such initiatives pose a challenge for developing countries due to a lack of high quality in situ information. Our proposed methodology could help developing countries bridge this gap by demonstrating the potential to quantify patterns of dry season rice production in Bangladesh. To analyze approximately 90,000 km2 of cultivated land in Bangladesh at 30 m spatial resolution, we used two decades of remote sensing data from the Landsat archive and Google Earth Engine (GEE), a cloud-based geospatial data analysis platform built on Google infrastructure and capable of processing petabyte-scale remote sensing data. We reconstructed the seasonal patterns of vegetation indices (VIs) for each pixel using a harmonic time series (HTS) model, which minimizes the effects of missing observations and noise. Next, we combined the seasonality information of VIs with our knowledge of rice cultivation systems in Bangladesh to delineate rice areas in the dry season, which are predominantly hybrid and High Yielding Varieties (HYV). Based on historical Landsat imagery, the harmonic time series of vegetation indices (HTS-VIs) model estimated 4.605 million ha, 3.519 million ha, and 4.021 million ha of rice production for Bangladesh in 2005, 2010, and 2015 respectively. Fine spatial scale information on HYV rice over the last 20 years will greatly improve our understanding of double-cropped rice systems, current status of production, and potential for HYV rice adoption in Bangladesh during the dry season.

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.

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.

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.

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.

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

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.

Web-Based Learning for Cultural Heritage: First Experienced with Students of the Private University of Technology in Northern Taiwan

NASA Astrophysics Data System (ADS)

Yen, Y.-N.; Wu, Y.-W.; Weng, K.-H.

2013-07-01

E-learning assisted teaching and learning is the trend of the 21st century and has many advantages - freedom from the constraints of time and space, hypertext and multimedia rich resources - enhancing the interaction between students and the teaching materials. The purpose of this study is to explore how rich Internet resources assisted students with the Western Architectural History course. First, we explored the Internet resources which could assist teaching and learning activities. Second, according to course objectives, we built a web-based platform which integrated the Google spreadsheets form, SIMILE widget, Wikipedia and the Google Maps and applied it to the course of Western Architectural History. Finally, action research was applied to understanding the effectiveness of this teaching/learning mode. Participants were the students of the Department of Architecture in the Private University of Technology in northern Taiwan. Results showed that students were willing to use the web-based platform to assist their learning. They found this platform to be useful in understanding the relationship between different periods of buildings. Through the view of the map mode, this platform also helped students expand their international perspective. However, we found that the information shared by students via the Internet were not completely correct. One possible reason was that students could easily acquire information on Internet but they could not determine the correctness of the information. To conclude, this study found some useful and rich resources that could be well-integrated, from which we built a web-based platform to collect information and present this information in diverse modes to stimulate students' learning motivation. We recommend that future studies should consider hiring teaching assistants in order to ease the burden on teachers, and to assist in the maintenance of information quality.

Development of a New Research Data Infrastructure for Collaboration in Earth Observation and Global Change Science

NASA Astrophysics Data System (ADS)

Wagner, Wolfgang; Briese, Christian

2017-04-01

With the global population having surpassed 7 billion people in 2012, the impacts of human activities on the environment have started to be noticeable almost everywhere on our planet. Yet, while pressing social problems such as mass migration may be at least be partly a consequence of these impacts, many are still elusive, particularly when trying to quantify them on larger scales. Therefore, it is essential to collect verifiable observations that allow tracing environmental changes from a local to global scale over several decades. Complementing in situ networks, this task is increasingly fulfilled by earth observation satellites which have been acquiring measurements of the land, atmosphere and oceans since the beginning of the 1970s. While many multi-decadal data sets are already available, the major limitation hindering their effective exploitation in global change studies is the lack of dedicated data centres offering the high performance processing capabilities needed to process multi-year global data sets at a fine spatial resolution (Wagner, 2015). Essentially the only platform which currently offers these capabilities is Google's Earth Engine. From a scientific perspective there is undoubtedly a high need to build up independent science-driven platforms that are transparent for their users and offer a higher diversity and flexibility in terms of the data sets and algorithms used. Recognizing this need, TU Wien founded the EODC Earth Observation Data Centre for Water Resources Monitoring together with other Austrian partners in May 2014 as a public-private partnership (Wagner et al. 2014). Thanks to its integrative governance approach, EODC has succeeded of quickly developing an international cooperation consisting of scientific institutions, public organisations and several private partners. Making best use of their existing infrastructures, the EODC partners have already created the first elements of a federated IT infrastructure capable of storing and processing Petabytes of satellite data. One central site of this infrastructure is the Science Centre Arsenal in Vienna, where a cloud platform and storage system were set up and connected to the Vienna Scientific Cluster (VSC). To provide functionality, this facility connects several hardware components including a Petabyte-scale frontend storage for making data available for scientific analysis and high-performance-computing on the VSC, and robotic tape libraries for mirroring and archiving tens of Petabyte of data. In this contribution, the EODC approach for building a federated IT infrastructure and collaborative data storage and analysis capabilities are presented. REFERENCES Wagner, W. (2015) Big Data infrastructures for processing Sentinel data, in Photogrammetric Week 2015, Dieter Fritsch (Ed.), Wichmann/VDE, Berlin Offenbach, 93-104. Wagner, W., J. Fröhlich, G. Wotawa, R. Stowasser, M. Staudinger, C. Hoffmann, A. Walli, C. Federspiel, M. Aspetsberger, C. Atzberger, C. Briese, C. Notarnicola, M. Zebisch, A. Boresch, M. Enenkel, R. Kidd, A. von Beringe, S. Hasenauer, V. Naeimi, W. Mücke (2014) Addressing grand challenges in earth observation science: The Earth Observation Data Centre for Water Resources Monitoring, ISPRS Commission VII Symposium, Istanbul, Turkey, 29 September-2 October 2014, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Annals), Volume II-7, 81-88.

Moon-Based INSAR Geolocation and Baseline Analysis

NASA Astrophysics Data System (ADS)

Liu, Guang; Ren, Yuanzhen; Ye, Hanlin; Guo, Huadong; Ding, Yixing; Ruan, Zhixing; Lv, Mingyang; Dou, Changyong; Chen, Zhaoning

2016-07-01

Earth observation platform is a host, the characteristics of the platform in some extent determines the ability for earth observation. Currently most developing platforms are satellite, in contrast carry out systematic observations with moon based Earth observation platform is still a new concept. The Moon is Earth's only natural satellite and is the only one which human has reached, it will give people different perspectives when observe the earth with sensors from the moon. Moon-based InSAR (SAR Interferometry), one of the important earth observation technology, has all-day, all-weather observation ability, but its uniqueness is still a need for analysis. This article will discuss key issues of geometric positioning and baseline parameters of moon-based InSAR. Based on the ephemeris data, the position, liberation and attitude of earth and moon will be obtained, and the position of the moon-base SAR sensor can be obtained by coordinate transformation from fixed seleno-centric coordinate systems to terrestrial coordinate systems, together with the Distance-Doppler equation, the positioning model will be analyzed; after establish of moon-based InSAR baseline equation, the different baseline error will be analyzed, the influence of the moon-based InSAR baseline to earth observation application will be obtained.

Aeolian transport of Icelandic dust: a look from Space

NASA Astrophysics Data System (ADS)

Smejda, Ladislav; Dagsson Waldhauserova, Pavla; Hejcman, Michal

2017-04-01

Iceland represents a unique type of Arctic environment where glaciers capture the precipitation, consequently forming large deserts on the leeward side. Deserts are subject to strong winds and dust is reported to be suspended at least 135 days a year. Icelandic dust has seven major dust sources in extensive deserts, consisting mainly of volcanic glass. In this paper, we address a new approach to the question of the island's contribution to atmospheric dust transport in the North Atlantic and Arctic Oceans. We explore the strengths and limitations of satellite imagery for the study of high altitude dust storm phenomenon, and more specifically the potential of freely available set of tools for remote sensing and spatial data analysis, the Earth Engine provided by Google. This cloud-based geospatial processing platform requires only a web browser on the side of a user, and it allows writing powerful and versatile algorithms for scientific analysis of spatial data. We demonstrate how this approach can be applied to mapping of Icelandic dust sources and studying the wind erosion and transport of particles in the atmosphere in high latitudes.

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

Advanced propulsion for LEO and GEO platforms

NASA Technical Reports Server (NTRS)

Sovey, James S.; Pidgeon, David J.

1990-01-01

Mission requirements and mass savings applicable to specific low earth orbit and geostationary earth orbit platforms using three highly developed propulsion systems are described. Advanced hypergolic bipropellant thrusters and hydrazine arcjets can provide about 11 percent additional instrument payload to 14,000 kg LEO platforms. By using electric propulsion on a 8,000 kg class GEO platform, mass savings in excess of 15 percent of the beginning-of-life platform mass are obtained. Effects of large, advanced technology solar arrays and antennas on platform propulsion requirements are also discussed.

Novel Use of Google Glass for Procedural Wireless Vital Sign Monitoring.

PubMed

Liebert, Cara A; Zayed, Mohamed A; Aalami, Oliver; Tran, Jennifer; Lau, James N

2016-08-01

Purpose This study investigates the feasibility and potential utility of head-mounted displays for real-time wireless vital sign monitoring during surgical procedures. Methods In this randomized controlled pilot study, surgery residents (n = 14) performed simulated bedside procedures with traditional vital sign monitors and were randomized to addition of vital sign streaming to Google Glass. Time to recognition of preprogrammed vital sign deterioration and frequency of traditional monitor use was recorded. User feedback was collected by electronic survey. Results The experimental group spent 90% less time looking away from the procedural field to view traditional monitors during bronchoscopy (P = .003), and recognized critical desaturation 8.8 seconds earlier; the experimental group spent 71% (P = .01) less time looking away from the procedural field during thoracostomy, and recognized hypotension 10.5 seconds earlier. Trends toward earlier recognition of deterioration did not reach statistical significance. The majority of participants agreed that Google Glass increases situational awareness (64%), is helpful in monitoring vitals (86%), is easy to use (93%), and has potential to improve patient safety (85%). Conclusion In this early feasibility study, use of streaming to Google Glass significantly decreased time looking away from procedural fields and resulted in a nonsignificant trend toward earlier recognition of vital sign deterioration. Vital sign streaming with Google Glass or similar platforms is feasible and may enhance procedural situational awareness. © The Author(s) 2016.

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.

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.

Mapping paddy rice planting area in northeastern Asia with Landsat 8 images, phenology-based algorithm and Google Earth Engine

PubMed Central

Dong, Jinwei; Xiao, Xiangming; Menarguez, Michael A.; Zhang, Geli; Qin, Yuanwei; Thau, David; Biradar, Chandrashekhar; Moore, Berrien

2016-01-01

Area and spatial distribution information of paddy rice are important for understanding of food security, water use, greenhouse gas emission, and disease transmission. Due to climatic warming and increasing food demand, paddy rice has been expanding rapidly in high latitude areas in the last decade, particularly in northeastern (NE) Asia. Current knowledge about paddy rice fields in these cold regions is limited. The phenology- and pixel-based paddy rice mapping (PPPM) algorithm, which identifies the flooding signals in the rice transplanting phase, has been effectively applied in tropical areas, but has not been tested at large scale of cold regions yet. Despite the effects from more snow/ice, paddy rice mapping in high latitude areas is assumed to be more encouraging due to less clouds, lower cropping intensity, and more observations from Landsat sidelaps. Moreover, the enhanced temporal and geographic coverage from Landsat 8 provides an opportunity to acquire phenology information and map paddy rice. This study evaluated the potential of Landsat 8 images on annual paddy rice mapping in NE Asia which was dominated by single cropping system, including Japan, North Korea, South Korea, and NE China. The cloud computing approach was used to process all the available Landsat 8 imagery in 2014 (143 path/rows, ~3290 scenes) with the Google Earth Engine (GEE) platform. The results indicated that the Landsat 8, GEE, and improved PPPM algorithm can effectively support the yearly mapping of paddy rice in NE Asia. The resultant paddy rice map has a high accuracy with the producer (user) accuracy of 73% (92%), based on the validation using very high resolution images and intensive field photos. Geographic characteristics of paddy rice distribution were analyzed from aspects of country, elevation, latitude, and climate. The resultant 30-m paddy rice map is expected to provide unprecedented details about the area, spatial distribution, and landscape pattern of paddy rice fields in NE Asia, which will contribute to food security assessment, water resource management, estimation of greenhouse gas emissions, and disease control. PMID:28025586

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

USGS Publications Warehouse

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

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) platform: the delta normalized burn ratio (dNBR), the relativized delta normalized burn ratio (RdNBR), and the relativized burn ratio (RBR). Our methods do not rely on time-consuming a priori scene selection and instead use a mean compositing approach in which all valid pixels (e.g. cloud-free) over a pre-specified date range (pre- and post-fire) are stacked and the mean value for each pixel over each stack is used to produce the resulting fire severity datasets. This approach demonstrates that fire severity datasets can be produced with relative ease and speed compared the standard approach in which one pre-fire and post-fire scene are judiciously identified and used to produce fire severity datasets. We also validate the GEE-derived fire severity metrics using field-based fire severity plots for 18 fires in the western US. These validations are compared to Landsat-based fire severity datasets produced using only one pre- and post-fire scene, which has been the standard approach in producing such datasets since their inception. Results indicate that the GEE-derived fire severity datasets show improved validation statistics compared to parallel versions in which only one pre-fire and post-fire scene are used. We provide code and a sample geospatial fire history layer to produce dNBR, RdNBR, and RBR for the 18 fires we evaluated. Although our approach requires that a geospatial fire history layer (i.e. fire perimeters) be produced independently and prior to applying our methods, we suggest our GEE methodology can reasonably be implemented on hundreds to thousands of fires, thereby increasing opportunities for fire severity monitoring and research across the globe.

Mapping paddy rice planting area in northeastern Asia with Landsat 8 images, phenology-based algorithm and Google Earth Engine.

PubMed

Dong, Jinwei; Xiao, Xiangming; Menarguez, Michael A; Zhang, Geli; Qin, Yuanwei; Thau, David; Biradar, Chandrashekhar; Moore, Berrien

2016-11-01

Area and spatial distribution information of paddy rice are important for understanding of food security, water use, greenhouse gas emission, and disease transmission. Due to climatic warming and increasing food demand, paddy rice has been expanding rapidly in high latitude areas in the last decade, particularly in northeastern (NE) Asia. Current knowledge about paddy rice fields in these cold regions is limited. The phenology- and pixel-based paddy rice mapping (PPPM) algorithm, which identifies the flooding signals in the rice transplanting phase, has been effectively applied in tropical areas, but has not been tested at large scale of cold regions yet. Despite the effects from more snow/ice, paddy rice mapping in high latitude areas is assumed to be more encouraging due to less clouds, lower cropping intensity, and more observations from Landsat sidelaps. Moreover, the enhanced temporal and geographic coverage from Landsat 8 provides an opportunity to acquire phenology information and map paddy rice. This study evaluated the potential of Landsat 8 images on annual paddy rice mapping in NE Asia which was dominated by single cropping system, including Japan, North Korea, South Korea, and NE China. The cloud computing approach was used to process all the available Landsat 8 imagery in 2014 (143 path/rows, ~3290 scenes) with the Google Earth Engine (GEE) platform. The results indicated that the Landsat 8, GEE, and improved PPPM algorithm can effectively support the yearly mapping of paddy rice in NE Asia. The resultant paddy rice map has a high accuracy with the producer (user) accuracy of 73% (92%), based on the validation using very high resolution images and intensive field photos. Geographic characteristics of paddy rice distribution were analyzed from aspects of country, elevation, latitude, and climate. The resultant 30-m paddy rice map is expected to provide unprecedented details about the area, spatial distribution, and landscape pattern of paddy rice fields in NE Asia, which will contribute to food security assessment, water resource management, estimation of greenhouse gas emissions, and disease control.

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.

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

Using Google Drive to Facilitate a Blended Approach to Authentic Learning

ERIC Educational Resources Information Center

Rowe, Michael; Bozalek, Vivienne; Frantz, Jose

2013-01-01

While technology has the potential to create opportunities for transformative learning in higher education, it is often used to merely reinforce didactic teaching that aims to control access to expert knowledge. Instead, educators should consider using technology to enhance communication and provide richer, more meaningful platforms for the social…

Exploring Telecollaboration through the Lens of University Students: A Spanish-Cypriot Telecollaborative Exchange

ERIC Educational Resources Information Center

Nicolaou, Anna; Sevilla-Pavón, Ana

2016-01-01

This paper examines university students' views about a Cypriot-Spanish telecollaboration project through which participants used Google+ Communities for intercultural exchange over the course of one semester. The project was established through the UNICollaboration platform and it involved first-year students at the Cyprus University of Technology…

Secure and Resilient Cloud Computing for the Department of Defense

DTIC Science & Technology

2015-11-16

platform as a service (PaaS), and software as a service ( SaaS )—that target system administrators, developers, and end-users respectively (see Table 2...interfaces (API) and services Medium Amazon Elastic MapReduce, MathWorks Cloud, Red Hat OpenShift SaaS Full-fledged applications Low Google gMail

Video Lecture Watching Behaviors of Learners in Online Courses

ERIC Educational Resources Information Center

Ozan, Ozlem; Ozarslan, Yasin

2016-01-01

This paper examines learners' behaviors while watching online video lectures to understand learner preferences. 2927 students' 18,144 video events across 13 courses on Sakai CLE LMS, which were integrated with Kaltura Video Platform and Google Analytics, were analyzed. For the analysis of the quantitative data, one-way ANOVA, Chi-square test of…

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;

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.

