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.

Make Your Own Mashup Maps

ERIC Educational Resources Information Center

Lucking, Robert A.; Christmann, Edwin P.; Whiting, Mervyn J.

2008-01-01

"Mashup" is a new technology term used to describe a web application that combines data or technology from several different sources. You can apply this concept in your classroom by having students create their own mashup maps. Google Maps provides you with the simple tools, map databases, and online help you'll need to quickly master this…

In campus location finder using mobile application services

NASA Astrophysics Data System (ADS)

Fai, Low Weng; Audah, Lukman

2017-09-01

Navigation services become very common in this era, the application include Google Map, Waze and etc. Although navigation application contains the main routing service in open area but not all of the buildings are recorded in the database. In this project, an application is made for the indoor and outdoor navigation in Universiti Tun Hussein Onn Malaysia (UTHM). It is used to help outsider and new incoming students by navigating them from their current location to destination using mobile application name "U Finder". Thunkable website has been used to build the application for outdoor and indoor navigation. Outdoor navigation is linked to the Google Map and indoor navigation is using the QR code for positioning and routing picture for navigation. The outdoor navigation can route user to the main faculties in UTHM and indoor navigation is only done for the G1 building in UTHM.

Towards a geospatial wikipedia

NASA Astrophysics Data System (ADS)

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

2009-04-01

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

An interactive GIS based tool on Chinese history and its topography

NASA Astrophysics Data System (ADS)

Konda, Ashish Reddy

The aim of the thesis is to demonstrate how China was attacked by the foreign powers, the rise and fall of the empires, the border conflicts with India, Russia, Vietnam and territorial disputes in South China Sea. This thesis is focused on creating a GIS tool showcasing the modern Chinese history, which includes the major wars fought during that period. This tool is developed using the features of Google Maps that shows the location of the wars. The topography of China is also represented on the interactive Google Map by creating layers for rivers, mountain ranges and deserts. The provinces with highest population are also represented on the Google Map with circles. The application also shows the historical events in chronological order using a timeline feature. This has been implemented using JQuery, JavaScript, HTML5 and CSS. Chinese culture and biographies of important leaders are also included in this thesis, which is embedded with pictures and videos.

How to Display Hazards and other Scientific Data Using Google Maps

NASA Astrophysics Data System (ADS)

Venezky, D. Y.; Fee, J. M.

2007-12-01

The U.S. Geological Survey's (USGS) Volcano Hazard Program (VHP) is launching a map-based interface to display hazards information using the Google® Map API (Application Program Interface). Map-based interfaces provide a synoptic view of data, making patterns easier to detect and allowing users to quickly ascertain where hazards are in relation to major population and infrastructure centers. Several map-based interfaces are now simple to run on a web server, providing ideal platforms for sharing information with colleagues, emergency managers, and the public. There are three main steps to making data accessible on a map-based interface; formatting the input data, plotting the data on the map, and customizing the user interface. The presentation, "Creating Geospatial RSS and ATOM feeds for Map-based Interfaces" (Fee and Venezky, this session), reviews key features for map input data. Join us for this presentation on how to plot data in a geographic context and then format the display with images, custom markers, and links to external data. Examples will show how the VHP Volcano Status Map was created and how to plot a field trip with driving directions.

In Pursuit of Agile Acquisition: Are We There Yet?

DTIC Science & Technology

2013-03-01

digital mapping capabilities like Google , 71Microsoft,72 and Wikimapia,73 are readily obtainable in the commercial marketplace. This knowledge...Fox. Defense Acquisition Reform, 14. 69 Ibid., 8. 70 XBRADTC, “Army Acquisition Woes,” Bring the Heat Bring the Stupid , entry posted May 1, 2011...https://xbradtc.wordpress.com/2011/05/01/Army-acquisition-woes/ (accessed on December 5, 2012). 71 Google Maps, http://maps.google.com/maps (accessed

Online Public Access Catalog: The Google Maps of the Library World

ERIC Educational Resources Information Center

Bailey, Kieren

2011-01-01

What do Google Maps and a library's Online Public Access Catalog (OPAC) have in common? Google Maps provides users with all the information they need for a trip in one place; users can get directions and find out what attractions, hotels, and restaurants are close by. Librarians must find the ultimate OPAC that will provide, in one place, all 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.

Predicting Ambulance Time of Arrival to the Emergency Department Using Global Positioning System and Google Maps

PubMed Central

Fleischman, Ross J.; Lundquist, Mark; Jui, Jonathan; Newgard, Craig D.; Warden, Craig

2014-01-01

Objective To derive and validate a model that accurately predicts ambulance arrival time that could be implemented as a Google Maps web application. Methods This was a retrospective study of all scene transports in Multnomah County, Oregon, from January 1 through December 31, 2008. Scene and destination hospital addresses were converted to coordinates. ArcGIS Network Analyst was used to estimate transport times based on street network speed limits. We then created a linear regression model to improve the accuracy of these street network estimates using weather, patient characteristics, use of lights and sirens, daylight, and rush-hour intervals. The model was derived from a 50% sample and validated on the remainder. Significance of the covariates was determined by p < 0.05 for a t-test of the model coefficients. Accuracy was quantified by the proportion of estimates that were within 5 minutes of the actual transport times recorded by computer-aided dispatch. We then built a Google Maps-based web application to demonstrate application in real-world EMS operations. Results There were 48,308 included transports. Street network estimates of transport time were accurate within 5 minutes of actual transport time less than 16% of the time. Actual transport times were longer during daylight and rush-hour intervals and shorter with use of lights and sirens. Age under 18 years, gender, wet weather, and trauma system entry were not significant predictors of transport time. Our model predicted arrival time within 5 minutes 73% of the time. For lights and sirens transports, accuracy was within 5 minutes 77% of the time. Accuracy was identical in the validation dataset. Lights and sirens saved an average of 3.1 minutes for transports under 8.8 minutes, and 5.3 minutes for longer transports. Conclusions An estimate of transport time based only on a street network significantly underestimated transport times. A simple model incorporating few variables can predict ambulance time of arrival to the emergency department with good accuracy. This model could be linked to global positioning system data and an automated Google Maps web application to optimize emergency department resource use. Use of lights and sirens had a significant effect on transport times. PMID:23865736

Google Maps for Crowdsourced Emergency Routing

NASA Astrophysics Data System (ADS)

Nedkov, S.; Zlatanova, S.

2012-08-01

Gathering infrastructure data in emergency situations is challenging. The affected by a disaster areas are often large and the needed observations numerous. Spaceborne remote sensing techniques cover large areas but they are of limited use as their field of view may be blocked by clouds, smoke, buildings, highways, etc. Remote sensing products furthermore require specialists to collect and analyze the data. This contrasts the nature of the damage detection problem: almost everyone is capable of observing whether a street is usable or not. The crowd is fit for solving these challenges as its members are numerous, they are willing to help and are often in the vicinity of the disaster thereby forming a highly dispersed sensor network. This paper proposes and implements a small WebGIS application for performing shortest path calculations based on crowdsourced information about the infrastructure health. The application is built on top of Google Maps and uses its routing service to calculate the shortest distance between two locations. Impassable areas are indicated on a map by people performing in-situ observations on a mobile device, and by users on a desktop machine who consult a multitude of information sources.

SpaceTime Environmental Image Information for Scene Understanding

DTIC Science & Technology

2016-04-01

public Internet resources such as Google,65 MapQuest,66 Bing,67 and Yahoo Maps.68 Approved for public release; distribution unlimited. 9 Table 3...azimuth angle 3 Terrain and location: USACE AGC — Satellite/aerial imagery and terrain analysis 4 Terrain and location: Google, MapQuest, Bing, Yahoo ...Maps. [accessed 2015 Dec]. https://www.bing.com/maps/. 68. YAHOO ! Maps. [accessed 2015 Dec]. https://maps.yahoo.com/b/. 69. 557th Weather Wing. US

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 offers an accurate, efficient, inexpensive, and readily accessible way to assess walking distances in patients with peripheral vascular disease. Copyright © 2017 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

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.

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

KSC-2013-3233

NASA Image and Video Library

2013-08-09

CAPE CANAVERAL, Fla. – Google used an assortment of vehicles to precisely map NASA's Kennedy Space Center in Florida to be featured on the company's map page. The work allows Internet users to see inside buildings at Kennedy as they were used during the space shuttle era. Google used a car, tricycle and pushcart to maneuver around the center and through some of its facilities. Photo credit: Google/Wendy Wang

Recent Advances in Geospatial Visualization with the New Google Earth

NASA Astrophysics Data System (ADS)

Anderson, J. C.; Poyart, E.; Yan, S.; Sargent, R.

2017-12-01

Google Earth's detailed, world-wide imagery and terrain data provide a rich backdrop for geospatial visualization at multiple scales, from global to local. The Keyhole Markup Language (KML) is an open standard that has been the primary way for users to author and share data visualizations in Google Earth. Despite its ease of use and flexibility for relatively small amounts of data, users can quickly run into difficulties and limitations working with large-scale or time-varying datasets using KML in Google Earth. Recognizing these challenges, we present our recent work toward extending Google Earth to be a more powerful data visualization platform. We describe a new KML extension to simplify the display of multi-resolution map tile pyramids - which can be created by analysis platforms like Google Earth Engine, or by a variety of other map tile production pipelines. We also describe how this implementation can pave the way to creating novel data visualizations by leveraging custom graphics shaders. Finally, we present our investigations into native support in Google Earth for data storage and transport formats that are well-suited for big raster and vector data visualization. Taken together, these capabilities make it easier to create and share new scientific data visualization experiences using Google Earth, and simplify the integration of Google Earth with existing map data products, services, and analysis pipelines.

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

PubMed

Jianu, Radu; Laidlaw, David H

2013-05-04

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

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

PubMed Central

2013-01-01

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

Population resizing on fitness improvement genetic algorithm to optimize promotion visit route based on android and google maps API

NASA Astrophysics Data System (ADS)

Listyorini, Tri; Muzid, Syafiul

2017-06-01

The promotion team of Muria Kudus University (UMK) has done annual promotion visit to several senior high schools in Indonesia. The visits were done to numbers of schools in Kudus, Jepara, Demak, Rembang and Purwodadi. To simplify the visit, each visit round is limited to 15 (fifteen) schools. However, the team frequently faces some obstacles during the visit, particularly in determining the route that they should take toward the targeted school. It is due to the long distance or the difficult route to reach the targeted school that leads to elongated travel duration and inefficient fuel cost. To solve these problems, the development of a certain application using heuristic genetic algorithm method based on the dynamic of population size or Population Resizing on Fitness lmprovement Genetic Algorithm (PRoFIGA), was done. This android-based application was developed to make the visit easier and to determine a shorter route for the team, hence, the visiting period will be effective and efficient. The result of this research was an android-based application to determine the shortest route by combining heuristic method and Google Maps Application Programming lnterface (API) that display the route options for the team.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Supporting our scientists with Google Earth-based UIs.

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

Scott, Janine

2010-10-01

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

Participating in the Geospatial Web: Collaborative Mapping, Social Networks and Participatory GIS

NASA Astrophysics Data System (ADS)

Rouse, L. Jesse; Bergeron, Susan J.; Harris, Trevor M.

In 2005, Google, Microsoft and Yahoo! released free Web mapping applications that opened up digital mapping to mainstream Internet users. Importantly, these companies also released free APIs for their platforms, allowing users to geo-locate and map their own data. These initiatives have spurred the growth of the Geospatial Web and represent spatially aware online communities and new ways of enabling communities to share information from the bottom up. This chapter explores how the emerging Geospatial Web can meet some of the fundamental needs of Participatory GIS projects to incorporate local knowledge into GIS, as well as promote public access and collaborative mapping.

PhyloGeoViz: a web-based program that visualizes genetic data on maps.

PubMed

Tsai, Yi-Hsin E

2011-05-01

The first step of many population genetic studies is the simple visualization of allele frequencies on a landscape. This basic data exploration can be challenging without proprietary software, and the manual plotting of data is cumbersome and unfeasible at large sample sizes. I present an open source, web-based program that plots any kind of frequency or count data as pie charts in Google Maps (Google Inc., Mountain View, CA). Pie polygons are then exportable to Google Earth (Google Inc.), a free Geographic Information Systems platform. Import of genetic data into Google Earth allows phylogeographers access to a wealth of spatial information layers integral to forming hypotheses and understanding patterns in the data. © 2010 Blackwell Publishing Ltd.

Exploring the Effects of Employing Google Docs in Collaborative Concept Mapping on Achievement, Concept Representation, and Attitudes

ERIC Educational Resources Information Center

Lin, Yu-Tzu; Chang, Chia-Hu; Hou, Huei-Tse; Wu, Ke-Chou

2016-01-01

This study investigated the effectiveness of using Google Docs in collaborative concept mapping (CCM) by comparing it with a paper-and-pencil approach. A quasi-experimental study was conducted in a physics course. The control group drew concept maps using the paper-and-pencil method and face-to-face discussion, whereas the experimental group…

KML Super Overlay to WMS Translator

NASA Technical Reports Server (NTRS)

Plesea, Lucian

2007-01-01

This translator is a server-based application that automatically generates KML super overlay configuration files required by Google Earth for map data access via the Open Geospatial Consortium WMS (Web Map Service) standard. The translator uses a set of URL parameters that mirror the WMS parameters as much as possible, and it also can generate a super overlay subdivision of any given area that is only loaded when needed, enabling very large areas of coverage at very high resolutions. It can make almost any dataset available as a WMS service visible and usable in any KML application, without the need to reformat the data.

77 FR 40579 - Tapered Roller Bearings and Parts Thereof, Finished or Unfinished, From the People's Republic of...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-10

... explained in the legislative history of the Omnibus Trade and Competitiveness Act of 1988, the Department... Google Maps: https://maps.google.com . The rates were in effect prior to the POR, so we adjusted them to...

Analysis of world terror networks from the reduced Google matrix of Wikipedia

NASA Astrophysics Data System (ADS)

El Zant, Samer; Frahm, Klaus M.; Jaffrès-Runser, Katia; Shepelyansky, Dima L.

2018-01-01

We apply the reduced Google matrix method to analyze interactions between 95 terrorist groups and determine their relationships and influence on 64 world countries. This is done on the basis of the Google matrix of the English Wikipedia (2017) composed of 5 416 537 articles which accumulate a great part of global human knowledge. The reduced Google matrix takes into account the direct and hidden links between a selection of 159 nodes (articles) appearing due to all paths of a random surfer moving over the whole network. As a result we obtain the network structure of terrorist groups and their relations with selected countries including hidden indirect links. Using the sensitivity of PageRank to a weight variation of specific links we determine the geopolitical sensitivity and influence of specific terrorist groups on world countries. The world maps of the sensitivity of various countries to influence of specific terrorist groups are obtained. We argue that this approach can find useful application for more extensive and detailed data bases analysis.

GIS tool to locate major Sikh temples in USA

NASA Astrophysics Data System (ADS)

Sharma, Saumya

This tool is a GIS based interactive and graphical user interface tool, which locates the major Sikh temples of USA on a map. This tool is using Java programming language along with MOJO (Map Object Java Object) provided by ESRI that is the organization that provides the GIS software. It also includes some of the integration with Google's API's like Google Translator API. This application will tell users about the origin of Sikhism in India and USA, the major Sikh temples in each state of USA, location, name and detail information through their website. The primary purpose of this application is to make people aware about this religion and culture. This tool will also measure the distance between two temple points in a map and display the result in miles and kilometers. Also, there is an added support to convert each temple's website language from English to Punjabi or any other language using a language convertor tool so that people from different nationalities can understand their culture. By clicking on each point on a map, a new window will pop up showing the picture of the temple and a hyperlink that will redirect to the website of that particular temple .It will also contain links to their dance, music, history, and also a help menu to guide the users to use the software efficiently.

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

KSC-2013-3239

NASA Image and Video Library

2013-08-09

CAPE CANAVERAL, Fla. – As seen on Google Maps, the massive F-1 engines of the Saturn V's first stage on display inside the Apollo/Saturn V Center at the Kennedy Space Center Visitor Complex. Each engine stands 19 feet tall with a diameter of more than 12 feet. The five engines on the first stage produced 7.5 million pounds of thrust at liftoff. The Saturn V was used to launch NASA's Apollo missions to the moon which saw 12 astronauts land and work on the lunar surface. Google precisely mapped Kennedy Space Center and some of its historical facilities for the company's map page. Photo credit: Google/Wendy Wang

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 Google Streetview Panoramic Imagery for Geoscience Education

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Secure and Resilient Cloud Computing for the Department of Defense

DTIC Science & Technology

2015-11-16

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

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.

Usability evaluation of mobile applications using ISO 9241 and ISO 25062 standards.

PubMed

Moumane, Karima; Idri, Ali; Abran, Alain

2016-01-01

This paper presents an empirical study based on a set of measures to evaluate the usability of mobile applications running on different mobile operating systems, including Android, iOS and Symbian. The aim is to evaluate empirically a framework that we have developed on the use of the Software Quality Standard ISO 9126 in mobile environments, especially the usability characteristic. To do that, 32 users had participated in the experiment and we have used ISO 25062 and ISO 9241 standards for objective measures by working with two widely used mobile applications: Google Apps and Google Maps. The QUIS 7.0 questionnaire have been used to collect measures assessing the users' level of satisfaction when using these two mobile applications. By analyzing the results we highlighted a set of mobile usability issues that are related to the hardware as well as to the software and that need to be taken into account by designers and developers in order to improve the usability of mobile applications.

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

NASA Astrophysics Data System (ADS)

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

2008-12-01

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

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 technology and the creation of a commercial climate and conditions that allowed businesses anywhere to exploit the new information. This talk will draw lessons from the experience and imagine how Google Maps could become Google Models. The first lesson is time scale, it took far longer for digital mapping to move out of the development phase than most expected. Its first real customers were the public utilities. They are large organisations, risk averse and take time to change their ways of working; integrated modellers should not be surprised by the slow take up. Few of the early commercial entrants made any significant profits. It was only when the data reached critical mass and became accessible, when the systems became easy to use, affordable and accessible via the web, when convincing demonstrations became available and the necessary standards emerged that Google Maps could emerge. IM has yet to reach this point. It has far bigger technical, scientific and institutional challenges to overcome. The resources required will be large. It is possible though that they could be marshalled by creating an open source community of practice. However, that community will need a facilitating core group and standards to succeed. Having seen what Google Maps made possible, the innovative ideas it released, it is not difficult to imagine where a community of practice might take IM.

Visualizing Moon Data and Imagery with Google Earth

NASA Astrophysics Data System (ADS)

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

2009-12-01

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

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.

Creation of a Web-Based GIS Server and Custom Geoprocessing Tools for Enhanced Hydrologic Applications

NASA Astrophysics Data System (ADS)

Welton, B.; Chouinard, K.; Sultan, M.; Becker, D.; Milewski, A.; Becker, R.

2010-12-01

Rising populations in the arid and semi arid parts of the World are increasing the demand for fresh water supplies worldwide. Many data sets needed for assessment of hydrologic applications across vast regions of the world are expensive, unpublished, difficult to obtain, or at varying scales which complicates their use. Fortunately, this situation is changing with the development of global remote sensing datasets and web-based platforms such as GIS Server. GIS provides a cost effective vehicle for comparing, analyzing, and querying a variety of spatial datasets as geographically referenced layers. We have recently constructed a web-based GIS, that incorporates all relevant geological, geochemical, geophysical, and remote sensing data sets that were readily used to identify reservoir types and potential well locations on local and regional scales in various tectonic settings including: (1) extensional environment (Red Sea rift), (2) transcurrent fault system (Najd Fault in the Arabian-Nubian Shield), and (3) compressional environments (Himalayas). The web-based GIS could also be used to detect spatial and temporal trends in precipitation, recharge, and runoff in large watersheds on local, regional, and continental scales. These applications were enabled through the construction of a web-based ArcGIS Server with Google Map’s interface and the development of customized geoprocessing tools. ArcGIS Server provides out-of-the-box setups that are generic in nature. This platform includes all of the standard web based GIS tools (e.g. pan, zoom, identify, search, data querying, and measurement). In addition to the standard suite of tools provided by ArcGIS Server an additional set of advanced data manipulation and display tools was also developed to allow for a more complete and customizable view of the area of interest. The most notable addition to the standard GIS Server tools is the custom on-demand geoprocessing tools (e.g., graph, statistical functions, custom raster creation, profile, TRMM). The generation of a wide range of derivative maps (e.g., buffer zone, contour map, graphs, temporal rainfall distribution maps) from various map layers (e.g., geologic maps, geophysics, satellite images) allows for more user flexibility. The use of these tools along with Google Map’s API which enables the website user to utilize high quality GeoEye 2 images provide by Google in conjunction with our data, creates a more complete image of the area being observed and allows for custom derivative maps to be created in the field and viewed immediately on the web, processes that were restricted to offline databases.

Application based on ArcObject inquiry and Google maps demonstration to real estate database

NASA Astrophysics Data System (ADS)

Hwang, JinTsong

2007-06-01

Real estate industry in Taiwan has been flourishing in recent years. To acquire various and abundant information of real estate for sale is the same goal for the consumers and the brokerages. Therefore, before looking at the property, it is important to get all pertinent information possible. Not only this beneficial for the real estate agent as they can provide the sellers with the most information, thereby solidifying the interest of the buyer, but may also save time and the cost of manpower were something out of place. Most of the brokerage sites are aware of utilizes Internet as form of media for publicity however; the contents are limited to specific property itself and the functions of query are mostly just provided searching by condition. This paper proposes a query interface on website which gives function of zone query by spatial analysis for non-GIS users, developing a user-friendly interface with ArcObject in VB6, and query by condition. The inquiry results can show on the web page which is embedded functions of Google Maps and the UrMap API on it. In addition, the demonstration of inquiry results will give the multimedia present way which includes hyperlink to Google Earth with surrounding of the property, the Virtual Reality scene of house, panorama of interior of building and so on. Therefore, the website provides extra spatial solution for query and demonstration abundant information of real estate in two-dimensional and three-dimensional types of view.

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

PubMed

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

2013-01-01

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

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

PubMed Central

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

2013-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Atlas of Cancer Signalling Network: a systems biology resource for integrative analysis of cancer data with Google Maps

PubMed Central

Kuperstein, I; Bonnet, E; Nguyen, H-A; Cohen, D; Viara, E; Grieco, L; Fourquet, S; Calzone, L; Russo, C; Kondratova, M; Dutreix, M; Barillot, E; Zinovyev, A

2015-01-01

Cancerogenesis is driven by mutations leading to aberrant functioning of a complex network of molecular interactions and simultaneously affecting multiple cellular functions. Therefore, the successful application of bioinformatics and systems biology methods for analysis of high-throughput data in cancer research heavily depends on availability of global and detailed reconstructions of signalling networks amenable for computational analysis. We present here the Atlas of Cancer Signalling Network (ACSN), an interactive and comprehensive map of molecular mechanisms implicated in cancer. The resource includes tools for map navigation, visualization and analysis of molecular data in the context of signalling network maps. Constructing and updating ACSN involves careful manual curation of molecular biology literature and participation of experts in the corresponding fields. The cancer-oriented content of ACSN is completely original and covers major mechanisms involved in cancer progression, including DNA repair, cell survival, apoptosis, cell cycle, EMT and cell motility. Cell signalling mechanisms are depicted in detail, together creating a seamless ‘geographic-like' map of molecular interactions frequently deregulated in cancer. The map is browsable using NaviCell web interface using the Google Maps engine and semantic zooming principle. The associated web-blog provides a forum for commenting and curating the ACSN content. ACSN allows uploading heterogeneous omics data from users on top of the maps for visualization and performing functional analyses. We suggest several scenarios for ACSN application in cancer research, particularly for visualizing high-throughput data, starting from small interfering RNA-based screening results or mutation frequencies to innovative ways of exploring transcriptomes and phosphoproteomes. Integration and analysis of these data in the context of ACSN may help interpret their biological significance and formulate mechanistic hypotheses. ACSN may also support patient stratification, prediction of treatment response and resistance to cancer drugs, as well as design of novel treatment strategies. PMID:26192618

KSC-2013-3238

NASA Image and Video Library

2013-08-09

CAPE CANAVERAL, Fla. – As seen on Google Maps, a Space Shuttle Main Engine, or SSME, stands inside the Engine Shop at Orbiter Processing Facility 3 at NASA's Kennedy Space Center. Each orbiter used three of the engines during launch and ascent into orbit. The engines burn super-cold liquid hydrogen and liquid oxygen and each one produces 155,000 pounds of thrust. The engines, known in the industry as RS-25s, could be reused on multiple shuttle missions. They will be used again later this decade for NASA's Space Launch System rocket. Google precisely mapped the space center and some of its historical facilities for the company's map page. The work allows Internet users to see inside buildings at Kennedy as they were used during the space shuttle era. Photo credit: Google/Wendy Wang

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.

The GLIMS Glacier Database

NASA Astrophysics Data System (ADS)

Raup, B. H.; Khalsa, S. S.; Armstrong, R.

2007-12-01

The Global Land Ice Measurements from Space (GLIMS) project has built a geospatial and temporal database of glacier data, composed of glacier outlines and various scalar attributes. These data are being derived primarily from satellite imagery, such as from ASTER and Landsat. Each "snapshot" of a glacier is from a specific time, and the database is designed to store multiple snapshots representative of different times. We have implemented two web-based interfaces to the database; one enables exploration of the data via interactive maps (web map server), while the other allows searches based on text-field constraints. The web map server is an Open Geospatial Consortium (OGC) compliant Web Map Server (WMS) and Web Feature Server (WFS). This means that other web sites can display glacier layers from our site over the Internet, or retrieve glacier features in vector format. All components of the system are implemented using Open Source software: Linux, PostgreSQL, PostGIS (geospatial extensions to the database), MapServer (WMS and WFS), and several supporting components such as Proj.4 (a geographic projection library) and PHP. These tools are robust and provide a flexible and powerful framework for web mapping applications. As a service to the GLIMS community, the database contains metadata on all ASTER imagery acquired over glacierized terrain. Reduced-resolution of the images (browse imagery) can be viewed either as a layer in the MapServer application, or overlaid on the virtual globe within Google Earth. The interactive map application allows the user to constrain by time what data appear on the map. For example, ASTER or glacier outlines from 2002 only, or from Autumn in any year, can be displayed. The system allows users to download their selected glacier data in a choice of formats. The results of a query based on spatial selection (using a mouse) or text-field constraints can be downloaded in any of these formats: ESRI shapefiles, KML (Google Earth), MapInfo, GML (Geography Markup Language) and GMT (Generic Mapping Tools). This "clip-and-ship" function allows users to download only the data they are interested in. Our flexible web interfaces to the database, which includes various support layers (e.g. a layer to help collaborators identify satellite imagery over their region of expertise) will facilitate enhanced analysis to be undertaken on glacier systems, their distribution, and their impacts on other Earth systems.

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.

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 Voice: Connecting Your Telephone to the 21st Century

ERIC Educational Resources Information Center

Johnson, Benjamin E.

2010-01-01

The foundation of the mighty Google Empire rests upon an algorithm that connects people to information--things such as websites, maps, and restaurant reviews. Lately it seems that people are less interested in connecting with information than they are with connecting to one another, which begs the question, "Is Facebook the new Google?" Given this…

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…

Seismicity map tools for earthquake studies

NASA Astrophysics Data System (ADS)

Boucouvalas, Anthony; Kaskebes, Athanasios; Tselikas, Nikos

2014-05-01

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

Visualize Your Data with Google Fusion Tables

NASA Astrophysics Data System (ADS)

Brisbin, K. E.

2011-12-01

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

[Who Hits the Mark? A Comparative Study of the Free Geocoding Services of Google and OpenStreetMap].

PubMed

Lemke, D; Mattauch, V; Heidinger, O; Hense, H W

2015-09-01

Geocoding, the process of converting textual information (addresses) into geographic coordinates is increasingly used in public health/epidemiological research and practice. To date, little attention has been paid to geocoding quality and its impact on different types of spatially-related health studies. The primary aim of this study was to compare 2 freely available geocoding services (Google and OpenStreetMap) with regard to matching rate (percentage of address records capable of being geocoded) and positional accuracy (distance between geocodes and the ground truth locations). Residential addresses were geocoded by the NRW state office for information and technology and were considered as reference data (gold standard). The gold standard included the coordinates, the quality of the addresses (4 categories), and a binary urbanity indicator based on the CORINE land cover data. 2 500 addresses were randomly sampled after stratification for address quality and urbanity indicator (approximately 20 000 addresses). These address samples were geocoded using the geocoding services from Google and OSM. In general, both geocoding services showed a decrease in the matching rate with decreasing address quality and urbanity. Google showed consistently a higher completeness than OSM (>93 vs. >82%). Also, the cartographic confounding between urban and rural regions was less distinct with Google's geocoding API. Regarding the positional accuracy of the geo-coordinates, Google also showed the smallest deviations from the reference coordinates, with a median of <9 vs. <175.8 m. The cumulative density function derived from the positional accuracy showed for Google that nearly 95% and for OSM 50% of the addresses were geocoded within <50 m of their reference coordinates. The geocoding API from Google is superior to OSM regarding completeness and positional accuracy of the geocoded addresses. On the other hand, Google has several restrictions, such as the limitation of the requests to 2 500 addresses per 24 h and the presentation of the results exclusively on Google Maps, which may complicate the use for scientific purposes. © Georg Thieme Verlag KG Stuttgart · New York.

Ajax Architecture Implementation Techniques

NASA Astrophysics Data System (ADS)

Hussaini, Syed Asadullah; Tabassum, S. Nasira; Baig, Tabassum, M. Khader

2012-03-01

Today's rich Web applications use a mix of Java Script and asynchronous communication with the application server. This mechanism is also known as Ajax: Asynchronous JavaScript and XML. The intent of Ajax is to exchange small pieces of data between the browser and the application server, and in doing so, use partial page refresh instead of reloading the entire Web page. AJAX (Asynchronous JavaScript and XML) is a powerful Web development model for browser-based Web applications. Technologies that form the AJAX model, such as XML, JavaScript, HTTP, and XHTML, are individually widely used and well known. However, AJAX combines these technologies to let Web pages retrieve small amounts of data from the server without having to reload the entire page. This capability makes Web pages more interactive and lets them behave like local applications. Web 2.0 enabled by the Ajax architecture has given rise to a new level of user interactivity through web browsers. Many new and extremely popular Web applications have been introduced such as Google Maps, Google Docs, Flickr, and so on. Ajax Toolkits such as Dojo allow web developers to build Web 2.0 applications quickly and with little effort.

Signalling maps in cancer research: construction and data analysis

PubMed Central

Kondratova, Maria; Sompairac, Nicolas; Barillot, Emmanuel; Zinovyev, Andrei

2018-01-01

Abstract Generation and usage of high-quality molecular signalling network maps can be augmented by standardizing notations, establishing curation workflows and application of computational biology methods to exploit the knowledge contained in the maps. In this manuscript, we summarize the major aims and challenges of assembling information in the form of comprehensive maps of molecular interactions. Mainly, we share our experience gained while creating the Atlas of Cancer Signalling Network. In the step-by-step procedure, we describe the map construction process and suggest solutions for map complexity management by introducing a hierarchical modular map structure. In addition, we describe the NaviCell platform, a computational technology using Google Maps API to explore comprehensive molecular maps similar to geographical maps and explain the advantages of semantic zooming principles for map navigation. We also provide the outline to prepare signalling network maps for navigation using the NaviCell platform. Finally, several examples of cancer high-throughput data analysis and visualization in the context of comprehensive signalling maps are presented. PMID:29688383

Towards better digital pathology workflows: programming libraries for high-speed sharpness assessment of Whole Slide Images.

PubMed

Ameisen, David; Deroulers, Christophe; Perrier, Valérie; Bouhidel, Fatiha; Battistella, Maxime; Legrès, Luc; Janin, Anne; Bertheau, Philippe; Yunès, Jean-Baptiste

2014-01-01

Since microscopic slides can now be automatically digitized and integrated in the clinical workflow, quality assessment of Whole Slide Images (WSI) has become a crucial issue. We present a no-reference quality assessment method that has been thoroughly tested since 2010 and is under implementation in multiple sites, both public university-hospitals and private entities. It is part of the FlexMIm R&D project which aims to improve the global workflow of digital pathology. For these uses, we have developed two programming libraries, in Java and Python, which can be integrated in various types of WSI acquisition systems, viewers and image analysis tools. Development and testing have been carried out on a MacBook Pro i7 and on a bi-Xeon 2.7GHz server. Libraries implementing the blur assessment method have been developed in Java, Python, PHP5 and MySQL5. For web applications, JavaScript, Ajax, JSON and Sockets were also used, as well as the Google Maps API. Aperio SVS files were converted into the Google Maps format using VIPS and Openslide libraries. We designed the Java library as a Service Provider Interface (SPI), extendable by third parties. Analysis is computed in real-time (3 billion pixels per minute). Tests were made on 5000 single images, 200 NDPI WSI, 100 Aperio SVS WSI converted to the Google Maps format. Applications based on our method and libraries can be used upstream, as calibration and quality control tool for the WSI acquisition systems, or as tools to reacquire tiles while the WSI is being scanned. They can also be used downstream to reacquire the complete slides that are below the quality threshold for surgical pathology analysis. WSI may also be displayed in a smarter way by sending and displaying the regions of highest quality before other regions. Such quality assessment scores could be integrated as WSI's metadata shared in clinical, research or teaching contexts, for a more efficient medical informatics workflow.

KSC-2013-3236

NASA Image and Video Library

2013-08-09

CAPE CANAVERAL, Fla. – As seen on Google Maps, the Rotating Service Structure at Launch Complex 39A at NASA's Kennedy Space Center housed space shuttle payloads temporarily so they could be loaded inside the 60-foot-long cargo bay of a shuttle before launch. The RSS, as the structure was known, was hinged to the Fixed Service Structure on one side and rolled on a rail on the other. As its name suggests, the enclosed facility would rotate into place around the shuttle as it stood at the launch pad. Once in place, the RSS protected the shuttle and its cargo. Google precisely mapped the space center and some of its historical facilities for the company's map page. The work allows Internet users to see inside buildings at Kennedy as they were used during the space shuttle era. Photo credit: Google/Wendy Wang

Voice Based City Panic Button System

NASA Astrophysics Data System (ADS)

Febriansyah; Zainuddin, Zahir; Bachtiar Nappu, M.

2018-03-01

The development of voice activated panic button application aims to design faster early notification of hazardous condition in community to the nearest police by using speech as the detector where the current application still applies touch-combination on screen and use coordination of orders from control center then the early notification still takes longer time. The method used in this research was by using voice recognition as the user voice detection and haversine formula for the comparison of closest distance between the user and the police. This research was equipped with auto sms, which sent notification to the victim’s relatives, that was also integrated with Google Maps application (GMaps) as the map to the victim’s location. The results show that voice registration on the application reaches 100%, incident detection using speech recognition while the application is running is 94.67% in average, and the auto sms to the victim relatives reaches 100%.

Active Fire Mapping Program

MedlinePlus

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

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…

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Tracking changes of river morphology in Ayeyarwady River in Myanmar using earth observations and surface water mapping tool

NASA Astrophysics Data System (ADS)

Piman, T.; Schellekens, J.; Haag, A.; Donchyts, G.; Apirumanekul, C.; Hlaing, K. T.

2017-12-01

River morphology changes is one of the key issues in Ayeyarwady River in Myanmar which cause impacts on navigation, riverine habitats, agriculture lands, communities and livelihoods near the bank of the river. This study is aimed to track the changes in river morphology in the middle reach of Ayeyarwady River over last 30 years from 1984-2014 to improve understanding of riverbank dynamic, erosion and deposition procress. Earth observations including LandSat-7, LandSat-8, Digital Elevation Model from SRTM Plus and, ASTER-2 GoogleMap and Open Street Map were obtained for the study. GIS and remote sensing tools were used to analyze changes in river morphology while surface water mapping tool was applied to determine how the dynamic behaviour of the surface river and effect of river morphology changes. The tool consists of two components: (1) a Google Earth Engine (GEE) javascript or python application that performs image analysis and (2) a user-friendly site/app using Google's appspot.com that exposes the application to the users. The results of this study shown that the fluvial morphology in the middle reach of Ayeyarwady River is continuously changing under the influence of high water flows in particularly from extreme flood events and land use change from mining and deforestation. It was observed that some meandering sections of the riverbank were straightened, which results in the movement of sediment downstream and created new sections of meandering riverbank. Several large islands have formed due to the stabilization by vegetation and is enforced by sedimentation while many small bars were formed and migrated dynamically due to changes in water levels and flow velocity in the wet and dry seasons. The main channel was changed to secondary channel in some sections of the river. This results a constant shift of the navigation route. We also found that some villages were facing riverbank erosion which can force villagers to relocate. The study results demonstrated that the products from earth observations and the surface water mapping tool could detect dynamic changes of river morphology in the Ayeyarwady River. This information is useful to support navigation and riverbank protection planning and formulating mitigation measures for local communities that are affecting by riverbank erosion.

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.

KSC-2013-3237

NASA Image and Video Library

2013-08-09

CAPE CANAVERAL, Fla. – As seen on Google Maps, the view from the top of the Fixed Service Structure at Launch Complex 39A at NASA's Kennedy Space Center. The FSS, as the structure is known, is 285 feet high and overlooks the Rotating Service Structure that was rolled into place when a space shuttle was at the pad. The path taken by NASA's massive crawler-transporters that carried the shuttle stack 3 miles from Vehicle Assembly Building are also visible leading up to the launch pad. In the distance are seen the launch pads and support structures at Cape Canaveral Air Force Station for the Atlas V, Delta IV and Falcon 9 rockets. Google precisely mapped the space center and some of its historical facilities for the company's map page. The work allows Internet users to see inside buildings at Kennedy as they were used during the space shuttle era. Photo credit: Google/Wendy Wang

KSC-2013-3240

NASA Image and Video Library

2013-08-09

CAPE CANAVERAL, Fla. – As seen on Google Maps, space shuttle Endeavour goes through transition and retirement processing in high bay 4 of the Vehicle Assembly Building at NASA's Kennedy Space Center. The spacecraft completed 25 missions beginning with its first flight, STS-49, in May 1992, and ending with STS-134 in May 2011. It helped construct the International Space Station in orbit and travelled more than 122 million miles in orbit during its career. The reaction control system pods in the shuttle's nose and aft section were removed for processing before Endeavour was put on public display at the California Science Center in Los Angeles. Google precisely mapped the space center and some of its historical facilities for the company's map page. The work allows Internet users to see inside buildings at Kennedy as they were used during the space shuttle era. Photo credit: Google/Wendy Wang

Improving Land Cover Mapping: a Mobile Application Based on ESA Sentinel 2 Imagery

NASA Astrophysics Data System (ADS)

Melis, M. T.; Dessì, F.; Loddo, P.; La Mantia, C.; Da Pelo, S.; Deflorio, A. M.; Ghiglieri, G.; Hailu, B. T.; Kalegele, K.; Mwasi, B. N.

2018-04-01

The increasing availability of satellite data is a real value for the enhancement of environmental knowledge and land management. Possibilities to integrate different source of geo-data are growing and methodologies to create thematic database are becoming very sophisticated. Moreover, the access to internet services and, in particular, to web mapping services is well developed and spread either between expert users than the citizens. Web map services, like Google Maps or Open Street Maps, give the access to updated optical imagery or topographic maps but information on land cover/use - are not still provided. Therefore, there are many failings in the general utilization -non-specialized users- and access to those maps. This issue is particularly felt where the digital (web) maps could form the basis for land use management as they are more economic and accessible than the paper maps. These conditions are well known in many African countries where, while the internet access is becoming open to all, the local map agencies and their products are not widespread.

Assessing species habitat using Google Street View: a case study of cliff-nesting vultures.

PubMed

Olea, Pedro P; Mateo-Tomás, Patricia

2013-01-01

The assessment of a species' habitat is a crucial issue in ecology and conservation. While the collection of habitat data has been boosted by the availability of remote sensing technologies, certain habitat types have yet to be collected through costly, on-ground surveys, limiting study over large areas. Cliffs are ecosystems that provide habitat for a rich biodiversity, especially raptors. Because of their principally vertical structure, however, cliffs are not easy to study by remote sensing technologies, posing a challenge for many researches and managers working with cliff-related biodiversity. We explore the feasibility of Google Street View, a freely available on-line tool, to remotely identify and assess the nesting habitat of two cliff-nesting vultures (the griffon vulture and the globally endangered Egyptian vulture) in northwestern Spain. Two main usefulness of Google Street View to ecologists and conservation biologists were evaluated: i) remotely identifying a species' potential habitat and ii) extracting fine-scale habitat information. Google Street View imagery covered 49% (1,907 km) of the roads of our study area (7,000 km²). The potential visibility covered by on-ground surveys was significantly greater (mean: 97.4%) than that of Google Street View (48.1%). However, incorporating Google Street View to the vulture's habitat survey would save, on average, 36% in time and 49.5% in funds with respect to the on-ground survey only. The ability of Google Street View to identify cliffs (overall accuracy = 100%) outperformed the classification maps derived from digital elevation models (DEMs) (62-95%). Nonetheless, high-performance DEM maps may be useful to compensate Google Street View coverage limitations. Through Google Street View we could examine 66% of the vultures' nesting-cliffs existing in the study area (n = 148): 64% from griffon vultures and 65% from Egyptian vultures. It also allowed us the extraction of fine-scale features of cliffs. This World Wide Web-based methodology may be a useful, complementary tool to remotely map and assess the potential habitat of cliff-dependent biodiversity over large geographic areas, saving survey-related costs.

Assessing Species Habitat Using Google Street View: A Case Study of Cliff-Nesting Vultures

PubMed Central

Olea, Pedro P.; Mateo-Tomás, Patricia

2013-01-01

The assessment of a species’ habitat is a crucial issue in ecology and conservation. While the collection of habitat data has been boosted by the availability of remote sensing technologies, certain habitat types have yet to be collected through costly, on-ground surveys, limiting study over large areas. Cliffs are ecosystems that provide habitat for a rich biodiversity, especially raptors. Because of their principally vertical structure, however, cliffs are not easy to study by remote sensing technologies, posing a challenge for many researches and managers working with cliff-related biodiversity. We explore the feasibility of Google Street View, a freely available on-line tool, to remotely identify and assess the nesting habitat of two cliff-nesting vultures (the griffon vulture and the globally endangered Egyptian vulture) in northwestern Spain. Two main usefulness of Google Street View to ecologists and conservation biologists were evaluated: i) remotely identifying a species’ potential habitat and ii) extracting fine-scale habitat information. Google Street View imagery covered 49% (1,907 km) of the roads of our study area (7,000 km2). The potential visibility covered by on-ground surveys was significantly greater (mean: 97.4%) than that of Google Street View (48.1%). However, incorporating Google Street View to the vulture’s habitat survey would save, on average, 36% in time and 49.5% in funds with respect to the on-ground survey only. The ability of Google Street View to identify cliffs (overall accuracy = 100%) outperformed the classification maps derived from digital elevation models (DEMs) (62–95%). Nonetheless, high-performance DEM maps may be useful to compensate Google Street View coverage limitations. Through Google Street View we could examine 66% of the vultures’ nesting-cliffs existing in the study area (n = 148): 64% from griffon vultures and 65% from Egyptian vultures. It also allowed us the extraction of fine-scale features of cliffs. This World Wide Web-based methodology may be a useful, complementary tool to remotely map and assess the potential habitat of cliff-dependent biodiversity over large geographic areas, saving survey-related costs. PMID:23355880

GIS Application Management for Disabled People

NASA Astrophysics Data System (ADS)

Tongkaw, Sasalak

2017-08-01

This research aimed to develop and design Geographical Information Systems (GIS) for facilitating disabled people by presenting some useful disabled information on the Google Map. The map could provide information about disabled types of people such as blind, deaf and physical movement. This research employed the Multiview 2 theory and method to plan and find out the problems in real world situation. This research used many designing data structure methods such as Data Flow Diagram, and ER-Diagram. The research focused into two parts: server site and client site which included the interface for Web-based application. The clear information of disable people on the map was useful for facilitating disabled people to find some useful information. In addition, it provided specialized data for company and government officers for managing and planning local facilities for disabled people in the cities. The disable could access the system through the Internet access at any time by using mobile or portable devices.

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

USGS Publications Warehouse

Walsh, Gregory J.

2009-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2010-02-01

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

New Delhi Metallo-beta-lactamase around the world: an eReview using Google Maps.

PubMed

Berrazeg, M; Diene, Sm; Medjahed, L; Parola, P; Drissi, M; Raoult, D; Rolain, Jm

2014-05-22

Gram-negative carbapenem-resistant bacteria, in particular those producing New Delhi Metallo-betalactamase-1 (NDM-1), are a major global health problem. To inform the scientific and medical community in real time about worldwide dissemination of isolates of NDM-1-producing bacteria, we used the PubMed database to review all available publications from the first description in 2009 up to 31 December 2012, and created a regularly updated worldwide dissemination map using a web-based mapping application. We retrieved 33 reviews, and 136 case reports describing 950 isolates of NDM-1-producing bacteria. Klebsiella pneumoniae (n= 359) and Escherichia coli (n=268) were the most commonly reported bacteria producing NDM-1 enzyme. Several case reports of infections due to imported NDM-1 producing bacteria have been reported in a number of countries, including the United Kingdom, Italy, and Oman. In most cases (132/153, 86.3%), patients had connections with the Indian subcontinent or Balkan countries. Those infected were originally from these areas, had either spent time and/or been hospitalised there, or were potentially linked to other patients who had been hospitalised in these regions. By using Google Maps, we were able to trace spread of NDM-1-producing bacteria. We strongly encourage epidemiologists to use these types of interactive tools for surveillance purposes and use the information to prevent the spread and outbreaks of such bacteria.

