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.

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…

Multi-source Geospatial Data Analysis with Google Earth Engine

NASA Astrophysics Data System (ADS)

Erickson, T.

2014-12-01

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

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…

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.

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…

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.

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.

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.

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

NASA Astrophysics Data System (ADS)

Erickson, T.

2016-12-01

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

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.

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

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

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

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.

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

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

PubMed

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

2010-06-01

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

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

ERIC Educational Resources Information Center

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

2012-01-01

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

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…

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.

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.

[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.

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

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

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.

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

NASA Astrophysics Data System (ADS)

Hancher, M.

2013-12-01

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

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…

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.

Automatic Building Detection based on Supervised Classification using High Resolution Google Earth Images

NASA Astrophysics Data System (ADS)

Ghaffarian, S.; Ghaffarian, S.

2014-08-01

This paper presents a novel approach to detect the buildings by automization of the training area collecting stage for supervised classification. The method based on the fact that a 3d building structure should cast a shadow under suitable imaging conditions. Therefore, the methodology begins with the detection and masking out the shadow areas using luminance component of the LAB color space, which indicates the lightness of the image, and a novel double thresholding technique. Further, the training areas for supervised classification are selected by automatically determining a buffer zone on each building whose shadow is detected by using the shadow shape and the sun illumination direction. Thereafter, by calculating the statistic values of each buffer zone which is collected from the building areas the Improved Parallelepiped Supervised Classification is executed to detect the buildings. Standard deviation thresholding applied to the Parallelepiped classification method to improve its accuracy. Finally, simple morphological operations conducted for releasing the noises and increasing the accuracy of the results. The experiments were performed on set of high resolution Google Earth images. The performance of the proposed approach was assessed by comparing the results of the proposed approach with the reference data by using well-known quality measurements (Precision, Recall and F1-score) to evaluate the pixel-based and object-based performances of the proposed approach. Evaluation of the results illustrates that buildings detected from dense and suburban districts with divers characteristics and color combinations using our proposed method have 88.4 % and 853 % overall pixel-based and object-based precision performances, respectively.

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

NASA Astrophysics Data System (ADS)

Nurik, R.; Marks, M.

2009-12-01

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

The Chandra Source Catalog : Google Earth Interface

NASA Astrophysics Data System (ADS)

Glotfelty, Kenny; McLaughlin, W.; Evans, I.; Evans, J.; Anderson, C. S.; Bonaventura, N. R.; Davis, J. E.; Doe, S. M.; Fabbiano, G.; Galle, E. C.; Gibbs, D. G., II; Grier, J. D.; Hain, R.; Hall, D. M.; Harbo, P. N.; He, H.; Houck, J. C.; Karovska, M.; Kashyap, V. L.; Lauer, J.; McCollough, M. L.; McDowell, J. C.; Miller, J. B.; Mitschang, A. W.; Morgan, D. L.; Mossman, A. E.; Nichols, J. S.; Nowak, M. A.; Plummer, D. A.; Primini, F. A.; Refsdal, B. L.; Rots, A. R.; Siemiginowska, A. L.; Sundheim, B. A.; Tibbetts, M. S.; van Stone, D. W.; Winkelman, S. L.; Zografou, P.

2009-09-01

The Chandra Source Catalog (CSC) contains multi-resolution, exposure corrected, background subtracted, full-field images that are stored as individual FITS files and as three-color JPEG files. In this poster we discuss how we took these data and were able to, with relatively minimal effort, convert them for use with the Google Earth application in its ``Sky'' mode. We will highlight some of the challenges which include converting the data to the required Mercator projection, reworking the 3-color algorithm for pipeline processing, and ways to reduce the data volume through re-binning, using color-maps, and special Keyhole Markup Language (kml) tags to only load images on-demand. The result is a collection of some 11,000 3-color images that are available for all the individual observation in the CSC Release 1. We also have made available all ˜4000 Field-of-View outlines (with per-chip regions), which turns out are trivial to produce starting with a simple dmlist command. In the first week of release, approximately 40% of the images have been accessed at least once through some 50,000 individual web hits which have served over 4Gb of data to roughly 750 users in 60+ countries. We will also highlight some future directions we are exploring, including real-time catalog access to individual source properties and eventual access to file based products such as FITS images, spectra, and light-curves.

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

Google Mercury: The Launch of a New Planet

NASA Astrophysics Data System (ADS)

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

2010-12-01

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

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…

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"

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)

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.

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…

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

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.

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…

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

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.

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

NASA Astrophysics Data System (ADS)

Zetterlind, V.; Pledgie, S.

2009-12-01

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

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

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)

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

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.

Object recognition based on Google's reverse image search and image similarity

NASA Astrophysics Data System (ADS)

Horváth, András.

2015-12-01

Image classification is one of the most challenging tasks in computer vision and a general multiclass classifier could solve many different tasks in image processing. Classification is usually done by shallow learning for predefined objects, which is a difficult task and very different from human vision, which is based on continuous learning of object classes and one requires years to learn a large taxonomy of objects which are not disjunct nor independent. In this paper I present a system based on Google image similarity algorithm and Google image database, which can classify a large set of different objects in a human like manner, identifying related classes and taxonomies.

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

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

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 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.

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)

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

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

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.

Traffic Sign Inventory from Google Street View Images

NASA Astrophysics Data System (ADS)

Tsai, Victor J. D.; Chen, Jyun-Han; Huang, Hsun-Sheng

2016-06-01

Traffic sign detection and recognition (TSDR) has drawn considerable attention on developing intelligent transportation systems (ITS) and autonomous vehicle driving systems (AVDS) since 1980's. Unlikely to the general TSDR systems that deal with real-time images captured by the in-vehicle cameras, this research aims on developing techniques for detecting, extracting, and positioning of traffic signs from Google Street View (GSV) images along user-selected routes for low-cost, volumetric and quick establishment of the traffic sign infrastructural database that may be associated with Google Maps. The framework and techniques employed in the proposed system are described.

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

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.

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.

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.

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…

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 .

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 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)

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.…

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

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)

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)

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

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

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.

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.

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).

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…

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).

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.

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.

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.

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

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).

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…

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).

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

Using Google Earth To Interpret The Southern Taiwan Hsiaolin Village Catastrophe

NASA Astrophysics Data System (ADS)

Lin, Y. H.; Huang, C. M.; Keck, J.; Wei, L. W.; Pan, K. L.

2012-04-01

The August, 2009 Typhoon Morakot resulted in accumulated rainfalls exceeding 2000 mm and the triggering of a massive debris flow that buried Hsiaolin village. Hundreds of people were killed and both domestic and international natural disaster prevention agencies took note of this large scale disaster that was not prevented. Interpretation of Google Earth satellite images reveals that the Hsiaolin debris flow originated in a single location and then split into two parts. The northern debris flow, the smaller of the two parts, flowed within a ravine. The southern part of the debris flow, much larger than the northern part, was responsible for the burial of Hsiaolin village. The movement of the debris flow can be divided into three processes. First a slope failure and subsequent debris flow occurred within a curved ravine. Second, the debris flow eroded the bank of the ravine laterally, causing translational failure of the ravine walls. A massive debris flow, made up of a combination of materials from both the original debris flow and the ravine walls, jammed within the ravine. Finally, as a result of the jam, the debris flow was redirected towards Hsiaolin village. Overlaying locations of the post-Hsiaolin debris flow landforms on top of pre-failure satellite images reveals that characteristics of the post failure landforms match perfectly with characteristics observed in the pre-failure satellite images. This finding supports the thought that large scale geologic disasters are reoccurring. This finding also suggests that areas near villages can use simple satellite image analysis to rapidly identify ancient landslides and that such information may help early evacuation planning. With such planning, property and life losses due to natural disasters can be reduced. Key word: Hsiaolin Village, Debris Flow, Remote Sensing, Image Interpretation, Cause of Disaster, Disaster Recovery, Deep-Seated Landslide, Ancient Debris Flow

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…

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

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…

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

Facilitating medical information search using Google Glass connected to a content-based medical image retrieval system.

PubMed

Widmer, Antoine; Schaer, Roger; Markonis, Dimitrios; Muller, Henning

2014-01-01

Wearable computing devices are starting to change the way users interact with computers and the Internet. Among them, Google Glass includes a small screen located in front of the right eye, a camera filming in front of the user and a small computing unit. Google Glass has the advantage to provide online services while allowing the user to perform tasks with his/her hands. These augmented glasses uncover many useful applications, also in the medical domain. For example, Google Glass can easily provide video conference between medical doctors to discuss a live case. Using these glasses can also facilitate medical information search by allowing the access of a large amount of annotated medical cases during a consultation in a non-disruptive fashion for medical staff. In this paper, we developed a Google Glass application able to take a photo and send it to a medical image retrieval system along with keywords in order to retrieve similar cases. As a preliminary assessment of the usability of the application, we tested the application under three conditions (images of the skin; printed CT scans and MRI images; and CT and MRI images acquired directly from an LCD screen) to explore whether using Google Glass affects the accuracy of the results returned by the medical image retrieval system. The preliminary results show that despite minor problems due to the relative stability of the Google Glass, images can be sent to and processed by the medical image retrieval system and similar images are returned to the user, potentially helping in the decision making process.

Monitoring of coalbed water retention ponds in the Powder River Basin using Google Earth images and an Unmanned Aircraft System

NASA Astrophysics Data System (ADS)

Zhou, X.; Zhou, Z.; Apple, M. E.; Spangler, L.

2016-12-01

To extract methane from unminable seams of coal in the Powder River Basin of Montana and Wyoming, coalbed methane (CBM) water has to be pumped and kept in retention ponds rather than discharged to the vadose zone to mix with the ground water. The water areal coverage of these ponds changes due to evaporation and repetitive refilling. The water quality also changes due to growing of microalgae (unicellular or filamentous including green algae and diatoms), evaporation, and refilling. To estimate the water coverage changes and monitor water quality becomes important for monitoring the CBM water retention ponds to provide timely management plan for the newly pumped CBM water. Conventional methods such as various water indices based on multi-spectral satellite data such as Landsat because of the small pond size ( 100mx100m scale) and low spatial resolution ( 30m scale) of the satellite data. In this study we will present new methods to estimate water coverage and water quality changes using Google Earth images and images collected from an unmanned aircraft system (UAS) (Phantom 2 plus). Because these images have only visible bands (red, green, and blue bands), the conventional water index methods that involve near-infrared bands do not work. We design a new method just based on the visible bands to automatically extract water pixels and the intensity of the water pixel as a proxy for water quality after a series of image processing such as georeferencing, resampling, filtering, etc. Differential GPS positions along the water edges were collected the same day as the images collected from the UAS. Area of the water area was calculated from the GPS positions and used for the validation of the method. Because of the very high resolution ( 10-30 cm scale), the water areal coverage and water quality distribution can be accurately estimated. Since the UAS can be flied any time, water area and quality information can be collected timely.

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

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.

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.

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

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

NASA Astrophysics Data System (ADS)

Hancher, M.

2017-12-01

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

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

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…

Harnessing Satellite Imageries in Feature Extraction Using Google Earth Pro

NASA Astrophysics Data System (ADS)

Fernandez, Sim Joseph; Milano, Alan

2016-07-01

Climate change has been a long-time concern worldwide. Impending flooding, for one, is among its unwanted consequences. The Phil-LiDAR 1 project of the Department of Science and Technology (DOST), Republic of the Philippines, has developed an early warning system in regards to flood hazards. The project utilizes the use of remote sensing technologies in determining the lives in probable dire danger by mapping and attributing building features using LiDAR dataset and satellite imageries. A free mapping software named Google Earth Pro (GEP) is used to load these satellite imageries as base maps. Geotagging of building features has been done so far with the use of handheld Global Positioning System (GPS). Alternatively, mapping and attribution of building features using GEP saves a substantial amount of resources such as manpower, time and budget. Accuracy-wise, geotagging by GEP is dependent on either the satellite imageries or orthophotograph images of half-meter resolution obtained during LiDAR acquisition and not on the GPS of three-meter accuracy. The attributed building features are overlain to the flood hazard map of Phil-LiDAR 1 in order to determine the exposed population. The building features as obtained from satellite imageries may not only be used in flood exposure assessment but may also be used in assessing other hazards and a number of other uses. Several other features may also be extracted from the satellite imageries.

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

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.

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

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)...

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.

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

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

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

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

NASA Astrophysics Data System (ADS)

Triantafyllou, Antoine; Bastin, Christophe; Watlet, Arnaud

2016-04-01

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

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.

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.

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.

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

Automatic Ship Detection in Remote Sensing Images from Google Earth of Complex Scenes Based on Multiscale Rotation Dense Feature Pyramid Networks

NASA Astrophysics Data System (ADS)

Yang, Xue; Sun, Hao; Fu, Kun; Yang, Jirui; Sun, Xian; Yan, Menglong; Guo, Zhi

2018-01-01

Ship detection has been playing a significant role in the field of remote sensing for a long time but it is still full of challenges. The main limitations of traditional ship detection methods usually lie in the complexity of application scenarios, the difficulty of intensive object detection and the redundancy of detection region. In order to solve such problems above, we propose a framework called Rotation Dense Feature Pyramid Networks (R-DFPN) which can effectively detect ship in different scenes including ocean and port. Specifically, we put forward the Dense Feature Pyramid Network (DFPN), which is aimed at solving the problem resulted from the narrow width of the ship. Compared with previous multi-scale detectors such as Feature Pyramid Network (FPN), DFPN builds the high-level semantic feature-maps for all scales by means of dense connections, through which enhances the feature propagation and encourages the feature reuse. Additionally, in the case of ship rotation and dense arrangement, we design a rotation anchor strategy to predict the minimum circumscribed rectangle of the object so as to reduce the redundant detection region and improve the recall. Furthermore, we also propose multi-scale ROI Align for the purpose of maintaining the completeness of semantic and spatial information. Experiments based on remote sensing images from Google Earth for ship detection show that our detection method based on R-DFPN representation has a state-of-the-art performance.

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.

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

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

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…

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.

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

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.

A Google Glass navigation system for ultrasound and fluorescence dual-mode image-guided surgery

NASA Astrophysics Data System (ADS)

Zhang, Zeshu; Pei, Jing; Wang, Dong; Hu, Chuanzhen; Ye, Jian; Gan, Qi; Liu, Peng; Yue, Jian; Wang, Benzhong; Shao, Pengfei; Povoski, Stephen P.; Martin, Edward W.; Yilmaz, Alper; Tweedle, Michael F.; Xu, Ronald X.

2016-03-01

Surgical resection remains the primary curative intervention for cancer treatment. However, the occurrence of a residual tumor after resection is very common, leading to the recurrence of the disease and the need for re-resection. We develop a surgical Google Glass navigation system that combines near infrared fluorescent imaging and ultrasonography for intraoperative detection of sites of tumor and assessment of surgical resection boundaries, well as for guiding sentinel lymph node (SLN) mapping and biopsy. The system consists of a monochromatic CCD camera, a computer, a Google Glass wearable headset, an ultrasonic machine and an array of LED light sources. All the above components, except the Google Glass, are connected to a host computer by a USB or HDMI port. Wireless connection is established between the glass and the host computer for image acquisition and data transport tasks. A control program is written in C++ to call OpenCV functions for image calibration, processing and display. The technical feasibility of the system is tested in both tumor simulating phantoms and in a human subject. When the system is used for simulated phantom resection tasks, the tumor boundaries, invisible to the naked eye, can be clearly visualized with the surgical Google Glass navigation system. This system has also been used in an IRB approved protocol in a single patient during SLN mapping and biopsy in the First Affiliated Hospital of Anhui Medical University, demonstrating the ability to successfully localize and resect all apparent SLNs. In summary, our tumor simulating phantom and human subject studies have demonstrated the technical feasibility of successfully using the proposed goggle navigation system during cancer surgery.

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.

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

Open Availability of Patient Medical Photographs in Google Images Search Results: Cross-Sectional Study of Transgender Research.

PubMed

Marshall, Zack; Brunger, Fern; Welch, Vivian; Asghari, Shabnam; Kaposy, Chris

2018-02-26

This paper focuses on the collision of three factors: a growing emphasis on sharing research through open access publication, an increasing awareness of big data and its potential uses, and an engaged public interested in the privacy and confidentiality of their personal health information. One conceptual space where this collision is brought into sharp relief is with the open availability of patient medical photographs from peer-reviewed journal articles in the search results of online image databases such as Google Images. The aim of this study was to assess the availability of patient medical photographs from published journal articles in Google Images search results and the factors impacting this availability. We conducted a cross-sectional study using data from an evidence map of research with transgender, gender non-binary, and other gender diverse (trans) participants. For the original evidence map, a comprehensive search of 15 academic databases was developed in collaboration with a health sciences librarian. Initial search results produced 25,230 references after duplicates were removed. Eligibility criteria were established to include empirical research of any design that included trans participants or their personal information and that was published in English in peer-reviewed journals. We identified all articles published between 2008 and 2015 with medical photographs of trans participants. For each reference, images were individually numbered in order to track the total number of medical photographs. We used odds ratios (OR) to assess the association between availability of the clinical photograph on Google Images and the following factors: whether the article was openly available online (open access, Researchgate.net, or Academia.edu), whether the article included genital images, if the photographs were published in color, and whether the photographs were located on the journal article landing page. We identified 94 articles with medical photographs

Open Availability of Patient Medical Photographs in Google Images Search Results: Cross-Sectional Study of Transgender Research

PubMed Central

Brunger, Fern; Welch, Vivian; Asghari, Shabnam; Kaposy, Chris

2018-01-01

Background This paper focuses on the collision of three factors: a growing emphasis on sharing research through open access publication, an increasing awareness of big data and its potential uses, and an engaged public interested in the privacy and confidentiality of their personal health information. One conceptual space where this collision is brought into sharp relief is with the open availability of patient medical photographs from peer-reviewed journal articles in the search results of online image databases such as Google Images. Objective The aim of this study was to assess the availability of patient medical photographs from published journal articles in Google Images search results and the factors impacting this availability. Methods We conducted a cross-sectional study using data from an evidence map of research with transgender, gender non-binary, and other gender diverse (trans) participants. For the original evidence map, a comprehensive search of 15 academic databases was developed in collaboration with a health sciences librarian. Initial search results produced 25,230 references after duplicates were removed. Eligibility criteria were established to include empirical research of any design that included trans participants or their personal information and that was published in English in peer-reviewed journals. We identified all articles published between 2008 and 2015 with medical photographs of trans participants. For each reference, images were individually numbered in order to track the total number of medical photographs. We used odds ratios (OR) to assess the association between availability of the clinical photograph on Google Images and the following factors: whether the article was openly available online (open access, Researchgate.net, or Academia.edu), whether the article included genital images, if the photographs were published in color, and whether the photographs were located on the journal article landing page. Results We identified

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.

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

NASA Astrophysics Data System (ADS)

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

2007-12-01

One of the main challenges facing current and future environmental satellite systems (e.g, the future National Polar Orbiting Environmental Satellite System (NPOESS)) is reaching and entraining the diverse user community via communication of how these systems address their particular needs. A necessary element to meeting this challenge is effective data visualization: facilitating the display, animation and layering of multiple satellite imaging and sounding sensors (providing complementary information) in a user-friendly and intuitive fashion. In light of the fact that these data are rapidly making their way into the classroom owing to efficient and timely data archival systems and dissemination over the Internet, there is a golden opportunity to leverage existing technology to introduce environmental science to wide spectrum of users. Google Earth's simplified interface and underlying markup language enables access to detailed global geographic information, and contains features which are both desirable and advantageous for geo-referencing and combining a wide range of environmental satellite data types. Since these satellite data are available with a variety of horizontal spatial resolutions (tens of km down to hundreds of meters), the imagery can be sub-setted (tiled) at a very small size. This allows low-bandwidth users to efficiently view and animate a sequence of imagery while zoomed out from the surface, whereas high-bandwidth users can efficiently zoom into the finest image resolution when viewing fine-scale phenomena such as fires, volcanic activity, as well as the details of meteorological phenomena such as hurricanes, rainfall, lightning, winds, etc. Dynamically updated network links allow for near real-time updates such that these data can be integrated with other Earth-hosted applications and exploited not only in the teaching environment, but also for operational users in the government and private industry sectors. To conceptualize how environmental

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.

Dynamic Flood Vulnerability Mapping with Google Earth Engine

NASA Astrophysics Data System (ADS)

Tellman, B.; Kuhn, C.; Max, S. A.; Sullivan, J.

2015-12-01

Satellites capture the rate and character of environmental change from local to global levels, yet integrating these changes into flood exposure models can be cost or time prohibitive. We explore an approach to global flood modeling by leveraging satellite data with computing power in Google Earth Engine to dynamically map flood hazards. Our research harnesses satellite imagery in two main ways: first to generate a globally consistent flood inundation layer and second to dynamically model flood vulnerability. Accurate and relevant hazard maps rely on high quality observation data. Advances in publicly available spatial, spectral, and radar data together with cloud computing allow us to improve existing efforts to develop a comprehensive flood extent database to support model training and calibration. This talk will demonstrate the classification results of algorithms developed in Earth Engine designed to detect flood events by combining observations from MODIS, Landsat 8, and Sentinel-1. Our method to derive flood footprints increases the number, resolution, and precision of spatial observations for flood events both in the US, recorded in the NCDC (National Climatic Data Center) storm events database, and globally, as recorded events from the Colorado Flood Observatory database. This improved dataset can then be used to train machine learning models that relate spatial temporal flood observations to satellite derived spatial temporal predictor variables such as precipitation, antecedent soil moisture, and impervious surface. This modeling approach allows us to rapidly update models with each new flood observation, providing near real time vulnerability maps. We will share the water detection algorithms used with each satellite and discuss flood detection results with examples from Bihar, India and the state of New York. We will also demonstrate how these flood observations are used to train machine learning models and estimate flood exposure. The final stage of

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

NASA Astrophysics Data System (ADS)

Thau, D.

2017-12-01

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

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

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.

Calibration Image of Earth by Mars Color Imager

NASA Technical Reports Server (NTRS)

2005-01-01

Three days after the Mars Reconnaissance Orbiter's Aug. 12, 2005, launch, the NASA spacecraft was pointed toward Earth and the Mars Color Imager camera was powered up to acquire a suite of color and ultraviolet images of Earth and the Moon. When it gets to Mars, the Mars Color Imager's main objective will be to obtain daily global color and ultraviolet images of the planet to observe martian meteorology by documenting the occurrence of dust storms, clouds, and ozone. This camera will also observe how the martian surface changes over time, including changes in frost patterns and surface brightness caused by dust storms and dust devils.

The purpose of acquiring an image of Earth and the Moon just three days after launch was to help the Mars Color Imager science team obtain a measure, in space, of the instrument's sensitivity, as well as to check that no contamination occurred on the camera during launch. Prior to launch, the team determined that, three days out from Earth, the planet would only be about 4.77 pixels across, and the Moon would be less than one pixel in size, as seen from the Mars Color Imager's wide-angle perspective. If the team waited any longer than three days to test the camera's performance in space, Earth would be too small to obtain meaningful results.

The images were acquired by turning Mars Reconnaissance Orbiter toward Earth, then slewing the spacecraft so that the Earth and Moon would pass before each of the five color and two ultraviolet filters of the Mars Color Imager. The distance to Earth was about 1,170,000 kilometers (about 727,000 miles).

This image shows a color composite view of Mars Color Imager's image of Earth. As expected, it covers only five pixels. This color view has been enlarged five times. The Sun was illuminating our planet from the left, thus only one quarter of Earth is seen from this perspective. North America was in daylight and facing toward the camera at the time the picture was taken; the data

On the use of wavelet for extracting feature patterns from Multitemporal google earth satellite data sets

NASA Astrophysics Data System (ADS)

Lasaponara, R.

2012-04-01

The great amount of multispectral VHR satellite images, even available free of charge in Google earth has opened new strategic challenges in the field of remote sensing for archaeological studies. These challenges substantially deal with: (i) the strategic exploitation of satellite data as much as possible, (ii) the setting up of effective and reliable automatic and/or semiautomatic data processing strategies and (iii) the integration with other data sources from documentary resources to the traditional ground survey, historical documentation, geophysical prospection, etc. VHR satellites provide high resolution data which can improve knowledge on past human activities providing precious qualitative and quantitative information developed to such an extent that currently they share many of the physical characteristics of aerial imagery. This makes them ideal for investigations ranging from a local to a regional scale (see. for example, Lasaponara and Masini 2006a,b, 2007a, 2011; Masini and Lasaponara 2006, 2007, Sparavigna, 2010). Moreover, satellite data are still the only data source for research performed in areas where aerial photography is restricted because of military or political reasons. Among the main advantages of using satellite remote sensing compared to traditional field archaeology herein we briefly focalize on the use of wavelet data processing for enhancing google earth satellite data with particular reference to multitemporal datasets. Study areas selected from Southern Italy, Middle East and South America are presented and discussed. Results obtained point out the use of automatic image enhancement can successfully applied as first step of supervised classification and intelligent data analysis for semiautomatic identification of features of archaeological interest. Reference Lasaponara R, Masini N (2006a) On the potential of panchromatic and multispectral Quickbird data for archaeological prospection. Int J Remote Sens 27: 3607-3614. Lasaponara R

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.

Clementine Images of Earth and Moon

NASA Technical Reports Server (NTRS)

1997-01-01

During its flight and lunar orbit, the Clementine spacecraft returned images of the planet Earth and the Moon. This collection of UVVIS camera Clementine images shows the Earth from the Moon and 3 images of the Earth.

The image on the left shows the Earth as seen across the lunar north pole; the large crater in the foreground is Plaskett. The Earth actually appeared about twice as far above the lunar horizon as shown. The top right image shows the Earth as viewed by the UVVIS camera while Clementine was in transit to the Moon; swirling white cloud patterns indicate storms. The two views of southeastern Africa were acquired by the UVVIS camera while Clementine was in low Earth orbit early in the mission

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.