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.

Ideas for a future earth observing system from geosynchronous orbit

NASA Technical Reports Server (NTRS)

Shenk, William E.; Hall, Forrest; Esaias, Wayne; Maxwell, Marvin; Suomi, Verner E.; Von Bun, Fritz

1986-01-01

Uses for the proposed geosynchronous platform are described. The geosynchronous satellite could provide good spatial and temporal resolution, a large field-of-view, easier calibration, stereography, and data relay. The limitations of the platform are discussed. The applications of the geosynchronous platform to meteorology, earth surveying, and oceanography are examined.

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.

Cloud masking and removal in remote sensing image time series

NASA Astrophysics Data System (ADS)

Gómez-Chova, Luis; Amorós-López, Julia; Mateo-García, Gonzalo; Muñoz-Marí, Jordi; Camps-Valls, Gustau

2017-01-01

Automatic cloud masking of Earth observation images is one of the first required steps in optical remote sensing data processing since the operational use and product generation from satellite image time series might be hampered by undetected clouds. The high temporal revisit of current and forthcoming missions and the scarcity of labeled data force us to cast cloud screening as an unsupervised change detection problem in the temporal domain. We introduce a cloud screening method based on detecting abrupt changes along the time dimension. The main assumption is that image time series follow smooth variations over land (background) and abrupt changes will be mainly due to the presence of clouds. The method estimates the background surface changes using the information in the time series. In particular, we propose linear and nonlinear least squares regression algorithms that minimize both the prediction and the estimation error simultaneously. Then, significant differences in the image of interest with respect to the estimated background are identified as clouds. The use of kernel methods allows the generalization of the algorithm to account for higher-order (nonlinear) feature relations. After the proposed cloud masking and cloud removal, cloud-free time series at high spatial resolution can be used to obtain a better monitoring of land cover dynamics and to generate more elaborated products. The method is tested in a dataset with 5-day revisit time series from SPOT-4 at high resolution and with Landsat-8 time series. Experimental results show that the proposed method yields more accurate cloud masks when confronted with state-of-the-art approaches typically used in operational settings. In addition, the algorithm has been implemented in the Google Earth Engine platform, which allows us to access the full Landsat-8 catalog and work in a parallel distributed platform to extend its applicability to a global planetary scale.

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.

Mastering the intermediaries.

PubMed

Edelman, Benjamin

2014-06-01

Almost every retailer looks to Google to refer customers, and it's rare to find a manufacturer whose products aren't sold on Amazon. But these and other big platforms can capture a disproportionate share of the value a company creates: Buy an app on iTunes, and Apple takes 30%. The author presents four strategies to help businesses reduce their dependence on powerful platforms. Exploit the platform's need to be comprehensive. American Airlines' strong coverage of key routes made its presence on the travel website Kayak indispensable to Kayak's value proposition. As a result, AA negotiated a better deal. Identify and discredit discrimination. Public complaints that eBay was giving search prominence to suppliers who advertised on the site forced a reversal of the policy. Create an alternative platform. When MovieTickets was on the verge of dominating phone and online ticketing, Regal Entertainment and two other large theater chains formed Fandango. Deal more directly. People ordering takeout through online platforms like Foodler and GrubHub have often already chosen their restaurant. Restaurants that deal directly can exit the platform.

Unique Offerings of the ISS as an Earth Observing Platform

NASA Technical Reports Server (NTRS)

Cooley, Victor M.

2013-01-01

The International Space Station offers unique capabilities for earth remote sensing. An established Earth orbiting platform with abundant power, data and commanding infrastructure, the ISS has been in operation for twelve years as a crew occupied science laboratory and offers low cost and expedited concept-to-operation paths for new sensing technologies. Plug in modularity on external platforms equipped with structural, power and data interfaces standardizes and streamlines integration and minimizes risk and start up difficulties. Data dissemination is also standardized. Emerging sensor technologies and instruments tailored for sensing of regional dynamics may not be worthy of dedicated platforms and launch vehicles, but may well be worthy of ISS deployment, hitching a ride on one of a variety of government or commercial visiting vehicles. As global acceptance of the urgent need for understanding Climate Change continues to grow, the value of ISS, orbiting in Low Earth Orbit, in complementing airborne, sun synchronous polar, geosynchronous and other platform remote sensing will also grow.

Integrated Tourism E-Commerce Platform for Scenery Administration Bureau, Travel Agency and Tourist

NASA Astrophysics Data System (ADS)

Liang, Zhixue; Wang, Shui

Collaboration among multiple travel agencies and with scenery administration bureaus is vital for small or medium sized travel companies to succeed in the fierce competition of the tourism industry; business processes such as regrouping individual travelers between different agencies prove to be difficult and unpleasant user experience; tourists want to be more informed and have more initiative. To address these issues, proposes an integrated tourism e-commerce platform for travel agencies and scenery administration bureaus as well as tourists to interact in a more smooth way; this platform is constructed upon J2EE framework, provides online collaboration & coordination for companies and information services (such as self-navigation using Google Map etc) for tourists. A running implementation of this platform has been put into real business for a small travel company.

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.

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

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.

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…

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.

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…

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.

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.

Earth Science Geostationary Platform Technology

NASA Technical Reports Server (NTRS)

Wright, Robert L. (Editor); Campbell, Thomas G. (Editor)

1989-01-01

The objective of the workshop was to address problems in science and in four technology areas (large space antenna technology, microwave sensor technology, electromagnetics-phased array adaptive systems technology, and optical metrology technology) related to Earth Science Geostationary Platform missions.

BioSmalltalk: a pure object system and library for bioinformatics.

PubMed

Morales, Hernán F; Giovambattista, Guillermo

2013-09-15

We have developed BioSmalltalk, a new environment system for pure object-oriented bioinformatics programming. Adaptive end-user programming systems tend to become more important for discovering biological knowledge, as is demonstrated by the emergence of open-source programming toolkits for bioinformatics in the past years. Our software is intended to bridge the gap between bioscientists and rapid software prototyping while preserving the possibility of scaling to whole-system biology applications. BioSmalltalk performs better in terms of execution time and memory usage than Biopython and BioPerl for some classical situations. BioSmalltalk is cross-platform and freely available (MIT license) through the Google Project Hosting at http://code.google.com/p/biosmalltalk hernan.morales@gmail.com Supplementary data are available at Bioinformatics online.

Googling in anatomy education: Can google trends inform educators of national online search patterns of anatomical syllabi?

PubMed

Phelan, Nigel; Davy, Shane; O'Keeffe, Gerard W; Barry, Denis S

2017-03-01

The role of e-learning platforms in anatomy education continues to expand as self-directed learning is promoted in higher education. Although a wide range of e-learning resources are available, determining student use of non-academic internet resources requires novel approaches. One such approach that may be useful is the Google Trends © web application. To determine the feasibility of Google Trends to gain insights into anatomy-related online searches, Google Trends data from the United States from January 2010 to December 2015 were analyzed. Data collected were based on the recurrence of keywords related to head and neck anatomy generated from the American Association of Clinical Anatomists and the Anatomical Society suggested anatomy syllabi. Relative search volume (RSV) data were analyzed for seasonal periodicity and their overall temporal trends. Following exclusions due to insufficient search volume data, 29 out of 36 search terms were analyzed. Significant seasonal patterns occurred in 23 search terms. Thirty-nine seasonal peaks were identified, mainly in October and April, coinciding with teaching periods in anatomy curricula. A positive correlation of RSV with time over the 6-year study period occurred in 25 out of 29 search terms. These data demonstrate how Google Trends may offer insights into the nature and timing of online search patterns of anatomical syllabi and may potentially inform the development and timing of targeted online supports to ensure that students of anatomy have the opportunity to engage with online content that is both accurate and fit for purpose. Anat Sci Educ 10: 152-159. © 2016 American Association of Anatomists. © 2016 American Association of Anatomists.

Happy and Unhappy Patients: A Quantitative Analysis of Online Plastic Surgeon Reviews for Breast Augmentation.

PubMed

Dorfman, Robert G; Purnell, Chad; Qiu, Cecil; Ellis, Marco F; Basu, C Bob; Kim, John Y S

2018-05-01

Online reviews have become modern versions of the word-of-mouth recommendation, and prospective patients are increasingly consulting them before making decisions about their surgical care. The authors' objectives were to (1) identify trends in the use of online reviews, and (2) important reasons for patient satisfaction and dissatisfaction with aesthetic surgery. The authors selected breast augmentation as the primary procedure of interest. Reviews of the top 10 to 20 most reviewed plastic surgeons in each of six large metropolitan areas were obtained from Google, Yelp, and RealSelf. Reviews were assessed for predefined dimensions of satisfaction and dissatisfaction. A total of 1077 breast augmentation reviews were obtained. Ratings were distributed bimodally, with peaks at five stars and one star. The majority of reviews were positive (87.5 percent). Relative popularity of Google versus Yelp varied across geographic regions, and average rating varied by platform. Between 2011 and 2016, the number of online reviews for breast augmentation grew at an average rate of 42.6 percent per year. Aesthetic outcome was the most commonly cited dimension (69.8 percent of reviews), whereas cost was mentioned in only 7.8 percent of reviews. A substantial minority of negative Yelp (37 percent) and Google (9.4 percent) reviews were written by patients who did not actually undergo surgery. Free-text analysis of heterogeneous reviews (containing positive and negative attributes) classified dimensions as critical, redeemable, or protective. As the influence of online review platforms continues to grow, understanding drivers of positive and negative reviews may help surgeons improve patient satisfaction.

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

Earth resources instrumentation for the Space Station Polar Platform

NASA Technical Reports Server (NTRS)

Donohoe, Martin J.; Vane, Deborah

1986-01-01

The spacecraft and payloads of the Space Station Polar Platform program are described in a brief overview. Present plans call for one platform in a descending morning-equator-crossing orbit at 824 km and two or three platforms in ascending afternoon-crossing orbits at 542-824 km. The components of the NASA Earth Observing System (EOS) and NOAA payloads are listed in tables and briefly characterized, and data-distribution requirements and the mission development schedule are discussed. A drawing of the platform, a graph showing the spectral coverage of the EOS instruments, and a glossary of acronyms are provided.

Large Diffractive Optics for GEo-Based Earth Surveillance

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

Hyde, R A

2003-09-11

The natural vantage point for performing Earth-centric operations from space is geosynchronous orbit (GEO); a platform there moves at the same rate as the Earth's surface, so appears to continually ''hover'' over a fixed site on the Earth. Unlike spacecraft in other orbits, which rapidly fly-over targets, a GEO-based platform remains in-position all the time. In order to insure continual access to sites using low earth orbit (LEO) platforms, one needs a large enough constellation ({approx} 50) of spacecraft so that one is always overhead; in contrast, a single GEO platform provides continuous coverage over sites throughout Euro-Asia. This permanentmore » coverage comes, unfortunately, with a stiff price-tag; geosynchronous orbit is 36,000 km high, so space platforms there must operate at ranges roughly 100 times greater than ones located in LEO. For optical-based applications, this extreme range is difficult to deal with; for surveillance the price is a 100-fold loss of resolution, for laser weapons it is a 10,000-fold loss in flux-on-target. These huge performance penalties are almost always unacceptable, preventing us from successfully using GEO-based platforms. In practice, we are forced to either settle for brief, infrequent access to targets, or, if we demand continuous coverage, to invest in large, many-satellite, constellations. There is, fortunately, a way to use GEO-based optical platforms without incurring the huge, range-dependent, performance penalties; one must simply use bigger optics. As long as the aperture of a platform's optics increases as much as its operating range, then its performance (resolution and/or flux) does not suffer; the price for operating from GEO is simply 100-fold larger optics. This is, of course, a very stiff price; while meter-class optics may suffice for many low-earth-orbit applications, 100 meter apertures are needed in order to achieve similar performance from GEO. Since even the largest Earth-based telescope is only 10 meters in diameter, building ten-fold larger ones for GEO applications (let alone delivering and operating them there) presents major difficulties. However, since the challenges of fielding large platforms in GEO are matched by the benefits of continuous coverage, we propose a program to develop such optical platforms. In this section, we will examine a particular form of large aperture optic, using a flat diffractive lens instead of the more conventional curved reflectors considered elsewhere in this report. We will discuss both the development of this type of large aperture optics, as well as the steps necessary to use it for GEO-based Earth surveillance. In a later section of this report we will discuss another use for large diffractive optics, their application for global-reach laser weapons.« less

What does it take to build a medium scale scientific cloud to process significant amounts of Earth observation data?

NASA Astrophysics Data System (ADS)

Hollstein, André; Diedrich, Hannes; Spengler, Daniel

2017-04-01

The installment of the operational fleet of Sentinels by Copernicus offers an unprecedented influx of freely available Earth Observation data with Sentinel-2 being a great example. It offers a broad range of land applications due to its high spatial sampling from 10 m to 20 m and its multi-spectral imaging capabilities with 13 spectral bands. The open access policy allows unrestricted use by everybody and provides data downloads for on the respective sites. For a small area of interest and shorter time series, data processing, and exploitation can easily be done manually. However, for multi-temporal analysis of larger areas, the data size can quickly increase such that it is not manageable in practice on a personal computer which leads to an increasing interest in central data exploitation platforms. Prominent examples are GoogleEarth Engine, NASA Earth Exchange (NEX) or current developments such as CODE-DE in Germany. Open standards are still evolving, and the choice of a platform may create lock-in scenarios and a situation where scientists are not anymore in full control of all aspects of their analysis. Securing intellectual properties of researchers can become a major issue in the future. Partnering with a startup company that is dedicated to providing tools for farm management and precision farming, GFZ builds a small-scale science cloud named GTS2 for processing and distribution of Sentinel-2 data. The service includes a sophisticated atmospheric correction algorithm, spatial co-registration of time series data, as well as a web API for data distribution. This approach is different from the drag to centralized research using infrastructures controlled by others. By keeping the full licensing rights, it allows developing new business models independent from the initially chosen processing provider. Currently, data is held for the greater German area but is extendable to larger areas on short notice due to a scalable distributed network file system. For a given area of interest, band and time range selection, the API returns only the data that was requested in a fast manner and thereby saves storage space on the user's machine. A jupyterhub instance is a main tool for data exploitation by our users. Nearly all used software is open source, is based on open standards, and allows to transfer software to other infrastructures. In the talk, we give an overview of the current status of the project and the service, but also want to share our experience with its development.

Exploring University Students' Use of Technologies beyond the Formal Learning Context: A Tale of Two Online Platforms

ERIC Educational Resources Information Center

Deng, Liping; Tavares, Nicole Judith

2015-01-01

Situated within an informal learning context, this study examines how a group of pre-service teachers in Hong Kong use Facebook and Google Sites on their own initiative to fulfil their academic and socio-emotional needs during their teaching practice. Also included in the study are the motivating and inhibiting factors that influence student…

Prepare to Engage: Building Relationships through Social Media Is a Smart Investment for Institutions

ERIC Educational Resources Information Center

Doak, Jennifer

2011-01-01

The people an educational institution is trying to reach--prospective and current students, alumni and parents, to name a few--are no longer passive recipients of press releases and newsletters. They are on Facebook, Twitter, LinkedIn, Google+, and any other social media platform that comes to mind. What can sometimes get lost amid the constant…

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…

A new tool for supervised classification of satellite images available on web servers: Google Maps as a case study

NASA Astrophysics Data System (ADS)

García-Flores, Agustín.; Paz-Gallardo, Abel; Plaza, Antonio; Li, Jun

2016-10-01

This paper describes a new web platform dedicated to the classification of satellite images called Hypergim. The current implementation of this platform enables users to perform classification of satellite images from any part of the world thanks to the worldwide maps provided by Google Maps. To perform this classification, Hypergim uses unsupervised algorithms like Isodata and K-means. Here, we present an extension of the original platform in which we adapt Hypergim in order to use supervised algorithms to improve the classification results. This involves a significant modification of the user interface, providing the user with a way to obtain samples of classes present in the images to use in the training phase of the classification process. Another main goal of this development is to improve the runtime of the image classification process. To achieve this goal, we use a parallel implementation of the Random Forest classification algorithm. This implementation is a modification of the well-known CURFIL software package. The use of this type of algorithms to perform image classification is widespread today thanks to its precision and ease of training. The actual implementation of Random Forest was developed using CUDA platform, which enables us to exploit the potential of several models of NVIDIA graphics processing units using them to execute general purpose computing tasks as image classification algorithms. As well as CUDA, we use other parallel libraries as Intel Boost, taking advantage of the multithreading capabilities of modern CPUs. To ensure the best possible results, the platform is deployed in a cluster of commodity graphics processing units (GPUs), so that multiple users can use the tool in a concurrent way. The experimental results indicate that this new algorithm widely outperform the previous unsupervised algorithms implemented in Hypergim, both in runtime as well as precision of the actual classification of the images.