Quantification of Plant Chlorophyll Content Using Google Glass

PubMed Central

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

2015-01-01

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

Quantification of plant chlorophyll content using Google Glass.

PubMed

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

2015-04-07

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

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).

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

PubMed Central

Boulos, Maged N Kamel; Burden, David

2007-01-01

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

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).

Caltrans - California Department of Transportation

Science.gov Websites

Caltrans QuickMap QuickMap Mobile QuickMap Android App Check Current Highway Conditions: Enter Highway the App Store. Google Play Apple Store Quickmap Mobile Version Quickmap Full Version CA Safety

Immunochromatographic diagnostic test analysis using Google Glass.

PubMed

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

2014-03-25

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

Immunochromatographic Diagnostic Test Analysis Using Google Glass

PubMed Central

2014-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2006-12-01

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

Mapping rice extent map with crop intensity in south China through integration of optical and microwave images based on google earth engine

NASA Astrophysics Data System (ADS)

Zhang, X.; Wu, B.; Zhang, M.; Zeng, H.

2017-12-01

Rice is one of the main staple foods in East Asia and Southeast Asia, which has occupied more than half of the world's population with 11% of cultivated land. Study on rice can provide direct or indirect information on food security and water source management. Remote sensing has proven to be the most effective method to monitoring the cropland in large scale by using temporary and spectral information. There are two main kinds of satellite have been used to mapping rice including microwave and optical. Rice, as the main crop of paddy fields, the main feature different from other crops is flooding phenomenon at planning stage (Figure 1). Microwave satellites can penetrate through clouds and efficiency on monitoring flooding phenomenon. Meanwhile, the vegetation index based on optical satellite can well distinguish rice from other vegetation. Google Earth Engine is a cloud-based platform that makes it easy to access high-performance computing resources for processing very large geospatial datasets. Google has collected large number of remote sensing satellite data around the world, which providing researchers with the possibility of doing application by using multi-source remote sensing data in a large area. In this work, we map rice planting area in south China through integration of Landsat-8 OLI, Sentienl-2, and Sentinel-1 Synthetic Aperture Radar (SAR) images. The flowchart is shown in figure 2. First, a threshold method the VH polarized backscatter from SAR sensor and vegetation index including normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) from optical sensor were used the classify the rice extent map. The forest and water surface extent map provided by earth engine were used to mask forest and water. To overcome the problem of the "salt and pepper effect" by Pixel-based classification when the spatial resolution increased, we segment the optical image and use the pixel- based classification results to merge the object-oriented segmentation data, and finally get the rice extent map. At last, by using the time series analysis, the peak count was obtained for each rice area to ensure the crop intensity. In this work, the rice ground point from a GVG crowdsourcing smartphone and rice area statistical results from National Bureau of Statistics were used to validate and evaluate our result.

Novel data sources for women's health research: mapping breast screening online information seeking through Google trends.

PubMed

Fazeli Dehkordy, Soudabeh; Carlos, Ruth C; Hall, Kelli S; Dalton, Vanessa K

2014-09-01

Millions of people use online search engines everyday to find health-related information and voluntarily share their personal health status and behaviors in various Web sites. Thus, data from tracking of online information seeker's behavior offer potential opportunities for use in public health surveillance and research. Google Trends is a feature of Google which allows Internet users to graph the frequency of searches for a single term or phrase over time or by geographic region. We used Google Trends to describe patterns of information-seeking behavior in the subject of dense breasts and to examine their correlation with the passage or introduction of dense breast notification legislation. To capture the temporal variations of information seeking about dense breasts, the Web search query "dense breast" was entered in the Google Trends tool. We then mapped the dates of legislative actions regarding dense breasts that received widespread coverage in the lay media to information-seeking trends about dense breasts over time. Newsworthy events and legislative actions appear to correlate well with peaks in search volume of "dense breast". Geographic regions with the highest search volumes have passed, denied, or are currently considering the dense breast legislation. Our study demonstrated that any legislative action and respective news coverage correlate with increase in information seeking for "dense breast" on Google, suggesting that Google Trends has the potential to serve as a data source for policy-relevant research. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

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.

KSC-2013-3234

NASA Image and Video Library

2013-08-09

CAPE CANAVERAL, Fla. – As seen on Google Maps, Firing Room 3 inside the Launch Control Center at NASA's Kennedy Space Center was one of the four control rooms used by NASA and contractor launch teams to oversee a space shuttle countdown. This firing room is furnished in the classic style with the same metal computer cabinets and some of the same monitors in place when the first shuttle mission launched April 12, 1981. Specialized operators worked at consoles tailored to keep track of the status of shuttle systems while the spacecraft was processed in the Orbiter Processing Facility, being stacked inside the Vehicle Assembly Building and standing at the launch pad before liftoff. The firing rooms, including 3, were also used during NASA's Apollo Program. Google precisely mapped the space center and some of its historical facilities for the company's map page. The work allows Internet users to see inside buildings at Kennedy as they were used during the space shuttle era. Photo credit: Google/Wendy Wang

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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.

Towards better digital pathology workflows: programming libraries for high-speed sharpness assessment of Whole Slide Images

PubMed Central

2014-01-01

Background Since microscopic slides can now be automatically digitized and integrated in the clinical workflow, quality assessment of Whole Slide Images (WSI) has become a crucial issue. We present a no-reference quality assessment method that has been thoroughly tested since 2010 and is under implementation in multiple sites, both public university-hospitals and private entities. It is part of the FlexMIm R&D project which aims to improve the global workflow of digital pathology. For these uses, we have developed two programming libraries, in Java and Python, which can be integrated in various types of WSI acquisition systems, viewers and image analysis tools. Methods Development and testing have been carried out on a MacBook Pro i7 and on a bi-Xeon 2.7GHz server. Libraries implementing the blur assessment method have been developed in Java, Python, PHP5 and MySQL5. For web applications, JavaScript, Ajax, JSON and Sockets were also used, as well as the Google Maps API. Aperio SVS files were converted into the Google Maps format using VIPS and Openslide libraries. Results We designed the Java library as a Service Provider Interface (SPI), extendable by third parties. Analysis is computed in real-time (3 billion pixels per minute). Tests were made on 5000 single images, 200 NDPI WSI, 100 Aperio SVS WSI converted to the Google Maps format. Conclusions Applications based on our method and libraries can be used upstream, as calibration and quality control tool for the WSI acquisition systems, or as tools to reacquire tiles while the WSI is being scanned. They can also be used downstream to reacquire the complete slides that are below the quality threshold for surgical pathology analysis. WSI may also be displayed in a smarter way by sending and displaying the regions of highest quality before other regions. Such quality assessment scores could be integrated as WSI's metadata shared in clinical, research or teaching contexts, for a more efficient medical informatics workflow. PMID:25565494

Measurable realistic image-based 3D mapping

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

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…

An application of traveling salesman problem using the improved genetic algorithm on android google maps

NASA Astrophysics Data System (ADS)

Narwadi, Teguh; Subiyanto

2017-03-01

The Travelling Salesman Problem (TSP) is one of the best known NP-hard problems, which means that no exact algorithm to solve it in polynomial time. This paper present a new variant application genetic algorithm approach with a local search technique has been developed to solve the TSP. For the local search technique, an iterative hill climbing method has been used. The system is implemented on the Android OS because android is now widely used around the world and it is mobile system. It is also integrated with Google API that can to get the geographical location and the distance of the cities, and displays the route. Therefore, we do some experimentation to test the behavior of the application. To test the effectiveness of the application of hybrid genetic algorithm (HGA) is compare with the application of simple GA in 5 sample from the cities in Central Java, Indonesia with different numbers of cities. According to the experiment results obtained that in the average solution HGA shows in 5 tests out of 5 (100%) is better than simple GA. The results have shown that the hybrid genetic algorithm outperforms the genetic algorithm especially in the case with the problem higher complexity.

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].

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.

Novel Data Sources for Women’s Health Research: Mapping Breast Screening Online Information Seeking Through Google Trends

PubMed Central

Dehkordy, Soudabeh Fazeli; Carlos, Ruth C.; Hall, Kelli S.; Dalton, Vanessa K.

2015-01-01

Rationale and Objectives Millions of people use online search engines every day to find health-related information and voluntarily share their personal health status and behaviors in various Web sites. Thus, data from tracking of online information seeker’s behavior offer potential opportunities for use in public health surveillance and research. Google Trends is a feature of Google which allows internet users to graph the frequency of searches for a single term or phrase over time or by geographic region. We used Google Trends to describe patterns of information seeking behavior in the subject of dense breasts and to examine their correlation with the passage or introduction of dense breast notification legislation. Materials and Methods In order to capture the temporal variations of information seeking about dense breasts, the web search query “dense breast” was entered in the Google Trends tool. We then mapped the dates of legislative actions regarding dense breasts that received widespread coverage in the lay media to information seeking trends about dense breasts over time. Results Newsworthy events and legislative actions appear to correlate well with peaks in search volume of “dense breast”. Geographic regions with the highest search volumes have either passed, denied, or are currently considering the dense breast legislation. Conclusions Our study demonstrated that any legislative action and respective news coverage correlate with increase in information seeking for “dense breast” on Google, suggesting that Google Trends has the potential to serve as a data source for policy-relevant research. PMID:24998689

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

The World in Spatial Terms: Mapmaking and Map Reading

ERIC Educational Resources Information Center

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

2007-01-01

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

Web application and database modeling of traffic impact analysis using Google Maps

NASA Astrophysics Data System (ADS)

Yulianto, Budi; Setiono

2017-06-01

Traffic impact analysis (TIA) is a traffic study that aims at identifying the impact of traffic generated by development or change in land use. In addition to identifying the traffic impact, TIA is also equipped with mitigation measurement to minimize the arising traffic impact. TIA has been increasingly important since it was defined in the act as one of the requirements in the proposal of Building Permit. The act encourages a number of TIA studies in various cities in Indonesia, including Surakarta. For that reason, it is necessary to study the development of TIA by adopting the concept Transportation Impact Control (TIC) in the implementation of the TIA standard document and multimodal modeling. It includes TIA's standardization for technical guidelines, database and inspection by providing TIA checklists, monitoring and evaluation. The research was undertaken by collecting the historical data of junctions, modeling of the data in the form of relational database, building a user interface for CRUD (Create, Read, Update and Delete) the TIA data in the form of web programming with Google Maps libraries. The result research is a system that provides information that helps the improvement and repairment of TIA documents that exist today which is more transparent, reliable and credible.

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

NASA Astrophysics Data System (ADS)

de Paor, D. G.

2008-12-01

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

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

PubMed

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

2013-01-18

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

KSC-2013-3235

NASA Image and Video Library

2013-08-09

CAPE CANAVERAL, Fla. – As seen on Google Maps, Firing Room 4 inside the Launch Control Center at NASA's Kennedy Space Center was one of the four control rooms used by NASA and contractor launch teams to oversee a space shuttle countdown. This firing room was the most advanced of the control rooms used for shuttle missions and was the primary firing room for the shuttle's final series of launches before retirement. It is furnished in a more contemporary style with wood cabinets and other features, although it retains many of the computer systems the shuttle counted on to operate safely. Specialized operators worked at consoles tailored to keep track of the status of shuttle systems while the spacecraft was processed in the Orbiter Processing Facility, being stacked inside the Vehicle Assembly Building and standing at the launch pad before liftoff. The firing rooms, including 3, were also used during NASA's Apollo Program. Google precisely mapped the space center and some of its historical facilities for the company's map page. The work allows Internet users to see inside buildings at Kennedy as they were used during the space shuttle era. Photo credit: Google/Wendy Wang

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.

High-Performance Signal Detection for Adverse Drug Events using MapReduce Paradigm.

PubMed

Fan, Kai; Sun, Xingzhi; Tao, Ying; Xu, Linhao; Wang, Chen; Mao, Xianling; Peng, Bo; Pan, Yue

2010-11-13

Post-marketing pharmacovigilance is important for public health, as many Adverse Drug Events (ADEs) are unknown when those drugs were approved for marketing. However, due to the large number of reported drugs and drug combinations, detecting ADE signals by mining these reports is becoming a challenging task in terms of computational complexity. Recently, a parallel programming model, MapReduce has been introduced by Google to support large-scale data intensive applications. In this study, we proposed a MapReduce-based algorithm, for common ADE detection approach, Proportional Reporting Ratio (PRR), and tested it in mining spontaneous ADE reports from FDA. The purpose is to investigate the possibility of using MapReduce principle to speed up biomedical data mining tasks using this pharmacovigilance case as one specific example. The results demonstrated that MapReduce programming model could improve the performance of common signal detection algorithm for pharmacovigilance in a distributed computation environment at approximately liner speedup rates.

Design and Implementation of Surrounding Transaction Plotting and Management System Based on Google Map API

NASA Astrophysics Data System (ADS)

Cao, Y. B.; Hua, Y. X.; Zhao, J. X.; Guo, S. M.

2013-11-01

With China's rapid economic development and comprehensive national strength growing, Border work has become a long-term and important task in China's diplomatic work. How to implement rapid plotting, real-time sharing and mapping surrounding affairs has taken great significance for government policy makers and diplomatic staff. However, at present the already exists Boundary information system are mainly have problems of Geospatial data update is heavily workload, plotting tools are in a state of serious lack of, Geographic events are difficult to share, this phenomenon has seriously hampered the smooth development of the border task. The development and progress of Geographic information system technology especially the development of Web GIS offers the possibility to solve the above problems, this paper adopts four layers of B/S architecture, with the support of Google maps service, uses the free API which is offered by Google maps and its features of openness, ease of use, sharing characteristics, highresolution images to design and implement the surrounding transaction plotting and management system based on the web development technology of ASP.NET, C#, Ajax. The system can provide decision support for government policy makers as well as diplomatic staff's real-time plotting and sharing of surrounding information. The practice has proved that the system has good usability and strong real-time.

Decision support system for the response to infectious disease emergencies based on WebGIS and mobile services in China.

PubMed

Li, Ya-pin; Fang, Li-qun; Gao, Su-qing; Wang, Zhen; Gao, Hong-wei; Liu, Peng; Wang, Ze-Rui; Li, Yan-Li; Zhu, Xu-Guang; Li, Xin-Lou; Xu, Bo; Li, Yin-Jun; Yang, Hong; de Vlas, Sake J; Shi, Tao-Xing; Cao, Wu-Chun

2013-01-01

For years, emerging infectious diseases have appeared worldwide and threatened the health of people. The emergence and spread of an infectious-disease outbreak are usually unforeseen, and have the features of suddenness and uncertainty. Timely understanding of basic information in the field, and the collection and analysis of epidemiological information, is helpful in making rapid decisions and responding to an infectious-disease emergency. Therefore, it is necessary to have an unobstructed channel and convenient tool for the collection and analysis of epidemiologic information in the field. Baseline information for each county in mainland China was collected and a database was established by geo-coding information on a digital map of county boundaries throughout the country. Google Maps was used to display geographic information and to conduct calculations related to maps, and the 3G wireless network was used to transmit information collected in the field to the server. This study established a decision support system for the response to infectious-disease emergencies based on WebGIS and mobile services (DSSRIDE). The DSSRIDE provides functions including data collection, communication and analyses in real time, epidemiological detection, the provision of customized epidemiological questionnaires and guides for handling infectious disease emergencies, and the querying of professional knowledge in the field. These functions of the DSSRIDE could be helpful for epidemiological investigations in the field and the handling of infectious-disease emergencies. The DSSRIDE provides a geographic information platform based on the Google Maps application programming interface to display information of infectious disease emergencies, and transfers information between workers in the field and decision makers through wireless transmission based on personal computers, mobile phones and personal digital assistants. After a 2-year practice and application in infectious disease emergencies, the DSSRIDE is becoming a useful platform and is a useful tool for investigations in the field carried out by response sections and individuals. The system is suitable for use in developing countries and low-income districts.

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…

Monitoring Global Precipitation through UCI CHRS's RainMapper App on Mobile Devices

NASA Astrophysics Data System (ADS)

Nguyen, P.; Huynh, P.; Braithwaite, D.; Hsu, K. L.; Sorooshian, S.

2014-12-01

The Water and Development Information for Arid Lands-a Global Network (G-WADI) Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks—Cloud Classification System (PERSIANN-CCS) GeoServer has been developed through a collaboration between the Center for Hydrometeorology and Remote Sensing (CHRS) at the University of California, Irvine (UCI) and the UNESCO's International Hydrological Program (IHP). G-WADI PERSIANN-CCS GeoServer provides near real-time high resolution (0.04o, approx 4km) global (60oN - 60oS) satellite precipitation estimated by the PERSIANN-CCS algorithm developed by the scientists at CHRS. The G-WADI PERSIANN-CCS GeoServer utilizes the open-source MapServer software from the University of Minnesota to provide a user-friendly web-based mapping and visualization of satellite precipitation data. Recent efforts have been made by the scientists at CHRS to provide free on-the-go access to the PERSIANN-CCS precipitation data through an application named RainMapper for mobile devices. RainMapper provides visualization of global satellite precipitation of the most recent 3, 6, 12, 24, 48 and 72-hour periods overlaid with various basemaps. RainMapper uses the Google maps application programing interface (API) and embedded global positioning system (GPS) access to better monitor the global precipitation data on mobile devices. Functionalities include using geographical searching with voice recognition technologies make it easy for the user to explore near real-time precipitation in a certain location. RainMapper also allows for conveniently sharing the precipitation information and visualizations with the public through social networks such as Facebook and Twitter. RainMapper is available for iOS and Android devices and can be downloaded (free) from the App Store and Google Play. The usefulness of RainMapper was demonstrated through an application in tracking the evolution of the recent Rammasun Typhoon over the Philippines in mid July 2014.

EPA Recovery Mapper

EPA Pesticide Factsheets

The EPA Recovery Mapper is an Internet interactive mapping application that allows users to discover information about every American Recovery and Reinvestment Act (ARRA) award that EPA has funded for six programs. By integrating data reported by the recipients of Recovery Act funding and data created by EPA, this application delivers a level of transparency and public accessibility to users interested in EPA's use of Recovery Act monies. The application is relatively easy to use and builds on the same mapping model as Google, Bing, MapQuest and other commonly used mapping interfaces. EPA Recovery Mapper tracks each award made by each program and gives basic Quick Facts information for each award including award name, location, award date, dollar amounts and more. Data Summaries for each EPA program or for each state are provided displaying dollars for Total Awarded, Total Received (Paid), and Total Jobs This Quarter by Recovery for the latest quarter of data released by Recovery.gov. The data are reported to the government and EPA four times a year by the award recipients. The latest quarterly report will always be displayed in the EPA Recovery Mapper. In addition, the application provides many details about each award. Users will learn more about how to access and interpret these data later in this document. Data shown in the EPA Recovery Mapper are derived from information reported back to FederalReporting.gov from the recipients of Recovery Act funding. EPA

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…

GeoSymbio: a hybrid, cloud-based web application of global geospatial bioinformatics and ecoinformatics for Symbiodinium-host symbioses.

PubMed

Franklin, Erik C; Stat, Michael; Pochon, Xavier; Putnam, Hollie M; Gates, Ruth D

2012-03-01

The genus Symbiodinium encompasses a group of unicellular, photosynthetic dinoflagellates that are found free living or in hospite with a wide range of marine invertebrate hosts including scleractinian corals. We present GeoSymbio, a hybrid web application that provides an online, easy to use and freely accessible interface for users to discover, explore and utilize global geospatial bioinformatic and ecoinformatic data on Symbiodinium-host symbioses. The novelty of this application lies in the combination of a variety of query and visualization tools, including dynamic searchable maps, data tables with filter and grouping functions, and interactive charts that summarize the data. Importantly, this application is hosted remotely or 'in the cloud' using Google Apps, and therefore does not require any specialty GIS, web programming or data programming expertise from the user. The current version of the application utilizes Symbiodinium data based on the ITS2 genetic marker from PCR-based techniques, including denaturing gradient gel electrophoresis, sequencing and cloning of specimens collected during 1982-2010. All data elements of the application are also downloadable as spatial files, tables and nucleic acid sequence files in common formats for desktop analysis. The application provides a unique tool set to facilitate research on the basic biology of Symbiodinium and expedite new insights into their ecology, biogeography and evolution in the face of a changing global climate. GeoSymbio can be accessed at https://sites.google.com/site/geosymbio/. © 2011 Blackwell Publishing Ltd.

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

ERIC Educational Resources Information Center

Mercier, O. Ripeka; Rata, Arama

2017-01-01

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

How to Use This Website | USDA Plant Hardiness Zone Map

Science.gov Websites

, regional or national plant hardiness zone maps in three different resolutions using the following steps. To default printing menu option or button. Viewing the Map - Open Full Map Button c. Save Full Map Button can copy the e-mail address and paste it into a different e-mail client (e.g., Google Gmail, Yahoo

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.

Cartographic analyses of geographic information available on Google Earth Images

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Interpretation of earthquake-induced landslides triggered by the 12 May 2008, M7.9 Wenchuan earthquake in the Beichuan area, Sichuan Province, China using satellite imagery and Google Earth

USGS Publications Warehouse

Sato, H.P.; Harp, E.L.

2009-01-01

The 12 May 2008 M7.9 Wenchuan earthquake in the People's Republic of China represented a unique opportunity for the international community to use commonly available GIS (Geographic Information System) tools, like Google Earth (GE), to rapidly evaluate and assess landslide hazards triggered by the destructive earthquake and its aftershocks. In order to map earthquake-triggered landslides, we provide details on the applicability and limitations of publicly available 3-day-post- and pre-earthquake imagery provided by GE from the FORMOSAT-2 (formerly ROCSAT-2; Republic of China Satellite 2). We interpreted landslides on the 8-m-resolution FORMOSAT-2 image by GE; as a result, 257 large landslides were mapped with the highest concentration along the Beichuan fault. An estimated density of 0.3 landslides/km2 represents a minimum bound on density given the resolution of available imagery; higher resolution data would have identified more landslides. This is a preliminary study, and further study is needed to understand the landslide characteristics in detail. Although it is best to obtain landslide locations and measurements from satellite imagery having high resolution, it was found that GE is an effective and rapid reconnaissance tool. ?? 2009 Springer-Verlag.

An Interactive Web System for Field Data Sharing and Collaboration

NASA Astrophysics Data System (ADS)

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

2010-12-01

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

Be-safe travel, a web-based geographic application to explore safe-route in an area

NASA Astrophysics Data System (ADS)

Utamima, Amalia; Djunaidy, Arif

2017-08-01

In large cities in developing countries, the various forms of criminality are often found. For instance, the most prominent crimes in Surabaya, Indonesia is 3C, that is theft with violence (curas), theft by weighting (curat), and motor vehicle theft (curanmor). 3C case most often occurs on the highway and residential areas. Therefore, new entrants in an area should be aware of these kind of crimes. Route Planners System or route planning system such as Google Maps only consider the shortest distance in the calculation of the optimal route. The selection of the optimal path in this study not only consider the shortest distance, but also involves other factors, namely the security level. This research considers at the need for an application to recommend the safest road to be passed by the vehicle passengers while drive an area. This research propose Be-Safe Travel, a web-based application using Google API that can be accessed by people who like to drive in an area, but still lack of knowledge of the pathways which are safe from crime. Be-Safe Travel is not only useful for the new entrants, but also useful for delivery courier of valuables goods to go through the safest streets.

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)...

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

NASA Astrophysics Data System (ADS)

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

2009-12-01

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

Data visualization in interactive maps and time series

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

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.

Google Earth Engine

NASA Astrophysics Data System (ADS)

Gorelick, Noel

2013-04-01

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

Google Earth Engine

NASA Astrophysics Data System (ADS)

Gorelick, N.

2012-12-01

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

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…

75 FR 5310 - Combined Notice of Filings #1

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-02

... Wednesday, February 10, 2010. Docket Numbers: ER10-468-001. Applicants: Google Energy LLC. Description: Clarifying amendments to Google Energy LLC's Application for market based rate authority and granting of...

75 FR 61724 - Combined Notice of Filings #2

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-06

..., October 13, 2010. Docket Numbers: ER10-2835-000. Applicants: Google Energy LLC. Description: Google Energy LLC submits tariff filing per 35.12: Google Energy LLC Baseline Filing for MBR Tariff to be effective...

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.

BatMis: a fast algorithm for k-mismatch mapping.

PubMed

Tennakoon, Chandana; Purbojati, Rikky W; Sung, Wing-Kin

2012-08-15

Second-generation sequencing (SGS) generates millions of reads that need to be aligned to a reference genome allowing errors. Although current aligners can efficiently map reads allowing a small number of mismatches, they are not well suited for handling a large number of mismatches. The efficiency of aligners can be improved using various heuristics, but the sensitivity and accuracy of the alignments are sacrificed. In this article, we introduce Basic Alignment tool for Mismatches (BatMis)--an efficient method to align short reads to a reference allowing k mismatches. BatMis is a Burrows-Wheeler transformation based aligner that uses a seed and extend approach, and it is an exact method. Benchmark tests show that BatMis performs better than competing aligners in solving the k-mismatch problem. Furthermore, it can compete favorably even when compared with the heuristic modes of the other aligners. BatMis is a useful alternative for applications where fast k-mismatch mappings, unique mappings or multiple mappings of SGS data are required. BatMis is written in C/C++ and is freely available from http://code.google.com/p/batmis/

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.

Distributed Kernelized Locality-Sensitive Hashing for Faster Image Based Navigation

DTIC Science & Technology

2015-03-26

Facebook, Google, and Yahoo !. Current methods for image retrieval become problematic when implemented on image datasets that can easily reach billions of...correlations. Tech industry leaders like Facebook, Google, and Yahoo ! sort and index even larger volumes of “big data” daily. When attempting to process...open source implementation of Google’s MapReduce programming paradigm [13] which has been used for many different things. Using Apache Hadoop, Yahoo

75 FR 357 - Combined Notice of Filings #1

Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-05

..., January 13, 2010. Docket Numbers: ER10-468-000. Applicants: Google Energy LLC. Description: Application of Google Energy LLC for Market Based Rate Authority and Granting of Waivers and Blanket Authority. Filed...

LLMapReduce: Multi-Lingual Map-Reduce for Supercomputing Environments

DTIC Science & Technology

2015-11-20

1990s. Popularized by Google [36] and Apache Hadoop [37], map-reduce has become a staple technology of the ever- growing big data community...Lexington, MA, U.S.A Abstract— The map-reduce parallel programming model has become extremely popular in the big data community. Many big data ...to big data users running on a supercomputer. LLMapReduce dramatically simplifies map-reduce programming by providing simple parallel programming

Semantic Segmentation and Difference Extraction via Time Series Aerial Video Camera and its Application

NASA Astrophysics Data System (ADS)

Amit, S. N. K.; Saito, S.; Sasaki, S.; Kiyoki, Y.; Aoki, Y.

2015-04-01

Google earth with high-resolution imagery basically takes months to process new images before online updates. It is a time consuming and slow process especially for post-disaster application. The objective of this research is to develop a fast and effective method of updating maps by detecting local differences occurred over different time series; where only region with differences will be updated. In our system, aerial images from Massachusetts's road and building open datasets, Saitama district datasets are used as input images. Semantic segmentation is then applied to input images. Semantic segmentation is a pixel-wise classification of images by implementing deep neural network technique. Deep neural network technique is implemented due to being not only efficient in learning highly discriminative image features such as road, buildings etc., but also partially robust to incomplete and poorly registered target maps. Then, aerial images which contain semantic information are stored as database in 5D world map is set as ground truth images. This system is developed to visualise multimedia data in 5 dimensions; 3 dimensions as spatial dimensions, 1 dimension as temporal dimension, and 1 dimension as degenerated dimensions of semantic and colour combination dimension. Next, ground truth images chosen from database in 5D world map and a new aerial image with same spatial information but different time series are compared via difference extraction method. The map will only update where local changes had occurred. Hence, map updating will be cheaper, faster and more effective especially post-disaster application, by leaving unchanged region and only update changed region.

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

NASA Astrophysics Data System (ADS)

Zlinszky, András; Supan, Peter; Koma, Zsófia

2017-04-01

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

TouchTerrain: A simple web-tool for creating 3D-printable topographic models

NASA Astrophysics Data System (ADS)

Hasiuk, Franciszek J.; Harding, Chris; Renner, Alex Raymond; Winer, Eliot

2017-12-01

An open-source web-application, TouchTerrain, was developed to simplify the production of 3D-printable terrain models. Direct Digital Manufacturing (DDM) using 3D Printers can change how geoscientists, students, and stakeholders interact with 3D data, with the potential to improve geoscience communication and environmental literacy. No other manufacturing technology can convert digital data into tangible objects quickly at relatively low cost; however, the expertise necessary to produce a 3D-printed terrain model can be a substantial burden: knowledge of geographical information systems, computer aided design (CAD) software, and 3D printers may all be required. Furthermore, printing models larger than the build volume of a 3D printer can pose further technical hurdles. The TouchTerrain web-application simplifies DDM for elevation data by generating digital 3D models customized for a specific 3D printer's capabilities. The only required user input is the selection of a region-of-interest using the provided web-application with a Google Maps-style interface. Publically available digital elevation data is processed via the Google Earth Engine API. To allow the manufacture of 3D terrain models larger than a 3D printer's build volume the selected area can be split into multiple tiles without third-party software. This application significantly reduces the time and effort required for a non-expert like an educator to obtain 3D terrain models for use in class. The web application is deployed at http://touchterrain.geol.iastate.edu/.

SECURE INTERNET OF THINGS-BASED CLOUD FRAMEWORK TO CONTROL ZIKA VIRUS OUTBREAK.

PubMed

Sareen, Sanjay; Sood, Sandeep K; Gupta, Sunil Kumar

2017-01-01

Zika virus (ZikaV) is currently one of the most important emerging viruses in the world which has caused outbreaks and epidemics and has also been associated with severe clinical manifestations and congenital malformations. Traditional approaches to combat the ZikaV outbreak are not effective for detection and control. The aim of this study is to propose a cloud-based system to prevent and control the spread of Zika virus disease using integration of mobile phones and Internet of Things (IoT). A Naive Bayesian Network (NBN) is used to diagnose the possibly infected users, and Google Maps Web service is used to provide the geographic positioning system (GPS)-based risk assessment to prevent the outbreak. It is used to represent each ZikaV infected user, mosquito-dense sites, and breeding sites on the Google map that helps the government healthcare authorities to control such risk-prone areas effectively and efficiently. The performance and accuracy of the proposed system are evaluated using dataset for 2 million users. Our system provides high accuracy for initial diagnosis of different users according to their symptoms and appropriate GPS-based risk assessment. The cloud-based proposed system contributed to the accurate NBN-based classification of infected users and accurate identification of risk-prone areas using Google Maps.

UNAVCO Software and Services for Visualization and Exploration of Geoscience Data

NASA Astrophysics Data System (ADS)

Meertens, C.; Wier, S.

2007-12-01

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

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).

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Implementing a geographical information system to assess endemic fluoride areas in Lamphun, Thailand

PubMed Central

Theerawasttanasiri, Nonthaphat; Taneepanichskul, Surasak; Pingchai, Wichain; Nimchareon, Yuwaree; Sriwichai, Sangworn

2018-01-01

Introduction Many studies have shown that fluoride can cross the placenta and that exposure to high fluoride during pregnancy may result in premature birth and/or a low birth weight. Lamphun is one of six provinces in Thailand where natural water fluoride (WF) concentrations >10.0 mg/L were found, and it was also found that >50% of households used water with high fluoride levels. Nevertheless, geographical information system (GIS) and maps of endemic fluoride areas are lacking. We aimed to measure the fluoride level of village water supplies to assess endemic fluoride areas and present GIS with maps in Google Maps. Methods A cross-sectional survey was conducted from July 2016 to January 2017. Purpose sampling was used to identify villages of districts with WF >10.0 mg/L in the Mueang Lamphun, Pasang, and Ban Thi districts. Water samples were collected with the geolocation measured by Smart System Info. Fluoride was analyzed with an ion-selective electrode instrument using a total ionic strength adjustment buffer. WF >0.70 mg/L was used to identify unsafe drinking water and areas with high endemic fluoride levels. Descriptive statistics were used to describe the findings, and MS Excel was used to create the GIS database. Maps were created in Google Earth and presented in Google Maps. Results We found that WF concentrations ranged between 0.10–13.60 mg/L. Forty-four percent (n=439) of samples were at unsafe levels (>0.70 mg/L), and. 54% (n=303) of villages and 46% (n=79,807) of households used the unsafe drinking water. Fifty percent (n=26) of subdistricts were classified as being endemic fluoride areas. Five subdistricts were endemic fluoride areas, and in those, there were two subdistricts in which every household used unsafe drinking water. Conclusion These findings show the distribution of endemic fluoride areas and unsafe drinking water in Lamphun. This is useful for health policy authorities, local governments, and villagers and enables collaboration to resolve these issues. The GIS data are available at https://drive.google.com/open?id=1mi4Pvomf5xHZ1MQjK44pdp2xXFw&usp=sharing. PMID:29398924

Implementing a geographical information system to assess endemic fluoride areas in Lamphun, Thailand.

PubMed

Theerawasttanasiri, Nonthaphat; Taneepanichskul, Surasak; Pingchai, Wichain; Nimchareon, Yuwaree; Sriwichai, Sangworn

2018-01-01

Many studies have shown that fluoride can cross the placenta and that exposure to high fluoride during pregnancy may result in premature birth and/or a low birth weight. Lamphun is one of six provinces in Thailand where natural water fluoride (WF) concentrations >10.0 mg/L were found, and it was also found that >50% of households used water with high fluoride levels. Nevertheless, geographical information system (GIS) and maps of endemic fluoride areas are lacking. We aimed to measure the fluoride level of village water supplies to assess endemic fluoride areas and present GIS with maps in Google Maps. A cross-sectional survey was conducted from July 2016 to January 2017. Purpose sampling was used to identify villages of districts with WF >10.0 mg/L in the Mueang Lamphun, Pasang, and Ban Thi districts. Water samples were collected with the geolocation measured by Smart System Info. Fluoride was analyzed with an ion-selective electrode instrument using a total ionic strength adjustment buffer. WF >0.70 mg/L was used to identify unsafe drinking water and areas with high endemic fluoride levels. Descriptive statistics were used to describe the findings, and MS Excel was used to create the GIS database. Maps were created in Google Earth and presented in Google Maps. We found that WF concentrations ranged between 0.10-13.60 mg/L. Forty-four percent (n=439) of samples were at unsafe levels (>0.70 mg/L), and. 54% (n=303) of villages and 46% (n=79,807) of households used the unsafe drinking water. Fifty percent (n=26) of subdistricts were classified as being endemic fluoride areas. Five subdistricts were endemic fluoride areas, and in those, there were two subdistricts in which every household used unsafe drinking water. These findings show the distribution of endemic fluoride areas and unsafe drinking water in Lamphun. This is useful for health policy authorities, local governments, and villagers and enables collaboration to resolve these issues. The GIS data are available at https://drive.google.com/open?id=1mi4Pvomf5xHZ1MQjK44pdp2xXFw&usp=sharing.

An Android based location service using GSMCellID and GPS to obtain a graphical guide to the nearest cash machine

NASA Astrophysics Data System (ADS)

Jacobsen, Jurma; Edlich, Stefan

2009-02-01

There is a broad range of potential useful mobile location-based applications. One crucial point seems to be to make them available to the public at large. This case illuminates the abilities of Android - the operating system for mobile devices - to fulfill this demand in the mashup way by use of some special geocoding web services and one integrated web service for getting the nearest cash machines data. It shows an exemplary approach for building mobile location-based mashups for everyone: 1. As a basis for reaching as many people as possible the open source Android OS is assumed to spread widely. 2. Everyone also means that the handset has not to be an expensive GPS device. This is realized by re-utilization of the existing GSM infrastructure with the Cell of Origin (COO) method which makes a lookup of the CellID in one of the growing web available CellID databases. Some of these databases are still undocumented and not yet published. Furthermore the Google Maps API for Mobile (GMM) and the open source counterpart OpenCellID are used. The user's current position localization via lookup of the closest cell to which the handset is currently connected to (COO) is not as precise as GPS, but appears to be sufficient for lots of applications. For this reason the GPS user is the most pleased one - for this user the system is fully automated. In contrary there could be some users who doesn't own a GPS cellular. This user should refine his/her location by one click on the map inside of the determined circular region. The users are then shown and guided by a path to the nearest cash machine by integrating Google Maps API with an overlay. Additionally, the GPS user can keep track of him- or herself by getting a frequently updated view via constantly requested precise GPS data for his or her position.

Decision Support System for the Response to Infectious Disease Emergencies Based on WebGIS and Mobile Services in China

PubMed Central

Gao, Su-qing; Wang, Zhen; Gao, Hong-wei; Liu, Peng; Wang, Ze-rui; Li, Yan-li; Zhu, Xu-guang; Li, Xin-lou; Xu, Bo; Li, Yin-jun; Yang, Hong; de Vlas, Sake J.; Shi, Tao-xing; Cao, Wu-chun

2013-01-01

Background For years, emerging infectious diseases have appeared worldwide and threatened the health of people. The emergence and spread of an infectious-disease outbreak are usually unforeseen, and have the features of suddenness and uncertainty. Timely understanding of basic information in the field, and the collection and analysis of epidemiological information, is helpful in making rapid decisions and responding to an infectious-disease emergency. Therefore, it is necessary to have an unobstructed channel and convenient tool for the collection and analysis of epidemiologic information in the field. Methodology/Principal Findings Baseline information for each county in mainland China was collected and a database was established by geo-coding information on a digital map of county boundaries throughout the country. Google Maps was used to display geographic information and to conduct calculations related to maps, and the 3G wireless network was used to transmit information collected in the field to the server. This study established a decision support system for the response to infectious-disease emergencies based on WebGIS and mobile services (DSSRIDE). The DSSRIDE provides functions including data collection, communication and analyses in real time, epidemiological detection, the provision of customized epidemiological questionnaires and guides for handling infectious disease emergencies, and the querying of professional knowledge in the field. These functions of the DSSRIDE could be helpful for epidemiological investigations in the field and the handling of infectious-disease emergencies. Conclusions/Significance The DSSRIDE provides a geographic information platform based on the Google Maps application programming interface to display information of infectious disease emergencies, and transfers information between workers in the field and decision makers through wireless transmission based on personal computers, mobile phones and personal digital assistants. After a 2-year practice and application in infectious disease emergencies, the DSSRIDE is becoming a useful platform and is a useful tool for investigations in the field carried out by response sections and individuals. The system is suitable for use in developing countries and low-income districts. PMID:23372780

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/

Visualizing Mars data and imagery with Google Earth

NASA Astrophysics Data System (ADS)

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

2009-12-01

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

A campus-based course in field geology

NASA Astrophysics Data System (ADS)

Richard, G. A.; Hanson, G. N.

2009-12-01

GEO 305: Field Geology offers students practical experience in the field and in the computer laboratory conducting geological field studies on the Stony Brook University campus. Computer laboratory exercises feature mapping techniques and field studies of glacial and environmental geology, and include geophysical and hydrological analysis, interpretation, and mapping. Participants learn to use direct measurement and mathematical techniques to compute the location and geometry of features and gain practical experience in representing raster imagery and vector geographic data as features on maps. Data collecting techniques in the field include the use of hand-held GPS devices, compasses, ground-penetrating radar, tape measures, pacing, and leveling devices. Assignments that utilize these skills and techniques include mapping campus geology with GPS, using Google Earth to explore our geologic context, data file management and ArcGIS, tape and compass mapping of woodland trails, pace and compass mapping of woodland trails, measuring elevation differences on a hillside, measuring geologic sections and cores, drilling through glacial deposits, using ground penetrating radar on glaciotectonic topography, mapping the local water table, and the identification and mapping of boulders. Two three-hour sessions are offered per week, apportioned as needed between lecture; discussion; guided hands-on instruction in geospatial and other software such as ArcGIS, Google Earth, spreadsheets, and custom modules such as an arc intersection calculator; outdoor data collection and mapping; and writing of illustrated reports.

The Qatar National Historic Environment Record: a Platform for the Development of a Fully-Integrated Cultural Heritage Management Application

NASA Astrophysics Data System (ADS)

Cuttler, R. T. H.; Tonner, T. W. W.; Al-Naimi, F. A.; Dingwall, L. M.; Al-Hemaidi, N.

2013-07-01

The development of the Qatar National Historic Environment Record (QNHER) by the Qatar Museums Authority and the University of Birmingham in 2008 was based on a customised, bilingual Access database and ArcGIS. While both platforms are stable and well supported, neither was designed for the documentation and retrieval of cultural heritage data. As a result it was decided to develop a custom application using Open Source code. The core module of this application is now completed and is orientated towards the storage and retrieval of geospatial heritage data for the curation of heritage assets. Based on MIDAS Heritage data standards and regionally relevant thesauri, it is a truly bilingual system. Significant attention has been paid to the user interface, which is userfriendly and intuitive. Based on a suite of web services and accessed through a web browser, the system makes full use of internet resources such as Google Maps and Bing Maps. The application avoids long term vendor ''tie-ins'' and as a fully integrated data management system, is now an important tool for both cultural resource managers and heritage researchers in Qatar.

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

Using Google Earth for Submarine Operations at Pavilion Lake

NASA Astrophysics Data System (ADS)

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

2009-12-01

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

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.

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

NASA Astrophysics Data System (ADS)

Bailey, J.

2017-12-01

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

Quantifying the effect of media limitations on outbreak data in a global online web-crawling epidemic intelligence system, 2008–2011

PubMed Central

Scales, David; Zelenev, Alexei; Brownstein, John S.

2013-01-01

Background This is the first study quantitatively evaluating the effect that media-related limitations have on data from an automated epidemic intelligence system. Methods We modeled time series of HealthMap's two main data feeds, Google News and Moreover, to test for evidence of two potential limitations: first, human resources constraints, and second, high-profile outbreaks “crowding out” coverage of other infectious diseases. Results Google News events declined by 58.3%, 65.9%, and 14.7% on Saturday, Sunday and Monday, respectively, relative to other weekdays. Events were reduced by 27.4% during Christmas/New Years weeks and 33.6% lower during American Thanksgiving week than during an average week for Google News. Moreover data yielded similar results with the addition of Memorial Day (US) being associated with a 36.2% reduction in events. Other holiday effects were not statistically significant. We found evidence for a crowd out phenomenon for influenza/H1N1, where a 50% increase in influenza events corresponded with a 4% decline in other disease events for Google News only. Other prominent diseases in this database – avian influenza (H5N1), cholera, or foodborne illness – were not associated with a crowd out phenomenon. Conclusions These results provide quantitative evidence for the limited impact of editorial biases on HealthMap's web-crawling epidemic intelligence. PMID:24206612

Challenges in the Development and Evolution of Secure Open Architecture Command and Control Systems (Briefing Charts)

DTIC Science & Technology

2013-06-01

widgets for an OA system Design-time architecture: Browser, email, widget, DB, OS Go ogle Instance architecture: Chrome, Gmail, Google...provides functionally similar components or applications compatible with an OA system design Firefox Browser, WP, calendar Opera Instance...architecture: Firefox , AbiWord, Evolution, Fedora GPL Ab1Word Google Docs Instance ardlitecture: Fire fox, OR Google cal., Google Docs, Fedora

Using GeoRSS feeds to distribute house renting and selling information based on Google map

NASA Astrophysics Data System (ADS)

Nong, Yu; Wang, Kun; Miao, Lei; Chen, Fei

2007-06-01

Geographically Encoded Objects RSS (GeoRSS) is a way to encode location in RSS feeds. RSS is a widely supported format for syndication of news and weblogs, and is extendable to publish any sort of itemized data. When Weblogs explode since RSS became new portals, Geo-tagged feed is necessary to show the location that story tells. Geographically Encoded Objects adopts the core of RSS framework, making itself the map annotations specified in the RSS XML format. The case studied illuminates that GeoRSS could be maximally concise in representation and conception, so it's simple to manipulate generation and then mashup GeoRSS feeds with Google Map through API to show the real estate information with other attribute in the information window. After subscribe to feeds of concerned subjects, users could easily check for new bulletin showing on map through syndication. The primary design goal of GeoRSS is to make spatial data creation as easy as regular Web content development. However, it does more for successfully bridging the gap between traditional GIS professionals and amateurs, Web map hackers, and numerous services that enable location-based content for its simplicity and effectiveness.

Real-time bus location monitoring using Arduino

NASA Astrophysics Data System (ADS)

Ibrahim, Mohammad Y. M.; Audah, Lukman

2017-09-01

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

Googling Service Boundaries for Endovascular Clot Retrieval Hub Hospitals in a Metropolitan Setting: Proof-of-Concept Study.