Clementine Images of Earth and Moon

NASA Image and Video Library

1999-06-12

During its flight and lunar orbit, NASA’s Clementine spacecraft returned images of the planet Earth and the Moon. This collection of UVVIS camera Clementine images shows the Earth from the Moon and 3 images of the Earth. The image on the left shows the Earth as seen across the lunar north pole; the large crater in the foreground is Plaskett. The Earth actually appeared about twice as far above the lunar horizon as shown. The top right image shows the Earth as viewed by the UVVIS camera while Clementine was in transit to the Moon; swirling white cloud patterns indicate storms. The two views of southeastern Africa were acquired by the UVVIS camera while Clementine was in low Earth orbit early in the mission. http://photojournal.jpl.nasa.gov/catalog/PIA00432

Google Book Search: The Good, the Bad, & the Ugly

ERIC Educational Resources Information Center

Schaffhauser, Dian

2008-01-01

Google is opening up whole new worlds for internet surfers and researchers everywhere. Google Book Search (books.google.com), which is still in beta after several years of testing, offers the ubiquitous Google search box on its home page. It also has categories of books as well as book cover images that refresh every time the home page is…

Visualizing Glaciers and Sea Ice via Google Earth

NASA Astrophysics Data System (ADS)

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

2006-12-01

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

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

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

NASA Image and Video Library

2013-12-19

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

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

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

NASA Captures 'EPIC' Earth Image

NASA Image and Video Library

2017-12-08

A NASA camera on the Deep Space Climate Observatory satellite has returned its first view of the entire sunlit side of Earth from one million miles away. This color image of Earth was taken by NASA’s Earth Polychromatic Imaging Camera (EPIC), a four megapixel CCD camera and telescope. The image was generated by combining three separate images to create a photographic-quality image. The camera takes a series of 10 images using different narrowband filters -- from ultraviolet to near infrared -- to produce a variety of science products. The red, green and blue channel images are used in these color images. The image was taken July 6, 2015, showing North and Central America. The central turquoise areas are shallow seas around the Caribbean islands. This Earth image shows the effects of sunlight scattered by air molecules, giving the image a characteristic bluish tint. The EPIC team is working to remove this atmospheric effect from subsequent images. Once the instrument begins regular data acquisition, EPIC will provide a daily series of Earth images allowing for the first time study of daily variations over the entire globe. These images, available 12 to 36 hours after they are acquired, will be posted to a dedicated web page by September 2015. The primary objective of DSCOVR, a partnership between NASA, the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Air Force, is to maintain the nation’s real-time solar wind monitoring capabilities, which are critical to the accuracy and lead time of space weather alerts and forecasts from NOAA. For more information about DSCOVR, visit: www.nesdis.noaa.gov/DSCOVR/

Assessing Nebraska playa wetland inundation status during 1985-2015 using Landsat data and Google Earth Engine.

PubMed

Tang, Zhenghong; Li, Yao; Gu, Yue; Jiang, Weiguo; Xue, Yuan; Hu, Qiao; LaGrange, Ted; Bishop, Andy; Drahota, Jeff; Li, Ruopu

2016-12-01

Playa wetlands in Nebraska provide globally important habitats for migratory waterfowl. Inundation condition is an important indicator of playa wetland functionality. However, there is a lack of long-term continuous monitoring records for playa wetlands. The objective of this study was to determine a suitable index for Landsat images to map the playa inundation status in March and April during 1985-2015. Four types of spectral indices-negative normalized vegetation index, Normalized Difference Water Index (NDWI), modified NDWI, and Tasseled Cap Wetness-Greenness Difference (TCWGD)-were evaluated to detect playa inundation conditions from Landsat images. The results indicate that the TCWGD is the most suitable index for distinguishing playa inundation status. By using Landsat images and Google Earth Engine, we mapped the spring inundation condition of Nebraska playas during 1985-2015. The results show that the total inundated areas were 176.79 km 2 in spring migratory season, representing 18.92% of the total area of playa wetlands. There were 9898 wetlands inundated at least once in either March or April during the past 30 years, representing 29.41% of a total of 33,659 historical wetlands. After comparing the historical hydric soil footprints and the inundated areas, the results indicate that the hydrological conditions of the majority of playas in Nebraska have changed. The inundated wetlands are candidates for protection and/or partial restoration, and the un-inundated wetlands need more attention for wetland restoration. Wetlands in areas enrolled in conservation easements had a significantly high level of playa inundation status than non-conserved wetlands during spring migratory seasons in the past decades.These conservation easements only count for 4.29% of the total footprint areas, but they have contributed 20.82% of the inundation areas in Nebraska during the past 30 years.

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

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.

Calibration Image of Earth by Mars Color Imager

NASA Image and Video Library

2005-08-22

Three days after the Mars Reconnaissance Orbiter Aug. 12, 2005, launch, the NASA spacecraft was pointed toward Earth and the Mars Color Imager camera was powered up to acquire a suite of color and ultraviolet images of Earth and the Moon.

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.

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.

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

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.

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.

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.

The excitement of Google Scholar, the worry of Google Print

PubMed Central

Banks, Marcus A

2005-01-01

In late 2004 Google announced two major projects, the unveiling of Google Scholar and a major expansion of the Google Print digitization program. Both projects have generated discussion within the library and research communities, and Google Print has received significant media attention. This commentary describes exciting educational possibilities stimulated by Google Scholar, and argues for caution regarding the Google Print project. PMID:15784147

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.

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

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)

Google searches help with diagnosis in dermatology.

PubMed

Amri, Montassar; Feroz, Kaliyadan

2014-01-01

Several previous studies have tried to assess the usefulness of Google search as a diagnostic aid. The results were discordant and have led to controversies. To investigate how often Google search is helpful to reach correct diagnoses in dermatology. Two fifth-year students (A and B) and one demonstrator (C) have participated as investigators in this paper. Twenty-five diagnostic dermatological cases were selected from all the clinical cases published in the Web only images in clinical medicine from March 2005 to November 2009. The main outcome measure of our paper was to compare the number of correct diagnoses provided by the investigators without, and with Google search. Investigator A gave correct diagnoses in 9/25 (36%) cases without Google search, his diagnostic success after Google search was 18/25 (72%). Investigator B results were 11/25 (44%) correct diagnoses without Google search, and 19/25 (76%) after this search. For investigator C, the results were 12/25 (48%) without Google search, and 18/25 (72%) after the use of this tool. Thus, the total correct diagnoses provided by the three investigators were 32 (42.6%) without Google search, and 55 (73.3%) when using this facility. The difference was statistically significant between the total number of correct diagnoses given by the three investigators without, and with Google search (p = 0.0002). In the light of our paper, Google search appears to be an interesting diagnostic aid in dermatology. However, we emphasize that diagnosis is primarily an art based on clinical skills and experience.

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.

From Google Maps to Google Models (Invited)

NASA Astrophysics Data System (ADS)

Moore, R. V.

2010-12-01

Why hasn’t integrated modelling taken off? To its advocates, it is self-evidently the best and arguably the only tool available for understanding and predicting the likely response of the environment to events and policies. Legislation requires managers to ensure that their plans are sustainable. How, other than by modelling the interacting processes involved, can the option with the greatest benefits be identified? Integrated modelling (IM) is seen to have huge potential. In science, IM is used to extend and encapsulate our understanding of the whole earth system. Such models are beginning to be incorporated in operational decision support systems and used to seek sustainable solutions to society’s problems, but only on a limited scale. Commercial take up is negligible yet the opportunities would appear limitless. The need is there; the potential is there, so what is inhibiting IM’s take up? What must be done to reap the rewards of the R & D to date? To answer the question, it useful to look back at the developments which have seen paper maps evolve into Google Maps and the systems that now surround it; facilities available not just to experts and governments but to anyone with a an iphone and an internet connection. The initial objective was to automate the process of drawing lines on paper, though it was quickly realised that digitising maps was the key to unlocking the information they held. However, it took thousands of PhD and MSc projects before a computer could generate a map comparable to that produced by a cartographer and many more before it was possible to extract reliable useful information from maps. It also required advances in IT and a change of mindset from one focused on paper map production to one focused on information delivery. To move from digital maps to Google Maps required the availability of data on a world scale, the resources to bring them together, the development of remote sensing, satellite navigation and communications

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

Looking at plastic surgery through Google Glass: part 1. Systematic review of Google Glass evidence and the first plastic surgical procedures.

PubMed

Davis, Christopher R; Rosenfield, Lorne K

2015-03-01

Google Glass has the potential to become a ubiquitous and translational technological tool within clinical plastic surgery. Google Glass allows clinicians to remotely view patient notes, laboratory results, and imaging; training can be augmented via streamed expert master classes; and patient safety can be improved by remote advice from a senior colleague. This systematic review identified and appraised every Google Glass publication relevant to plastic surgery and describes the first plastic surgical procedures recorded using Google Glass. A systematic review was performed using PubMed National Center for Biotechnology Information, Ovid MEDLINE, and the Cochrane Central Register of Controlled Trials, following modified Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Key search terms "Google" and "Glass" identified mutually inclusive publications that were screened for inclusion. Eighty-two publications were identified, with 21 included for review. Google Glass publications were formal articles (n = 3), editorial/commentary articles (n = 7), conference proceedings (n = 1), news reports (n = 3), and online articles (n = 7). Data support Google Glass' positive impact on health care delivery, clinical training, medical documentation, and patient safety. Concerns exist regarding patient confidentiality, technical issues, and limited software. The first plastic surgical procedure performed using Google Glass was a blepharoplasty on October 29, 2013. Google Glass is an exciting translational technology with the potential to positively impact health care delivery, medical documentation, surgical training, and patient safety. Further high-quality scientific research is required to formally appraise Google Glass in the clinical setting.

Using Google Earth to Explore Multiple Data Sets and Plate Tectonic Concepts

NASA Astrophysics Data System (ADS)

Goodell, L. P.

2015-12-01

Google Earth (GE) offers an engaging and dynamic environment for exploration of earth science data. While GIS software offers higher-level analytical capability, it comes with a steep learning curve and complex interface that is not easy for the novice, and in many cases the instructor, to negotiate. In contrast, the intuitive interface of GE makes it easy for students to quickly become proficient in manipulating the globe and independently exploring relationships between multiple data sets at a wide range of scales. Inquiry-based, data-rich exercises have been developed for both introductory and upper-level activities including: exploration of plate boundary characteristics and relative motion across plate boundaries; determination and comparison of short-term and long-term average plate velocities; crustal strain analysis (modeled after the UNAVCO activity); and determining earthquake epicenters, body-wave magnitudes, and focal plane solutions. Used successfully in undergraduate course settings, for TA training and for professional development programs for middle and high school teachers, the exercises use the following GE data sets (with sources) that have been collected/compiled by the author and are freely available for non-commercial use: 1) tectonic plate boundaries and plate names (Bird, 2003 model); 2) real-time earthquakes (USGS); 3) 30 years of M>=5.0 earthquakes, plotted by depth (USGS); 4) seafloor age (Mueller et al., 1997, 2008); 5) location and age data for hot spot tracks (published literature); 6) Holocene volcanoes (Smithsonian Global Volcanism Program); 7) GPS station locations with links to times series (JPL, NASA, UNAVCO); 8) short-term motion vectors derived from GPS times series; 9) long-term average motion vectors derived from plate motion models (UNAVCO plate motion calculator); 10) earthquake data sets consisting of seismic station locations and links to relevant seismograms (Rapid Earthquake Viewer, USC/IRIS/DELESE).

Integrating Radar Image Data with Google Maps

NASA Technical Reports Server (NTRS)

Chapman, Bruce D.; Gibas, Sarah

2010-01-01

A public Web site has been developed as a method for displaying the multitude of radar imagery collected by NASA s Airborne Synthetic Aperture Radar (AIRSAR) instrument during its 16-year mission. Utilizing NASA s internal AIRSAR site, the new Web site features more sophisticated visualization tools that enable the general public to have access to these images. The site was originally maintained at NASA on six computers: one that held the Oracle database, two that took care of the software for the interactive map, and three that were for the Web site itself. Several tasks were involved in moving this complicated setup to just one computer. First, the AIRSAR database was migrated from Oracle to MySQL. Then the back-end of the AIRSAR Web site was updated in order to access the MySQL database. To do this, a few of the scripts needed to be modified; specifically three Perl scripts that query that database. The database connections were then updated from Oracle to MySQL, numerous syntax errors were corrected, and a query was implemented that replaced one of the stored Oracle procedures. Lastly, the interactive map was designed, implemented, and tested so that users could easily browse and access the radar imagery through the Google Maps interface.

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

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.

First "glass" education: telementored cardiac ultrasonography using Google Glass- a pilot study.

PubMed

Russell, Patrick M; Mallin, Michael; Youngquist, Scott T; Cotton, Jennifer; Aboul-Hosn, Nael; Dawson, Matt

2014-11-01

The objective of this study was to determine the feasibility of telementored instruction in bedside ultrasonography (US) using Google Glass. The authors sought to examine whether first-time US users could obtain adequate parasternal long axis (PSLA) views to approximate ejection fraction (EF) using Google Glass telementoring. This was a prospective, randomized, single-blinded study. Eighteen second-year medical students were randomized into three groups and tasked with obtaining PSLA cardiac imaging. Group A received real-time telementored education through Google Glass via Google Hangout from a remotely located expert. Group B received bedside education from the same expert. Group C represented the control and received no instruction. Each subject was given 3 minutes to obtain a best PSLA cardiac imaging using a portable GE Vscan. Image clips obtained by each subject were stored. A second expert, blinded to instructional mode, evaluated images for adequacy and assigned an image quality rating on a 0 to 10 scale. Group A was able to obtain adequate images six out of six times (100%) with a median image quality rating of 7.5 (interquartile range [IQR] = 6 to 10) out of 10. Group B was also able to obtain adequate views six out of six times (100%), with a median image quality rating of 8 (IQR = 7 to 9). Group C was able to obtain adequate views one out of six times (17%), with a median image quality of 0 (IQR = 0 to 2). There were no statistically significant differences between Group A and Group B in the achievement of adequate images for E-point septal separation measurement or in image quality. In this pilot/feasibility study, novice US users were able to obtain adequate imaging to determine a healthy patient's EF through telementored education using Google Glass. These preliminary data suggest telementoring as an adequate means of medical education in bedside US. This conclusion will need to be validated with larger, more powerful studies including evaluation of

Earth - Departing Image by Galileo

NASA Image and Video Library

1996-02-08

This color image of the Earth was taken by NASA’s Galileo spacecraft on December 11 as it departed on its 3-year flight to Jupiter, about 2 1/2 days after the second Earth flyby. http://photojournal.jpl.nasa.gov/catalog/PIA00232

Lunar Satellite Snaps Image of Earth

NASA Image and Video Library

2014-05-07

This image, captured Feb. 1, 2014, shows a colorized view of Earth from the moon-based perspective of NASA's Lunar Reconnaissance Orbiter. Credit: NASA/Goddard/Arizona State University -- NASA's Lunar Reconnaissance Orbiter (LRO) experiences 12 "earthrises" every day, however LROC (short for LRO Camera) is almost always busy imaging the lunar surface so only rarely does an opportunity arise such that LROC can capture a view of Earth. On Feb. 1, 2014, LRO pitched forward while approaching the moon's north pole allowing the LROC Wide Angle Camera to capture Earth rising above Rozhdestvenskiy crater (112 miles, or 180 km, in diameter). Read more: go.nasa.gov/1oqMlgu NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

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

High-Definition Television (HDTV) Images for Earth Observations and Earth Science Applications

NASA Technical Reports Server (NTRS)

Robinson, Julie A.; Holland, S. Douglas; Runco, Susan K.; Pitts, David E.; Whitehead, Victor S.; Andrefouet, Serge M.

2000-01-01

As part of Detailed Test Objective 700-17A, astronauts acquired Earth observation images from orbit using a high-definition television (HDTV) camcorder, Here we provide a summary of qualitative findings following completion of tests during missions STS (Space Transport System)-93 and STS-99. We compared HDTV imagery stills to images taken using payload bay video cameras, Hasselblad film camera, and electronic still camera. We also evaluated the potential for motion video observations of changes in sunlight and the use of multi-aspect viewing to image aerosols. Spatial resolution and color quality are far superior in HDTV images compared to National Television Systems Committee (NTSC) video images. Thus, HDTV provides the first viable option for video-based remote sensing observations of Earth from orbit. Although under ideal conditions, HDTV images have less spatial resolution than medium-format film cameras, such as the Hasselblad, under some conditions on orbit, the HDTV image acquired compared favorably with the Hasselblad. Of particular note was the quality of color reproduction in the HDTV images HDTV and electronic still camera (ESC) were not compared with matched fields of view, and so spatial resolution could not be compared for the two image types. However, the color reproduction of the HDTV stills was truer than colors in the ESC images. As HDTV becomes the operational video standard for Space Shuttle and Space Station, HDTV has great potential as a source of Earth-observation data. Planning for the conversion from NTSC to HDTV video standards should include planning for Earth data archiving and distribution.

Curiosity Mars Rover First Image of Earth and Earth Moon

NASA Image and Video Library

2014-02-06

The two bodies in this portion of an evening-sky view by NASA Mars rover Curiosity are Earth and Earth moon. The rover Mast Camera Mastcam imaged them in the twilight sky of Curiosity 529th Martian day, or sol Jan. 31, 2014.

Galileo multispectral imaging of Earth.

PubMed

Geissler, P; Thompson, W R; Greenberg, R; Moersch, J; McEwen, A; Sagan, C

1995-08-25

Nearly 6000 multispectral images of Earth were acquired by the Galileo spacecraft during its two flybys. The Galileo images offer a unique perspective on our home planet through the spectral capability made possible by four narrowband near-infrared filters, intended for observations of methane in Jupiter's atmosphere, which are not incorporated in any of the currently operating Earth orbital remote sensing systems. Spectral variations due to mineralogy, vegetative cover, and condensed water are effectively mapped by the visible and near-infrared multispectral imagery, showing a wide variety of biological, meteorological, and geological phenomena. Global tectonic and volcanic processes are clearly illustrated by these images, providing a useful basis for comparative planetary geology. Differences between plant species are detected through the narrowband IR filters on Galileo, allowing regional measurements of variation in the "red edge" of chlorophyll and the depth of the 1-micrometer water band, which is diagnostic of leaf moisture content. Although evidence of life is widespread in the Galileo data set, only a single image (at approximately 2 km/pixel) shows geometrization plausibly attributable to our technical civilization. Water vapor can be uniquely imaged in the Galileo 0.73-micrometer band, permitting spectral discrimination of moist and dry clouds with otherwise similar albedo. Surface snow and ice can be readily distinguished from cloud cover by narrowband imaging within the sensitivity range of Galileo's silicon CCD camera. Ice grain size variations can be mapped using the weak H2O absorption at 1 micrometer, a technique which may find important applications in the exploration of the moons of Jupiter. The Galileo images have the potential to make unique contributions to Earth science in the areas of geological, meteorological and biological remote sensing, due to the inclusion of previously untried narrowband IR filters. The vast scale and near global

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.

Earth observation images taken as part of the EarthKAM educational program

NASA Image and Video Library

2000-02-13

S99-E-5267 (13 February 2000) --- City of El Paso, Texas, and Ciudad Juarez, Chihuahua, Mexico and the Rio Grande River, which separates them. An electronic still camera (ESC), mounted in one of Endeavour's aft flight deck windows, is recording imagery of hundreds of Earth targets for the EarthKAM project. Students across the United States and in France, Germany and Japan are taking photos throughout the STS-99 mission. And they are using these new photos, plus all the images already available in the EarthKAM system, to enhance their classroom learning in Earth and space science, social studies, geography, mathematics and more. For general EarthKAM information and more images from this flight, go to http://www.earthkam.ucsd.edu/

Integrated visualization of remote sensing data using Google Earth

NASA Astrophysics Data System (ADS)

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

2009-09-01

The need for advanced visualization tools for meteorological data has lead in the last years to the development of sophisticated software packages either by observing systems manufacturers or by third-party solution providers. For example, manufacturers of remote sensing systems such as weather radars or lightning detection systems include zoom, product selection, archive access capabilities, as well as quantitative tools for data analysis, as standard features which are highly appreciated in weather surveillance or post-event case study analysis. However, the fact that each manufacturer has its own visualization system and data formats hampers the usability and integration of different data sources. In this context, Google Earth (GE) offers the possibility of combining several graphical information types in a unique visualization system which can be easily accessed by users. The Meteorological Service of Catalonia (SMC) has been evaluating the use of GE as a visualization platform for surveillance tasks in adverse weather events. First experiences are related to the integration in real-time of remote sensing data: radar, lightning, and satellite. The tool shows the animation of the combined products in the last hour, giving a good picture of the meteorological situation. One of the main advantages of this product is that is easy to be installed in many computers and does not need high computational requirements. Besides this, the capability of GE provides information about the most affected areas by heavy rain or other weather phenomena. On the opposite, the main disadvantage is that the product offers only qualitative information, and quantitative data is only available though the graphical display (i.e. trough color scales but not associated to physical values that can be accessed by users easily). The procedure developed to run in real time is divided in three parts. First of all, a crontab file launches different applications, depending on the data type

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.

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

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.

Surgical Vision: Google Glass and Surgery.

PubMed

Chang, Johnny Yau Cheung; Tsui, Lok Yee; Yeung, Keith Siu Kay; Yip, Stefanie Wai Ying; Leung, Gilberto Ka Kit

2016-08-01

Google Glass is, in essence, a smartphone in the form of a pair of spectacles. It has a display system, a bone conduction "speaker," video camera, and connectivity via WiFi or Bluetooth technologies. It can also be controlled by voice command. Seizing Google Glass' capabilities as windows of opportunity, surgeons have been the first group of doctors trying to incorporate the technology into their daily practices. Experiences from different groups have demonstrated Google Glass' potential in improving perioperative care, intraoperative communication and documentation, surgical outcome as well as surgical training. On the other hand, the device has technical limitations, notably suboptimal image qualities and a short battery life. Its operational functions also bring forth concerns on the protection of patient privacy. Nonetheless, the technological advances that this device embodies hold promises in surgical innovations. Further studies are required, and surgeons should explore, investigate, and embrace similar technologies with keen and informed anticipation. © The Author(s) 2016.

Google Earth elevation data extraction and accuracy assessment for transportation applications.

PubMed

Wang, Yinsong; Zou, Yajie; Henrickson, Kristian; Wang, Yinhai; Tang, Jinjun; Park, Byung-Jung

2017-01-01

Roadway elevation data is critical for a variety of transportation analyses. However, it has been challenging to obtain such data and most roadway GIS databases do not have them. This paper intends to address this need by proposing a method to extract roadway elevation data from Google Earth (GE) for transportation applications. A comprehensive accuracy assessment of the GE-extracted elevation data is conducted for the area of conterminous USA. The GE elevation data was compared with the ground truth data from nationwide GPS benchmarks and roadway monuments from six states in the conterminous USA. This study also compares the GE elevation data with the elevation raster data from the U.S. Geological Survey National Elevation Dataset (USGS NED), which is a widely used data source for extracting roadway elevation. Mean absolute error (MAE) and root mean squared error (RMSE) are used to assess the accuracy and the test results show MAE, RMSE and standard deviation of GE roadway elevation error are 1.32 meters, 2.27 meters and 2.27 meters, respectively. Finally, the proposed extraction method was implemented and validated for the following three scenarios: (1) extracting roadway elevation differentiating by directions, (2) multi-layered roadway recognition in freeway segment and (3) slope segmentation and grade calculation in freeway segment. The methodology validation results indicate that the proposed extraction method can locate the extracting route accurately, recognize multi-layered roadway section, and segment the extracted route by grade automatically. Overall, it is found that the high accuracy elevation data available from GE provide a reliable data source for various transportation applications.

2001 Mars Odyssey Images Earth (Visible and Infrared)

NASA Technical Reports Server (NTRS)

2001-01-01

2001 Mars Odyssey's Thermal Emission Imaging System (THEMIS) acquired these images of the Earth using its visible and infrared cameras as it left the Earth. The visible image shows the thin crescent viewed from Odyssey's perspective. The infrared image was acquired at exactly the same time, but shows the entire Earth using the infrared's 'night-vision' capability. Invisible light the instrument sees only reflected sunlight and therefore sees nothing on the night side of the planet. In infrared light the camera observes the light emitted by all regions of the Earth. The coldest ground temperatures seen correspond to the nighttime regions of Antarctica; the warmest temperatures occur in Australia. The low temperature in Antarctica is minus 50 degrees Celsius (minus 58 degrees Fahrenheit); the high temperature at night in Australia 9 degrees Celsius(48.2 degrees Fahrenheit). These temperatures agree remarkably well with observed temperatures of minus 63 degrees Celsius at Vostok Station in Antarctica, and 10 degrees Celsius in Australia. The images were taken at a distance of 3,563,735 kilometers (more than 2 million miles) on April 19,2001 as the Odyssey spacecraft left Earth.

Google Earth elevation data extraction and accuracy assessment for transportation applications

PubMed Central

Wang, Yinsong; Zou, Yajie; Henrickson, Kristian; Wang, Yinhai; Tang, Jinjun; Park, Byung-Jung

2017-01-01

Roadway elevation data is critical for a variety of transportation analyses. However, it has been challenging to obtain such data and most roadway GIS databases do not have them. This paper intends to address this need by proposing a method to extract roadway elevation data from Google Earth (GE) for transportation applications. A comprehensive accuracy assessment of the GE-extracted elevation data is conducted for the area of conterminous USA. The GE elevation data was compared with the ground truth data from nationwide GPS benchmarks and roadway monuments from six states in the conterminous USA. This study also compares the GE elevation data with the elevation raster data from the U.S. Geological Survey National Elevation Dataset (USGS NED), which is a widely used data source for extracting roadway elevation. Mean absolute error (MAE) and root mean squared error (RMSE) are used to assess the accuracy and the test results show MAE, RMSE and standard deviation of GE roadway elevation error are 1.32 meters, 2.27 meters and 2.27 meters, respectively. Finally, the proposed extraction method was implemented and validated for the following three scenarios: (1) extracting roadway elevation differentiating by directions, (2) multi-layered roadway recognition in freeway segment and (3) slope segmentation and grade calculation in freeway segment. The methodology validation results indicate that the proposed extraction method can locate the extracting route accurately, recognize multi-layered roadway section, and segment the extracted route by grade automatically. Overall, it is found that the high accuracy elevation data available from GE provide a reliable data source for various transportation applications. PMID:28445480

Using Google Maps to Access USGS Volcano Hazards Information

NASA Astrophysics Data System (ADS)

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

2006-12-01

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

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

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.

Imaging_Earth_With_MUSES

NASA Image and Video Library

2017-07-11

Commercial businesses and scientific researchers have a new capability to capture digital imagery of Earth, thanks to MUSES: the Multiple User System for Earth Sensing facility. This platform on the outside of the International Space Station is capable of holding four different payloads, ranging from high-resolution digital cameras to hyperspectral imagers, which will support Earth science observations in agricultural awareness, air quality, disaster response, fire detection, and many other research topics. MUSES program manager Mike Soutullo explains the system and its unique features including the ability to change and upgrade payloads using the space station’s Canadarm2 and Special Purpose Dexterous Manipulator. For more information about MUSES, please visit: https://www.nasa.gov/mission_pages/station/research/news/MUSES For more on ISS science, https://www.nasa.gov/mission_pages/station/research/index.html or follow us on Twitter @ISS_research

Beyond Kepler: Direct Imaging of Earth-like Planets

NASA Technical Reports Server (NTRS)

Belikov, Ruslan

2012-01-01

Is there another Earth out there? Is there life on it? People have been asking these questions for over two thousand years, and we finally stand on the verge of answering them. The Kepler space telescope is NASA's first mission designed to study Earthlike exoplanets (exo-Earths), and it will soon tell us how often exo-Earths occur in the habitable zones of their stars. The next natural step after Kepler is spectroscopic characterization of exo-Earths, which would tell us whether they possess an atmosphere, oxygen, liquid water, as well as other biomarkers. In order to do this, directly imaging an exo-Earth may be necessary (at least for Sun-like stars). Directly imaging an exo-Earth is challenging and likely requires a flagship-size optical space telescope with an unprecedented imaging system capable of achieving contrasts of 1(exp 10) very close to the diffraction limit. Several coronagraphs and external occulters have been proposed to meet this challenge and are in development. After first overviewing the history and current state of the field, my talk will focus on the work proceeding at the Ames Coronagraph Experiment (ACE) at the NASA Ames Research Center, where we are developing the Phase Induced Amplitude Apodization (PIAA) coronagraph in a collaboration with JPL. PIAA is a powerful technique with demonstrated aggressive performance that defines the state of the art at small inner working angles. At ACE, we have achieved contrasts of 2(exp -8) with an inner working angle of 2 lambda/D and 1(exp -6) at 1.4 lambda/D. On the path to exo-Earth imaging, we are also pursuing a smaller telescope concept called EXCEDE (EXoplanetary Circumstellar Environments and Disk Explorer), which was recently selected for technology development (Category III) by NASA's Explorer program. EXCEDE will do fundamental science on debris disks as well as serve as a technological and scientific pathfinder for an exo-Earth imaging mission.