Small unmanned aircraft systems for remote sensing and Earth science research

NASA Astrophysics Data System (ADS)

Hugenholtz, Chris H.; Moorman, Brian J.; Riddell, Kevin; Whitehead, Ken

2012-06-01

To understand and predict Earth-surface dynamics, scientists often rely on access to the latest remote sensing data. Over the past several decades, considerable progress has been made in the development of specialized Earth observation sensors for measuring a wide range of processes and features. Comparatively little progress has been made, however, in the development of new platforms upon which these sensors can be deployed. Conventional platforms are still almost exclusively restricted to piloted aircraft and satellites. For many Earth science research questions and applications these platforms do not yet have the resolution or operational flexibility to provide answers affordably. The most effective remote sensing data match the spatiotemporal scale of the process or feature of interest. An emerging technology comprising unmanned aircraft systems (UAS), also known as unmanned aerial vehicles (UAV), is poised to offer a viable alternative to conventional platforms for acquiring high-resolution remote sensing data with increased operational flexibility, lower cost, and greater versatility (Figure 1).

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.

Cloud-based simulations on Google Exacycle reveal ligand modulation of GPCR activation pathways

NASA Astrophysics Data System (ADS)

Kohlhoff, Kai J.; Shukla, Diwakar; Lawrenz, Morgan; Bowman, Gregory R.; Konerding, David E.; Belov, Dan; Altman, Russ B.; Pande, Vijay S.

2014-01-01

Simulations can provide tremendous insight into the atomistic details of biological mechanisms, but micro- to millisecond timescales are historically only accessible on dedicated supercomputers. We demonstrate that cloud computing is a viable alternative that brings long-timescale processes within reach of a broader community. We used Google's Exacycle cloud-computing platform to simulate two milliseconds of dynamics of a major drug target, the G-protein-coupled receptor β2AR. Markov state models aggregate independent simulations into a single statistical model that is validated by previous computational and experimental results. Moreover, our models provide an atomistic description of the activation of a G-protein-coupled receptor and reveal multiple activation pathways. Agonists and inverse agonists interact differentially with these pathways, with profound implications for drug design.

Phenology of Succession: Tracking the Recovery of Dryland Forests after Wildfire Events

NASA Astrophysics Data System (ADS)

Walker, J.; Brown, J. F.; Sankey, J. B.; Wallace, C.; Weltzin, J. F.

2016-12-01

The frequency, size, and intensity of forest wildfires in the U.S. Southwest have increased over the past 30 years. In the coming decades, burn effects and altered climatic conditions may increasingly divert vegetation recovery trajectories from pre-disturbance forested ecosystems toward grassland or shrub woodlands. Dryland herbaceous and woody vegetation species exhibit different phenological responses to precipitation, resulting in temporal and spatial shifts in landscape phenology patterns as the proportions of plant functional groups change over time. We have developed time series of Normalized Difference Vegetation Index (NDVI) and Soil-Adjusted Vegetation Index (SAVI) greenness measures derived from satellite imagery from 1984 - 2015 to record the phenological signatures that characterize recovery trajectories towards predominantly grassland, shrubland, or forest land cover types. We leveraged the data and computational resources available through the Google Earth Engine cloud-based platform to analyze time series of Landsat Thematic Mapper and Enhanced Thematic Mapper Plus imagery collected over maturing (40 years or more post-fire) dryland forests in Arizona and New Mexico, USA. These time series provided the basis for long-term comparisons of phenology behavior in different successional trajectories and enabled the assessment of climatic influence on the eventual outcomes.

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.

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.

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.

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…

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.

Strategy for earth explorers in global earth sciences

NASA Technical Reports Server (NTRS)

1988-01-01

The goal of the current NASA Earth System Science initiative is to obtain a comprehensive scientific understanding of the Earth as an integrated, dynamic system. The centerpiece of the Earth System Science initiative will be a set of instruments carried on polar orbiting platforms under the Earth Observing System program. An Earth Explorer program can open new vistas in the earth sciences, encourage innovation, and solve critical scientific problems. Specific missions must be rigorously shaped by the demands and opportunities of high quality science and must complement the Earth Observing System and the Mission to Planet Earth. The committee believes that the proposed Earth Explorer program provides a substantial opportunity for progress in the earth sciences, both through independent missions and through missions designed to complement the large scale platforms and international research programs that represent important national commitments. The strategy presented is intended to help ensure the success of the Earth Explorer program as a vital stimulant to the study of the planet.

Utah's Mobile Earth Science Outreach Vehicle

NASA Astrophysics Data System (ADS)

Schoessow, F. S.; Christian, L.

2016-12-01

Students at Utah State University's College of Natural Resources have engineered the first mobile Earth Science outreach platform capable of delivering high-tech and interactive solar-powered educational resources to the traditionally-underserved, remote communities of rural Utah. By retrofitting and modifying an industrial box-truck, this project effectively created a highly mobile and energy independent "school in a box" which seeks to help change the way that Earth science is communicated, eliminate traditional barriers, and increase science accessibility - both physically and conceptually. The project's education platform is focused on developing a more effective, sustainable, and engaging platform for presenting Earth science outreach curricula to community members of all ages in an engaging fashion. Furthermore, this project affords university students the opportunity to demonstrate innovative science communication techniques, translating vital university research into educational outreach operations aimed at doing real, measurable good for local communities.

Global 30m Height Above the Nearest Drainage

NASA Astrophysics Data System (ADS)

Donchyts, Gennadii; Winsemius, Hessel; Schellekens, Jaap; Erickson, Tyler; Gao, Hongkai; Savenije, Hubert; van de Giesen, Nick

2016-04-01

Variability of the Earth surface is the primary characteristics affecting the flow of surface and subsurface water. Digital elevation models, usually represented as height maps above some well-defined vertical datum, are used a lot to compute hydrologic parameters such as local flow directions, drainage area, drainage network pattern, and many others. Usually, it requires a significant effort to derive these parameters at a global scale. One hydrological characteristic introduced in the last decade is Height Above the Nearest Drainage (HAND): a digital elevation model normalized using nearest drainage. This parameter has been shown to be useful for many hydrological and more general purpose applications, such as landscape hazard mapping, landform classification, remote sensing and rainfall-runoff modeling. One of the essential characteristics of HAND is its ability to capture heterogeneities in local environments, difficult to measure or model otherwise. While many applications of HAND were published in the academic literature, no studies analyze its variability on a global scale, especially, using higher resolution DEMs, such as the new, one arc-second (approximately 30m) resolution version of SRTM. In this work, we will present the first global version of HAND computed using a mosaic of two DEMS: 30m SRTM and Viewfinderpanorama DEM (90m). The lower resolution DEM was used to cover latitudes above 60 degrees north and below 56 degrees south where SRTM is not available. We compute HAND using the unmodified version of the input DEMs to ensure consistency with the original elevation model. We have parallelized processing by generating a homogenized, equal-area version of HydroBASINS catchments. The resulting catchment boundaries were used to perform processing using 30m resolution DEM. To compute HAND, a new version of D8 local drainage directions as well as flow accumulation were calculated. The latter was used to estimate river head by incorporating fixed and variable thresholding methods. The resulting HAND dataset was analyzed regarding its spatial variability and to assess the global distribution of the main landform types: valley, ecotone, slope, and plateau. The method used to compute HAND was implemented using PCRaster software, running on Google Compute Engine platform running under Ubuntu Linux. The Google Earth Engine was used to perform mosaicing and clipping of the original DEMs as well as to provide access to the final product. The effort took about three months of computing time on eight core CPU virtual machine.

Using Google Earth Engine To Apply Spectral Mixture Analysis Over Landsat 5TM Imagery To Map Fire Scars In The Alto Teles Pires River Basin, Mato Grosso State, Brazil.

NASA Astrophysics Data System (ADS)

Antunes Daldegan, G.; Ribeiro, F.; Roberts, D. A.

2016-12-01

The two most extensive biomes in Brazil, the Amazon Forest and the Cerrado (the Brazilian savanna), are subject to many fire events every dry season. Both biomes are well-known for their ecological and environmental importance but, due to the intensive human occupation over the last decades, they have been experiencing high deforestation rates with much of their natural landscape being converted to agriculture and pasture uses. The Cerrado, as a savanna, has naturally evolved adapted to fire. According to some researchers, this biome has been exposed to fire for the last 25 million years, forging the diversification of many C4 grass species, for example. The Amazon forest does not have similar characteristics and studies have shown that forest areas that have been already burned become more prone to recurrent burns. Forest patches that are close to open areas have their edges exposed to higher insolation and greater turbulence, drying the understory vegetation and litter, turning those areas more susceptible to fire events. In cases where grass species become established in the understory they can be a renewable source of fuel for recurrent burns. This study aimed to identify and map fire scars present in the region of Alto Teles Pires river basin, State of Mato Grosso - Brazil, during 10 years (2002-2011). This region is located in the transition zone between the two biomes and is known for its high deforestation rates. By taking advantage of the Landsat 5TM imagery collection present in Google Earth Engine platform as well as applying Spectral Mixture Analysis (SMA) techniques over them it was possible to estimate fractions of Green Vegetation (GV), Non-Photosynthetic Vegetation (NPV), and Soil targets, which are the surfaces that compose the vast majority of the landscape in the study region. Iteratively running SMA analysis over the imagery using burned vegetation endmembers allowed us to further identify fire scars present in the region, returning excellent accuracy. Burned vegetation endmembers were extracted from Landsat 5TM imagery that cover burned control areas that are part of the Projeto Fogo, a project that has been under development for the last 27 year in an ecological reserve (Roncador Ecological Reserve) close to Brasilia, Distrito Federal, Brazil.

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.

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.

Data Redistribution through MY NASA DATA: Striving to bring authentic NASA data into education

NASA Astrophysics Data System (ADS)

Lewis, P. M.; Oostra, D.; Oots, P.; Chambers, L. H.; Moore, S.; Crecelius, S.; Taylor, J.

2012-12-01

The Mentoring and inquirY using NASA Data on Atmospheric and Earth science for Teachers and Amateurs (MY NASA DATA or MND) project was launched in 2004 to bring authentic data into K-12 education. The MND website features a Live Access Server (LAS), an open source tool which allows users to customize data sets to suit their individual needs, choosing from among 200 global Level 3 data sets. Approximately 120 lesson plans that utilize the available parameters are offered to help teachers and students get started with data exploration. Grade appropriate data documentation is also provided (with continual efforts to improve it to better meet the needs of this target audience). Through inquiry and lesson utilization, educators have several connection points to the data. As classrooms shift to problem-based and inquiry learning, the need for a data visualizer/server increases. Through numerous and growing connections to NASA satellite missions, and with access to data as a built-in feature, MND effectively fills this niche to provide a first level of data re-use that is friendly to the K-12 community. Offering a wide variety of data sets allows MND to support many science topics within the K-12 curriculum while extending the use of scientific data from NASA Earth science satellites. Lessons, created by educators across the country, allow MND to connect with the classroom teacher and to meet their data needs. As technology continues to evolve, a second level of data re-use becomes both interesting and possible. Thus, the MND team is now exploring new web and mobile platforms that can be built and distributed on an accelerated time cycle to keep up with information technology developments. With implementation of these new platforms come challenges in promoting new items to the education community, the public, and other potential users. Included in the list of challenges are: ever-evolving technology, prediction of the market, web/mobile platforms, and time-to-market for new items. The MND team has addressed some of these barriers by embracing new technologies: 1) the Observe Your World blog utilizes WordPress and provides a central place to announce new resources; 2) The use of HTML5 has enabled cross-platform web application development and avoids native application release pitfalls; 3) close monitoring of server performance and access metrics (using, for example, Google analytics) provides real-time feedback and allows MND to make informed changes to content and delivery methods. Old-fashioned approaches to communication, such as paying close attention to the needs of the end user through relationship building and responsiveness, are also keys to success. Outcome: This paper will show the various platforms through which the MY NASA DATA project has made available data for use in the educational community. Successes and challenges will be shared from 8 years of working on data re-use tools to support the education community.

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).

A web-based platform to support an evidence-based mental health intervention: lessons from the CBITS web site.

PubMed

Vona, Pamela; Wilmoth, Pete; Jaycox, Lisa H; McMillen, Janey S; Kataoka, Sheryl H; Wong, Marleen; DeRosier, Melissa E; Langley, Audra K; Kaufman, Joshua; Tang, Lingqi; Stein, Bradley D

2014-11-01

To explore the role of Web-based platforms in behavioral health, the study examined usage of a Web site for supporting training and implementation of an evidence-based intervention. Using data from an online registration survey and Google Analytics, the investigators examined user characteristics and Web site utilization. Site engagement was substantial across user groups. Visit duration differed by registrants' characteristics. Less experienced clinicians spent more time on the Web site. The training section accounted for most page views across user groups. Individuals previously trained in the Cognitive-Behavioral Intervention for Trauma in Schools intervention viewed more implementation assistance and online community pages than did other user groups. Web-based platforms have the potential to support training and implementation of evidence-based interventions for clinicians of varying levels of experience and may facilitate more rapid dissemination. Web-based platforms may be promising for trauma-related interventions, because training and implementation support should be readily available after a traumatic event.

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.

VALIDATING the Accuracy of Sighten's Automated Shading Tool

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

Solar companies - including installers, financiers, and distributors - leverage Sighten software to deliver accurate shading calculations and solar proposals. Sighten recently partnered with Google Project Sunroof to provide automated remote shading analysis directly within the Sighten platform. The National Renewable Energy Laboratory (NREL), in partnership with Sighten, independently verified the accuracy of Sighten's remote-shading solar access values (SAVs) on an annual basis for locations in Los Angeles, California, and Denver, Colorado.

PHIT for Duty, a Personal Health Intervention Tool for Psychological Health and Traumatic Brain Injury

DTIC Science & Technology

2016-06-01

smartphone or tablet computer platforms, including both Google Android™ and Apple iOS based devices. Recruiting for the pilot study was very...framework design.. 15. SUBJECT TERMS PTSD, post-traumatic stress disorder, mobile health, self-help, iOS , Android, mindfulness, relaxation... study and subsequent randomized controlled trial (RCT) with post-deployed personnel; and (5) adapting the developed system for several popular

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.

Use of Open Standards and Technologies at the Lunar Mapping and Modeling Project

NASA Astrophysics Data System (ADS)

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

2011-12-01

The Lunar Mapping and Modeling Project (LMMP), led by the Marshall Space Flight center (MSFC), is tasked by NASA. The project is responsible for the development of an information system to support lunar exploration activities. It provides lunar explorers a set of tools and lunar map and model products that are predominantly derived from present lunar missions (e.g., the Lunar Reconnaissance Orbiter (LRO)) and from historical missions (e.g., Apollo). At Jet Propulsion Laboratory (JPL), we have built the LMMP interoperable geospatial information system's underlying infrastructure and a single point of entry - the LMMP Portal by employing a number of open standards and technologies. The Portal exposes a set of services to users to allow search, visualization, subset, and download of lunar data managed by the system. Users also have access to a set of tools that visualize, analyze and annotate the data. The infrastructure and Portal are based on web service oriented architecture. We designed the system to support solar system bodies in general including asteroids, earth and planets. We employed a combination of custom software, commercial and open-source components, off-the-shelf hardware and pay-by-use cloud computing services. The use of open standards and web service interfaces facilitate platform and application independent access to the services and data, offering for instances, iPad and Android mobile applications and large screen multi-touch with 3-D terrain viewing functions, for a rich browsing and analysis experience from a variety of platforms. The web services made use of open standards including: Representational State Transfer (REST); and Open Geospatial Consortium (OGC)'s Web Map Service (WMS), Web Coverage Service (WCS), Web Feature Service (WFS). Its data management services have been built on top of a set of open technologies including: Object Oriented Data Technology (OODT) - open source data catalog, archive, file management, data grid framework; openSSO - open source access management and federation platform; solr - open source enterprise search platform; redmine - open source project collaboration and management framework; GDAL - open source geospatial data abstraction library; and others. Its data products are compliant with Federal Geographic Data Committee (FGDC) metadata standard. This standardization allows users to access the data products via custom written applications or off-the-shelf applications such as GoogleEarth. We will demonstrate this ready-to-use system for data discovery and visualization by walking through the data services provided through the portal such as browse, search, and other tools. We will further demonstrate image viewing and layering of lunar map images from the Internet, via mobile devices such as Apple's iPad.

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

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…

Hybrid Cloud Computing Environment for EarthCube and Geoscience Community

NASA Astrophysics Data System (ADS)

Yang, C. P.; Qin, H.

2016-12-01

The NSF EarthCube Integration and Test Environment (ECITE) has built a hybrid cloud computing environment to provides cloud resources from private cloud environments by using cloud system software - OpenStack and Eucalyptus, and also manages public cloud - Amazon Web Service that allow resource synchronizing and bursting between private and public cloud. On ECITE hybrid cloud platform, EarthCube and geoscience community can deploy and manage the applications by using base virtual machine images or customized virtual machines, analyze big datasets by using virtual clusters, and real-time monitor the virtual resource usage on the cloud. Currently, a number of EarthCube projects have deployed or started migrating their projects to this platform, such as CHORDS, BCube, CINERGI, OntoSoft, and some other EarthCube building blocks. To accomplish the deployment or migration, administrator of ECITE hybrid cloud platform prepares the specific needs (e.g. images, port numbers, usable cloud capacity, etc.) of each project in advance base on the communications between ECITE and participant projects, and then the scientists or IT technicians in those projects launch one or multiple virtual machines, access the virtual machine(s) to set up computing environment if need be, and migrate their codes, documents or data without caring about the heterogeneity in structure and operations among different cloud platforms.