PubMed

Phan, Thanh G; Beare, Richard; Chen, Jian; Clissold, Benjamin; Ly, John; Singhal, Shaloo; Ma, Henry; Srikanth, Velandai

2017-05-01

There is great interest in how endovascular clot retrieval hubs provide services to a population. We applied a computational method to objectively generate service boundaries for such endovascular clot retrieval hubs, defined by traveling time to hub. Stroke incidence data merged with population census to estimate numbers of stroke in metropolitan Melbourne, Australia. Traveling time from randomly generated addresses to 4 endovascular clot retrieval-capable hubs (Royal Melbourne Hospital [RMH], Monash Medical Center [MMC], Alfred Hospital [ALF], and Austin Hospital [AUS]) estimated using Google Map application program interface. Boundary maps generated based on traveling time at various times of day for combinations of hubs. In a 2-hub model, catchment was best distributed when RMH was paired with MMC (model 1a, RMH 1765 km 2 and MMC 1164 km 2 ) or with AUS (model 1c, RMH 1244 km 2 and AUS 1685 km 2 ), with no statistical difference between models ( P =0.20). Catchment was poorly distributed when RMH was paired with ALF (model 1b, RMH 2252 km 2 and ALF 676 km 2 ), significantly different from both models 1a and 1c (both P <0.05). Model 1a had the greatest proportion of patients arriving within ideal time of 30 minutes followed by model 1c ( P <0.001). In a 3-hub model, the combination of RMH, MMC, and AUS was superior to that of RMH, MMC, and ALF in catchment distribution and travel time. The method was also successfully applied to the city of Adelaide demonstrating wider applicability. We provide proof of concept for a novel computational method to objectively designate service boundaries for endovascular clot retrieval hubs. © 2017 American Heart Association, Inc.

Smart "geomorphological" map browsing - a tale about geomorphological maps and the internet

NASA Astrophysics Data System (ADS)

Geilhausen, M.; Otto, J.-C.

2012-04-01

With the digital production of geomorphological maps, the dissemination of research outputs now extends beyond simple paper products. Internet technologies can contribute to both, the dissemination of geomorphological maps and access to geomorphologic data and help to make geomorphological knowledge available to a greater public. Indeed, many national geological surveys employ end-to-end digital workflows from data capture in the field to final map production and dissemination. This paper deals with the potential of web mapping applications and interactive, portable georeferenced PDF maps for the distribution of geomorphological information. Web mapping applications such as Google Maps have become very popular and widespread and increased the interest and access to mapping. They link the Internet with GIS technology and are a common way of presenting dynamic maps online. The GIS processing is performed online and maps are visualised in interactive web viewers characterised by different capabilities such as zooming, panning or adding further thematic layers, with the map refreshed after each task. Depending on the system architecture and the components used, advanced symbology, map overlays from different applications and sources and their integration into a Desktop GIS are possible. This interoperability is achieved through the use of international open standards that include mechanisms for the integration and visualisation of information from multiple sources. The portable document format (PDF) is commonly used for printing and is a standard format that can be processed by many graphic software and printers without loss of information. A GeoPDF enables the sharing of geospatial maps and data in PDF documents. Multiple, independent map frames with individual spatial reference systems are possible within a GeoPDF, for example, for map overlays or insets. Geospatial functionality of a GeoPDF includes scalable map display, layer visibility control, access to attribute data, coordinate queries and spatial measurements. The full functionality of GeoPDFs requires free and user-friendly plug-ins for PDF readers and GIS software. A GeoPDF enables fundamental GIS functionality turning the formerly static PDF map into an interactive, portable georeferenced PDF map. GeoPDFs are easy to create and provide an interesting and valuable way to disseminate geomorphological maps. Our motivation to engage with the online distribution of geomorphological maps originates in the increasing number of web mapping applications available today indicating that the Internet has become a medium for displaying geographical information in rich forms and user-friendly interfaces. So, why not use the Internet to distribute geomorphological maps and enhance their practical application? Web mapping and dynamic PDF maps can play a key role in the movement towards a global dissemination of geomorphological information. This will be exemplified by live demonstrations of i.) existing geomorphological WebGIS applications, ii.) data merging from various sources using web map services, and iii.) free to download GeoPDF maps during the presentations.

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

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

PubMed Central

Kamadjeu, Raoul

2009-01-01

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

Using Google Maps to Access USGS Volcano Hazards Information

NASA Astrophysics Data System (ADS)

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

2006-12-01

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

[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.

Designing human centered GeoVisualization application--the SanaViz--for telehealth users: a case study.

PubMed

Joshi, Ashish; de Araujo Novaes, Magdala; Machiavelli, Josiane; Iyengar, Sriram; Vogler, Robert; Johnson, Craig; Zhang, Jiajie; Hsu, Chiehwen E

2012-01-01

Public health data is typically organized by geospatial unit. GeoVisualization (GeoVis) allows users to see information visually on a map. Examine telehealth users' perceptions towards existing public health GeoVis applications and obtains users' feedback about features important for the design and development of Human Centered GeoVis application "the SanaViz". We employed a cross sectional study design using mixed methods approach for this pilot study. Twenty users involved with the NUTES telehealth center at Federal University of Pernambuco (UFPE), Recife, Brazil were enrolled. Open and closed ended questionnaires were used to gather data. We performed audio recording for the interviews. Information gathered included socio-demographics, prior spatial skills and perception towards use of GeoVis to evaluate telehealth services. Card sorting and sketching methods were employed. Univariate analysis was performed for the continuous and categorical variables. Qualitative analysis was performed for open ended questions. Existing Public Health GeoVis applications were difficult to use. Results found interaction features zooming, linking and brushing and representation features Google maps, tables and bar chart as most preferred GeoVis features. Early involvement of users is essential to identify features necessary to be part of the human centered GeoVis application "the SanaViz".

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.

An integrated WebGIS framework for volunteered geographic information and social media in soil and water conservation.

PubMed

Werts, Joshua D; Mikhailova, Elena A; Post, Christopher J; Sharp, Julia L

2012-04-01

Volunteered geographic information and social networking in a WebGIS has the potential to increase public participation in soil and water conservation, promote environmental awareness and change, and provide timely data that may be otherwise unavailable to policymakers in soil and water conservation management. The objectives of this study were: (1) to develop a framework for combining current technologies, computing advances, data sources, and social media; and (2) develop and test an online web mapping interface. The mapping interface integrates Microsoft Silverlight, Bing Maps, ArcGIS Server, Google Picasa Web Albums Data API, RSS, Google Analytics, and Facebook to create a rich user experience. The website allows the public to upload photos and attributes of their own subdivisions or sites they have identified and explore other submissions. The website was made available to the public in early February 2011 at http://www.AbandonedDevelopments.com and evaluated for its potential long-term success in a pilot study.

An Integrated WebGIS Framework for Volunteered Geographic Information and Social Media in Soil and Water Conservation

NASA Astrophysics Data System (ADS)

Werts, Joshua D.; Mikhailova, Elena A.; Post, Christopher J.; Sharp, Julia L.

2012-04-01

Volunteered geographic information and social networking in a WebGIS has the potential to increase public participation in soil and water conservation, promote environmental awareness and change, and provide timely data that may be otherwise unavailable to policymakers in soil and water conservation management. The objectives of this study were: (1) to develop a framework for combining current technologies, computing advances, data sources, and social media; and (2) develop and test an online web mapping interface. The mapping interface integrates Microsoft Silverlight, Bing Maps, ArcGIS Server, Google Picasa Web Albums Data API, RSS, Google Analytics, and Facebook to create a rich user experience. The website allows the public to upload photos and attributes of their own subdivisions or sites they have identified and explore other submissions. The website was made available to the public in early February 2011 at http://www.AbandonedDevelopments.com and evaluated for its potential long-term success in a pilot study.

75 FR 359 - Google Energy LLC; Supplemental Notice That Initial Market-Based Rate Filing Includes Request for...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-05

... DEPARTMENT OF ENERGY Federal Energy Regulatory Commission [Docket No. ER10-468-000] Google Energy LLC; Supplemental Notice That Initial Market-Based Rate Filing Includes Request for Blanket Section... of Google Energy LLC's application for market-based rate authority, with an accompanying rate tariff...

Flight Planning in the Cloud

NASA Technical Reports Server (NTRS)

Flores, Sarah L.; Chapman, Bruce D.; Tung, Waye W.; Zheng, Yang

2011-01-01

This new interface will enable Principal Investigators (PIs), as well as UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar) members to do their own flight planning and time estimation without having to request flight lines through the science coordinator. It uses an all-in-one Google Maps interface, a JPL hosted database, and PI flight requirements to design an airborne flight plan. The application will enable users to see their own flight plan being constructed interactively through a map interface, and then the flight planning software will generate all the files necessary for the flight. Afterward, the UAVSAR team can then complete the flight request, including calendaring and supplying requisite flight request files in the expected format for processing by NASA s airborne science program. Some of the main features of the interface include drawing flight lines on the map, nudging them, adding them to the current flight plan, and reordering them. The user can also search and select takeoff, landing, and intermediate airports. As the flight plan is constructed, all of its components are constantly being saved to the database, and the estimated flight times are updated. Another feature is the ability to import flight lines from previously saved flight plans. One of the main motivations was to make this Web application as simple and intuitive as possible, while also being dynamic and robust. This Web application can easily be extended to support other airborne instruments.

Decision support system for emergency management of oil spill accidents in the Mediterranean Sea

NASA Astrophysics Data System (ADS)

Liubartseva, Svitlana; Coppini, Giovanni; Pinardi, Nadia; De Dominicis, Michela; Lecci, Rita; Turrisi, Giuseppe; Cretì, Sergio; Martinelli, Sara; Agostini, Paola; Marra, Palmalisa; Palermo, Francesco

2016-08-01

This paper presents an innovative web-based decision support system to facilitate emergency management in the case of oil spill accidents, called WITOIL (Where Is The Oil). The system can be applied to create a forecast of oil spill events, evaluate uncertainty of the predictions, and calculate hazards based on historical meteo-oceanographic datasets. To compute the oil transport and transformation, WITOIL uses the MEDSLIK-II oil spill model forced by operational meteo-oceanographic services. Results of the modeling are visualized through Google Maps. A special application for Android is designed to provide mobile access for competent authorities, technical and scientific institutions, and citizens.

Spatiotemporal-Thematic Data Processing for the Semantic Web

NASA Astrophysics Data System (ADS)

Hakimpour, Farshad; Aleman-Meza, Boanerges; Perry, Matthew; Sheth, Amit

This chapter presents practical approaches to data processing in the space, time and theme dimensions using existing Semantic Web technologies. It describes how we obtain geographic and event data from Internet sources and also how we integrate them into an RDF store. We briefly introduce a set of functionalities in space, time and semantics. These functionalities are implemented based on our existing technology for main-memory-based RDF data processing developed at the LSDIS Lab. A number of these functionalities are exposed as REST Web services. We present two sample client-side applications that are developed using a combination of our services with Google Maps service.

Near real-time aftershock hazard maps for earthquakes

NASA Astrophysics Data System (ADS)

McCloskey, J.; Nalbant, S. S.

2009-04-01

Stress interaction modelling is routinely used to explain the spatial relationships between earthquakes and their aftershocks. On 28 October 2008 a M6.4 earthquake occurred near the Pakistan-Afghanistan border killing several hundred and causing widespread devastation. A second M6.4 event occurred 12 hours later 20km to the south east. By making some well supported assumptions concerning the source event and the geometry of any likely triggered event it was possible to map those areas most likely to experience further activity. Using Google earth, it would further have been possible to identify particular settlements in the source area which were particularly at risk and to publish their locations globally within about 3 hours of the first earthquake. Such actions could have significantly focused the initial emergency response management. We argue for routine prospective testing of such forecasts and dialogue between social and physical scientists and emergency response professionals around the practical application of these techniques.

Beebook: light field mapping app

NASA Astrophysics Data System (ADS)

De Donatis, Mauro; Di Pietro, Gianfranco; Rinnone, Fabio

2014-05-01

In the last decade the mobile systems for field digital mapping were developed (see Wikipedia for "Digital geologic mapping"), also against many skeptic traditional geologists. Until now, hardware was often heavy (tablet PC) and software sometime difficult also for expert GIS users. At present, the advent of light tablet and applications makes things easier, but we are far to find a whole solution for a complex survey like the geological one where you have to manage complexities such information, hypothesis, data, interpretation. Beebook is a new app for Android devices, has been developed for fast ad easy mapping work in the field trying to try to solve this problem. The main features are: • off-line raster management, GeoTIFF ed other raster format using; • on-line map visualisation (Google Maps, OSM, WMS, WFS); • SR management and conversion using PROJ.4; • vector file mash-up (KML and SQLite format); • editing of vector data on the map (lines, points, polygons); • augmented reality using "Mixare" platform; • export of vector data in KML, CSV, SQLite (Spatialite) format; • note: GPS or manual point inserting linked to other application files (pictures, spreadsheet, etc.); • form: creation, edition and filling of customized form; • GPS: status control, tracker and positioning on map; • sharing: synchronization and sharing of data, forms, positioning and other information can be done among users. The input methods are different from digital keyboard to fingers touch, from voice recording to stylus. In particular the most efficient way of inserting information is the stylus (or pen): field geologists are familiar with annotation and sketches. Therefore we suggest the use of devices with stylus. The main point is that Beebook is the first "transparent" mobile GIS for tablet and smartphone deriving from previous experience as traditional mapping and different previous digital mapping software ideation and development (MapIT, BeeGIS, Geopaparazzi). Deriving from those experiences, we developed a tool which is easy to use and applicable not only for geology but also to every field survey.

ESPACE - a geodetic Master's program for the education of Satellite Application Engineers

NASA Astrophysics Data System (ADS)

Hedman, K.; Kirschner, S.; Seitz, F.

2012-04-01

In the last decades there has been a rapid development of new geodetic and other Earth observation satellites. Applications of these satellites such as car navigation systems, weather predictions, and, digital maps (such as Google Earth or Google Maps) play a more and more important role in our daily life. For geosciences, satellite applications such as remote sensing and precise positioning/navigation have turned out to be extremely useful and are meanwhile indispensable. Today, researchers within geodesy, climatology, oceanography, meteorology as well as within Earth system science are all dependent on up-to-date satellite data. Design, development and handling of these missions require experts with knowledge not only in space engineering, but also in the specific applications. That gives rise to a new kind of engineers - satellite application engineers. The study program for these engineers combines parts of different classical disciplines such as geodesy, aerospace engineering or electronic engineering. The satellite application engineering program Earth Oriented Space Science and Technology (ESPACE) was founded in 2005 at the Technische Universität München, mainly from institutions involved in geodesy and aerospace engineering. It is an international, interdisciplinary Master's program, and is open to students with a BSc in both Science (e.g. Geodesy, Mathematics, Informatics, Geophysics) and Engineering (e.g. Aerospace, Electronical and Mechanical Engineering). The program is completely conducted in English. ESPACE benefits from and utilizes its location in Munich with its unique concentration of expertise related to space science and technology. Teaching staff from 3 universities (Technische Universität München, Ludwig-Maximilian University, University of the Federal Armed Forces), research institutions (such as the German Aerospace Center, DLR and the German Geodetic Research Institute, DGFI) and space industry (such as EADS or Kayser-Threde) are involved in ESPACE. This paper will first give the background and objectives of ESPACE with focus on its specific position in geodetic education programmes. Second, we will introduce the interdisciplinary study program and explain the involvement of external teaching staff. Further we will give an up-to-date description of current students and ESPACE alumni. The job market and international demand for satellite application engineers will be shown especially with focus to geodetic fields.

Smartphones for Geological Data Collection- an Android Phone Application

NASA Astrophysics Data System (ADS)

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

2010-12-01

Recently, smartphones have attracted great attention in the wireless device market because of their powerful processors, ample memory capacity, advanced connectivity, and numerous utility programs. Considering the prominent new features a smartphone has, such as the large touch screen, speaker, microphone, camera, GPS receiver, accelerometer, and Internet connections, it can serve as a perfect digital aide for data recording on any geological field trip. We have designed and developed an application by using aforementioned features in an Android phone to provide functionalities used in field studies. For example, employing the accelerometer in the Android phone, the application turns the handset into a brunton-like device by which users can measure directions, strike and dip of a bedding plane or trend and plunge of a fold. Our application also includes functionalities of image taking, GPS coordinates tracking, videotaping, audio recording, and note writing. Data recorded from the application are tied together by the time log, which makes the task easy to track all data regarding a specific geologic object. The application pulls the GPS reading from the phone’s built-in GPS receiver and uses it as a spatial index to link up the other type of data, then maps them to the Google Maps/Earth for visualization. In this way, notes, pictures, audio or video recordings to depict the characteristics of the outcrops and their spatial relations, all can be well documented and organized in one handy gadget.

The use of mobile technology for tourism development (case study: banyumas regency)

NASA Astrophysics Data System (ADS)

Gunawan, H.

2018-01-01

Banyumas is regency in Central Java Province and Purwokerto Capital City. Banyumas has a lot of tourism areas, but not all of the areas are known by tourists because the lack of information. The information on Banyumas government’s website is not updated and uncomplete, so that it needs other information services for the tourism information in Banyumas. An android-based application Banyumas Travel Guide (BMSGuide) is a location-based application to help the people can access the information whenever and wherever they are. The service in this application is using Android which is platform that is now developing rapidly with interface User Friendly and the price is affordable. The application will access Google Maps and show the user location, destination location along with the information, and the navigation to the location. The information is gotten by accessing the satellite with GPS (Global Positioning System) tool of the user’s headset. By using BMSGuide application, the information service of tourism location and the supporting place around is served.

Local Air Quality Conditions and Forecasts

MedlinePlus

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

Zebra Crossing Spotter: Automatic Population of Spatial Databases for Increased Safety of Blind Travelers

PubMed Central

Ahmetovic, Dragan; Manduchi, Roberto; Coughlan, James M.; Mascetti, Sergio

2016-01-01

In this paper we propose a computer vision-based technique that mines existing spatial image databases for discovery of zebra crosswalks in urban settings. Knowing the location of crosswalks is critical for a blind person planning a trip that includes street crossing. By augmenting existing spatial databases (such as Google Maps or OpenStreetMap) with this information, a blind traveler may make more informed routing decisions, resulting in greater safety during independent travel. Our algorithm first searches for zebra crosswalks in satellite images; all candidates thus found are validated against spatially registered Google Street View images. This cascaded approach enables fast and reliable discovery and localization of zebra crosswalks in large image datasets. While fully automatic, our algorithm could also be complemented by a final crowdsourcing validation stage for increased accuracy. PMID:26824080

Understanding the productive author who published papers in medicine using National Health Insurance Database: A systematic review and meta-analysis.

PubMed

Chien, Tsair-Wei; Chang, Yu; Wang, Hsien-Yi

2018-02-01

Many researchers used National Health Insurance database to publish medical papers which are often retrospective, population-based, and cohort studies. However, the author's research domain and academic characteristics are still unclear.By searching the PubMed database (Pubmed.com), we used the keyword of [Taiwan] and [National Health Insurance Research Database], then downloaded 2913 articles published from 1995 to 2017. Social network analysis (SNA), Gini coefficient, and Google Maps were applied to gather these data for visualizing: the most productive author; the pattern of coauthor collaboration teams; and the author's research domain denoted by abstract keywords and Pubmed MESH (medical subject heading) terms.Utilizing the 2913 papers from Taiwan's National Health Insurance database, we chose the top 10 research teams shown on Google Maps and analyzed one author (Dr. Kao) who published 149 papers in the database in 2015. In the past 15 years, we found Dr. Kao had 2987 connections with other coauthors from 13 research teams. The cooccurrence abstract keywords with the highest frequency are cohort study and National Health Insurance Research Database. The most coexistent MESH terms are tomography, X-ray computed, and positron-emission tomography. The strength of the author research distinct domain is very low (Gini < 0.40).SNA incorporated with Google Maps and Gini coefficient provides insight into the relationships between entities. The results obtained in this study can be applied for a comprehensive understanding of other productive authors in the field of academics.

Medical student appraisal: searching on smartphones.

PubMed

Khalifian, S; Markman, T; Sampognaro, P; Mitchell, S; Weeks, S; Dattilo, J

2013-01-01

The rapidly growing industry for mobile medical applications provides numerous smartphone resources designed for healthcare professionals. However, not all applications are equally useful in addressing the questions of early medical trainees. Three popular, free, mobile healthcare applications were evaluated along with a Google(TM) web search on both Apple(TM) and Android(TM) devices. Six medical students at a large academic hospital evaluated each application for a one-week period while on various clinical rotations. Google(TM) was the most frequently used search method and presented multimedia resources but was inefficient for obtaining clinical management information. Epocrates(TM) Pill ID feature was praised for its clinical utility. Medscape(TM) had the highest satisfaction of search and excelled through interactive educational features. Micromedex(TM) offered both FDA and off-label dosing for drugs. Google(TM) was the preferred search method for questions related to basic disease processes and multimedia resources, but was inadequate for clinical management. Caution should also be exercised when using Google(TM) in front of patients. Medscape(TM) was the most appealing application due to a broad scope of content and educational features relevant to medical trainees. Students should also be cognizant of how mobile technology may be perceived by their evaluators to avoid false impressions.

Augmented Reality as a Navigation Tool to Employment Opportunities for Postsecondary Education Students with Intellectual Disabilities and Autism

ERIC Educational Resources Information Center

McMahon, Don; Cihak, David F.; Wright, Rachel

2015-01-01

The purpose of this study was to examine the effects of location-based augmented reality navigation compared to Google Maps and paper maps as navigation aids for students with disabilities. The participants in this single subject study were three college students with intellectual disability and one college student with autism spectrum disorder.…

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

EPA Science Inventory

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

ClimateWizard: A Framework and Easy-to-Use Web-Mapping Tool for Global, Regional, and Local Climate-Change Analysis

NASA Astrophysics Data System (ADS)

Girvetz, E. H.; Zganjar, C.; Raber, G. T.; Hoekstra, J.; Lawler, J. J.; Kareiva, P.

2008-12-01

Now that there is overwhelming evidence of global climate change, scientists, managers and planners (i.e. practitioners) need to assess the potential impacts of climate change on particular ecological systems, within specific geographic areas, and at spatial scales they care about, in order to make better land management, planning, and policy decisions. Unfortunately, this application of climate science to real world decisions and planning has proceeded too slowly because we lack tools for translating cutting-edge climate science and climate-model outputs into something managers and planners can work with at local or regional scales (CCSP 2008). To help increase the accessibility of climate information, we have developed a freely-available, easy-to-use, web-based climate-change analysis toolbox, called ClimateWizard, for assessing how climate has and is projected to change at specific geographic locations throughout the world. The ClimateWizard uses geographic information systems (GIS), web-services (SOAP/XML), statistical analysis platforms (e.g. R- project), and web-based mapping services (e.g. Google Earth/Maps, KML/GML) to provide a variety of different analyses (e.g. trends and departures) and outputs (e.g. maps, graphs, tables, GIS layers). Because ClimateWizard analyzes large climate datasets stored remotely on powerful computers, users of the tool do not need to have fast computers or expensive software, but simply need access to the internet. The analysis results are then provided to users in a Google Maps webpage tailored to the specific climate-change question being asked. The ClimateWizard is not a static product, but rather a framework to be built upon and modified to suit the purposes of specific scientific, management, and policy questions. For example, it can be expanded to include bioclimatic variables (e.g. evapotranspiration) and marine data (e.g. sea surface temperature), as well as improved future climate projections, and climate-change impact analyses involving hydrology, vegetation, wildfire, disease, and food security. By harnessing the power of computer and web- based technologies, the ClimateWizard puts local, regional, and global climate-change analyses in the hands of a wider array of managers, planners, and scientists.

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

Using Internet-Based Applications to Increase Collaboration among Stakeholders in Special Education

ERIC Educational Resources Information Center

Riggleman, Samantha; Buchter, Jennifer M.

2017-01-01

Input from parents of children with disabilities is highly valuable; however, barriers such as lack of time or travel can hinder the partnership between parents and stakeholders. Internet-based applications (e.g., Google Groups, Google Drive, and OneDrive) can alleviate some of the difficulties in collaborating. This article describes the use and…

NaviCell: a web-based environment for navigation, curation and maintenance of large molecular interaction maps

PubMed Central

2013-01-01

Background Molecular biology knowledge can be formalized and systematically represented in a computer-readable form as a comprehensive map of molecular interactions. There exist an increasing number of maps of molecular interactions containing detailed and step-wise description of various cell mechanisms. It is difficult to explore these large maps, to organize discussion of their content and to maintain them. Several efforts were recently made to combine these capabilities together in one environment, and NaviCell is one of them. Results NaviCell is a web-based environment for exploiting large maps of molecular interactions, created in CellDesigner, allowing their easy exploration, curation and maintenance. It is characterized by a combination of three essential features: (1) efficient map browsing based on Google Maps; (2) semantic zooming for viewing different levels of details or of abstraction of the map and (3) integrated web-based blog for collecting community feedback. NaviCell can be easily used by experts in the field of molecular biology for studying molecular entities of interest in the context of signaling pathways and crosstalk between pathways within a global signaling network. NaviCell allows both exploration of detailed molecular mechanisms represented on the map and a more abstract view of the map up to a top-level modular representation. NaviCell greatly facilitates curation, maintenance and updating the comprehensive maps of molecular interactions in an interactive and user-friendly fashion due to an imbedded blogging system. Conclusions NaviCell provides user-friendly exploration of large-scale maps of molecular interactions, thanks to Google Maps and WordPress interfaces, with which many users are already familiar. Semantic zooming which is used for navigating geographical maps is adopted for molecular maps in NaviCell, making any level of visualization readable. In addition, NaviCell provides a framework for community-based curation of maps. PMID:24099179

NaviCell: a web-based environment for navigation, curation and maintenance of large molecular interaction maps.

PubMed

Kuperstein, Inna; Cohen, David P A; Pook, Stuart; Viara, Eric; Calzone, Laurence; Barillot, Emmanuel; Zinovyev, Andrei

2013-10-07

Molecular biology knowledge can be formalized and systematically represented in a computer-readable form as a comprehensive map of molecular interactions. There exist an increasing number of maps of molecular interactions containing detailed and step-wise description of various cell mechanisms. It is difficult to explore these large maps, to organize discussion of their content and to maintain them. Several efforts were recently made to combine these capabilities together in one environment, and NaviCell is one of them. NaviCell is a web-based environment for exploiting large maps of molecular interactions, created in CellDesigner, allowing their easy exploration, curation and maintenance. It is characterized by a combination of three essential features: (1) efficient map browsing based on Google Maps; (2) semantic zooming for viewing different levels of details or of abstraction of the map and (3) integrated web-based blog for collecting community feedback. NaviCell can be easily used by experts in the field of molecular biology for studying molecular entities of interest in the context of signaling pathways and crosstalk between pathways within a global signaling network. NaviCell allows both exploration of detailed molecular mechanisms represented on the map and a more abstract view of the map up to a top-level modular representation. NaviCell greatly facilitates curation, maintenance and updating the comprehensive maps of molecular interactions in an interactive and user-friendly fashion due to an imbedded blogging system. NaviCell provides user-friendly exploration of large-scale maps of molecular interactions, thanks to Google Maps and WordPress interfaces, with which many users are already familiar. Semantic zooming which is used for navigating geographical maps is adopted for molecular maps in NaviCell, making any level of visualization readable. In addition, NaviCell provides a framework for community-based curation of maps.

75 FR 21289 - Combined Notice of Filings #1

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-23

...: 5 p.m. Eastern Time on Friday, April 30, 2010. Docket Numbers: ER10-468-002. Applicants: Google Energy LLC. Description: Google Energy LLC submits substitute FERC Electric Tariff, Volume No. 1. Filed...

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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.

Utilization of Google enterprise tools to georeference survey data among hard-to-reach groups: strategic application in international settings.

PubMed

Beletsky, Leo; Arredondo, Jaime; Werb, Dan; Vera, Alicia; Abramovitz, Daniela; Amon, Joseph J; Brouwer, Kimberly C; Strathdee, Steffanie A; Gaines, Tommi L

2016-07-28

As geospatial data have become increasingly integral to health and human rights research, their collection using formal address designations or paper maps has been complicated by numerous factors, including poor cartographic literacy, nomenclature imprecision, and human error. As part of a longitudinal study of people who inject drugs in Tijuana, Mexico, respondents were prompted to georeference specific experiences. At baseline, only about one third of the 737 participants were native to Tijuana, underscoring prevalence of migration/deportation experience. Areas frequented typically represented locations with no street address (e.g. informal encampments). Through web-based cartographic technology and participatory mapping, this study was able to overcome the use of vernacular names and difficulties mapping liminal spaces in generating georeferenced data points that were subsequently analyzed in other research. Integrating low-threshold virtual navigation as part of data collection can enhance investigations of mobile populations, informal settlements, and other locations in research into structural production of health at low- or no cost. However, further research into user experience is warranted.

Mapping for the masses: using free remote sensing data for disaster management

NASA Astrophysics Data System (ADS)

Teeuw, R.; McWilliam, N.; Morris, N.; Saunders, C.

2009-04-01

We examine the uses of free satellite imagery and Digital Elevation Models (DEMs) for disaster management, targeting three data sources: the United Nations Charter on Space and Disasters, Google Earth and internet-based satellite data archives, such as the Global Land Cover Facility (GLCF). The research has assessed SRTM and ASTER DEM data, Landsat TM/ETM+ and ASTER imagery, as well as utilising datasets and basic GIS operations available via Google Earth. As an aid to Disaster Risk Reduction, four sets of maps can be produced from satellite data: (i) Multiple Geohazards: areas prone to slope instability, coastal inundation and fluvial flooding; (ii) Vulnerability: population density, habitation types, land cover types and infrastructure; (iii) Disaster Risk: produced by combining severity scores from (i) and (ii); (iv) Reconstruction: zones of rock/sediment with construction uses; areas of woodland (for fuel/construction) water sources; transport routes; zones suitable for re-settlement. This set of Disaster Risk Reduction maps are ideal for regional (1:50,000 to 1:250,000 scale) planning for in low-income countries: more detailed assessments require relatively expensive high resolution satellite imagery or aerial photography, although Google Earth has a good track record for posting high-res imagery of disaster zones (e.g. the 2008 Burma storm surge). The Disaster Risk maps highlight areas of maximum risk to a region's emergency planners and decision makers, enabling various types of public education and other disaster mitigation measures. The Reconstruction map also helps to save lives, by facilitating disaster recovery. Many problems have been identified. Access to the UN Charter imagery is fine after a disaster, but very difficult if assessing pre-disaster indicators: the data supplied also tends to be pre-processed, when some relief agencies would prefer to have raw data. The limited and expensive internet access in many developing countries limits access to archives of free satellite data, such as the GLCF. Finally, data integration, spatial/temporal analysis and map production are all hindered by the high price of most GIS software, making the development of suitable open-source software a priority.

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

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

PubMed

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

2011-01-01

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

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

PubMed

Marek, Lukáš; Tuček, Pavel; Pászto, Vít

2015-01-28

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

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

NASA Astrophysics Data System (ADS)

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

2009-12-01

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

Use of Openly Available Satellite Images for Remote Sensing Education

NASA Astrophysics Data System (ADS)

Wang, C.-K.

2011-09-01

With the advent of Google Earth, Google Maps, and Microsoft Bing Maps, high resolution satellite imagery are becoming more easily accessible than ever. It have been the case that the college students may already have wealth experiences with the high resolution satellite imagery by using these software and web services prior to any formal remote sensing education. It is obvious that the remote sensing education should be adjusted to the fact that the audience are already the customers of remote sensing products (through the use of the above mentioned services). This paper reports the use of openly available satellite imagery in an introductory-level remote sensing course in the Department of Geomatics of National Cheng Kung University as a term project. From the experience learned from the fall of 2009 and 2010, it shows that this term project has effectively aroused the students' enthusiastic toward Remote Sensing.

Recent Development of an Earth Science App - FieldMove Clino

NASA Astrophysics Data System (ADS)

Vaughan, Alan; Collins, Nathan; Krus, Mike; Rourke, Peter

2014-05-01

As geological modelling and analysis move into 3D digital space, it becomes increasingly important to be able to rapidly integrate new data with existing databases, without the potential degradation caused by repeated manual transcription of numeric, graphical and meta-data. Digital field mapping offers significant benefits when compared with traditional paper mapping techniques, in that it can directly and interactively feed and be guided by downstream geological modelling and analysis. One of the most important pieces of equipment used by the field geologists is the compass clinometer. Midland Valley's development team have recently release their highly anticipated FieldMove Clino App. FieldMove Clino is a digital compass-clinometer for data capture on a smartphone. The app allows the user to use their phone as a traditional hand-held bearing compass, as well as a digital compass-clinometer for rapidly measuring and capturing the georeferenced location and orientation of planar and linear features in the field. The user can also capture and store digital photographs and text notes. FieldMove Clino supports online Google Maps as well as offline maps, so that the user can import their own georeferenced basemaps. Data can be exported as comma-separated values (.csv) or Move™ (.mve) files and then imported directly into FieldMove™, Move™ or other applications. Midland Valley is currently pioneering tablet-based mapping and, along with its industrial and academic partners, will be using the application in field based projects throughout this year and will be integrating feedback in further developments of this technology.

Pulse oximeter for cyclists in smartphone

NASA Astrophysics Data System (ADS)

Martins, L.; Gaidos, O.; dos Santos, I.

2015-01-01

The monitoring of cyclists during physical activity is an important factor to improve their performance. We discuss a new approaches based on smartphone for monitoring physiological signal wirelessly for cyclists, using a pulse oximeter sensor attached to the rider's forehead. This paper presents a wireless pulse Oximeter that was developed with a Nellcor's module, which uses the Standard Host Interface Protocol (SHIP) for communication with the Bluetooth module and sends data for a Smartphone with Android O.S. Then these data are shown in the screen: the heartbeat and saturation percentage. The application was created with App Inventor and the data are sent to Google Maps via Twitter. The results demonstrate the possibility of developing a successful prototype.

Oyster Fisheries App

NASA Technical Reports Server (NTRS)

Perez Guerrero, Geraldo A.; Armstrong, Duane; Underwood, Lauren

2015-01-01

This project is creating a cloud-enabled, HTML 5 web application to help oyster fishermen and state agencies apply Earth science to improve the management of this important natural and economic resource. The Oyster Fisheries app gathers and analyzes environmental and water quality information, and alerts fishermen and resources managers about problems in oyster fishing waters. An intuitive interface based on Google Maps displays the geospatial information and provides familiar interactive controls to the users. Alerts can be tailored to notify users when conditions in specific leases or public fishing areas require attention. The app is hosted on the Amazon Web Services cloud. It is being developed and tested using some of the latest web development tools such as web components and Polymer.

USGS Coastal and Marine Geology Survey Data in Google Earth

NASA Astrophysics Data System (ADS)

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

2006-12-01

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

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.

Mapping of traditional settlements by unmanned airborne vehicles towards architectural restoration

NASA Astrophysics Data System (ADS)

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

2015-06-01

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

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.

Mars @ ASDC

NASA Astrophysics Data System (ADS)

Carraro, Francesco

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

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

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

PubMed

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

2014-08-01

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

Timely Reporting and Interactive Visualization of Animal Health and Slaughterhouse Surveillance Data in Switzerland.

PubMed

Muellner, Ulrich J; Vial, Flavie; Wohlfender, Franziska; Hadorn, Daniela; Reist, Martin; Muellner, Petra

2015-01-01

The reporting of outputs from health surveillance systems should be done in a near real-time and interactive manner in order to provide decision makers with powerful means to identify, assess, and manage health hazards as early and efficiently as possible. While this is currently rarely the case in veterinary public health surveillance, reporting tools do exist for the visual exploration and interactive interrogation of health data. In this work, we used tools freely available from the Google Maps and Charts library to develop a web application reporting health-related data derived from slaughterhouse surveillance and from a newly established web-based equine surveillance system in Switzerland. Both sets of tools allowed entry-level usage without or with minimal programing skills while being flexible enough to cater for more complex scenarios for users with greater programing skills. In particular, interfaces linking statistical softwares and Google tools provide additional analytical functionality (such as algorithms for the detection of unusually high case occurrences) for inclusion in the reporting process. We show that such powerful approaches could improve timely dissemination and communication of technical information to decision makers and other stakeholders and could foster the early-warning capacity of animal health surveillance systems.

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.

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.

There's An App For That: Planning Ahead for the Solar Eclipse in August 2017

NASA Astrophysics Data System (ADS)

Chizek Frouard, Malynda R.; Lesniak, Michael V.; Bell, Steve

2017-01-01

With the total solar eclipse of 2017 August 21 over the continental United States approaching, the U.S. Naval Observatory (USNO) on-line Solar Eclipse Computer can now be accessed via an Android application, available on Google Play.Over the course of the eclipse, as viewed from a specific site, several events may be visible: the beginning and ending of the eclipse (first and fourth contacts), the beginning and ending of totality (second and third contacts), the moment of maximum eclipse, sunrise, or sunset. For each of these events, the USNO Solar Eclipse 2017 Android application reports the time, Sun's altitude and azimuth, and the event's position and vertex angles. The app also lists the duration of the total phase, the duration of the eclipse, the magnitude of the eclipse, and the percent of the Sun obscured for a particular eclipse site.All of the data available in the app comes from the flexible USNO Solar Eclipse Computer Application Programming Interface (API), which produces JavaScript Object Notation (JSON) that can be incorporated into third-party Web sites or custom applications. Additional information is available in the on-line documentation (http://aa.usno.navy.mil/data/docs/api.php).For those who prefer using a traditional data input form, the local circumstances can still be requested at http://aa.usno.navy.mil/data/docs/SolarEclipses.php.In addition the 2017 August 21 Solar Eclipse Resource page (http://aa.usno.navy.mil/data/docs/Eclipse2017.php) consolidates all of the USNO resources for this event, including a Google Map view of the eclipse track designed by Her Majesty's Nautical Almanac Office (HMNAO).Looking further ahead, a 2024 April 8 Solar Eclipse Resource page (http://aa.usno.navy.mil/data/docs/Eclipse2024.php) is also available.

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.

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

NASA Astrophysics Data System (ADS)

Manaud, Nicolas; Carter, John; Boix, Oriol

2016-10-01

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

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.

National Geothermal Data System: Open Access to Geoscience Data, Maps, and Documents

NASA Astrophysics Data System (ADS)

Caudill, C. M.; Richard, S. M.; Musil, L.; Sonnenschein, A.; Good, J.

2014-12-01

The U.S. National Geothermal Data System (NGDS) provides free open access to millions of geoscience data records, publications, maps, and reports via distributed web services to propel geothermal research, development, and production. NGDS is built on the US Geoscience Information Network (USGIN) data integration framework, which is a joint undertaking of the USGS and the Association of American State Geologists (AASG), and is compliant with international standards and protocols. NGDS currently serves geoscience information from 60+ data providers in all 50 states. Free and open source software is used in this federated system where data owners maintain control of their data. This interactive online system makes geoscience data easily discoverable, accessible, and interoperable at no cost to users. The dynamic project site http://geothermaldata.org serves as the information source and gateway to the system, allowing data and applications discovery and availability of the system's data feed. It also provides access to NGDS specifications and the free and open source code base (on GitHub), a map-centric and library style search interface, other software applications utilizing NGDS services, NGDS tutorials (via YouTube and USGIN site), and user-created tools and scripts. The user-friendly map-centric web-based application has been created to support finding, visualizing, mapping, and acquisition of data based on topic, location, time, provider, or key words. Geographic datasets visualized through the map interface also allow users to inspect the details of individual GIS data points (e.g. wells, geologic units, etc.). In addition, the interface provides the information necessary for users to access the GIS data from third party software applications such as GoogleEarth, UDig, and ArcGIS. A redistributable, free and open source software package called GINstack (USGIN software stack) was also created to give data providers a simple way to release data using interoperable and shareable standards, upload data and documents, and expose those data as a node in the NGDS or any larger data system through a CSW endpoint. The easy-to-use interface is supported by back-end software including Postgres, GeoServer, and custom CKAN extensions among others.

Landsat Based Woody Vegetation Loss Detection in Queensland, Australia Using the Google Earth Engine

NASA Astrophysics Data System (ADS)

Johansen, K.; Phinn, S. R.; Taylor, M.

2014-12-01

Land clearing detection and woody Foliage Projective Cover (FPC) monitoring at the state and national level in Australia has mainly been undertaken by state governments and the Terrestrial Ecosystem Research Network (TERN) because of the considerable expense, expertise, sustained duration of activities and staffing levels needed. Only recently have services become available, providing low budget, generalized access to change detection tools suited to this task. The objective of this research was to examine if a globally available service, Google Earth Engine Beta, could be used to predict woody vegetation loss with accuracies approaching the methods used by TERN and the government of the state of Queensland, Australia. Two change detection approaches were investigated using Landsat Thematic Mapper time series and the Google Earth Engine Application Programming Interface: (1) CART and Random Forest classifiers; and (2) a normalized time series of Foliage Projective Cover (FPC) and NDVI combined with a spectral index. The CART and Random Forest classifiers produced high user's and producer's mapping accuracies of clearing (77-92% and 54-77%, respectively) when detecting change within epochs for which training data were available, but extrapolation to epochs without training data reduced the mapping accuracies. The use of FPC and NDVI time series provided a more robust approach for calculation of a clearing probability, as it did not rely on training data but instead on the difference of the normalized FPC / NDVI mean and standard deviation of a single year at the change point in relation to the remaining time series. However, the FPC and NDVI time series approach represented a trade-off between user's and producer's accuracies. Both change detection approaches explored in this research were sensitive to ephemeral greening and drying of the landscape. However, the developed normalized FPC and NDVI time series approach can be tuned to provide automated alerts for large woody vegetation clearing events by selecting suitable thresholds to identify very likely clearing. This research provides a comprehensive foundation to build further capacity to use globally accessible, free, online image datasets and processing tools to accurately detect woody vegetation clearing in an automated and rapid manner.

Global Analysis of River Planform Change using the Google Earth Engine

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Measuring Neighborhood Walkable Environments: A Comparison of Three Approaches

PubMed Central

Chiang, Yen-Cheng; Sullivan, William; Larsen, Linda

2017-01-01

Multiple studies have revealed the impact of walkable environments on physical activity. Scholars attach considerable importance to leisure and health-related walking. Recent studies have used Google Street View as an instrument to assess city streets and walkable environments; however, no study has compared the validity of Google Street View assessments of walkable environment attributes to assessments made by local residents and compiled from field visits. In this study, we involved nearby residents and compared the extent to which Google Street View assessments of the walkable environment correlated with assessments from local residents and with field visits. We determined the assessment approaches (local resident or field visit assessments) that exhibited the highest agreement with Google Street View. One city with relatively high-quality walkable environments and one city with relatively low-quality walkable environments were examined, and three neighborhoods from each city were surveyed. Participants in each neighborhood used one of three approaches to assess the walkability of the environment: 15 local residents assessed the environment using a map, 15 participants made a field visit to assess the environment, and 15 participants used Google Street View to assess the environment, yielding a total of 90 valid samples for the two cities. Findings revealed that the three approaches to assessing neighborhood walkability were highly correlated for traffic safety, aesthetics, sidewalk quality, and physical barriers. Compared with assessments from participants making field visits, assessments by local residents were more highly correlated with Google Street View assessments. Google Street View provides a more convenient, low-cost, efficient, and safe approach to assess neighborhood walkability. The results of this study may facilitate future large-scale walkable environment surveys, effectively reduce expenses, and improve survey efficiency. PMID:28587186

Assessing the environmental characteristics of cycling routes to school: a study on the reliability and validity of a Google Street View-based audit.

PubMed

Vanwolleghem, Griet; Van Dyck, Delfien; Ducheyne, Fabian; De Bourdeaudhuij, Ilse; Cardon, Greet

2014-06-10

Google Street View provides a valuable and efficient alternative to observe the physical environment compared to on-site fieldwork. However, studies on the use, reliability and validity of Google Street View in a cycling-to-school context are lacking. We aimed to study the intra-, inter-rater reliability and criterion validity of EGA-Cycling (Environmental Google Street View Based Audit - Cycling to school), a newly developed audit using Google Street View to assess the physical environment along cycling routes to school. Parents (n = 52) of 11-to-12-year old Flemish children, who mostly cycled to school, completed a questionnaire and identified their child's cycling route to school on a street map. Fifty cycling routes of 11-to-12-year olds were identified and physical environmental characteristics along the identified routes were rated with EGA-Cycling (5 subscales; 37 items), based on Google Street View. To assess reliability, two researchers performed the audit. Criterion validity of the audit was examined by comparing the ratings based on Google Street View with ratings through on-site assessments. Intra-rater reliability was high (kappa range 0.47-1.00). Large variations in the inter-rater reliability (kappa range -0.03-1.00) and criterion validity scores (kappa range -0.06-1.00) were reported, with acceptable inter-rater reliability values for 43% of all items and acceptable criterion validity for 54% of all items. EGA-Cycling can be used to assess physical environmental characteristics along cycling routes to school. However, to assess the micro-environment specifically related to cycling, on-site assessments have to be added.