The EarthKAM project: creating space imaging tools for teaching and learning

NASA Astrophysics Data System (ADS)

Dodson, Holly; Levin, Paula; Ride, Sally; Souviney, Randall

2000-07-01

The EarthKAM Project is a NASA-supported partnership of secondary and university students with Earth Science and educational researchers. This report describes an ongoing series of activities that more effectively integrate Earth images into classroom instruction. In this project, students select and analyze images of the Earth taken during Shuttle flights and use the tools of modern science (computers, data analysis tools and the Internet) to disseminate the images and results of their research. A related study, the Visualizing Earth Project, explores in greater detail the cognitive aspects of image processing and the educational potential of visualizations in science teaching and learning. The content and organization of the EarthKAM datasystem of images and metadata are also described. An associated project is linking this datasystem of images with the Getty Thesaurus of Geographic Names, which will allow users to access a wide range of geographic and political information for the regions shown in EarthKAM images. Another project will provide tools for automated feature extraction from EarthKAM images. In order to make EarthKAM resources available to a larger number of schools, the next important goal is to create an integrated datasystem that combines iterative resource validation and publication, with multimedia management of instructional materials.

Calibration View of Earth and the Moon by Mars Color Imager

NASA Technical Reports Server (NTRS)

2005-01-01

Three days after the Mars Reconnaissance Orbiter's Aug. 12, 2005, launch, the spacecraft was pointed toward Earth and the Mars Color Imager camera was powered up to acquire a suite of images of Earth and the Moon. When it gets to Mars, the Mars Color Imager's main objective will be to obtain daily global color and ultraviolet images of the planet to observe martian meteorology by documenting the occurrence of dust storms, clouds, and ozone. This camera will also observe how the martian surface changes over time, including changes in frost patterns and surface brightness caused by dust storms and dust devils.

The purpose of acquiring an image of Earth and the Moon just three days after launch was to help the Mars Color Imager science team obtain a measure, in space, of the instrument's sensitivity, as well as to check that no contamination occurred on the camera during launch. Prior to launch, the team determined that, three days out from Earth, the planet would only be about 4.77 pixels across, and the Moon would be less than one pixel in size, as seen from the Mars Color Imager's wide-angle perspective. If the team waited any longer than three days to test the camera's performance in space, Earth would be too small to obtain meaningful results.

The Earth and Moon images were acquired by turning Mars Reconnaissance Orbiter toward Earth, then slewing the spacecraft so that the Earth and Moon would pass before each of the five color and two ultraviolet filters of the Mars Color Imager. The distance to the Moon was about 1,440,000 kilometers (about 895,000 miles); the range to Earth was about 1,170,000 kilometers (about 727,000 miles).

This view combines a sequence of frames showing the passage of Earth and the Moon across the field of view of a single color band of the Mars Color Imager. As the spacecraft slewed to view the two objects, they passed through the camera's field of view. Earth has been saturated white in this image so that both Earth

Accuracy of remote electrocardiogram interpretation with the use of Google Glass technology.

PubMed

Jeroudi, Omar M; Christakopoulos, George; Christopoulos, George; Kotsia, Anna; Kypreos, Megan A; Rangan, Bavana V; Banerjee, Subhash; Brilakis, Emmanouil S

2015-02-01

We sought to investigate the accuracy of remote electrocardiogram (ECG) interpretation using Google Glass (Google, Mountain View, California). Google Glass is an optical head mounted display device with growing applications in medicine. We compared interpretation of 10 ECGs with 21 clinically important findings by faculty and fellow cardiologists by (1) viewing the electrocardiographic image at the Google Glass screen; (2) viewing a photograph of the ECG taken using Google Glass and interpreted on a mobile device; (3) viewing the original paper ECG; and (4) viewing a photograph of the ECG taken with a high-resolution camera and interpreted on a mobile device. One point was given for identification of each correct finding. Subjective rating of the user experience was also recorded. Twelve physicians (4 faculty and 8 fellow cardiologists) participated. The average electrocardiographic interpretation score (maximum 21 points) as viewed through the Google Glass, Google Glass photograph on a mobile device, on paper, and high-resolution photograph on a mobile device was 13.5 ± 1.8, 16.1 ± 2.6, 18.3 ± 1.7, and 18.6 ± 1.5, respectively (p = 0.0005 between Google Glass and mobile device, p = 0.0005 between Google Glass and paper, and p = 0.002 between mobile device and paper). Of the 12 physicians, 9 (75%) were dissatisfied with ECGs viewing on the prism display of Google Glass. In conclusion, further improvements are needed before Google Glass can be reliably used for remote electrocardiographic analysis. Published by Elsevier Inc.

Accuracy of remote chest X-ray interpretation using Google Glass technology.

PubMed

Spaedy, Emily; Christakopoulos, Georgios E; Tarar, Muhammad Nauman J; Christopoulos, Georgios; Rangan, Bavana V; Roesle, Michele; Ochoa, Cristhiaan D; Yarbrough, William; Banerjee, Subhash; Brilakis, Emmanouil S

2016-09-15

We sought to explore the accuracy of remote chest X-ray reading using hands-free, wearable technology (Google Glass, Google, Mountain View, California). We compared interpretation of twelve chest X-rays with 23 major cardiopulmonary findings by faculty and fellows from cardiology, radiology, and pulmonary-critical care via: (1) viewing the chest X-ray image on the Google Glass screen; (2) viewing a photograph of the chest X-ray taken using Google Glass and interpreted on a mobile device; (3) viewing the original chest X-ray on a desktop computer screen. One point was given for identification of each correct finding and a subjective rating of user experience was recorded. Fifteen physicians (5 faculty and 10 fellows) participated. The average chest X-ray reading score (maximum 23 points) as viewed through the Google Glass, Google Glass photograph on a mobile device, and the original X-ray viewed on a desktop computer was 14.1±2.2, 18.5±1.5 and 21.3±1.7, respectively (p<0.0001 between Google Glass and mobile device, p<0.0001 between Google Glass and desktop computer and p=0.0004 between mobile device and desktop computer). Of 15 physicians, 11 (73.3%) felt confident in detecting findings using the photograph taken by Google Glass as viewed on a mobile device. Remote chest X-ray interpretation using hands-free, wearable technology (Google Glass) is less accurate than interpretation using a desktop computer or a mobile device, suggesting that further technical improvements are needed before widespread application of this novel technology. Published by Elsevier Ireland Ltd.

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.

The Google-ization of Knowledge

ERIC Educational Resources Information Center

Larson, Natasja; Parsons, Jim; Servage, Laura

2007-01-01

How has GOOGLE shaped knowledge? How has it shaped those who use it? This article considers the impact of online knowledge upon the content of knowledge and upon the people who seek it and create it. The authors suggest that 1. Google-ization is reshaping knowledge. 2. Google-ization is changing how knowledge counts as important. 3. Google-ization…

Google Test MPI Listener

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

Oxberry, Geoffrey

Google Test MPI Listener is a plugin for the Google Test c++ unit testing library that organizes test output of software that uses both the MPI parallel programming model and Google Test. Typically, such output is ordered arbitrarily and disorganized, making difficult the process of interpreting test output. This plug organizes output in MPI rank order, enabling easy interpretation of test results.

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.

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.

Most Amazing High Definition Image of Earth - Blue Marble 2012

NASA Image and Video Library

2017-12-08

January 25, 2012 *Updated February 2, 2012: According to Flickr, "The western hemisphere Blue Marble 2012 image has rocketed up to over 3.1 million views making it one of the all time most viewed images on the site after only one week." A 'Blue Marble' image of the Earth taken from the VIIRS instrument aboard NASA's most recently launched Earth-observing satellite - Suomi NPP. This composite image uses a number of swaths of the Earth's surface taken on January 4, 2012. The NPP satellite was renamed 'Suomi NPP' on January 24, 2012 to honor the late Verner E. Suomi of the University of Wisconsin. Suomi NPP is NASA's next Earth-observing research satellite. It is the first of a new generation of satellites that will observe many facets of our changing Earth. Suomi NPP is carrying five instruments on board. The biggest and most important instrument is The Visible/Infrared Imager Radiometer Suite or VIIRS. To read more about NASA's Suomi NPP go to: www.nasa.gov/npp Credit: NASA/NOAA/GSFC/Suomi NPP/VIIRS/Norman Kuring NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Earth Observation Services (Image Processing Software)

NASA Technical Reports Server (NTRS)

1992-01-01

San Diego State University and Environmental Systems Research Institute, with other agencies, have applied satellite imaging and image processing techniques to geographic information systems (GIS) updating. The resulting images display land use and are used by a regional planning agency for applications like mapping vegetation distribution and preserving wildlife habitats. The EOCAP program provides government co-funding to encourage private investment in, and to broaden the use of NASA-developed technology for analyzing information about Earth and ocean resources.

Google glass based immunochromatographic diagnostic test analysis

NASA Astrophysics Data System (ADS)

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

2015-03-01

Integration of optical imagers and sensors into recently emerging wearable computational devices allows for simpler and more intuitive methods of integrating biomedical imaging and medical diagnostics tasks into existing infrastructures. Here we demonstrate the ability of one such device, the Google Glass, to perform qualitative and quantitative analysis of immunochromatographic rapid diagnostic tests (RDTs) using a voice-commandable hands-free software-only interface, as an alternative to larger and more bulky desktop or handheld units. Using the built-in camera of Glass to image one or more RDTs (labeled with Quick Response (QR) codes), our Glass software application uploads the captured image and related information (e.g., user name, GPS, etc.) to our servers for remote analysis and storage. After digital analysis of the RDT images, the results are transmitted back to the originating Glass device, and made available through a website in geospatial and tabular representations. We tested this system on qualitative human immunodeficiency virus (HIV) and quantitative prostate-specific antigen (PSA) RDTs. For qualitative HIV tests, we demonstrate successful detection and labeling (i.e., yes/no decisions) for up to 6-fold dilution of HIV samples. For quantitative measurements, we activated and imaged PSA concentrations ranging from 0 to 200 ng/mL and generated calibration curves relating the RDT line intensity values to PSA concentration. By providing automated digitization of both qualitative and quantitative test results, this wearable colorimetric diagnostic test reader platform on Google Glass can reduce operator errors caused by poor training, provide real-time spatiotemporal mapping of test results, and assist with remote monitoring of various biomedical conditions.

[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.

Top 16 Earth Images of 2016

NASA Image and Video Library

2017-02-12

Astronauts on the International Space Station take pictures of Earth out their windows nearly every day; over a year that adds up to thousands of photos. The people at the Earth Science and Remote Sensing Unit at NASA’s Johnson Space Center in Houston pored through this year’s crop to pick their top 16 photos of Earth for 2016—enjoy! Download the images: https://www.flickr.com/photos/nasa2explore/albums/72157674260752223 HD download link: https://archive.org/details/TheSpaceProgram _______________________________________ FOLLOW THE SPACE STATION! Twitter: https://twitter.com/Space_Station Facebook: https://www.facebook.com/ISS Instagram: https://instagram.com/iss/

Dr Google

PubMed Central

Pías-Peleteiro, Leticia; Cortés-Bordoy, Javier; Martinón-Torres, Federico

2013-01-01

Objectives: To assess and analyze the information and recommendations provided by Google Web Search™ (Google) in relation to web searches on the HPV vaccine, indications for females and males and possible adverse effects. Materials and Methods: Descriptive cross-sectional study of the results of 14 web searches. Comprehensive analysis of results based on general recommendation given (favorable/dissuasive), as well as compliance with pre-established criteria, namely design, content and credibility. Sub-analysis of results according to site category: general information, blog / forum and press. Results: In the comprehensive analysis of results, 72.2% of websites offer information favorable to HPV vaccination, with varying degrees of content detail, vs. 27.8% with highly dissuasive content in relation to HPV vaccination. The most frequent type of site is the blog or forum. The information found is frequently incomplete, poorly structured, and often lacking in updates, bibliography and adequate citations, as well as sound credibility criteria (scientific association accreditation and/or trust mark system). Conclusions: Google, as a tool which users employ to locate medical information and advice, is not specialized in providing information that is necessarily rigorous or valid from a scientific perspective. Search results and ranking based on Google's generalized algorithms can lead users to poorly grounded opinions and statements, which may impact HPV vaccination perception and subsequent decision making. PMID:23744505

Earth Observation Services Weather Imaging

NASA Technical Reports Server (NTRS)

1992-01-01

Microprocessor-based systems for processing satellite data offer mariners real-time images of weather systems, day and night, of large areas or allow them to zoom in on a few square miles. Systems West markets these commercial image processing systems, which have significantly decreased the cost of satellite weather stations. The company was assisted by the EOCAP program, which provides government co-funding to encourage private investment in, and to broaden the use of, NASA-developed technology for analyzing information about Earth and ocean resources.

Steno Google doodle

NASA Astrophysics Data System (ADS)

Showstack, Randy

2012-01-01

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

The MESSENGER Earth Flyby: Results from the Mercury Dual Imaging System

NASA Astrophysics Data System (ADS)

Prockter, L. M.; Murchie, S. L.; Hawkins, S. E.; Robinson, M. S.; Shelton, R. G.; Vaughan, R. M.; Solomon, S. C.

2005-12-01

The MESSENGER (MErcury Surface, Space ENvironment, Geochemistry, and Ranging) spacecraft was launched from Cape Canaveral Air Force Station, Fla., on 3 August 2004. It returned to Earth for a gravity assist on 2 August 2005, providing an exceptional opportunity for the Science Team to perform instrument calibrations and to test some of the data acquisition sequences that will be used to meet Mercury science goals. The Mercury Dual Imaging System (MDIS), one of seven science instruments on MESSENGER, consists of a wide-angle and a narrow-angle imager that together can map landforms, track variations in surface color, and carry out stereogrammetry. The two imagers are mounted on a pivot platform that enables the instrument to point in a different direction from the spacecraft boresight, allowing great flexibility and increased imaging coverage. During the week prior to the closest approach to Earth, MDIS acquired a number of images of the Moon for radiometric calibration and to test optical navigation sequences that will be used to target planetary flybys. Twenty-four hours before closest approach, images of the Earth were acquired with 11 filters of the wide-angle camera. After MDIS flew over the nightside of the Earth, additional color images centered on South America were obtained at sufficiently high resolution to discriminate small-scale features such as the Amazon River and Lake Titicaca. During its departure from Earth, MDIS acquired a sequence of images taken in three filters every 4 minutes over a period of 24 hours. These images have been assembled into a movie of a crescent Earth that begins as South America slides across the terminator into darkness and continues for one full Earth rotation. This movie and the other images have provided a successful test of the sequences that will be used during the MESSENGER Mercury flybys in 2008 and 2009 and have demonstrated the high quality of the MDIS wide-angle camera.

Applications of NASA Earth Observation Imagery in Google Earth Engine to Estimate Glacier Trends and Water Availability in Chile's Aconcagua Watershed

NASA Astrophysics Data System (ADS)

Webb, M. J.; Babis, B.; Deland, S.; McGurk, G.

2017-12-01

The Aconcagua basin of Central Chile, just north of the capital city of Santiago, is characterized by the glaciated Andes to the east, which supply meltwater runoff to the lower fertile river valleys. Known for the production of fruit and vegetable crops, the region is experiencing stressed hydrologic resources as a result of anomalous climate conditions and anthropogenic water consumption. Traditionally, the wet and cool winter months account for 80 percent of Aconcagua's total annual precipitation, while dry and warm conditions prevail during the summer months. Consequently, the basin depends on seasonal glacial accumulation to provide water storage for the dry season when up to 67 percent of water is derived from glacial runoff. Overall, 70 percent of regional water is consumed by agricultural practices, specifically the fruit and vegetable farming that thrives in Aconcagua's Mediterranean-type climate. Globally, weather intensification and the rising zero-degree isotherm are poised to threaten the stability and longevity of glacial water resources. In recent years, Chile has experienced periods of prolonged drought as well as glacier shrinkage. The Aconcagua basin is especially vulnerable to these changes as a consequence of its agricultural economies and reliance on sub-tropical glaciers for water resources. Aconcagua is among the top three regions contributing to Chile's gross domestic product (GDP). Furthermore, in 2011 the Chilean government announced plans to increase the national land under irrigation by 57 percent by 2022. In partnership with the Chilean Ministry of Agriculture, the objective of this research was to integrate NASA Earth observations in conjunction with in situ river discharge measurements into Google Earth Engine to enhance regional understanding of current and future climate conditions in Chile. The remotely-sensed datasets included Landsat TM/OLI derived glacial extent, Terra MODIS snow cover and surface temperature, and Aqua AMSR

Google Books: making the public domain universally accessible

NASA Astrophysics Data System (ADS)

Langley, Adam; Bloomberg, Dan S.

2007-01-01

Google Book Search is working with libraries and publishers around the world to digitally scan books. Some of those works are now in the public domain and, in keeping with Google's mission to make all the world's information useful and universally accessible, we wish to allow users to download them all. For users, it is important that the files are as small as possible and of printable quality. This means that a single codec for both text and images is impractical. We use PDF as a container for a mixture of JBIG2 and JPEG2000 images which are composed into a final set of pages. We discuss both the implementation of an open source JBIG2 encoder, which we use to compress text data, and the design of the infrastructure needed to meet the technical, legal and user requirements of serving many scanned works. We also cover the lessons learnt about dealing with different PDF readers and how to write files that work on most of the readers, most of the time.

An algorithm to estimate building heights from Google street-view imagery using single view metrology across a representational state transfer system

NASA Astrophysics Data System (ADS)

Díaz, Elkin; Arguello, Henry

2016-05-01

Urban ecosystem studies require monitoring, controlling and planning to analyze building density, urban density, urban planning, atmospheric modeling and land use. In urban planning, there are many methods for building height estimation using optical remote sensing images. These methods however, highly depend on sun illumination and cloud-free weather. In contrast, high resolution synthetic aperture radar provides images independent from daytime and weather conditions, although, these images rely on special hardware and expensive acquisition. Most of the biggest cities around the world have been photographed by Google street view under different conditions. Thus, thousands of images from the principal streets of a city can be accessed online. The availability of this and similar rich city imagery such as StreetSide from Microsoft, represents huge opportunities in computer vision because these images can be used as input in many applications such as 3D modeling, segmentation, recognition and stereo correspondence. This paper proposes a novel algorithm to estimate building heights using public Google Street-View imagery. The objective of this work is to obtain thousands of geo-referenced images from Google Street-View using a representational state transfer system, and estimate their average height using single view metrology. Furthermore, the resulting measurements and image metadata are used to derive a layer of heights in a Google map available online. The experimental results show that the proposed algorithm can estimate an accurate average building height map of thousands of images using Google Street-View Imagery of any city.

Exploring Google to Enhance Reference Services

ERIC Educational Resources Information Center

Jia, Peijun

2011-01-01

Google is currently recognized as the world's most powerful search engine. Google is so powerful and intuitive that one does not need to possess many skills to use it. However, Google is more than just simple search. For those who have special search skills and know Google's superior search features, it becomes an extraordinary tool. To understand…

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.

Calibration View of Earth and the Moon by Mars Color Imager

NASA Image and Video Library

2005-08-22

Three days after the Mars Reconnaissance Orbiter Aug. 12, 2005, launch, the spacecraft was pointed toward Earth and the Mars Color Imager camera was powered up to acquire a suite of images of Earth and the Moon.

Ultrasound-guided central venous access using Google Glass.

PubMed

Wu, Teresa S; Dameff, Christian J; Tully, Jeffrey L

2014-12-01

The use of ultrasound during invasive bedside procedures is quickly becoming the standard of care. Ultrasound machine placement during procedures often requires the practitioner to turn their head during the procedure to view the screen. Such turning has been implicated in unintentional hand movements in novices. Google Glass is a head-mounted computer with a specialized screen capable of projecting images and video into the view of the wearer. Such technology may help decrease unintentional hand movements. Our aim was to evaluate whether or not medical practitioners at various levels of training could use Google Glass to perform an ultrasound-guided procedure, and to explore potential advantages of this technology. Forty participants of varying training levels were randomized into two groups. One group used Google Glass to perform an ultrasound-guided central line. The other group used traditional ultrasound during the procedure. Video recordings of eye and hand movements were analyzed. All participants from both groups were able to complete the procedure without difficulty. Google Glass wearers took longer to perform the procedure at all training levels (medical student year 1 [MS1]: 193 s vs. 77 s, p > 0.5; MS4: 197s vs. 91s, p ≤ 0.05; postgraduate year 1 [PGY1]: 288s vs. 125 s, p > 0.5; PGY3: 151 s vs. 52 s, p ≤ 0.05), and required more needle redirections (MS1: 4.4 vs. 2.0, p > 0.5; MS4: 4.8 vs. 2.8, p > 0.5; PGY1: 4.4 vs. 2.8, p > 0.5; PGY3: 2.0 vs. 1.0, p > 0.5). In this study, it was possible to perform ultrasound-guided procedures with Google Glass. Google Glass wearers, on average, took longer to gain access, and had more needle redirections, but less head movements were noted. Copyright © 2014 Elsevier Inc. All rights reserved.

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.

Imaging spectrometry of the Earth and other solar system bodies

NASA Technical Reports Server (NTRS)

Vane, Gregg

1993-01-01

Imaging spectrometry is a relatively new tool for remote sensing of the Earth and other bodies of the solar system. The technique dates back to the late 1970's and early 1980's. It is a natural extension of the earlier multi-spectral imagers developed for remote sensing that acquire images in a few, usually broad spectral bands. Imaging spectrometers combine aspects of classical spectrometers and imaging systems, making it possible to acquire literally hundreds of images of an object, each image in a separate, narrow spectral band. It is thus possible to perform spectroscopy on a pixel-by-pixel basis with the data acquired with an imaging spectrometer. Two imaging spectrometers have flown in space and several others are planned for future Earth and planetary missions. The French-built Phobos Infrared Spectrometer (ISM) was part of the payload of the Soviet Mars mission in 1988, and the JPL-built Near Infrared Mapping Spectrometer (NIMS) is currently en route to Jupiter aboard the Galileo spacecraft. Several airborne imaging spectrometers have been built in the past decade including the JPL-built Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) which is the only such sensor that covers the full solar reflected portion of the spectrum in narrow, contiguous spectral bands. NASA plans two imaging spectrometers for its Earth Observing System, the Moderate and the High Resolution Imaging Spectrometers (MODIS and HIRIS). A brief overview of the applications of imaging spectrometry to Earth science will be presented to illustrate the value of the tool to remote sensing and indicate the types of measurements that are required. The system design for AVIRS and a planetary imaging spectrometer will be presented to illustrate the engineering considerations and challenges that must be met in building such instruments. Several key sensor technology areas will be discussed in which miniaturization and/or enhanced performance through micromachining and nanofabrication may

Google Scholar Goes to School: The Presence of Google Scholar on College and University Web Sites

ERIC Educational Resources Information Center

Neuhaus, Chris; Neuhaus, Ellen; Asher, Alan

2008-01-01

This study measured the degree of Google Scholar adoption within academia by analyzing the frequency of Google Scholar appearances on 948 campus and library Web sites, and by ascertaining the establishment of link resolution between Google Scholar and library resources. Results indicate a positive correlation between the implementation of Google…

Earth elevation map production and high resolution sensing camera imaging analysis

NASA Astrophysics Data System (ADS)

Yang, Xiubin; Jin, Guang; Jiang, Li; Dai, Lu; Xu, Kai

2010-11-01

The Earth's digital elevation which impacts space camera imaging has prepared and imaging has analysed. Based on matching error that TDI CCD integral series request of the speed of image motion, statistical experimental methods-Monte Carlo method is used to calculate the distribution histogram of Earth's elevation in image motion compensated model which includes satellite attitude changes, orbital angular rate changes, latitude, longitude and the orbital inclination changes. And then, elevation information of the earth's surface from SRTM is read. Earth elevation map which produced for aerospace electronic cameras is compressed and spliced. It can get elevation data from flash according to the shooting point of latitude and longitude. If elevation data between two data, the ways of searching data uses linear interpolation. Linear interpolation can better meet the rugged mountains and hills changing requests. At last, the deviant framework and camera controller are used to test the character of deviant angle errors, TDI CCD camera simulation system with the material point corresponding to imaging point model is used to analyze the imaging's MTF and mutual correlation similarity measure, simulation system use adding cumulation which TDI CCD imaging exceeded the corresponding pixel horizontal and vertical offset to simulate camera imaging when stability of satellite attitude changes. This process is practicality. It can effectively control the camera memory space, and meet a very good precision TDI CCD camera in the request matches the speed of image motion and imaging.

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.

How To: Maximize Google

ERIC Educational Resources Information Center

Branzburg, Jeffrey

2004-01-01

Google is shaking out to be the leading Web search engine, with recent research from Nielsen NetRatings reporting about 40 percent of all U.S. households using the tool at least once in January 2004. This brief article discusses how teachers and students can maximize their use of Google.

Google Scholar's Ghost Authors

ERIC Educational Resources Information Center

Jacso, Peter

2009-01-01

In the journal "The Chronicle of Higher Education," an article by Geoffrey Nunberg criticizes Google's Book Search (GBS), emphasizing that disturbing errors are endemic. He recognizes that for mainstream "googling" purposes, "they don't really care about metadata provided by a library catalog." In perhaps his most discouraging point, linguistics…

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.

What, where and when? Using Google Trends and Google to investigate patient needs and inform pharmacy practice.