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.

Google Hangouts: Leveraging Social Media to Reach the Education Community

NASA Astrophysics Data System (ADS)

Eisenhamer, Bonnie; Summers, Frank; McCallister, Dan; Ryer, Holly

2015-01-01

Research shows that educator professional development is most effective when it is sustained and/or when a follow-on component is included to support the learning process. In order to create more comprehensive learning experiences for our workshop participants, the education team at the Space Telescope Science Institute is working collaboratively with scientific staff and other experts to create a follow-on component for our professional development program. The new component utilizes video conferencing platforms, such as Google's Hangouts On Air, to provide educators with content updates and extended learning opportunities in between in-person professional development experiences. The goal is to enhance our professional development program in a cost-effective way while reaching a greater cross-section of educators. Video broadcasts go live on Google+, YouTube, and our website - thus providing access to any user with a web browser. Additionally, the broadcasts are automatically recorded and archived for future viewing on our YouTube channel. This provides educators with anywhere, anytime training that best suits their needs and schedules. This poster will highlight our new Hangouts for educators as well as our cross-departmental efforts to expand the reach of our Hubble Hangouts for the public through a targeted recruitment strategy.

Landspotting: collecting essential land cover information via an attractive internet game

NASA Astrophysics Data System (ADS)

Fritz, Steffen; McCallum, Ian; Perger, Christoph; Christian, Schill; Florian, Kraxner; Erik, Lindquist; Michael, Obersteiner

2010-05-01

Based on the geo-wiki.org concept of collecting land cover information via crowdsourcing, we present a novel approach on how to get the crowd involved. Internet games as well as social networks are becoming increasingly popular and the full potential is yet to be exploited. However, thus far, few if any games provide anything other than entertainment. Can an attractive philanthropic game be created which uses the crowd to collect essential information needed to help to acquire better data to improve the understanding of the earth system? Since accurate and up to date information on global land cover plays a very important role in a number of different research fields such as climate change, monitoring of tropical deforestation, land use monitoring and land-use modelling, but still shows high levels of disagreement, the game will focus on how this essential land cover calibration and validation data can be collected in areas where uncertainty is currently highest. In the current version of the land spotting game, we combine uncertainty hotspot information from three global land cover datasets (GLC, MODIS and 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 landspotting game community to certain hotspots of land cover uncertainty and then ask them to enter/record the type of land cover they see (for this they will be able to acquire a certain number of points), possibly uploading pictures at that location (additional points will be received). Even though the development of the game "landspotting.org" is still underway, we illustrate what the functionality will be and what features are envisaged for the near future. Landspotting.org will be designed in such a way as to challenge users to help map out the remaining areas of confusion over the globe - possibly in the form of an adventure game. Users will be primarily directed to areas with high disagreement, and where high resolution scenes are available for validation. The players will be directed to specifically validate and carefully select pixels on top of the Google earth platform. In order to control for misuse, there will be overlap among the land cover validation pixels. The selection of those validation pixels can be manifold: a certain lattice, random points or a stratified sample. Moreover, we show how Facebook and other social networks can be used to promote the tool and a huge crowd can potentially become involved. Preliminary results will be presented and a mockup version of the game will be shown.

Lunar-based Earth observation geometrical characteristics research

NASA Astrophysics Data System (ADS)

Ren, Yuanzhen; Liu, Guang; Ye, Hanlin; Guo, Huadong; Ding, Yixing; Chen, Zhaoning

2016-07-01

As is known to all, there are various platforms for carrying sensors to observe Earth, such as automobiles, aircrafts and satellites. Nowadays, we focus on a new platform, Moon, because of its longevity, stability and vast space. These advantages make it to be the next potential platform for observing Earth, enabling us to get the consistent and global measurements. In order to get a better understanding of lunar-based Earth observation, we discuss its geometrical characteristics. At present, there are no sensors on the Moon for observing Earth and we are not able to obtain a series of real experiment data. As a result, theoretical modeling and numerical calculation are used in this paper. At first, we construct an approximate geometrical model of lunar-based Earth observation, which assumes that Earth and Moon are spheres. Next, we calculate the position of Sun, Earth and Moon based on the JPL ephemeris. With the help of positions data and geometrical model, it is possible for us to decide the location of terminator and substellar points. However, in order to determine their precise position in the conventional terrestrial coordinate system, reference frames transformations are introduced as well. Besides, taking advantages of the relative positions of Sun, Earth and Moon, we get the total coverage of lunar-based Earth optical observation. Furthermore, we calculate a more precise coverage, considering placing sensors on different positions of Moon, which is influenced by its attitude parameters. In addition, different ephemeris data are compared in our research and little difference is found.

Evaluating Palliative Care Resources Available to the Public Using the Internet and Social Media.

PubMed

Claudio, Celeste H; Dizon, Zoelle B; October, Tessie W

2018-01-01

Accessible information about palliative care available to the public on the Internet is growing. We do not know whether this information is consistent with the current accepted definition of palliative care. To identify resources on the Internet and social media regarding palliative care and evaluate the information conveyed. A cross-sectional study of "palliative care" search results. Top 10 Google websites, top 10 most viewed YouTube videos, and social media platforms, Facebook and Twitter, were searched. The most popular Google websites were mostly from national organizations promoting palliative care, whose definitions of palliative care consistently mention "quality of life" and "relief from symptoms and stress." None of the websites mentioned children, and 77% cited palliative care as treatment for cancer with less focus on other diseases. No personal stories were included in Google websites, while 60% of YouTube videos included personal stories. Five main themes were generated from 266 YouTube video comments analyzed. The most common theme was emotionality, of which 91% were positive statements. Facebook and Twitter were mostly used by health-care professionals and not the public. Palliative care resources are mostly positive and consistent with the current definition of palliative care. Major Internet search engines such as Google and YouTube provide valuable insight into information the public receives about palliative care. Future development of Internet resources on palliative care should consider including children and emphasizing palliative care for all life-limiting illnesses.

A Scalable Infrastructure for Lidar Topography Data Distribution, Processing, and Discovery

NASA Astrophysics Data System (ADS)

Crosby, C. J.; Nandigam, V.; Krishnan, S.; Phan, M.; Cowart, C. A.; Arrowsmith, R.; Baru, C.

2010-12-01

High-resolution topography data acquired with lidar (light detection and ranging) technology have emerged as a fundamental tool in the Earth sciences, and are also being widely utilized for ecological, planning, engineering, and environmental applications. Collected from airborne, terrestrial, and space-based platforms, these data are revolutionary because they permit analysis of geologic and biologic processes at resolutions essential for their appropriate representation. Public domain lidar data collection by federal, state, and local agencies are a valuable resource to the scientific community, however the data pose significant distribution challenges because of the volume and complexity of data that must be stored, managed, and processed. Lidar data acquisition may generate terabytes of data in the form of point clouds, digital elevation models (DEMs), and derivative products. This massive volume of data is often challenging to host for resource-limited agencies. Furthermore, these data can be technically challenging for users who lack appropriate software, computing resources, and expertise. The National Science Foundation-funded OpenTopography Facility (www.opentopography.org) has developed a cyberinfrastructure-based solution to enable online access to Earth science-oriented high-resolution lidar topography data, online processing tools, and derivative products. OpenTopography provides access to terabytes of point cloud data, standard DEMs, and Google Earth image data, all co-located with computational resources for on-demand data processing. The OpenTopography portal is built upon a cyberinfrastructure platform that utilizes a Services Oriented Architecture (SOA) to provide a modular system that is highly scalable and flexible enough to support the growing needs of the Earth science lidar community. OpenTopography strives to host and provide access to datasets as soon as they become available, and also to expose greater application level functionalities to our end-users (such as generation of custom DEMs via various gridding algorithms, and hydrological modeling algorithms). In the future, the SOA will enable direct authenticated access to back-end functionality through simple Web service Application Programming Interfaces (APIs), so that users may access our data and compute resources via clients other than Web browsers. In addition to an overview of the OpenTopography SOA, this presentation will discuss our recently developed lidar data ingestion and management system for point cloud data delivered in the binary LAS standard. This system compliments our existing partitioned database approach for data delivered in ASCII format, and permits rapid ingestion of data. The system has significantly reduced data ingestion times and has implications for data distribution in emergency response situations. We will also address on ongoing work to develop a community lidar metadata catalog based on the OGC Catalogue Service for Web (CSW) standard, which will help to centralize discovery of public domain lidar data.

The International Space Station: A Unique Platform For Terrestrial Remote Sensing

NASA Technical Reports Server (NTRS)

Stefanov, William L.; Evans, Cynthia A.

2012-01-01

The International Space Station (ISS) became operational in November of 2000, and until recently remote sensing activities and operations have focused on handheld astronaut photography of the Earth. This effort builds from earlier NASA and Russian space programs (e.g. Evans et al. 2000; Glazovskiy and Dessinov 2000). To date, astronauts have taken more than 600,000 images of the Earth s land surface, oceans, and atmospheric phenomena from orbit using film and digital cameras as part two payloads: NASA s Crew Earth Observations experiment (http://eol.jsc.nasa.gov/) and Russia s Uragan experiment (Stefanov et al. 2012). Many of these images have unique attributes - varying look angles, ground resolutions, and illumination - that are not available from other remote sensing platforms. Despite this large volume of imagery and clear capability for Earth remote sensing, the ISS historically has not been perceived as an Earth observations platform by many remote sensing scientists. With the recent installation of new facilities and sophisticated sensor systems, and additional systems manifested and in development, that perception is changing to take advantage of the unique capabilities and viewing opportunities offered by the ISS.

Hydraulic correction method (HCM) to enhance the efficiency of SRTM DEM in flood modeling

NASA Astrophysics Data System (ADS)

Chen, Huili; Liang, Qiuhua; Liu, Yong; Xie, Shuguang

2018-04-01

Digital Elevation Model (DEM) is one of the most important controlling factors determining the simulation accuracy of hydraulic models. However, the currently available global topographic data is confronted with limitations for application in 2-D hydraulic modeling, mainly due to the existence of vegetation bias, random errors and insufficient spatial resolution. A hydraulic correction method (HCM) for the SRTM DEM is proposed in this study to improve modeling accuracy. Firstly, we employ the global vegetation corrected DEM (i.e. Bare-Earth DEM), developed from the SRTM DEM to include both vegetation height and SRTM vegetation signal. Then, a newly released DEM, removing both vegetation bias and random errors (i.e. Multi-Error Removed DEM), is employed to overcome the limitation of height errors. Last, an approach to correct the Multi-Error Removed DEM is presented to account for the insufficiency of spatial resolution, ensuring flow connectivity of the river networks. The approach involves: (a) extracting river networks from the Multi-Error Removed DEM using an automated algorithm in ArcGIS; (b) correcting the location and layout of extracted streams with the aid of Google Earth platform and Remote Sensing imagery; and (c) removing the positive biases of the raised segment in the river networks based on bed slope to generate the hydraulically corrected DEM. The proposed HCM utilizes easily available data and tools to improve the flow connectivity of river networks without manual adjustment. To demonstrate the advantages of HCM, an extreme flood event in Huifa River Basin (China) is simulated on the original DEM, Bare-Earth DEM, Multi-Error removed DEM, and hydraulically corrected DEM using an integrated hydrologic-hydraulic model. A comparative analysis is subsequently performed to assess the simulation accuracy and performance of four different DEMs and favorable results have been obtained on the corrected DEM.

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).

Flexible Description and Adaptive Processing of Earth Observation Data through the BigEarth Platform

NASA Astrophysics Data System (ADS)

Gorgan, Dorian; Bacu, Victor; Stefanut, Teodor; Nandra, Cosmin; Mihon, Danut

2016-04-01

The Earth Observation data repositories extending periodically by several terabytes become a critical issue for organizations. The management of the storage capacity of such big datasets, accessing policy, data protection, searching, and complex processing require high costs that impose efficient solutions to balance the cost and value of data. Data can create value only when it is used, and the data protection has to be oriented toward allowing innovation that sometimes depends on creative people, which achieve unexpected valuable results through a flexible and adaptive manner. The users need to describe and experiment themselves different complex algorithms through analytics in order to valorize data. The analytics uses descriptive and predictive models to gain valuable knowledge and information from data analysis. Possible solutions for advanced processing of big Earth Observation data are given by the HPC platforms such as cloud. With platforms becoming more complex and heterogeneous, the developing of applications is even harder and the efficient mapping of these applications to a suitable and optimum platform, working on huge distributed data repositories, is challenging and complex as well, even by using specialized software services. From the user point of view, an optimum environment gives acceptable execution times, offers a high level of usability by hiding the complexity of computing infrastructure, and supports an open accessibility and control to application entities and functionality. The BigEarth platform [1] supports the entire flow of flexible description of processing by basic operators and adaptive execution over cloud infrastructure [2]. The basic modules of the pipeline such as the KEOPS [3] set of basic operators, the WorDeL language [4], the Planner for sequential and parallel processing, and the Executor through virtual machines, are detailed as the main components of the BigEarth platform [5]. The presentation exemplifies the development of some Earth Observation oriented applications based on flexible description of processing, and adaptive and portable execution over Cloud infrastructure. Main references for further information: [1] BigEarth project, http://cgis.utcluj.ro/projects/bigearth [2] Gorgan, D., "Flexible and Adaptive Processing of Earth Observation Data over High Performance Computation Architectures", International Conference and Exhibition Satellite 2015, August 17-19, Houston, Texas, USA. [3] Mihon, D., Bacu, V., Colceriu, V., Gorgan, D., "Modeling of Earth Observation Use Cases through the KEOPS System", Proceedings of the Intelligent Computer Communication and Processing (ICCP), IEEE-Press, pp. 455-460, (2015). [4] Nandra, C., Gorgan, D., "Workflow Description Language for Defining Big Earth Data Processing Tasks", Proceedings of the Intelligent Computer Communication and Processing (ICCP), IEEE-Press, pp. 461-468, (2015). [5] Bacu, V., Stefan, T., Gorgan, D., "Adaptive Processing of Earth Observation Data on Cloud Infrastructures Based on Workflow Description", Proceedings of the Intelligent Computer Communication and Processing (ICCP), IEEE-Press, pp.444-454, (2015).

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.

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

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.

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.

Relatedness-based Multi-Entity Summarization

PubMed Central

Gunaratna, Kalpa; Yazdavar, Amir Hossein; Thirunarayan, Krishnaprasad; Sheth, Amit; Cheng, Gong

2017-01-01

Representing world knowledge in a machine processable format is important as entities and their descriptions have fueled tremendous growth in knowledge-rich information processing platforms, services, and systems. Prominent applications of knowledge graphs include search engines (e.g., Google Search and Microsoft Bing), email clients (e.g., Gmail), and intelligent personal assistants (e.g., Google Now, Amazon Echo, and Apple’s Siri). In this paper, we present an approach that can summarize facts about a collection of entities by analyzing their relatedness in preference to summarizing each entity in isolation. Specifically, we generate informative entity summaries by selecting: (i) inter-entity facts that are similar and (ii) intra-entity facts that are important and diverse. We employ a constrained knapsack problem solving approach to efficiently compute entity summaries. We perform both qualitative and quantitative experiments and demonstrate that our approach yields promising results compared to two other stand-alone state-of-the-art entity summarization approaches. PMID:29051696

Functional design for operational earth resources ground data processing

NASA Technical Reports Server (NTRS)

Baldwin, C. J. (Principal Investigator); Bradford, L. H.; Hutson, D. E.; Jugle, D. R.

1972-01-01

The author has identified the following significant results. Study emphasis was on developing a unified concept for the required ground system, capable of handling data from all viable acquisition platforms and sensor groupings envisaged as supporting operational earth survey programs. The platforms considered include both manned and unmanned spacecraft in near earth orbit, and continued use of low and high altitude aircraft. The sensor systems include both imaging and nonimaging devices, operated both passively and actively, from the ultraviolet to the microwave regions of the electromagnetic spectrum.

A Dynamic Landsat Derived Normalized Difference Vegetation Index (NDVI) Product for the Conterminous United States

DOE PAGES

Robinson, Nathaniel; Allred, Brady; Jones, Matthew; ...