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

NASA Technical Reports Server (NTRS)

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

2017-01-01

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

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

PubMed Central

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

2011-01-01

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

A web-based screening tool for near-port air quality assessments

PubMed Central

Isakov, Vlad; Barzyk, Timothy M.; Smith, Elizabeth R.; Arunachalam, Saravanan; Naess, Brian; Venkatram, Akula

2018-01-01

The Community model for near-PORT applications (C-PORT) is a screening tool with an intended purpose of calculating differences in annual averaged concentration patterns and relative contributions of various source categories over the spatial domain within about 10 km of the port. C-PORT can inform decision-makers and concerned citizens about local air quality due to mobile source emissions related to commercial port activities. It allows users to visualize and evaluate different planning scenarios, helping them identify the best alternatives for making long-term decisions that protect community health and sustainability. The web-based, easy-to-use interface currently includes data from 21 seaports primarily in the Southeastern U.S., and has a map-based interface based on Google Maps. The tool was developed to visualize and assess changes in air quality due to changes in emissions and/or meteorology in order to analyze development scenarios, and is not intended to support or replace any regulatory models or programs. PMID:29681760

Robust, Efficient Depth Reconstruction With Hierarchical Confidence-Based Matching.

PubMed

Sun, Li; Chen, Ke; Song, Mingli; Tao, Dacheng; Chen, Gang; Chen, Chun

2017-07-01

In recent years, taking photos and capturing videos with mobile devices have become increasingly popular. Emerging applications based on the depth reconstruction technique have been developed, such as Google lens blur. However, depth reconstruction is difficult due to occlusions, non-diffuse surfaces, repetitive patterns, and textureless surfaces, and it has become more difficult due to the unstable image quality and uncontrolled scene condition in the mobile setting. In this paper, we present a novel hierarchical framework with multi-view confidence-based matching for robust, efficient depth reconstruction in uncontrolled scenes. Particularly, the proposed framework combines local cost aggregation with global cost optimization in a complementary manner that increases efficiency and accuracy. A depth map is efficiently obtained in a coarse-to-fine manner by using an image pyramid. Moreover, confidence maps are computed to robustly fuse multi-view matching cues, and to constrain the stereo matching on a finer scale. The proposed framework has been evaluated with challenging indoor and outdoor scenes, and has achieved robust and efficient depth reconstruction.

Usability evaluation of cloud-based mapping tools for the display of very large datasets

NASA Astrophysics Data System (ADS)

Stotz, Nicole Marie

The elasticity and on-demand nature of cloud services have made it easier to create web maps. Users only need access to a web browser and the Internet to utilize cloud based web maps, eliminating the need for specialized software. To encourage a wide variety of users, a map must be well designed; usability is a very important concept in designing a web map. Fusion Tables, a new product from Google, is one example of newer cloud-based distributed GIS services. It allows for easy spatial data manipulation and visualization, within the Google Maps framework. ESRI has also introduced a cloud based version of their software, called ArcGIS Online, built on Amazon's EC2 cloud. Utilizing a user-centered design framework, two prototype maps were created with data from the San Diego East County Economic Development Council. One map was built on Fusion Tables, and another on ESRI's ArcGIS Online. A usability analysis was conducted and used to compare both map prototypes in term so of design and functionality. Load tests were also ran, and performance metrics gathered on both map prototypes. The usability analysis was taken by 25 geography students, and consisted of time based tasks and questions on map design and functionality. Survey participants completed the time based tasks for the Fusion Tables map prototype quicker than those of the ArcGIS Online map prototype. While response was generally positive towards the design and functionality of both prototypes, overall the Fusion Tables map prototype was preferred. For the load tests, the data set was broken into 22 groups for a total of 44 tests. While the Fusion Tables map prototype performed more efficiently than the ArcGIS Online prototype, differences are almost unnoticeable. A SWOT analysis was conducted for each prototype. The results from this research point to the Fusion Tables map prototype. A redesign of this prototype would incorporate design suggestions from the usability survey, while some functionality would need to be dropped. This is a free product and would therefore be the best option if cost is an issue, but this map may not be supported in the future.

DistMap: a toolkit for distributed short read mapping on a Hadoop cluster.

PubMed

Pandey, Ram Vinay; Schlötterer, Christian

2013-01-01

With the rapid and steady increase of next generation sequencing data output, the mapping of short reads has become a major data analysis bottleneck. On a single computer, it can take several days to map the vast quantity of reads produced from a single Illumina HiSeq lane. In an attempt to ameliorate this bottleneck we present a new tool, DistMap - a modular, scalable and integrated workflow to map reads in the Hadoop distributed computing framework. DistMap is easy to use, currently supports nine different short read mapping tools and can be run on all Unix-based operating systems. It accepts reads in FASTQ format as input and provides mapped reads in a SAM/BAM format. DistMap supports both paired-end and single-end reads thereby allowing the mapping of read data produced by different sequencing platforms. DistMap is available from http://code.google.com/p/distmap/

DistMap: A Toolkit for Distributed Short Read Mapping on a Hadoop Cluster

PubMed Central

Pandey, Ram Vinay; Schlötterer, Christian

2013-01-01

With the rapid and steady increase of next generation sequencing data output, the mapping of short reads has become a major data analysis bottleneck. On a single computer, it can take several days to map the vast quantity of reads produced from a single Illumina HiSeq lane. In an attempt to ameliorate this bottleneck we present a new tool, DistMap - a modular, scalable and integrated workflow to map reads in the Hadoop distributed computing framework. DistMap is easy to use, currently supports nine different short read mapping tools and can be run on all Unix-based operating systems. It accepts reads in FASTQ format as input and provides mapped reads in a SAM/BAM format. DistMap supports both paired-end and single-end reads thereby allowing the mapping of read data produced by different sequencing platforms. DistMap is available from http://code.google.com/p/distmap/ PMID:24009693

Cropland Capture: A Game to Improve Global Cropland through Crowdsourcing

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Panoramic Images Mapping Tools Integrated Within the ESRI ArcGIS Software

NASA Astrophysics Data System (ADS)

Guo, Jiao; Zhong, Ruofei; Zeng, Fanyang

2014-03-01

There is a general study on panoramic images which are presented along with appearance of the Google street map. Despite 360 degree viewing of street, we can realize more applications over panoramic images. This paper developed a toolkits plugged in ArcGIS, which can view panoramic photographs at street level directly from ArcMap and measure and capture all visible elements as frontages, trees and bridges. We use a series of panoramic images adjoined with absolute coordinate through GPS and IMU. There are two methods in this paper to measure object from these panoramic images: one is to intersect object position through a stereogram; the other one is multichip matching involved more than three images which all cover the object. While someone wants to measure objects from these panoramic images, each two panoramic images which both contain the object can be chosen to display on ArcMap. Then we calculate correlation coefficient of the two chosen panoramic images so as to calculate the coordinate of object. Our study test different patterns of panoramic pairs and compare the results of measurement to the real value of objects so as to offer the best choosing suggestion. The article has mainly elaborated the principles of calculating correlation coefficient and multichip matching.

Large Scale Crop Mapping in Ukraine Using Google Earth Engine

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Destination Information System for Bandung City Using Location-Based Services (LBS) on Android

NASA Astrophysics Data System (ADS)

Kurniawan, B.; Pranoto, H.

2018-02-01

Bandung is a city in West Java, Indonesia with many interesting locations to visit. For most favourite destinations, we can easily look for it on Google and we will find some blogs there discussing about related content. The problem is we can not guarantee that the destination is frequented by visitor. In this research, we utilizes an application to help everyone choosing destination frequented by visitor. The use of information technology in the form of picture, maps, and textual on Android application makes it possible for user to have information about destination with its visitor in a period of time. If destination has visit history, selection of proper destination will be given with fresh informations. This application can run well on Android Lollipop (API Level 21) or above with a minimum RAM of 2 GB since it will compare two coordinates for every data. The use of this app make it possible to access information about location with its visitor history and could help choosing proper destinations for the users.

Results of Prospecting of Impact Craters in Morocco

NASA Astrophysics Data System (ADS)

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

2014-09-01

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

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

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Mashup Scheme Design of Map Tiles Using Lightweight Open Source Webgis Platform

NASA Astrophysics Data System (ADS)

Hu, T.; Fan, J.; He, H.; Qin, L.; Li, G.

2018-04-01

To address the difficulty involved when using existing commercial Geographic Information System platforms to integrate multi-source image data fusion, this research proposes the loading of multi-source local tile data based on CesiumJS and examines the tile data organization mechanisms and spatial reference differences of the CesiumJS platform, as well as various tile data sources, such as Google maps, Map World, and Bing maps. Two types of tile data loading schemes have been designed for the mashup of tiles, the single data source loading scheme and the multi-data source loading scheme. The multi-sources of digital map tiles used in this paper cover two different but mainstream spatial references, the WGS84 coordinate system and the Web Mercator coordinate system. According to the experimental results, the single data source loading scheme and the multi-data source loading scheme with the same spatial coordinate system showed favorable visualization effects; however, the multi-data source loading scheme was prone to lead to tile image deformation when loading multi-source tile data with different spatial references. The resulting method provides a low cost and highly flexible solution for small and medium-scale GIS programs and has a certain potential for practical application values. The problem of deformation during the transition of different spatial references is an important topic for further research.

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

PubMed Central

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

2009-01-01

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

Geonucleus, the freeware application for managing geological mapping data in GIS

NASA Astrophysics Data System (ADS)

Albert, Gáspár

2016-04-01

Geological mapping is the most traditional way of collecting information from the deposits and rocks. The traditional technique of the documentation was refined by generations of geologists. These traditions were implemented into Geonucleus to create a tool for precise data-recording after fieldwork, but giving the freedom of pondering the details of the observation as well. In 2012 a general xml-based data structure was worked out for storing field observations for the Geological Institute of Hungary (Albert et al. 2012). This structure was implemented into the desktop version of Geonucleus, which creates a database of the recorded data on the client computer. The application saves the complete database in one file, which can be loaded into a GIS. The observations can be saved in simple text format as well, but primarily the kml (Keyhole Markup Languege) is supported. This way, the observations are visualized in comprehensible forms (e.g. on a 3D surface model with satellite photos in Google Earth). If the kml is directly visualized in Google Earth, an info-bubble will appear via clicking on a pinpoint. It displays all the metadata (e.g. index, coordinates, date, logger name, etc.), the descriptions and the photos of the observed site. If a more general GIS application is the aim (e.g. Global Mapper or QGIS), the file can be saved in a different format, but still in a kml-structure. The simple text format is recommended if the observations are to be imported in a user-defined relational database system (RDB). Report text-type is also available if a detailed description of one or more observed site is needed. Importing waypoint gpx-files can quicken the logging. The code was written in VisualBasic.Net. The app is freely accessible from the geonucleus.elte.hu site and it can be installed on any system, which has the .Net framework 4.0 or higher. The software is bilingual (English and Hungarian), and the app is designed for general geological mapping purposes (e.g. quick logging of field trips). The layout of the GUI has three components: 1) metadata area, 2) general description area with unlimited storing capacity, 3) switchable panels for observations, measurements, photos and notes. The latter includes panels for stratigraphy, structures, fossils, samples, photo uploads and general notes. Details like the sequence and contact type of layers, the parameters of structures and slickensides, name and condition of fossils and purpose of sampling are also available to log (but not compulsorily). It is also a tool for teaching geological mapping, since the available parameters - listed in the app - draws attention to the details, which are to be observed on the field. Reference: Albert G, Csillag G, Fodor L, Zentai L. 2012: Visualisation of Geological Observations on Web 2.0 Based Maps, in: Zentai, L. and Reyes-Nunez, J (eds.): Maps for the Future - Children, Education and Internet, Series: Lecture Notes in Geoinformation and Cartography, Tentative volume 5 - Springer, pp. 165-178.

Satellite Radar Detects Damage from Sept. 19, 2017 Raboso, Mexico, Quake

NASA Image and Video Library

2017-09-20

The Advanced Rapid Imaging and Analysis (ARIA) team at NASA's Jet Propulsion Laboratory in Pasadena, California, and Caltech, also in Pasadena, created this Damage Proxy Map (DPM) depicting areas of Central Mexico, including Mexico City, that are likely damaged (shown by red and yellow pixels) from the magnitude 7.1 Raboso earthquake of Sept. 19, 2017 (local time). The map is derived from synthetic aperture radar (SAR) images from the Copernicus Sentinel-1A and Sentinel-1B satellites, operated by the European Space Agency (ESA). The images were taken before (Sept. 8, 2017) and after (Sept. 20, 2017) the earthquake. The map covers an area of 109 by 106 miles (175 by 170 kilometers). Each pixel measures about 33 yards (30 meters) across. The color variation from yellow to red indicates increasingly more significant ground and building surface change. Preliminary validation was done by comparing the DPM to a crowd-sourced Google Map (https://www.google.com/maps/d/u/0/viewer?mid=1_-V97lbdgLFHpx-CtqhLWlJAnYY&ll=19.41452166501326%2C-99.16498240436704&z=16). This damage proxy map should be used as guidance to identify damaged areas, and may be less reliable over vegetated areas. Sentinel-1 data were accessed through the Copernicus Open Access Hub. The image contains modified Copernicus Sentinel data (2017), processed by ESA and analyzed by the NASA-JPL/Caltech ARIA team. This research was carried out at JPL under contract with NASA. https://photojournal.jpl.nasa.gov/catalog/PIA21963

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.

Web based tools for data manipulation, visualisation and validation with interactive georeferenced graphs

NASA Astrophysics Data System (ADS)

Ivankovic, D.; Dadic, V.

2009-04-01

Some of oceanographic parameters have to be manually inserted into database; some (for example data from CTD probe) are inserted from various files. All this parameters requires visualization, validation and manipulation from research vessel or scientific institution, and also public presentation. For these purposes is developed web based system, containing dynamic sql procedures and java applets. Technology background is Oracle 10g relational database, and Oracle application server. Web interfaces are developed using PL/SQL stored database procedures (mod PL/SQL). Additional parts for data visualization include use of Java applets and JavaScript. Mapping tool is Google maps API (javascript) and as alternative java applet. Graph is realized as dynamically generated web page containing java applet. Mapping tool and graph are georeferenced. That means that click on some part of graph, automatically initiate zoom or marker onto location where parameter was measured. This feature is very useful for data validation. Code for data manipulation and visualization are partially realized with dynamic SQL and that allow as to separate data definition and code for data manipulation. Adding new parameter in system requires only data definition and description without programming interface for this kind of data.

JournalMap: Geo-semantic searching for relevant knowledge

USDA-ARS?s Scientific Manuscript database

Ecologists struggling to understand rapidly changing environments and evolving ecosystem threats need quick access to relevant research and documentation of natural systems. The advent of semantic and aggregation searching (e.g., Google Scholar, Web of Science) has made it easier to find useful lite...

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.

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…

Researchermap: a tool for visualizing author locations using Google maps.

PubMed

Rastegar-Mojarad, Majid; Bales, Michael E; Yu, Hong

2013-01-01

We hereby present ResearcherMap, a tool to visualize locations of authors of scholarly papers. In response to a query, the system returns a map of author locations. To develop the system we first populated a database of author locations, geocoding institution locations for all available institutional affiliation data in our database. The database includes all authors of Medline papers from 1990 to 2012. We conducted a formative heuristic usability evaluation of the system and measured the system's accuracy and performance. The accuracy of finding the accurate address is 97.5% in our system.

Detecting Runtime Anomalies in AJAX Applications through Trace Analysis

DTIC Science & Technology

2011-08-10

statements by adding the instrumentation to the GWT UI classes, leaving the user code untouched. Some content management frameworks such as Drupal [12...Google web toolkit.” http://code.google.com/webtoolkit/. [12] “Form generation – drupal api.” http://api.drupal.org/api/group/form_api/6. 9

An Information Infrastructure for Coastal Models and Data

NASA Astrophysics Data System (ADS)

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

2007-12-01

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

Fluvial ecosystem services in the Rhine delta distributaries between 1995 and 2035

NASA Astrophysics Data System (ADS)

Straatsma, Menno; Kleinhans, Maarten

2016-04-01

Mapping of ecosystem services (ES) and documenting their change over time provides important information for the societal debate and decision making on river management. Large and Gilvear (2014) showed how to score fluvial ES using imagery and tools available through Google Earth, linking observable features, or landcover to ES through inferred fluvial processes, and natural ecosystem functions. While the use of Google Earth enables application anywhere on the globe, their method is labor intensive, and involves subjective judgement as not all parameters are easily observable in spectral data, e.g. the location of embankments. In addition, the method does not take advantage of readily available spatial databases, and existing hydrodynamic model parameterizations, nor can it be used in scenario studies of future fluvial landscapes. Therefore, we aimed at the development of a generic GIS routine to extract the ecosystem services from existing spatial and hydrodynamic model data, and its application to historic and future fluvial landscapes in the Rhine delta. Here, we consider the Rhine distributaries, sized 400 km2, where river restoration measures were carried out between 1995 and 2015 to reduce flood risk reduction and simultaneously improve the ecological status. We computed ES scores for provisioning ES (fisheries, agriculture, timber, water supply), regulating ES (flood mitigation, carbon sequestration, water quality), and supporting ES (biodiversity). Historic ES were derived for the years 1997, 2005, and 2012, based on ecotope maps for these respective years, combined with a water levels and flow velocities derived from a calibrated 2D hydrodynamic model (WAQUA). Ecotopes are defined as 'spatial landscape units that are homogeneous as to vegetation structure, succession stage, and the main abiotic factors that are relevant to plant growth'. ES for 2035 were based on scenarios of landscaping measures. Suitable locations for the measures were determined automatically using map algebra, scripted in PCRaster-Python, with existing spatial data as input. Each scenario provided an updated ecotope map and bathymetry for the whole study area. Biodiversity indices were computed for all species that are protected by policy and legal documents using the BIOSAFE model, which was adapted for automated mapping. BIOSAFE links 614 protected species in seven taxonomic to 82 ecotope classes. Over the historic period, the ES increased, especially the biodiversity scores of birds and mammals improved by more than 10% due to the restoration measures. One of the main drivers is the creation of new side channels, and allowing natural succession to occur to a limited extent. For the future, the scenarios showed that the overall ES score varied strongly with the type of measure chosen. Floodplain smoothing and lowering negatively impacted ES, whereas embankment relocation, and side channels increased ES scores. We conclude that the automated methods provide fast insights in the historic and future developments of fluvial ES. This is useful for the decision making and natural capital mapping, but we require increased precision in defining fluvial ES, and additional quantification and validation of the methods.

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

NASA Technical Reports Server (NTRS)

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

2012-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2009-12-01

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

Data Visualization of Lunar Orbiter KAGUYA (SELENE) using web-based GIS

NASA Astrophysics Data System (ADS)

Okumura, H.; Sobue, S.; Yamamoto, A.; Fujita, T.

2008-12-01

The Japanese Lunar Orbiter KAGUYA (SELENE) was launched on Sep.14 2007, and started nominal observation from Dec. 21 2007. KAGUYA has 15 ongoing observation missions and is obtaining various physical quantity data of the moon such as elemental abundance, mineralogical composition, geological feature, magnetic field and gravity field. We are working on the visualization of these data and the application of them to web-based GIS. Our purpose of data visualization is the promotion of science and education and public outreach (EPO). As for scientific usage and public outreach, we already constructed KAGUYA Web Map Server (WMS) at JAXA Sagamihara Campus and began to test it among internal KAGUYA project. KAGUYA science team plans the integrated science using the data of multiple instruments with the aim of obtaining the new findings of the origin and the evolution of the moon. In the study of the integrated science, scientists have to access, compare and analyze various types of data with different resolution. Web-based GIS will allow users to map, overlay and share the data and information easily. So it will be the best way to progress such a study and we are developing the KAGUYA WMS as a platform of the KAGUYA integrated science. For the purpose of EPO, we are customizing NASA World Wind (NWW) JAVA for KAGUYA supported by NWW project. Users will be able to search and view many images and movies of KAGUYA on NWW JAVA in the easy and attractive way. In addition, we are considering applying KAGUYA images to Google Moon with KML format and adding KAGUYA movies to Google/YouTube.

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 94 articles with medical photographs of trans participants, including a total of 605 photographs. Of the 94 publications, 35 (37%) included at least one medical photograph that was found on Google Images. The ability to locate the article freely online contributes to the availability of at least one image from the article on Google Images (OR 2.99, 95% CI 1.20-7.45). Conclusions This is the first study to document the existence of medical photographs from peer-reviewed journals appearing in Google Images search results. Almost all of the images we searched for included sensitive photographs of patient genitals, chests, or breasts. Given that it is unlikely that patients consented to sharing their personal health information in these ways, this constitutes a risk to patient privacy. Based on the impact of current practices, revisions to informed consent policies and guidelines are required. PMID:29483069

Transport Statistics - Transport - UNECE

Science.gov Websites

Statistics and Data Online Infocards Database SDG Papers E-Road Census Traffic Census Map Traffic Census 2015 available. Two new datasets have been added to the transport statistics database: bus and coach statistics Database Evaluations Follow UNECE Facebook Rss Twitter You tube Contact us Instagram Flickr Google+ Â

An Automated Approach to Extracting River Bank Locations from Aerial Imagery Using Image Texture

DTIC Science & Technology

2013-01-01

Atchafalaya River, LA. Map Data: Google, United States Department of Agriculture Farm Ser- vice Agency, Europa Technologies AUTOMATED RIVER BANK...traverse morphologically smooth landscapes including rivers in sand or ice . Within these limitations, we hold that this technique rep- resents a valuable

Children Creating Multimodal Stories about a Familiar Environment

ERIC Educational Resources Information Center

Kervin, Lisa; Mantei, Jessica

2017-01-01

Storytelling is a practice that enables children to apply their literacy skills. This article shares a collaborative literacy strategy devised to enable children to create multimodal stories about their familiar school environment. The strategy uses resources, including the children's own drawings, images from Google Maps, and the Puppet Pals…

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

ERIC Educational Resources Information Center

Karatepe, Akif

2012-01-01

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

Gaga for Google in the Twenty-First Century Advanced Placement Language Classroom

ERIC Educational Resources Information Center

Adams, Devon Christopher

2008-01-01

The migration of online educational needs to tools like Google applications, coupled with the realization that today's twenty-first-century students are digital natives who have lived their entire lives exposed to current technology, forces educators to find ways to use technology to enhance traditional curriculum. In this article, the author…

Problem solving in magnetic field: Animation in mobile application

NASA Astrophysics Data System (ADS)

Najib, A. S. M.; Othman, A. P.; Ibarahim, Z.

2014-09-01

This paper is focused on the development of mobile application for smart phone, Android, tablet, iPhone, and iPad as a problem solving tool in magnetic field. Mobile application designs consist of animations that were created by using Flash8 software which could be imported and compiled to prezi.com software slide. The Prezi slide then had been duplicated in Power Point format and instead question bank with complete answer scheme was also additionally generated as a menu in the application. Results of the published mobile application can be viewed and downloaded at Infinite Monkey website or at Google Play Store from your gadgets. Statistics of the application from Google Play Developer Console shows the high impact of the application usage in all over the world.

Interactive web-based mapping: bridging technology and data for health.

PubMed

Highfield, Linda; Arthasarnprasit, Jutas; Ottenweller, Cecelia A; Dasprez, Arnaud

2011-12-23

The Community Health Information System (CHIS) online mapping system was first launched in 1998. Its overarching goal was to provide researchers, residents and organizations access to health related data reflecting the overall health and well-being of their communities within the Greater Houston area. In September 2009, initial planning and development began for the next generation of CHIS. The overarching goal for the new version remained to make health data easily accessible for a wide variety of research audiences. However, in the new version we specifically sought to make the CHIS truly interactive and give the user more control over data selection and reporting. In July 2011, a beta version of the next-generation of the application was launched. This next-generation is also a web based interactive mapping tool comprised of two distinct portals: the Breast Health Portal and Project Safety Net. Both are accessed via a Google mapping interface. Geographic coverage for the portals is currently an 8 county region centered on Harris County, Texas. Data accessed by the application include Census 2000, Census 2010 (underway), cancer incidence from the Texas Cancer Registry (TX Dept. of State Health Services), death data from Texas Vital Statistics, clinic locations for free and low-cost health services, along with service lists, hours of operation, payment options and languages spoken, uninsured and poverty data. The system features query on the fly technology, which means the data is not generated until the query is provided to the system. This allows users to interact in real-time with the databases and generate customized reports and maps. To the author's knowledge, the Breast Health Portal and Project Safety Net are the first local-scale interactive online mapping interfaces for public health data which allow users to control the data generated. For example, users may generate breast cancer incidence rates by Census tract, in real time, for women aged 40-64. Conversely, they could then generate the same rates for women aged 35-55. The queries are user controlled.

Access High Quality Imagery from the NOAA View Portal

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

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

NASA Astrophysics Data System (ADS)

Kim, H.

2013-12-01

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

Understanding Urban Watersheds through Digital Interactive Maps, San Francisco Bay Area, California

NASA Astrophysics Data System (ADS)

Sowers, J. M.; Ticci, M. G.; Mulvey, P.

2014-12-01

Dense urbanization has resulted in the "disappearance" of many local creeks in urbanized areas surrounding the San Francisco Bay. Long reaches of creeks now flow in underground pipes. Municipalities and water agencies trying to reduce non-point-source pollution are faced with a public that cannot see and therefore does not understand the interconnected nature of the drainage system or its ultimate discharge to the bay. Since 1993, we have collaborated with the Oakland Museum, the San Francisco Estuary Institute, public agencies, and municipalities to create creek and watershed maps to address the need for public understanding of watershed concepts. Fifteen paper maps are now published (www.museumca.org/creeks), which have become a standard reference for educators and anyone working on local creek-related issues. We now present digital interactive creek and watershed maps in Google Earth. Four maps are completed covering urbanized areas of Santa Clara and Alameda Counties. The maps provide a 3D visualization of the watersheds, with cartography draped over the landscape in transparent colors. Each mapped area includes both Present and Past (circa 1800s) layers which can be clicked on or off by the user. The Present layers include the modern drainage network, watershed boundaries, and reservoirs. The Past layers include the 1800s-era creek systems, tidal marshes, lagoons, and other habitats. All data are developed in ArcGIS software and converted to Google Earth format. To ensure the maps are interesting and engaging, clickable icons pop-up provide information on places to visit, restoration projects, history, plants, and animals. Maps of Santa Clara Valley are available at http://www.valleywater.org/WOW.aspx. Maps of western Alameda County will soon be available at http://acfloodcontrol.org/. Digital interactive maps provide several advantages over paper maps. They are seamless within each map area, and the user can zoom in or out, and tilt, and fly over to explore any area of interest. They can be easily customized, for example, adding placemarks or notes. Enrichment information can be added, using clickable icons, without cluttering the map. Best, the maps are fun to use. Digital interactive maps will be another effective tool for enhancing public understanding of urban creeks & watersheds.

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

NASA Astrophysics Data System (ADS)

McBeck, J.; Condit, C. D.

2012-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-06-01

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

In-field Access to Geoscientific Metadata through GPS-enabled Mobile Phones

NASA Astrophysics Data System (ADS)

Hobona, Gobe; Jackson, Mike; Jordan, Colm; Butchart, Ben

2010-05-01

Fieldwork is an integral part of much geosciences research. But whilst geoscientists have physical or online access to data collections whilst in the laboratory or at base stations, equivalent in-field access is not standard or straightforward. The increasing availability of mobile internet and GPS-supported mobile phones, however, now provides the basis for addressing this issue. The SPACER project was commissioned by the Rapid Innovation initiative of the UK Joint Information Systems Committee (JISC) to explore the potential for GPS-enabled mobile phones to access geoscientific metadata collections. Metadata collections within the geosciences and the wider geospatial domain can be disseminated through web services based on the Catalogue Service for Web(CSW) standard of the Open Geospatial Consortium (OGC) - a global grouping of over 380 private, public and academic organisations aiming to improve interoperability between geospatial technologies. CSW offers an XML-over-HTTP interface for querying and retrieval of geospatial metadata. By default, the metadata returned by CSW is based on the ISO19115 standard and encoded in XML conformant to ISO19139. The SPACER project has created a prototype application that enables mobile phones to send queries to CSW containing user-defined keywords and coordinates acquired from GPS devices built-into the phones. The prototype has been developed using the free and open source Google Android platform. The mobile application offers views for listing titles, presenting multiple metadata elements and a Google Map with an overlay of bounding coordinates of datasets. The presentation will describe the architecture and approach applied in the development of the prototype.

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

Reaching the Next Generation of College Students via Their Digital Devices.

NASA Astrophysics Data System (ADS)

Whitmeyer, S. J.; De Paor, D. G.; Bentley, C.

2015-12-01

Current college students attended school during a decade in which many school districts banned cellphones from the classroom or even from school grounds. These students are used to being told to put away their mobile devices and concentrate on traditional classroom activities such as watching PowerPoint presentations or calculating with pencil and paper. However, due to a combination of parental security concerns and recent education research, schools are rapidly changing policy and embracing mobile devices for ubiquitous learning opportunities inside and outside of the classroom. Consequently, many of the next generation of college students will have expectations of learning via mobile technology. We have developed a range of digital geology resources to aid mobile-based geoscience education at college level, including mapping on iPads and other tablets, "crowd-sourced" field projects, augmented reality-supported asynchronous field classes, 3D and 4D split-screen virtual reality tours, macroscopic and microscopic gigapixel imagery, 360° panoramas, assistive devices for inclusive field education, and game-style educational challenges. Class testing of virtual planetary tours shows modest short-term learning gains, but more work is needed to ensure long-term retention. Many of our resources rely on the Google Earth browser plug-in and application program interface (API). Because of security concerns, browser plug-ins in general are being phased out and the Google Earth API will not be supported in future browsers. However, a new plug-in-free API is promised by Google and an alternative open-source virtual globe called Cesium is undergoing rapid development. It already supports the main aspects of Keyhole Markup Language and has features of significant benefit to geoscience, including full support on mobile devices and sub-surface viewing and touring. The research team includes: Heather Almquist, Stephen Burgin, Cinzia Cervato, Filis Coba, Chloe Constants, Gene Cooper, Mladen Dordevic, Marissa Dudek, Brandon Fitzwater, Bridget Gomez, Tyler Hansen, Paul Karabinos, Terry Pavlis, Jen Piatek, Alan Pitts, Robin Rohrback, Bill Richards, Caroline Robinson, Jeff Rollins, Jeff Ryan, Ron Schott, Kristen St. John, and Barb Tewksbury. Supported by NSF DUE 1323419 and by Google Geo Curriculum Awards.

Assessing Landslide Characteristics and Developing a Landslide Potential Hazard Map in Rwanda and Uganda Using NASA Earth Observations

NASA Astrophysics Data System (ADS)

Sinclair, L.; Conner, P.; le Roux, J.; Finley, T.

2015-12-01

The International Emergency Disasters Database indicates that a total of 482 people have been killed and another 27,530 have been affected by landslides in Rwanda and Uganda, although the actual numbers are thought to be much higher. Data for individual countries are poorly tracked, but hotspots for devastating landslides occur throughout Rwanda and Uganda due to the local topography and soil type, intense rainfall events, and deforestation. In spite of this, there has been little research in this region that utilizes satellite imagery to estimate areas susceptible to landslides. This project utilized Landsat 8 Operational Land Imager (OLI) data and Google Earth to identify landslides that occurred within the study area. These landslides were then added to SERVIR's Global Landslide Catalog (GLC). Next, Landsat 8 OLI, the Tropical Rainfall Measuring Mission (TRMM), the Global Precipitation Measurement (GPM), and Shuttle Radar Topography Mission Version 2 (SRTM V2) data were used to create a Landslide Susceptibility Map. This was combined with population data from the Socioeconomic Data and Applications Center (SEDAC) to create a Landslide Hazard map. A preliminary assessment of the relative performance of GPM and TRMM in identifying landslide conditions was also performed. The additions to the GLC, the Landslide Susceptibility Map, the Landslide Hazard Map, and the preliminary assessment of satellite rainfall performance will be used by SERVIR and the Regional Centre for Mapping of Resources for Development (RCMRD) for disaster risk management, land use planning, and determining landslide conditions and moisture thresholds.

A global map of rainfed cropland areas (GMRCA) at the end of last millennium using remote sensing

USGS Publications Warehouse

Biradar, C.M.; Thenkabail, P.S.; Noojipady, P.; Li, Y.; Dheeravath, V.; Turral, H.; Velpuri, M.; Gumma, M.K.; Gangalakunta, O.R.P.; Cai, X.L.; Xiao, X.; Schull, M.A.; Alankara, R.D.; Gunasinghe, S.; Mohideen, S.

2009-01-01

The overarching goal of this study was to produce a global map of rainfed cropland areas (GMRCA) and calculate country-by-country rainfed area statistics using remote sensing data. A suite of spatial datasets, methods and protocols for mapping GMRCA were described. These consist of: (a) data fusion and composition of multi-resolution time-series mega-file data-cube (MFDC), (b) image segmentation based on precipitation, temperature, and elevation zones, (c) spectral correlation similarity (SCS), (d) protocols for class identification and labeling through uses of SCS R2-values, bi-spectral plots, space-time spiral curves (ST-SCs), rich source of field-plot data, and zoom-in-views of Google Earth (GE), and (e) techniques for resolving mixed classes by decision tree algorithms, and spatial modeling. The outcome was a 9-class GMRCA from which country-by-country rainfed area statistics were computed for the end of the last millennium. The global rainfed cropland area estimate from the GMRCA 9-class map was 1.13 billion hectares (Bha). The total global cropland areas (rainfed plus irrigated) was 1.53 Bha which was close to national statistics compiled by FAOSTAT (1.51 Bha). The accuracies and errors of GMRCA were assessed using field-plot and Google Earth data points. The accuracy varied between 92 and 98% with kappa value of about 0.76, errors of omission of 2-8%, and the errors of commission of 19-36%. ?? 2008 Elsevier B.V.

jmzIdentML API: A Java interface to the mzIdentML standard for peptide and protein identification data.

PubMed

Reisinger, Florian; Krishna, Ritesh; Ghali, Fawaz; Ríos, Daniel; Hermjakob, Henning; Vizcaíno, Juan Antonio; Jones, Andrew R

2012-03-01

We present a Java application programming interface (API), jmzIdentML, for the Human Proteome Organisation (HUPO) Proteomics Standards Initiative (PSI) mzIdentML standard for peptide and protein identification data. The API combines the power of Java Architecture of XML Binding (JAXB) and an XPath-based random-access indexer to allow a fast and efficient mapping of extensible markup language (XML) elements to Java objects. The internal references in the mzIdentML files are resolved in an on-demand manner, where the whole file is accessed as a random-access swap file, and only the relevant piece of XMLis selected for mapping to its corresponding Java object. The APIis highly efficient in its memory usage and can handle files of arbitrary sizes. The APIfollows the official release of the mzIdentML (version 1.1) specifications and is available in the public domain under a permissive licence at http://www.code.google.com/p/jmzidentml/. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Research of GIS-services applicability for solution of spatial analysis tasks.

NASA Astrophysics Data System (ADS)

Terekhin, D. A.; Botygin, I. A.; Sherstneva, A. I.; Sherstnev, V. S.

2017-01-01

Experiments for working out the areas of applying various gis-services in the tasks of spatial analysis are discussed in this paper. Google Maps, Yandex Maps, Microsoft SQL Server are used as services of spatial analysis. All services have shown a comparable speed of analyzing the spatial data when carrying out elemental spatial requests (building up the buffer zone of a point object) as well as the preferences of Microsoft SQL Server in operating with more complicated spatial requests. When building up elemental spatial requests, internet-services show higher efficiency due to cliental data handling with JavaScript-subprograms. A weak point of public internet-services is an impossibility to handle data on a server side and a barren variety of spatial analysis functions. Microsoft SQL Server offers a large variety of functions needed for spatial analysis on the server side. The authors conclude that when solving practical problems, the capabilities of internet-services used in building up routes and completing other functions with spatial analysis with Microsoft SQL Server should be involved.

Geographic Information Technologies as an outreach activity in geo-scientific education

NASA Astrophysics Data System (ADS)

Maman, Shimrit; Isaacson, Sivan; Blumberg, Dan G.

2016-04-01

In recent years, a decline in the rates of examinees in the academic track that were entitled to an enhanced matriculation certificate in scientific-technological education was reported in Israel. To confront this problem the Earth and Planetary Image Facility (EPIF) at Ben-Gurion University of the Negev fosters interdisciplinary exploration through educational programs that make use of the facility and its equipment and enable the empowerment of the community by understanding and appreciating science and technology. This is achieved by using Geographic Information Technologies (GIT) such as remote sensing and Geographical Information Systems (GIS) for geo-physical sciences in activities that combine theoretical background with hands-on activities. Monitoring Earth from space by satellites, digital atlases and virtual-based positioning applications are examples for fusion of spatial information (geographic) and technology that the activity is based on. GIT opens a new chapter and a recent history of Cartography starting from the collection of spatial data to its presentation and analysis. GIS have replaced the use of classical atlas books and offer a variety of Web-based applications that provide maps and display up-to-date imagery. The purpose of this workshop is to expose teachers and students to GITs which are applicable in every classroom. The activity imparts free geographic information systems that exist in cyberspace and accessible to single users as the Israeli national GIS and Google earth, which are based on a spatial data and long term local and global satellite imagery coverage. In this paper, our "Think global-Map Local" activity is presented. The activity uses GIS and change detection technologies as means to encourage students to explore environmental issues both around the globe and close to their surroundings. The students detect changes by comparing multi temporal images of a chosen site and learn how to map the alterations and produce change detection maps with simple and user friendly tools. The activity is offered both for students and supervised projects for teachers and youth.

The Dimensions of the Solar System

ERIC Educational Resources Information Center

Schneider, Stephen E.; Davis, Kathleen S.

2007-01-01

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

Geospatial Services in Special Libraries: A Needs Assessment Perspective

ERIC Educational Resources Information Center

Barnes, Ilana

2013-01-01

Once limited to geographers and mapmakers, Geographic Information Systems (GIS) has taken a growing central role in information management and visualization. Geospatial services run a gamut of different products and services from Google maps to ArcGIS servers to Mobile development. Geospatial services are not new. Libraries have been writing about…

Map Scale, Proportion, and Google[TM] Earth

ERIC Educational Resources Information Center

Roberge, Martin C.; Cooper, Linda L.

2010-01-01

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

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.

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.

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

A landslide susceptibility map of Africa

NASA Astrophysics Data System (ADS)

Broeckx, Jente; Vanmaercke, Matthias; Duchateau, Rica; Poesen, Jean

2017-04-01

Studies on landslide risks and fatalities indicate that landslides are a global threat to humans, infrastructure and the environment, certainly in Africa. Nonetheless our understanding of the spatial patterns of landslides and rockfalls on this continent is very limited. Also in global landslide susceptibility maps, Africa is mostly underrepresented in the inventories used to construct these maps. As a result, predicted landslide susceptibilities remain subject to very large uncertainties. This research aims to produce a first continent-wide landslide susceptibility map for Africa, calibrated with a well-distributed landslide dataset. As a first step, we compiled all available landslide inventories for Africa. This data was supplemented by additional landslide mapping with Google Earth in underrepresented regions. This way, we compiled 60 landslide inventories from the literature (ca. 11000 landslides) and an additional 6500 landslides through mapping in Google Earth (including 1500 rockfalls). Various environmental variables such as slope, lithology, soil characteristics, land use, precipitation and seismic activity, were investigated for their significance in explaining the observed spatial patterns of landslides. To account for potential mapping biases in our dataset, we used Monte Carlo simulations that selected different subsets of mapped landslides, tested the significance of the considered environmental variables and evaluated the performance of the fitted multiple logistic regression model against another subset of mapped landslides. Based on these analyses, we constructed two landslide susceptibility maps for Africa: one for all landslide types and one excluding rockfalls. In both maps, topography, lithology and seismic activity were the most significant variables. The latter factor may be surprising, given the overall limited degree of seismicity in Africa. However, its significance indicates that frequent seismic events may serve as in important preparatory factor for landslides. This finding concurs with several other recent studies. Rainfall explains a significant, but limited part of the observed landslide pattern and becomes insignificant when also rockfalls are considered. This may be explained by the fact that a significant fraction of the mapped rockfalls occurred in the Sahara desert. Overall, both maps perform well in predicting intra-continental patterns of mass movements in Africa and explain about 80% of the observed variance in landslide occurrence. As a result, these maps may be a valuable tool for planning and risk reduction strategies.

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

PubMed

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

2018-02-28

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

ICT approaches to integrating institutional and non-institutional data services for better understanding of hydro-meteorological phenomena

NASA Astrophysics Data System (ADS)

Bedrina, T.; Parodi, A.; Quarati, A.; Clematis, A.

2012-06-01

It is widely recognised that an effective exploitation of Information and Communication Technologies (ICT) is an enabling factor to achieve major advancements in Hydro-Meteorological Research (HMR). Recently, a lot of attention has been devoted to the use of ICT in HMR activities, e.g. in order to facilitate data exchange and integration, to improve computational capabilities and consequently model resolution and quality. Nowadays, ICT technologies have demonstrated that it is possible to extend monitoring networks by integrating sensors and other sources of data managed by volunteer's communities. These networks are constituted by peers that span a wide portion of the territory in many countries. The peers are "location aware" in the sense that they provide information strictly related with their geospatial location. The coverage of these networks, in general, is not uniform and the location of peers may follow random distribution. The ICT features used to set up the network are lightweight and user friendly, thus, permitting the peers to join the network without the necessity of specialised ICT knowledge. In this perspective it is of increasing interest for HMR activities to elaborate of Personal Weather Station (PWS) networks, capable to provide almost real-time, location aware, weather data. Moreover, different big players of the web arena are now providing world-wide backbones, suitable to present on detailed map location aware information, obtained by mashing up data from different sources. This is the case, for example, with Google Earth and Google Maps. This paper presents the design of a mashup application aimed at aggregating, refining and visualizing near real-time hydro-meteorological datasets. In particular, we focused on the integration of instant precipitation depths, registered either by widespread semi-professional weather stations and official ones. This sort of information has high importance and usefulness in decision support systems and Civil Protection applications. As a significant case study, we analysed the rainfall data observed during the severe flash-flood event of 4 November 2011 over Liguria region, Italy. The joint use of official observation network with PWS networks and meteorological radar allowed for the making of evident finger-like convection structure.

[Google Flu Trends--the initial application of big data in public health].

PubMed

Zou, Xiaohui; Zhu, Wenfei; Yang, Lei; Shu, Yuelong

2015-06-01

Google Flu Trends (GFT) was the first application of big data in the public health field. GFT was open online in 2009 and attracted worldwide attention immediately. However, GFT failed catching the 2009 pandemic H1N1 and kept overestimating the intensity of influenza-like illness in the 2012-2014 season in the United States. GFT model has been updated for three times since 2009, making its prediction bias controlled. Here, we summarized the mechanism GFT worked, the strategy GFT used to update, and its influence on public health.

SIG Contribution in the Making of Geotechnical Maps in Urban Areas

NASA Astrophysics Data System (ADS)

Monteiro, António; Pais, Luís Andrade; Rodrigues, Carlos; Carvalho, Paulo

2017-10-01

The use of Geographic Information Systems (GIS) has spread to several science areas, from oceanography to geotechnics. Its application in the urban mapping was intensified in the last century, which allowed a great development, due to the use of geographic database, new analysis tools and, more recently, free open source software. Geotechnical cartography struggle with a permanent and large environment re-organization in urban area, due to new building construction, trenching and the drilling of sampling wells and holes. This creates an extra important and largest volume of data at any pre-existence geological map. The main problem results on the fact that the natural environment is covered with buildings and communications system. The purpose of this work is to create a viable geographic information base for geotechnical mapping through a free GIS computer program and open source, with non-traditional cartographic sources, giving preference to open platforms. QGIS was used as software and “Google Maps”, “Bing Maps” and “OpenStreetMap” were applied as cartographic sources using the “OpenLayers plugin” module. Finally, we also pretend to identify and delimit the degree of granite’s change and fracturing areas using a “Streetview” platform. This model has cartographic input which are a geological map study area, open cartographic web archives and the use of “Streetview” platform. The output has several layouts, such as topography intersection (roads, borders, etc.), with geological map and the bordering area of Guarda Urban Zone. The use of this platform types decrease the collect data time and, sometimes, a careful observation of pictures that were taken during excavations may reveal important details for geological mapping in the study area.

Supporting diagnosis and treatment in medical care based on Big Data processing.

PubMed

Lupşe, Oana-Sorina; Crişan-Vida, Mihaela; Stoicu-Tivadar, Lăcrămioara; Bernard, Elena

2014-01-01

With information and data in all domains growing every day, it is difficult to manage and extract useful knowledge for specific situations. This paper presents an integrated system architecture to support the activity in the Ob-Gin departments with further developments in using new technology to manage Big Data processing - using Google BigQuery - in the medical domain. The data collected and processed with Google BigQuery results from different sources: two Obstetrics & Gynaecology Departments, the TreatSuggest application - an application for suggesting treatments, and a home foetal surveillance system. Data is uploaded in Google BigQuery from Bega Hospital Timişoara, Romania. The analysed data is useful for the medical staff, researchers and statisticians from public health domain. The current work describes the technological architecture and its processing possibilities that in the future will be proved based on quality criteria to lead to a better decision process in diagnosis and public health.

Review of infectious diseases applications for iPhone/iPad and Android: from pocket to patient.