PubMed

Hanna, Alan; Hanna, Lezley-Anne

2018-03-30

The aim was to provide a comprehensive overview (using pertinent examples) of the various ways that Google Trends and Google data could inform pharmacy practice. The objectives were to: examine what type of information people search for in relation to a common class of medicines; ascertain where people are directed to (websites) following an initial search for a medicine or medical condition; and establish information about when they search. The methodology differed depending on whether Google Trends or Google was being interrogated, but the search domain was always limited to the United Kingdom. Google Trends was queried, typically for a 5-year time frame, and data downloaded for many search inputs relating to medical conditions (self-treatable and non-self-treatable) and medicines (bought over-the-counter and prescribed). Google was queried and data collected for searches related to 'antibiotics'. Google Trends revealed a previously unknown seasonality pattern for irritable bowel syndrome. Related searches for 'antibiotics' revealed a high level of interest in the appropriateness of concomitant alcohol consumption and queries about what antibiotics are. Largely, people were being directed to reputable websites following their initial search input about a prescription-only medicine. However, searches for over-the-counter medicines were more likely to lead to commercial domains. This is one of the first studies to investigate use of Google Trends and Google in a pharmacy-specific context. It is relevant for practice as it could inform marketing strategies, public health policy and help tailor patient advice and counselling. © 2018 Royal Pharmaceutical Society.

Detection of disturbed earth using hyperspectral LWIR imaging data

NASA Astrophysics Data System (ADS)

Hubbard, Wendy; Bishop, Gary; Gagnon, Jean-Philippe; Lagueux, Philippe; Hannuna, Sion; Campbell, Neill

2010-10-01

The Reststrahlen effect has been investigated for detecting regions of recently disturbed earth, by taking images where metallic objects had been buried in a sandy soil and comparing with images of undisturbed soil. The images were taken with a Long wave Infrared (LWIR) Hyperspectral Sensor, the Hyper-Cam.

Where Did Google Get Its Value?

ERIC Educational Resources Information Center

Caufield, James

2005-01-01

Google's extraordinary success is usually attributed to innovative technology and new business models. By contrast, this paper argues that Google's success is mostly due to its adoption of certain library values. First, Google has refused to adopt the standard practices of the search engine business, practices that compromised service to the user…

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 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.

Low bit rate coding of Earth science images

NASA Technical Reports Server (NTRS)

Kossentini, Faouzi; Chung, Wilson C.; Smith, Mark J. T.

1993-01-01

In this paper, the authors discuss compression based on some new ideas in vector quantization and their incorporation in a sub-band coding framework. Several variations are considered, which collectively address many of the individual compression needs within the earth science community. The approach taken in this work is based on some recent advances in the area of variable rate residual vector quantization (RVQ). This new RVQ method is considered separately and in conjunction with sub-band image decomposition. Very good results are achieved in coding a variety of earth science images. The last section of the paper provides some comparisons that illustrate the improvement in performance attributable to this approach relative the the JPEG coding standard.

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.

Automated cropland mapping of continental Africa using Google Earth Engine cloud computing

NASA Astrophysics Data System (ADS)

Xiong, Jun; Thenkabail, Prasad S.; Gumma, Murali K.; Teluguntla, Pardhasaradhi; Poehnelt, Justin; Congalton, Russell G.; Yadav, Kamini; Thau, David

2017-04-01

's population, but only about 6% of world's irrigation. Net cropland area distribution was 95 Mha during season 1, 117 Mha during season 2, and 84 Mha continuous. About 58% of the rainfed and 39% of the irrigated were single crops (net cropland area without cropland fallows) cropped during either season 1 (January-May) or season 2 (June-September). The ACMA algorithm was deployed on Google Earth Engine (GEE) cloud computing platform and applied on MODIS time-series data from 2003 through 2014 to obtain ACMA-derived cropland layers for these years (ACL2003 to ACL2014). The results indicated that over these twelve years, on average: (a) croplands increased by 1 Mha/yr, and (b) cropland fallows decreased by 1 Mha/year. Cropland areas computed from ACL2014 for the 55 African countries were largely underestimated when compared with an independent source of census-based cropland data, with a root-mean-square error (RMSE) of 3.5 Mha. ACMA demonstrated the ability to hind-cast (past years), now-cast (present year), and forecast (future years) cropland products using MODIS 250-m time-series data rapidly, but currently, insufficient reference data exist to rigorously report trends from these results.

Automated cropland mapping of continental Africa using Google Earth Engine cloud computing

USGS Publications Warehouse

Xiong, Jun N.; Thenkabail, Prasad S.; Gumma, Murali Krishna; Teluguntla, Pardhasaradhi G.; Poehnelt, Justin; Congalton, Russell G.; Yadav, Kamini; Thau, David

2017-01-01

world’s population, but only about 6% of world’s irrigation. Net cropland area distribution was 95 Mha during season 1, 117 Mha during season 2, and 84 Mha continuous. About 58% of the rainfed and 39% of the irrigated were single crops (net cropland area without cropland fallows) cropped during either season 1 (January-May) or season 2 (June-September). The ACMA algorithm was deployed on Google Earth Engine (GEE) cloud computing platform and applied on MODIS time-series data from 2003 through 2014 to obtain ACMA-derived cropland layers for these years (ACL2003 to ACL2014). The results indicated that over these twelve years, on average: (a) croplands increased by 1 Mha/yr, and (b) cropland fallows decreased by 1 Mha/year. Cropland areas computed from ACL2014 for the 55 African countries were largely underestimated when compared with an independent source of census-based cropland data, with a root-mean-square error (RMSE) of 3.5 Mha. ACMA demonstrated the ability to hind-cast (past years), now-cast (present year), and forecast (future years) cropland products using MODIS 250-m time-series data rapidly, but currently, insufficient reference data exist to rigorously report trends from these results.

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

jsc2017m001088_Top-17-Earth-Images-of-2017

NASA Image and Video Library

2017-12-27

Top 17 Earth Images of 2017 The astronauts and cosmonauts on the International Space Station take pictures of Earth out their windows nearly every day, and over a year that adds up to thousands of photos. The people at the Earth Science and Remote Sensing Unit at NASA’s Johnson Space Center in Houston had the enviable job of going through this year’s crop to pick their top 17 photos of Earth for 2017—here’s what they chose! Gateway to Astronaut Photography of Earth: https://eol.jsc.nasa.gov/

Earth-from-Luna Limb Imager (ELLI) for Deep Space Gateway

NASA Astrophysics Data System (ADS)

Gorkavyi, N.; DeLand, M.

2018-02-01

The new type of limb imager with a high-frequency imaging proposed for Deep Space Gateway. Each day this CubeSat' scale imager will generate the global 3D model of the aerosol component of the Earth's atmosphere and Polar Mesospheric Clouds.

Googling trends in conservation biology.

PubMed

Proulx, Raphaël; Massicotte, Philippe; Pépino, Marc

2014-02-01

Web-crawling approaches, that is, automated programs data mining the internet to obtain information about a particular process, have recently been proposed for monitoring early signs of ecosystem degradation or for establishing crop calendars. However, lack of a clear conceptual and methodological framework has prevented the development of such approaches within the field of conservation biology. Our objective was to illustrate how Google Trends, a freely accessible web-crawling engine, can be used to track changes in timing of biological processes, spatial distribution of invasive species, and level of public awareness about key conservation issues. Google Trends returns the number of internet searches that were made for a keyword in a given region of the world over a defined period. Using data retrieved online for 13 countries, we exemplify how Google Trends can be used to study the timing of biological processes, such as the seasonal recurrence of pollen release or mosquito outbreaks across a latitudinal gradient. We mapped the spatial extent of results from Google Trends for 5 invasive species in the United States and found geographic patterns in invasions that are consistent with their coarse-grained distribution at state levels. From 2004 through 2012, Google Trends showed that the level of public interest and awareness about conservation issues related to ecosystem services, biodiversity, and climate change increased, decreased, and followed both trends, respectively. Finally, to further the development of research approaches at the interface of conservation biology, collective knowledge, and environmental management, we developed an algorithm that allows the rapid retrieval of Google Trends data. © 2013 Society for Conservation Biology.

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

Google Tools in the Classroom

NASA Astrophysics Data System (ADS)

Albee, E. M.; Koons, P. O.; Schauffler, M.; Zhu, Y.; Segee, B. E.

2009-12-01

The Maine Learning Technology Initiative provides every seventh and eighth grade student in the state with MacBook laptop computers. Limitless education possibilities exist with the inclusion of Google Tools and laptops as learning tools in our modern classrooms. Google Applications allow students to create documents, spreadsheets, charts, graphs, forms, and presentations and easily allows the sharing of information with their fellow classmates and teachers. These applications invite the use of inquiry and critical thinking skills, collaboration among peers, and subject integration to teach students crucial concepts. The benefits for teachers extend into the realm of using Google sites to easily create a teacher website and blog to upload classroom information and create a communication connection for parents and students as well as collaborations between the teachers and University researchers and educators. Google Applications further enhances the possibilities for learning, sharing a wealth of information, and enhancing communication inside and outside of the classroom.

Where on Earth...? MISR Mystery Image Quiz #24: Shandong Province, China

NASA Image and Video Library

2010-11-03

This image of the Shandong Province, China was acquired by the Multi-angle Imaging SpectroRadiometer instrument aboard NASA Terra spacecraft. This image is from the MISR Where on Earth...? Mystery Quiz #24.

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).

The use of multisensor images for Earth Science applications

NASA Technical Reports Server (NTRS)

Evans, D.; Stromberg, B.

1983-01-01

The use of more than one remote sensing technique is particularly important for Earth Science applications because of the compositional and textural information derivable from the images. The ability to simultaneously analyze images acquired by different sensors requires coregistration of the multisensor image data sets. In order to insure pixel to pixel registration in areas of high relief, images must be rectified to eliminate topographic distortions. Coregistered images can be analyzed using a variety of multidimensional techniques and the acquired knowledge of topographic effects in the images can be used in photogeologic interpretations.

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

The EarthCARE multi spectral imager thermal infrared optical unit

NASA Astrophysics Data System (ADS)

Chang, M. P. J. L.; Woods, D.; Baister, Guy; Lobb, Dan; Wood, Trevor

2017-11-01

The EarthCARE satellite mission objective is the observation of clouds and aerosols from low Earth orbit. The key spatial context providing instrument within the payload suite of 4 instruments is the Multi-Spectral Imager (MSI), previously described in [1]. The MSI is intended to provide information on the horizontal variability of the atmospheric conditions and to identify e.g. cloud type, textures, and temperature. It will form Earth images at 500m ground sample distance (GSD) over a swath width of 150km; it will image Earth in 7 spectral bands: one visible, one near-IR, two short-wave IR and three thermal IR. The instrument will be comprised of two key parts: • a visible-NIR-SWIR (VNS) optical unit radiometrically calibrated using a sun illuminated quasivolume diffuser and shutter system • a thermal IR (TIR) optical unit radiometrically calibrated using cold space and an internal black-body. This paper, being the first of a sequence of two, will provide an overview of the MSI and enter into more detail the critical performance parameters and detailed design the MSI TIR optical design. The TIR concept is to provide pushbroom imaging of its 3 bands through spectral separation from a common aperture. The result is an efficient, well controlled optical design without the need for multiple focal plane arrays. The designed focal plane houses an area array detector and will meet a challenging set of requirements, including radiometric resolution, accuracy, distortion and MTF.

Feasibility of digital imaging to characterize earth materials : part 2.

DOT National Transportation Integrated Search

2012-06-06

This study demonstrated the feasibility of digital imaging to characterize earth materials. Two rapid, relatively low cost image-based methods were developed for determining the grain size distribution of soils and aggregates. The first method, calle...

Feasibility of digital imaging to characterize earth materials : part 6.

DOT National Transportation Integrated Search

2012-06-06

This study demonstrated the feasibility of digital imaging to characterize earth materials. Two rapid, relatively low cost image-based methods were developed for determining the grain size distribution of soils and aggregates. The first method, calle...

Feasibility of digital imaging to characterize earth materials : part 3.

DOT National Transportation Integrated Search

2012-06-06

This study demonstrated the feasibility of digital imaging to characterize earth materials. Two rapid, relatively low cost image-based methods were developed for determining the grain size distribution of soils and aggregates. The first method, calle...

Feasibility of digital imaging to characterize earth materials : part 1.

DOT National Transportation Integrated Search

2012-06-06

This study demonstrated the feasibility of digital imaging to characterize earth materials. Two rapid, relatively low cost image-based methods were developed for determining the grain size distribution of soils and aggregates. The first method, calle...

Feasibility of digital imaging to characterize earth materials : part 4.

DOT National Transportation Integrated Search

2012-06-06

This study demonstrated the feasibility of digital imaging to characterize earth materials. Two rapid, relatively low cost image-based methods were developed for determining the grain size distribution of soils and aggregates. The first method, calle...

Feasibility of digital imaging to characterize earth materials : part 5.

DOT National Transportation Integrated Search

2012-05-06

This study demonstrated the feasibility of digital imaging to characterize earth materials. Two rapid, relatively low cost image-based methods were developed for determining the grain size distribution of soils and aggregates. The first method, calle...

Imaging plasmas at the Earth and other planets

NASA Astrophysics Data System (ADS)

Mitchell, D. G.

2006-05-01

The field of space physics, both at Earth and at other planets, was for decades a science based on local observations. By stitching together measurements of plasmas and fields from multiple locations either simultaneously or for similar conditions over time, and by comparing those measurements against models of the physical systems, great progress was made in understanding the physics of Earth and planetary magnetospheres, ionospheres, and their interactions with the solar wind. However, the pictures of the magnetospheres were typically statistical, and the large-scale global models were poorly constrained by observation. This situation changed dramatically with global auroral imaging, which provided snapshots and movies of the effects of field aligned currents and particle precipitation over the entire auroral oval during quiet and disturbed times. And with the advent of global energetic neutral atom (ENA) and extreme ultraviolet (EUV) imaging, global constraints have similarly been added to ring current and plasmaspheric models, respectively. Such global constraints on global models are very useful for validating the physics represented in those models, physics of energy and momentum transport, electric and magnetic field distribution, and magnetosphere-ionosphere coupling. These techniques are also proving valuable at other planets. For example with Hubble Space Telescope imaging of Jupiter and Saturn auroras, and ENA imaging at Jupiter and Saturn, we are gaining new insights into the magnetic fields, gas-plasma interactions, magnetospheric dynamics, and magnetosphere-ionosphere coupling at the giant planets. These techniques, especially ENA and EUV imaging, rely on very recent and evolving technological capabilities. And because ENA and EUV techniques apply to optically thin media, interpretation of their measurements require sophisticated inversion procedures, which are still under development. We will discuss the directions new developments in imaging are

Corner Office: Google's Dan Clancy

ERIC Educational Resources Information Center

Albanese, Andrew Richard; Oder, Norman

2009-01-01

This article presents an interview with Dan Clancy, engineering director for Google Book Search. In this interview, Clancy talks about the pending Google Book Search settlement, involving millions of volumes digitized from libraries, which drew a lawsuit from the Association of American Publishers and the Authors Guild. He also discusses pricing,…

Google Scholar: The 800-Pound Gorilla in the Room

ERIC Educational Resources Information Center

Shapiro, Steven

2012-01-01

There is a "clash of civilizations" going on in the information field--a clash characterized by a brash upstart, Google, and its attendant creations, Google Scholar and Google Books, and the old guard represented by the library world. Librarians who deprecate Google Scholar or simply ignore the Google phenomenon do so at their own risk. Google…

Tag Team Tech: What Makes Google Tick.

ERIC Educational Resources Information Center

Janes, Joseph

2002-01-01

The Google search engine is growing in popularity and usually shines in performance ratings. This article summarizes findings from a technical paper written by Google's developers in 1998 before anyone had seen Google. Suggests that a careful reader of the paper will be rewarded with a deeper appreciation of the designers' ideas and…

Taking advantage of Google's Web-based applications and services.

PubMed

Brigham, Tara J

2014-01-01

Google is a company that is constantly expanding and growing its services and products. While most librarians possess a "love/hate" relationship with Google, there are a number of reasons you should consider exploring some of the tools Google has created and made freely available. Applications and services such as Google Docs, Slides, and Google+ are functional and dynamic without the cost of comparable products. This column will address some of the issues users should be aware of before signing up to use Google's tools, and a description of some of Google's Web applications and services, plus how they can be useful to librarians in health care.

Google Maps: You Are Here

ERIC Educational Resources Information Center

Jacobsen, Mikael

2008-01-01

Librarians use online mapping services such as Google Maps, MapQuest, Yahoo Maps, and others to check traffic conditions, find local businesses, and provide directions. However, few libraries are using one of Google Maps most outstanding applications, My Maps, for the creation of enhanced and interactive multimedia maps. My Maps is a simple and…

Auroral x-ray imaging from high- and low-Earth orbit

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

McKenzie, D.L.; Gorney, D.J.; Imhof, W.L.

Observations of bremsstrahlung x rays emitted by energetic electrons impacting the Earth's atmosphere can be used for remotely sensing the morphology, intensity, and energy spectra of electron precipitation from the magnetosphere. The utility of the technique is derived from the broad energy range of observable x rays (2 to > 100 KeV), the simple emission process, the large x-ray mean free path in the atmosphere, and negligible background. Two auroral x-ray imagers, developed for future spaceflights, are discussed. The Polar Ionospheric X-Ray Imaging Experiment is scheduled for launch on the NASA International Solar-Terrestrial Physics/Global Geospace Science program POLAR satellite inmore » 1994. The POLAR orbit, with an apogee and perigee of 9 and 1.8 R[sub e] (Earth radii), respectively, affords the opportunity to image the aurora from a high altitude above the north pole continuously for several hours. The Magnetospheric Atmospheric X-Ray Imaging Experiment (MAXIE) was launched aboard the NOAA-I satellite on August 8, 1993. The 800-km polar orbit passes over both the northern and southern auroral zones every 101 min. MAXIE will be capable of obtaining multiple images of the same auroral region during a single satellite orbit. The experimental approaches used to exploit these very different orbits for remote sensing of the Earth's auroral zones are emphasized.« less

Image Segmentation Analysis for NASA Earth Science Applications

NASA Technical Reports Server (NTRS)

Tilton, James C.

2010-01-01

NASA collects large volumes of imagery data from satellite-based Earth remote sensing sensors. Nearly all of the computerized image analysis of this data is performed pixel-by-pixel, in which an algorithm is applied directly to individual image pixels. While this analysis approach is satisfactory in many cases, it is usually not fully effective in extracting the full information content from the high spatial resolution image data that s now becoming increasingly available from these sensors. The field of object-based image analysis (OBIA) has arisen in recent years to address the need to move beyond pixel-based analysis. The Recursive Hierarchical Segmentation (RHSEG) software developed by the author is being used to facilitate moving from pixel-based image analysis to OBIA. The key unique aspect of RHSEG is that it tightly intertwines region growing segmentation, which produces spatially connected region objects, with region object classification, which groups sets of region objects together into region classes. No other practical, operational image segmentation approach has this tight integration of region growing object finding with region classification This integration is made possible by the recursive, divide-and-conquer implementation utilized by RHSEG, in which the input image data is recursively subdivided until the image data sections are small enough to successfully mitigat the combinatorial explosion caused by the need to compute the dissimilarity between each pair of image pixels. RHSEG's tight integration of region growing object finding and region classification is what enables the high spatial fidelity of the image segmentations produced by RHSEG. This presentation will provide an overview of the RHSEG algorithm and describe how it is currently being used to support OBIA or Earth Science applications such as snow/ice mapping and finding archaeological sites from remotely sensed data.

NASA Spacecraft Images One of Earth Iceberg Incubators

NASA Image and Video Library

2012-04-13

Acquired by NASA Terra spacecraft, this image shows the west coast of Greenland, one of Earth premiere incubators for icebergs -- large blocks of land ice that break off from glaciers or ice shelves and float in the ocean.

Evaluation of Google Glass Technical Limitations on Their Integration in Medical Systems.

PubMed

Martinez-Millana, Antonio; Bayo-Monton, Jose-Luis; Lizondo, Aroa; Fernandez-Llatas, Carlos; Traver, Vicente

2016-12-15

Google Glass is a wearable sensor presented to facilitate access to information and assist while performing complex tasks. Despite the withdrawal of Google in supporting the product, today there are multiple applications and much research analyzing the potential impact of this technology in different fields of medicine. Google Glass satisfies the need of managing and having rapid access to real-time information in different health care scenarios. Among the most common applications are access to electronic medical records, display monitorizations, decision support and remote consultation in specialties ranging from ophthalmology to surgery and teaching. The device enables a user-friendly hands-free interaction with remote health information systems and broadcasting medical interventions and consultations from a first-person point of view. However, scientific evidence highlights important technical limitations in its use and integration, such as failure in connectivity, poor reception of images and automatic restart of the device. This article presents a technical study on the aforementioned limitations (specifically on the latency, reliability and performance) on two standard communication schemes in order to categorize and identify the sources of the problems. Results have allowed us to obtain a basis to define requirements for medical applications to prevent network, computational and processing failures associated with the use of Google Glass.

Evaluation of Google Glass Technical Limitations on Their Integration in Medical Systems

PubMed Central

Martinez-Millana, Antonio; Bayo-Monton, Jose-Luis; Lizondo, Aroa; Fernandez-Llatas, Carlos; Traver, Vicente

2016-01-01

Google Glass is a wearable sensor presented to facilitate access to information and assist while performing complex tasks. Despite the withdrawal of Google in supporting the product, today there are multiple applications and much research analyzing the potential impact of this technology in different fields of medicine. Google Glass satisfies the need of managing and having rapid access to real-time information in different health care scenarios. Among the most common applications are access to electronic medical records, display monitorizations, decision support and remote consultation in specialties ranging from ophthalmology to surgery and teaching. The device enables a user-friendly hands-free interaction with remote health information systems and broadcasting medical interventions and consultations from a first-person point of view. However, scientific evidence highlights important technical limitations in its use and integration, such as failure in connectivity, poor reception of images and automatic restart of the device. This article presents a technical study on the aforementioned limitations (specifically on the latency, reliability and performance) on two standard communication schemes in order to categorize and identify the sources of the problems. Results have allowed us to obtain a basis to define requirements for medical applications to prevent network, computational and processing failures associated with the use of Google Glass. PMID:27983691

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.

DSCOVR/EPIC Images and Science: A New Way to View the Entire Sunlit Earth From A Sun-Earth Lagrange-1 Orbit

NASA Astrophysics Data System (ADS)

Herman, J. R.; Marshak, A.; Szabo, A.

2015-12-01

The DSCOVR mission was launched into a Sun-Earth Lagrange-1 orbit 1.5 million kilometers from earth in February 2015 onboard a SpaceX Falcon-9 rocket. The solar wind and earth science instruments were tested during the 4.5 month journey to L-1. The first data were obtained during the June-July commissioning phase, which included the first moderate resolution (10 km) color images of the entire sunlit earth, color images of the Moon, and scientific data from 10 narrow band filters (317.5, 325, 340, 388, 443, 551, 680, 687.75, 764, and 779.5 nm). Three of these filters were used to construct the color images (443, 551, 680 nm) based on the average eye response histogram of the sunlit earth. This talk will discuss some of the issues involved in deriving science quality data for global ozone, the aerosol index (dust, smoke, and volcanic ash), cloud amounts and reflectivity, and cloud height (measured from the O2 A- and B-bands). As with most new satellites, the science data are preliminary.

The Earth and Moon As Seen by 2001 Mars Odyssey's Thermal Emission Imaging System

NASA Technical Reports Server (NTRS)

2001-01-01

2001 Mars Odyssey's Thermal Emission Imaging System (THEMIS) took this portrait of the Earth and its companion Moon, using the infrared camera, one of two cameras in the instrument. It was taken at a distance of 3,563,735 kilometers (more than 2 million miles) on April 19, 2001 as the 2001 Mars Odyssey spacecraft left the Earth. From this distance and perspective the camera was able to acquire an image that directly shows the true distance from the Earth to the Moon. The Earth's diameter is about 12,750 km, and the distance from the Earth to the Moon is about 385,000 km, corresponding to 30 Earth diameters. The dark region seen on Earth in the infrared temperature image is the cold south pole, with a temperature of minus 50 degrees Celsius (minus 58 degrees Fahrenheit). The small bright region above it is warm Australia. This image was acquired using the 9.1 um infrared filter, one of nine filters that the instrument will use to map the mineral composition and temperature of the martian surface. From this great distance, each picture element (pixel) in the image corresponds to a region 900 by 900 kilometers or greater in size or about size of the state of Texas. Once Odyssey reaches Mars orbit each infrared pixel will cover a region only 100 by 100 meters on the surface, about the size of a major league baseball field.

Google Analytics: Single Page Traffic Reports

EPA Pesticide Factsheets

These are pages that live outside of Google Analytics (GA) but allow you to view GA data for any individual page on either the public EPA web or EPA intranet. You do need to log in to Google Analytics to view them.

Technologies Required to Image Earth 2.0 with a Space Coronagraph

NASA Astrophysics Data System (ADS)

Siegler, Nicholas

2017-01-01

NASA's Exoplanet Exploration Program (ExEP) guides the development of technology that enables the direct imaging and characterization of exo-Earths in the habitable zone of their stars for future space observatories. Here we present the coronagraph portion of the 2017 ExEP Technology Gap List, an annual update to ExEP's list of of technologies, to be advanced in the next 1-5 years. A coronagraph is an internal occulter that allows a space telescope to achieve exo-Earth imaging contrast requirements (more than 10 billion) by blocking on-axis starlight while allowing the reflected light of off-axis exoplanets be detected. Building and operating a space coronagraph capable of imaging an exo-Earth will require new technologies beyond those of WFIRST, the first high-contrast conronagraph in space. We review the current state-of-the-art performance of space coronagraphs and the performance level that must be achieved for a coronagraph..

SRTM Radar Image, Wrapped Color as Height/EarthKam Optical Honolulu, Hawaii

NASA Technical Reports Server (NTRS)

2000-01-01

These two images of the eastern part of the island of Oahu, Hawaii provide information on regional topography and show the relationship between urban development and sensitive ecosystems. On the left is a topographic radar image collected by the Shuttle Radar Topography Mission (SRTM.) On the right is an optical image acquired by a digital camera on the Space Shuttle Endeavour, which carried SRTM. Features of interest in this scene include Diamond Head (an extinct volcano at the lower center), Waikiki Beach (just left of Diamond Head), the Punchbowl National Cemetery (another extinct volcano, at the foot of the Koolau Mountains), downtown Honolulu and Honolulu airport (lower left of center), and Pearl Harbor (at the left edge.)

The topography shows the steep, high central part of the island surrounded by flatter coastal areas. The optical image shows the urban areas and a darker, forested region on the mountain slopes. The clouds in the optical image and the black areas on the topographic image are both a result of the steep topography. In this tropical region, high mountain peaks are usually covered in clouds. These steep peaks also cause shadows in the radar data, resulting in missing data 'holes.' A second pass over the island was obtained by SRTM and will be used to fill in the holes.