2017-08-21

Satellite derived vegetation indices (VIs) are broadly used in ecological research, ecosystem modeling, and land surface monitoring. The Normalized Difference Vegetation Index (NDVI), perhaps the most utilized VI, has countless applications across ecology, forestry, agriculture, wildlife, biodiversity, and other disciplines. Calculating satellite derived NDVI is not always straight-forward, however, as satellite remote sensing datasets are inherently noisy due to cloud and atmospheric contamination, data processing failures, and instrument malfunction. Readily available NDVI products that account for these complexities are generally at coarse resolution; high resolution NDVI datasets are not conveniently accessible and developing them often presents numerous technical and methodologicalmore » challenges. Here, we address this deficiency by producing a Landsat derived, high resolution (30 m), long-term (30+ years) NDVI dataset for the conterminous United States. We use Google Earth Engine, a planetary-scale cloud-based geospatial analysis platform, for processing the Landsat data and distributing the final dataset. We use a climatology driven approach to fill missing data and validate the dataset with established remote sensing products at multiple scales. We provide access to the composites through a simple web application, allowing users to customize key parameters appropriate for their application, question, and region of interest.« less

A Dynamic Landsat Derived Normalized Difference Vegetation Index (NDVI) Product for the Conterminous United States

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

Robinson, Nathaniel; Allred, Brady; Jones, Matthew

Satellite derived vegetation indices (VIs) are broadly used in ecological research, ecosystem modeling, and land surface monitoring. The Normalized Difference Vegetation Index (NDVI), perhaps the most utilized VI, has countless applications across ecology, forestry, agriculture, wildlife, biodiversity, and other disciplines. Calculating satellite derived NDVI is not always straight-forward, however, as satellite remote sensing datasets are inherently noisy due to cloud and atmospheric contamination, data processing failures, and instrument malfunction. Readily available NDVI products that account for these complexities are generally at coarse resolution; high resolution NDVI datasets are not conveniently accessible and developing them often presents numerous technical and methodologicalmore » challenges. Here, we address this deficiency by producing a Landsat derived, high resolution (30 m), long-term (30+ years) NDVI dataset for the conterminous United States. We use Google Earth Engine, a planetary-scale cloud-based geospatial analysis platform, for processing the Landsat data and distributing the final dataset. We use a climatology driven approach to fill missing data and validate the dataset with established remote sensing products at multiple scales. We provide access to the composites through a simple web application, allowing users to customize key parameters appropriate for their application, question, and region of interest.« less

Fire Weather Products for Public and Emergency Use: Extending Professional Resources to the Public

NASA Astrophysics Data System (ADS)

Rogers, M. A.; Schranz, S.; Kriederman, L.

2012-12-01

Large wildfires require significant resources to combat, including dedicated meteorological support to provide accurate and timely forecasts to assist incident commanders in making decisions for logistical and tactical firefighting operations. Smaller fires often require the same capabilities for understanding fire and the fire weather environment, but access to needed resources and tools is often limited due to technical, training, or education limitations. Providing fire weather information and training to incident commanders for smaller wildfires should prove to enhance firefighting capabilities and improve safety for both firefighters and for the public as well. One of the premier tools used to support fire weather forecasting for the largest wildfires is the FX-Net product, a thin-client version of the Advanced Weather Interactive Processing System used by NWS incident meteorologists (IMETs) deployed to large wildfires. We present results from an ongoing project to extend the sophisticated products available from FX-Net to more accessible and mobile software platforms, such as Google Earth. The project involves input from IMETs and fire commanders to identify the key parameters used in fighting wildfires, and involves a large training component for fire responders to utilize simplified products to improve understanding of fire weather in the context of firefighting operations.

SenSyF Experience on Integration of EO Services in a Generic, Cloud-Based EO Exploitation Platform

NASA Astrophysics Data System (ADS)

Almeida, Nuno; Catarino, Nuno; Gutierrez, Antonio; Grosso, Nuno; Andrade, Joao; Caumont, Herve; Goncalves, Pedro; Villa, Guillermo; Mangin, Antoine; Serra, Romain; Johnsen, Harald; Grydeland, Tom; Emsley, Stephen; Jauch, Eduardo; Moreno, Jose; Ruiz, Antonio

2016-08-01

SenSyF is a cloud-based data processing framework for EO- based services. It has been pioneer in addressing Big Data issues from the Earth Observation point of view, and is a precursor of several of the technologies and methodologies that will be deployed in ESA's Thematic Exploitation Platforms and other related systems.The SenSyF system focuses on developing fully automated data management, together with access to a processing and exploitation framework, including Earth Observation specific tools. SenSyF is both a development and validation platform for data intensive applications using Earth Observation data. With SenSyF, scientific, institutional or commercial institutions developing EO- based applications and services can take advantage of distributed computational and storage resources, tailored for applications dependent on big Earth Observation data, and without resorting to deep infrastructure and technological investments.This paper describes the integration process and the experience gathered from different EO Service providers during the project.

Design of an imaging spectrometer for earth observation using freeform mirrors

NASA Astrophysics Data System (ADS)

Peschel, T.; Damm, C.; Beier, M.; Gebhardt, A.; Risse, S.; Walter, I.; Sebastian, I.; Krutz, D.

2017-09-01

In 2017 the new hyperspectral DLR Earth Sensing Imaging Spectrometer (DESIS) will be integrated in the Multi-User-System for Earth Sensing (MUSES) platform [1] installed on the International Space Station (ISS).

Route Sanitizer: Connected Vehicle Trajectory De-Identification Tool

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

Carter, Jason M; Ferber, Aaron E

Route Sanitizer is ORNL's connected vehicle moving object database de-identification tool and a graphical user interface to ORNL's connected vehicle de-identification algorithm. It uses the Google Chrome (soon to be Electron) platform so it will run on different computing platforms. The basic de-identification strategy is record redaction: portions of a vehicle trajectory (e.g. sequences of precise temporal spatial records) are removed. It does not alter retained records. The algorithm uses custom techniques to find areas within trajectories that may be considered private, then it suppresses those in addition to enough of the trajectory surrounding those locations to protect against "inferencemore » attacks" in a mathematically sound way. Map data is integrated into the process to make this possible.« less

Space environmental effects on materials

NASA Technical Reports Server (NTRS)

Schwinghmaer, R. J.

1980-01-01

The design of long life platforms and structures for space is discussed in terms of the space environmental effects on the materials used. Vacuum, ultraviolet radiation, and charged particle radiation are among the factors considered. Research oriented toward the acquisition of long term environmental effects data needed to support the design and development of large low Earth orbit and geosynchronous Earth orbit space platforms and systems is described.

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.

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.

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.

Observing the Anthropocene from Space

NASA Astrophysics Data System (ADS)

Dittus, Hansjörg

2016-07-01

Influence of mankind on Earth's climate is evident. The growing population using the resources available, especially by burning goal, oil and gas, changes the composition of the Earth's atmosphere with the result of a continuously increasing temperature. Effects are not limited to the regional scale but are evident on the whole planet, meanwhile named Anthropocene. According to this global influence, it's necessary to also extend monitoring to the entire planet. Space-based observation systems are not limited by any artificial borders and are in principle able, to cover the whole Earth. In principle, two different ways of observation can be selected: Either a dedicated spacecraft will be send into low earth orbit (LEO) or existing platforms are used. Advantages of satellites are the more or less freely selectable orbit (with orbits covering also the polar regions) and the possible adaption of spacecraft platform for the dedicated instrument. On the other hand platforms like the ISS space station enable continuous long term coverage with different instruments. The drawback of an only limited coverage based on the orbit inclination is made up by the possibility to service systems on the station. Furthermore different generations of sensors can be run in parallel and therefore cross calibrated if needed. This paper reviews the currently available sensors types and discusses potential future needs. Included in this discussion is the international space station as an already available platform for earth observation. Furthermore, discussion should also take into account, that an increasing number of constellations with dozens or even thousand satellites are planned. Are these constellations also an option for an increased temporal and spatial monitoring of the Earth?

An online app platform enhances collaborative medical student group learning and classroom management.

PubMed

Peacock, Justin G; Grande, Joseph P

2016-01-01

The authors presented their results in effectively using a free and widely-accessible online app platform to manage and teach a first-year pathology course at Mayo Medical School. The authors utilized the Google "Blogger", "Forms", "Flubaroo", "Sheets", "Docs", and "Slides" apps to effectively build a collaborative classroom teaching and management system. Students were surveyed on the use of the app platform in the classroom, and 44 (94%) students responded. Thirty-two (73%) of the students reported that "Blogger" was an effective place for online discussion of pathology topics and questions. 43 (98%) of the students reported that the "Forms/Flubaroo" grade-reporting system was helpful. 40 (91%) of the students used the remote, collaborative features of "Slides" to create team-based learning presentations, and 39 (89%) of the students found those collaborative features helpful. "Docs" helped teaching assistants to collaboratively create study guides or grading rubrics. Overall, 41 (93%) of the students found that the app platform was helpful in establishing a collaborative, online classroom environment. The online app platform allowed faculty to build an efficient and effective classroom teaching and management system. The ease of accessibility and opportunity for collaboration allowed for collaborative learning, grading, and teaching.

Cannabis Mobile Apps: A Content Analysis.

PubMed

Ramo, Danielle E; Popova, Lucy; Grana, Rachel; Zhao, Shirley; Chavez, Kathryn

2015-08-12

Mobile technology is pervasive and widely used to obtain information about drugs such as cannabis, especially in a climate of rapidly changing cannabis policy; yet the content of available cannabis apps is largely unknown. Understanding the resources available to those searching for cannabis apps will clarify how this technology is being used to reflect and influence cannabis use behavior. We investigated the content of 59 cannabis-related mobile apps for Apple and Android devices as of November 26, 2014. The Apple and Google Play app stores were searched using the terms "cannabis" and "marijuana." Three trained coders classified the top 20 apps for each term and each store, using a coding guide. Apps were examined for the presence of 20 content codes derived by the researchers. Total apps available for each search term were 124 for cannabis and 218 for marijuana in the Apple App Store, and 250 each for cannabis and marijuana on Google Play. The top 20 apps in each category in each store were coded for 59 independent apps (30 Apple, 29 Google Play). The three most common content areas were cannabis strain classification (33.9%), facts about cannabis (20.3%), and games (20.3%). In the Apple App Store, most apps were free (77%), all were rated "17+" years, and the average user rating was 3.9/5 stars. The most popular apps provided cannabis strain classifications (50%), dispensary information (27%), or general facts about cannabis (27%). Only one app (3%) provided information or resources related to cannabis abuse, addiction, or treatment. On Google Play, most apps were free (93%), rated "high maturity" (79%), and the average user rating was 4.1/5. The most popular app types offered games (28%), phone utilities (eg, wallpaper, clock; 21%) and cannabis food recipes (21%); no apps addressed abuse, addiction, or treatment. Cannabis apps are generally free and highly rated. Apps were most often informational (facts, strain classification), or recreational (games), likely reflecting and influencing the growing acceptance of cannabis for medical and recreational purposes. Apps addressing addiction or cessation were underrepresented in the most popular cannabis mobile apps. Differences among apps for Apple and Android platforms likely reflect differences in the population of users, developer choice, and platform regulations.

Cannabis Mobile Apps: A Content Analysis

PubMed Central

Popova, Lucy; Grana, Rachel; Zhao, Shirley; Chavez, Kathryn

2015-01-01

Background Mobile technology is pervasive and widely used to obtain information about drugs such as cannabis, especially in a climate of rapidly changing cannabis policy; yet the content of available cannabis apps is largely unknown. Understanding the resources available to those searching for cannabis apps will clarify how this technology is being used to reflect and influence cannabis use behavior. Objective We investigated the content of 59 cannabis-related mobile apps for Apple and Android devices as of November 26, 2014. Methods The Apple and Google Play app stores were searched using the terms “cannabis” and “marijuana.” Three trained coders classified the top 20 apps for each term and each store, using a coding guide. Apps were examined for the presence of 20 content codes derived by the researchers. Results Total apps available for each search term were 124 for cannabis and 218 for marijuana in the Apple App Store, and 250 each for cannabis and marijuana on Google Play. The top 20 apps in each category in each store were coded for 59 independent apps (30 Apple, 29 Google Play). The three most common content areas were cannabis strain classification (33.9%), facts about cannabis (20.3%), and games (20.3%). In the Apple App Store, most apps were free (77%), all were rated “17+” years, and the average user rating was 3.9/5 stars. The most popular apps provided cannabis strain classifications (50%), dispensary information (27%), or general facts about cannabis (27%). Only one app (3%) provided information or resources related to cannabis abuse, addiction, or treatment. On Google Play, most apps were free (93%), rated “high maturity” (79%), and the average user rating was 4.1/5. The most popular app types offered games (28%), phone utilities (eg, wallpaper, clock; 21%) and cannabis food recipes (21%); no apps addressed abuse, addiction, or treatment. Conclusions Cannabis apps are generally free and highly rated. Apps were most often informational (facts, strain classification), or recreational (games), likely reflecting and influencing the growing acceptance of cannabis for medical and recreational purposes. Apps addressing addiction or cessation were underrepresented in the most popular cannabis mobile apps. Differences among apps for Apple and Android platforms likely reflect differences in the population of users, developer choice, and platform regulations. PMID:26268634

SPEKTROP DPU: optoelectronic platform for fast multispectral imaging

NASA Astrophysics Data System (ADS)

Graczyk, Rafal; Sitek, Piotr; Stolarski, Marcin

2010-09-01

In recent years it easy to spot and increasing need of high-quality Earth imaging in airborne and space applications. This is due fact that government and local authorities urge for up to date topological data for administrative purposes. On the other hand, interest in environmental sciences, push for ecological approach, efficient agriculture and forests management are also heavily supported by Earth images in various resolutions and spectral ranges. "SPEKTROP DPU: Opto-electronic platform for fast multi-spectral imaging" paper describes architectural datails of data processing unit, part of universal and modular platform that provides high quality imaging functionality in aerospace applications.

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.

Geostationary multipurpose platforms

NASA Technical Reports Server (NTRS)

Bekey, I.; Bowman, R. M.

1981-01-01

In addition to the advantages generally associated with orbital platforms, such as improved reliability, economies of scale, simple connectivity of elements, reduced tracking demands and the restraint of orbital object population growth, geostationary platforms yield: (1) continuous access by fixed ground antennas for communications services; (2) continuous monitoring of phenomena over chosen regions of the earth's surface; (3) a preferred location for many solar-terrestrial physics experiments. The geostationary platform also offers a low-risk and economical solution to the impending saturation of the orbital arc/frequency spectrum, maximizing the capacity of individual slots and increasing the utility of the entire arc. It also allows the use of many small, simple and inexpensive earth stations through complexity inversion and high power per beam. Block diagram and operational flowcharts are provided.

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.

ANTP Protocol Suite Software Implementation Architecture in Python

DTIC Science & Technology

2011-06-03

a popular platform of networking programming, an area in which C has traditionally dominated. 2 NetController AeroRP AeroNP AeroNP API AeroTP...visualisation of the running system. For example using the Google Maps API , the main logging web page can show all the running nodes in the system. By...communication between AeroNP and AeroRP and runs on the operating system as daemon. Furthermore, it creates an API interface to mange the communication between

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.

Vehicle-based Methane Mapping Helps Find Natural Gas Leaks and Prioritize Leak Repairs

NASA Astrophysics Data System (ADS)

von Fischer, J. C.; Weller, Z.; Roscioli, J. R.; Lamb, B. K.; Ferrara, T.

2017-12-01

Recently, mobile methane sensing platforms have been developed to detect and locate natural gas (NG) leaks in urban distribution systems and to estimate their size. Although this technology has already been used in targeted deployment for prioritization of NG pipeline infrastructure repair and replacement, one open question regarding this technology is how effective the resulting data are for prioritizing infrastructure repair and replacement. To answer this question we explore the accuracy and precision of the natural gas leak location and emission estimates provided by methane sensors placed on Google Street View (GSV) vehicles. We find that the vast majority (75%) of methane emitting sources detected by these mobile platforms are NG leaks and that the location estimates are effective at identifying the general location of leaks. We also show that the emission rate estimates from mobile detection platforms are able to effectively rank NG leaks for prioritizing leak repair. Our findings establish that mobile sensing platforms are an efficient and effective tool for improving the safety and reducing the environmental impacts of low-pressure NG distribution systems by reducing atmospheric methane emissions.

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.

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

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

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.

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.

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.

Space technology and the optical sciences.

PubMed

Yates, H W

1982-01-15

The earth-orbiting satellites and the deep-space probes have provided for the optical sciences platforms from which to study the earth, the solar system, and the universe with truly revolutionary capability. For the terrestrial sciences the orbiting platforms for optical measurements in both low and geostationary orbits have given us a view of our planet and a global coverage never before possible. For the astronomical applications of optical instruments that "cataract of the telescopic eye," the atmosphere of the earth has been left behind and through proximity, including actual contact, we now have resolution and spectral coverage limited only by money and motive.

The military health system's personal health record pilot with Microsoft HealthVault and Google Health.

PubMed

Do, Nhan V; Barnhill, Rick; Heermann-Do, Kimberly A; Salzman, Keith L; Gimbel, Ronald W

2011-01-01

To design, build, implement, and evaluate a personal health record (PHR), tethered to the Military Health System, that leverages Microsoft® HealthVault and Google® Health infrastructure based on user preference. A pilot project was conducted in 2008-2009 at Madigan Army Medical Center in Tacoma, Washington. Our PHR was architected to a flexible platform that incorporated standards-based models of Continuity of Document and Continuity of Care Record to map Department of Defense-sourced health data, via a secure Veterans Administration data broker, to Microsoft® HealthVault and Google® Health based on user preference. The project design and implementation were guided by provider and patient advisory panels with formal user evaluation. The pilot project included 250 beneficiary users. Approximately 73.2% of users were < 65 years of age, and 38.4% were female. Of the users, 169 (67.6%) selected Microsoft® HealthVault, and 81 (32.4%) selected Google® Health as their PHR of preference. Sample evaluation of users reflected 100% (n = 60) satisfied with convenience of record access and 91.7% (n = 55) satisfied with overall functionality of PHR. Key lessons learned related to data-transfer decisions (push vs pull), purposeful delays in reporting sensitive information, understanding and mapping PHR use and clinical workflow, and decisions on information patients may choose to share with their provider. Currently PHRs are being viewed as empowering tools for patient activation. Design and implementation issues (eg, technical, organizational, information security) are substantial and must be thoughtfully approached. Adopting standards into design can enhance the national goal of portability and interoperability.