PubMed

Moodley, Amaran; Mangino, Julie E; Goff, Debra A

2013-10-01

The explosion of medical applications (apps) in the Apple and Google Play app stores has made it increasingly difficult to find relevant and reliable infectious diseases (ID) apps. Apple created a section called "Apps for Healthcare Professionals"; however, several ID apps are missing. Google Play's ID category has several non-ID apps. Many apps involve diagnosis and patient management, creating a need for regulations and oversight by the US Food and Drug Administration. There are no standards to guide accuracy or reliability of medical apps' content. We searched Apple and Google Play app stores to identify new ID apps. Over 1200 apps were identified. We applied several exclusion criteria to identify adult/pediatric apps with data from trustworthy sources that were not reviewed within the last year. Twelve new ID apps were identified with a comprehensive list of 24 ID apps to assist healthcare professionals at the point of care.

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.

Snake River Plain Geothermal Play Fairway Analysis - Phase 1 KMZ files

DOE Data Explorer

John Shervais

2015-10-10

This dataset contain raw data files in kmz files (Google Earth georeference format). These files include volcanic vent locations and age, the distribution of fine-grained lacustrine sediments (which act as both a seal and an insulating layer for hydrothermal fluids), and post-Miocene faults compiled from the Idaho Geological Survey, the USGS Quaternary Fault database, and unpublished mapping. It also contains the Composite Common Risk Segment Map created during Phase 1 studies, as well as a file with locations of select deep wells used to interrogate the subsurface.

Combating Conflict Related Sexual Violence: More Than a Stability Concern

DTIC Science & Technology

2014-06-13

violence can cause serious bodily harm or mental harm to members of the group (International Criminal Court 2002, 3; Ellis 2007). Under crimes against...population was subjugated to Japanese 46 rule and were provided with horrific visual, physical, and emotional reminders of the futility of any...maps.google.com/ maps /ms?msid=214870171076954118166.0004b9bcb533b0ee2c1f8&msa=0&ie= UTF8&ll=12.848235,58.136902&spn=43.135476,135.258178&t=m&output=em bed

AIDSinfo Glossary

MedlinePlus

... Drug Application CCR5 Antagonist Acquired Immunodeficiency Syndrome Free Mobile Apps Download these free applications for your iOS and Android devices. Guidelines App Store Google Play Drug Database App ...

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

ERIC Educational Resources Information Center

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

2013-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2009-12-01

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

Facilitating Semantic Interoperability Among Ocean Data Systems: ODIP-R2R Student Outcomes

NASA Astrophysics Data System (ADS)

Stocks, K. I.; Chen, Y.; Shepherd, A.; Chandler, C. L.; Dockery, N.; Elya, J. L.; Smith, S. R.; Ferreira, R.; Fu, L.; Arko, R. A.

2014-12-01

With informatics providing an increasingly important set of tools for geoscientists, it is critical to train the next generation of scientists in information and data techniques. The NSF-supported Rolling Deck to Repository (R2R) Program works with the academic fleet community to routinely document, assess, and preserve the underway sensor data from U.S. research vessels. The Ocean Data Interoperability Platform (ODIP) is an EU-US-Australian collaboration fostering interoperability among regional e-infrastructures through workshops and joint prototype development. The need to align terminology between systems is a common challenge across all of the ODIP prototypes. Five R2R students were supported to address aspects of semantic interoperability within ODIP. Developing a vocabulary matching service that links terms from different vocabularies with similar concept. The service implements Google Refine reconciliation service interface such that users can leverage Google Refine application as a friendly user interface while linking different vocabulary terms. Developing Resource Description Framework (RDF) resources that map Shipboard Automated Meteorological Oceanographic System (SAMOS) vocabularies to internationally served vocabularies. Each SAMOS vocabulary term (data parameter and quality control flag) will be described as an RDF resource page. These RDF resources allow for enhanced discoverability and retrieval of SAMOS data by enabling data searches based on parameter. Improving data retrieval and interoperability by exposing data and mapped vocabularies using Semantic Web technologies. We have collaborated with ODIP participating organizations in order to build a generalized data model that will be used to populate a SPARQL endpoint in order to provide expressive querying over our data files. Mapping local and regional vocabularies used by R2R to those used by ODIP partners. This work is described more fully in a companion poster. Making published Linked Data Web developer-friendly with a RESTful service. This goal was achieved by defining a proxy layer on top of the existing SPARQL endpoint that 1) translates HTTP requests into SPARQL queries, and 2) renders the returned results as required by the request sender using content negotiation, suffixes and parameters.

Google Glass-Directed Monitoring and Control of Microfluidic Biosensors and Actuators

PubMed Central

Zhang, Yu Shrike; Busignani, Fabio; Ribas, João; Aleman, Julio; Rodrigues, Talles Nascimento; Shaegh, Seyed Ali Mousavi; Massa, Solange; Rossi, Camilla Baj; Taurino, Irene; Shin, Su-Ryon; Calzone, Giovanni; Amaratunga, Givan Mark; Chambers, Douglas Leon; Jabari, Saman; Niu, Yuxi; Manoharan, Vijayan; Dokmeci, Mehmet Remzi; Carrara, Sandro; Demarchi, Danilo; Khademhosseini, Ali

2016-01-01

Google Glass is a recently designed wearable device capable of displaying information in a smartphone-like hands-free format by wireless communication. The Glass also provides convenient control over remote devices, primarily enabled by voice recognition commands. These unique features of the Google Glass make it useful for medical and biomedical applications where hands-free experiences are strongly preferred. Here, we report for the first time, an integral set of hardware, firmware, software, and Glassware that enabled wireless transmission of sensor data onto the Google Glass for on-demand data visualization and real-time analysis. Additionally, the platform allowed the user to control outputs entered through the Glass, therefore achieving bi-directional Glass-device interfacing. Using this versatile platform, we demonstrated its capability in monitoring physical and physiological parameters such as temperature, pH, and morphology of liver- and heart-on-chips. Furthermore, we showed the capability to remotely introduce pharmaceutical compounds into a microfluidic human primary liver bioreactor at desired time points while monitoring their effects through the Glass. We believe that such an innovative platform, along with its concept, has set up a premise in wearable monitoring and controlling technology for a wide variety of applications in biomedicine. PMID:26928456

Google Glass-Directed Monitoring and Control of Microfluidic Biosensors and Actuators

NASA Astrophysics Data System (ADS)

Zhang, Yu Shrike; Busignani, Fabio; Ribas, João; Aleman, Julio; Rodrigues, Talles Nascimento; Shaegh, Seyed Ali Mousavi; Massa, Solange; Rossi, Camilla Baj; Taurino, Irene; Shin, Su-Ryon; Calzone, Giovanni; Amaratunga, Givan Mark; Chambers, Douglas Leon; Jabari, Saman; Niu, Yuxi; Manoharan, Vijayan; Dokmeci, Mehmet Remzi; Carrara, Sandro; Demarchi, Danilo; Khademhosseini, Ali

2016-03-01

Google Glass is a recently designed wearable device capable of displaying information in a smartphone-like hands-free format by wireless communication. The Glass also provides convenient control over remote devices, primarily enabled by voice recognition commands. These unique features of the Google Glass make it useful for medical and biomedical applications where hands-free experiences are strongly preferred. Here, we report for the first time, an integral set of hardware, firmware, software, and Glassware that enabled wireless transmission of sensor data onto the Google Glass for on-demand data visualization and real-time analysis. Additionally, the platform allowed the user to control outputs entered through the Glass, therefore achieving bi-directional Glass-device interfacing. Using this versatile platform, we demonstrated its capability in monitoring physical and physiological parameters such as temperature, pH, and morphology of liver- and heart-on-chips. Furthermore, we showed the capability to remotely introduce pharmaceutical compounds into a microfluidic human primary liver bioreactor at desired time points while monitoring their effects through the Glass. We believe that such an innovative platform, along with its concept, has set up a premise in wearable monitoring and controlling technology for a wide variety of applications in biomedicine.

Google Glass-Directed Monitoring and Control of Microfluidic Biosensors and Actuators.

PubMed

Zhang, Yu Shrike; Busignani, Fabio; Ribas, João; Aleman, Julio; Rodrigues, Talles Nascimento; Shaegh, Seyed Ali Mousavi; Massa, Solange; Baj Rossi, Camilla; Taurino, Irene; Shin, Su-Ryon; Calzone, Giovanni; Amaratunga, Givan Mark; Chambers, Douglas Leon; Jabari, Saman; Niu, Yuxi; Manoharan, Vijayan; Dokmeci, Mehmet Remzi; Carrara, Sandro; Demarchi, Danilo; Khademhosseini, Ali

2016-03-01

Google Glass is a recently designed wearable device capable of displaying information in a smartphone-like hands-free format by wireless communication. The Glass also provides convenient control over remote devices, primarily enabled by voice recognition commands. These unique features of the Google Glass make it useful for medical and biomedical applications where hands-free experiences are strongly preferred. Here, we report for the first time, an integral set of hardware, firmware, software, and Glassware that enabled wireless transmission of sensor data onto the Google Glass for on-demand data visualization and real-time analysis. Additionally, the platform allowed the user to control outputs entered through the Glass, therefore achieving bi-directional Glass-device interfacing. Using this versatile platform, we demonstrated its capability in monitoring physical and physiological parameters such as temperature, pH, and morphology of liver- and heart-on-chips. Furthermore, we showed the capability to remotely introduce pharmaceutical compounds into a microfluidic human primary liver bioreactor at desired time points while monitoring their effects through the Glass. We believe that such an innovative platform, along with its concept, has set up a premise in wearable monitoring and controlling technology for a wide variety of applications in biomedicine.

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

NASA Astrophysics Data System (ADS)

Zhou, Z.; Zhou, X.

2016-12-01

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

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 of trans participants, including a total of 605 photographs. Of the 94 publications, 35 (37%) included at least one medical photograph that was found on Google Images. The ability to locate the article freely online contributes to the availability of at least one image from the article on Google Images (OR 2.99, 95% CI 1.20-7.45). This is the first study to document the existence of medical photographs from peer-reviewed journals appearing in Google Images search results. Almost all of the images we searched for included sensitive photographs of patient genitals, chests, or breasts. Given that it is unlikely that patients consented to sharing their personal health information in these ways, this constitutes a risk to patient privacy. Based on the impact of current practices, revisions to informed consent policies and guidelines are required. ©Zack Marshall, Fern Brunger, Vivian Welch, Shabnam Asghari, Chris Kaposy. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 26.02.2018.

iPads at Field Camp: A First Test of the Challenges and Opportunities

NASA Astrophysics Data System (ADS)

Hurst, S. D.; Stewart, M. A.

2011-12-01

An iPad 2 was given to approximately half of the University of Illinois students attending the Wasatch-Uinta Field Camp (WUFC) in summer 2011. The iPads were provisioned with orientation measuring, mapping and location software. The software would automatically transfer an orientation measurement to the current location on the Google Maps application, and was able to output a full list of orientation data. Students also had normal access to more traditional mapping tools such as Brunton compasses and GPS units and were required to map with these tools along with other students of WUFC not provided iPads. Compared to traditional tools, iPads have drawbacks such as increased weight, break-ability, need for power source and wireless connectivity; in sum, they need a substantial infrastructure that reduces range, availability, and probably most importantly, convenience. Some of these drawbacks inhibited adoption by our students, the primary reasons being the added weight and the inability to map directly to a GIS application with detailed topographic maps equivalent to the physical topographic map sheets used at WUFC. In their favor, the iPads combine a host of tools into one, including software that can measure orientation in a fashion more intuitively than a Brunton. They also allow storage, editing and analysis of data, notes (spoken and/or written) and potentially unlimited access to a variety of maps. Via a post-field camp survey of the University of Illinois students at WUFC, we have identified some of the important issues that need to be addressed before portable tablets like the iPad become the tool of choice for general field work. Some problems are intrinsic to almost any advanced technology, some are artifacts of the current generations of hardware and software available for these devices. Technical drawbacks aside, the adoption of iPads was further inhibited primarily by inexperience with their use as a mapping tool and secondarily by their redundancy with traditional tools. We are addressing some aspects of software limitations and future technology improvements by the industry will naturally reduce other limitations. We will continue testing iPads during field trips and courses for the foreseeable future. As we begin to deal with these limitations and students become more accustomed to their use in the field, we expect our students to more fully embrace iPads as a convenient field and mapping tool.

Visualizing and communicating climate change using the ClimateWizard: decision support and education through web-based analysis and mapping

NASA Astrophysics Data System (ADS)

Girvetz, E. H.; Zganjar, C.; Raber, G. T.; Maurer, E. P.; Duffy, P.

2009-12-01

Virtually all fields of study and parts of society—from ecological science and nature conservation, to global development, multinational corporations, and government bodies—need to know how climate change has and may impact specific locations of interest. Our ability to respond to climate change depends on having convenient tools that make past and projected climate trends available to planners, managers, scientists and the general public, at scales ranging from global to local scales. Web-mapping applications provide an effective platform for communicating climate change impacts in specific geographic areas of interest to the public. Here, we present one such application, the ClimateWizard, that allows users to analyze, visualize and explore climate change maps for specific geographic areas of interest throughout the world (http://ClimateWizard.org). Built on Web 2.0 web-services (SOAP), Google Maps mash-up, and cloud computing technologies, the ClimateWizard analyzes large databases of climate information located on remote servers to create synthesized information and useful products tailored to geographic areas of interest (e.g. maps, graphs, tables, GIS layers). We demonstrate how the ClimateWizard can be used to assess projected changes to temperature and precipitation across all states in the contiguous United States and all countries of the world using statistically downscaled general circulation models from the CMIP3 dataset. We then go on to show how ClimateWizard can be used to analyze changes to other climate related variables, such as moisture stress and water production. Finally, we discuss how this tool can be adapted to develop a wide range of web-based tools that are targeted at informing specific audiences—from scientific research and natural resource management, to K-12 and higher education—about how climate change may affect different aspects of human and natural systems.

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.

The impact of land use changes in the Banjarsari village, Cerme district of Gresik Regency, East Java Province

NASA Astrophysics Data System (ADS)

Ayu Larasati, Dian; Hariyanto, Bambang

2018-01-01

High population growth, and development activities in various fields will lead to join the growing demand for land. Cerme is a district close to the city of Surabaya, therefore a lot of agricultural land in Cerme used as housing and industry in order to support the growth of the population whose land in Surabaya city could not accommodate more. Base on this fact the research be did. The aim of this research is: determine the pattern of land use changes in the last year and to analyze the socioeconomic changes in the Banjarsari village, Gresik Regency. To determine the socioeconomic changes in the area of research is required: a). population change data from 2010 to 2015, b). Google Earth Imagery 2010 to 2015. The population data and the type of work changes are described by the time series and land cover change analysis. To analysis the land use conversion we also use Google Earth imagery with ArcGIS applications. For astronomical layout correction based on GPS field checks and RBI Map. The goal of this study is 1). Farmland change into residential/settlements in 2004-2014 is 12%; 2). Peoples who changing their livelihood is 39%. In occupational changes affect the population income ranges from 500,000 IDR -. 1,000,000 IDR per month/percapita.

Sedimentation and erosion in Lake Diefenbaker, Canada: solutions for shoreline retreat monitoring.

PubMed

Sadeghian, Amir; de Boer, Dirk; Lindenschmidt, Karl-Erich

2017-09-15

This study looks into sedimentation and erosion rates in Lake Diefenbaker, a prairie reservoir, in Saskatchewan, Canada, which has been in operation since 1968. First, we looked at the historical data in all different formats over the last 70 years, which includes data from more than 20 years before the formation of the lake. The field observations indicate high rates of shoreline erosion, especially in the upstream portion as a potential region for shoreline retreat. Because of the great importance of this waterbody to the province, monitoring sedimentation and erosion rates is necessary for maintaining the quality of water especially after severe floods which are more common due to climate change effects. Second, we used Google Maps Elevation API, a new tool from Google that provides elevation data for cross sections drawn between two points, by drawing 24 cross sections in the upstream area extending 250 m from each bank. This feature from Google can be used as an easy and fast monitoring tool, is free of charge, and provides excellent control capabilities for monitoring changes in cross-sectional profiles.

AFRC2016-0054-528

NASA Image and Video Library

2016-02-27

Sam Choi and Naiara Pinto observe Google Earth overlaid with in almost real time what the synthetic aperture radar is mapping from the C-20A aircraft. Researchers were in the sky and on the ground to take measurements of plant mass, distribution of trees, shrubs and ground cover and the diversity of plants and how much carbon is absorbed by them.

Ingress in Geography: Portals to Academic Success?

ERIC Educational Resources Information Center

Davis, Michael

2017-01-01

Niantic Labs has developed an augmented virtual reality mobile app game called Ingress in which agents must seek out and control locations for their designated factions. The app uses the Google Maps interface along with GPS to enhance a geocaching-like experience with elements of other classical games such as capture-the-flag. This study aims to…

Applying Modern Stage Theory to Mauritania: A Prescription to Encourage Entrepreneurship

DTIC Science & Technology

2014-12-01

entrepreneurship, stage theory, development, Africa , factor-driven, trade freedom, business freedom 15. NUMBER OF PAGES 77 16. PRICE CODE 17...SOUTH ASIA, SUB-SAHARAN AFRICA ) from the NAVAL POSTGRADUATE SCHOOL December 2014 Author: Jennifer M. Warren Approved by: Robert E...Notes, Coins) .......................................................................... 4  Figure 2.  Satellite map of West Africa (from Google Earth

Re-Purposing Google Maps Visualisation for Teaching Logistics Systems

ERIC Educational Resources Information Center

Cheong, France; Cheong, Christopher; Jie, Ferry

2012-01-01

Routing is the process of selecting appropriate paths and ordering waypoints in a network. It plays an important part in logistics and supply chain management as choosing the optimal route can minimise distribution costs. Routing optimisation, however, is a difficult problem to solve and computer software is often used to determine the best route.…

Regional early flood warning system: design and implementation

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

The New USGS Volcano Hazards Program Web Site

NASA Astrophysics Data System (ADS)

Venezky, D. Y.; Graham, S. E.; Parker, T. J.; Snedigar, S. F.

2008-12-01

The U.S. Geological Survey's (USGS) Volcano Hazard Program (VHP) has launched a revised web site that uses a map-based interface to display hazards information for U.S. volcanoes. The web site is focused on better communication of hazards and background volcano information to our varied user groups by reorganizing content based on user needs and improving data display. The Home Page provides a synoptic view of the activity level of all volcanoes for which updates are written using a custom Google® Map. Updates are accessible by clicking on one of the map icons or clicking on the volcano of interest in the adjacent color-coded list of updates. The new navigation provides rapid access to volcanic activity information, background volcano information, images and publications, volcanic hazards, information about VHP, and the USGS volcano observatories. The Volcanic Activity section was tailored for emergency managers but provides information for all our user groups. It includes a Google® Map of the volcanoes we monitor, an Elevated Activity Page, a general status page, information about our Volcano Alert Levels and Aviation Color Codes, monitoring information, and links to monitoring data from VHP's volcano observatories: Alaska Volcano Observatory (AVO), Cascades Volcano Observatory (CVO), Long Valley Observatory (LVO), Hawaiian Volcano Observatory (HVO), and Yellowstone Volcano Observatory (YVO). The YVO web site was the first to move to the new navigation system and we are working on integrating the Long Valley Observatory web site next. We are excited to continue to implement new geospatial technologies to better display our hazards and supporting volcano information.

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

NASA Astrophysics Data System (ADS)

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

2014-08-01

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

MGDS: Free, on-line, cutting-edge tools to enable the democratisation of geoscience data

NASA Astrophysics Data System (ADS)

Goodwillie, A. M.; Ryan, W. B.; O'Hara, S.; Ferrini, V.; Arko, R. A.; Coplan, J.; Chan, S.; Carbotte, S. M.; Nitsche, F. O.; Bonczkowski, J.; Morton, J. J.; Weissel, R.; Leung, A.

2010-12-01

The availability of user-friendly, effective cyber-information resources for accessing and manipulating geoscience data has grown rapidly in recent years. Based at Lamont-Doherty Earth Observatory the MGDS group has developed a number of free tools that have wide application across the geosciences for both educators and researchers. A simple web page (http://www.marine-geo.org/) allows users to search for and download many types of data by key word, geographical region, or published citation. The popular Create Maps and Grids function and the downloadable Google Earth-compatible KML files appeal to a wide user base. MGDS MediaBank galleries (http://media.marine-geo.org/) enable users to view and download compelling images that are purposefully selected for their educational value from NSF-funded field programs. GeoMapApp (http://www.geomapapp.org), a free map-based interactive tool that works on any machine, is increasingly being adopted across a broad suite of users from middle school students to university researchers. GeoMapApp allows users to plot, manipulate and present data in an intuitive geographical reference frame. GeoMapApp offers a convenient way to explore the wide range of built-in data sets, to quickly generate maps and images that aid visualisation and, when importing their own gridded and tabular data sets, to access the same rich built-in functionality. A user guide, short multi-media tutorials, and webinar are available on-line. The regularly-updated Global Multi-Resolution Topography (GMRT) Synthesis is used as the default GeoMapApp base map and is an increasingly popular means to rapidly create location maps. Additionally, the layer manager offers a fast way to overlay and compare multiple data sets and is augmented by the ability to alter layer transparency so that underlying layers become visible. Examples of GeoMapApp built-in data sets include high-resolution land topography and ocean floor bathymetry derived from satellite and multi-beam swath mapping systems - these can be profiled, shaded, and contoured; geo-registered geochemical sample analyses from the EarthChem database; plate boundary, earthquake and volcano catalogues; physical oceanography global and water column data; seafloor photos and Alvin dive video images; geological maps at various scales; and, high-quality coastline, lakes and rivers data. Customised data portals offer enhanced functionality for multi-channel seismic profiles, drill core logs, and earthquake animations. GeoMapApp is used in many MARGINS undergraduate-level off-the-shelf interactive learning activities called mini-lessons (http://serc.carleton.edu/margins/collection.html). Examples of educational applicability will be shown.

Perils of using speed zone data to assess real-world compliance to speed limits.

PubMed

Chevalier, Anna; Clarke, Elizabeth; Chevalier, Aran John; Brown, Julie; Coxon, Kristy; Ivers, Rebecca; Keay, Lisa

2017-11-17

Real-world driving studies, including those involving speeding alert devices and autonomous vehicles, can gauge an individual vehicle's speeding behavior by comparing measured speed with mapped speed zone data. However, there are complexities with developing and maintaining a database of mapped speed zones over a large geographic area that may lead to inaccuracies within the data set. When this approach is applied to large-scale real-world driving data or speeding alert device data to determine speeding behavior, these inaccuracies may result in invalid identification of speeding. We investigated speeding events based on service provider speed zone data. We compared service provider speed zone data (Speed Alert by Smart Car Technologies Pty Ltd., Ultimo, NSW, Australia) against a second set of speed zone data (Google Maps Application Programming Interface [API] mapped speed zones). We found a systematic error in the zones where speed limits of 50-60 km/h, typical of local roads, were allocated to high-speed motorways, which produced false speed limits in the speed zone database. The result was detection of false-positive high-range speeding. Through comparison of the service provider speed zone data against a second set of speed zone data, we were able to identify and eliminate data most affected by this systematic error, thereby establishing a data set of speeding events with a high level of sensitivity (a true positive rate of 92% or 6,412/6,960). Mapped speed zones can be a source of error in real-world driving when examining vehicle speed. We explored the types of inaccuracies found within speed zone data and recommend that a second set of speed zone data be utilized when investigating speeding behavior or developing mapped speed zone data to minimize inaccuracy in estimates of speeding.

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.

Mapping and inventorying active rock glaciers in the northern Tien Shan of China using satellite SAR interferometry

NASA Astrophysics Data System (ADS)

Wang, Xiaowen; Liu, Lin; Zhao, Lin; Wu, Tonghua; Li, Zhongqin; Liu, Guoxiang

2017-04-01

Rock glaciers are widespread in the Tien Shan. However, rock glaciers in the Chinese part of the Tien Shan have not been systematically investigated for more than 2 decades. In this study, we propose a new method that combines SAR interferometry and optical images from Google Earth to map active rock glaciers (ARGs) in the northern Tien Shan (NTS) of China. We compiled an inventory that includes 261 ARGs and quantitative information about their locations, geomorphic parameters, and downslope velocities. Our inventory shows that most of the ARGs are moraine-derived (69 %) and facing northeast (56 %). The altitude distribution of ARGs in the western NTS is significantly different from those located in the eastern part. The downslope velocities of the ARGs vary significantly in space, with a maximum of about 114 cm yr-1 and a mean of about 37 cm yr-1. Using the ARG locations as a proxy for the extent of alpine permafrost, our inventory suggests that the lowest altitudinal limit for the presence of permafrost in the NTS is about 2500-2800 m, a range determined by the lowest ARG in the entire inventory and by a statistics-based estimation. The successful application of the proposed method would facilitate effective and robust efforts to map rock glaciers over mountain ranges globally. This study provides an important dataset to improve mapping and modeling permafrost occurrence in vast western China.

Towards the Development and Validation of a Global Field Size and Irrigation Map using Crowdsourcing, Mobile Apps and Google Earth Engine in support of GEOGLAM

NASA Astrophysics Data System (ADS)

Fritz, S.; Nordling, J.; See, L. M.; McCallum, I.; Perger, C.; Becker-Reshef, I.; Mucher, S.; Bydekerke, L.; Havlik, P.; Kraxner, F.; Obersteiner, M.

2014-12-01

The International Institute for Applied Systems Analysis (IIASA) has developed a global cropland extent map, which supports the monitoring and assessment activities of GEOGLAM (Group on Earth Observations Global Agricultural Monitoring Initiative). Through the European-funded SIGMA (Stimulating Innovation for Global Monitoring of Agriculture and its Impact on the Environment in support of GEOGLAM) project, IIASA is continuing to support GEOGLAM by providing cropland projections in the future and modelling environmental impacts on agriculture under various scenarios. In addition, IIASA is focusing on two specific elements within SIGMA: the development of a global field size and irrigation map; and mobile app development for in-situ data collection and validation of remotely-sensed products. Cropland field size is a very useful indicator for agricultural monitoring yet the information we have at a global scale is currently very limited. IIASA has already created a global map of field size at a 1 km resolution using crowdsourced data from Geo-Wiki as a first approximation. Using automatic classification of Landsat imagery and algorithms contained within Google Earth Engine, initial experimentation has shown that circular fields and landscape structures can easily be extracted. Not only will this contribute to improving the global map of field size, it can also be used to create a global map that contains a large proportion of the world's irrigated areas, which will be another useful contribution to GEOGLAM. The field size map will also be used to stratify and develop a global crop map in SIGMA. Mobile app development in support of in-situ data collection is another area where IIASA is currently working. An Android app has been built using the Open Data Toolkit (ODK) and extended further with spatial mapping capabilities called GeoODK. The app allows users to collect data on different crop types and delineate fields on the ground, which can be used to validate the field size map. The app can also cache map data so that high resolution satellite imagery and reference data from the users can be viewed in the field without the need for an internet connection. This app will be used for calibration and validation of the data products in SIGMA, e.g. data collection at JECAM (Joint Experiment of Crop Assessment and Monitoring) sites.

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.

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-11-01

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

Using Google Applications as Part of Cloud Computing to Improve Knowledge and Teaching Skills of Faculty Members at the University of Bisha, Bisha, Saudi Arabia

ERIC Educational Resources Information Center

Alshihri, Bandar A.

2017-01-01

Cloud computing is a recent computing paradigm that has been integrated into the educational system. It provides numerous opportunities for delivering a variety of computing services in a way that has not been experienced before. The Google Company is among the top business companies that afford their cloud services by launching a number of…

Application of neogeographic tools for geochemistry

NASA Astrophysics Data System (ADS)

Zhilin, Denis

2010-05-01

Neogeography is a usage of geographical tools for utilization by a non-expert group of users. It have been rapidly developing last ten years and is founded on (a) availability of Global Positioning System (GPS) receivers, that allows to obtain very precise geographical position (b) services, that allows linking geographical position with satellite images, GoogleEarth for example and (c) programs as GPS Track Maker or OziExplorer, that allows linking geographical coordinates with other raster images (for example, maps). However, the possibilities of neogeographic approach are much wider. It allows linking different parameters with geographical coordinates on the one hand and space image or map - on the other. If it is easy to measure a parameter, a great database could be collected for a very small time. The results can be presented in very different ways. One can plot a parameter versus the distance from a particular point (for example, a source of a substance), make two-dimension distribution of parameter of put the results onto a map or space image. In the case of chemical parameters it can help finding the source of pollution, trace the influence of pollution, reveal geochemical processes and patterns. The main advantage of neogeograpic approach is the employment of non-experts in collecting data. Now non-experts can easily measure electrical conductivity and pH of natural waters, concentration of different gases in the atmosphere, solar irradiation, radioactivity and so on. If the results are obtained (for example, by students of secondary schools) and shared, experts can proceed them and make significant conclusions. An interface of sharing the results (http://maps.sch192.ru/) was elaborated by V. Ilyin. Within the interface a user can load *.csv file with coordinates, type of parameter and the value of parameter in a particular point. The points are marked on the GoogleEarth map with the color corresponding the value of the parameter. The color scale can be edited manually. We would like to show some results of practical and scientific importance, obtained by non-experts. At 2006 our secondary school students investigated the distribution of snow salinity around Kosygina Street in Moscow. One can conclude that the distribution of salinity is reproducible and that the street influences the snow up to 150 meters. Another example obtained by our students is the distribution of electrical conductivity of swamp water showing extreme irregularity of this parameter within the small area (about 0.5x0.5 km) the electrical conductivity varied from 22 to 77 uS with no regularity. It points out the key role of local processes in swamp water chemistry. The third example (maps of electrical conductivity and pH of water on a large area) one can see at http://fenevo.narod.ru/maps/ec-maps.htm and http://fenevo.narod.ru/maps/ph-maps.htm. Basing on the map one can conclude mechanisms of formation of water mineralization in the area. Availability of GPS receivers and systems for easy measuring of chemical parameters can lead to neogeochemical revolution as GPS receivers have led to neogeographical. A great number of non-experts can share their geochemical results, forming huge amount of available geochemical data. It will help to falsify and visualize concepts of geochemistry and environmental chemistry and, maybe, develop new ones. Geophysical and biological data could be shared as well with the same advantages for corresponding sciences.

Visualization of High-Resolution LiDAR Topography in Google Earth

NASA Astrophysics Data System (ADS)

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

2009-12-01

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

Alternative Fuels Data Center: Fleet Applications for Vehicles

Science.gov Websites

Applications for Vehicles to someone by E-mail Share Alternative Fuels Data Center: Fleet Applications for Vehicles on Facebook Tweet about Alternative Fuels Data Center: Fleet Applications for Vehicles on Twitter Bookmark Alternative Fuels Data Center: Fleet Applications for Vehicles on Google

Interactive web-based mapping: bridging technology and data for health

PubMed Central

2011-01-01

Background The Community Health Information System (CHIS) online mapping system was first launched in 1998. Its overarching goal was to provide researchers, residents and organizations access to health related data reflecting the overall health and well-being of their communities within the Greater Houston area. In September 2009, initial planning and development began for the next generation of CHIS. The overarching goal for the new version remained to make health data easily accessible for a wide variety of research audiences. However, in the new version we specifically sought to make the CHIS truly interactive and give the user more control over data selection and reporting. Results In July 2011, a beta version of the next-generation of the application was launched. This next-generation is also a web based interactive mapping tool comprised of two distinct portals: the Breast Health Portal and Project Safety Net. Both are accessed via a Google mapping interface. Geographic coverage for the portals is currently an 8 county region centered on Harris County, Texas. Data accessed by the application include Census 2000, Census 2010 (underway), cancer incidence from the Texas Cancer Registry (TX Dept. of State Health Services), death data from Texas Vital Statistics, clinic locations for free and low-cost health services, along with service lists, hours of operation, payment options and languages spoken, uninsured and poverty data. Conclusions The system features query on the fly technology, which means the data is not generated until the query is provided to the system. This allows users to interact in real-time with the databases and generate customized reports and maps. To the author's knowledge, the Breast Health Portal and Project Safety Net are the first local-scale interactive online mapping interfaces for public health data which allow users to control the data generated. For example, users may generate breast cancer incidence rates by Census tract, in real time, for women aged 40-64. Conversely, they could then generate the same rates for women aged 35-55. The queries are user controlled. PMID:22195603

A Pyramid Scheme for Constructing Geologic Maps on Geobrowsers

NASA Astrophysics Data System (ADS)

Whitmeyer, S. J.; de Paor, D. G.; Daniels, J.; Jeremy, N.; Michael, R.; Santangelo, B.

2008-12-01

Hundreds of geologic maps have been draped onto Google Earth (GE) using the ground overlay tag of Keyhole Markup Language (KML) and dozens have been published on academic and survey web pages as downloadable KML or KMZ (zipped KML) files. The vast majority of these are small KML docs that link to single, large - often very large - image files (jpegs, tiffs, etc.) Files that exceed 50 MB in size defeat the purpose of GE as an interactive and responsive, and therefore fast, virtual terrain medium. KML supports super-overlays (a.k.a. image pyramids), which break large graphic files into manageable tiles that load only when they are in the visible region at a sufficient level of detail (LOD), and several automatic tile-generating applications have been written. The process of exporting map data from applications such as ArcGIS® to KML format is becoming more manageable but still poses challenges. Complications arise, for example, because of differences between grid-north at a point on a map and true north at the equivalent location on the virtual globe. In our recent field season, we devised ways of overcoming many of these obstacles in order to generate responsive, panable, zoomable geologic maps in which data is layered in a pyramid structure similar to the image pyramid used for default GE terrain. The structure of our KML code for each level of the pyramid is self-similar: (i) check whether the current tile is in the visible region, (ii) if so, render the current overlay, (iii) add the current data level, and (iv) using four network links, check the visibility and LOD of four nested tiles. By using this pyramid structure we provide the user with access to geologic and map data at multiple levels of observation. For example, when the viewpoint is distant, regional structures and stratigraphy (e.g. lithological groups and terrane boundaries) are visible. As the user zooms to lower elevations, formations and ultimately individual outcrops come into focus. The pyramid structure is ideally suited to geologic data which tends to be unevenly exposed across the earth's surface.

The Lunar Mapping and Modeling Project

NASA Technical Reports Server (NTRS)

Nall, M.; French, R.; Noble, S.; Muery, K.

2010-01-01

The Lunar Mapping and Modeling Project (LMMP) is managing a suite of lunar mapping and modeling tools and data products that support lunar exploration activities, including the planning, de-sign, development, test, and operations associated with crewed and/or robotic operations on the lunar surface. Although the project was initiated primarily to serve the needs of the Constellation program, it is equally suited for supporting landing site selection and planning for a variety of robotic missions, including NASA science and/or human precursor missions and commercial missions such as those planned by the Google Lunar X-Prize participants. In addition, LMMP should prove to be a convenient and useful tool for scientific analysis and for education and public out-reach (E/PO) activities.

A 50-m forest cover map in Southeast Asia from ALOS/PALSAR and its application on forest fragmentation assessment.

PubMed

Dong, Jinwei; Xiao, Xiangming; Sheldon, Sage; Biradar, Chandrashekhar; Zhang, Geli; Duong, Nguyen Dinh; Hazarika, Manzul; Wikantika, Ketut; Takeuhci, Wataru; Moore, Berrien

2014-01-01

Southeast Asia experienced higher rates of deforestation than other continents in the 1990s and still was a hotspot of forest change in the 2000s. Biodiversity conservation planning and accurate estimation of forest carbon fluxes and pools need more accurate information about forest area, spatial distribution and fragmentation. However, the recent forest maps of Southeast Asia were generated from optical images at spatial resolutions of several hundreds of meters, and they do not capture well the exceptionally complex and dynamic environments in Southeast Asia. The forest area estimates from those maps vary substantially, ranging from 1.73×10(6) km(2) (GlobCover) to 2.69×10(6) km(2) (MCD12Q1) in 2009; and their uncertainty is constrained by frequent cloud cover and coarse spatial resolution. Recently, cloud-free imagery from the Phased Array Type L-band Synthetic Aperture Radar (PALSAR) onboard the Advanced Land Observing Satellite (ALOS) became available. We used the PALSAR 50-m orthorectified mosaic imagery in 2009 to generate a forest cover map of Southeast Asia at 50-m spatial resolution. The validation, using ground-reference data collected from the Geo-Referenced Field Photo Library and high-resolution images in Google Earth, showed that our forest map has a reasonably high accuracy (producer's accuracy 86% and user's accuracy 93%). The PALSAR-based forest area estimates in 2009 are significantly correlated with those from GlobCover and MCD12Q1 at national and subnational scales but differ in some regions at the pixel scale due to different spatial resolutions, forest definitions, and algorithms. The resultant 50-m forest map was used to quantify forest fragmentation and it revealed substantial details of forest fragmentation. This new 50-m map of tropical forests could serve as a baseline map for forest resource inventory, deforestation monitoring, reducing emissions from deforestation and forest degradation (REDD+) implementation, and biodiversity.

A 50-m Forest Cover Map in Southeast Asia from ALOS/PALSAR and Its Application on Forest Fragmentation Assessment

PubMed Central

Dong, Jinwei; Xiao, Xiangming; Sheldon, Sage; Biradar, Chandrashekhar; Zhang, Geli; Dinh Duong, Nguyen; Hazarika, Manzul; Wikantika, Ketut; Takeuhci, Wataru; Moore, Berrien

2014-01-01

Southeast Asia experienced higher rates of deforestation than other continents in the 1990s and still was a hotspot of forest change in the 2000s. Biodiversity conservation planning and accurate estimation of forest carbon fluxes and pools need more accurate information about forest area, spatial distribution and fragmentation. However, the recent forest maps of Southeast Asia were generated from optical images at spatial resolutions of several hundreds of meters, and they do not capture well the exceptionally complex and dynamic environments in Southeast Asia. The forest area estimates from those maps vary substantially, ranging from 1.73×106 km2 (GlobCover) to 2.69×106 km2 (MCD12Q1) in 2009; and their uncertainty is constrained by frequent cloud cover and coarse spatial resolution. Recently, cloud-free imagery from the Phased Array Type L-band Synthetic Aperture Radar (PALSAR) onboard the Advanced Land Observing Satellite (ALOS) became available. We used the PALSAR 50-m orthorectified mosaic imagery in 2009 to generate a forest cover map of Southeast Asia at 50-m spatial resolution. The validation, using ground-reference data collected from the Geo-Referenced Field Photo Library and high-resolution images in Google Earth, showed that our forest map has a reasonably high accuracy (producer's accuracy 86% and user's accuracy 93%). The PALSAR-based forest area estimates in 2009 are significantly correlated with those from GlobCover and MCD12Q1 at national and subnational scales but differ in some regions at the pixel scale due to different spatial resolutions, forest definitions, and algorithms. The resultant 50-m forest map was used to quantify forest fragmentation and it revealed substantial details of forest fragmentation. This new 50-m map of tropical forests could serve as a baseline map for forest resource inventory, deforestation monitoring, reducing emissions from deforestation and forest degradation (REDD+) implementation, and biodiversity. PMID:24465714

Using Webgis and Cloud Tools to Promote Cultural Heritage Dissemination: the Historic up Project

NASA Astrophysics Data System (ADS)

Tommasi, A.; Cefalo, R.; Zardini, F.; Nicolaucig, M.

2017-05-01

On the occasion of the First World War centennial, GeoSNav Lab (Geodesy and Satellite Navigation Laboratory), Department of Engineering and Architecture, University of Trieste, Italy, in coooperation with Radici&Futuro Association, Trieste, Italy, carried out an educational Project named "Historic Up" involving a group of students from "F. Petrarca" High School of Trieste, Italy. The main goal of the project is to make available to students of Middle and High Schools a set of historical and cultural contents in a simple and immediate way, through the production of a virtual and interactive tour following the event that caused the burst of the First World War: the assassination of Franz Ferdinand and his wife Sofia in Sarajevo occurred on June 28, 1914. A set of Google Apps was used, including Google Earth, Maps, Tour Builder, Street View, Gmail, Drive, and Docs. The Authors instructed the students about software and team-working and supported them along the research. After being checked, all the historical and geographic data have been uploaded on a Google Tour Builder to create a sequence of historical checkpoints. Each checkpoint has texts, pictures and videos that connect the tour-users to 1914. Moreover, GeoSNaV Lab researchers produced a KML (Keyhole Markup Language) file, formed by several polylines and points, representing the itinerary of the funeral procession that has been superimposed on ad-hoc georeferenced historical maps. This tour, freely available online, starts with the arrival of the royals, on June 28th 1914, and follows the couple along the events, from the assassination to the burial in Arstetten (Austria), including their passages through Trieste (Italy), Ljubljana (Slovenia), Graz and Wien (Austria).

TumorMap: Exploring the Molecular Similarities of Cancer Samples in an Interactive Portal.

PubMed

Newton, Yulia; Novak, Adam M; Swatloski, Teresa; McColl, Duncan C; Chopra, Sahil; Graim, Kiley; Weinstein, Alana S; Baertsch, Robert; Salama, Sofie R; Ellrott, Kyle; Chopra, Manu; Goldstein, Theodore C; Haussler, David; Morozova, Olena; Stuart, Joshua M

2017-11-01

Vast amounts of molecular data are being collected on tumor samples, which provide unique opportunities for discovering trends within and between cancer subtypes. Such cross-cancer analyses require computational methods that enable intuitive and interactive browsing of thousands of samples based on their molecular similarity. We created a portal called TumorMap to assist in exploration and statistical interrogation of high-dimensional complex "omics" data in an interactive and easily interpretable way. In the TumorMap, samples are arranged on a hexagonal grid based on their similarity to one another in the original genomic space and are rendered with Google's Map technology. While the important feature of this public portal is the ability for the users to build maps from their own data, we pre-built genomic maps from several previously published projects. We demonstrate the utility of this portal by presenting results obtained from The Cancer Genome Atlas project data. Cancer Res; 77(21); e111-4. ©2017 AACR . ©2017 American Association for Cancer Research.

Map based multimedia tool on Pacific theatre in World War II

NASA Astrophysics Data System (ADS)

Pakala Venkata, Devi Prasada Reddy

Maps have been used for depicting data of all kinds in the educational community for many years. A standout amongst the rapidly changing methods of teaching is through the development of interactive and dynamic maps. The emphasis of the thesis is to develop an intuitive map based multimedia tool, which provides a timeline of battles and events in the Pacific theatre of World War II. The tool contains summaries of major battles and commanders and has multimedia content embedded in it. The primary advantage of this Map tool is that one can quickly know about all the battles and campaigns of the Pacific Theatre by accessing Timeline of Battles in each region or Individual Battles in each region or Summary of each Battle in an interactive way. This tool can be accessed via any standard web browser and motivate the user to know more about the battles involved in the Pacific Theatre. It was made responsive using Google maps API, JavaScript, HTML5 and CSS.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Planetary Data Systems (PDS) Imaging Node Atlas II

NASA Technical Reports Server (NTRS)

Stanboli, Alice; McAuley, James M.

2013-01-01

The Planetary Image Atlas (PIA) is a Rich Internet Application (RIA) that serves planetary imaging data to the science community and the general public. PIA also utilizes the USGS Unified Planetary Coordinate system (UPC) and the on-Mars map server. The Atlas was designed to provide the ability to search and filter through greater than 8 million planetary image files. This software is a three-tier Web application that contains a search engine backend (MySQL, JAVA), Web service interface (SOAP) between server and client, and a GWT Google Maps API client front end. This application allows for the search, retrieval, and download of planetary images and associated meta-data from the following missions: 2001 Mars Odyssey, Cassini, Galileo, LCROSS, Lunar Reconnaissance Orbiter, Mars Exploration Rover, Mars Express, Magellan, Mars Global Surveyor, Mars Pathfinder, Mars Reconnaissance Orbiter, MESSENGER, Phoe nix, Viking Lander, Viking Orbiter, and Voyager. The Atlas utilizes the UPC to translate mission-specific coordinate systems into a unified coordinate system, allowing the end user to query across missions of similar targets. If desired, the end user can also use a mission-specific view of the Atlas. The mission-specific views rely on the same code base. This application is a major improvement over the initial version of the Planetary Image Atlas. It is a multi-mission search engine. This tool includes both basic and advanced search capabilities, providing a product search tool to interrogate the collection of planetary images. This tool lets the end user query information about each image, and ignores the data that the user has no interest in. Users can reduce the number of images to look at by defining an area of interest with latitude and longitude ranges.

Integrating multi-omic features exploiting Chromosome Conformation Capture data.