The left image combines two types of SRTM data. Brightness corresponds to the strength of the radar signal reflected from the ground, while colors show the elevation. Each color cycle (from pink through blue and back to pink) represents 400 meters (1,300 feet) of elevation difference, like the contour lines on a topographic map. This image contains about 2,400 meters (8,000 feet) of total relief. The optical image was acquired by the Shuttle Electronic Still Camera with a lens focal length of 64 millimeters (2.5 inches) for the Earth Knowledge Acquired by Middle school students (EarthKAM) project. EarthKAM has flown on five space shuttle missions since 1996. Additional

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…

The Direct Imaging Search for Earth 2.0: Quantifying Biases and Planetary False Positives

NASA Astrophysics Data System (ADS)

Guimond, Claire Marie; Cowan, Nicolas B.

2018-06-01

Direct imaging is likely the best way to characterize the atmospheres of Earth-sized exoplanets in the habitable zone of Sun-like stars. Previously, Stark et al. estimated the Earth twin yield of future direct imaging missions, such as LUVOIR and HabEx. We extend this analysis to other types of planets, which will act as false positives for Earth twins. We define an Earth twin as any exoplanet within half an e-folding of 1 au in semimajor axis and 1 {R}\\oplus in planetary radius, orbiting a G-dwarf. Using Monte Carlo analyses, we quantify the biases and planetary false-positive rates of Earth searches. That is, given a pale dot at the correct projected separation and brightness to be a candidate Earth, what are the odds that it is, in fact, an Earth twin? Our notional telescope has a diameter of 10 m, an inner working angle of 3λ/D, and an outer working angle of 10λ/D (62 mas and 206 mas at 1.0 μm). With no precursor knowledge and one visit per star, 77% of detected candidate Earths are actually un-Earths; their mean radius is 2.3 {R}\\oplus , a sub-Neptune. The odds improve if we image every planet at its optimal orbital phase, either by relying on precursor knowledge, or by performing multi-epoch direct imaging. In such a targeted search, 47% of detected Earth twin candidates are false positives, and they have a mean radius of 1.7 {R}\\oplus . The false-positive rate is insensitive to stellar spectral type and the assumption of circular orbits.

The Long-Wave Infrared Earth Image as a Pointing Reference for Deep-Space Optical Communications

NASA Astrophysics Data System (ADS)

Biswas, A.; Piazzolla, S.; Peterson, G.; Ortiz, G. G.; Hemmati, H.

2006-11-01

Optical communications from space require an absolute pointing reference. Whereas at near-Earth and even planetary distances out to Mars and Jupiter a laser beacon transmitted from Earth can serve as such a pointing reference, for farther distances extending to the outer reaches of the solar system, the means for meeting this requirement remains an open issue. We discuss in this article the prospects and consequences of utilizing the Earth image sensed in the long-wave infrared (LWIR) spectral band as a beacon to satisfy the absolute pointing requirements. We have used data from satellite-based thermal measurements of Earth to synthesize images at various ranges and have shown the centroiding accuracies that can be achieved with prospective LWIR image sensing arrays. The nonuniform emissivity of Earth causes a mispointing bias error term that exceeds a provisional pointing budget allocation when using simple centroiding algorithms. Other issues related to implementing thermal imaging of Earth from deep space for the purposes of providing a pointing reference are also reported.

An augmented-reality edge enhancement application for Google Glass.

PubMed

Hwang, Alex D; Peli, Eli

2014-08-01

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

Radar Images of the Earth and the World Wide Web

NASA Technical Reports Server (NTRS)

Chapman, B.; Freeman, A.

1995-01-01

A perspective of NASA's Jet Propulsion Laboratory as a center of planetary exploration, and its involvement in studying the earth from space is given. Remote sensing, radar maps, land topography, snow cover properties, vegetation type, biomass content, moisture levels, and ocean data are items discussed related to earth orbiting satellite imaging radar. World Wide Web viewing of this content is discussed.

Blazing a Trail: Towards Imaging Super-Earths from the Ground and Space

NASA Astrophysics Data System (ADS)

Meyer, M. R.; Quanz, S. P.; Kasper, M.; Guyon, O.; Monnier, J.

2017-11-01

We will review recent progress in imaging super-earths around the very nearest stars, new opportunities for 10 microns imaging, contributions JWST will make to imaging ice giants, and complementary work to be done by WFIRST-AFTA.

The Google Online Marketing Challenge and Research Opportunities

ERIC Educational Resources Information Center

Neale, Larry; Treiblmaier, Horst; Henderson, Vani; Hunter, Lee; Hudson, Karen; Murphy, Jamie

2009-01-01

The Google Online Marketing Challenge is an ongoing collaboration between Google and academics, to give students experiential learning. The Challenge gives student teams US$200 in AdWords, Google's flagship advertising product, to develop online marketing campaigns for actual businesses. The end result is an engaging in-class exercise that…

Lithospheric Subduction on Earth and Venus?

NASA Astrophysics Data System (ADS)

Sandwell, D. T.; Garcia, E.; Stegman, D. R.; Schubert, G.

2016-12-01

There are three mechanisms by which terrestrial planets can shed excess heat: conduction across a surface thermal boundary layer; advection of heat through volcanic pipes; and mobile plates/subduction. On the Earth about 30% is released by conduction and 70% by subduction. The dominant mode of heat transport on Venus is largely unknown. Plate flexure models rule out significant heat loss by conduction and the resurfacing from active volcanism is in discordance with a surface age of 600 Ma. There are 9000 km of trenches on Venus that may have been subduction sites but they do not appear active today and are only 25% of the length of the subduction zones on the Earth. Turcotte and others have proposed an episodic recycling model that has short bursts ( 150 Ma) of plate tectonic activity followed by long periods ( 450 Ma) of stagnant lid convection. This talk will review the arguments for and against subduction zones on Venus and discuss possible new satellite observations that could help resolve the subduction issue. Figure Caption. (a) Global mosaic of Magellan SAR imagery. (b) Zoom of area along the Artemis trench, which has similar topography and fracture patterns as the Aleutian subduction zone on Earth. Trench and outer rise lines were digitized from the matching topography image (not shown). The Magellan SAR imagery and topography, displayed on Google Earth, can be downloaded at http://topex.ucsd.edu/venus/index.html

A Google Official Stresses the Positive

ERIC Educational Resources Information Center

Chronicle of Higher Education, 2005

2005-01-01

What will Google do next? Representatives of the company divulge few details of their projects -- a policy that, in the case of its partnerships with university libraries, probably only fuels the buzz. In this interview, Adam M. Smith, a senior business-product manager, discusses Google's work with publishers and libraries on expanding its…

Imaging of near-Earth space plasma.

PubMed

Mitchell, Cathryn N

2002-12-15

This paper describes the technique of imaging the ionosphere using tomographic principles. It reports on current developments and speculates on the future of this research area. Recent developments in computing and ionospheric measurement, together with the sharing of data via the internet, now allow us to envisage a time when high-resolution, real-time images and 'movies' of the ionosphere will be possible for radio communications planning. There is great potential to use such images for improving our understanding of the physical processes controlling the behaviour of the ionosphere. While real-time images and movies of the electron concentration are now almost possible, forecasting of ionospheric morphology is still in its early stages. It has become clear that the ionosphere cannot be considered as a system in isolation, and consequently new research projects to link together models of the solar-terrestrial system, including the Sun, solar wind, magnetosphere, ionosphere and thermosphere, are now being proposed. The prospect is now on the horizon of assimilating data from the entire solar-terrestrial system to produce a real-time computer model and 'space weather' forecast. The role of tomography in imaging beyond the ionosphere to include the whole near-Earth space-plasma realm is yet to be realized, and provides a challenging prospect for the future. Finally, exciting possibilities exist in applying such methods to image the atmospheres and ionospheres of other planets.

An earth imaging camera simulation using wide-scale construction of reflectance surfaces

NASA Astrophysics Data System (ADS)

Murthy, Kiran; Chau, Alexandra H.; Amin, Minesh B.; Robinson, M. Dirk

2013-10-01

Developing and testing advanced ground-based image processing systems for earth-observing remote sensing applications presents a unique challenge that requires advanced imagery simulation capabilities. This paper presents an earth-imaging multispectral framing camera simulation system called PayloadSim (PaySim) capable of generating terabytes of photorealistic simulated imagery. PaySim leverages previous work in 3-D scene-based image simulation, adding a novel method for automatically and efficiently constructing 3-D reflectance scenes by draping tiled orthorectified imagery over a geo-registered Digital Elevation Map (DEM). PaySim's modeling chain is presented in detail, with emphasis given to the techniques used to achieve computational efficiency. These techniques as well as cluster deployment of the simulator have enabled tuning and robust testing of image processing algorithms, and production of realistic sample data for customer-driven image product development. Examples of simulated imagery of Skybox's first imaging satellite are shown.

Advances in target imaging of deep Earth structure

NASA Astrophysics Data System (ADS)

Masson, Y.; Romanowicz, B. A.; Clouzet, P.

2015-12-01

A new generation of global tomographic models (Lekić and Romanowicz, 2011; French et al, 2013, 2014) has emerged with the development of accurate numerical wavefield computations in a 3D earth combined with access to enhanced HPC capabilities. These models have sharpened up mantle images and unveiled relatively small scale structures that were blurred out in previous generation models. Fingerlike structures have been found at the base of the oceanic asthenosphere, and vertically oriented broad low velocity plume conduits extend throughout the lower mantle beneath those major hotspots that are located within the perimeter of the deep mantle large low shear velocity provinces (LLSVPs). While providing new insights into our understanding of mantle dynamics, the detailed morphology of these features, requires further efforts to obtain higher resolution images. The focus of our ongoing effort is to develop advanced tomographic methods to image remote regions of the Earth at fine scales. We have developed an approach in which distant sources (located outside of the target region) are replaced by an equivalent set of local sources located at the border of the computational domain (Masson et al., 2014). A limited number of global simulations in a reference 3D earth model is then required. These simulations are computed prior to the regional inversion, while iterations of the model need to be performed only within the region of interest, potentially allowing us to include shorter periods at limited additional computational cost. Until now, the application was limited to a distribution of receivers inside the target region. This is particularly suitable for studies of upper mantle structure in regions with dense arrays (e.g. see our companion presentation Clouzet et al., this Fall AGU). Here we present our latest development that now can include teleseismic data recorded outside the imaged region. This allows us to perform regional waveform tomography in the situation where

Disaster medicine through Google Glass.

PubMed

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

2015-06-01

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

Google+ and the Commodification of Cool

ERIC Educational Resources Information Center

Thomas, Lisa Carlucci

2011-01-01

This summer's "make a statement" statement was simple to understand: "I have moved." Facebook friends and colleagues marked their mass exodus from the social networking giant with these words as they left to start a new colony of peers on the newly announced Google+ (Google Plus). G+, as it is abbreviated, offered an appealing alternative from the…

A laboratory demonstration of the capability to image an Earth-like extrasolar planet.

PubMed

Trauger, John T; Traub, Wesley A

2007-04-12

The detection and characterization of an Earth-like planet orbiting a nearby star requires a telescope with an extraordinarily large contrast at small angular separations. At visible wavelengths, an Earth-like planet would be 1 x 10(-10) times fainter than the star at angular separations of typically 0.1 arcsecond or less. There are several proposed space telescope systems that could, in principle, achieve this. Here we report a laboratory experiment that reaches these limits. We have suppressed the diffracted and scattered light near a star-like source to a level of 6 x 10(-10) times the peak intensity in individual coronagraph images. In a series of such images, together with simple image processing, we have effectively reduced this to a residual noise level of about 0.1 x 10(-10). This demonstrates that a coronagraphic telescope in space could detect and spectroscopically characterize nearby exoplanetary systems, with the sensitivity to image an 'Earth-twin' orbiting a nearby star.

Operational GPS Imaging System at Multiple Scales for Earth Science and Monitoring of Geohazards

NASA Astrophysics Data System (ADS)

Blewitt, Geoffrey; Hammond, William; Kreemer, Corné

2016-04-01

Toward scientific targets that range from slow deep Earth processes to geohazard rapid response, our operational GPS data analysis system produces smooth, yet detailed maps of 3-dimensional land motion with respect to our Earth's center of mass at multiple spatio-temporal scales with various latencies. "GPS Imaging" is implemented operationally as a back-end processor to our GPS data processing facility, which uses JPL's GIPSY OASIS II software to produce positions from 14,000 GPS stations in ITRF every 5 minutes, with coordinate precision that gradually improves as latency increases upward from 1 hour to 2 weeks. Our GPS Imaging system then applies sophisticated signal processing and image filtering techniques to generate images of land motion covering our Earth's continents with high levels of robustness, accuracy, spatial resolution, and temporal resolution. Techniques employed by our GPS Imaging system include: (1) similarity transformation of polyhedron coordinates to ITRF with optional common-mode filtering to enhance local transient signal to noise ratio, (2) a comprehensive database of ~100,000 potential step events based on earthquake catalogs and equipment logs, (3) an automatic, robust, and accurate non-parametric estimator of station velocity that is insensitive to prevalent step discontinuities, outliers, seasonality, and heteroscedasticity; (4) a realistic estimator of velocity error bars based on subsampling statistics; (5) image processing to create a map of land motion that is based on median spatial filtering on the Delauney triangulation, which is effective at despeckling the data while faithfully preserving edge features; (6) a velocity time series estimator to assist identification of transient behavior, such as unloading caused by drought, and (7) a method of integrating InSAR and GPS for fine-scale seamless imaging in ITRF. Our system is being used to address three main scientific focus areas, including (1) deep Earth processes, (2

Magellan radar image compared to high resolution Earth-based image of Venus

NASA Technical Reports Server (NTRS)

1990-01-01

A strip of a Magellan radar image (left) is compared to a high resolution Earth-based radar image of Venus, obtained by the U.S. National Astronomy and Ionosphere Center's Arecibo Observatory in Puerto Rico. The small white box in the Arecibo image corresponds to the Magellan image. This portion of the Magellan imagery shows a small region on the east flank of a major volcanic upland called Beta Regio. The image is centered at 23 degrees north latitude and 286.7 degrees east longitude. The ridge and valley network in the middle part of the image is formed by intersecting faults which have broken the Venusian crust into a complex deformed type of surface called tessera, the Latin word for tile. The parallel mountains and valleys resemble the Basin and Range Province in the western United States. The irregular dark patch near the top of the image is a smooth surface, probably formed, according to scientists, by lava flows in a region about 10 kilometers (6 miles) across. Similar dark sur

Using Google Glass in Surgical Settings: Systematic Review

PubMed Central

Wei, Nancy J; Dougherty, Bryn; Myers, Aundria

2018-01-01

Background In recent years, wearable devices have become increasingly attractive and the health care industry has been especially drawn to Google Glass because of its ability to serve as a head-mounted wearable device. The use of Google Glass in surgical settings is of particular interest due to the hands-free device potential to streamline workflow and maintain sterile conditions in an operating room environment. Objective The aim is to conduct a systematic evaluation of the literature on the feasibility and acceptability of using Google Glass in surgical settings and to assess the potential benefits and limitations of its application. Methods The literature was searched for articles published between January 2013 and May 2017. The search included the following databases: PubMed MEDLINE, Embase, Cumulative Index to Nursing and Allied Health Literature, PsycINFO (EBSCO), and IEEE Xplore. Two reviewers independently screened titles and abstracts and assessed full-text articles. Original research articles that evaluated the feasibility, usability, or acceptability of using Google Glass in surgical settings were included. This review was completed following the Preferred Reporting Results of Systematic Reviews and Meta-Analyses guidelines. Results Of the 520 records obtained, 31 met all predefined criteria and were included in this review. Google Glass was used in various surgical specialties. Most studies were in the United States (23/31, 74%) and all were conducted in hospital settings: 29 in adult hospitals (29/31, 94%) and two in children’s hospitals (2/31, 7%). Sample sizes of participants who wore Google Glass ranged from 1 to 40. Of the 31 studies, 25 (81%) were conducted under real-time conditions or actual clinical care settings, whereas the other six (19%) were conducted under simulated environment. Twenty-six studies were pilot or feasibility studies (84%), three were case studies (10%), and two were randomized controlled trials (6%). The majority of

Use of "Google Scholar" in Corpus-Driven EAP Research

ERIC Educational Resources Information Center

Brezina, Vaclav

2012-01-01

This primarily methodological article makes a proposition for linguistic exploration of textual resources available through the "Google Scholar" search engine. These resources ("Google Scholar virtual corpus") are significantly larger than any existing corpus of academic writing. "Google Scholar", however, was not designed for linguistic searches…

Apollo 8 Mission image,Earth and Lunar Horizon

NASA Image and Video Library

1968-12-21

Apollo 8,Earth and Lunar Horizon. Image taken on Revolution 10 during Transearth Injection (TEI). Original Film Magazine was labeled D. Camera Data: 70mm Hasselblad. Lens: 80mm; F-Stop: F/11; Shutter Speed: 1/250 second. Film Type: Kodak SO-3400 Black and White,ASA 40. Flight Date: December 21-27,1968.

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…

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

NASA Astrophysics Data System (ADS)

Choi, Sung-Ja; Lee, Gang-Soo

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

Earth resources shuttle imaging radar. [systems analysis and design analysis of pulse radar for earth resources information system

NASA Technical Reports Server (NTRS)

1975-01-01

A report is presented on a preliminary design of a Synthetic Array Radar (SAR) intended for experimental use with the space shuttle program. The radar is called Earth Resources Shuttle Imaging Radar (ERSIR). Its primary purpose is to determine the usefulness of SAR in monitoring and managing earth resources. The design of the ERSIR, along with tradeoffs made during its evolution is discussed. The ERSIR consists of a flight sensor for collecting the raw radar data and a ground sensor used both for reducing these radar data to images and for extracting earth resources information from the data. The flight sensor consists of two high powered coherent, pulse radars, one that operates at L and the other at X-band. Radar data, recorded on tape can be either transmitted via a digital data link to a ground terminal or the tape can be delivered to the ground station after the shuttle lands. A description of data processing equipment and display devices is given.

Technology Required to Image and Characterize an exo-Earth from Space

NASA Astrophysics Data System (ADS)

Crill, Brendan

2018-01-01

NASA's Exoplanet Exploration Program (ExEP) guides the development of technology that enables the direct imaging and characterization of exo-Earths in the habitable zone of Sun-like stars with future space observatories. Here we present the 2018 ExEP Technology Gap List, an annual update to ExEP's list of technologies, to be advanced in the next 1-5 years. Key technology gaps are starlight suppression with a coronagraph (internal occulters) or a starshade (external occulters), enabling imaging at extreme contrast (more than 10 billion) by blocking on-axis starlight, while allowing the reflected light of off-axis exoplanets be detected. Building and operating a space coronagraph capable of imaging an exo-Earth will require new technologies beyond those of WFIRST, the first high-contrast coronagraph in space. A starshade has never been used in a space mission and requires new capabilities in precision deployment of large structures, starlight suppression, and in formation sensing and control. We review the current state-of-the-art in coronagraph and starshade technology and the performance level that must be achieved to discover and characterize Earth analogs.

Google vs. the Library: Student Preferences and Perceptions when Doing Research Using Google and a Federated Search Tool

ERIC Educational Resources Information Center

Georgas, Helen

2013-01-01

Federated searching was once touted as the library world's answer to Google, but ten years since federated searching technology's inception, how does it actually compare? This study focuses on undergraduate student preferences and perceptions when doing research using both Google and a federated search tool. Students were asked about their…

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

A Google-based approach for monitoring suicide risk.

PubMed

Solano, Paola; Ustulin, Morena; Pizzorno, Enrico; Vichi, Monica; Pompili, Maurizio; Serafini, Gianluca; Amore, Mario

2016-12-30

People seeking information and news regarding suicide are likely to use the Internet. However, evidence of the relationship between suicide-related search volumes and national suicide-rates in different countries can be strikingly different. We aimed to investigate the relationship between suicide-rates and Google suicide-related search volumes in the Italian population (2008-2012) using the Italian mortality database that provided monthly national data concerning suicides (2008-2012). Moreover, this study aimed to identify future trends of national suicide rates on the basis of the results we obtained concerning the period 2013-14. Google Trends provided data of online monthly search-volumes of the term "suicide", "commit suicide" and "how to commit suicide" in Google Search and Google News (2008-2014). Google Search volumes for the term "suicide" lags suicide by three months (ρ=0.482, p-value<0.001), whereas no correlation was found between search volumes for "commit suicide" and "how to commit suicide" and national suicide rates. Google News search volumes for the three terms resulted in white noise. Apparently, online searches for suicide-related terms in Italy are more likely to be linked to factors other than suicidiality such as personal interest and suicide bereavement. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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

Putting Google Scholar to the Test: A Preliminary Study

ERIC Educational Resources Information Center

Robinson, Mary L.; Wusteman, Judith

2007-01-01

Purpose: To describe a small-scale quantitative evaluation of the scholarly information search engine, Google Scholar. Design/methodology/approach: Google Scholar's ability to retrieve scholarly information was compared to that of three popular search engines: Ask.com, Google and Yahoo! Test queries were presented to all four search engines and…

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.

Using Google Glass in Surgical Settings: Systematic Review.

PubMed

Wei, Nancy J; Dougherty, Bryn; Myers, Aundria; Badawy, Sherif M

2018-03-06

In recent years, wearable devices have become increasingly attractive and the health care industry has been especially drawn to Google Glass because of its ability to serve as a head-mounted wearable device. The use of Google Glass in surgical settings is of particular interest due to the hands-free device potential to streamline workflow and maintain sterile conditions in an operating room environment. The aim is to conduct a systematic evaluation of the literature on the feasibility and acceptability of using Google Glass in surgical settings and to assess the potential benefits and limitations of its application. The literature was searched for articles published between January 2013 and May 2017. The search included the following databases: PubMed MEDLINE, Embase, Cumulative Index to Nursing and Allied Health Literature, PsycINFO (EBSCO), and IEEE Xplore. Two reviewers independently screened titles and abstracts and assessed full-text articles. Original research articles that evaluated the feasibility, usability, or acceptability of using Google Glass in surgical settings were included. This review was completed following the Preferred Reporting Results of Systematic Reviews and Meta-Analyses guidelines. Of the 520 records obtained, 31 met all predefined criteria and were included in this review. Google Glass was used in various surgical specialties. Most studies were in the United States (23/31, 74%) and all were conducted in hospital settings: 29 in adult hospitals (29/31, 94%) and two in children's hospitals (2/31, 7%). Sample sizes of participants who wore Google Glass ranged from 1 to 40. Of the 31 studies, 25 (81%) were conducted under real-time conditions or actual clinical care settings, whereas the other six (19%) were conducted under simulated environment. Twenty-six studies were pilot or feasibility studies (84%), three were case studies (10%), and two were randomized controlled trials (6%). The majority of studies examined the potential use of

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

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

NASA Astrophysics Data System (ADS)

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

2006-12-01

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

Google in the Research and Teaching of Instruction Librarians

ERIC Educational Resources Information Center

Sorensen, Charlene; Dahl, Candice

2008-01-01

This exploratory study assesses the differences and similarities between how instruction librarians in Western Canada use Google and how they instruct students to use it. Survey results indicate that these librarians do use Google but can be influenced by faculty to present Google negatively to students. (Contains 4 figures and 1 table.)

Google Scholar Users and User Behaviors: An Exploratory Study

ERIC Educational Resources Information Center

Herrera, Gail

2011-01-01

The University of Mississippi Library created a profile to provide linking from Google Scholar (GS) to library resources in 2005. Although Google Scholar does not provide usage statistics for institutions, use of Google Scholar is clearly evident in looking at library link resolver logs. The purpose of this project is to examine users of Google…

Places to Go: Google's Search Results for "Net Generation"

ERIC Educational Resources Information Center

Downes, Stephen

2007-01-01

In his Places to Go column for a special issue on the Net Generation, Stephen Downes takes an unexpected trip--to Google. According to Downes, Google epitomizes the essence of the Net Generation. Infinitely searchable and adaptable, Google represents the spirit of a generation raised in the world of the Internet, a generation that adapts…

ALISEO on MIOSat: an imaging interferometer for earth observation

NASA Astrophysics Data System (ADS)

Barducci, A.; Castagnoli, F.; Castellini, G.; Guzzi, D.; Marcoionni, P.; Pippi, I.

2017-11-01

The Italian Space Agency (ASI) decided to perform an low cost Earth observation mission based on a new mini satellite named MIOsat which will carry various technological payloads. Among them an imaging interferometer designed and now ready to be assembled and tested by our Institute. The instrument, named ALISEO (Aerospace Leap-frog Imaging Stationary interferometer for Earth Observation), operates in the common-path Sagnac configuration, and it does not utilize any moving part to scan the phase delays between the two interfering beams. The sensor acquires target images modulated by a pattern of autocorrelation functions of the energy coming from each scene pixel, and the resulting fringe pattern remains spatially fixed with respect to the instrument's field-of-view. The complete interferogram of each target location is retrieved by introducing a relative source-observer motion, which allows any image pixels to be observed under different viewing-angles and experience discrete path differences. The paper describes the main characteristics of the imaging interferometer as well as the overall optical configuration and the electronics layout. Moreover some theoretical issues concerning sampling theory in "common path" imaging interferometry are investigated. The experimental activity performed in laboratory is presented and its outcomes are analysed. Particularly, a set of measurements has been carried out using both standard (certificate) reflectance tiles and natural samples of different volcanic rocks. An algorithm for raw data pre-processing aimed at retrieving the at-sensor radiance spectrum is introduced and its performance is addressed by taking into account various issues such as dark signal subtraction, spectral instrument response compensation, effects of vignetting, and Fourier backtransform. Finally, examples of retrieved absolute reflectance of several samples are sketched at different wavelengths.

Google Scholar and the Continuing Education Literature

ERIC Educational Resources Information Center

Howland, Jared L.; Howell, Scott; Wright, Thomas C.; Dickson, Cody

2009-01-01

The recent introduction of Google Scholar has renewed hope that someday a powerful research tool will bring continuing education literature more quickly, freely, and completely to one's computer. The authors suggest that using Google Scholar with other traditional search methods will narrow the research gap between what is discoverable and…

Enhanced near-infrared photoacoustic imaging of silica-coated rare-earth doped nanoparticles.

PubMed

Sheng, Yang; Liao, Lun-De; Bandla, Aishwarya; Liu, Yu-Hang; Yuan, Jun; Thakor, Nitish; Tan, Mei Chee

2017-01-01

Near-infrared photoacoustic (PA) imaging is an emerging diagnostic technology that utilizes the tissue transparent window to achieve improved contrast and spatial resolution for deep tissue imaging. In this study, we investigated the enhancement effect of the SiO 2 shell on the PA property of our core/shell rare-earth nanoparticles (REs) consisting of an active rare-earth doped core of NaYF 4 :Yb,Er (REDNPs) and an undoped NaYF 4 shell. We observed that the PA signal amplitude increased with SiO 2 shell thickness. Although the SiO 2 shell caused an observed decrease in the integrated fluorescence intensity due to the dilution effect, fluorescence quenching of the rare earth emitting ions within the REDNPs cores was successfully prevented by the undoped NaYF 4 shell. Therefore, our multilayer structure consisting of an active core with successive functional layers was demonstrated to be an effective design for dual-modal fluorescence and PA imaging probes with improved PA property. The result from this work addresses a critical need for the development of dual-modal contrast agent that advances deep tissue imaging with high resolution and signal-to-noise ratio. Copyright © 2016 Elsevier B.V. All rights reserved.