Googling DNA sequences on the World Wide Web.

PubMed

Hajibabaei, Mehrdad; Singer, Gregory A C

2009-11-10

New web-based technologies provide an excellent opportunity for sharing and accessing information and using web as a platform for interaction and collaboration. Although several specialized tools are available for analyzing DNA sequence information, conventional web-based tools have not been utilized for bioinformatics applications. We have developed a novel algorithm and implemented it for searching species-specific genomic sequences, DNA barcodes, by using popular web-based methods such as Google. We developed an alignment independent character based algorithm based on dividing a sequence library (DNA barcodes) and query sequence to words. The actual search is conducted by conventional search tools such as freely available Google Desktop Search. We implemented our algorithm in two exemplar packages. We developed pre and post-processing software to provide customized input and output services, respectively. Our analysis of all publicly available DNA barcode sequences shows a high accuracy as well as rapid results. Our method makes use of conventional web-based technologies for specialized genetic data. It provides a robust and efficient solution for sequence search on the web. The integration of our search method for large-scale sequence libraries such as DNA barcodes provides an excellent web-based tool for accessing this information and linking it to other available categories of information on the web.

Utility of Web search query data in testing theoretical assumptions about mephedrone.

PubMed

Kapitány-Fövény, Máté; Demetrovics, Zsolt

2017-05-01

With growing access to the Internet, people who use drugs and traffickers started to obtain information about novel psychoactive substances (NPS) via online platforms. This paper aims to analyze whether a decreasing Web interest in formerly banned substances-cocaine, heroin, and MDMA-and the legislative status of mephedrone predict Web interest about this NPS. Google Trends was used to measure changes of Web interest on cocaine, heroin, MDMA, and mephedrone. Google search results for mephedrone within the same time frame were analyzed and categorized. Web interest about classic drugs found to be more persistent. Regarding geographical distribution, location of Web searches for heroin and cocaine was less centralized. Illicit status of mephedrone was a negative predictor of its Web search query rates. The connection between mephedrone-related Web search rates and legislative status of this substance was significantly mediated by ecstasy-related Web search queries, the number of documentaries, and forum/blog entries about mephedrone. The results might provide support for the hypothesis that mephedrone's popularity was highly correlated with its legal status as well as it functioned as a potential substitute for MDMA. Google Trends was found to be a useful tool for testing theoretical assumptions about NPS. Copyright © 2017 John Wiley & Sons, Ltd.

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

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.

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.

Pict'Earth: A new Method of Virtual Globe Data Acquisition

NASA Astrophysics Data System (ADS)

Johnson, J.; Long, S.; Riallant, D.; Hronusov, V.

2007-12-01

Georeferenced aerial imagery facilitates and enhances Earth science investigations. The realized value of imagery as a tool is measured from the spatial, temporal and radiometric resolution of the imagery. Currently, there is an need for a system which facilitates the rapid acquisition and distribution of high-resolution aerial earth images of localized areas. The Pict'Earth group has developed an apparatus and software algorithms which facilitate such tasks. Hardware includes a small radio-controlled model airplane (RC UAV); Light smartphones with high resolution cameras (Nokia NSeries Devices); and a GPS connected to the smartphone via the bluetooth protocol, or GPS-equipped phone. Software includes python code which controls the functions of the smartphone and GPS to acquire data in-flight; Online Virtual Globe applications including Google Earth, AJAX/Web2.0 technologies and services; APIs and libraries for developers, all of which are based on open XML-based GIS data standards. This new process for acquisition and distribution of high-resolution aerial earth images includes the following stages: Perform Survey over area of interest (AOI) with the RC UAV (Mobile Liveprocessing). In real-time our software collects images from the smartphone camera and positional data (latitude, longitude, altitude and heading) from the GPS. The software then calculates the earth footprint (geoprint) of each image and creates KML files which incorporate the georeferenced images and tracks of UAV. Optionally, it is possible to send the data in- flight via SMS/MMS (text and multimedia messages), or cellular internet networks via FTP. In Post processing the images are filtered, transformed, and assembled into a orthorectified image mosaic. The final mosaic is then cut into tiles and uploaded as a user ready product to web servers in kml format for use in Virtual Globes and other GIS applications. The obtained images and resultant data have high spatial resolution, can be updated in near-real time (high temporal resolution), and provide current radiance values (which is important for seasonal work). The final mosaics can also be assembled into time-lapse sequences and presented temporally. The suggested solution is cost effective when compared to the alternative methods of acquiring similar imagery. The systems are compact, mobile, and do not require a substantial amount of auxiliary equipment. Ongoing development of the software makes it possible to adapt the technology to different platforms, smartphones, sensors, and types of data. The range of application of this technology potentially covers a large part of the spectrum of Earth sciences including the calibration and validation of high-resolution satellite-derived products. These systems are currently being used for monitoring of dynamic land and water surface processes, and can be used for reconnaissance when locating and establishing field measurement sites.

Cropland Capture: A Game to Improve Global Cropland through Crowdsourcing

NASA Astrophysics Data System (ADS)

Fritz, Steffen; Sturn, Tobias; See, Linda; Perger, Christoph; Schill, Christian; McCallum, Ian; Schepaschenko, Dmitry; Karner, Mathias; Dueruer, Martina; Kraxner, Florian; Obersteiner, Michael

2014-05-01

Accurate and reliable global cropland extent maps are essential for estimating and forecasting crop yield, in particular losses due to drought and production anomalies. Major questions surrounding energy futures and environmental change (EU and US biofuel target setting, determination of greenhouse gas emissions, REDD initiatives, and implications of climate change on crop production and productivity patterns) also require reliable information on the spatial distribution of cropland as well as crop types. Although global land cover maps identify cropland (which exist as one or more land cover categories), this information is currently not accurate enough for many applications. There are several ways of improving current cropland extent though hybrid approaches and by integrating information collected though Geo-Wiki (a global crowdsourcing platform) from very high resolution imagery such as that found on Google Earth. Another way of getting improved cropland extent maps would be to classify all very high resolution images found on Google Earth and to create a wall-to-wall map of cropland. This is a very ambitious task that would require a large number of individuals, like that found in massive multiplayer online games. For this reason we have developed a game called 'Cropland Capture'. The game can be played on a desktop, on a tablet (iPad or Android) or mobile phone (iPhone or Android) where the game mechanics are very simple. The player is provided with a satellite image or in-situ photo and they must determine if the image contains cropland or not. The game was launched in the middle of November 2013 and will run for 6 months, after which the weekly winners will be entered into a draw to win large prizes. To date we have collected more than 2.5 million areas, where we will continue to expand the sample to more locations around the world. Eventually the data will be used to calibrate and validate a new version of our global cropland map, where the latest version is available from http://beta-hybrid.geo-wiki.org. If we find, however, that a large number of people participate in the game, we will aim to make wall-to-wall cropland maps for those countries where no national maps exist. This paper will present an overview of the game and a summary of the crowdsourced data from the game, including information about quality and user performance. If successful, this gaming approach could be used to gather information about other land cover types in the future in order to improve global land cover information more generally.

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.

Accelerating Neoproterozoic Research through Scientific Drilling

NASA Astrophysics Data System (ADS)

Condon, Daniel; Prave, Anthony; Boggiani, Paulo; Fike, David; Halverson, Galen; Kasemann, Simone; Knoll, Andrew; Zhu, Maoyan

2014-05-01

The Neoproterozoic Era (1.0 to 0.541 Ga) and earliest Cambrian (541 to ca. 520 Ma) records geologic changes unlike any other in Earth history: supercontinental tectonics of Rodinia followed by its breakup and dispersal into fragments that form the core of today's continents; a rise in oxygen that, perhaps for the first time in Earth history, resulted in the deep oceans becoming oxic; snowball Earth, which envisages a blanketing of global ice cover for millions of years; and, at the zenith of these combined biogeochemical changes, the evolutionary leap from eukaryotes to animals. Such a concentration of hallmark events in the evolution of our planet is unparalleled and many questions regarding Earth System evolution during times of profound climatic and geological changes remain to be answered. Neoproterozoic successions also offer insight into the genesis of a number of natural resources. These include banded-iron formation, organic-rich shale intervals (with demonstrated hydrocarbon source rocks already economically viable in some countries), base and precious metal ore deposits and REE occurrences, as well as industrial minerals and dimension stone. Developing our understanding of the Neoproterozoic Earth-system, combined with regional geology has the potential to impact the viability of these resources. Our understanding of the Neoproterozoic and early Cambrian, though, is overwhelmingly dependent on outcrop-based studies, which suffer from lack of continuity of outcrop and, in many instances, deep weathering profiles. A limited number of research projects study Precambrian strata have demonstrated the potential impact of scientific drilling to augment and complement ongoing outcrop based studies and advancing research. An ICDP and ECORD sponsored workshop, to be held in March 2014, has been convened to discuss the utility of scientific drilling for accelerating research of the Neoproterozoic through early Cambrian (ca. 0.9 to 0.52 Ga) rock record. The aim is to discuss the potential for establishing a collaborative, integrated, worldwide drilling programme to obtain the pristine samples and continuous sections needed to refine Neoproterozoic Earth history, inform assessment of resource potential, and address the major questions noted above. Such an initiative would be a platform to define complementary research and discovery between cutting-edge interdisciplinary scientific studies and synergistic collaborations with national agencies (Geological Surveys) and industry partners. A number of potential sites have been identified and discussed, along with identifying the mechanisms by which the Neoproterozoic research community can development data archives, open access data, sample archiving, and the approaches to multi-national funding. We will, amongst other things, present a summary of the workshop discussions. For more information visit: https://sites.google.com/site/drillingtheneoproterozoic/

Earth system modelling on system-level heterogeneous architectures: EMAC (version 2.42) on the Dynamical Exascale Entry Platform (DEEP)

NASA Astrophysics Data System (ADS)

Christou, Michalis; Christoudias, Theodoros; Morillo, Julián; Alvarez, Damian; Merx, Hendrik

2016-09-01

We examine an alternative approach to heterogeneous cluster-computing in the many-core era for Earth system models, using the European Centre for Medium-Range Weather Forecasts Hamburg (ECHAM)/Modular Earth Submodel System (MESSy) Atmospheric Chemistry (EMAC) model as a pilot application on the Dynamical Exascale Entry Platform (DEEP). A set of autonomous coprocessors interconnected together, called Booster, complements a conventional HPC Cluster and increases its computing performance, offering extra flexibility to expose multiple levels of parallelism and achieve better scalability. The EMAC model atmospheric chemistry code (Module Efficiently Calculating the Chemistry of the Atmosphere (MECCA)) was taskified with an offload mechanism implemented using OmpSs directives. The model was ported to the MareNostrum 3 supercomputer to allow testing with Intel Xeon Phi accelerators on a production-size machine. The changes proposed in this paper are expected to contribute to the eventual adoption of Cluster-Booster division and Many Integrated Core (MIC) accelerated architectures in presently available implementations of Earth system models, towards exploiting the potential of a fully Exascale-capable platform.

Promoting scientific collaboration and research through integrated social networking capabilities within the OpenTopography Portal

NASA Astrophysics Data System (ADS)

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

2009-04-01

LiDAR (Light Distance And Ranging) topography data offer earth scientists the opportunity to study the earth's surface at very high resolutions. As a result, the popularity of these data is growing dramatically. However, the management, distribution, and analysis of community LiDAR data sets is a challenge due to their massive size (multi-billion point, mutli-terabyte). We have also found that many earth science users of these data sets lack the computing resources and expertise required to process these data. We have developed the OpenTopography Portal to democratize access to these large and computationally challenging data sets. The OpenTopography Portal uses cyberinfrastructure technology developed by the GEON project to provide access to LiDAR data in a variety of formats. LiDAR data products available range from simple Google Earth visualizations of LiDAR-derived hillshades to 1 km2 tiles of standard digital elevation model (DEM) products as well as LiDAR point cloud data and user generated custom-DEMs. We have found that the wide spectrum of LiDAR users have variable scientific applications, computing resources and technical experience and thus require a data system with multiple distribution mechanisms and platforms to serve a broader range of user communities. Because the volume of LiDAR topography data available is rapidly expanding, and data analysis techniques are evolving, there is a need for the user community to be able to communicate and interact to share knowledge and experiences. To address this need, the OpenTopography Portal enables social networking capabilities through a variety of collaboration tools, web 2.0 technologies and customized usage pattern tracking. Fundamentally, these tools offer users the ability to communicate, to access and share documents, participate in discussions, and to keep up to date on upcoming events and emerging technologies. The OpenTopography portal achieves the social networking capabilities by integrating various software technologies and platforms. These include the Expression Engine Content Management System (CMS) that comes with pre-packaged collaboration tools like blogs and wikis, the Gridsphere portal framework that contains the primary GEON LiDAR System portlet with user job monitoring capabilities and a java web based discussion forum (Jforums) application all seamlessly integrated under one portal. The OpenTopography Portal also provides integrated authentication mechanism between the various CMS collaboration tools and the core gridsphere based portlets. The integration of these various technologies allows for enhanced user interaction capabilities within the portal. By integrating popular collaboration tools like discussion forums and blogs we can promote conversation and openness among users. The ability to ask question and share expertise in forum discussions allows users to easily find information and interact with users facing similar challenges. The OpenTopography Blog enables our domain experts to post ideas, news items, commentary, and other resources in order to foster discussion and information sharing. The content management capabilities of the portal allow for easy updates to information in the form of publications, documents, and news articles. Access to the most current information fosters better decision-making. As has become the standard for web 2.0 technologies, the OpenTopography Portal is fully RSS enabled to allow users of the portal to keep track of news items, forum discussions, blog updates, and system outages. We are currently exploring how the information captured by user and job monitoring components of the Gridsphere based GEON LiDAR System can be harnessed to provide a recommender system that will help users to identify appropriate processing parameters and to locate related documents and data. By seamlessly integrating the various platforms and technologies under one single portal, we can take advantage of popular online collaboration tools that are either stand alone or software platform restricted. The availability of these collaboration tools along with the data will foster more community interaction and increase the strength and vibrancy of the LiDAR topography user community.

Geosynchronous earth orbit/low earth orbit space object inspection and debris disposal: A preliminary analysis using a carrier satellite with deployable small satellites

NASA Astrophysics Data System (ADS)

Crockett, Derick

Detailed observations of geosynchronous satellites from earth are very limited. To better inspect these high altitude satellites, the use of small, refuelable satellites is proposed. The small satellites are stationed on a carrier platform in an orbit near the population of geosynchronous satellites. A carrier platform equipped with deployable, refuelable SmallSats is a viable option to inspect geosynchronous satellites. The propellant requirement to transfer to a targeted geosynchronous satellite, perform a proximity inspection mission, and transfer back to the carrier platform in a nearby orbit is determined. Convex optimization and traditional optimization techniques are explored, determining minimum propellant trajectories. Propellant is measured by the total required change in velocity, delta-v. The trajectories were modeled in a relative reference frame using the Clohessy-Wiltshire equations. Mass estimations for the carrier platform and the SmallSat were determined by using the rocket equation. The mass estimates were compared to the mass of a single, non-refuelable satellite performing the same geosynchronous satellite inspection missions. From the minimum delta-v trajectories and the mass analysis, it is determined that using refuelable SmallSats and a carrier platform in a nearby orbit can be more efficient than using a single non-refuelable satellite to perform multiple geosynchronous satellite inspections.

Earth Observation-Supported Service Platform for the Development and Provision of Thematic Information on the Built Environment - the Tep-Urban Project

NASA Astrophysics Data System (ADS)

Esch, T.; Asamer, H.; Boettcher, M.; Brito, F.; Hirner, A.; Marconcini, M.; Mathot, E.; Metz, A.; Permana, H.; Soukop, T.; Stanek, F.; Kuchar, S.; Zeidler, J.; Balhar, J.

2016-06-01

The Sentinel fleet will provide a so-far unique coverage with Earth observation data and therewith new opportunities for the implementation of methodologies to generate innovative geo-information products and services. It is here where the TEP Urban project is supposed to initiate a step change by providing an open and participatory platform based on modern ICT technologies and services that enables any interested user to easily exploit Earth observation data pools, in particular those of the Sentinel missions, and derive thematic information on the status and development of the built environment from these data. Key component of TEP Urban project is the implementation of a web-based platform employing distributed high-level computing infrastructures and providing key functionalities for i) high-performance access to satellite imagery and derived thematic data, ii) modular and generic state-of-the art pre-processing, analysis, and visualization techniques, iii) customized development and dissemination of algorithms, products and services, and iv) networking and communication. This contribution introduces the main facts about the TEP Urban project, including a description of the general objectives, the platform systems design and functionalities, and the preliminary portfolio products and services available at the TEP Urban platform.

Mobile Videoconferencing Apps for Telemedicine

PubMed Central

Liu, Wei-Li; Locatis, Craig; Ackerman, Michael

2016-01-01

Abstract Introduction: The quality and performance of several videoconferencing applications (apps) tested on iOS (Apple, Cupertino, CA) and Android™ (Google, Mountain View, CA) mobile platforms using Wi-Fi (802.11), third-generation (3G), and fourth-generation (4G) cellular networks are described. Materials and Methods: The tests were done to determine how well apps perform compared with videoconferencing software installed on computers or with more traditional videoconferencing using dedicated hardware. The rationale for app assessment and the testing methodology are described. Results: Findings are discussed in relation to operating system platform (iOS or Android) for which the apps were designed and the type of network (Wi-Fi, 3G, or 4G) used. The platform, network, and apps interact, and it is impossible to discuss videoconferencing experienced on mobile devices in relation to one of these factors without referencing the others. Conclusions: Apps for mobile devices can vary significantly from other videoconferencing software or hardware. App performance increased over the testing period due to improvements in network infrastructure and how apps manage bandwidth. PMID:26204322

Mobile Videoconferencing Apps for Telemedicine.