PubMed

Merelli, Ivan; Tordini, Fabio; Drocco, Maurizio; Aldinucci, Marco; Liò, Pietro; Milanesi, Luciano

2015-01-01

The representation, integration, and interpretation of omic data is a complex task, in particular considering the huge amount of information that is daily produced in molecular biology laboratories all around the world. The reason is that sequencing data regarding expression profiles, methylation patterns, and chromatin domains is difficult to harmonize in a systems biology view, since genome browsers only allow coordinate-based representations, discarding functional clusters created by the spatial conformation of the DNA in the nucleus. In this context, recent progresses in high throughput molecular biology techniques and bioinformatics have provided insights into chromatin interactions on a larger scale and offer a formidable support for the interpretation of multi-omic data. In particular, a novel sequencing technique called Chromosome Conformation Capture allows the analysis of the chromosome organization in the cell's natural state. While performed genome wide, this technique is usually called Hi-C. Inspired by service applications such as Google Maps, we developed NuChart, an R package that integrates Hi-C data to describe the chromosomal neighborhood starting from the information about gene positions, with the possibility of mapping on the achieved graphs genomic features such as methylation patterns and histone modifications, along with expression profiles. In this paper we show the importance of the NuChart application for the integration of multi-omic data in a systems biology fashion, with particular interest in cytogenetic applications of these techniques. Moreover, we demonstrate how the integration of multi-omic data can provide useful information in understanding why genes are in certain specific positions inside the nucleus and how epigenetic patterns correlate with their expression.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Machine Learning for Flood Prediction in Google Earth Engine

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

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.

GIS Technologies For The New Planetary Science Archive (PSA)

NASA Astrophysics Data System (ADS)

Docasal, R.; Barbarisi, I.; Rios, C.; Macfarlane, A. J.; Gonzalez, J.; Arviset, C.; De Marchi, G.; Martinez, S.; Grotheer, E.; Lim, T.; Besse, S.; Heather, D.; Fraga, D.; Barthelemy, M.

2015-12-01

Geographical information system (GIS) is becoming increasingly used for planetary science. GIS are computerised systems for the storage, retrieval, manipulation, analysis, and display of geographically referenced data. Some data stored in the Planetary Science Archive (PSA), for instance, a set of Mars Express/Venus Express data, have spatial metadata associated to them. To facilitate users in handling and visualising spatial data in GIS applications, the new PSA should support interoperability with interfaces implementing the standards approved by the Open Geospatial Consortium (OGC). These standards are followed in order to develop open interfaces and encodings that allow data to be exchanged with GIS Client Applications, well-known examples of which are Google Earth and NASA World Wind as well as open source tools such as Openlayers. The technology already exists within PostgreSQL databases to store searchable geometrical data in the form of the PostGIS extension. An existing open source maps server is GeoServer, an instance of which has been deployed for the new PSA, uses the OGC standards to allow, among others, the sharing, processing and editing of data and spatial data through the Web Feature Service (WFS) standard as well as serving georeferenced map images through the Web Map Service (WMS). The final goal of the new PSA, being developed by the European Space Astronomy Centre (ESAC) Science Data Centre (ESDC), is to create an archive which enables science exploitation of ESA's planetary missions datasets. This can be facilitated through the GIS framework, offering interfaces (both web GUI and scriptable APIs) that can be used more easily and scientifically by the community, and that will also enable the community to build added value services on top of the PSA.

Towards Scalable Graph Computation on Mobile Devices.

PubMed

Chen, Yiqi; Lin, Zhiyuan; Pienta, Robert; Kahng, Minsuk; Chau, Duen Horng

2014-10-01

Mobile devices have become increasingly central to our everyday activities, due to their portability, multi-touch capabilities, and ever-improving computational power. Such attractive features have spurred research interest in leveraging mobile devices for computation. We explore a novel approach that aims to use a single mobile device to perform scalable graph computation on large graphs that do not fit in the device's limited main memory, opening up the possibility of performing on-device analysis of large datasets, without relying on the cloud. Based on the familiar memory mapping capability provided by today's mobile operating systems, our approach to scale up computation is powerful and intentionally kept simple to maximize its applicability across the iOS and Android platforms. Our experiments demonstrate that an iPad mini can perform fast computation on large real graphs with as many as 272 million edges (Google+ social graph), at a speed that is only a few times slower than a 13″ Macbook Pro. Through creating a real world iOS app with this technique, we demonstrate the strong potential application for scalable graph computation on a single mobile device using our approach.

Towards Scalable Graph Computation on Mobile Devices

PubMed Central

Chen, Yiqi; Lin, Zhiyuan; Pienta, Robert; Kahng, Minsuk; Chau, Duen Horng

2015-01-01

Mobile devices have become increasingly central to our everyday activities, due to their portability, multi-touch capabilities, and ever-improving computational power. Such attractive features have spurred research interest in leveraging mobile devices for computation. We explore a novel approach that aims to use a single mobile device to perform scalable graph computation on large graphs that do not fit in the device's limited main memory, opening up the possibility of performing on-device analysis of large datasets, without relying on the cloud. Based on the familiar memory mapping capability provided by today's mobile operating systems, our approach to scale up computation is powerful and intentionally kept simple to maximize its applicability across the iOS and Android platforms. Our experiments demonstrate that an iPad mini can perform fast computation on large real graphs with as many as 272 million edges (Google+ social graph), at a speed that is only a few times slower than a 13″ Macbook Pro. Through creating a real world iOS app with this technique, we demonstrate the strong potential application for scalable graph computation on a single mobile device using our approach. PMID:25859564

iAnn: an event sharing platform for the life sciences.

PubMed

Jimenez, Rafael C; Albar, Juan P; Bhak, Jong; Blatter, Marie-Claude; Blicher, Thomas; Brazas, Michelle D; Brooksbank, Cath; Budd, Aidan; De Las Rivas, Javier; Dreyer, Jacqueline; van Driel, Marc A; Dunn, Michael J; Fernandes, Pedro L; van Gelder, Celia W G; Hermjakob, Henning; Ioannidis, Vassilios; Judge, David P; Kahlem, Pascal; Korpelainen, Eija; Kraus, Hans-Joachim; Loveland, Jane; Mayer, Christine; McDowall, Jennifer; Moran, Federico; Mulder, Nicola; Nyronen, Tommi; Rother, Kristian; Salazar, Gustavo A; Schneider, Reinhard; Via, Allegra; Villaveces, Jose M; Yu, Ping; Schneider, Maria V; Attwood, Teresa K; Corpas, Manuel

2013-08-01

We present iAnn, an open source community-driven platform for dissemination of life science events, such as courses, conferences and workshops. iAnn allows automatic visualisation and integration of customised event reports. A central repository lies at the core of the platform: curators add submitted events, and these are subsequently accessed via web services. Thus, once an iAnn widget is incorporated into a website, it permanently shows timely relevant information as if it were native to the remote site. At the same time, announcements submitted to the repository are automatically disseminated to all portals that query the system. To facilitate the visualization of announcements, iAnn provides powerful filtering options and views, integrated in Google Maps and Google Calendar. All iAnn widgets are freely available. http://iann.pro/iannviewer manuel.corpas@tgac.ac.uk.

Alabama Public Scoping Meeting | NOAA Gulf Spill Restoration

Science.gov Websites

: Mobile, AL Start Time: 6:30 p.m. Central Time Description: As part of the public scoping process, the co open at 6:30 p.m. and the meeting will begin at 7:30 p.m. Location: The Battle House Renaissance Mobile Hotel & Spa 26 North Royal Street Mobile, AL 36602 (google map of location) Gulf Spill Restoration

Tactical Level Commander and Staff Toolkit

DTIC Science & Technology

2010-01-01

Sites Geodata.gov (for maps) http://gos2.geodata.gov Google Earth for .mil (United States Army Corps of Engineers (USACE) site) https...the eyes, ears, head, hands, back, and feet. When appropriate, personnel should wear protective lenses, goggles, or face shields . Leaders should...Typical hurricanes are about 300 miles wide, although they can vary considerably. Size is not necessarily an indication of hurricane intensity. The

Towards democracy in spatial planning through spatial information built by communities: The investigation of spatial information built by citizens from participatory mapping to volunteered geographic information in Indonesia

NASA Astrophysics Data System (ADS)

Yudono, Adipandang

2017-06-01

Recently, crowd-sourced information is used to produce and improve collective knowledge and community capacity building. Triggered by broadening and expanding access to the Internet and cellular telephones, the utilisation of crowd-sourcing for policy advocacy, e-government and e-participation has increased globally [1]. Crowd-sourced information can conceivably support government’s or general social initiatives to inform, counsel, and cooperate, by engaging subjects and empowering decentralisation and democratization [2]. Crowd-sourcing has turned into a major technique for interactive mapping initiatives by urban or rural community because of its capability to incorporate a wide range of data. Continuously accumulated spatial data can be sorted, layered, and envisioned in ways that even beginners can comprehend with ease. Interactive spatial visualization has the possibility to be a useful democratic planning tool to empower citizens participating in spatial data provision and sharing in government programmes. Since the global emergence of World Wide Web (WWW) technology, the interaction between information providers and users has increased. Local communities are able to produce and share spatial data to produce web interfaces with territorial information in mapping application programming interfaces (APIs) public, such as Google maps, OSM and Wikimapia [3][4][5]. In terms of the democratic spatial planning action, Volunteered Geographic Information (VGI) is considered an effective voluntary method of helping people feel comfortable with the technology and other co-participants in order to shape coalitions of local knowledge. This paper has aim to investigate ‘How is spatial data created by citizens used in Indonesia?’ by discussing the characteristics of spatial data usage by citizens to support spatial policy formulation, starting with the history of participatory mapping to current VGI development in Indonesia.

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.

Exploring U.S Cropland - A Web Service based Cropland Data Layer Visualization, Dissemination and Querying System (Invited)

NASA Astrophysics Data System (ADS)

Yang, Z.; Han, W.; di, L.

2010-12-01

The National Agricultural Statistics Service (NASS) of the USDA produces the Cropland Data Layer (CDL) product, which is a raster-formatted, geo-referenced, U.S. crop specific land cover classification. These digital data layers are widely used for a variety of applications by universities, research institutions, government agencies, and private industry in climate change studies, environmental ecosystem studies, bioenergy production & transportation planning, environmental health research and agricultural production decision making. The CDL is also used internally by NASS for crop acreage and yield estimation. Like most geospatial data products, the CDL product is only available by CD/DVD delivery or online bulk file downloading via the National Research Conservation Research (NRCS) Geospatial Data Gateway (external users) or in a printed paper map format. There is no online geospatial information access and dissemination, no crop visualization & browsing, no geospatial query capability, nor online analytics. To facilitate the application of this data layer and to help disseminating the data, a web-service based CDL interactive map visualization, dissemination, querying system is proposed. It uses Web service based service oriented architecture, adopts open standard geospatial information science technology and OGC specifications and standards, and re-uses functions/algorithms from GeoBrain Technology (George Mason University developed). This system provides capabilities of on-line geospatial crop information access, query and on-line analytics via interactive maps. It disseminates all data to the decision makers and users via real time retrieval, processing and publishing over the web through standards-based geospatial web services. A CDL region of interest can also be exported directly to Google Earth for mashup or downloaded for use with other desktop application. This web service based system greatly improves equal-accessibility, interoperability, usability, and data visualization, facilitates crop geospatial information usage, and enables US cropland online exploring capability without any client-side software installation. It also greatly reduces the need for paper map and analysis report printing and media usages, and thus enhances low-carbon Agro-geoinformation dissemination for decision support.

WebViz:A Web-based Collaborative Interactive Visualization System for large-Scale Data Sets

NASA Astrophysics Data System (ADS)

Yuen, D. A.; McArthur, E.; Weiss, R. M.; Zhou, J.; Yao, B.

2010-12-01

WebViz is a web-based application designed to conduct collaborative, interactive visualizations of large data sets for multiple users, allowing researchers situated all over the world to utilize the visualization services offered by the University of Minnesota’s Laboratory for Computational Sciences and Engineering (LCSE). This ongoing project has been built upon over the last 3 1/2 years .The motivation behind WebViz lies primarily with the need to parse through an increasing amount of data produced by the scientific community as a result of larger and faster multicore and massively parallel computers coming to the market, including the use of general purpose GPU computing. WebViz allows these large data sets to be visualized online by anyone with an account. The application allows users to save time and resources by visualizing data ‘on the fly’, wherever he or she may be located. By leveraging AJAX via the Google Web Toolkit (http://code.google.com/webtoolkit/), we are able to provide users with a remote, web portal to LCSE's (http://www.lcse.umn.edu) large-scale interactive visualization system already in place at the University of Minnesota. LCSE’s custom hierarchical volume rendering software provides high resolution visualizations on the order of 15 million pixels and has been employed for visualizing data primarily from simulations in astrophysics to geophysical fluid dynamics . In the current version of WebViz, we have implemented a highly extensible back-end framework built around HTTP "server push" technology. The web application is accessible via a variety of devices including netbooks, iPhones, and other web and javascript-enabled cell phones. Features in the current version include the ability for users to (1) securely login (2) launch multiple visualizations (3) conduct collaborative visualization sessions (4) delegate control aspects of a visualization to others and (5) engage in collaborative chats with other users within the user interface of the web application. These features are all in addition to a full range of essential visualization functions including 3-D camera and object orientation, position manipulation, time-stepping control, and custom color/alpha mapping.

Global 30m Height Above the Nearest Drainage

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Utility of Mobile phones to support In-situ data collection for Land Cover Mapping

NASA Astrophysics Data System (ADS)

Oduor, P.; Omondi, S.; Wahome, A.; Mugo, R. M.; Flores, A.

2017-12-01

With the compelling need to create better monitoring tools for our landscapes to enhance better decision making processes, it becomes imperative to do so in much more sophisticated yet simple ways. Making it possible to leverage untapped potential of our "lay men" at the same time enabling us to respond to the complexity of the information we have to get out. SERVIR Eastern and Southern Africa has developed a mobile app that can be utilized with very little prior knowledge or no knowledge at all to collect spatial information on land cover. This set of in-situ data can be collected by masses because the tools is very simple to use, and have this information fed in classification algorithms than can then be used to map out our ever changing landscape. The LULC Mapper is a subset of JiMap system and is able to pull the google earth imagery and open street maps to enable user familiarize with their location. It uses phone GPS, phone network information to map location coordinates and at the same time gives the user sample picture of what to categorize their landscape. The system is able to work offline and when user gets access to internet they can push the information into an amazon database as bulk data. The location details including geotagged photos allows the data to be used in development of a lot of spatial information including land cover data. The app is currently available in Google Play Store and will soon be uploaded on Appstore for utilization by a wider community. We foresee a lot of potential in this tool in terms of making data collection cheaper and affordable. Taking advantage of the advances made in phone technology. We envisage to do a data collection campaign where we can have the tool used for crowdsourcing.

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

NASA Astrophysics Data System (ADS)

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

2008-12-01

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

Processable Data Making in the Remote Server Sent by Android Phone as a GIS Data Collecting Tool

NASA Astrophysics Data System (ADS)

Karaagac, Abdullah; Bostancı, Bulent

2016-04-01

Mobile technologies are improving and getting cheaper everyday. Not only smart phones are improved much but also new types of mobile applications and sensors come with the smart phone together. Maps and navigation applications one of the most popular types of applications on these types. Most of these applications uses location services including GNSS, Wi Fi, cellular data and beacon services. Although these coordinate precision not very high, it is appropriate for many applications to utilize. Android is a mobile operating system based on Linux Kernel. It is compatible for varies mobile devices like smart phones, tablets, smart TV's, wearable technologies etc. Android has large capability for application development by using the open source libraries and device sensors like gyroscope, GNSS etc. Android Studio is the most popular integrated development environment (IDE) for Android devices, mainly developing by Google. It had been announced on May 16, 2013 at Google I/O conference. Android Studio is built upon Gradle architecture which is written in Java language. SQLite is a relational database operating system which has so common usage for mobile devices. It developed by using C programming library. It is mostly used via embedding into a software or application. It supports many operating systems including Android. Remote servers can be in several forms from high complexity to simplicity. For this project we will use a open source quad core board computer named Raspberry Pi 2. This device includes 900 MHz ARMv7 compatible quad core CPU, VideoCore IV GPU and 1 GB RAM. Although Raspberry Pi 2's main operating system is Raspbian, we use Debian which are both Linux based operating systems. Raspberry is compatible for many programming language, however some languages are optimized for this device. These are Python, Java, C, C++, Ruby, Perl and Squeak Smalltalk. In this paper, a mobile application will be developed to send coordinate and string data to a SQL database embedded to a remote server. The application will run on Android Operating System running mobile phone. The application will get the location information from the GNSS and cellular data. The user will enter the other information individually. These information will send by clicking a button to remote server which runs SQLite. All these informations will be convertible to any type of measure like type of coordinates could be converted from WGS 84 to ITRF.

Identification and Evaluation of Medical Translator Mobile Applications Using an Adapted APPLICATIONS Scoring System.

PubMed

Khander, Amrin; Farag, Sara; Chen, Katherine T

2017-12-22

With an increasing number of patients requiring translator services, many providers are turning to mobile applications (apps) for assistance. However, there have been no published reviews of medical translator apps. To identify and evaluate medical translator mobile apps using an adapted APPLICATIONS scoring system. A list of apps was identified from the Apple iTunes and Google Play stores, using the search term, "medical translator." Apps not found on two different searches, not in an English-based platform, not used for translation, or not functional after purchase, were excluded. The remaining apps were evaluated using an adapted APPLICATIONS scoring system, which included both objective and subjective criteria. App comprehensiveness was a weighted score defined by the number of non-English languages included in each app relative to the proportion of non-English speakers in the United States. The Apple iTunes and Google Play stores. Medical translator apps identified using the search term "medical translator." Main Outcomes and Measures: Compilation of medical translator apps for provider usage. A total of 524 apps were initially found. After applying the exclusion criteria, 20 (8.2%) apps from the Google Play store and 26 (9.2%) apps from the Apple iTunes store remained for evaluation. The highest scoring apps, Canopy Medical Translator, Universal Doctor Speaker, and Vocre Translate, scored 13.5 out of 18.7 possible points. A large proportion of apps initially found did not function as medical translator apps. Using the APPLICATIONS scoring system, we have identified and evaluated medical translator apps for providers who care for non-English speaking patients.

Interoperability In The New Planetary Science Archive (PSA)

NASA Astrophysics Data System (ADS)

Rios, C.; Barbarisi, I.; Docasal, R.; Macfarlane, A. J.; Gonzalez, J.; Arviset, C.; Grotheer, E.; Besse, S.; Martinez, S.; Heather, D.; De Marchi, G.; Lim, T.; Fraga, D.; Barthelemy, M.

2015-12-01

As the world becomes increasingly interconnected, there is a greater need to provide interoperability with software and applications that are commonly being used globally. For this purpose, the development of the new Planetary Science Archive (PSA), by the European Space Astronomy Centre (ESAC) Science Data Centre (ESDC), is focused on building a modern science archive that takes into account internationally recognised standards in order to provide access to the archive through tools from third parties, for example by the NASA Planetary Data System (PDS), the VESPA project from the Virtual Observatory of Paris as well as other international institutions. The protocols and standards currently being supported by the new Planetary Science Archive at this time are the Planetary Data Access Protocol (PDAP), the EuroPlanet-Table Access Protocol (EPN-TAP) and Open Geospatial Consortium (OGC) standards. The architecture of the PSA consists of a Geoserver (an open-source map server), the goal of which is to support use cases such as the distribution of search results, sharing and processing data through a OGC Web Feature Service (WFS) and a Web Map Service (WMS). This server also allows the retrieval of requested information in several standard output formats like Keyhole Markup Language (KML), Geography Markup Language (GML), shapefile, JavaScript Object Notation (JSON) and Comma Separated Values (CSV), among others. The provision of these various output formats enables end-users to be able to transfer retrieved data into popular applications such as Google Mars and NASA World Wind.

The Analysis Of Smartphone Apps In Geomatics Education

NASA Astrophysics Data System (ADS)

Teo, T.-A.; Wu, H.-M.; Shih, T.-Y.; Tsai, F.

2014-04-01

Geomatics is a discipline of collecting, processing and analysing geospatial data. Data collection is a core process of geomatics which usually adopt precise equipment to measure geospatial data. With the development of technology, a smartphone in this present era is not simply for communication; several low cost measurement devices such as Global Positioning System (GPS), gyro and camera are assembled in a smartphone. Although the devices assembled in a smartphone could not meet the needs of accuracy requirement for many geomatics applications, millions of mobile applications (Apps) can be downloaded and installed from Google Play and Apple Store freely, and a variety of sensors can be chosen for user. Considering that the popularity and convenience of a smartphone, and assuming that the accuracy of those collected data is acceptable for learning purposes, it is expected that a smartphone can be employed in geomatics for hand-on education. For example, Vespucci OSM Editor is an App to edit the OpenStreetMap on Android. The user may have the hand-on experience on GPS positioning, web services and mapping via Vespucci OSM Editor. The aim of this paper is to collect and analyze different Apps for geomatics education. The Apps are classified into four categories, namely, surveying, remote sensing, GPS and Geographic Information System (GIS). In this paper, more than 20 free Apps are collected and analysed for different hand-on studies in geomatics education. Finally, all the related Apps are listed on a website for updating.

There comes a baby! What should I do? Smartphones' pregnancy-related applications: A web-based overview.

PubMed

Bert, Fabrizio; Passi, Stefano; Scaioli, Giacomo; Gualano, Maria R; Siliquini, Roberta

2016-09-01

Our article aims to give an overview of the most mentioned smartphones' pregnancy-related applications (Apps). A keywords string with selected keywords was entered both in a general search engine (Google(®)) and PubMed. While PubMed returned no pertinent results, a total of 370 web pages were found on Google(®), and 146 of them were selected. All the pregnancy-related Apps cited at least eight times were included. Information about App's producer, price, contents, privacy policy, and presence of a scientific board was collected. Finally, nine apps were considered. The majority of them were free and available in the two main online markets (Apple(®) App Store and Android(®) Google Play). Five apps presented a privacy policy statement, while a scientific board was mentioned in only three. Further studies are needed in order to deepen the knowledge regarding the main risks of these devices, such as privacy loss, contents control concerns, the digital divide and a potential humanization reduction. © The Author(s) 2015.

Exchanging the Context between OGC Geospatial Web clients and GIS applications using Atom

NASA Astrophysics Data System (ADS)

Maso, Joan; Díaz, Paula; Riverola, Anna; Pons, Xavier

2013-04-01

Currently, the discovery and sharing of geospatial information over the web still presents difficulties. News distribution through website content was simplified by the use of Really Simple Syndication (RSS) and Atom syndication formats. This communication exposes an extension of Atom to redistribute references to geospatial information in a Spatial Data Infrastructure distributed environment. A geospatial client can save the status of an application that involves several OGC services of different kind and direct data and share this status with other users that need the same information and use different client vendor products in an interoperable way. The extensibility of the Atom format was essential to define a format that could be used in RSS enabled web browser, Mass Market map viewers and emerging geospatial enable integrated clients that support Open Geospatial Consortium (OGC) services. Since OWS Context has been designed as an Atom extension, it is possible to see the document in common places where Atom documents are valid. Internet web browsers are able to present the document as a list of items with title, abstract, time, description and downloading features. OWS Context uses GeoRSS so that, the document can be to be interpreted by both Google maps and Bing Maps as items that have the extent represented in a dynamic map. Another way to explode a OWS Context is to develop an XSLT to transform the Atom feed into an HTML5 document that shows the exact status of the client view window that saved the context document. To accomplish so, we use the width and height of the client window, and the extent of the view in world (geographic) coordinates in order to calculate the scale of the map. Then, we can mix elements in world coordinates (such as CF-NetCDF files or GML) with elements in pixel coordinates (such as WMS maps, WMTS tiles and direct SVG content). A smarter map browser application called MiraMon Map Browser is able to write a context document and read it again to recover the context of the previous view or load a context generated by another application. The possibility to store direct links to direct files in OWS Context is particularly interesting for GIS desktop solutions. This communication also presents the development made in the MiraMon desktop GIS solution to include OWS Context. MiraMon software is able to deal either with local files, web services and database connections. As in any other GIS solution, MiraMon team designed its own file (MiraMon Map MMM) for storing and sharing the status of a GIS session. The new OWS Context format is now adopted as an interoperable substitution of the MMM. The extensibility of the format makes it possible to map concepts in the MMM to current OWS Context elements (such as titles, data links, extent, etc) and to generate new elements that are able to include all extra metadata not currently covered by OWS Context. These developments were done in the nine edition of the OpenGIS Web Services Interoperability Experiment (OWS-9) and are demonstrated in this communication.

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

NASA Astrophysics Data System (ADS)

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

2008-12-01

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

The effectiveness of Google GLASS as a vital signs monitor in surgery: A simulation study.

PubMed

Iqbal, Mohammed Husnain; Aydin, Abdullatif; Lowdon, Alexandra; Ahmed, Hamza Ibn; Muir, Gordon H; Khan, M Shamim; Dasgupta, Prokar; Ahmed, Kamran

2016-12-01

To assess the effectiveness of the Google GLASS as a vital signs monitor in a surgical setting and identify potential uses. This prospective, observational and comparative study recruited novice (n = 24), intermediate (n = 8) and expert urologists (n = 5). All candidates performed a procedure on the GreenLight Simulator within a simulated setting using a standard vital signs monitor and then the Google GLASS. The time taken to respond to abnormal vital signs during both sessions was recorded. A quantitative survey was used to assess the usability and acceptability of the Google GLASS surgery. The majority (84%) of participants responded quicker to abnormal signs with the Google GLASS compared to a standard monitor (p = 0.0267). The average simulation score during a standard-monitor and GLASS-session scored to be statistically insignificant (p = 0.253). All parameters of simulation were also similar in both sessions including average sweep speed (p = 0.594), average blood loss (p = 0.761) and average grams vaporised (p = 0.102). Surgical performance between both sessions was similar and not hampered by the use of Google GLASS. Furthermore, 81% of candidates stated the GLASS was comfortable to wear during the procedure. This study has demonstrated that head-mounted displays such as the Google GLASS are potentially useful in surgery to aid patient care without hampering the surgeons view. It is hoped that the innovation and evolution of these devices triggers the potential future application of such devices within the medical field. Copyright © 2016 IJS Publishing Group Ltd. Published by Elsevier Ltd. All rights reserved.

A blinded assessment of video quality in wearable technology for telementoring in open surgery: the Google Glass experience.

PubMed

Hashimoto, Daniel A; Phitayakorn, Roy; Fernandez-del Castillo, Carlos; Meireles, Ozanan

2016-01-01

The goal of telementoring is to recreate face-to-face encounters with a digital presence. Open-surgery telementoring is limited by lack of surgeon's point-of-view cameras. Google Glass is a wearable computer that looks like a pair of glasses but is equipped with wireless connectivity, a camera, and viewing screen for video conferencing. This study aimed to assess the safety of using Google Glass by assessing the video quality of a telementoring session. Thirty-four (n = 34) surgeons at a single institution were surveyed and blindly compared via video captured with Google Glass versus an Apple iPhone 5 during the open cholecystectomy portion of a Whipple. Surgeons were asked to evaluate the quality of the video and its adequacy for safe use in telementoring. Thirty-four of 107 invited surgical attendings (32%) responded to the anonymous survey. A total of 50% rated the Google Glass video as fair with the other 50% rating it as bad to poor. A total of 52.9% of respondents rated the Apple iPhone video as good. A significantly greater proportion of respondents felt Google Glass video quality was inadequate for telementoring versus the Apple iPhone's (82.4 vs 26.5%, p < 0.0001). Intraclass correlation coefficient was 0.924 (95% CI 0.660-0.999, p < 0.001). While Google Glass provides a great breadth of functionality as a wearable device with two-way communication capabilities, current hardware limitations prevent its use as a telementoring device in surgery as the video quality is inadequate for safe telementoring. As the device is still in initial phases of development, future iterations or competitor devices may provide a better telementoring application for wearable devices.

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.

Medical applications of near-eye display devices: an exploratory study.

PubMed

Vorraber, Wolfgang; Voessner, Siegfried; Stark, Gerhard; Neubacher, Dietmar; DeMello, Steven; Bair, Aaron

2014-12-01

Near-eye display devices (such as Google Glass) may improve the efficiency and effectiveness of clinical care by giving clinicians information (such as the patient's vital signs) continuously within their field of vision during various procedures. We describe the use of Glass during a radiological intervention in three patients. Other possible applications (including tele-mentoring and the supervision of trainees) are discussed and a classification proposed. An app was developed to facilitate the use of Glass, so vital physical signs (pulse and blood pressure) could be projected on the near-eye display, via an intranet to protect sensitive data. The device was then used during radiological interventions (percutaneous transluminal angioplasty) in three patients, and assessed by the interventionalists who were interviewed before and after each procedure. The interventionalists reported that Google Glass improved concentration on the task in hand by reducing head and neck movements (which would be needed to view several remote monitors). However, heat generation by the device and low battery capacity are shortcomings for which solutions must be developed, and data protection is mandatory. Google Glass may have a number of clinical applications and can quicken interventions where vital signs or other visual data need to be monitored by the operator. Copyright © 2014 Surgical Associates Ltd. All rights reserved.

Extensible Probabilistic Repository Technology (XPRT)

DTIC Science & Technology

2004-10-01

projects, such as, Centaurus , Evidence Data Base (EDB), etc., others were fabricated, such as INS and FED, while others contain data from the open...Google Web Report Unlimited SOAP API News BBC News Unlimited WEB RSS 1.0 Centaurus Person Demographics 204,402 people from 240 countries...objects of the domain ontology map to the various simulated data-sources. For example, the PersonDemographics are stored in the Centaurus database, while

Reaching Forward in the War against the Islamic State

DTIC Science & Technology

2016-12-07

every week with U.S.- and Coalition-advised ISOF troops taking the lead in combat operations using cellular communications systems that link them...tions—Offline Maps, Google Earth , and Viber, to name a few—which allowed them to bring tablets and phones on their operations to help communicate ...provided an initial Remote Advise and Assist capability that enabled the special forces advisors to track, communicate , and share limited data with

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.

An intelligent and secure system for predicting and preventing Zika virus outbreak using Fog computing

NASA Astrophysics Data System (ADS)

Sareen, Sanjay; Gupta, Sunil Kumar; Sood, Sandeep K.

2017-10-01

Zika virus is a mosquito-borne disease that spreads very quickly in different parts of the world. In this article, we proposed a system to prevent and control the spread of Zika virus disease using integration of Fog computing, cloud computing, mobile phones and the Internet of things (IoT)-based sensor devices. Fog computing is used as an intermediary layer between the cloud and end users to reduce the latency time and extra communication cost that is usually found high in cloud-based systems. A fuzzy k-nearest neighbour is used to diagnose the possibly infected users, and Google map web service is used to provide the geographic positioning system (GPS)-based risk assessment to prevent the outbreak. It is used to represent each Zika virus (ZikaV)-infected user, mosquito-dense sites and breeding sites on the Google map that help the government healthcare authorities to control such risk-prone areas effectively and efficiently. The proposed system is deployed on Amazon EC2 cloud to evaluate its performance and accuracy using data set for 2 million users. Our system provides high accuracy of 94.5% for initial diagnosis of different users according to their symptoms and appropriate GPS-based risk assessment.

Northeast India Helminth Parasite Information Database (NEIHPID): Knowledge Base for Helminth Parasites

PubMed Central

Debnath, Manish; Kharumnuid, Graciously; Thongnibah, Welfrank; Tandon, Veena

2016-01-01

Most metazoan parasites that invade vertebrate hosts belong to three phyla: Platyhelminthes, Nematoda and Acanthocephala. Many of the parasitic members of these phyla are collectively known as helminths and are causative agents of many debilitating, deforming and lethal diseases of humans and animals. The North-East India Helminth Parasite Information Database (NEIHPID) project aimed to document and characterise the spectrum of helminth parasites in the north-eastern region of India, providing host, geographical distribution, diagnostic characters and image data. The morphology-based taxonomic data are supplemented with information on DNA sequences of nuclear, ribosomal and mitochondrial gene marker regions that aid in parasite identification. In addition, the database contains raw next generation sequencing (NGS) data for 3 foodborne trematode parasites, with more to follow. The database will also provide study material for students interested in parasite biology. Users can search the database at various taxonomic levels (phylum, class, order, superfamily, family, genus, and species), or by host, habitat and geographical location. Specimen collection locations are noted as co-ordinates in a MySQL database and can be viewed on Google maps, using Google Maps JavaScript API v3. The NEIHPID database has been made freely available at http://nepiac.nehu.ac.in/index.php PMID:27285615

HCLS 2.0/3.0: health care and life sciences data mashup using Web 2.0/3.0.

PubMed

Cheung, Kei-Hoi; Yip, Kevin Y; Townsend, Jeffrey P; Scotch, Matthew

2008-10-01

We describe the potential of current Web 2.0 technologies to achieve data mashup in the health care and life sciences (HCLS) domains, and compare that potential to the nascent trend of performing semantic mashup. After providing an overview of Web 2.0, we demonstrate two scenarios of data mashup, facilitated by the following Web 2.0 tools and sites: Yahoo! Pipes, Dapper, Google Maps and GeoCommons. In the first scenario, we exploited Dapper and Yahoo! Pipes to implement a challenging data integration task in the context of DNA microarray research. In the second scenario, we exploited Yahoo! Pipes, Google Maps, and GeoCommons to create a geographic information system (GIS) interface that allows visualization and integration of diverse categories of public health data, including cancer incidence and pollution prevalence data. Based on these two scenarios, we discuss the strengths and weaknesses of these Web 2.0 mashup technologies. We then describe Semantic Web, the mainstream Web 3.0 technology that enables more powerful data integration over the Web. We discuss the areas of intersection of Web 2.0 and Semantic Web, and describe the potential benefits that can be brought to HCLS research by combining these two sets of technologies.

Northeast India Helminth Parasite Information Database (NEIHPID): Knowledge Base for Helminth Parasites.

PubMed

Biswal, Devendra Kumar; Debnath, Manish; Kharumnuid, Graciously; Thongnibah, Welfrank; Tandon, Veena

2016-01-01

Most metazoan parasites that invade vertebrate hosts belong to three phyla: Platyhelminthes, Nematoda and Acanthocephala. Many of the parasitic members of these phyla are collectively known as helminths and are causative agents of many debilitating, deforming and lethal diseases of humans and animals. The North-East India Helminth Parasite Information Database (NEIHPID) project aimed to document and characterise the spectrum of helminth parasites in the north-eastern region of India, providing host, geographical distribution, diagnostic characters and image data. The morphology-based taxonomic data are supplemented with information on DNA sequences of nuclear, ribosomal and mitochondrial gene marker regions that aid in parasite identification. In addition, the database contains raw next generation sequencing (NGS) data for 3 foodborne trematode parasites, with more to follow. The database will also provide study material for students interested in parasite biology. Users can search the database at various taxonomic levels (phylum, class, order, superfamily, family, genus, and species), or by host, habitat and geographical location. Specimen collection locations are noted as co-ordinates in a MySQL database and can be viewed on Google maps, using Google Maps JavaScript API v3. The NEIHPID database has been made freely available at http://nepiac.nehu.ac.in/index.php.

High-Resolution Air Pollution Mapping with Google Street View Cars: Exploiting Big Data.

PubMed

Apte, Joshua S; Messier, Kyle P; Gani, Shahzad; Brauer, Michael; Kirchstetter, Thomas W; Lunden, Melissa M; Marshall, Julian D; Portier, Christopher J; Vermeulen, Roel C H; Hamburg, Steven P

2017-06-20

Air pollution affects billions of people worldwide, yet ambient pollution measurements are limited for much of the world. Urban air pollution concentrations vary sharply over short distances (≪1 km) owing to unevenly distributed emission sources, dilution, and physicochemical transformations. Accordingly, even where present, conventional fixed-site pollution monitoring methods lack the spatial resolution needed to characterize heterogeneous human exposures and localized pollution hotspots. Here, we demonstrate a measurement approach to reveal urban air pollution patterns at 4-5 orders of magnitude greater spatial precision than possible with current central-site ambient monitoring. We equipped Google Street View vehicles with a fast-response pollution measurement platform and repeatedly sampled every street in a 30-km 2 area of Oakland, CA, developing the largest urban air quality data set of its type. Resulting maps of annual daytime NO, NO 2 , and black carbon at 30 m-scale reveal stable, persistent pollution patterns with surprisingly sharp small-scale variability attributable to local sources, up to 5-8× within individual city blocks. Since local variation in air quality profoundly impacts public health and environmental equity, our results have important implications for how air pollution is measured and managed. If validated elsewhere, this readily scalable measurement approach could address major air quality data gaps worldwide.

HCLS 2.0/3.0: Health Care and Life Sciences Data Mashup Using Web 2.0/3.0

PubMed Central

Cheung, Kei-Hoi; Yip, Kevin Y.; Townsend, Jeffrey P.; Scotch, Matthew

2010-01-01

We describe the potential of current Web 2.0 technologies to achieve data mashup in the health care and life sciences (HCLS) domains, and compare that potential to the nascent trend of performing semantic mashup. After providing an overview of Web 2.0, we demonstrate two scenarios of data mashup, facilitated by the following Web 2.0 tools and sites: Yahoo! Pipes, Dapper, Google Maps and GeoCommons. In the first scenario, we exploited Dapper and Yahoo! Pipes to implement a challenging data integration task in the context of DNA microarray research. In the second scenario, we exploited Yahoo! Pipes, Google Maps, and GeoCommons to create a geographic information system (GIS) interface that allows visualization and integration of diverse categories of public health data, including cancer incidence and pollution prevalence data. Based on these two scenarios, we discuss the strengths and weaknesses of these Web 2.0 mashup technologies. We then describe Semantic Web, the mainstream Web 3.0 technology that enables more powerful data integration over the Web. We discuss the areas of intersection of Web 2.0 and Semantic Web, and describe the potential benefits that can be brought to HCLS research by combining these two sets of technologies. PMID:18487092

Open data mining for Taiwan's dengue epidemic.

PubMed

Wu, ChienHsing; Kao, Shu-Chen; Shih, Chia-Hung; Kan, Meng-Hsuan

2018-07-01

By using a quantitative approach, this study examines the applicability of data mining technique to discover knowledge from open data related to Taiwan's dengue epidemic. We compare results when Google trend data are included or excluded. Data sources are government open data, climate data, and Google trend data. Research findings from analysis of 70,914 cases are obtained. Location and time (month) in open data show the highest classification power followed by climate variables (temperature and humidity), whereas gender and age show the lowest values. Both prediction accuracy and simplicity decrease when Google trends are considered (respectively 0.94 and 0.37, compared to 0.96 and 0.46). The article demonstrates the value of open data mining in the context of public health care. Copyright © 2018 Elsevier B.V. All rights reserved.

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.

Mapping the Americanization of English in space and time

PubMed Central

Gonçalves, Bruno; Loureiro-Porto, Lucía; Ramasco, José J.

2018-01-01

As global political preeminence gradually shifted from the United Kingdom to the United States, so did the capacity to culturally influence the rest of the world. In this work, we analyze how the world-wide varieties of written English are evolving. We study both the spatial and temporal variations of vocabulary and spelling of English using a large corpus of geolocated tweets and the Google Books datasets corresponding to books published in the US and the UK. The advantage of our approach is that we can address both standard written language (Google Books) and the more colloquial forms of microblogging messages (Twitter). We find that American English is the dominant form of English outside the UK and that its influence is felt even within the UK borders. Finally, we analyze how this trend has evolved over time and the impact that some cultural events have had in shaping it. PMID:29799872

Mapping the Americanization of English in space and time.

PubMed

Gonçalves, Bruno; Loureiro-Porto, Lucía; Ramasco, José J; Sánchez, David

2018-01-01

As global political preeminence gradually shifted from the United Kingdom to the United States, so did the capacity to culturally influence the rest of the world. In this work, we analyze how the world-wide varieties of written English are evolving. We study both the spatial and temporal variations of vocabulary and spelling of English using a large corpus of geolocated tweets and the Google Books datasets corresponding to books published in the US and the UK. The advantage of our approach is that we can address both standard written language (Google Books) and the more colloquial forms of microblogging messages (Twitter). We find that American English is the dominant form of English outside the UK and that its influence is felt even within the UK borders. Finally, we analyze how this trend has evolved over time and the impact that some cultural events have had in shaping it.

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.

Soil erodibility mapping using the RUSLE model to prioritize erosion control in the Wadi Sahouat basin, North-West of Algeria.

PubMed

Toubal, Abderrezak Kamel; Achite, Mohammed; Ouillon, Sylvain; Dehni, Abdelatif

2018-03-12

Soil losses must be quantified over watersheds in order to set up protection measures against erosion. The main objective of this paper is to quantify and to map soil losses in the Wadi Sahouat basin (2140 km 2 ) in the north-west of Algeria, using the Revised Universal Soil Loss Equation (RUSLE) model assisted by a Geographic Information System (GIS) and remote sensing. The Model Builder of the GIS allowed the automation of the different operations for establishing thematic layers of the model parameters: the erosivity factor (R), the erodibility factor (K), the topographic factor (LS), the crop management factor (C), and the conservation support practice factor (P). The average annual soil loss rate in the Wadi Sahouat basin ranges from 0 to 255 t ha -1  year -1 , maximum values being observed over steep slopes of more than 25% and between 600 and 1000 m elevations. 3.4% of the basin is classified as highly susceptible to erosion, 4.9% with a medium risk, and 91.6% at a low risk. Google Earth reveals a clear conformity with the degree of zones to erosion sensitivity. Based on the soil loss map, 32 sub-basins were classified into three categories by priority of intervention: high, moderate, and low. This priority is available to sustain a management plan against sediment filling of the Ouizert dam at the basin outlet. The method enhancing the RUSLE model and confrontation with Google Earth can be easily adapted to other watersheds.

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

PubMed

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

2016-06-13

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

Evaluating Google, Twitter, and Wikipedia as Tools for Influenza Surveillance Using Bayesian Change Point Analysis: A Comparative Analysis.

PubMed

Sharpe, J Danielle; Hopkins, Richard S; Cook, Robert L; Striley, Catherine W

2016-10-20

Traditional influenza surveillance relies on influenza-like illness (ILI) syndrome that is reported by health care providers. It primarily captures individuals who seek medical care and misses those who do not. Recently, Web-based data sources have been studied for application to public health surveillance, as there is a growing number of people who search, post, and tweet about their illnesses before seeking medical care. Existing research has shown some promise of using data from Google, Twitter, and Wikipedia to complement traditional surveillance for ILI. However, past studies have evaluated these Web-based sources individually or dually without comparing all 3 of them, and it would be beneficial to know which of the Web-based sources performs best in order to be considered to complement traditional methods. The objective of this study is to comparatively analyze Google, Twitter, and Wikipedia by examining which best corresponds with Centers for Disease Control and Prevention (CDC) ILI data. It was hypothesized that Wikipedia will best correspond with CDC ILI data as previous research found it to be least influenced by high media coverage in comparison with Google and Twitter. Publicly available, deidentified data were collected from the CDC, Google Flu Trends, HealthTweets, and Wikipedia for the 2012-2015 influenza seasons. Bayesian change point analysis was used to detect seasonal changes, or change points, in each of the data sources. Change points in Google, Twitter, and Wikipedia that occurred during the exact week, 1 preceding week, or 1 week after the CDC's change points were compared with the CDC data as the gold standard. All analyses were conducted using the R package "bcp" version 4.0.0 in RStudio version 0.99.484 (RStudio Inc). In addition, sensitivity and positive predictive values (PPV) were calculated for Google, Twitter, and Wikipedia. During the 2012-2015 influenza seasons, a high sensitivity of 92% was found for Google, whereas the PPV for Google was 85%. A low sensitivity of 50% was calculated for Twitter; a low PPV of 43% was found for Twitter also. Wikipedia had the lowest sensitivity of 33% and lowest PPV of 40%. Of the 3 Web-based sources, Google had the best combination of sensitivity and PPV in detecting Bayesian change points in influenza-related data streams. Findings demonstrated that change points in Google, Twitter, and Wikipedia data occasionally aligned well with change points captured in CDC ILI data, yet these sources did not detect all changes in CDC data and should be further studied and developed.

Brain maps 4.0-Structure of the rat brain: An open access atlas with global nervous system nomenclature ontology and flatmaps.

PubMed

Swanson, Larry W

2018-04-15

The fourth edition (following editions in 1992, 1998, 2004) of Brain maps: structure of the rat brain is presented here as an open access internet resource for the neuroscience community. One new feature is a set of 10 hierarchical nomenclature tables that define and describe all parts of the rat nervous system within the framework of a strictly topographic system devised previously for the human nervous system. These tables constitute a global ontology for knowledge management systems dealing with neural circuitry. A second new feature is an aligned atlas of bilateral flatmaps illustrating rat nervous system development from the neural plate stage to the adult stage, where most gray matter regions, white matter tracts, ganglia, and nerves listed in the nomenclature tables are illustrated schematically. These flatmaps are convenient for future development of online applications analogous to "Google Maps" for systems neuroscience. The third new feature is a completely revised Atlas of the rat brain in spatially aligned transverse sections that can serve as a framework for 3-D modeling. Atlas parcellation is little changed from the preceding edition, but the nomenclature for rat is now aligned with an emerging panmammalian neuroanatomical nomenclature. All figures are presented in Adobe Illustrator vector graphics format that can be manipulated, modified, and resized as desired, and freely used with a Creative Commons license. © 2018 The Authors The Journal of Comparative Neurology Published by Wiley Periodicals, Inc.