Working Together: Google Apps Goes to School

ERIC Educational Resources Information Center

Oishi, Lindsay

2007-01-01

Online collaboration and project-management tools allow people to work together without being in the same place at the same time. However, that is not all, Google Docs & Spreadsheets, for example, allows the creation of documents and spreadsheets just like in Microsoft Word and Excel, but with more collaborative capacity. Google Calendar lets…

Radiometry with nighttime DMSP images in digital form. [satellite earth observations

NASA Technical Reports Server (NTRS)

Croft, T. A.

1981-01-01

The USAF Defense Meteorological Satellite Program (DMSP) spacecraft sends images to earth in the form of numbers. It has been common practice to erase the only digital records, the magnetic tapes, for reuse, after films (resembling photographs) have been created from the numbers. While the DMSP images have been widely used, their application in research has been hindered by both the lack of digital data and the lack of an authoritative source of related technical information. The character of the digital form is considered. Each image is essentially a three-dimensional list (X,Y,Z) in which X and Y represent the position coordinates of a pixel and Z is its associated radiance. Only the value of Z is given and the X-Y position must be deduced from adjunct information. Each original scan composed of 1464 pixels represents an area on the earth's surface about 3 km wide and 3000 km long. Strengths and weaknesses of the system with respect to research applications are considered, and concepts for the design of a nocturnal imager are discussed.

Where on Earth...? MISR Mystery Image Quiz #13: Western Uzbekistan and Northeastern Turkmenistan

NASA Image and Video Library

2003-03-19

Acquired by the Multi-angle Imaging SpectroRadiometer instrument aboard NASA Terra spacecraft, this image is from the MISR Where on Earth...? Mystery Quiz #13. The location is Western Uzbekistan and Northeastern Turkmenistan.

Monitoring of Non-cigarette Tobacco Use using Google Trends

PubMed Central

Cavazos-Rehg, Patricia A.; Krauss, Melissa J.; Spitznagel, Edward L.; Lowery, Ashley; Grucza, Richard A.; Chaloupka, Frank J.; Bierut, Laura Jean

2014-01-01

Background Google Trends is an innovative monitoring system with unique potential to monitor and predict important phenomena that may be occurring at a population-level. We sought to validate whether Google Trends can additionally detect regional trends in youth and adult tobacco use. Methods We compared 2011 Google Trends relative search volume data for cigars, cigarillos, little cigars and smokeless tobacco with state prevalence of youth (grades 9–12) and adult (age 18 and older) use of these products using data from the 2011 United States state-level Youth Risk Behaviors Surveillance System and the 2010–2011 United States National Survey on Drug Use and Health (NSDUH), respectively. We used the Pearson correlation coefficient to measure the associations. Results We found significant positive correlations between state Google Trends cigar relative search volume and prevalence of cigar use among youth (r=0.39, R-square=0.154, p= .018) and adults (r=0.49, R-square=0.243, p<.001). Similarly, we found that the correlations between state Google trends smokeless tobacco relative search volume and prevalence of smokeless tobacco use among youth and adults were both positive and significant (r=0.46, R-square=0.209, p=.003 and r=0.48, R-square=0.226, p<.001, respectively). Conclusion The results of this study validate that Google Trends has the potential to be a valuable monitoring tool for tobacco use. The near real-time monitoring features of Google Trends may complement traditional surveillance methods and lead to faster and more convenient monitoring of emerging trends in tobacco use. What this paper adds Efforts to promptly track tobacco use at a population-level are an important endeavor that could assist key stakeholders with making informed decisions about prevention plans and policies. Our findings establish the validity of Google Trends as an indicator of cigar and smokeless tobacco use by demonstrating that states with higher relative volumes of Google

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.

Transforming Polar Research with Google Glass Augmented Reality (Invited)

NASA Astrophysics Data System (ADS)

Ruthkoski, T.

2013-12-01

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

Transforming Polar Research with Google Glass Augmented Reality (Invited)

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Google Scholar Usage: An Academic Library's Experience

ERIC Educational Resources Information Center

Wang, Ya; Howard, Pamela

2012-01-01

Google Scholar is a free service that provides a simple way to broadly search for scholarly works and to connect patrons with the resources libraries provide. The researchers in this study analyzed Google Scholar usage data from 2006 for three library tools at San Francisco State University: SFX link resolver, Web Access Management proxy server,…

Google and Godel

ERIC Educational Resources Information Center

Oberdan, Thomas

2009-01-01

The article "Is Google Making Us Stupid?" in last Summer's "Atlantic Monthly," raised a number of provocative, and indeed worrisome, questions about computer usage and cognitive development. For instance, persons with considerable experience of reading for the sake of pleasure report that, after a couple of years using computers a great deal, they…

Influenza forecasting with Google Flu Trends.

PubMed

Dugas, Andrea Freyer; Jalalpour, Mehdi; Gel, Yulia; Levin, Scott; Torcaso, Fred; Igusa, Takeru; Rothman, Richard E

2013-01-01

We developed a practical influenza forecast model based on real-time, geographically focused, and easy to access data, designed to provide individual medical centers with advanced warning of the expected number of influenza cases, thus allowing for sufficient time to implement interventions. Secondly, we evaluated the effects of incorporating a real-time influenza surveillance system, Google Flu Trends, and meteorological and temporal information on forecast accuracy. Forecast models designed to predict one week in advance were developed from weekly counts of confirmed influenza cases over seven seasons (2004-2011) divided into seven training and out-of-sample verification sets. Forecasting procedures using classical Box-Jenkins, generalized linear models (GLM), and generalized linear autoregressive moving average (GARMA) methods were employed to develop the final model and assess the relative contribution of external variables such as, Google Flu Trends, meteorological data, and temporal information. A GARMA(3,0) forecast model with Negative Binomial distribution integrating Google Flu Trends information provided the most accurate influenza case predictions. The model, on the average, predicts weekly influenza cases during 7 out-of-sample outbreaks within 7 cases for 83% of estimates. Google Flu Trend data was the only source of external information to provide statistically significant forecast improvements over the base model in four of the seven out-of-sample verification sets. Overall, the p-value of adding this external information to the model is 0.0005. The other exogenous variables did not yield a statistically significant improvement in any of the verification sets. Integer-valued autoregression of influenza cases provides a strong base forecast model, which is enhanced by the addition of Google Flu Trends confirming the predictive capabilities of search query based syndromic surveillance. This accessible and flexible forecast model can be used by

Image data processing system requirements study. Volume 1: Analysis. [for Earth Resources Survey Program

NASA Technical Reports Server (NTRS)

Honikman, T.; Mcmahon, E.; Miller, E.; Pietrzak, L.; Yorsz, W.

1973-01-01

Digital image processing, image recorders, high-density digital data recorders, and data system element processing for use in an Earth Resources Survey image data processing system are studied. Loading to various ERS systems is also estimated by simulation.

Development of detailed design concepts for the EarthCARE multi-spectral imager

NASA Astrophysics Data System (ADS)

Lobb, Dan; Escadero, Isabel; Chang, Mark; Gode, Sophie

2017-11-01

The EarthCARE mission is dedicated to the study of clouds by observations from a satellite in low Earth orbit. The payload will include major radar and LIDAR instruments, supported by a multi-spectral imager (MSI) and a broadband radiometer. The paper describes development of detailed design concepts for the MSI, and analysis of critical performance parameters. The MSI will form Earth images at 500m ground sample distance (GSD) over a swath width of 150km, from a nominal platform altitude of around 400km. The task of the MSI is to provide spatial context for the single-point measurements made by the radar and LIDAR systems; it will image Earth in 7 spectral bands: one visible, one near-IR, two short-wave IR and three thermal IR. The MSI instrument will be formed in two parts: a visible-NIR-SWIR (VNS) system, radiometrically calibrated using a sunilluminated diffuser, and a thermal IR (TIR) system calibrated using cold space and an internal black-body. The VNS system will perform push-broom imaging, using linear array detectors (silicon and InGaAs) and 4 separate lenses. The TIR system will use a microbolometer array detector in a time delay and integration (TDI) mode. Critical issues discussed for the VNS system include detector selection and detailed optical design trade-offs. The latter are related to the desirability of dichroics to achieve a common aperture, which influences the calibration hardware and lens design. The TIR system's most significant problems relate to control of random noise and bias errors, requiring optimisation of detector operation and calibration procedures.

Geological Deformations and Potential Hazards Triggered by the 01-12-2010 Haiti Earthquake: Insights from Google Earth Imagery

NASA Astrophysics Data System (ADS)

Doblas, M.; Benito, B.; Torres, Y.; Belizaire, D.; Dorfeuille, J.; Aretxabala, A.

2013-05-01

In this study we compare the different Google Earth imagery (GEI) available before and after the 01-12-2010 earthquake of Haiti and carry out a detailed analysis of the superficial seismic-related geological deformations in the following sites: 1) the capital Port-Au-Prince and other cities (Carrefour and Gresslier); 2) the mountainous area of the Massif de la Selle which is transected by the "Enriquillo-Plaintain-Garden" (EPG) interplate boundary-fault (that supposedly triggered the seism); 3) some of the most important river channels and their corresponding deltas (Momanche, Grise and Frorse). The initial results of our researches were published in March 2010 in a special web page created by the scientific community to try to mitigate the devastating effects of this catastrophe (http://supersites.earthobservations.org/haiti.php). Six types of superficial geological deformations triggered by the seismic event have been identified with the GEI: liquefaction structures, chaotic rupture zones, coastal and domal uplifts, river-delta turnovers, faults/ruptures and landslides. Potential geological hazards triggered by the Haiti earthquake include landslides, inundations, reactivation of active tectonic elements (e.g., fractures), river-delta turnovers, etc. We analyzed again the GEI after the rain period and, as expected, most of the geological deformations that we initially identified had been erased and/or modified by the water washout or buried by the sediments. In this sense the GEI constitutes an invaluable instrument in the analysis of seismic geological hazards: we still have the possibility to compare all the images before and after the seism that are recorded in its useful "time tool". These are in fact the only witnesses of most of the geological deformations triggered by the Haiti earthquake that remain stored in the virtual archives of the GEI. In fact a field trip to the area today would be useless as most of these structures have disappeared. We will show

Exploring Sustainability Using images from Space

NASA Astrophysics Data System (ADS)

Chen, Loris; Salmon, Jennifer; Burns, Courtney

2016-04-01

, laptops, iPads). As a result, web-based resources are incorporated into student learning on a daily basis. This has created a truly global classroom for students who, via the Internet, can and do access materials from any country in the world. Students work collaboratively using Google Classroom and a suite of Google apps. Teacher-created websites serve as the textbook with text, video, static images, interactive images, and external links designed to stimulate student growth in scientific literacy, language arts, and mathematics. Images of Earth's systems generated from data collected by Earth orbiting spacecraft are essential tools for understanding sustainability concepts at global, national, regional, and local scales. Images and supporting data from NASA (U.S.), ESA (Europe), and JAXA (Japan) are used to explore Earth's atmosphere, hydrosphere, and geosphere. Simulations, time-lapses, and graphical representations of historical and real-time, remote-sensing data stimulate student questions and engage students in learning as they design and test models to explain complex interactions of Earth's systems and feedback loops between natural and human-made environments. As students make meaning of observations and communicate their perceptions and understandings to a variety of audiences, they gain mastery of scientific literacy, language arts skills, and mathematics skills.

Iterative electromagnetic Born inversion applied to earth conductivity imaging

NASA Astrophysics Data System (ADS)

Alumbaugh, D. L.

1993-08-01

This thesis investigates the use of a fast imaging technique to deduce the spatial conductivity distribution in the earth from low frequency (less than 1 MHz), cross well electromagnetic (EM) measurements. The theory embodied in this work is the extension of previous strategies and is based on the Born series approximation to solve both the forward and inverse problem. Nonlinear integral equations are employed to derive the series expansion which accounts for the scattered magnetic fields that are generated by inhomogeneities embedded in either a homogenous or a layered earth. A sinusoidally oscillating, vertically oriented magnetic dipole is employed as a source, and it is assumed that the scattering bodies are azimuthally symmetric about the source dipole axis. The use of this model geometry reduces the 3-D vector problem to a more manageable 2-D scalar form. The validity of the cross well EM method is tested by applying the imaging scheme to two sets of field data. Images of the data collected at the Devine, Texas test site show excellent correlation with the well logs. Unfortunately there is a drift error present in the data that limits the accuracy of the results. A more complete set of data collected at the Richmond field station in Richmond, California demonstrates that cross well EM can be successfully employed to monitor the position of an injected mass of salt water. Both the data and the resulting images clearly indicate the plume migrates toward the north-northwest. The plausibility of these conclusions is verified by applying the imaging code to synthetic data generated by a 3-D sheet model.

Earth Observing-1 Advanced Land Imager: Imaging Performance On-Orbit

NASA Technical Reports Server (NTRS)

Hearn, D. R.

2002-01-01

This report analyzes the on-orbit imaging performance of the Advanced Land Imager (ALI) on the Earth Observing-1 satellite. The pre-flight calibrations are first summarized. The methods used to reconstruct and geometrically correct the image data from this push-broom sensor are described. The method used here does not refer to the position and attitude telemetry from the spacecraft. Rather, it is assumed that the image of the scene moves across the focal plane with a constant velocity, which can be ascertained from the image data itself. Next, an assortment of the images so reconstructed is presented. Color images sharpened with the 10-m panchromatic band data are shown, and the algorithm for producing them from the 30-m multispectral data is described. The approach taken for assessing spatial resolution is to compare the sharpness of features in the on-orbit image data with profiles predicted on the basis of the pre-flight calibrations. A large assortment of bridge profiles is analyzed, and very good fits to the predicted shapes are obtained. Lunar calibration scans are analyzed to examine the sharpness of the edge-spread function at the limb of the moon. The darkness of the space beyond the limb is better for this purpose than anything that could be simulated on the ground. From these scans, we find clear evidence of scattering in the optical system, as well as some weak ghost images. Scans of planets and stars are also analyzed. Stars are useful point sources of light at all wavelengths, and delineate the point-spread functions of the system. From a quarter-speed scan over the Pleiades, we find that the ALI can detect 6th magnitude stars. The quality of the reconstructed images verifies the capability of the ALI to produce Landsat-type multi spectral data. The signal-to-noise and panchromatic spatial resolution are considerably superior to those of the existing Landsat sensors. The spatial resolution is confirmed to be as good as it was designed to be.

Beyond seismic interferometry: imaging the earth's interior with virtual sources and receivers inside the earth

NASA Astrophysics Data System (ADS)

Wapenaar, C. P. A.; Van der Neut, J.; Thorbecke, J.; Broggini, F.; Slob, E. C.; Snieder, R.

2015-12-01

Imagine one could place seismic sources and receivers at any desired position inside the earth. Since the receivers would record the full wave field (direct waves, up- and downward reflections, multiples, etc.), this would give a wealth of information about the local structures, material properties and processes in the earth's interior. Although in reality one cannot place sources and receivers anywhere inside the earth, it appears to be possible to create virtual sources and receivers at any desired position, which accurately mimics the desired situation. The underlying method involves some major steps beyond standard seismic interferometry. With seismic interferometry, virtual sources can be created at the positions of physical receivers, assuming these receivers are illuminated isotropically. Our proposed method does not need physical receivers at the positions of the virtual sources; moreover, it does not require isotropic illumination. To create virtual sources and receivers anywhere inside the earth, it suffices to record the reflection response with physical sources and receivers at the earth's surface. We do not need detailed information about the medium parameters; it suffices to have an estimate of the direct waves between the virtual-source positions and the acquisition surface. With these prerequisites, our method can create virtual sources and receivers, anywhere inside the earth, which record the full wave field. The up- and downward reflections, multiples, etc. in the virtual responses are extracted directly from the reflection response at the surface. The retrieved virtual responses form an ideal starting point for accurate seismic imaging, characterization and monitoring.

Google Docs in an Out-of-Class Collaborative Writing Activity

ERIC Educational Resources Information Center

Zhou, Wenyi; Simpson, Elizabeth; Domizi, Denise Pinette

2012-01-01

Google Docs, an online word processing application, is a promising tool for collaborative learning. However, many college instructors and students lack knowledge to effectively use Google Docs to enhance teaching and learning. Goals of this study include (1) assessing the effectiveness of using Google Docs in an out-of-class collaborative writing…

Space technology for directly imaging and characterizing exo-Earths

NASA Astrophysics Data System (ADS)

Crill, Brendan P.; Siegler, Nicholas

2017-09-01

The detection of Earth-like exoplanets in the habitable zone of their stars, and their spectroscopic characterization in a search for biosignatures, requires starlight suppression that exceeds the current best ground-based performance by orders of magnitude. The required planet/star brightness ratio of order 10-10 at visible wavelengths can be obtained by blocking stellar photons with an occulter, either externally (a starshade) or internally (a coronagraph) to the telescope system, and managing diffracted starlight, so as to directly image the exoplanet in reflected starlight. Coronagraph instruments require advancement in telescope aperture (either monolithic or segmented), aperture obscurations (obscured by secondary mirror and its support struts), and wavefront error sensitivity (e.g. line-of-sight jitter, telescope vibration, polarization). The starshade, which has never been used in a science application, benefits a mission by being decoupled from the telescope, allowing a loosening of telescope stability requirements. In doing so, it transfers the difficult technology from the telescope system to a large deployable structure (tens of meters to greater than 100 m in diameter) that must be positioned precisely at a distance of tens of thousands of kilometers from the telescope. We describe in this paper a roadmap to achieving the technological capability to search for biosignatures on an Earth-like exoplanet from a future space telescope. Two of these studies, HabEx and LUVOIR, include the direct imaging of Earth-sized habitable exoplanets as a central science theme.

Obtaining coincident image observations for Mission to Planet Earth science data return

NASA Technical Reports Server (NTRS)

Newman, Lauri Kraft; Folta, David C.; Farrell, James P.

1994-01-01

One objective of the Mission to Planet Earth (MTPE) program involves comparing data from various instruments on multiple spacecraft to obtain a total picture of the Earth's systems. To correlate image data from instruments on different spacecraft, these spacecraft must be able to image the same location on the Earth at approximately the same time. Depending on the orbits of the spacecraft involved, complicated operational details must be considered to obtain such observations. If the spacecraft are in similar orbits, close formation flying or synchronization techniques may be used to assure coincident observations. If the orbits are dissimilar, the launch time of the second satellite may need to be restricted in order to align its orbit with that of the first satellite launched. This paper examines strategies for obtaining coincident observations for spacecraft in both similar and dissimilar orbits. Although these calculations may be performed easily for coplanar spacecraft, the non-coplanar case involves additional considerations which are incorporated into the algorithms presented herein.

Measuring the Earth System in a Time of Global Environmental Change with Image Spectroscopy

NASA Technical Reports Server (NTRS)

Green, Robert O.

2005-01-01

Measuring the Earth system in a time of global environmental change. Imaging Spectroscopy enables remote measurement. Remote Measurement determination of the properties of the Earth's surface and atmosphere through the physics, chemistry and biology of the interaction of electromagnetic energy with matter.

Moonshot Laboratories' Lava Relief Google Mapping Project

NASA Astrophysics Data System (ADS)

Brennan, B.; Tomita, M.

2016-12-01

The Moonshot Laboratories were conceived at the University Laboratory School (ULS) on Oahu, Hawaii as way to develop creative problem solvers able to resourcefully apply 21st century technologies to respond to the problems and needs of their communities. One example of this was involved students from ULS using modern mapping and imaging technologies to assist peers who had been displaced from their own school in Pahoe on the Big Island of Hawaii. During 2015, lava flows from the eruption of Kilauea Volcano were slowly encroaching into the district of Puna in 2015. The lava flow was cutting the main town of Pahoa in half, leaving no safe routes of passage into or out of the town. One elementary school in the path of the flow was closed entirely and a new one was erected north of the flow for students living on that side. Pahoa High School students and teachers living to the north were been forced to leave their school and transfer to Kea'au High School. These students were separated from friends, family and the community they grew up in and were being thrust into a foreign environment that until then had been their local rival. Using Google Mapping technologies, Moonshot Laboratories students created a dynamic map to introduce the incoming Pahoa students to their new school in Kea'au. Elements included a stylized My Maps basemap, YouTube video descriptions of the building, videos recorded by Google Glass showing first person experiences, and immersive images of classrooms were created using 360 cameras. During the first day of orientation at Kea'au for the 200 Pahoa students, each of them were given a tablet to view the map as they toured and got to know their new campus. The methods and technologies, and more importantly innovative thinking, used to create this map have enormous potential for how to educate all students about the world around us, and the issues facing it. http://www.moonshotincubator.com/

Through the Google Goggles: Sociopolitical Bias in Search Engine Design

NASA Astrophysics Data System (ADS)

Diaz, A.

Search engines like Google are essential to navigating the Web's endless supply of news, political information, and citizen discourse. The mechanisms and conditions under which search results are selected should therefore be of considerable interest to media scholars, political theorists, and citizens alike. In this chapter, I adopt a "deliberative" ideal for search engines and examine whether Google exhibits the "same old" media biases of mainstreaming, hypercommercialism, and industry consolidation. In the end, serious objections to Google are raised: Google may favor popularity over richness; it provides advertising that competes directly with "editorial" content; it so overwhelmingly dominates the industry that users seldom get a second opinion, and this is unlikely to change. Ultimately, however, the results of this analysis may speak less about Google than about contradictions in the deliberative ideal and the so-called "inherently democratic" nature of the Web.

Effects of Direct Systematic Instruction on Google Glass Orientation with Individuals with Intellectual Disability

ERIC Educational Resources Information Center

Kelley, Kelly R.; Rivera, Christopher J.; Kellems, Ryan O.

2016-01-01

Glass, designed by Google, is a fairly new wearable and mobile technology that projects an image into a glass prism above the eye and is currently in beta testing. A touch pad on the side of Glass allows users to engage with the device through swiping gestures and voice control to perform several functions similar to mobile devices. This initial…

Variable optical filters for earth-observation imaging minispectrometers

NASA Astrophysics Data System (ADS)

Piegari, A.; Bulir, J.; Krasilnikova, A.; Dami, M.; Harnisch, B.

2017-11-01

Small-dimension, low-mass spectrometers are useful for both Earth observation and planetary missions. A very compact multi-spectral mini-spectrometer that contains no moving parts, can be constructed combining a graded-thickness filter, having a spatially variable narrow-band transmission, to a CCD array detector. The peak wavelength of the transmission filter is moving along one direction of the filter surface, such that each line of a two-dimensional array detector, equipped with this filter, will detect radiation in a different pass band. The spectrum of interest for image spectrometry of the Earth surface is very wide, 400-1000nm. This requirement along with the need of a very small dimension, makes this filter very difficult to manufacture. Preliminary results on metal-dielectric wedge filters, with a gradient of the transmission peak wavelength equal to 60nm/mm, are reported.

Lessons Learned From Google Glass: Telemedical Spark or Unfulfilled Promise?

PubMed

Yu, Jonathan; Ferniany, William; Guthrie, Barton; Parekh, Selene G; Ponce, Brent

2016-04-01

Wearable devices such as Google Glass could potentially be used in the health care setting to expand access and improve quality of care. This study aims to assess the demographics of Google Glass users in health care and determine the obstacles to using Google Glass by surveying those who are known to use the device. A 48-question survey was designed to assess demographics of users, technological limitations of Google Glass, and obstacles to implementation of the device. The physicians surveyed worked in various fields of health care, with 50% of the respondents being surgeons. Potential participants were found using an Internet search for physicians using Google Glass in their practice. Outcome measures were divided into demographic information of users, technological limitations of the device, and administrative obstacles. A 43.6% response rate was observed. The majority of users were male, assistant professors, in academic hospitals, and in the United States. Numerous technological limitations were observed by the majority, including device ergonomics, display location, video quality, and audio quality. Patient confidentiality and data security were the major concerns among administrative obstacles. Despite the potential of Google Glass, numerous obstacles exist that limit its use in health care. While Google Glass has been discontinued, the results of this study may be used to guide future designs of wearable devices. © The Author(s) 2015.

Box Tomography: An efficient tomographic method for imaging localized structures in the deep Earth

NASA Astrophysics Data System (ADS)

Masson, Yder; Romanowicz, Barbara

2017-04-01

The accurate imaging of localized geological structures inside the deep Earth is key to understand our planet and its history. Since the introduction of the Preliminary Reference Earth Model, many generations of global tomographic models have been developed and give us access to the 3D structure of the Earth's interior. The latest generation of global tomographic models has emerged with the development of accurate numerical wavefield computations in a 3D earth combined with access to enhanced HPC capabilities. These models have sharpened up mantle images and unveiled relatively small scale structures that were blurred out in previous generation models. Fingerlike structures have been found at the base of the oceanic asthenosphere, and vertically oriented broad low velocity plume conduits [1] extend throughout the lower mantle beneath those major hotspots that are located within the perimeter of the deep mantle large low shear velocity provinces (LLSVPs). While providing new insights into our understanding of mantle dynamics, the detailed morphology of these features requires further efforts to obtain higher resolution images. In recent years, we developed a theoretical framework [2][3] for the tomographic imaging of localised geological structures buried inside the Earth, where no seismic sources nor receivers are necessarily present. We call this "box tomography" [4]. The essential difference between box-tomography and standard tomographic methods is that the numerical modeling (i.e. the raytracing in travel time tomography and the wave propagation in waveform tomography or full waveform inversion) is completely confined within the small box-region imaged. Thus, box tomography is a lot more efficient than global tomography (i.e. where we invert for the velocity in the larger volume that encompasses all the sources and receivers), for imaging localised objects. We present 2D and 3D examples showing that box tomography can be employed for imaging structures present

Earth observation photo taken by JPL with the Shuttle Imaging Radar-A

NASA Technical Reports Server (NTRS)

1981-01-01

Earth observation photo taken by the Jet Propulsion Laboratory (JPL) with the Shuttle Imaging Radar-A (SIR-A). This image shows the Los Angeles basin. The area's freeways are visible as dark lines. The Los Angles harbor breakwater off Long Beach is seen as a bright line. Vessels in the harbor show as bright points.

Earth observation photo taken by JPL with the Shuttle Imaging Radar-A

NASA Technical Reports Server (NTRS)

1981-01-01

Photos of earth observations taken by the Jet Propulsion Laboratory (JPL) with the Shuttle Imaging Radar-A (SIR-A). This image shows Lake Okeechobee (right) and Lake Istokopoga (left) in Central Florida. Lake Okeechobee is bounded on the east by rectangular agricultural fields and to the south and west by swamps and wetlands which appear as bright features.