PubMed

Zhang, Kai; Liu, Wei-Li; Locatis, Craig; Ackerman, Michael

2016-01-01

The quality and performance of several videoconferencing applications (apps) tested on iOS (Apple, Cupertino, CA) and Android (Google, Mountain View, CA) mobile platforms using Wi-Fi (802.11), third-generation (3G), and fourth-generation (4G) cellular networks are described. The tests were done to determine how well apps perform compared with videoconferencing software installed on computers or with more traditional videoconferencing using dedicated hardware. The rationale for app assessment and the testing methodology are described. Findings are discussed in relation to operating system platform (iOS or Android) for which the apps were designed and the type of network (Wi-Fi, 3G, or 4G) used. The platform, network, and apps interact, and it is impossible to discuss videoconferencing experienced on mobile devices in relation to one of these factors without referencing the others. Apps for mobile devices can vary significantly from other videoconferencing software or hardware. App performance increased over the testing period due to improvements in network infrastructure and how apps manage bandwidth.

Distributed Processing of Sentinel-2 Products using the BIGEARTH Platform

NASA Astrophysics Data System (ADS)

Bacu, Victor; Stefanut, Teodor; Nandra, Constantin; Mihon, Danut; Gorgan, Dorian

2017-04-01

The constellation of observational satellites orbiting around Earth is constantly increasing, providing more data that need to be processed in order to extract meaningful information and knowledge from it. Sentinel-2 satellites, part of the Copernicus Earth Observation program, aim to be used in agriculture, forestry and many other land management applications. ESA's SNAP toolbox can be used to process data gathered by Sentinel-2 satellites but is limited to the resources provided by a stand-alone computer. In this paper we present a cloud based software platform that makes use of this toolbox together with other remote sensing software applications to process Sentinel-2 products. The BIGEARTH software platform [1] offers an integrated solution for processing Earth Observation data coming from different sources (such as satellites or on-site sensors). The flow of processing is defined as a chain of tasks based on the WorDeL description language [2]. Each task could rely on a different software technology (such as Grass GIS and ESA's SNAP) in order to process the input data. One important feature of the BIGEARTH platform comes from this possibility of interconnection and integration, throughout the same flow of processing, of the various well known software technologies. All this integration is transparent from the user perspective. The proposed platform extends the SNAP capabilities by enabling specialists to easily scale the processing over distributed architectures, according to their specific needs and resources. The software platform [3] can be used in multiple configurations. In the basic one the software platform runs as a standalone application inside a virtual machine. Obviously in this case the computational resources are limited but it will give an overview of the functionalities of the software platform, and also the possibility to define the flow of processing and later on to execute it on a more complex infrastructure. The most complex and robust configuration is based on cloud computing and allows the installation on a private or public cloud infrastructure. In this configuration, the processing resources can be dynamically allocated and the execution time can be considerably improved by the available virtual resources and the number of parallelizable sequences in the processing flow. The presentation highlights the benefits and issues of the proposed solution by analyzing some significant experimental use cases. Main references for further information: [1] BigEarth project, http://cgis.utcluj.ro/projects/bigearth [2] Constantin Nandra, Dorian Gorgan: "Defining Earth data batch processing tasks by means of a flexible workflow description language", ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-4, 59-66, (2016). [3] Victor Bacu, Teodor Stefanut, Dorian Gorgan, "Adaptive Processing of Earth Observation Data on Cloud Infrastructures Based on Workflow Description", Proceedings of the Intelligent Computer Communication and Processing (ICCP), IEEE-Press, pp.444-454, (2015).

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.

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.

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

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

DSCOVR: A New Perspective for Earth Observations from Space. Synergism and Complementarity with Existing Platforms

NASA Astrophysics Data System (ADS)

Valero, F. P.

2011-12-01

The Sun-Earth Lagrange points L-1 and L-2 mark positions where the gravitational pull of the Earth and Sun precisely equals the centripetal force required to rotate with the Earth about the Sun with the same orbital period as the Earth. Therefore, a satellite maintained at one of these Lagrange points would keep the same relative position to the Sun and the Earth and be able to observe most points on the planet as the Earth rotates during the day. L-1 and L-2 are of particular interest because a satellite at either location can easily be maintained near the Sun-Earth line and views the entire daytime hemisphere from L-1 and the entire nighttime hemisphere from L-2. Since L-1 and L-2 are in the ecliptic plane, synoptic, high temporal-resolution observations would be obtained as every point on the planet, including both polar regions, transits from sunrise to sunset (L-1) or from sunset to sunrise (L-2). In summary, a pair of deep-space observatories, one at L-1 (daytime) and one at L-2 (nighttime), could acquire minute by minute climate quality data for essentially every point on Earth, all observations simultaneously for the whole planet. Such unique attributes are incorporated in the Deep Space Climate Observatory (DSCOVR) that will systematically observe climate drivers (radiation, aerosols, ozone, clouds, oxygen A-band) from L-1 in ways not possible but synergistically complementary with platforms in Low Earth Orbit (LEO) or Geostationary Earth Orbit (GEO). The combination of Solar Lagrange Points (located in the ecliptic plane) GEO (located in the equatorial plane) and LEO platforms would certainly provide a powerful observational tool as well as enriched data sets for Earth sciences. Such synergism is greatly enhanced when one considers the potential of utilizing LEO, GEO, and Lagrange point satellites as components of an integrated observational system. For example, satellites at L-1 and L-2 will view the Earth plus the Moon while simultaneously having in their fields of view (at one time or another) all Earth-orbiting and GEO satellites. This view offers the opportunity to use the Moon as a comparison reference that can in turn be shared with all other Earth observation satellites. The L-1 and L-2 observatories can become important links between LEO and GEO satellites while at the same time providing the data necessary to build an integrated Earth observational system. A synergistic, integrated system composed of LEO, GEO, L-1 and L-2 platforms is likely the way of the future.

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.

Information services platforms at geosynchronous earth orbit: A requirements analysis

NASA Technical Reports Server (NTRS)

1978-01-01

The potential user requirements for Information Services Platforms at geosynchronous orbits were investigated. A rationale for identifying the corollary system requirements and supporting research and technology needs was provided.

Farm Management Support on Cloud Computing Platform: A System for Cropland Monitoring Using Multi-Source Remotely Sensed Data

NASA Astrophysics Data System (ADS)

Coburn, C. A.; Qin, Y.; Zhang, J.; Staenz, K.

2015-12-01

Food security is one of the most pressing issues facing humankind. Recent estimates predict that over one billion people don't have enough food to meet their basic nutritional needs. The ability of remote sensing tools to monitor and model crop production and predict crop yield is essential for providing governments and farmers with vital information to ensure food security. Google Earth Engine (GEE) is a cloud computing platform, which integrates storage and processing algorithms for massive remotely sensed imagery and vector data sets. By providing the capabilities of storing and analyzing the data sets, it provides an ideal platform for the development of advanced analytic tools for extracting key variables used in regional and national food security systems. With the high performance computing and storing capabilities of GEE, a cloud-computing based system for near real-time crop land monitoring was developed using multi-source remotely sensed data over large areas. The system is able to process and visualize the MODIS time series NDVI profile in conjunction with Landsat 8 image segmentation for crop monitoring. With multi-temporal Landsat 8 imagery, the crop fields are extracted using the image segmentation algorithm developed by Baatz et al.[1]. The MODIS time series NDVI data are modeled by TIMESAT [2], a software package developed for analyzing time series of satellite data. The seasonality of MODIS time series data, for example, the start date of the growing season, length of growing season, and NDVI peak at a field-level are obtained for evaluating the crop-growth conditions. The system fuses MODIS time series NDVI data and Landsat 8 imagery to provide information of near real-time crop-growth conditions through the visualization of MODIS NDVI time series and comparison of multi-year NDVI profiles. Stakeholders, i.e., farmers and government officers, are able to obtain crop-growth information at crop-field level online. This unique utilization of GEE in combination with advanced analytic and extraction techniques provides a vital remote sensing tool for decision makers and scientists with a high-degree of flexibility to adapt to different uses.

Teaching Earth Signals Analysis Using the Java-DSP Earth Systems Edition: Modern and Past Climate Change

ERIC Educational Resources Information Center

Ramamurthy, Karthikeyan Natesan; Hinnov, Linda A.; Spanias, Andreas S.

2014-01-01

Modern data collection in the Earth Sciences has propelled the need for understanding signal processing and time-series analysis techniques. However, there is an educational disconnect in the lack of instruction of time-series analysis techniques in many Earth Science academic departments. Furthermore, there are no platform-independent freeware…

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.

Mission specification for three generic mission classes

NASA Technical Reports Server (NTRS)

1979-01-01

Mission specifications for three generic mission classes are generated to provide a baseline for definition and analysis of data acquisition platform system concepts. The mission specifications define compatible groupings of sensors that satisfy specific earth resources and environmental mission objectives. The driving force behind the definition of sensor groupings is mission need; platform and space transportation system constraints are of secondary importance. The three generic mission classes are: (1) low earth orbit sun-synchronous; (2) geosynchronous; and (3) non-sun-synchronous, nongeosynchronous. These missions are chosen to provide a variety of sensor complements and implementation concepts. Each mission specification relates mission categories, mission objectives, measured parameters, and candidate sensors to orbits and coverage, operations compatibility, and platform fleet size.

[Sexuality education on the Internet : From Dr. Sommer to Dr. Google].

PubMed

Döring, Nicola

2017-09-01

Female and male adolescents in Germany are increasingly using the Internet to find information about sexuality and sexual health. This review paper summarizes what we know about the status quo of online sexuality education in Germany.Based on a systematic literature review including 40 papers from international, peer-reviewed journals spanning 2010-2017, this paper first describes different aspects of the sexuality-related online search behavior of adolescents: its prevalence, predictors, topics and contexts. One main finding is the fact that adolescents use a computer or smartphone to type their sexuality-related questions into the search engine Google or the search engine of the video platform YouTube.Based on 54 online searches, this paper subsequently presents the kind of sexuality-related online content adolescents find if they ask "Dr. Google" for sexual advice; a collection of 1236 authentic sexuality-related questions of adolescents was used for this analysis. It turned out that online sexuality education offered by leading professional organizations like the BZgA ("Bundeszentrale für gesundheitliche Aufklärung") or pro familia was nearly invisible, while numerous other providers of online sex education consistently appeared in the top Google search results. Among them were the "Dr. Sommer" team of the youth magazine Bravo; online healthcare and advice portals; online forums; the online encyclopedia Wikipedia and, above all, sex education channels on YouTube. In this paper, the latter are presented in more detail for the first time.The third part of the paper addresses the quality of online sexual education over four main areas of quality evaluation. The presentation of the status quo ends with some recommendations both for future research and for sexuality education in practice.

Quantification of Plant Chlorophyll Content Using Google Glass

PubMed Central

Cortazar, Bingen; Koydemir, Hatice Ceylan; Tseng, Derek; Feng, Steve; Ozcan, Aydogan

2015-01-01

Measuring plant chlorophyll concentration is a well-known and commonly used method in agriculture and environmental applications for monitoring plant health, which also correlates with many other plant parameters including, e.g., carotenoids, nitrogen, maximum green fluorescence, etc. Direct chlorophyll measurement using chemical extraction is destructive, complex and time-consuming, which has led to the development of mobile optical readers, providing non-destructive but at the same time relatively expensive tools for evaluation of plant chlorophyll levels. Here we demonstrate accurate measurement of chlorophyll concentration in plant leaves using Google Glass and a custom-developed software application together with a cost-effective leaf holder and multi-spectral illuminator device. Two images, taken using Google Glass, of a leaf placed in our portable illuminator device under red and white (i.e., broadband) light-emitting-diode (LED) illumination are uploaded to our servers for remote digital processing and chlorophyll quantification, with results returned to the user in less than 10 seconds. Intensity measurements extracted from the uploaded images are mapped against gold-standard colorimetric measurements made through a commercially available reader to generate calibration curves for plant leaf chlorophyll concentration. Using five plant species to calibrate our system, we demonstrate that our approach can accurately and rapidly estimate chlorophyll concentration of fifteen different plant species under both indoor and outdoor lighting conditions. This Google Glass based chlorophyll measurement platform can display the results in spatiotemporal and tabular forms and would be highly useful for monitoring of plant health in environmental and agriculture related applications, including e.g., urban plant monitoring, indirect measurements of the effects of climate change, and as an early indicator for water, soil, and air quality degradation. PMID:25669673

Quantification of plant chlorophyll content using Google Glass.

PubMed

Cortazar, Bingen; Koydemir, Hatice Ceylan; Tseng, Derek; Feng, Steve; Ozcan, Aydogan

2015-04-07

Measuring plant chlorophyll concentration is a well-known and commonly used method in agriculture and environmental applications for monitoring plant health, which also correlates with many other plant parameters including, e.g., carotenoids, nitrogen, maximum green fluorescence, etc. Direct chlorophyll measurement using chemical extraction is destructive, complex and time-consuming, which has led to the development of mobile optical readers, providing non-destructive but at the same time relatively expensive tools for evaluation of plant chlorophyll levels. Here we demonstrate accurate measurement of chlorophyll concentration in plant leaves using Google Glass and a custom-developed software application together with a cost-effective leaf holder and multi-spectral illuminator device. Two images, taken using Google Glass, of a leaf placed in our portable illuminator device under red and white (i.e., broadband) light-emitting-diode (LED) illumination are uploaded to our servers for remote digital processing and chlorophyll quantification, with results returned to the user in less than 10 seconds. Intensity measurements extracted from the uploaded images are mapped against gold-standard colorimetric measurements made through a commercially available reader to generate calibration curves for plant leaf chlorophyll concentration. Using five plant species to calibrate our system, we demonstrate that our approach can accurately and rapidly estimate chlorophyll concentration of fifteen different plant species under both indoor and outdoor lighting conditions. This Google Glass based chlorophyll measurement platform can display the results in spatiotemporal and tabular forms and would be highly useful for monitoring of plant health in environmental and agriculture related applications, including e.g., urban plant monitoring, indirect measurements of the effects of climate change, and as an early indicator for water, soil, and air quality degradation.

The military health system's personal health record pilot with Microsoft HealthVault and Google Health

PubMed Central

Barnhill, Rick; Heermann-Do, Kimberly A; Salzman, Keith L; Gimbel, Ronald W

2011-01-01

Objective To design, build, implement, and evaluate a personal health record (PHR), tethered to the Military Health System, that leverages Microsoft® HealthVault and Google® Health infrastructure based on user preference. Materials and methods A pilot project was conducted in 2008–2009 at Madigan Army Medical Center in Tacoma, Washington. Our PHR was architected to a flexible platform that incorporated standards-based models of Continuity of Document and Continuity of Care Record to map Department of Defense-sourced health data, via a secure Veterans Administration data broker, to Microsoft® HealthVault and Google® Health based on user preference. The project design and implementation were guided by provider and patient advisory panels with formal user evaluation. Results The pilot project included 250 beneficiary users. Approximately 73.2% of users were <65 years of age, and 38.4% were female. Of the users, 169 (67.6%) selected Microsoft® HealthVault, and 81 (32.4%) selected Google® Health as their PHR of preference. Sample evaluation of users reflected 100% (n=60) satisfied with convenience of record access and 91.7% (n=55) satisfied with overall functionality of PHR. Discussion Key lessons learned related to data-transfer decisions (push vs pull), purposeful delays in reporting sensitive information, understanding and mapping PHR use and clinical workflow, and decisions on information patients may choose to share with their provider. Conclusion Currently PHRs are being viewed as empowering tools for patient activation. Design and implementation issues (eg, technical, organizational, information security) are substantial and must be thoughtfully approached. Adopting standards into design can enhance the national goal of portability and interoperability. PMID:21292705

Social anxiety apps: a systematic review and assessment of app descriptors across mobile store platforms.

PubMed

Alyami, Mohsen; Giri, Bachan; Alyami, Hussain; Sundram, Frederick

2017-08-01

The aim of this systematic review is twofold: (1) to characterise the purpose and description of available social anxiety apps and (2) to review the evidence on the effectiveness of social anxiety apps. A search was conducted on three major mobile platforms: Apple iTunes, Google Play and Windows Store. Apps were included if they addressed social anxiety and used an English language interface. A systematic review of the literature from MEDLINE, EMBASE, PsycINFO, Cochrane, Scopus and Web of Science to identify evidence-based evaluations of social anxiety apps was also undertaken. Of the 1154 apps identified, 38 apps met the inclusion criteria: iTunes (n=18), Google Play (n=16) and Windows Store (n=4). Over 60% of apps were exclusively focused on social anxiety, while the remainder targeted social anxiety and related conditions. Most developers did not provide information on their organisational affiliations or their content source. Most apps used multimedia while 17 apps used text only. Finally, although the systematic review of the literature identified 94 articles, none of which met inclusion criteria. Social anxiety apps have the potential to overcome barriers to accessing treatment; however, none of the apps identified have had studies on their effectiveness published. As the evidence base is lacking, it is therefore not currently possible to recommend their use. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

A cross-sectional content analysis of Android applications for asthma.