Wikis and Collaborative Writing Applications in Health Care: A Scoping Review Protocol

PubMed Central

van de Belt, Tom H; Grajales III, Francisco J; Eysenbach, Gunther; Aubin, Karine; Gold, Irving; Gagnon, Marie-Pierre; Kuziemsky, Craig E; Turgeon, Alexis F; Poitras, Julien; Faber, Marjan J; Kremer, Jan A.M; Heldoorn, Marcel; Bilodeau, Andrea; Légaré, France

2012-01-01

The rapid rise in the use of collaborative writing applications (eg, wikis, Google Documents, and Google Knol) has created the need for a systematic synthesis of the evidence of their impact as knowledge translation (KT) tools in the health care sector and for an inventory of the factors that affect their use. While researchers have conducted systematic reviews on a range of software-based information and communication technologies as well as other social media (eg, virtual communities of practice, virtual peer-to-peer communities, and electronic support groups), none have reviewed collaborative writing applications in the medical sector. The overarching goal of this project is to explore the depth and breadth of evidence for the use of collaborative writing applications in health care. Thus, the purposes of this scoping review will be to (1) map the literature on collaborative writing applications; (2) compare the applications’ features; (3) describe the evidence of each application’s positive and negative effects as a KT intervention in health care; (4) inventory and describe the barriers and facilitators that affect the applications’ use; and (5) produce an action plan and a research agenda. A six-stage framework for scoping reviews will be used: (1) identifying the research question; (2) identifying relevant studies within the selected databases (using the EPPI-Reviewer software to classify the studies); (3) selecting studies (an iterative process in which two reviewers search the literature, refine the search strategy, and review articles for inclusion); (4) charting the data (using EPPI-Reviewer’s data-charting form); (5) collating, summarizing, and reporting the results (performing a descriptive, numerical, and interpretive synthesis); and (6) consulting knowledge users during three planned meetings. Since this scoping review concerns the use of collaborative writing applications as KT interventions in health care, we will use the Knowledge to Action (KTA) framework to describe and compare the various studies and collaborative writing projects we find. In addition to guiding the use of collaborative writing applications in health care, this scoping review will advance the science of KT by testing tools that could be used to evaluate other social media. We also expect to identify areas that require further systematic reviews and primary research and to produce a highly relevant research agenda that explores and leverages the potential of collaborative writing software. To date, this is the first study to use the KTA framework to study the role collaborative writing applications in KT, and the first to involve three national and international institutional knowledge users as part of the research process. PMID:23612481

A Grassroots Remote Sensing Toolkit Using Live Coding, Smartphones, Kites and Lightweight Drones

PubMed Central

Anderson, K.; Griffiths, D.; DeBell, L.; Hancock, S.; Duffy, J. P.; Shutler, J. D.; Reinhardt, W. J.; Griffiths, A.

2016-01-01

This manuscript describes the development of an android-based smartphone application for capturing aerial photographs and spatial metadata automatically, for use in grassroots mapping applications. The aim of the project was to exploit the plethora of on-board sensors within modern smartphones (accelerometer, GPS, compass, camera) to generate ready-to-use spatial data from lightweight aerial platforms such as drones or kites. A visual coding ‘scheme blocks’ framework was used to build the application (‘app’), so that users could customise their own data capture tools in the field. The paper reports on the coding framework, then shows the results of test flights from kites and lightweight drones and finally shows how open-source geospatial toolkits were used to generate geographical information system (GIS)-ready GeoTIFF images from the metadata stored by the app. Two Android smartphones were used in testing–a high specification OnePlus One handset and a lower cost Acer Liquid Z3 handset, to test the operational limits of the app on phones with different sensor sets. We demonstrate that best results were obtained when the phone was attached to a stable single line kite or to a gliding drone. Results show that engine or motor vibrations from powered aircraft required dampening to ensure capture of high quality images. We demonstrate how the products generated from the open-source processing workflow are easily used in GIS. The app can be downloaded freely from the Google store by searching for ‘UAV toolkit’ (UAV toolkit 2016), and used wherever an Android smartphone and aerial platform are available to deliver rapid spatial data (e.g. in supporting decision-making in humanitarian disaster-relief zones, in teaching or for grassroots remote sensing and democratic mapping). PMID:27144310

A Grassroots Remote Sensing Toolkit Using Live Coding, Smartphones, Kites and Lightweight Drones.

PubMed

Anderson, K; Griffiths, D; DeBell, L; Hancock, S; Duffy, J P; Shutler, J D; Reinhardt, W J; Griffiths, A

2016-01-01

This manuscript describes the development of an android-based smartphone application for capturing aerial photographs and spatial metadata automatically, for use in grassroots mapping applications. The aim of the project was to exploit the plethora of on-board sensors within modern smartphones (accelerometer, GPS, compass, camera) to generate ready-to-use spatial data from lightweight aerial platforms such as drones or kites. A visual coding 'scheme blocks' framework was used to build the application ('app'), so that users could customise their own data capture tools in the field. The paper reports on the coding framework, then shows the results of test flights from kites and lightweight drones and finally shows how open-source geospatial toolkits were used to generate geographical information system (GIS)-ready GeoTIFF images from the metadata stored by the app. Two Android smartphones were used in testing-a high specification OnePlus One handset and a lower cost Acer Liquid Z3 handset, to test the operational limits of the app on phones with different sensor sets. We demonstrate that best results were obtained when the phone was attached to a stable single line kite or to a gliding drone. Results show that engine or motor vibrations from powered aircraft required dampening to ensure capture of high quality images. We demonstrate how the products generated from the open-source processing workflow are easily used in GIS. The app can be downloaded freely from the Google store by searching for 'UAV toolkit' (UAV toolkit 2016), and used wherever an Android smartphone and aerial platform are available to deliver rapid spatial data (e.g. in supporting decision-making in humanitarian disaster-relief zones, in teaching or for grassroots remote sensing and democratic mapping).

Spatial confidentiality and GIS: re-engineering mortality locations from published maps about Hurricane Katrina.

PubMed

Curtis, Andrew J; Mills, Jacqueline W; Leitner, Michael

2006-10-10

Geographic Information Systems (GIS) can provide valuable insight into patterns of human activity. Online spatial display applications, such as Google Earth, can democratise this information by disseminating it to the general public. Although this is a generally positive advance for society, there is a legitimate concern involving the disclosure of confidential information through spatial display. Although guidelines exist for aggregated data, little has been written concerning the display of point level information. The concern is that a map containing points representing cases of cancer or an infectious disease, could be re-engineered back to identify an actual residence. This risk is investigated using point mortality locations from Hurricane Katrina re-engineered from a map published in the Baton Rouge Advocate newspaper, and a field team validating these residences using search and rescue building markings. We show that the residence of an individual, visualized as a generalized point covering approximately one and half city blocks on a map, can be re-engineered back to identify the actual house location, or at least a close neighbour, even if the map contains little spatial reference information. The degree of re-engineering success is also shown to depend on the urban characteristic of the neighborhood. The results in this paper suggest a need to re-evaluate current guidelines for the display of point (address level) data. Examples of other point maps displaying health data extracted from the academic literature are presented where a similar re-engineering approach might cause concern with respect to violating confidentiality. More research is also needed into the role urban structure plays in the accuracy of re-engineering. We suggest that health and spatial scientists should be proactive and suggest a series of point level spatial confidentiality guidelines before governmental decisions are made which may be reactionary toward the threat of revealing confidential information, thereby imposing draconian limits on research using a GIS.

Magnitude and extent of flooding at selected river reaches in western Washington, January 2009

USGS Publications Warehouse

Mastin, M.C.; Gendaszek, A.S.; Barnas, C.R.

2010-01-01

A narrow plume of warm, moist tropical air produced prolonged precipitation and melted snow in low-to-mid elevations throughout western Washington in January 2009. As a result, peak-of-record discharges occurred at many long-term streamflow-gaging stations in the region. A disaster was declared by the President for eight counties in Washington State and by May 2009, aid payments by the Federal Emergency Management Agency (FEMA) had exceeded $17 million. In an effort to document the flood and to obtain flood information that could be compared with simulated flood extents that are commonly prepared in conjunction with flood insurance studies by FEMA, eight stream reaches totaling 32.6 miles were selected by FEMA for inundation mapping. The U.S. Geological Survey?s Washington Water Science Center used a survey-grade global positioning system (GPS) the following summer to survey high-water marks (HWMs) left by the January 2009 flood at these reaches. A Google Maps (copyright) application was developed to display all HWM data on an interactive mapping tool on the project?s web site soon after the data were collected. Water-surface profiles and maps that display the area and depth of inundation were produced through a geographic information system (GIS) analysis that combined surveyed HWM elevations with Light Detection and Ranging (LiDAR)-derived digital elevation models of the study reaches and surrounding terrain. In several of the reaches, floods were well confined in their flood plains and were relatively straightforward to map. More common, however, were reaches with more complicated hydraulic geometries where widespread flooding resulted in flows that separated from the main channel. These proved to be more difficult to map, required subjective hydrologic judgment, and relied on supplementary information, such as aerial photographs and descriptions of the flooding from local landowners and government officials to obtain the best estimates of the extent of flooding.

Spatial confidentiality and GIS: re-engineering mortality locations from published maps about Hurricane Katrina

PubMed Central

Curtis, Andrew J; Mills, Jacqueline W; Leitner, Michael

2006-01-01

Background Geographic Information Systems (GIS) can provide valuable insight into patterns of human activity. Online spatial display applications, such as Google Earth, can democratise this information by disseminating it to the general public. Although this is a generally positive advance for society, there is a legitimate concern involving the disclosure of confidential information through spatial display. Although guidelines exist for aggregated data, little has been written concerning the display of point level information. The concern is that a map containing points representing cases of cancer or an infectious disease, could be re-engineered back to identify an actual residence. This risk is investigated using point mortality locations from Hurricane Katrina re-engineered from a map published in the Baton Rouge Advocate newspaper, and a field team validating these residences using search and rescue building markings. Results We show that the residence of an individual, visualized as a generalized point covering approximately one and half city blocks on a map, can be re-engineered back to identify the actual house location, or at least a close neighbour, even if the map contains little spatial reference information. The degree of re-engineering success is also shown to depend on the urban characteristic of the neighborhood. Conclusion The results in this paper suggest a need to re-evaluate current guidelines for the display of point (address level) data. Examples of other point maps displaying health data extracted from the academic literature are presented where a similar re-engineering approach might cause concern with respect to violating confidentiality. More research is also needed into the role urban structure plays in the accuracy of re-engineering. We suggest that health and spatial scientists should be proactive and suggest a series of point level spatial confidentiality guidelines before governmental decisions are made which may be reactionary toward the threat of revealing confidential information, thereby imposing draconian limits on research using a GIS. PMID:17032448

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Mobile Learning on the Basis of the Cloud Services

ERIC Educational Resources Information Center

Makarchuk, Tatyana

2017-01-01

Spreading of interactive applications for mobile devices became one of the trends of IT development in 2015-2017. In higher education mobile applications are being used to advance the productivity of professors and students, which raises the overall quality of education. In the article SkyDrive, GoogleDisk mobile applications' features for group…

Web-based visualization of gridded dataset usings OceanBrowser

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

Effects of Spatial Ability, Gender Differences, and Pictorial Training on Children Using 2-D and 3-D Environments to Recall Landmark Locations from Memory

ERIC Educational Resources Information Center

Kopcha, Theodore J.; Otumfuor, Beryl A.; Wang, Lu

2015-01-01

This study examines the effects of spatial ability, gender differences, and pictorial training on fourth grade students' ability to recall landmark locations from memory. Ninety-six students used Google Earth over a 3-week period to locate landmarks (3-D) and mark their location on a 2-D topographical map. Analysis of covariance on posttest scores…

VizieR Online Data Catalog: Orion Integral Filament ALMA+IRAM30m N2H+(1-0) data (Hacar+, 2018)

NASA Astrophysics Data System (ADS)

Hacar, A.; Tafalla, M.; Forbrich, J.; Alves, J.; Meingast, S.; Grossschedl, J.; Teixeira, P. S.

2018-01-01

Combined ALMA+IRAM30m large-scale N2H+(1-0) emission in the Orion ISF. Two datasets are presented here in FITS format: 1.- Full data cube: spectral resolution = 0.1 kms-1 2.- Total integrated line intensity (moment 0) map Units are in Jy/beam See also: https://sites.google.com/site/orion4dproject/home (2 data files).

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 Google Glass as an intraoperative intervention (27/31, 87%), whereas others observed its potential use in preoperative (4/31, 13%) and postoperative settings (5/31, 16%). Google Glass was utilized as a videography and photography device (21/31, 68%), a vital sign monitor (6/31, 19%), a surgical navigation display (5/31, 16%), and as a videoconferencing tool to communicate with remote surgeons intraoperatively (5/31, 16%). Most studies reported moderate or high acceptability of using Google Glass in surgical settings. The main reported limitations of using Google Glass utilization were short battery life (8/31, 26%) and difficulty with hands-free features (5/31, 16%). There are promising feasibility and usability data of using Google Glass in surgical settings with particular benefits for surgical education and training. Despite existing technical limitations, Google Glass was generally well received and several studies in surgical settings acknowledged its potential for training, consultation, patient monitoring, and audiovisual recording. ©Nancy J Wei, Bryn Dougherty, Aundria Myers, Sherif M Badawy. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 06.03.2018.

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 studies examined the potential use of Google Glass as an intraoperative intervention (27/31, 87%), whereas others observed its potential use in preoperative (4/31, 13%) and postoperative settings (5/31, 16%). Google Glass was utilized as a videography and photography device (21/31, 68%), a vital sign monitor (6/31, 19%), a surgical navigation display (5/31, 16%), and as a videoconferencing tool to communicate with remote surgeons intraoperatively (5/31, 16%). Most studies reported moderate or high acceptability of using Google Glass in surgical settings. The main reported limitations of using Google Glass utilization were short battery life (8/31, 26%) and difficulty with hands-free features (5/31, 16%). Conclusions There are promising feasibility and usability data of using Google Glass in surgical settings with particular benefits for surgical education and training. Despite existing technical limitations, Google Glass was generally well received and several studies in surgical settings acknowledged its potential for training, consultation, patient monitoring, and audiovisual recording. PMID:29510969

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

Research of cartographer laser SLAM algorithm

NASA Astrophysics Data System (ADS)

Xu, Bo; Liu, Zhengjun; Fu, Yiran; Zhang, Changsai

2017-11-01

As the indoor is a relatively closed and small space, total station, GPS, close-range photogrammetry technology is difficult to achieve fast and accurate indoor three-dimensional space reconstruction task. LIDAR SLAM technology does not rely on the external environment a priori knowledge, only use their own portable lidar, IMU, odometer and other sensors to establish an independent environment map, a good solution to this problem. This paper analyzes the Google Cartographer laser SLAM algorithm from the point cloud matching and closed loop detection. Finally, the algorithm is presented in the 3D visualization tool RViz from the data acquisition and processing to create the environment map, complete the SLAM technology and realize the process of indoor threedimensional space reconstruction

Integration of Bim, Web Maps and Iot for Supporting Comfort Analysis

NASA Astrophysics Data System (ADS)

Gunduz, M.; Isikdag, U.; Basaraner, M.

2017-11-01

The use of the Internet is expanding and the technological capabilities of electronic devices are evolving. Today, Internet of Things (IoT) solutions can be developed that were never even imaginable before. In this paper, a case study is presented on the joint use of Building Information Model (BIM), Geographical Information Systems (GIS) and Internet of Things (IoT) technologies. It is a part of an ongoing study that intends to overcome some problems about the management of complex facilities. In the study, a BIM has been converted and displayed in 2D on Google Maps, and information on various sensors have been represented on the web with geographic coordinates in real-time.

Use of Google Glass to Enhance Surgical Education of Neurosurgery Residents: "Proof-of-Concept" Study.

PubMed

Nakhla, Jonathan; Kobets, Andrew; De la Garza Ramos, Rafeal; Haranhalli, Neil; Gelfand, Yaroslav; Ammar, Adam; Echt, Murray; Scoco, Aleka; Kinon, Merritt; Yassari, Reza

2017-02-01

The relatively decreased time spent in the operating room and overall reduction in cases performed by neurosurgical trainees as a result of duty-hour restrictions demands that the pedagogical content within each surgical encounter be maximized and crafted toward the specific talents and shortcomings of the individual. It is imperative to future generations that the quality of training adapts to the changing administrative infrastructures and compensates for anything that may compromise the technical abilities of trainees. Neurosurgeons in teaching hospitals continue to experiment with various emerging technologies-such as simulators and virtual presence-to supplement and improve surgical training. The authors participated in the Google Glass Explorer Program in order to assess the applicability of Google Glass as a tool to enhance the operative education of neurosurgical residents. Google Glass is a type of wearable technology in the form of eyeglasses that employs a high-definition camera and allows the user to interact using voice commands. Google Glass was able to effectively capture video segments of various lengths for residents to review in a variety of clinical settings within a large, tertiary care university hospital, as well as during a surgical mission to a developing country. The resolution and quality of the video were adequate to review and use as a teaching tool. While Google Glass harbors the potential to dramatically improve both neurosurgical education and practice in a variety of ways, certain technical drawbacks of the current model limit its effectiveness as a teaching tool. Copyright © 2016 Elsevier Inc. All rights reserved.

Student computer attitudes, experience and perceptions about the use of two software applications in Building Engineering

NASA Astrophysics Data System (ADS)

Chiner, Esther; Garcia-Vera, Victoria E.

2017-11-01

The purpose of this study was to examine students' computer attitudes and experience, as well as students' perceptions about the use of two specific software applications (Google Drive Spreadsheets and Arquimedes) in the Building Engineering context. The relationships among these variables were also examined. Ninety-two students took part in this study. Results suggest that students hold favourable computer attitudes. Moreover, it was found a significant positive relationship among students' attitudes and their computer experience. Findings also show that students find Arquimedes software more useful and with higher output quality than Google Drive Spreadsheets, while the latter is perceived to be easier to use. Regarding the relationship among students' attitudes towards the use of computers and their perceptions about the use of both software applications, only a significant positive relationship in the case of Arquimedes was found. Findings are discussed in terms of its implications for practice and further research.

Incorporating Community Knowledge to Lahar Hazard Maps: Canton Buenos Aires Case Study, at Santa Ana (Ilamatepec) Volcano

NASA Astrophysics Data System (ADS)

Bajo, J. V.; Martinez-Hackert, B.; Polio, C.; Gutierrez, E.

2015-12-01

Santa Ana (Ilamatepec) Volcano is an active composite volcano located in the Apaneca Volcanic Field located in western part of El Salvador, Central America. The volcano is surrounded by rural communities in its proximal areas and the second (Santa Ana, 13 km) and fourth (Sonsosante, 15 km) largest cities of the country. On October 1st, 2005, the volcano erupted after months of increased activity. Following the eruption, volcanic mitigation projects were conducted in the region, but the communities had little or no input on them. This project consisted in the creation of lahar volcanic hazard map for the Canton Buanos Aires on the northern part of the volcano by incorporating the community's knowledge from prior events to model parameters and results. The work with the community consisted in several meetings where the community members recounted past events. They were asked to map the outcomes of those events using either a topographic map of the area, a Google Earth image, or a blank paper poster size. These maps have been used to identify hazard and vulnerable areas, and for model validation. These maps were presented to the communities and they accepted their results and the maps.

NaviCell Web Service for network-based data visualization.

PubMed

Bonnet, Eric; Viara, Eric; Kuperstein, Inna; Calzone, Laurence; Cohen, David P A; Barillot, Emmanuel; Zinovyev, Andrei

2015-07-01

Data visualization is an essential element of biological research, required for obtaining insights and formulating new hypotheses on mechanisms of health and disease. NaviCell Web Service is a tool for network-based visualization of 'omics' data which implements several data visual representation methods and utilities for combining them together. NaviCell Web Service uses Google Maps and semantic zooming to browse large biological network maps, represented in various formats, together with different types of the molecular data mapped on top of them. For achieving this, the tool provides standard heatmaps, barplots and glyphs as well as the novel map staining technique for grasping large-scale trends in numerical values (such as whole transcriptome) projected onto a pathway map. The web service provides a server mode, which allows automating visualization tasks and retrieving data from maps via RESTful (standard HTTP) calls. Bindings to different programming languages are provided (Python and R). We illustrate the purpose of the tool with several case studies using pathway maps created by different research groups, in which data visualization provides new insights into molecular mechanisms involved in systemic diseases such as cancer and neurodegenerative diseases. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Eye Tracking to Explore the Impacts of Photorealistic 3d Representations in Pedstrian Navigation Performance

NASA Astrophysics Data System (ADS)

Dong, Weihua; Liao, Hua

2016-06-01

Despite the now-ubiquitous two-dimensional (2D) maps, photorealistic three-dimensional (3D) representations of cities (e.g., Google Earth) have gained much attention by scientists and public users as another option. However, there is no consistent evidence on the influences of 3D photorealism on pedestrian navigation. Whether 3D photorealism can communicate cartographic information for navigation with higher effectiveness and efficiency and lower cognitive workload compared to the traditional symbolic 2D maps remains unknown. This study aims to explore whether the photorealistic 3D representation can facilitate processes of map reading and navigation in digital environments using a lab-based eye tracking approach. Here we show the differences of symbolic 2D maps versus photorealistic 3D representations depending on users' eye-movement and navigation behaviour data. We found that the participants using the 3D representation were less effective, less efficient and were required higher cognitive workload than using the 2D map for map reading. However, participants using the 3D representation performed more efficiently in self-localization and orientation at the complex decision points. The empirical results can be helpful to improve the usability of pedestrian navigation maps in future designs.

NaviCell Web Service for network-based data visualization

PubMed Central

Bonnet, Eric; Viara, Eric; Kuperstein, Inna; Calzone, Laurence; Cohen, David P. A.; Barillot, Emmanuel; Zinovyev, Andrei

2015-01-01

Data visualization is an essential element of biological research, required for obtaining insights and formulating new hypotheses on mechanisms of health and disease. NaviCell Web Service is a tool for network-based visualization of ‘omics’ data which implements several data visual representation methods and utilities for combining them together. NaviCell Web Service uses Google Maps and semantic zooming to browse large biological network maps, represented in various formats, together with different types of the molecular data mapped on top of them. For achieving this, the tool provides standard heatmaps, barplots and glyphs as well as the novel map staining technique for grasping large-scale trends in numerical values (such as whole transcriptome) projected onto a pathway map. The web service provides a server mode, which allows automating visualization tasks and retrieving data from maps via RESTful (standard HTTP) calls. Bindings to different programming languages are provided (Python and R). We illustrate the purpose of the tool with several case studies using pathway maps created by different research groups, in which data visualization provides new insights into molecular mechanisms involved in systemic diseases such as cancer and neurodegenerative diseases. PMID:25958393

GeoSearch: a new virtual globe application for the submission, storage, and sharing of point-based ecological data

NASA Astrophysics Data System (ADS)

Cardille, J. A.; Gonzales, R.; Parrott, L.; Bai, J.

2009-12-01

How should researchers store and share data? For most of history, scientists with results and data to share have been mostly limited to books and journal articles. In recent decades, the advent of personal computers and shared data formats has made it feasible, though often cumbersome, to transfer data between individuals or among small groups. Meanwhile, the use of automatic samplers, simulation models, and other data-production techniques has increased greatly. The result is that there is more and more data to store, and a greater expectation that they will be available at the click of a button. In 10 or 20 years, will we still send emails to each other to learn about what data exist? The development and widespread familiarity with virtual globes like Google Earth and NASA WorldWind has created the potential, in just the last few years, to revolutionize the way we share data, search for and search through data, and understand the relationship between individual projects in research networks, where sharing and dissemination of knowledge is encouraged. For the last two years, we have been building the GeoSearch application, a cutting-edge online resource for the storage, sharing, search, and retrieval of data produced by research networks. Linking NASA’s WorldWind globe platform, the data browsing toolkit prefuse, and SQL databases, GeoSearch’s version 1.0 enables flexible searches and novel geovisualizations of large amounts of related scientific data. These data may be submitted to the database by individual researchers and processed by GeoSearch’s data parser. Ultimately, data from research groups gathered in a research network would be shared among users via the platform. Access is not limited to the scientists themselves; administrators can determine which data can be presented publicly and which require group membership. Under the auspices of the Canada’s Sustainable Forestry Management Network of Excellence, we have created a moderate-sized database of ecological measurements in forests; we expect to extend the approach to a Quebec lake research network encompassing decades of lake measurements. In this session, we will describe and present four related components of the new system: GeoSearch’s globe-based searching and display of scientific data; prefuse-based visualization of social connections among members of a scientific research network; geolocation of research projects using Google Spreadsheets, KML, and Google Earth/Maps; and collaborative construction of a geolocated database of research articles. Each component is designed to have applications for scientists themselves as well as the general public. Although each implementation is in its infancy, we believe they could be useful to other researcher networks.

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.

Next Generation Landsat Products Delivered Using Virtual Globes and OGC Standard Services

NASA Astrophysics Data System (ADS)

Neiers, M.; Dwyer, J.; Neiers, S.

2008-12-01

The Landsat Data Continuity Mission (LDCM) is the next in the series of Landsat satellite missions and is tasked with the objective of delivering data acquired by the Operational Land Imager (OLI). The OLI instrument will provide data continuity to over 30 years of global multispectral data collected by the Landsat series of satellites. The U.S. Geological Survey Earth Resources Observation and Science (USGS EROS) Center has responsibility for the development and operation of the LDCM ground system. One of the mission objectives of the LDCM is to distribute OLI data products electronically over the Internet to the general public on a nondiscriminatory basis and at no cost. To ensure the user community and general public can easily access LDCM data from multiple clients, the User Portal Element (UPE) of the LDCM ground system will use OGC standards and services such as Keyhole Markup Language (KML), Web Map Service (WMS), Web Coverage Service (WCS), and Geographic encoding of Really Simple Syndication (GeoRSS) feeds for both access to and delivery of LDCM products. The USGS has developed and tested the capabilities of several successful UPE prototypes for delivery of Landsat metadata, full resolution browse, and orthorectified (L1T) products from clients such as Google Earth, Google Maps, ESRI ArcGIS Explorer, and Microsoft's Virtual Earth. Prototyping efforts included the following services: using virtual globes to search the historical Landsat archive by dynamic generation of KML; notification of and access to new Landsat acquisitions and L1T downloads from GeoRSS feeds; Google indexing of KML files containing links to full resolution browse and data downloads; WMS delivery of reduced resolution browse, full resolution browse, and cloud mask overlays; and custom data downloads using WCS clients. These various prototypes will be demonstrated and LDCM service implementation plans will be discussed during this session.

Smartphone and GPS technology for free-roaming dog population surveillance - a methodological study.

PubMed

Barnard, Shanis; Ippoliti, Carla; Di Flaviano, Daniele; De Ruvo, Andrea; Messori, Stefano; Giovannini, Armando; Dalla Villa, Paolo

2015-01-01

Free-roaming dogs (FRD) represent a potential threat to the quality of life in cities from an ecological, social and public health point of view. One of the most urgent concerns is the role of uncontrolled dogs as reservoirs of infectious diseases transmittable to humans and, above all, rabies. An estimate of the FRD population size and characteristics in a given area is the first step for any relevant intervention programme. Direct count methods are still prominent because of their non-invasive approach, information technologies can support such methods facilitating data collection and allowing for a more efficient data handling. This paper presents a new framework for data collection using a topological algorithm implemented as ArcScript in ESRI® ArcGIS software, which allows for a random selection of the sampling areas. It also supplies a mobile phone application for Android® operating system devices which integrates Global Positioning System (GPS) and Google MapsTM. The potential of such a framework was tested in 2 Italian regions. Coupling technological and innovative solutions associated with common counting methods facilitate data collection and transcription. It also paves the way to future applications, which could support dog population management systems.

Infusion of Climate Change and Geospatial Science Concepts into Environmental and Biological Science Curriculum

NASA Astrophysics Data System (ADS)

Balaji Bhaskar, M. S.; Rosenzweig, J.; Shishodia, S.

2017-12-01

The objective of our activity is to improve the students understanding and interpretation of geospatial science and climate change concepts and its applications in the field of Environmental and Biological Sciences in the College of Science Engineering and Technology (COEST) at Texas Southern University (TSU) in Houston, TX. The courses of GIS for Environment, Ecology and Microbiology were selected for the curriculum infusion. A total of ten GIS hands-on lab modules, along with two NCAR (National Center for Atmospheric Research) lab modules on climate change were implemented in the "GIS for Environment" course. GIS and Google Earth Labs along with climate change lectures were infused into Microbiology and Ecology courses. Critical thinking and empirical skills of the students were assessed in all the courses. The student learning outcomes of these courses includes the ability of students to interpret the geospatial maps and the student demonstration of knowledge of the basic principles and concepts of GIS (Geographic Information Systems) and climate change. At the end of the courses, students developed a comprehensive understanding of the geospatial data, its applications in understanding climate change and its interpretation at the local and regional scales during multiple years.

Bedrock geologic map of the Uxbridge quadrangle, Worcester County, Massachusetts, and Providence County, Rhode Island

USGS Publications Warehouse

Walsh, Gregory J.

2014-01-01

The bedrock geology of the 7.5-minute Uxbridge quadrangle consists of Neoproterozoic metamorphic and igneous rocks of the Avalon zone. In this area, rocks of the Avalon zone lie within the core of the Milford antiform, south and east of the terrane-bounding Bloody Bluff fault zone. Permian pegmatite dikes and quartz veins occur throughout the quadrangle. The oldest metasedimentary rocks include the Blackstone Group, which represents a Neoproterozoic peri-Gondwanan marginal shelf sequence. The metasedimentary rocks are intruded by Neoproterozoic arc-related plutonic rocks of the Rhode Island batholith. This report presents mapping by G.J. Walsh. The complete report consists of a map, text pamphlet, and GIS database. The map and text pamphlet are available only as downloadable files (see frame at right). The GIS database is available for download in ESRI™ shapefile and Google Earth™ formats, and includes contacts of bedrock geologic units, faults, outcrops, structural geologic information, geochemical data, and photographs.

Mapping 2000 2010 Impervious Surface Change in India Using Global Land Survey Landsat Data

NASA Technical Reports Server (NTRS)

Wang, Panshi; Huang, Chengquan; Brown De Colstoun, Eric C.

2017-01-01

Understanding and monitoring the environmental impacts of global urbanization requires better urban datasets. Continuous field impervious surface change (ISC) mapping using Landsat data is an effective way to quantify spatiotemporal dynamics of urbanization. It is well acknowledged that Landsat-based estimation of impervious surface is subject to seasonal and phenological variations. The overall goal of this paper is to map 200-02010 ISC for India using Global Land Survey datasets and training data only available for 2010. To this end, a method was developed that could transfer the regression tree model developed for mapping 2010 impervious surface to 2000 using an iterative training and prediction (ITP) approach An independent validation dataset was also developed using Google Earth imagery. Based on the reference ISC from the validation dataset, the RMSE of predicted ISC was estimated to be 18.4%. At 95% confidence, the total estimated ISC for India between 2000 and 2010 is 2274.62 +/- 7.84 sq km.

Community context and sub-neighborhood scale detail to explain dengue, chikungunya and Zika patterns in Cali, Colombia.

PubMed

Krystosik, Amy R; Curtis, Andrew; Buritica, Paola; Ajayakumar, Jayakrishnan; Squires, Robert; Dávalos, Diana; Pacheco, Robinson; Bhatta, Madhav P; James, Mark A

2017-01-01

Cali, Colombia has experienced chikungunya and Zika outbreaks and hypoendemic dengue. Studies have explained Cali's dengue patterns but lack the sub-neighborhood-scale detail investigated here. Spatial-video geonarratives (SVG) with Ministry of Health officials and Community Health Workers were collected in hotspots, providing perspective on perceptions of why dengue, chikungunya and Zika hotspots exist, impediments to control, and social outcomes. Using spatial video and Google Street View, sub-neighborhood features possibly contributing to incidence were mapped to create risk surfaces, later compared with dengue, chikungunya and Zika case data. SVG captured insights in 24 neighborhoods. Trash and water risks in Calipso were mapped using SVG results. Perceived risk factors included proximity to standing water, canals, poverty, invasions, localized violence and military migration. These risks overlapped case density maps and identified areas that are suitable for transmission but are possibly underreporting to the surveillance system. Resulting risk maps with local context could be leveraged to increase vector-control efficiency- targeting key areas of environmental risk.

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

NASA Astrophysics Data System (ADS)

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

2007-12-01

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

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

NASA Astrophysics Data System (ADS)

Herwig, C.

2017-12-01

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

Relating genes to function: identifying enriched transcription factors using the ENCODE ChIP-Seq significance tool.

PubMed

Auerbach, Raymond K; Chen, Bin; Butte, Atul J

2013-08-01

Biological analysis has shifted from identifying genes and transcripts to mapping these genes and transcripts to biological functions. The ENCODE Project has generated hundreds of ChIP-Seq experiments spanning multiple transcription factors and cell lines for public use, but tools for a biomedical scientist to analyze these data are either non-existent or tailored to narrow biological questions. We present the ENCODE ChIP-Seq Significance Tool, a flexible web application leveraging public ENCODE data to identify enriched transcription factors in a gene or transcript list for comparative analyses. The ENCODE ChIP-Seq Significance Tool is written in JavaScript on the client side and has been tested on Google Chrome, Apple Safari and Mozilla Firefox browsers. Server-side scripts are written in PHP and leverage R and a MySQL database. The tool is available at http://encodeqt.stanford.edu. abutte@stanford.edu Supplementary material is available at Bioinformatics online.

Diffusion MRI at 25: Exploring brain tissue structure and function

PubMed Central

Bihan, Denis Le; Johansen-Berg, Heidi

2013-01-01

Diffusion MRI (or dMRI) came into existence in the mid-1980s. During the last 25 years, diffusion MRI has been extraordinarily successful (with more than 300,000 entries on Google Scholar for diffusion MRI). Its main clinical domain of application has been neurological disorders, especially for the management of patients with acute stroke. It is also rapidly becoming a standard for white matter disorders, as diffusion tensor imaging (DTI) can reveal abnormalities in white matter fiber structure and provide outstanding maps of brain connectivity. The ability to visualize anatomical connections between different parts of the brain, non-invasively and on an individual basis, has emerged as a major breakthrough for neurosciences. The driving force of dMRI is to monitor microscopic, natural displacements of water molecules that occur in brain tissues as part of the physical diffusion process. Water molecules are thus used as a probe that can reveal microscopic details about tissue architecture, either normal or in a diseased state. PMID:22120012

Development of Web-Based Learning Application for Generation Z

ERIC Educational Resources Information Center

Hariadi, Bambang; Dewiyani Sunarto, M. J.; Sudarmaningtyas, Pantjawati

2016-01-01

This study aimed to develop a web-based learning application as a form of learning revolution. The form of learning revolution includes the provision of unlimited teaching materials, real time class organization, and is not limited by time or place. The implementation of this application is in the form of hybrid learning by using Google Apps for…

Distribution of the Population at Risk of Cholangiocarcinoma in Bua Yai District, Nakhon Ratchasima of Thailand Using Google Map.

PubMed

Kaewpitoon, Soraya J; Rujirakul, Ratana; Sangkudloa, Amnat; Kaewthani, Sarochinee; Khemplila, Kritsakorn; Cherdjirapong, Karuna; Kujapun, Jirawoot; Norkaew, Jun; Chavengkun, Wasugree; Ponphimai, Sukanya; Polsripradist, Poowadol; Padchasuwan, Natnapa; Joosiri, Apinya; Wakkhuwattapong, Parichart; Loyd, Ryan A; Matrakool, Likit; Tongtawee, Taweesak; Panpimanmas, Sukij; Kaewpitoon, Natthawut

2016-01-01

Cholangiocarcinoma (CCA), a major problem of health in Thailand, particularly in Northeastern and Northern regions, is generally incurable and rapidly lethal because of presentation in stage 3 or 4. Early diagnosis of stage 1 and 2 could allow better survival. Therefore, this study aimed to provide a distribution map of populations at risk for CCA in BuaYai district of Nakhon Ratchasima province, Northeast Thailand. A cross-sectional survey was carried out in 10 sub-districts and 122 villages, during June and November 2015. The populations at risk for CCA were screened using the Korat CCA verbal screening test (KCVST) and then risk areas were displayed by using Google map (GM). A total of 11,435 individuals from a 26,198 population completed the KCVST. The majority had a low score of risk for CCA (1-4 points; 93.3%). High scores with 6, 7 and 8 points accounted for 1.20%, 0.13% and 0.02%. The population at risk was found frequently in sub-district municipalities, followed by sub-district administrative organization and town municipalities, (F=396.220, P-value=0.000). Distribution mapping comprised 11 layers: 1, district; 2, local administrative organization; 3, hospital; 4, KCVST opisthorchiasis; 5, KCVST praziquantel used; 6, KCVST cholelithiasis; 7, KCVST raw fish consumption; 8, KCVST alcohol consumption; 9, KCVST pesticide used; 10, KCVST relative family with CCA; and 11, KCVST naive northeastern people. Geovisual display is now available online. This study indicated that the population at high risk of CCA in Bua Yai district is low, therefore setting a zero model project is possible. Key success factors for disease prevention and control need further study. GM production is suitable for further CCA surveillance and monitoring of the population with a high risk score in this area.

Bedrock geologic map of the Nashua South quadrangle, Hillsborough County, New Hampshire, and Middlesex County, Massachusetts

USGS Publications Warehouse

Walsh, Gregory J.; Jahns, Richard H.; Aleinikoff, John N.

2013-01-01

The bedrock geology of the 7.5-minute Nashua South quadrangle consists primarily of deformed Silurian metasedimentary rocks of the Berwick Formation. The metasedimentary rocks are intruded by a Late Silurian to Early Devonian diorite-gabbro suite, Devonian rocks of the Ayer Granodiorite, Devonian granitic rocks of the New Hampshire Plutonic Suite including pegmatite and the Chelmsford Granite, and Jurassic diabase dikes. The bedrock geology was mapped to study the tectonic history of the area and to provide a framework for ongoing hydrogeologic characterization of the fractured bedrock of Massachusetts and New Hampshire. This report presents mapping by G.J. Walsh and R.H. Jahns and zircon U-Pb geochronology by J.N. Aleinikoff. The complete report consists of a map, text pamphlet, and GIS database. The map and text pamphlet are only available as downloadable files (see frame at right). The GIS database is available for download in ESRITM shapefile and Google EarthTM formats, and includes contacts of bedrock geologic units, faults, outcrops, structural geologic information, photographs, and a three-dimensional model.

Evaluating Google, Twitter, and Wikipedia as Tools for Influenza Surveillance Using Bayesian Change Point Analysis: A Comparative Analysis

PubMed Central

Hopkins, Richard S; Cook, Robert L; Striley, Catherine W

2016-01-01

Background Traditional influenza surveillance relies on influenza-like illness (ILI) syndrome that is reported by health care providers. It primarily captures individuals who seek medical care and misses those who do not. Recently, Web-based data sources have been studied for application to public health surveillance, as there is a growing number of people who search, post, and tweet about their illnesses before seeking medical care. Existing research has shown some promise of using data from Google, Twitter, and Wikipedia to complement traditional surveillance for ILI. However, past studies have evaluated these Web-based sources individually or dually without comparing all 3 of them, and it would be beneficial to know which of the Web-based sources performs best in order to be considered to complement traditional methods. Objective The objective of this study is to comparatively analyze Google, Twitter, and Wikipedia by examining which best corresponds with Centers for Disease Control and Prevention (CDC) ILI data. It was hypothesized that Wikipedia will best correspond with CDC ILI data as previous research found it to be least influenced by high media coverage in comparison with Google and Twitter. Methods Publicly available, deidentified data were collected from the CDC, Google Flu Trends, HealthTweets, and Wikipedia for the 2012-2015 influenza seasons. Bayesian change point analysis was used to detect seasonal changes, or change points, in each of the data sources. Change points in Google, Twitter, and Wikipedia that occurred during the exact week, 1 preceding week, or 1 week after the CDC’s change points were compared with the CDC data as the gold standard. All analyses were conducted using the R package “bcp” version 4.0.0 in RStudio version 0.99.484 (RStudio Inc). In addition, sensitivity and positive predictive values (PPV) were calculated for Google, Twitter, and Wikipedia. Results During the 2012-2015 influenza seasons, a high sensitivity of 92% was found for Google, whereas the PPV for Google was 85%. A low sensitivity of 50% was calculated for Twitter; a low PPV of 43% was found for Twitter also. Wikipedia had the lowest sensitivity of 33% and lowest PPV of 40%. Conclusions Of the 3 Web-based sources, Google had the best combination of sensitivity and PPV in detecting Bayesian change points in influenza-related data streams. Findings demonstrated that change points in Google, Twitter, and Wikipedia data occasionally aligned well with change points captured in CDC ILI data, yet these sources did not detect all changes in CDC data and should be further studied and developed. PMID:27765731

ANTP Protocol Suite Software Implementation Architecture in Python

DTIC Science & Technology

2011-06-03

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

Optimizing Distributed Sensor Placement for Border Patrol Interdiction Using Microsoft Excel

DTIC Science & Technology

2007-04-01

weather conditions and they can be evaded by using techniques which minimize heat signatures use of lasers and other technologies day or night (26:8...technologies which can be used for border security. Maier [2004] developed a seismic intrusion sensor technology which uses fiber optic cables, lasers , and...needed to create the is used as the base map for the network. program originally developed by Keyhole by Google Inc. It provides satellite images of

Feasibility Study of Utilization of Action Camera, GoPro Hero 4, Google Glass, and Panasonic HX-A100 in Spine Surgery.

PubMed

Lee, Chang Kyu; Kim, Youngjun; Lee, Nam; Kim, Byeongwoo; Kim, Doyoung; Yi, Seong

2017-02-15

Study for feasibility of commercially available action cameras in recording video of spine. Recent innovation of the wearable action camera with high-definition video recording enables surgeons to use camera in the operation at ease without high costs. The purpose of this study is to compare the feasibility, safety, and efficacy of commercially available action cameras in recording video of spine surgery. There are early reports of medical professionals using Google Glass throughout the hospital, Panasonic HX-A100 action camera, and GoPro. This study is the first report for spine surgery. Three commercially available cameras were tested: GoPro Hero 4 Silver, Google Glass, and Panasonic HX-A100 action camera. Typical spine surgery was selected for video recording; posterior lumbar laminectomy and fusion. Three cameras were used by one surgeon and video was recorded throughout the operation. The comparison was made on the perspective of human factor, specification, and video quality. The most convenient and lightweight device for wearing and holding throughout the long operation time was Google Glass. The image quality; all devices except Google Glass supported HD format and GoPro has unique 2.7K or 4K resolution. Quality of video resolution was best in GoPro. Field of view, GoPro can adjust point of interest, field of view according to the surgery. Narrow FOV option was the best for recording in GoPro to share the video clip. Google Glass has potentials by using application programs. Connectivity such as Wi-Fi and Bluetooth enables video streaming for audience, but only Google Glass has two-way communication feature in device. Action cameras have the potential to improve patient safety, operator comfort, and procedure efficiency in the field of spinal surgery and broadcasting a surgery with development of the device and applied program in the future. N/A.

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.

Space Situational Awareness Data Processing Scalability Utilizing Google Cloud Services

NASA Astrophysics Data System (ADS)

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

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

What Is Being Played in the World? Mobile eSport Applications

ERIC Educational Resources Information Center

Atalay, Ahmet; Topuz, Arif Cem

2018-01-01

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

Environmental asbestos exposure sources in Korea

PubMed Central

2016-01-01

Background Because of the long asbestos-related disease latencies (10–50 years), detection, diagnosis, and epidemiologic studies require asbestos exposure history. However, environmental asbestos exposure source (EAES) data are lacking. Objectives To survey the available data for past EAES and supplement these data with interviews. Methods We constructed an EAES database using a literature review and interviews of experts, former traders, and workers. Exposure sources by time period and type were visualized using a geographic information system (ArcGIS), web-based mapping (Google Maps), and OpenWeatherMap. The data were mounted in the GIS to show the exposure source location and trend. Results The majority of asbestos mines, factories, and consumption was located in Chungnam; Gyeonggi, Busan, and Gyeongnam; and Gyeonggi, Daejeon, and Busan, respectively. Shipbuilding and repair companies were mostly located in Busan and Gyeongnam. Conclusions These tools might help evaluate past exposure from EAES and estimate the future asbestos burden in Korea. PMID:27726756

Environmental asbestos exposure sources in Korea.

PubMed

Kang, Dong-Mug; Kim, Jong-Eun; Kim, Ju-Young; Lee, Hyun-Hee; Hwang, Young-Sik; Kim, Young-Ki; Lee, Yong-Jin

2016-10-01

Because of the long asbestos-related disease latencies (10-50 years), detection, diagnosis, and epidemiologic studies require asbestos exposure history. However, environmental asbestos exposure source (EAES) data are lacking. To survey the available data for past EAES and supplement these data with interviews. We constructed an EAES database using a literature review and interviews of experts, former traders, and workers. Exposure sources by time period and type were visualized using a geographic information system (ArcGIS), web-based mapping (Google Maps), and OpenWeatherMap. The data were mounted in the GIS to show the exposure source location and trend. The majority of asbestos mines, factories, and consumption was located in Chungnam; Gyeonggi, Busan, and Gyeongnam; and Gyeonggi, Daejeon, and Busan, respectively. Shipbuilding and repair companies were mostly located in Busan and Gyeongnam. These tools might help evaluate past exposure from EAES and estimate the future asbestos burden in Korea.