The Design of Two Nano-Rovers for Lunar Surface Exploration in the Context of the Google Lunar X Prize

NASA Astrophysics Data System (ADS)

Gill, E.; Honfi Camilo, L.; Kuystermans, P.; Maas, A. S. B. B.; Buutfeld, B. A. M.; van der Pols, R. H.

2008-09-01

aid the human controller by obtaining stereoscopic images. An additional navigational camera in the rear is used as a contingency to drive rearwards. All navigational cameras have a maximal resolution of 640 by 480 pixels. Each rover has one main High Definition (HD) camera capable of acquiring still images and videos. These cameras have a resolution of 1920 by 1080 pixels and a frame rate of 60 frames per second. Resolution and sampling rates can be modified to accommodate data transmission constraints. To comply with the self portrait requirement imposed by the Google Lunar X Prize, the rovers will take images of each other, capturing 50% of the surface exploration system on the still image. As a contingency, both vehicles are also capable composing self portraits from an assembly of multiple images of its own structure, similar to the panoramic images. The camera is positioned above the rover on a mast providing two degrees of freedom for the camera to be able to rotate 360º horizontally and from -45º to 90º vertically. Both rovers are equipped with an omni-directional antenna. A WiMax system is used for all communication with the lander vehicle. The communication is done via the commonly used TCP/IP, which can be easily integrated in the software systems of the mission. The lander vehicle itself will act as a relay station for the data transfer with the ground station on Earth. The selected Digital Signal Processor (D.S.P.) has been specifically designed for compressing raw HD format using little power. The D.S.P. is capable of compressing the raw video data while at the same time performing remaining tasks such as navigation. Since the D.S.P. is designed for Earth use, it has to be adapted to cope with the lunar environment. This can be achieved by proper implication of radiation shielding. As the primary power source Gallium-Arsenide solar panels are used. These are the most efficient solar panels to date. Additionally, a Lithium-Ion battery is used as the

Monitoring of non-cigarette tobacco use using Google Trends.

PubMed

Cavazos-Rehg, Patricia A; Krauss, Melissa J; Spitznagel, Edward L; Lowery, Ashley; Grucza, Richard A; Chaloupka, Frank J; Bierut, Laura Jean

2015-05-01

Google Trends is an innovative monitoring system with unique potential to monitor and predict important phenomena that may be occurring at a population level. We sought to validate whether Google Trends can additionally detect regional trends in youth and adult tobacco use. We compared 2011 Google Trends relative search volume data for cigars, cigarillos, little cigars and smokeless tobacco with state prevalence of youth (grades 9-12) and adult (age 18 and older) use of these products using data from the 2011 United States state-level Youth Risk Behaviors Surveillance System and the 2010-2011 United States National Survey on Drug Use and Health (NSDUH), respectively. We used the Pearson correlation coefficient to measure the associations. We found significant positive correlations between state Google Trends cigar relative search volume and prevalence of cigar use among youth (r=0.39, R(2) = 0.154, p=0.018) and adults (r=0.49, R(2) = 0.243, p<0.001). Similarly, we found that the correlations between state Google Trends smokeless tobacco relative search volume and prevalence of smokeless tobacco use among youth and adults were both positive and significant (r=0.46, R(2) = 0.209, p=0.003 and r=0.48, R(2) = 0.226, p<0.001, respectively). The results of this study validate that Google Trends has the potential to be a valuable monitoring tool for tobacco use. The near real-time monitoring features of Google Trends may complement traditional surveillance methods and lead to faster and more convenient monitoring of emerging trends in tobacco use. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Integrating Google Apps and Google Chromebooks into the Core Curriculum: A Phenomenological Study of the Lived Experience of Public School Teachers

ERIC Educational Resources Information Center

Bartolo, Paula

2017-01-01

The purpose of this phenomenological study was to understand the lived experiences of public school teachers using Google Suite for Education with Google Chromebooks integrated into the core curriculum. With the adoption of Common Core standards by 46 states, the increased use of technology has occurred due to standards that integrate technology.…

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.

Hedging the Commons: Google Books, Libraries, and Open Access to Knowledge

ERIC Educational Resources Information Center

Bottando, Evelyn

2012-01-01

This dissertation analyzes the legal, social, technological, and cultural environment that gave rise to Google's library partnership program in order to propose an institutional corrective to Google's project to digitize cultural heritage. Interview research done with those actively involved with Google's project revealed the need for a history of…

Seeing Google through the Eyes of Turkish Academicians

ERIC Educational Resources Information Center

Alakurt, Turgay; Bardakci, Salih

2017-01-01

With its new variety of IT products and services created in the last decade for students, teachers and schools, Google has changed the face of education. Google technologies that can be used completely free of charge via a single account in any device offer innovative alternatives to meet the needs of education. These technologies also help…

Earth Observing-1 Advanced Land Imager: Radiometric Response Calibration

NASA Technical Reports Server (NTRS)

Mendenhall, J. A.; Lencioni, D. E.; Evans, J. B.

2000-01-01

The Advanced Land Imager (ALI) is one of three instruments to be flown on the first Earth Observing mission (EO-1) under NASA's New Millennium Program (NMP). ALI contains a number of innovative features, including a wide field of view optical design, compact multispectral focal plane arrays, non-cryogenic HgCdTe detectors for the short wave infrared bands, and silicon carbide optics. This document outlines the techniques adopted during ground calibration of the radiometric response of the Advanced Land Imager. Results from system level measurements of the instrument response, signal-to-noise ratio, saturation radiance, and dynamic range for all detectors of every spectral band are also presented.

NASA ARIA Project Provides New Look at Earth Surface Deformation from Nepal Quake

NASA Image and Video Library

2015-05-04

NASA and its partners are contributing important observations and expertise to the ongoing response to the April 25, 2015, magnitude 7.8 Gorkha earthquake in Nepal. The quake was the strongest to occur in that area since the 1934 Nepal-Bihar magnitude 8.0 event and caused significant regional damage and a humanitarian crisis. Scientists with the Advanced Rapid Imaging and Analysis project (ARIA), a collaboration between NASA's Jet Propulsion Laboratory, Pasadena, California, and the California Institute of Technology in Pasadena, analyzed interferometric synthetic aperture radar images from the PALSAR-2 instrument on the ALOS-2 satellite operated by the Japan Aerospace Exploration Agency (JAXA) to calculate a map of the deformation of Earth's surface caused by the quake. This false-color map shows the amount of permanent surface movement caused almost entirely by the earthquake, as viewed by the satellite, during a 70-day interval between two ALOS-2 images, acquired February 21 and May 2, 2015. In the map, surface displacements are seen as color contours (or "fringes"), where each color cycle represents 4.7 inches (11.9 centimeters) of surface motion. The contours show the land around Kathmandu has moved toward the satellite by up to 4.6 feet (1.4 meter), or 5.2 feet (1.6 meters) if we assume purely vertical motion. Areas without the color contours have snow or heavy vegetation that affects the radar measurements. Scientists use these maps to build detailed models of the fault and associated land movements to better understand the impact on future earthquake activity. The PALSAR-2 data were provided by JAXA through the Committee on Earth Observation Satellite (CEOS) in support of the response effort. The background image is from Google Earth. http://photojournal.jpl.nasa.gov/catalog/PIA19383

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

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

Building Extraction Based on Openstreetmap Tags and Very High Spatial Resolution Image in Urban Area

NASA Astrophysics Data System (ADS)

Kang, L.; Wang, Q.; Yan, H. W.

2018-04-01

How to derive contour of buildings from VHR images is the essential problem for automatic building extraction in urban area. To solve this problem, OSM data is introduced to offer vector contour information of buildings which is hard to get from VHR images. First, we import OSM data into database. The line string data of OSM with tags of building, amenity, office etc. are selected and combined into completed contours; Second, the accuracy of contours of buildings is confirmed by comparing with the real buildings in Google Earth; Third, maximum likelihood classification is conducted with the confirmed building contours, and the result demonstrates that the proposed approach is effective and accurate. The approach offers a new way for automatic interpretation of VHR images.

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

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.

Hands-Free Image Capture, Data Tagging and Transfer Using Google Glass: A Pilot Study for Improved Wound Care Management

PubMed Central

Aldaz, Gabriel; Shluzas, Lauren Aquino; Pickham, David; Eris, Ozgur; Sadler, Joel; Joshi, Shantanu; Leifer, Larry

2015-01-01

Chronic wounds, including pressure ulcers, compromise the health of 6.5 million Americans and pose an annual estimated burden of $25 billion to the U.S. health care system. When treating chronic wounds, clinicians must use meticulous documentation to determine wound severity and to monitor healing progress over time. Yet, current wound documentation practices using digital photography are often cumbersome and labor intensive. The process of transferring photos into Electronic Medical Records (EMRs) requires many steps and can take several days. Newer smartphone and tablet-based solutions, such as Epic Haiku, have reduced EMR upload time. However, issues still exist involving patient positioning, image-capture technique, and patient identification. In this paper, we present the development and assessment of the SnapCap System for chronic wound photography. Through leveraging the sensor capabilities of Google Glass, SnapCap enables hands-free digital image capture, and the tagging and transfer of images to a patient’s EMR. In a pilot study with wound care nurses at Stanford Hospital (n=16), we (i) examined feature preferences for hands-free digital image capture and documentation, and (ii) compared SnapCap to the state of the art in digital wound care photography, the Epic Haiku application. We used the Wilcoxon Signed-ranks test to evaluate differences in mean ranks between preference options. Preferred hands-free navigation features include barcode scanning for patient identification, Z(15) = -3.873, p < 0.001, r = 0.71, and double-blinking to take photographs, Z(13) = -3.606, p < 0.001, r = 0.71. In the comparison between SnapCap and Epic Haiku, the SnapCap System was preferred for sterile image-capture technique, Z(16) = -3.873, p < 0.001, r = 0.68. Responses were divided with respect to image quality and overall ease of use. The study’s results have contributed to the future implementation of new features aimed at enhancing mobile hands-free digital

Google glass-based remote control of a mobile robot

NASA Astrophysics Data System (ADS)

Yu, Song; Wen, Xi; Li, Wei; Chen, Genshe

2016-05-01

In this paper, we present an approach to remote control of a mobile robot via a Google Glass with the multi-function and compact size. This wearable device provides a new human-machine interface (HMI) to control a robot without need for a regular computer monitor because the Google Glass micro projector is able to display live videos around robot environments. In doing it, we first develop a protocol to establish WI-FI connection between Google Glass and a robot and then implement five types of robot behaviors: Moving Forward, Turning Left, Turning Right, Taking Pause, and Moving Backward, which are controlled by sliding and clicking the touchpad located on the right side of the temple. In order to demonstrate the effectiveness of the proposed Google Glass-based remote control system, we navigate a virtual Surveyor robot to pass a maze. Experimental results demonstrate that the proposed control system achieves the desired performance.

OnEarth: An Open Source Solution for Efficiently Serving High-Resolution Mapped Image Products

NASA Astrophysics Data System (ADS)

Thompson, C. K.; Plesea, L.; Hall, J. R.; Roberts, J. T.; Cechini, M. F.; Schmaltz, J. E.; Alarcon, C.; Huang, T.; McGann, J. M.; Chang, G.; Boller, R. A.; Ilavajhala, S.; Murphy, K. J.; Bingham, A. W.

2013-12-01

This presentation introduces OnEarth, a server side software package originally developed at the Jet Propulsion Laboratory (JPL), that facilitates network-based, minimum-latency geolocated image access independent of image size or spatial resolution. The key component in this package is the Meta Raster Format (MRF), a specialized raster file extension to the Geospatial Data Abstraction Library (GDAL) consisting of an internal indexed pyramid of image tiles. Imagery to be served is converted to the MRF format and made accessible online via an expandable set of server modules handling requests in several common protocols, including the Open Geospatial Consortium (OGC) compliant Web Map Tile Service (WMTS) as well as Tiled WMS and Keyhole Markup Language (KML). OnEarth has recently transitioned to open source status and is maintained and actively developed as part of GIBS (Global Imagery Browse Services), a collaborative project between JPL and Goddard Space Flight Center (GSFC). The primary function of GIBS is to enhance and streamline the data discovery process and to support near real-time (NRT) applications via the expeditious ingestion and serving of full-resolution imagery representing science products from across the NASA Earth Science spectrum. Open source software solutions are leveraged where possible in order to utilize existing available technologies, reduce development time, and enlist wider community participation. We will discuss some of the factors and decision points in transitioning OnEarth to a suitable open source paradigm, including repository and licensing agreement decision points, institutional hurdles, and perceived benefits. We will also provide examples illustrating how OnEarth is integrated within GIBS and other applications.

Evolution of Satellite Imagers and Sounders for Low Earth Orbit and Technology Directions at NASA

NASA Technical Reports Server (NTRS)

Pagano, Thomas S.; McClain, Charles R.

2010-01-01

Imagers and Sounders for Low Earth Orbit (LEO) provide fundamental global daily observations of the Earth System for scientists, researchers, and operational weather agencies. The imager provides the nominal 1-2 km spatial resolution images with global coverage in multiple spectral bands for a wide range of uses including ocean color, vegetation indices, aerosol, snow and cloud properties, and sea surface temperature. The sounder provides vertical profiles of atmospheric temperature, water vapor cloud properties, and trace gases including ozone, carbon monoxide, methane and carbon dioxide. Performance capabilities of these systems has evolved with the optical and sensing technologies of the decade. Individual detectors were incorporated on some of the first imagers and sounders that evolved to linear array technology in the '80's. Signal-to-noise constraints limited these systems to either broad spectral resolution as in the case of the imager, or low spatial resolution as in the case of the sounder. Today's area 2-dimensional large format array technology enables high spatial and high spectral resolution to be incorporated into a single instrument. This places new constraints on the design of these systems and enables new capabilities for scientists to examine the complex processes governing the Earth System.

Accurate estimation of influenza epidemics using Google search data via ARGO

PubMed Central

Yang, Shihao; Santillana, Mauricio; Kou, S. C.

2015-01-01

Accurate real-time tracking of influenza outbreaks helps public health officials make timely and meaningful decisions that could save lives. We propose an influenza tracking model, ARGO (AutoRegression with GOogle search data), that uses publicly available online search data. In addition to having a rigorous statistical foundation, ARGO outperforms all previously available Google-search–based tracking models, including the latest version of Google Flu Trends, even though it uses only low-quality search data as input from publicly available Google Trends and Google Correlate websites. ARGO not only incorporates the seasonality in influenza epidemics but also captures changes in people’s online search behavior over time. ARGO is also flexible, self-correcting, robust, and scalable, making it a potentially powerful tool that can be used for real-time tracking of other social events at multiple temporal and spatial resolutions. PMID:26553980

Accurate estimation of influenza epidemics using Google search data via ARGO.

PubMed

Yang, Shihao; Santillana, Mauricio; Kou, S C

2015-11-24

Accurate real-time tracking of influenza outbreaks helps public health officials make timely and meaningful decisions that could save lives. We propose an influenza tracking model, ARGO (AutoRegression with GOogle search data), that uses publicly available online search data. In addition to having a rigorous statistical foundation, ARGO outperforms all previously available Google-search-based tracking models, including the latest version of Google Flu Trends, even though it uses only low-quality search data as input from publicly available Google Trends and Google Correlate websites. ARGO not only incorporates the seasonality in influenza epidemics but also captures changes in people's online search behavior over time. ARGO is also flexible, self-correcting, robust, and scalable, making it a potentially powerful tool that can be used for real-time tracking of other social events at multiple temporal and spatial resolutions.

Earth observation photo taken by JPL with the Shuttle Imaging Radar-A

NASA Technical Reports Server (NTRS)

1981-01-01

Earth observation photo taken by the Jet Propulsion Laboratory (JPL) with the Shuttle Imaging Radar-A (SIR-A). This image shows a 50 by 120 kilometer (30 by 75 mile) area of the Mediterranean Sea and the eastern coast of Central Sardinia (left). The city of Arbatose is seen as a bright area along the coast in the lower part of the image, and the star-like spot off the coast is a ship's reflection. The Gulf of Orsei is near the top of the image. Bright, mottled features in the sea (right) represent surface choppiness.

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.

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.

NASA ARIA Project Maps Deformation of Earth Surface from Nepal Quake

NASA Image and Video Library

2015-05-02

NASA and its partners are contributing important observations and expertise to the ongoing response to the April 25, 2015, magnitude 7.8 Gorkha earthquake in Nepal. The quake was the strongest to occur in that area since the 1934 Nepal-Bihar magnitude 8.0 event and caused significant regional damage and a humanitarian crisis. Scientists with the Advanced Rapid Imaging and Analysis project (ARIA), a collaboration between NASA's Jet Propulsion Laboratory, Pasadena, California, and the California Institute of Technology in Pasadena, analyzed interferometric synthetic aperture radar images from the European Union's Copernicus Sentinel-1A satellite, operated by the European Space Agency and also available from the Alaska Satellite Facility (https://www.asf.alaska.edu), to calculate a map of the deformation of Earth's surface caused by the quake. This false-color map shows the amount of permanent surface movement caused almost entirely by the earthquake, as viewed by the satellite, during a 12-day interval between two Sentinel-1 images acquired on April 17 and April 29, 2015. In the map, surface displacements are seen as color contours (or "fringes"), where each color cycle represents 8 inches (20 centimeters) of surface motion. The contours show the land around Kathmandu has moved upward by more than 40 inches (1 meter). Areas without the color contours have snow or heavy vegetation that affects the radar measurements. Scientists use these maps to build detailed models of the fault and associated land movements to better understand the impact on future earthquake activity. The background image is from Google Earth. The map contains Copernicus data (2015). http://photojournal.jpl.nasa.gov/catalog/PIA19535

(Meta)Search like Google

ERIC Educational Resources Information Center

Rochkind, Jonathan

2007-01-01

The ability to search and receive results in more than one database through a single interface--or metasearch--is something many users want. Google Scholar--the search engine of specifically scholarly content--and library metasearch products like Ex Libris's MetaLib, Serials Solution's Central Search, WebFeat, and products based on MuseGlobal used…

Comparison of PubMed and Google Scholar literature searches.

PubMed

Anders, Michael E; Evans, Dennis P

2010-05-01

Literature searches are essential to evidence-based respiratory care. To conduct literature searches, respiratory therapists rely on search engines to retrieve information, but there is a dearth of literature on the comparative efficiencies of search engines for researching clinical questions in respiratory care. To compare PubMed and Google Scholar search results for clinical topics in respiratory care to that of a benchmark. We performed literature searches with PubMed and Google Scholar, on 3 clinical topics. In PubMed we used the Clinical Queries search filter. In Google Scholar we used the search filters in the Advanced Scholar Search option. We used the reference list of a related Cochrane Collaboration evidence-based systematic review as the benchmark for each of the search results. We calculated recall (sensitivity) and precision (positive predictive value) with 2 x 2 contingency tables. We compared the results with the chi-square test of independence and Fisher's exact test. PubMed and Google Scholar had similar recall for both overall search results (71% vs 69%) and full-text results (43% vs 51%). PubMed had better precision than Google Scholar for both overall search results (13% vs 0.07%, P < .001) and full-text results (8% vs 0.05%, P < .001). Our results suggest that PubMed searches with the Clinical Queries filter are more precise than with the Advanced Scholar Search in Google Scholar for respiratory care topics. PubMed appears to be more practical to conduct efficient, valid searches for informing evidence-based patient-care protocols, for guiding the care of individual patients, and for educational purposes.

Infrared cloud imaging in support of Earth-space optical communication.

PubMed

Nugent, Paul W; Shaw, Joseph A; Piazzolla, Sabino

2009-05-11

The increasing need for high data return from near-Earth and deep-space missions is driving a demand for the establishment of Earth-space optical communication links. These links will require a nearly obstruction-free path to the communication platform, so there is a need to measure spatial and temporal statistics of clouds at potential ground-station sites. A technique is described that uses a ground-based thermal infrared imager to provide continuous day-night cloud detection and classification according to the cloud optical depth and potential communication channel attenuation. The benefit of retrieving cloud optical depth and corresponding attenuation is illustrated through measurements that identify cloudy times when optical communication may still be possible through thin clouds.

Earth on the Horizon

NASA Image and Video Library

2004-03-13

This is the first image ever taken of Earth from the surface of a planet beyond the Moon. It was taken by the Mars Exploration Rover Spirit one hour before sunrise on the 63rd martian day, or sol, of its mission. Earth is the tiny white dot in the center. The image is a mosaic of images taken by the rover's navigation camera showing a broad view of the sky, and an image taken by the rover's panoramic camera of Earth. The contrast in the panoramic camera image was increased two times to make Earth easier to see. http://photojournal.jpl.nasa.gov/catalog/PIA05560

Live ECG readings using Google Glass in emergency situations.

PubMed

Schaer, Roger; Salamin, Fanny; Jimenez Del Toro, Oscar Alfonso; Atzori, Manfredo; Muller, Henning; Widmer, Antoine

2015-01-01

Most sudden cardiac problems require rapid treatment to preserve life. In this regard, electrocardiograms (ECG) shown on vital parameter monitoring systems help medical staff to detect problems. In some situations, such monitoring systems may display information in a less than convenient way for medical staff. For example, vital parameters are displayed on large screens outside the field of view of a surgeon during cardiac surgery. This may lead to losing time and to mistakes when problems occur during cardiac operations. In this paper we present a novel approach to display vital parameters such as the second derivative of the ECG rhythm and heart rate close to the field of view of a surgeon using Google Glass. As a preliminary assessment, we run an experimental study to verify the possibility for medical staff to identify abnormal ECG rhythms from Google Glass. This study compares 6 ECG rhythms readings from a 13.3 inch laptop screen and from the prism of Google Glass. Seven medical residents in internal medicine participated in the study. The preliminary results show that there is no difference between identifying these 6 ECG rhythms from the laptop screen versus Google Glass. Both allow close to perfect identification of the 6 common ECG rhythms. This shows the potential of connected glasses such as Google Glass to be useful in selected medical applications.

Using Google AdWords in the MBA MIS Course

ERIC Educational Resources Information Center

Rosso, Mark A.; McClelland, Marilyn K.; Jansen, Bernard J.; Fleming, Sundar W.

2009-01-01

From February to June 2008, Google ran its first ever student competition in sponsored Web search, the 2008 Google Online Marketing Challenge (GOMC). The 2008 GOMC was based on registrations from 61 countries: 629 course sections from 468 universities participated, fielding over 4000 student teams of approximately 21,000 students. Working with a…

Rage against the machine? Google's self-driving cars versus human drivers.

PubMed

Teoh, Eric R; Kidd, David G

2017-12-01

Automated driving represents both challenges and opportunities in highway safety. Google has been developing self-driving cars and testing them under employee supervision on public roads since 2009. These vehicles have been involved in several crashes, and it is of interest how this testing program compares to human drivers in terms of safety. Google car crashes were coded by type and severity based on narratives released by Google. Crash rates per million vehicle miles traveled (VMT) were computed for crashes deemed severe enough to be reportable to police. These were compared with police-reported crash rates for human drivers. Crash types also were compared. Google cars had a much lower rate of police-reportable crashes per million VMT than human drivers in Mountain View, Calif., during 2009-2015 (2.19 vs 6.06), but the difference was not statistically significant. The most common type of collision involving Google cars was when they got rear-ended by another (human-driven) vehicle. Google cars shared responsibility for only one crash. These results suggest Google self-driving cars, while a test program, are safer than conventional human-driven passenger vehicles; however, currently there is insufficient information to fully examine the extent to which disengagements affected these results. Results suggest that highly-automated vehicles can perform more safely than human drivers in certain conditions, but will continue to be involved in crashes with conventionally-driven vehicles. Copyright © 2017. Published by Elsevier Ltd.

The NASA Airborne Earth Science Microwave Imaging Radiometer (AESMIR): A New Sensor for Earth Remote Sensing

NASA Technical Reports Server (NTRS)

Kim, Edward

2003-01-01

The Airborne Earth Science Microwave Imaging Radiometer (AESMIR) is a versatile new airborne imaging radiometer recently developed by NASA. The AESMIR design is unique in that it performs dual-polarized imaging at all standard passive microwave frequency bands (6-89 GHz) using only one sensor headscanner package, providing an efficient solution for Earth remote sensing applications (snow, soil moisture/land parameters, precipitation, ocean winds, sea surface temperature, water vapor, sea ice, etc.). The microwave radiometers themselves will incorporate state-of-the-art receivers, with particular attention given to instrument calibration for the best possible accuracy and sensitivity. The single-package design of AESMIR makes it compatible with high-altitude aircraft platforms such as the NASA ER-2s. The arbitrary 2-axis gimbal can perform conical and cross-track scanning, as well as fixed-beam staring. This compatibility with high-altitude platforms coupled with the flexible scanning configuration, opens up previously unavailable science opportunities for convection/precip/cloud science and co-flying with complementary instruments, as well as providing wider swath coverage for all science applications. By designing AESMIR to be compatible with these high-altitude platforms, we are also compatible with the NASA P-3, the NASA DC-8, C-130s and ground-based deployments. Thus AESMIR can provide low-, mid-, and high- altitude microwave imaging. Parallel filter banks allow AESMIR to simultaneously simulate the exact passbands of multiple satellite radiometers: SSM/I, TMI, AMSR, Windsat, SSMI/S, and the upcoming GPM/GMI and NPOESS/CMIS instruments --a unique capability among aircraft radiometers. An L-band option is also under development, again using the same scanner. With this option, simultaneous imaging from 1.4 to 89 GHz will be feasible. And, all receivers except the sounding channels will be configured for 4-Stokes polarimetric operation using high-speed digital

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.

Using Google Glass in Nonsurgical Medical Settings: Systematic Review.