PubMed

Househ, Mowafa; Hossain, Nassif; Jamal, Amr; Zakaria, Nasriah; Elmetwally, Ashraf; Alsalamah, Majid; Khalifa, Mohamed

2017-06-01

Providing patients opportunities for self-management and education about their disease, asthma applications designed for use on an Android operating system can have positive health outcomes across the range of demographics who use mHealth applications. This study provides a content analysis of freely available Google Android Platform Mobile Applications for Asthma. A list of applications was collected on 26 October 2014, using the search feature of the Google Play Android platform and using the words and phrases "Asthma," "Lung Function" and "Peak Flow." Each application was coded for its approach to asthma self-management, based on categories adapted by Huckvale et al., which are based on the Global Initiative for Asthma and the National Asthma Education and Prevention Program. The characteristics of the 15 asthma applications are described. Most of the asthma applications' primary function focused on patient self-monitoring and self-assessment. Using the HON Code, we found low health information quality across all asthma applications. Android asthma applications can have positive outcomes in helping patients as they provide opportunities for self-management and education about their disease. Future research should continue to monitor and evaluate the development and use of mHealth Asthma Applications. Based on these findings, and their indication of a gap in existing research, subsequent studies can continue to evaluate the development and use of mHealth Asthma Applications with increasing methodological consistency to improve the quality of in-app health information.

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.

TERSSE: Definition of the Total Earth Resources System for the Shuttle Era. Volume 4: The Role of the Shuttle in the Earth Resources Program

NASA Technical Reports Server (NTRS)

1974-01-01

The potential of the space shuttle as a platform for captive earth resources payloads in the sortie mode, and as a launch and services vehicle for automated earth resources spacecraft is examined. The capabilities of the total space transportation system which are pertinent to earth resources sorties and automated spacecraft are included.

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.

Role of light satellites in the high-resolution Earth observation domain

NASA Astrophysics Data System (ADS)

Fishman, Moshe

1999-12-01

Current 'classic' applications using and exploring space based earth imagery are exclusive, narrow niche tailored, expensive and hardly accessible. On the other side new, inexpensive and widely used 'consumable' applications will be only developed concurrently to the availability of appropriate imagery allowing that process. A part of these applications can be imagined today, like WWW based 'virtual tourism' or news media, but the history of technological, cultural and entertainment evolution teaches us that most of future applications are unpredictable -- they emerge together with the platforms enabling their appearance. The only thing, which can be ultimately stated, is that the definitive condition for such applications is the availability of the proper imagery platform providing low cost, high resolution, large area, quick response, simple accessibility and quick dissemination of the raw picture. This platform is a constellation of Earth Observation satellites. Up to 1995 the Space Based High Resolution Earth Observation Domain was dominated by heavy, super-expensive and very inflexible birds. The launch of Israeli OFEQ-3 Satellite by MBT Division of Israel Aircraft Industries (IAI) marked the entrance to new era of light, smart and cheap Low Earth Orbited Imaging satellites. The Earth Resource Observation System (EROS) initiated by West Indian Space, is based on OFEQ class Satellites design and it is capable to gather visual data of Earth Surface both at high resolution and large image capacity. The main attributes, derived from its compact design, low weight and sophisticated logic and which convert the EROS Satellite to valuable and productive system, are discussed. The major advantages of Light Satellites in High Resolution Earth Observation Domain are presented and WIS guidelines featuring the next generation of LEO Imaging Systems are included.

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…

GenomicTools: a computational platform for developing high-throughput analytics in genomics.

PubMed

Tsirigos, Aristotelis; Haiminen, Niina; Bilal, Erhan; Utro, Filippo

2012-01-15

Recent advances in sequencing technology have resulted in the dramatic increase of sequencing data, which, in turn, requires efficient management of computational resources, such as computing time, memory requirements as well as prototyping of computational pipelines. We present GenomicTools, a flexible computational platform, comprising both a command-line set of tools and a C++ API, for the analysis and manipulation of high-throughput sequencing data such as DNA-seq, RNA-seq, ChIP-seq and MethylC-seq. GenomicTools implements a variety of mathematical operations between sets of genomic regions thereby enabling the prototyping of computational pipelines that can address a wide spectrum of tasks ranging from pre-processing and quality control to meta-analyses. Additionally, the GenomicTools platform is designed to analyze large datasets of any size by minimizing memory requirements. In practical applications, where comparable, GenomicTools outperforms existing tools in terms of both time and memory usage. The GenomicTools platform (version 2.0.0) was implemented in C++. The source code, documentation, user manual, example datasets and scripts are available online at http://code.google.com/p/ibm-cbc-genomic-tools.

ArXives of Earth science

NASA Astrophysics Data System (ADS)

2018-03-01

Preprint servers afford a platform for sharing research before peer review. We are pleased that two dedicated preprint servers have opened for the Earth sciences and welcome submissions that have been posted there first.

Mapping of traditional settlements by unmanned airborne vehicles towards architectural restoration

NASA Astrophysics Data System (ADS)

Partsinevelos, Panagiotis; Skoutelis, Nikolaos; Tripolitsiotis, Achilleas; Tsatsarounos, Stelios; Tsitonaki, Anna; Zervos, Panagiotis

2015-06-01

Conservation and restoration of traditional settlements are amongst the actions that international directives proclaim in order to protect our cultural heritage. Towards this end, a mandatory base step in all archaeological and historical practices includes the surveying and mapping of the study area. Often, new, unexplored or abandoned settlements are considered, where dense vegetation, damaged structures and ruins, incorporation of newer structures and renovation characteristics make the precise surveying procedure a labor intensive and time consuming procedure. Unmanned airborne vehicles (UAVs) have been effectively incorporated into several cultural heritage projects mainly for mapping archeological sites. However, the majority of relevant publications lack of quantitative evaluation of their results and when such a validation is provided it is rather a procedural error estimation readily available from the software used, without independent ground truth verification. In this study, a low-cost custom-built hexacopter prototype was employed to deliver accurate mapping of the traditional settlement of Kamariotis in east Crete, Greece. The case of Kamariotis settlement included highly dense urban structures with continuous building forms, curved walls and missing terraces, while wild vegetation made classic geodetic surveying unfeasible. The resulting maps were qualitatively compared against the ones derived using Google Earth and the Greek Cadastral Orthophoto Viewing platforms to evaluate their applicability for architectural mapping. Moreover, the overall precision of the photogrammetric procedure was compared against geodetic surveying.

Integrated thermal infrared imaging and Structure-from-Motion photogrametry to map apparent temperature and radiant hydrothermal heat flux at Mammoth Mountain, CA USA

USGS Publications Warehouse

Lewis, Aaron; George Hilley,; Lewicki, Jennifer L.

2015-01-01

This work presents a method to create high-resolution (cm-scale) orthorectified and georeferenced maps of apparent surface temperature and radiant hydrothermal heat flux and estimate the radiant hydrothermal heat emission rate from a study area. A ground-based thermal infrared (TIR) camera was used to collect (1) a set of overlapping and offset visible imagery around the study area during the daytime and (2) time series of co-located visible and TIR imagery at one or more sites within the study area from pre-dawn to daytime. Daytime visible imagery was processed using the Structure-from-Motion photogrammetric method to create a digital elevation model onto which pre-dawn TIR imagery was orthorectified and georeferenced. Three-dimensional maps of apparent surface temperature and radiant hydrothermal heat flux were then visualized and analyzed from various computer platforms (e.g., Google Earth, ArcGIS). We demonstrate this method at the Mammoth Mountain fumarole area on Mammoth Mountain, CA. Time-averaged apparent surface temperatures and radiant hydrothermal heat fluxes were observed up to 73.7 oC and 450 W m-2, respectively, while the estimated radiant hydrothermal heat emission rate from the area was 1.54 kW. Results should provide a basis for monitoring potential volcanic unrest and mitigating hydrothermal heat-related hazards on the volcano.

Conversion of the agent-oriented domain-specific language ALAS into JavaScript

NASA Astrophysics Data System (ADS)

Sredojević, Dejan; Vidaković, Milan; Okanović, Dušan; Mitrović, Dejan; Ivanović, Mirjana

2016-06-01

This paper shows generation of JavaScript code from code written in agent-oriented domain-specific language ALAS. ALAS is an agent-oriented domain-specific language for writing software agents that are executed within XJAF middleware. Since the agents can be executed on various platforms, they must be converted into a language of the target platform. We also try to utilize existing tools and technologies to make the whole conversion process as simple as possible, as well as faster and more efficient. We use the Xtext framework that is compatible with Java to implement ALAS infrastructure - editor and code generator. Since Xtext supports Java, generation of Java code from ALAS code is straightforward. To generate a JavaScript code that will be executed within the target JavaScript XJAF implementation, Google Web Toolkit (GWT) is used.

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).

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.

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)

Nominal 30-M Cropland Extent Map of Continental Africa by Integrating Pixel-Based and Object-Based Algorithms Using Sentinel-2 and Landsat-8 Data on Google Earth Engine

NASA Technical Reports Server (NTRS)

Xiong, Jun; Thenkabail, Prasad S.; Tilton, James C.; Gumma, Murali K.; Teluguntla, Pardhasaradhi; Oliphant, Adam; Congalton, Russell G.; Yadav, Kamini; Gorelick, Noel

2017-01-01

A satellite-derived cropland extent map at high spatial resolution (30-m or better) is a must for food and water security analysis. Precise and accurate global cropland extent maps, indicating cropland and non-cropland areas, is a starting point to develop high-level products such as crop watering methods (irrigated or rainfed), cropping intensities (e.g., single, double, or continuous cropping), crop types, cropland fallows, as well as assessment of cropland productivity (productivity per unit of land), and crop water productivity (productivity per unit of water). Uncertainties associated with the cropland extent map have cascading effects on all higher-level cropland products. However, precise and accurate cropland extent maps at high spatial resolution over large areas (e.g., continents or the globe) are challenging to produce due to the small-holder dominant agricultural systems like those found in most of Africa and Asia. Cloud-based Geospatial computing platforms and multi-date, multi-sensor satellite image inventories on Google Earth Engine offer opportunities for mapping croplands with precision and accuracy over large areas that satisfy the requirements of broad range of applications. Such maps are expected to provide highly significant improvements compared to existing products, which tend to be coarser in resolution, and often fail to capture fragmented small-holder farms especially in regions with high dynamic change within and across years. To overcome these limitations, in this research we present an approach for cropland extent mapping at high spatial resolution (30-m or better) using the 10-day, 10 to 20-m, Sentinel-2 data in combination with 16-day, 30-m, Landsat-8 data on Google Earth Engine (GEE). First, nominal 30-m resolution satellite imagery composites were created from 36,924 scenes of Sentinel-2 and Landsat-8 images for the entire African continent in 2015-2016. These composites were generated using a median-mosaic of five bands (blue, green, red, near-infrared, NDVI) during each of the two periods (period 1: January-June 2016 and period 2: July-December 2015) plus a 30-m slope layer derived from the Shuttle Radar Topographic Mission (SRTM) elevation dataset. Second, we selected Cropland/Non-cropland training samples (sample size 9791) from various sources in GEE to create pixel-based classifications. As supervised classification algorithm, Random Forest (RF) was used as the primary classifier because of its efficiency, and when over-fitting issues of RF happened due to the noise of input training data, Support Vector Machine (SVM) was applied to compensate for such defects in specific areas. Third, the Recursive Hierarchical Segmentation (RHSeg) algorithm was employed to generate an object-oriented segmentation layer based on spectral and spatial properties from the same input data. This layer was merged with the pixel-based classification to improve segmentation accuracy. Accuracies of the merged 30-m crop extent product were computed using an error matrix approach in which 1754 independent validation samples were used. In addition, a comparison was performed with other available cropland maps as well as with LULC maps to show spatial similarity. Finally, the cropland area results derived from the map were compared with UN FAO statistics. The independent accuracy assessment showed a weighted overall accuracy of 94, with a producers accuracy of 85.9 (or omission error of 14.1), and users accuracy of 68.5 (commission error of 31.5) for the cropland class. The total net cropland area (TNCA) of Africa was estimated as 313 Mha for the nominal year 2015.

An automated and integrated framework for dust storm detection based on ogc web processing services

NASA Astrophysics Data System (ADS)

Xiao, F.; Shea, G. Y. K.; Wong, M. S.; Campbell, J.

2014-11-01

Dust storms are known to have adverse effects on public health. Atmospheric dust loading is also one of the major uncertainties in global climatic modelling as it is known to have a significant impact on the radiation budget and atmospheric stability. The complexity of building scientific dust storm models is coupled with the scientific computation advancement, ongoing computing platform development, and the development of heterogeneous Earth Observation (EO) networks. It is a challenging task to develop an integrated and automated scheme for dust storm detection that combines Geo-Processing frameworks, scientific models and EO data together to enable the dust storm detection and tracking processes in a dynamic and timely manner. This study develops an automated and integrated framework for dust storm detection and tracking based on the Web Processing Services (WPS) initiated by Open Geospatial Consortium (OGC). The presented WPS framework consists of EO data retrieval components, dust storm detecting and tracking component, and service chain orchestration engine. The EO data processing component is implemented based on OPeNDAP standard. The dust storm detecting and tracking component combines three earth scientific models, which are SBDART model (for computing aerosol optical depth (AOT) of dust particles), WRF model (for simulating meteorological parameters) and HYSPLIT model (for simulating the dust storm transport processes). The service chain orchestration engine is implemented based on Business Process Execution Language for Web Service (BPEL4WS) using open-source software. The output results, including horizontal and vertical AOT distribution of dust particles as well as their transport paths, were represented using KML/XML and displayed in Google Earth. A serious dust storm, which occurred over East Asia from 26 to 28 Apr 2012, is used to test the applicability of the proposed WPS framework. Our aim here is to solve a specific instance of a complex EO data and scientific model integration problem by using a framework and scientific workflow approach together. The experimental result shows that this newly automated and integrated framework can be used to give advance near real-time warning of dust storms, for both environmental authorities and public. The methods presented in this paper might be also generalized to other types of Earth system models, leading to improved ease of use and flexibility.

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.

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.

"Where On Mars?": An Open Planetary Mapping Platform for Researchers, Educators, and the General Public

NASA Astrophysics Data System (ADS)

Manaud, Nicolas; Carter, John; Boix, Oriol

2016-10-01

The "Where On Mars?" project is essentially the evolution of an existing outreach product developed in collaboration between ESA and CartoDB; an interactive map visualisation of the ESA's ExoMars Rover candidate landing sites (whereonmars.co). Planetary imagery data and maps are increasingly produced by the scientific community, and shared typically as images, in scientific publications, presentations or public outreach websites. However, this media lacks of interactivity and contextual information available for further exploration, making it difficult for any audience to relate one location-based information to another. We believe that interactive web maps are a powerful way of telling stories, engaging with and educating people who, over the last decade, have become familiar with tools such as Google Maps. A few planetary web maps exist but they are either too complex for non-experts, or are closed-systems that do not allows anyone to publish and share content. The long-term vision for the project is to provide researchers, communicators, educators and a worldwide public with an open planetary mapping and social platform enabling them to create, share, communicate and consume research-based content. We aim for this platform to become the reference website everyone will go to learn about Mars and other planets in our Solar System; just like people head to Google Maps to find their bearings or any location-based information. The driver is clearly to create for people an emotional connection with Mars. The short-term objectives for the project are (1) to produce and curate an open repository of basemaps, geospatial data sets, map visualisations, and story maps; (2) to develop a beautifully crafted and engaging interactive map of Mars. Based on user-generated content, the underlying framework should (3) make it easy to create and share additional interactive maps telling specific stories.

Use of Social Media in Facilitating Health Care Research Among Nursing and Allied Health Undergraduates in Sri Lanka.

PubMed

Silva, S N

2016-01-01

A mentoring program was designed to promote conduction, completion and dissemination of undergraduate research among Nursing and Allied Health students in Sri Lanka. Several social media platforms were used; mainly the Facebook, YouTube and Google Hangouts. Knowledge sharing, interaction and collaboration were promoted. Student motivation was also done. Research presentation skills and applying for conferences was also facilitated. Over 90% of the participated 262 students completed a research project and close to 50% presented them both locally and internationally.

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.

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.

Collaborative Supercomputing for Global Change Science

NASA Astrophysics Data System (ADS)

Nemani, R.; Votava, P.; Michaelis, A.; Melton, F.; Milesi, C.

2011-03-01

There is increasing pressure on the science community not only to understand how recent and projected changes in climate will affect Earth's global environment and the natural resources on which society depends but also to design solutions to mitigate or cope with the likely impacts. Responding to this multidimensional challenge requires new tools and research frameworks that assist scientists in collaborating to rapidly investigate complex interdisciplinary science questions of critical societal importance. One such collaborative research framework, within the NASA Earth sciences program, is the NASA Earth Exchange (NEX). NEX combines state-of-the-art supercomputing, Earth system modeling, remote sensing data from NASA and other agencies, and a scientific social networking platform to deliver a complete work environment. In this platform, users can explore and analyze large Earth science data sets, run modeling codes, collaborate on new or existing projects, and share results within or among communities (see Figure S1 in the online supplement to this Eos issue (http://www.agu.org/eos_elec)).