PubMed

Dougherty, Bryn; Badawy, Sherif M

2017-10-19

Wearable technologies provide users hands-free access to computer functions and are becoming increasingly popular on both the consumer market and in various industries. The medical industry has pioneered research and implementation of head-mounted wearable devices, such as Google Glass. Most of this research has focused on surgical interventions; however, other medical fields have begun to explore the potential of this technology to support both patients and clinicians. Our aim was to systematically evaluate the feasibility, usability, and acceptability of using Google Glass in nonsurgical medical settings and to determine the benefits, limitations, and future directions of its application. This review covers literature published between January 2013 and May 2017. Searches included PubMed MEDLINE, Embase, INSPEC (Ebsco), Cochrane Central Register of Controlled Trials (CENTRAL), IEEE Explore, Web of Science, Scopus, and Compendex. The search strategy sought all articles on Google Glass. Two reviewers independently screened titles and abstracts, assessed full-text articles, and extracted data from articles that met all predefined criteria. Any disagreements were resolved by discussion or consultation by the senior author. Included studies were original research articles that evaluated the feasibility, usability, or acceptability of Google Glass in nonsurgical medical settings. The preferred reporting results of systematic reviews and meta-analyses (PRISMA) guidelines were followed for reporting of results. Of the 852 records examined, 51 met all predefined criteria, including patient-centered (n=21) and clinician-centered studies (n=30). Patient-centered studies explored the utility of Google Glass in supporting patients with motor impairments (n=8), visual impairments (n=5), developmental and psychiatric disorders (n=2), weight management concerns (n=3), allergies (n=1), or other health concerns (n=2). Clinician-centered studies explored the utility of Google Glass

Using Google Glass in Nonsurgical Medical Settings: Systematic Review

PubMed Central

Dougherty, Bryn

2017-01-01

Background Wearable technologies provide users hands-free access to computer functions and are becoming increasingly popular on both the consumer market and in various industries. The medical industry has pioneered research and implementation of head-mounted wearable devices, such as Google Glass. Most of this research has focused on surgical interventions; however, other medical fields have begun to explore the potential of this technology to support both patients and clinicians. Objective Our aim was to systematically evaluate the feasibility, usability, and acceptability of using Google Glass in nonsurgical medical settings and to determine the benefits, limitations, and future directions of its application. Methods This review covers literature published between January 2013 and May 2017. Searches included PubMed MEDLINE, Embase, INSPEC (Ebsco), Cochrane Central Register of Controlled Trials (CENTRAL), IEEE Explore, Web of Science, Scopus, and Compendex. The search strategy sought all articles on Google Glass. Two reviewers independently screened titles and abstracts, assessed full-text articles, and extracted data from articles that met all predefined criteria. Any disagreements were resolved by discussion or consultation by the senior author. Included studies were original research articles that evaluated the feasibility, usability, or acceptability of Google Glass in nonsurgical medical settings. The preferred reporting results of systematic reviews and meta-analyses (PRISMA) guidelines were followed for reporting of results. Results Of the 852 records examined, 51 met all predefined criteria, including patient-centered (n=21) and clinician-centered studies (n=30). Patient-centered studies explored the utility of Google Glass in supporting patients with motor impairments (n=8), visual impairments (n=5), developmental and psychiatric disorders (n=2), weight management concerns (n=3), allergies (n=1), or other health concerns (n=2). Clinician-centered studies

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.

The Earth & Moon

NASA Image and Video Library

1998-06-04

During its flight, NASA’s Galileo spacecraft returned images of the Earth and Moon. Separate images of the Earth and Moon were combined to generate this view. http://photojournal.jpl.nasa.gov/catalog/PIA00342

Correlation between national influenza surveillance data and google trends in South Korea.

PubMed

Cho, Sungjin; Sohn, Chang Hwan; Jo, Min Woo; Shin, Soo-Yong; Lee, Jae Ho; Ryoo, Seoung Mok; Kim, Won Young; Seo, Dong-Woo

2013-01-01

In South Korea, there is currently no syndromic surveillance system using internet search data, including Google Flu Trends. The purpose of this study was to investigate the correlation between national influenza surveillance data and Google Trends in South Korea. Our study was based on a publicly available search engine database, Google Trends, using 12 influenza-related queries, from September 9, 2007 to September 8, 2012. National surveillance data were obtained from the Korea Centers for Disease Control and Prevention (KCDC) influenza-like illness (ILI) and virologic surveillance system. Pearson's correlation coefficients were calculated to compare the national surveillance and the Google Trends data for the overall period and for 5 influenza seasons. The correlation coefficient between the KCDC ILI and virologic surveillance data was 0.72 (p<0.05). The highest correlation was between the Google Trends query of H1N1 and the ILI data, with a correlation coefficient of 0.53 (p<0.05), for the overall study period. When compared with the KCDC virologic data, the Google Trends query of bird flu had the highest correlation with a correlation coefficient of 0.93 (p<0.05) in the 2010-11 season. The following queries showed a statistically significant correlation coefficient compared with ILI data for three consecutive seasons: Tamiflu (r = 0.59, 0.86, 0.90, p<0.05), new flu (r = 0.64, 0.43, 0.70, p<0.05) and flu (r = 0.68, 0.43, 0.77, p<0.05). In our study, we found that the Google Trends for certain queries using the survey on influenza correlated with national surveillance data in South Korea. The results of this study showed that Google Trends in the Korean language can be used as complementary data for influenza surveillance but was insufficient for the use of predictive models, such as Google Flu Trends.

100 Colleges Sign Up with Google to Speed Access to Library Resources

ERIC Educational Resources Information Center

Young, Jeffrey R.

2005-01-01

More than 100 colleges and universities have arranged to give people using the Google Scholar search engine on their campuses more-direct access to library materials. Google Scholar is a free tool that searches scholarly materials on the Web and in academic databases. The new arrangements essentially let Google know which online databases the…

Interpretation of Coronary Angiograms Recorded Using Google Glass: A Comparative Analysis.

PubMed

Duong, Thao; Wosik, Jedrek; Christakopoulos, Georgios E; Martínez Parachini, José Roberto; Karatasakis, Aris; Tarar, Muhammad Nauman Javed; Resendes, Erica; Rangan, Bavana V; Roesle, Michele; Grodin, Jerrold; Abdullah, Shuaib M; Banerjee, Subhash; Brilakis, Emmanouil S

2015-10-01

Google Glass (Google, Inc) is a voice-activated, hands-free, optical head-mounted display device capable of taking pictures, recording videos, and transmitting data via wi-fi. In the present study, we examined the accuracy of coronary angiogram interpretation, recorded using Google Glass. Google Glass was used to record 15 angiograms with 17 major findings and the participants were asked to interpret those recordings on: (1) an iPad (Apple, Inc); or (2) a desktop computer. Interpretation was compared with the original angiograms viewed on a desktop. Ten physicians (2 interventional cardiologists and 8 cardiology fellows) participated. One point was assigned for each correct finding, for a maximum of 17 points. The mean angiogram interpretation score for Google Glass angiogram recordings viewed on an iPad or a desktop vs the original angiograms viewed on a desktop was 14.9 ± 1.1, 15.2 ± 1.8, and 15.9 ± 1.1, respectively (P=.06 between the iPad and the original angiograms, P=.51 between the iPad and recordings viewed on a desktop, and P=.43 between the recordings viewed on a desktop and the original angiograms). In a post-study survey, one of the 10 physicians (10%) was "neutral" with the quality of the recordings using Google Glass, 6 physicians (60%) were "somewhat satisfied," and 3 physicians (30%) were "very satisfied." This small pilot study suggests that the quality of coronary angiogram video recordings obtained using Google Glass may be adequate for recognition of major findings, supporting its expanding use in telemedicine.

The visible, near-infrared and short wave infrared channels of the EarthCARE multi-spectral imager

NASA Astrophysics Data System (ADS)

Doornink, J.; de Goeij, B.; Marinescu, O.; Meijer, E.; Vink, R.; van Werkhoven, W.; van't Hof, A.

2017-11-01

The EarthCARE satellite mission objective is the observation of clouds and aerosols from low Earth orbit. The payload will include active remote sensing instruments being the W-band Cloud Profiling Radar (CPR) and the ATLID LIDAR. These are supported by the passive instruments Broadband Radiometer (BBR) and the Multispectral Imager (MSI) providing the radiometric and spatial context of the ground scene being probed. The MSI will form Earth images over a swath width of 150 km; it will image the Earth atmosphere in 7 spectral bands. The MSI instrument consists of two parts: the Visible, Near infrared and Short wave infrared (VNS) unit, and the Thermal InfraRed (TIR) unit. Subject of this paper is the VNS unit. In the VNS optical unit, the ground scene is imaged in four spectral bands onto four linear detectors via separate optical channels. Driving requirements for the VNS instrument performance are the spectral sensitivity including out-of-band rejection, the MTF, co-registration and the inter-channel radiometric accuracy. The radiometric accuracy performance of the VNS is supported by in-orbit calibration, in which direct solar radiation is fed into the instrument via a set of quasi volume diffusers. The compact optical concept with challenging stability requirements together with the strict thermal constraints have led to a sophisticated opto-mechanical design. This paper, being the second of a sequence of two on the Multispectral Imager describes the VNS instrument concept chosen to fulfil the performance requirements within the resource and accommodation constraints.

Management of scientific information with Google Drive.

PubMed

Kubaszewski, Łukasz; Kaczmarczyk, Jacek; Nowakowski, Andrzej

2013-09-20

The amount and diversity of scientific publications requires a modern management system. By "management" we mean the process of gathering interesting information for the purpose of reading and archiving for quick access in future clinical practice and research activity. In the past, such system required physical existence of a library, either institutional or private. Nowadays in an era dominated by electronic information, it is natural to migrate entire systems to a digital form. In the following paper we describe the structure and functions of an individual electronic library system (IELiS) for the management of scientific publications based on the Google Drive service. Architecture of the system. Architecture system consists of a central element and peripheral devices. Central element of the system is virtual Google Drive provided by Google Inc. Physical elements of the system include: tablet with Android operating system and a personal computer, both with internet access. Required software includes a program to view and edit files in PDF format for mobile devices and another to synchronize the files. Functioning of the system. The first step in creating a system is collection of scientific papers in PDF format and their analysis. This step is performed most frequently on a tablet. At this stage, after being read, the papers are cataloged in a system of folders and subfolders, according to individual demands. During this stage, but not exclusively, the PDF files are annotated by the reader. This allows the user to quickly track down interesting information in review or research process. Modification of the document title is performed at this stage, as well. Second element of the system is creation of a mirror database in the Google Drive virtual memory. Modified and cataloged papers are synchronized with Google Drive. At this stage, a fully functional scientific information electronic library becomes available online. The third element of the system is a

Students' Google Drive Intended Usage: A Case Study of Mathematics Courses in Bangkok University

ERIC Educational Resources Information Center

Prasertsith, Krisawan; Kanthawongs, Penjira; Limpachote, Tan

2016-01-01

Many technologies have changed the way individuals live and learn. Google Inc. has played significant roles in business and academic worlds. Google Apps for Education and Google Classroom have been offered to higher institutions around the globe. Although large cloud service provider such as Google do not encrypt all their stored electronic data…

Institutional Repositories in the UK: What Can the Google User Find There?

ERIC Educational Resources Information Center

Markland, Margaret

2006-01-01

This study investigates the efficiency of the Google search engine at retrieving items from 26 UK Institutional Repositories, covering a wide range of subject areas. One item is chosen from each repository and four searches are carried out: two keyword searches and two full title searches, each using both Google and then Google Scholar. A further…

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

Scholars Are Wary of Deal on Google's Book Search

ERIC Educational Resources Information Center

Howard, Jennifer

2009-01-01

Google's Book Search program mines the holdings of research libraries for texts to digitize. Some of that material is out of copyright; a lot of it isn't. A lawsuit came about when some authors and publishers decided that Google's project exceeded the bounds of fair use. As part of a settlement, the parties have proposed creating a Book Rights…

Going Google: Powerful Tools for 21st Century Learning

ERIC Educational Resources Information Center

Covili, Jared

2012-01-01

Google is more than a search engine--it offers many tools that give people the opportunity to work virtually from anywhere, with anyone, at any time they choose. And these tools are available to teachers and students for free. This book for K-12 educators explores the wide array of Google tools and shows how to use them in the classroom to foster…

Use of Google Scholar public profiles in orthopedics.

PubMed

Tetsworth, Kevin; Fraser, Dave; Glatt, Vaida; Hohmann, Erik

2017-01-01

The purpose of this study was to survey the growth of Google Scholar public profiles in orthopedics over a 12-month period and to investigate global patterns. Data was prospectively acquired from June 2013 to June 2014. Google Scholar queries specific to orthopedic surgery were performed at 90-day intervals. Demographic aspects of each user were also compiled, including gender, current location, and primary interests. To determine differences between the growth of Google Scholar public profile registrations and citation counts, as well as differences in growth in different regions, repeated measures of analysis of variance (RMANOVA) were used. RMANOVA revealed statistically significant differences ( p = 0.0001) for regional growth. The largest growth was observed in the United Kingdom ( p = 0.009, 289%), followed by the Asia-Pacific region ( p = 0.004, 177%) and "Other" ( p = 0.006, 172%). The mean growth per 90-day interval is 19.9% ( p = 0.003) and the mean 12-month growth is 107% ( p = 0.05). Statistically significant differences between gender (male vs. female) and basic and clinical sciences ( χ 2 = 22.4, p = 0.0001) were observed. This study suggests an exponential growth in the number of authors in the field of orthopedic surgery creating a Google Scholar public profile, and at the current rate participation doubles every 10.6 months.

Measurable realistic image-based 3D mapping

NASA Astrophysics Data System (ADS)

Liu, W.; Wang, J.; Wang, J. J.; Ding, W.; Almagbile, A.

2011-12-01

Maps with 3D visual models are becoming a remarkable feature of 3D map services. High-resolution image data is obtained for the construction of 3D visualized models.The3D map not only provides the capabilities of 3D measurements and knowledge mining, but also provides the virtual experienceof places of interest, such as demonstrated in the Google Earth. Applications of 3D maps are expanding into the areas of architecture, property management, and urban environment monitoring. However, the reconstruction of high quality 3D models is time consuming, and requires robust hardware and powerful software to handle the enormous amount of data. This is especially for automatic implementation of 3D models and the representation of complicated surfacesthat still need improvements with in the visualisation techniques. The shortcoming of 3D model-based maps is the limitation of detailed coverage since a user can only view and measure objects that are already modelled in the virtual environment. This paper proposes and demonstrates a 3D map concept that is realistic and image-based, that enables geometric measurements and geo-location services. Additionally, image-based 3D maps provide more detailed information of the real world than 3D model-based maps. The image-based 3D maps use geo-referenced stereo images or panoramic images. The geometric relationships between objects in the images can be resolved from the geometric model of stereo images. The panoramic function makes 3D maps more interactive with users but also creates an interesting immersive circumstance. Actually, unmeasurable image-based 3D maps already exist, such as Google street view, but only provide virtual experiences in terms of photos. The topographic and terrain attributes, such as shapes and heights though are omitted. This paper also discusses the potential for using a low cost land Mobile Mapping System (MMS) to implement realistic image 3D mapping, and evaluates the positioning accuracy that a measureable

Methodology for classification of geographical features with remote sensing images: Application to tidal flats

NASA Astrophysics Data System (ADS)

Revollo Sarmiento, G. N.; Cipolletti, M. P.; Perillo, M. M.; Delrieux, C. A.; Perillo, Gerardo M. E.

2016-03-01

Tidal flats generally exhibit ponds of diverse size, shape, orientation and origin. Studying the genesis, evolution, stability and erosive mechanisms of these geographic features is critical to understand the dynamics of coastal wetlands. However, monitoring these locations through direct access is hard and expensive, not always feasible, and environmentally damaging. Processing remote sensing images is a natural alternative for the extraction of qualitative and quantitative data due to their non-invasive nature. In this work, a robust methodology for automatic classification of ponds and tidal creeks in tidal flats using Google Earth images is proposed. The applicability of our method is tested in nine zones with different morphological settings. Each zone is processed by a segmentation stage, where ponds and tidal creeks are identified. Next, each geographical feature is measured and a set of shape descriptors is calculated. This dataset, together with a-priori classification of each geographical feature, is used to define a regression model, which allows an extensive automatic classification of large volumes of data discriminating ponds and tidal creeks against other various geographical features. In all cases, we identified and automatically classified different geographic features with an average accuracy over 90% (89.7% in the worst case, and 99.4% in the best case). These results show the feasibility of using freely available Google Earth imagery for the automatic identification and classification of complex geographical features. Also, the presented methodology may be easily applied in other wetlands of the world and perhaps employing other remote sensing imagery.

Confessions of a Librarian or: How I Learned to Stop Worrying and Love Google

ERIC Educational Resources Information Center

Gunnels, Claire B.; Sisson, Amy

2009-01-01

Have you ever stopped to think about life before Google? We will make the argument that Google is the first manifestation of Web 2.0, of the power and promise of social networking and the ubiquitous wiki. We will discuss the positive influence of Google and how Google and other social networking tools afford librarians leading-edge technologies…

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.

Temporal patterns of scientific information-seeking on Google and Wikipedia.

PubMed

Segev, Elad; Sharon, Aviv J

2017-11-01

In response to the news coverage of scientific events and to science education, people increasingly go online to get more information. This study investigates how patterns of science and technology information-seeking on Google and Wikipedia change over time, in ways that differ between "ad hoc" terms that correspond to news coverage and "cyclic" terms that correspond to the academic period. Findings show that the science and technology activity in Google and Wikipedia was significantly associated with ad hoc and cyclic patterns. While the peak activity in Google and Wikipedia largely overlapped for ad hoc terms, it mismatched for cyclic terms. The findings indicate the importance of external cues such as news media and education, and also of the online engagement process, and particularly the crucial but different role played by Google and Wikipedia in gaining science and technology knowledge. Educators and policy makers could benefit from taking into account those different patterns.

PsyGlass: Capitalizing on Google Glass for naturalistic data collection.

PubMed

Paxton, Alexandra; Rodriguez, Kevin; Dale, Rick

2015-09-01

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

Medical literature searches: a comparison of PubMed and Google Scholar.

PubMed

Nourbakhsh, Eva; Nugent, Rebecca; Wang, Helen; Cevik, Cihan; Nugent, Kenneth

2012-09-01

Medical literature searches provide critical information for clinicians. However, the best strategy for identifying relevant high-quality literature is unknown. We compared search results using PubMed and Google Scholar on four clinical questions and analysed these results with respect to article relevance and quality. Abstracts from the first 20 citations for each search were classified into three relevance categories. We used the weighted kappa statistic to analyse reviewer agreement and nonparametric rank tests to compare the number of citations for each article and the corresponding journals' impact factors. Reviewers ranked 67.6% of PubMed articles and 80% of Google Scholar articles as at least possibly relevant (P = 0.116) with high agreement (all kappa P-values < 0.01). Google Scholar articles had a higher median number of citations (34 vs. 1.5, P < 0.0001) and came from higher impact factor journals (5.17 vs. 3.55, P = 0.036). PubMed searches and Google Scholar searches often identify different articles. In this study, Google Scholar articles were more likely to be classified as relevant, had higher numbers of citations and were published in higher impact factor journals. The identification of frequently cited articles using Google Scholar for searches probably has value for initial literature searches. © 2012 The authors. Health Information and Libraries Journal © 2012 Health Libraries Group.

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…

Integration of Apollo Lunar Sample Data into Google Moon

NASA Technical Reports Server (NTRS)

Dawson, Melissa D.; Todd, Nancy S.; Lofgren, Gary

2010-01-01

The Google Moon Apollo Lunar Sample Data Integration project is a continuation of the Apollo 15 Google Moon Add-On project, which provides a scientific and educational tool for the study of the Moon and its geologic features. The main goal of this project is to provide a user-friendly interface for an interactive and educational outreach and learning tool for the Apollo missions. Specifically, this project?s focus is the dissemination of information about the lunar samples collected during the Apollo missions by providing any additional information needed to enhance the Apollo mission data on Google Moon. Apollo missions 15 and 16 were chosen to be completed first due to the availability of digitized lunar sample photographs and the amount of media associated with these missions. The user will be able to learn about the lunar samples collected in these Apollo missions, as well as see videos, pictures, and 360 degree panoramas of the lunar surface depicting the lunar samples in their natural state, following collection and during processing at NASA. Once completed, these interactive data layers will be submitted for inclusion into the Apollo 15 and 16 missions on Google Moon.

[Pruritus in Germany-a Google search engine analysis].

PubMed

Zink, A; Rüth, M; Schuster, B; Darsow, U; Biedermann, T; Ständer, S

2018-06-06

Because affected persons often do not visit a doctor, the prevalence of chronic and acute pruritus in the general population is difficult to determine. The aim of this study is to estimate the frequency and the most common locations of pruritus in German internet users, who-with 62.4 million persons-represent a large majority of the German population, by analysing the Google search volume. Relevant keywords for the subject "pruritus" were identified and analysed using the Google AdWords Keyword Planner. The assessment period was January 2015 to December 2016. In total the Google AdWords Keyword Planner identified 701 keywords for the topic "Juckreiz" (German lay word for pruritus), resulting in 7,531,890 pruritus-related Google searches during the assessment period. Most common search terms were the German lay term for atopic eczema ("Neurodermitis", 23.7%), the German lay term for psoriasis ("Schuppenflechte", 17.8%) and "psoriasis" (13%). The German lay term for pruritus ("Juckreiz") was only the sixth most searched term (3%). Most searches (72%) focused on influencing factors for pruritus, especially on skin diseases and skin conditions. The most commonly searched location was pruritus on the whole body, followed by anal pruritus. Analysis of the temporal course showed a higher monthly search volume during winter. With its unconventional methodology, a Google search engine analysis, this study allows a rough estimation of the medical need of pruritus in the German general population, which seems to be higher than expected. Especially pruritus in the anal area was identified as an unmet medical need.

Going beyond Google for Faster and Smarter Web Searching

ERIC Educational Resources Information Center

Vine, Rita

2004-01-01

With more than 4 billion web pages in its database, Google is suitable for many different kinds of searches. When you know what you are looking for, Google can be a pretty good first choice, as long as you want to search a word pattern that can be expected to appear on any results pages. The problem starts when you don't know exactly what you're…

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

Google Maps offers a new way to evaluate claudication.

PubMed

Khambati, Husain; Boles, Kim; Jetty, Prasad

2017-05-01

Accurate determination of walking capacity is important for the clinical diagnosis and management plan for patients with peripheral arterial disease. The current "gold standard" of measurement is walking distance on a treadmill. However, treadmill testing is not always reflective of the patient's natural walking conditions, and it may not be fully accessible in every vascular clinic. The objective of this study was to determine whether Google Maps, the readily available GPS-based mapping tool, offers an accurate and accessible method of evaluating walking distances in vascular claudication patients. Patients presenting to the outpatient vascular surgery clinic between November 2013 and April 2014 at the Ottawa Hospital with vasculogenic calf, buttock, and thigh claudication symptoms were identified and prospectively enrolled in our study. Onset of claudication symptoms and maximal walking distance (MWD) were evaluated using four tools: history; Walking Impairment Questionnaire (WIQ), a validated claudication survey; Google Maps distance calculator (patients were asked to report their daily walking routes on the Google Maps-based tool runningmap.com, and walking distances were calculated accordingly); and treadmill testing for onset of symptoms and MWD, recorded in a double-blinded fashion. Fifteen patients were recruited for the study. Determination of walking distances using Google Maps proved to be more accurate than by both clinical history and WIQ, correlating highly with the gold standard of treadmill testing for both claudication onset (r = .805; P < .001) and MWD (r = .928; P < .0001). In addition, distances were generally under-reported on history and WIQ. The Google Maps tool was also efficient, with reporting times averaging below 4 minutes. For vascular claudicants with no other walking limitations, Google Maps is a promising new tool that combines the objective strengths of the treadmill test and incorporates real-world walking environments. It

Google Analytics – Index of Resources

EPA Pesticide Factsheets

Find how-to and best practice resources and training for accessing and understanding EPA's Google Analytics (GA) tools, including how to create reports that will help you improve and maintain the web areas you manage.

Data to Pictures to Data: Outreach Imaging Software and Metadata

NASA Astrophysics Data System (ADS)

Levay, Z.

2011-07-01

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

Correlation between National Influenza Surveillance Data and Google Trends in South Korea

PubMed Central

Jo, Min Woo; Shin, Soo-Yong; Lee, Jae Ho; Ryoo, Seoung Mok; Kim, Won Young; Seo, Dong-Woo

2013-01-01

Background In South Korea, there is currently no syndromic surveillance system using internet search data, including Google Flu Trends. The purpose of this study was to investigate the correlation between national influenza surveillance data and Google Trends in South Korea. Methods Our study was based on a publicly available search engine database, Google Trends, using 12 influenza-related queries, from September 9, 2007 to September 8, 2012. National surveillance data were obtained from the Korea Centers for Disease Control and Prevention (KCDC) influenza-like illness (ILI) and virologic surveillance system. Pearson's correlation coefficients were calculated to compare the national surveillance and the Google Trends data for the overall period and for 5 influenza seasons. Results The correlation coefficient between the KCDC ILI and virologic surveillance data was 0.72 (p<0.05). The highest correlation was between the Google Trends query of H1N1 and the ILI data, with a correlation coefficient of 0.53 (p<0.05), for the overall study period. When compared with the KCDC virologic data, the Google Trends query of bird flu had the highest correlation with a correlation coefficient of 0.93 (p<0.05) in the 2010-11 season. The following queries showed a statistically significant correlation coefficient compared with ILI data for three consecutive seasons: Tamiflu (r = 0.59, 0.86, 0.90, p<0.05), new flu (r = 0.64, 0.43, 0.70, p<0.05) and flu (r = 0.68, 0.43, 0.77, p<0.05). Conclusions In our study, we found that the Google Trends for certain queries using the survey on influenza correlated with national surveillance data in South Korea. The results of this study showed that Google Trends in the Korean language can be used as complementary data for influenza surveillance but was insufficient for the use of predictive models, such as Google Flu Trends. PMID:24339927

Earth Reflectivity from Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Camera (EPIC)

NASA Astrophysics Data System (ADS)

Song, W.; Knyazikhin, Y.; Wen, G.; Marshak, A.; Yan, G.; Mu, X.; Park, T.; Chen, C.; Xu, B.; Myneni, R. B.

2017-12-01

Earth reflectivity, which is also specified as Earth albedo or Earth reflectance, is defined as the fraction of incident solar radiation reflected back to space at the top of the atmosphere. It is a key climate parameter that describes climate forcing and associated response of the climate system. Satellite is one of the most efficient ways to measure earth reflectivity. Conventional polar orbit and geostationary satellites observe the Earth at a specific local solar time or monitor only a specific area of the Earth. For the first time, the NASA's Earth Polychromatic Imaging Camera (EPIC) onboard NOAA's Deep Space Climate Observatory (DSCOVR) collects simultaneously radiance data of the entire sunlit earth at 8 km resolution at nadir every 65 to 110 min. It provides reflectivity images in backscattering direction with the scattering angle between 168º and 176º at 10 narrow spectral bands in ultraviolet, visible, and near-Infrared (NIR) wavelengths. We estimate the Earth reflectivity using DSCOVR EPIC observations and analyze errors in Earth reflectivity due to sampling strategy of polar orbit Terra/Aqua MODIS and geostationary Goddard Earth Observing System-R series missions. We also provide estimates of contributions from ocean, clouds, land and vegetation to the Earth reflectivity. Graphic abstract shows enhanced RGB EPIC images of the Earth taken on July-24-2016 at 7:04GMT and 15:48 GMT. Parallel lines depict a 2330 km wide Aqua MODIS swath. The plot shows diurnal courses of mean Earth reflectance over the Aqua swath (triangles) and the entire image (circles). In this example the relative difference between the mean reflectances is +34% at 7:04GMT and -16% at 15:48 GMT. Corresponding daily averages are 0.256 (0.044) and 0.231 (0.025). The relative precision estimated as root mean square relative error is 17.9% in this example.