Map of Life - A Dashboard for Monitoring Planetary Species Distributions

NASA Astrophysics Data System (ADS)

Jetz, W.

2016-12-01

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

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.

An Integrated Approach for Accessing Multiple Datasets through LANCE

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Web-Based Survey Application to Collect Contextually Relevant Geographic Data With Exposure Times: Application Development and Feasibility Testing

PubMed Central

Tobin, Karin; Rudolph, Jonathan; Latkin, Carl

2018-01-01

Background Although studies that characterize the risk environment by linking contextual factors with individual-level data have advanced infectious disease and substance use research, there are opportunities to refine how we define relevant neighborhood exposures; this can in turn reduce the potential for exposure misclassification. For example, for those who do not inject at home, injection risk behaviors may be more influenced by the environment where they inject than where they live. Similarly, among those who spend more time away from home, a measure that accounts for different neighborhood exposures by weighting each unique location proportional to the percentage of time spent there may be more correlated with health behaviors than one’s residential environment. Objective This study aimed to develop a Web-based application that interacts with Google Maps application program interfaces (APIs) to collect contextually relevant locations and the amount of time spent in each. Our analysis examined the extent of overlap across different location types and compared different approaches for classifying neighborhood exposure. Methods Between May 2014 and March 2017, 547 participants enrolled in a Baltimore HIV care and prevention study completed an interviewer-administered Web-based survey that collected information about where participants were recruited, worked, lived, socialized, injected drugs, and spent most of their time. For each location, participants gave an address or intersection which they confirmed using Google Map and Street views. Geographic coordinates (and hours spent in each location) were joined to neighborhood indicators by Community Statistical Area (CSA). We computed a weighted exposure based on the proportion of time spent in each unique location. We compared neighborhood exposures based on each of the different location types with one another and the weighted exposure using analysis of variance with Bonferroni corrections to account for multiple comparisons. Results Participants reported spending the most time at home, followed by the location where they injected drugs. Injection locations overlapped most frequently with locations where people reported socializing and living or sleeping. The least time was spent in the locations where participants reported earning money and being recruited for the study; these locations were also the least likely to overlap with other location types. We observed statistically significant differences in neighborhood exposures according to the approach used. Overall, people reported earning money in higher-income neighborhoods and being recruited for the study and injecting in neighborhoods with more violent crime, abandoned houses, and poverty. Conclusions This analysis revealed statistically significant differences in neighborhood exposures when defined by different locations or weighted based on exposure time. Future analyses are needed to determine which exposure measures are most strongly associated with health and risk behaviors and to explore whether associations between individual-level behaviors and neighborhood exposures are modified by exposure times. PMID:29351899

The North America tapestry of time and terrain

USGS Publications Warehouse

Barton, Kate E.; Howell, David G.; Vigil, Jose F.

2003-01-01

The North America Tapestry of Time and Terrain (1:8,000,000 scale) is a product of the US Geological Survey in the I-map series (I-2781). This map was prepared in collaboration with the Geological Survey of Canada and the Mexican Consejo Recursos de Minerales. This cartographic Tapestry is woven from a geologic map and a shaded relief image. This digital combination reveals the geologic history of North America through the interrelation of rock type, topography and time. Regional surface processes as well as continent-scale tectonic events are exposed in the three dimensions of space and the fourth dimension, geologic time. The large map shows the varying age of bedrock underlying North America, while four smaller maps show the distribution of four principal types of rock: sedimentary, volcanic, plutonic and metamorphic.This map expands the original concept of the 2000 Tapestry of Time and Terrain, by José F. Vigil, Richard J. Pike and David G. Howell, which covered the conterminous United States. The U.S. Tapestry poster and website have been popular in classrooms, homes, and even the Google office building, and we anticipate the North America Tapestry will have a similarly wide appeal, and to a larger audience.

The Use of LANCE Imagery Products to Investigate Hazards and Disasters

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Atmospheric Infrared Sounder on NASA's Aqua Satellite: Applications for Volcano Rapid Response, Influenza Outbreak Prediction, and Drought Onset Prediction

NASA Astrophysics Data System (ADS)

Ray, S. E.; Fetzer, E. J.; Lambrigtsen, B.; Olsen, E. T.; Licata, S. J.; Hall, J. R.; Penteado, P. F.; Realmuto, V. J.; Thrastarson, H. T.; Teixeira, J.; Granger, S. L.; Behrangi, A.; Farahmand, A.

2017-12-01

The Atmospheric Infrared Sounder (AIRS) has been returning daily global observations of Earth's atmospheric constituents and properties since 2002. With its 15-year data record and near real-time capability, AIRS data are being used in the development of applications that fall within many of the NASA Applied Science focus areas. An automated alert system for volcanic plumes has been developed that triggers on threshold breaches of SO2, ash and dust in granules of AIRS data. The system generates a suite of granule-scale maps that depict both plume and clouds, all accessible from the AIRS web site. Alerts are sent to a curated list of volcano community members, and links to views in NASA Worldview and Google Earth are also available. Seasonal influenza epidemics are major public health concern with millions of cases of severe illness and large economic impact. Recent studies have highlighted the role of absolute or specific humidity as a likely player in the seasonal nature of these outbreaks. A quasi-operational influenza outbreak prediction system has been developed based on the SIRS model which uses AIRS and NCEP humidity data, Center for Disease Control reports on flu and flu-like illnesses, and results from Google Flu Trends. Work is underway to account for diffusion (spatial) in addition to the temporal spreading of influenza. The US Drought Monitor (USDM) is generated weekly by the National Drought Mitigation Center (NDMC) and is used by policymakers for drought decision-making. AIRS data have demonstrated utility in monitoring the development and detection of meteorological drought with both AIRS-derived standardized vapor pressure deficit and standardized relative humidity, showing early detection lead times of up to two months. An agreement was secured with the NDMC to begin a trial period using AIRS products in the production of the USDM, and in July of 2017 the operational delivery of weekly CONUS AIRS images of Relative Humidity, Surface Air Temperature, and Vapor Pressure Deficit to the National Drought Mitigation Center commenced. Next objectives include determining whether AIRS drought products can also be useful in the NDMC's VegDRI and QuickDRI products. This poster provides an overview of the work being done in these three application areas and summarize additional application efforts using data from AIRS.

Staff Recall Travel Time for ST Elevation Myocardial Infarction Impacted by Traffic Congestion and Distance: A Digitally Integrated Map Software Study.

PubMed

Cole, Justin; Beare, Richard; Phan, Thanh G; Srikanth, Velandai; MacIsaac, Andrew; Tan, Christianne; Tong, David; Yee, Susan; Ho, Jesslyn; Layland, Jamie

2017-01-01

Recent evidence suggests hospitals fail to meet guideline specified time to percutaneous coronary intervention (PCI) for a proportion of ST elevation myocardial infarction (STEMI) presentations. Implicit in achieving this time is the rapid assembly of crucial catheter laboratory staff. As a proof-of-concept, we set out to create regional maps that graphically show the impact of traffic congestion and distance to destination on staff recall travel times for STEMI, thereby producing a resource that could be used by staff to improve reperfusion time for STEMI. Travel times for staff recalled to one inner and one outer metropolitan hospital at midnight, 6 p.m., and 7 a.m. were estimated using Google Maps Application Programming Interface. Computer modeling predictions were overlaid on metropolitan maps showing color coded staff recall travel times for STEMI, occurring within non-peak and peak hour traffic congestion times. Inner metropolitan hospital staff recall travel times were more affected by traffic congestion compared with outer metropolitan times, and the latter was more affected by distance. The estimated mean travel times to hospital during peak hour were greater than midnight travel times by 13.4 min to the inner and 6.0 min to the outer metropolitan hospital at 6 p.m. ( p  < 0.001). At 7 a.m., the mean difference was 9.5 min to the inner and 3.6 min to the outer metropolitan hospital ( p  < 0.001). Only 45% of inner metropolitan staff were predicted to arrive within 30 min at 6 p.m. compared with 100% at midnight ( p  < 0.001), and 56% of outer metropolitan staff at 6 p.m. ( p  = 0.021). Our results show that integration of map software with traffic congestion data, distance to destination and travel time can predict optimal residence of staff when on-call for PCI.

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

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

Application of the improved fuzzy analytic hierarchy process for landslide hazard assessment based on RS and GIS

NASA Astrophysics Data System (ADS)

Li, Baishou; Gao, Yujiu

2015-12-01

The landslide is a geological disaster that caused the second disruptions and losses next to the earthquake, and people around the world suffered a serious threat to their lives and property damage as a result of landslide disaster every year. So carrying on the study of the landslide hazard will create important theoretical meaning and practical value for proposing targeted prevention and treatment measures. Landslides occur more frequently in Guangxi where serious landslide disasters run riot because of its unique karst topography environment and abundant rainfall. The Wanxiu District of Wuzhou, Guangxi was selected as the study area, the landslide hazard zonation evaluation was studied on the basis of RS and GIS technology. The factors that influence landslide occurrence, such as elevation, slope inclination, slope aspect, curvature and distance to streams were derived from the DEM; land use was extracted from the Google Earth image; lithology was digitalized from the geologic map; rainfall information was from the literature. An improved analytic hierarchy process was presented to determine the index weight in this study. The method weakens the uncertainty in the process of comparing the importance of each factor, it need not to do the consistency check, which can also reduce the iteration times enormously, and improve operating speed. Combined with fuzzy comprehensive evaluation method, the landslide hazard mapping of the study area was made according to the maximum membership degree principle. The resulting map can be used to provide some reference values for risk management, land-use planning and urbanization.

The value of spatial analysis for tracking supply for family planning: the case of Kinshasa, DRC.

PubMed

Hernandez, Julie H; Akilimali, Pierre; Kayembe, Patrick; Dikamba, Nelly; Bertrand, Jane

2016-10-01

While geographic information systems (GIS) are frequently used to research accessibility issues for healthcare services around the world, sophisticated spatial analysis protocols and outputs often prove inappropriate and unsustainable to support evidence-based programme strategies in resource-constrained environments. This article examines how simple, open-source and interactive GIS tools have been used to locate family planning (FP) services delivery points in Kinshasa (Democratic Republic of Congo) and to identify underserved areas, determining the potential location of new service points, and to support advocacy for FP programmes. Using smartphone-based data collection applications (OpenDataKit), we conducted two surveys of FP facilities supported by partner organizations in 2012 and 2013 and used the results to assess gaps in FP services coverage, using both ratio of facilities per population and distance-based accessibility criteria. The cartographic outputs included both static analysis maps and interactive Google Earth displays, and sought to support advocacy and evidence-based planning for the placement of new service points. These maps, at the scale of Kinshasa or for each of the 35 health zones that cover the city, garnered a wide interest from the operational level of the health zones' Chief Medical Officers, who were consulted to contribute field knowledge on potential new service delivery points, to the FP programmes officers at the Ministry of Health, who could use the map to inform resources allocation decisions throughout the city. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Global Imagery Browse Services (GIBS) - Rapidly Serving NASA Imagery for Applications and Science Users

NASA Astrophysics Data System (ADS)

Schmaltz, J. E.; Ilavajhala, S.; Plesea, L.; Hall, J. R.; Boller, R. A.; Chang, G.; Sadaqathullah, S.; Kim, R.; Murphy, K. J.; Thompson, C. K.

2012-12-01

Expedited processing of imagery from NASA satellites for near-real time use by non-science applications users has a long history, especially since the beginning of the Terra and Aqua missions. Several years ago, the Land Atmosphere Near-real-time Capability for EOS (LANCE) was created to greatly expand the range of near-real time data products from a variety of Earth Observing System (EOS) instruments. NASA's Earth Observing System Data and Information System (EOSDIS) began exploring methods to distribute these data as imagery in an intuitive, geo-referenced format, which would be available within three hours of acquisition. Toward this end, EOSDIS has developed the Global Imagery Browse Services (GIBS, http://earthdata.nasa.gov/gibs) to provide highly responsive, scalable, and expandable imagery services. The baseline technology chosen for GIBS was a Tiled Web Mapping Service (TWMS) developed at the Jet Propulsion Laboratory. Using this, global images and mosaics are divided into tiles with fixed bounding boxes for a pyramid of fixed resolutions. Initially, the satellite imagery is created at the existing data systems for each sensor, ensuring the oversight of those most knowledgeable about the science. There, the satellite data is geolocated and converted to an image format such as JPEG, TIFF, or PNG. The GIBS ingest server retrieves imagery from the various data systems and converts them into image tiles, which are stored in a highly-optimized raster format named Meta Raster Format (MRF). The image tiles are then served to users via HTTP by means of an Apache module. Services are available for the entire globe (lat-long projection) and for both polar regions (polar stereographic projection). Requests to the services can be made with the non-standard, but widely known, TWMS format or via the well-known OGC Web Map Tile Service (WMTS) standard format. Standard OGC Web Map Service (WMS) access to the GIBS server is also available. In addition, users may request a KML pyramid. This variety of access methods allows stakeholders to develop visualization/browse clients for a diverse variety of specific audiences. Currently, EOSDIS is providing an OpenLayers web client, Worldview (http://earthdata.nasa.gov/worldview), as an interface to GIBS. A variety of other existing clients can also be developed using such tools as Google Earth, Google Earth browser Plugin, ESRI's Adobe Flash/Flex Client Library, NASA World Wind, Perceptive Pixel Client, Esri's iOS Client Library, and OpenLayers for Mobile. The imagery browse capabilities from GIBS can be combined with other EOSDIS services (i.e. ECHO OpenSearch) via a client that ties them both together to provide an interface that enables data download from the onscreen imagery. Future plans for GIBS include providing imagery based on science quality data from the entire data record of these EOS instruments.

A new android smartphone app for geospatial mapping from drones and kites

NASA Astrophysics Data System (ADS)

Anderson, Karen; Griffiths, Dave; Debell, Leon; Steve, Hancock; James, Duffy; Jamie, Shutler; Liam, Reinhardt; Griffiths, Amber; Threadgill, Katie

2016-04-01

This paper will describe the development, testing and deployment of a free-to-use, open-source, android-based smartphone application for capturing geo-tagged aerial photographs for grass-roots remote sensing (RS) and mapping applications. Historically, RS data have been acquired from sensors on platforms such as piloted aircraft or satellites but a new self-service, and to some extent, 'grassroots' (participatory and distributed) RS revolution is underway making use of drones and kites as platforms for proximal observations of environmental phenomena. There are a growing number of papers in the geosciences and in landscape ecology utilising such platforms for cost-effective, self-service acquisition of RS data. These platforms cannot carry the heavy payloads used on satellites or aircraft, but they offer a more flexible way of gathering responsive survey data, and their low flying capability means that very fine-grained data can be captured easily. The current scientific focus for drone- and kite-based aerial mapping relies on automatically-triggered camera systems, followed by complex post-processing algorithms (e.g. computer vision-based 'structure-from-motion' software) to convert the resulting aerial photography data into orthorectified maps and point clouds. Whilst these approaches generate high quality products, for many applications the complexity is a barrier to uptake. Wiring the camera to an autopilot trigger is non-trivial, and the post-processing stage demands expensive and complex software and high performance computing. For many basic mapping applications, the workflow is too complex and the detail in the products exceed what is really needed. We asked: what if a basic smartphone, with its plethora of on-board sensors (accelerometer, GPS, compass, camera) could be used to generate ready-to-use spatial data from lightweight aerial platforms such as drones or kites? We built an android application to test the capability of standard smartphones as remote sensing devices. The application uses a visual coding 'scheme blocks' framework, so that users can customise their own data capture tools in the field. In our presentation we will demonstrate the coding framework, and then we will show the results that were gathered when we used the app to collect data during test flights - utilising various kite and lightweight drone platforms. We have also developed a simple to use open-source geospatial toolkit to allow geographical information system (GIS)-ready GeoTIFF images to be processed from the metadata stored by the app. We will demonstrate how this works in our presentation. Two Android smartphones were used in testing - a high specification OnePlus One handset and a lower cost Acer Liquid Z3 handset. We will show that the best results were obtained with the higher specification phone when it was attached to a single line kite or to a gliding drone. Finally, we will use data collected using the app, over a farmyard to demonstrate the power of the resultant fine-grained products for a simple application - advising farmers about small-scale interventions they can make to improve the quality of water run-off from their farms. The app can be downloaded freely, and used wherever an Android smartphone and aerial platform are available to deliver rapid spatial data (e.g. disaster zones, in teaching or for grassroots democratic mapping). [https://play.google.com/store/apps/details?id=foam.uavtoolkit&hl=en

3D Immersive Visualization with Astrophysical Data

NASA Astrophysics Data System (ADS)

Kent, Brian R.

2017-01-01

We present the refinement of a new 3D immersion technique for astrophysical data visualization.Methodology to create 360 degree spherical panoramas is reviewed. The 3D software package Blender coupled with Python and the Google Spatial Media module are used together to create the final data products. Data can be viewed interactively with a mobile phone or tablet or in a web browser. The technique can apply to different kinds of astronomical data including 3D stellar and galaxy catalogs, images, and planetary maps.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Assessing the methods needed for improved dengue mapping: a SWOT analysis

PubMed Central

Attaway, David Frost; Jacobsen, Kathryn H; Falconer, Allan; Manca, Germana; Waters, Nigel M

2014-01-01

Introduction Dengue fever, a mosquito-borne viral infection, is a growing threat to human health in tropical and subtropical areas worldwide. There is a demand from public officials for maps that capture the current distribution of dengue and maps that analyze risk factors to predict the future burden of disease. Methods To identify relevant articles, we searched Google Scholar, PubMed, BioMed Central, and WHOLIS (World Health Organization Library Database) for published articles with a specific set of dengue criteria between January 2002 and July 2013. Results After evaluating the currently available dengue models, we identified four key barriers to the creation of high-quality dengue maps: (1) data limitations related to the expense of diagnosing and reporting dengue cases in places where health information systems are underdeveloped; (2) issues related to the use of socioeconomic proxies in places with limited dengue incidence data; (3) mosquito ranges which may be changing as a result of climate changes; and (4) the challenges of mapping dengue events at a variety of scales. Conclusion An ideal dengue map will present endemic and epidemic dengue information from both rural and urban areas. Overcoming the current barriers requires expanded collaboration and data sharing by geographers, epidemiologists, and entomologists. Enhanced mapping techniques would allow for improved visualizations of dengue rates and risks. PMID:25328585

Assessing the methods needed for improved dengue mapping: a SWOT analysis.

PubMed

Attaway, David Frost; Jacobsen, Kathryn H; Falconer, Allan; Manca, Germana; Waters, Nigel M

2014-01-01

Dengue fever, a mosquito-borne viral infection, is a growing threat to human health in tropical and subtropical areas worldwide. There is a demand from public officials for maps that capture the current distribution of dengue and maps that analyze risk factors to predict the future burden of disease. To identify relevant articles, we searched Google Scholar, PubMed, BioMed Central, and WHOLIS (World Health Organization Library Database) for published articles with a specific set of dengue criteria between January 2002 and July 2013. After evaluating the currently available dengue models, we identified four key barriers to the creation of high-quality dengue maps: (1) data limitations related to the expense of diagnosing and reporting dengue cases in places where health information systems are underdeveloped; (2) issues related to the use of socioeconomic proxies in places with limited dengue incidence data; (3) mosquito ranges which may be changing as a result of climate changes; and (4) the challenges of mapping dengue events at a variety of scales. An ideal dengue map will present endemic and epidemic dengue information from both rural and urban areas. Overcoming the current barriers requires expanded collaboration and data sharing by geographers, epidemiologists, and entomologists. Enhanced mapping techniques would allow for improved visualizations of dengue rates and risks.

Digital Geological Map for Marie Byrd Land, West Antarctica: A resource for investigation of geotectonic frameworks and future glaciological change

NASA Astrophysics Data System (ADS)

Siddoway, C. S.; White, T.; Elkind, S.; Cox, S. C.; Lyttle, B. S.; Morin, P. J.

2016-12-01

Bedrock exposures are relatively sparse in Marie Byrd Land (MBL), where rock is concealed by the West Antarctic ice sheet, but they provide direct insight into the geological evolution and glacial history of West Antarctica. MBL is tectonically active, as evidenced by Late Pleistocene to Holocene volcanism and 2012 seismicity (3 events, M4.4 to M5.5) at sites beside Ross Sea. There are geological influences upon the ice sheet, namely, subglacial volcanism and associated geothermal flux, fault zone alteration/mineralization, and bedrock roughess. The former may influence the position and velocity of outlet glaciers and the latter may anchor or accelerate sectors of the ice sheet. To make MBL's geological framework accessible to investigators with diverse research priorities, we are preparing the first digital geological map of MBL by compiling ground-based geological data, incorporating firsthand observations, published geological maps and literature. The map covers an on-continent coastal area of 900 000 km2 between 090°E to 160°E, from 72°S to 80°S, at 1:250 000 scale or better. Exposed rock is delimited by 1976 polygons, occupying 410 km2. Supraglacial features and glacial till, seasonal water and blue ice, are also mapped, as a baseline for past and future glaciological change. Rendered in the ArcMap GIS software by Esri©, the database employs international GeoSciML data protocols for feature classification and description of rock and moraine polygons from the Antarctic Digital Database (www.add.scar.org), with shape and location adjusted to align with features in Landsat Image Mosaic of Antarctica imagery (lima.usgs.gov), where necessary. The GIS database is attribute-rich and queriable; including links to bibliographic source files for primary literature and published maps. It will soon be available as GoogleEarth kmz files and an ArcGIS online map service. An initial application is to the interpretation of sub-ice geology for a subglacial geotectonic map of this active region. This is undertaken as part of ROSETTA-Ice, an integrated systems science investigation of the Ross Ice Shelf that commenced in 2015. The next phases of MBL database development will assess icesheet-ocean interactions near grounding line, environmental domain analysis and ecological research.

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.

Generating and Visualizing Climate Indices using Google Earth Engine

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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.

Brain maps 4.0—Structure of the rat brain: An open access atlas with global nervous system nomenclature ontology and flatmaps

PubMed Central

2018-01-01

Abstract The fourth edition (following editions in 1992, 1998, 2004) of Brain maps: structure of the rat brain is presented here as an open access internet resource for the neuroscience community. One new feature is a set of 10 hierarchical nomenclature tables that define and describe all parts of the rat nervous system within the framework of a strictly topographic system devised previously for the human nervous system. These tables constitute a global ontology for knowledge management systems dealing with neural circuitry. A second new feature is an aligned atlas of bilateral flatmaps illustrating rat nervous system development from the neural plate stage to the adult stage, where most gray matter regions, white matter tracts, ganglia, and nerves listed in the nomenclature tables are illustrated schematically. These flatmaps are convenient for future development of online applications analogous to “Google Maps” for systems neuroscience. The third new feature is a completely revised Atlas of the rat brain in spatially aligned transverse sections that can serve as a framework for 3‐D modeling. Atlas parcellation is little changed from the preceding edition, but the nomenclature for rat is now aligned with an emerging panmammalian neuroanatomical nomenclature. All figures are presented in Adobe Illustrator vector graphics format that can be manipulated, modified, and resized as desired, and freely used with a Creative Commons license. PMID:29277900

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

NASA Technical Reports Server (NTRS)

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

[Metaphylaxis of urolithiasis: new look, modern approach, implementation in a mobile application].

PubMed

Gadzhiev, N K; Brovkin, S S; Grigorev, V E; Dmitriev, V V; Malkhasyan, V A; Shkarupa, D D; Pisarev, A V; Mazurenko, D A; Obidnyak, V M; Orlov, I N; Popov, S V; Tagirov, N S; Petrov, S V

2017-04-01

To analyze the sub-segment of mHealth devoted to assessing of the risk of recurrent stone formation and metaphylaxis of stone formation. To design a smartphone application (app.) in Russian language for urolithiasis patients. Three working groups of urologists from three St. Petersburg clinics searched for downloadable medical applications relevant to the above requirements. After searching and analyzing existing medical applications, the most acceptable design and structure of our own application were identified. The developed "Urolithiasis" application is available for free download in Russian language versions in App Store (Apple, Inc.) and Google Play (Android market, Google, Inc.). It features the following sections: 1) "Take the test" (personalized calculation of the risk of kidney stone recurrence and providing relevant recommendations using ROKS nomogram), 2) "Water" (with reminders to drink water and automatic logging of the water intake), 3) "Food" (Nutrition facts on the content of calcium, oxalate, purine, protein, citrate and calories in common foods), 4) "My doctor" (in the future this option will allow for on-line communication with a patients physician), 5) "Feedback" (if the patient does not find the desired product or has a question - this section is for him/her). The smartphone application "Urolithiasis" in Russian may be recommended to patients with urolithiasis for improving the effectiveness of metaphylaxis.

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

NASA Technical Reports Server (NTRS)

Baxes, Gregory; Mixon, Brian; Linger, TIm

2013-01-01

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

Fast and Sensitive Alignment of Microbial Whole Genome Sequencing Reads to Large Sequence Datasets on a Desktop PC: Application to Metagenomic Datasets and Pathogen Identification

PubMed Central

2014-01-01

Next generation sequencing (NGS) of metagenomic samples is becoming a standard approach to detect individual species or pathogenic strains of microorganisms. Computer programs used in the NGS community have to balance between speed and sensitivity and as a result, species or strain level identification is often inaccurate and low abundance pathogens can sometimes be missed. We have developed Taxoner, an open source, taxon assignment pipeline that includes a fast aligner (e.g. Bowtie2) and a comprehensive DNA sequence database. We tested the program on simulated datasets as well as experimental data from Illumina, IonTorrent, and Roche 454 sequencing platforms. We found that Taxoner performs as well as, and often better than BLAST, but requires two orders of magnitude less running time meaning that it can be run on desktop or laptop computers. Taxoner is slower than the approaches that use small marker databases but is more sensitive due the comprehensive reference database. In addition, it can be easily tuned to specific applications using small tailored databases. When applied to metagenomic datasets, Taxoner can provide a functional summary of the genes mapped and can provide strain level identification. Taxoner is written in C for Linux operating systems. The code and documentation are available for research applications at http://code.google.com/p/taxoner. PMID:25077800

Fast and sensitive alignment of microbial whole genome sequencing reads to large sequence datasets on a desktop PC: application to metagenomic datasets and pathogen identification.

PubMed

Pongor, Lőrinc S; Vera, Roberto; Ligeti, Balázs

2014-01-01

Next generation sequencing (NGS) of metagenomic samples is becoming a standard approach to detect individual species or pathogenic strains of microorganisms. Computer programs used in the NGS community have to balance between speed and sensitivity and as a result, species or strain level identification is often inaccurate and low abundance pathogens can sometimes be missed. We have developed Taxoner, an open source, taxon assignment pipeline that includes a fast aligner (e.g. Bowtie2) and a comprehensive DNA sequence database. We tested the program on simulated datasets as well as experimental data from Illumina, IonTorrent, and Roche 454 sequencing platforms. We found that Taxoner performs as well as, and often better than BLAST, but requires two orders of magnitude less running time meaning that it can be run on desktop or laptop computers. Taxoner is slower than the approaches that use small marker databases but is more sensitive due the comprehensive reference database. In addition, it can be easily tuned to specific applications using small tailored databases. When applied to metagenomic datasets, Taxoner can provide a functional summary of the genes mapped and can provide strain level identification. Taxoner is written in C for Linux operating systems. The code and documentation are available for research applications at http://code.google.com/p/taxoner.

An Evaluation of Mobile Applications for Reproductive Endocrinology and Infertility Providers.

PubMed

Shaia, Kathryn L; Farag, Sara; Chyjek, Kathy; Knopman, Jaime; Chen, Katherine T

2017-03-01

To identify and rate reproductive endocrinology and infertility (REI) mobile applications (apps) targeted toward REI providers. A list of REI apps was found in both the Apple iTunes and Google Play stores using the following seven MeSH terms: reproductive endocrinology, REI, infertility, fertility, In Vitro Fertilization, IVF, and embryology. Patient-centered apps were excluded. The remaining apps were then evaluated for accuracy using reliable references. Mobile technology. None. Accurate apps were evaluated for comprehensiveness (the extent of the ability to aid in clinical decision-making) and rated with objective and subjective components using the APPLICATIONS scoring system. Using the seven REI-related MeSH terms, 985 apps and 1,194 apps were identified in the Apple iTunes and Google Play stores, respectively. Of these unique apps, only 20 remained after excluding patient-centered apps. Upon further review for applicability to REI specifically and content accuracy, only seven apps remained. These seven apps were then rated using the APPLICATIONS scoring system. Only 0.32% of 2,179 apps reviewed for this study were useful to REI providers. There is potential for further mobile resource development in the area of REI, given the limited number and varying comprehensiveness and quality of available apps.

Smartphone Applications for the Clinical Oncologist in UK Practice.

PubMed

Rozati, Hamoun; Shah, Sonya Pratik; Shah, Neha

2015-06-01

A number of medical smartphone applications have been developed to assist clinical oncology specialists. Concerns have arisen that the information provided may not be under sufficient scrutiny. This study aims to analyse the current applications available for clinical oncologists in the UK. Applications aimed specifically at physician clinical oncologists were searched for on the major smartphone operating systems: Apple iOS; Google Android; Microsoft Windows OS; and Blackberry OS. All applications were installed and analysed. The applications were scrutinised to assess the following information: cost; whether the information included was referenced; when the information was last updated; and whether they made any reference to UK guidelines. A novel rating score based on these criteria was applied to each application. Fifty applications were identified: 24 for Apple's iOS; 23 for Google's Android; 2 for Blackberry OS; and 1 for Windows OS. The categories of applications available were: drug reference; journal reference; learning; clinical calculators; decision support; guidelines; and dictionaries. Journal reference and guideline applications scored highly on our rating system. Drug reference application costs were prohibitive. Learning tools were poorly referenced and not up-to-date. Smartphones provide easy access to information. There are numerous applications devoted to oncology physicians, many of which are free and contain referenced, up-to-date data. The cost and quality of drug reference and learning applications have significant scope for improvement. A regulatory body is needed to ensure the presence of peer-reviewed, validated applications to ensure their reliability.

Extra-terra incognita: Martian maps in the digital age.

PubMed

Messeri, Lisa

2017-02-01

Science and technology studies (STS) and critical cartography are both asking questions about the ontological fixity of maps and other scientific objects. This paper examines how a group of NASA computer scientists who call themselves The Mapmakers conceptualizes and creates maps in service of different commitments. The maps under construction are those of alien Mars, produced through partnerships that NASA has established with Google and Microsoft. With the goal of bringing an experience of Mars to as many people as possible, these maps influence how we imagine our neighbouring planet. This paper analyzes two attributes of the map, evident in both its representation and the attending cartographic practices: a sense of Mars as dynamic and a desire for a democratic experience of Mars in which up-to-date Mars data can be intuitively accessed not only by scientists but by lay users as well. Whereas a democratic Mars promises users the ability to decide how to interact with the map and understand Mars, dynamic Mars imposes a more singular sense of Mars as a target of continued robotic and maybe even human exploration. Because maps of Mars have a different (and arguably less complex) set of social and political commitments than those of Earth, they help us see how different goals contradict and complement each other in matters of exploration and state-craft relevant both to other worlds and our own.

The Cellular Automata for modelling of spreading of lava flow on the earth surface

NASA Astrophysics Data System (ADS)

Jarna, A.

2012-12-01

Volcanic risk assessment is a very important scientific, political and economic issue in densely populated areas close to active volcanoes. Development of effective tools for early prediction of a potential volcanic hazard and management of crises are paramount. However, to this date volcanic hazard maps represent the most appropriate way to illustrate the geographical area that can potentially be affected by a volcanic event. Volcanic hazard maps are usually produced by mapping out old volcanic deposits, however dynamic lava flow simulation gaining popularity and can give crucial information to corroborate other methodologies. The methodology which is used here for the generation of volcanic hazard maps is based on numerical simulation of eruptive processes by the principle of Cellular Automata (CA). The python script is integrated into ArcToolbox in ArcMap (ESRI) and the user can select several input and output parameters which influence surface morphology, size and shape of the flow, flow thickness, flow velocity and length of lava flows. Once the input parameters are selected, the software computes and generates hazard maps on the fly. The results can be exported to Google Maps (.klm format) to visualize the results of the computation. For validation of the simulation code are used data from a real lava flow. Comparison of the simulation results with real lava flows mapped out from satellite images will be presented.

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.

Can Satellite Remote Sensing be Applied in Geological Mapping in Tropics?

NASA Astrophysics Data System (ADS)

Magiera, Janusz

2018-03-01

Remote sensing (RS) techniques are based on spectral data registered by RS scanners as energy reflected from the Earth's surface or emitted by it. In "geological" RS the reflectance (or emittence) should come from rock or sediment. The problem in tropical and subtropical areas is a dense vegetation. Spectral response from the rocks and sediments is gathered only from the gaps among the trees and shrubs. Images of high resolution are appreciated here, therefore. New generation of satellites and scanners (Digital Globe WV2, WV3 and WV4) yield imagery of spatial resolution of 2 m and up to 16 spectral bands (WV3). Images acquired by Landsat (TM, ETM+, OLI) and Sentinel 2 have good spectral resolution too (6-12 bands in visible and infrared) and, despite lower spatial resolution (10-60 m of pixel size) are useful in extracting lithological information too. Lithological RS map may reveal good precision (down to a single rock or outcrop of a meter size). Supplemented with the analysis of Digital Elevation Model and high resolution ortophotomaps (Google Maps, Bing etc.) allows for quick and cheap mapping of unsurveyed areas.

Community context and sub-neighborhood scale detail to explain dengue, chikungunya and Zika patterns in Cali, Colombia

PubMed Central

Curtis, Andrew; Buritica, Paola; Ajayakumar, Jayakrishnan; Squires, Robert; Dávalos, Diana; Pacheco, Robinson; Bhatta, Madhav P.; James, Mark A.

2017-01-01

Background Cali, Colombia has experienced chikungunya and Zika outbreaks and hypoendemic dengue. Studies have explained Cali’s dengue patterns but lack the sub-neighborhood-scale detail investigated here. Methods Spatial-video geonarratives (SVG) with Ministry of Health officials and Community Health Workers were collected in hotspots, providing perspective on perceptions of why dengue, chikungunya and Zika hotspots exist, impediments to control, and social outcomes. Using spatial video and Google Street View, sub-neighborhood features possibly contributing to incidence were mapped to create risk surfaces, later compared with dengue, chikungunya and Zika case data. Results SVG captured insights in 24 neighborhoods. Trash and water risks in Calipso were mapped using SVG results. Perceived risk factors included proximity to standing water, canals, poverty, invasions, localized violence and military migration. These risks overlapped case density maps and identified areas that are suitable for transmission but are possibly underreporting to the surveillance system. Conclusion Resulting risk maps with local context could be leveraged to increase vector-control efficiency- targeting key areas of environmental risk. PMID:28767730

Mapping and characterization from aeromagnetic data of the Foum Zguid dolerite Dyke (Anti-Atlas, Morocco) a member of the Central Atlantic Magmatic Province (CAMP)

NASA Astrophysics Data System (ADS)

Bouiflane, Mustapha; Manar, Ahmed; Medina, Fida; Youbi, Nasrrddine; Rimi, Abdelkrim

2017-06-01

A high-resolution aeromagnetic survey was carried out in the Anti- Atlas, Morocco covering the main areas traversed by the Great CAMP Foum Zguid dyke (FZD). This ;doleritic; dyke belongs to the Central Atlantic Magmatic Province (CAMP), a Large Igneous Province which is associated with the fragmentation of the supercontinent Pangaea and the initial stages of rifting of the Central Atlantic Ocean. It also coincides in time with the mass extinction of the Triassic - Jurassic boundary. Based on the study of geological maps and Google Earth satellite images, it appears that the FZD is poorly exposed and, often covered by Quaternary deposits. This work proposes aeromagnetic modelling and interpretation of the FZD in order to better constrain its structural extent. The data have allowed (i) mapping of the dyke over great distances, under the Quaternary deposits and through areas where it was poorly characterized on the geological map; (ii) identifying major tectonic lineaments interpreted as faults; (iii) recognizing magnetic anomalies related to mafic intrusive bodies; and (iv) informing about regional structural context.

Virtual GEOINT Center: C2ISR through an avatar's eyes

NASA Astrophysics Data System (ADS)

Seibert, Mark; Tidbal, Travis; Basil, Maureen; Muryn, Tyler; Scupski, Joseph; Williams, Robert

2013-05-01

As the number of devices collecting and sending data in the world are increasing, finding ways to visualize and understand that data is becoming more and more of a problem. This has often been coined as the problem of "Big Data." The Virtual Geoint Center (VGC) aims to aid in solving that problem by providing a way to combine the use of the virtual world with outside tools. Using open-source software such as OpenSim and Blender, the VGC uses a visually stunning 3D environment to display the data sent to it. The VGC is broken up into two major components: The Kinect Minimap, and the Geoint Map. The Kinect Minimap uses the Microsoft Kinect and its open-source software to make a miniature display of people the Kinect detects in front of it. The Geoint Map collect smartphone sensor information from online databases and displays them in real time onto a map generated by Google Maps. By combining outside tools and the virtual world, the VGC can help a user "visualize" data, and provide additional tools to "understand" the data.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Operational Use of OGC Web Services at the Met Office

NASA Astrophysics Data System (ADS)

Wright, Bruce

2010-05-01

The Met Office has adopted the Service-Orientated Architecture paradigm to deliver services to a range of customers through Rich Internet Applications (RIAs). The approach uses standard Open Geospatial Consortium (OGC) web services to provide information to web-based applications through a range of generic data services. "Invent", the Met Office beta site, is used to showcase Met Office future plans for presenting web-based weather forecasts, product and information to the public. This currently hosts a freely accessible Weather Map Viewer, written in JavaScript, which accesses a Web Map Service (WMS), to deliver innovative web-based visualizations of weather and its potential impacts to the public. The intention is to engage the public in the development of new web-based services that more accurately meet their needs. As the service is intended for public use within the UK, it has been designed to support a user base of 5 million, the analysed level of UK web traffic reaching the Met Office's public weather information site. The required scalability has been realised through the use of multi-tier tile caching: - WMS requests are made for 256x256 tiles for fixed areas and zoom levels; - a Tile Cache, developed in house, efficiently serves tiles on demand, managing WMS request for the new tiles; - Edge Servers, externally hosted by Akamai, provide a highly scalable (UK-centric) service for pre-cached tiles, passing new requests to the Tile Cache; - the Invent Weather Map Viewer uses the Google Maps API to request tiles from Edge Servers. (We would expect to make use of the Web Map Tiling Service, when it becomes an OGC standard.) The Met Office delivers specialist commercial products to market sectors such as transport, utilities and defence, which exploit a Web Feature Service (WFS) for data relating forecasts and observations to specific geographic features, and a Web Coverage Service (WCS) for sub-selections of gridded data. These are locally rendered as maps or graphs, and combined with the WMS pre-rendered images and text, in a FLEX application, to provide sophisticated, user impact-based view of the weather. The OGC web services supporting these applications have been developed in collaboration with commercial companies. Visual Weather was originally a desktop application for forecasters, but IBL have developed it to expose the full range of forecast and observation data through standard web services (WCS and WMS). Forecasts and observations relating to specific locations and geographic features are held in an Oracle Database, and exposed as a WFS using Snowflake Software's GO-Publisher application. The Met Office has worked closely with both IBL and Snowflake Software to ensure that the web services provided strike a balance between conformance to the standards and performance in an operational environment. This has proved challenging in areas where the standards are rapidly evolving (e.g. WCS) or do not allow adequate description of the Met-Ocean domain (e.g. multiple time coordinates and parametric vertical coordinates). It has also become clear that careful selection of the features to expose, based on the way in which you expect users to query those features, in necessary in order to deliver adequate performance. These experiences are providing useful 'real-world' input in to the recently launched OGC MetOcean Domain Working Group and World Meteorological Organisation (WMO) initiatives in this area.

Using Cloud-Computing Applications to Support Collaborative Scientific Inquiry: Examining Pre-Service Teachers' Perceived Barriers to Integration

ERIC Educational Resources Information Center

Donna, Joel D.; Miller, Brant G.

2013-01-01

Technology plays a crucial role in facilitating collaboration within the scientific community. Cloud-computing applications, such as Google Drive, can be used to model such collaboration and support inquiry within the secondary science classroom. Little is known about pre-service teachers' beliefs related to the envisioned use of collaborative,…

Student Computer Attitudes, Experience and Perceptions about the Use of Two Software Applications in Building Engineering

ERIC Educational Resources Information Center

Chiner, Esther; Garcia-Vera, Victoria E.

2017-01-01

The purpose of this study was to examine students' computer attitudes and experience, as well as students' perceptions about the use of two specific software applications (Google Drive Spreadsheets and Arquimedes) in the Building Engineering context. The relationships among these variables were also examined. Ninety-two students took part in this…

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

PubMed

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

2017-06-01

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

Maritime Domain Awareness via Agent Learning and Collaboration

DTIC Science & Technology

2010-06-24

available search engines (e.g. Google-like search) are based on popularity or authority scores, which are proven to be useful in marketing and advertising applications...Useful in  marketing   and   advertising  applications  – Not as useful for intelligence applications  – Finding anomalous information can be the goal  • Our

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

Susandi, Armi, E-mail: armi@meteo.itb.ac.id; Tamamadin, Mamad, E-mail: mamadtama@meteo.itb.ac.id; Djamal, Erizal, E-mail: erizal-jamal@yahoo.com

This paper describes information system of rice planting calendar to help farmers in determining the time for rice planting. The information includes rainfall prediction in ten days (dasarian) scale overlaid to map of rice field to produce map of rice planting in village level. The rainfall prediction was produced by stochastic modeling using Fast Fourier Transform (FFT) and Non-Linier Least Squares methods to fit the curve of function to the rainfall data. In this research, the Fourier series has been modified become non-linear function to follow the recent characteristics of rainfall that is non stationary. The results have been alsomore » validated in 4 steps, including R-Square, RMSE, R-Skill, and comparison with field data. The development of information system (cyber extension) provides information such as rainfall prediction, prediction of the planting time, and interactive space for farmers to respond to the information submitted. Interfaces for interactive response will be critical to the improvement of prediction accuracy of information, both rainfall and planting time. The method used to get this information system includes mapping on rice planting prediction, converting the format file, developing database system, developing website, and posting website. Because of this map was overlaid with the Google map, the map files must be converted to the .kml file format.« less

A Different Web-Based Geocoding Service Using Fuzzy Techniques

NASA Astrophysics Data System (ADS)

Pahlavani, P.; Abbaspour, R. A.; Zare Zadiny, A.

2015-12-01

Geocoding - the process of finding position based on descriptive data such as address or postal code - is considered as one of the most commonly used spatial analyses. Many online map providers such as Google Maps, Bing Maps and Yahoo Maps present geocoding as one of their basic capabilities. Despite the diversity of geocoding services, users usually face some limitations when they use available online geocoding services. In existing geocoding services, proximity and nearness concept is not modelled appropriately as well as these services search address only by address matching based on descriptive data. In addition there are also some limitations in display searching results. Resolving these limitations can enhance efficiency of the existing geocoding services. This paper proposes the idea of integrating fuzzy technique with geocoding process to resolve these limitations. In order to implement the proposed method, a web-based system is designed. In proposed method, nearness to places is defined by fuzzy membership functions and multiple fuzzy distance maps are created. Then these fuzzy distance maps are integrated using fuzzy overlay technique for obtain the results. Proposed methods provides different capabilities for users such as ability to search multi-part addresses, searching places based on their location, non-point representation of results as well as displaying search results based on their priority.

The Status of Topographic Mapping in the World a Unggim-Isprs Project 2012-2015

NASA Astrophysics Data System (ADS)

Konecny, G.; Breitkopf, U.; Radtke, A.

2016-06-01

In December 2011, UNGGIM initiated a cooperative project with ISPRS to resume the former UN Secretariat studies on the status of topographic mapping in the world, conducted between 1968 and 1986. After the design of a questionnaire with 27 questions, the UNGGIM Secretariat sent the questionnaires to the UN member states. 115 replies were received from the 193 member states and regions thereof. Regarding the global data coverage and age, the UN questionnaire survey was supplemented by data from the Eastview database. For each of the 27 questions, an interactive viewer was programmed permitting the analysis of the results. The authoritative data coverage at the various scale ranges has greatly increased between 1986 and 2012. Now, a 30 % 1 : 25 000 map data coverage and a 75 % 1 : 50 000 map data coverage has been completed. Nevertheless, there is still an updating problem, as data for some countries is 10 to 30 years old. Private Industry, with Google, Microsoft and Navigation system providers, have undertaken huge efforts to supplement authoritative mapping. For critical areas on the globe, MGCP committed to military mapping at 1 : 50 000. ISPRS has decided to make such surveys a sustainable issue by establishing a working group.

Mapping paddy rice planting area in wheat-rice double-cropped areas through integration of Landsat-8 OLI, MODIS, and PALSAR images.

PubMed

Wang, Jie; Xiao, Xiangming; Qin, Yuanwei; Dong, Jinwei; Zhang, Geli; Kou, Weili; Jin, Cui; Zhou, Yuting; Zhang, Yao

2015-05-12

As farmland systems vary over space and time (season and year), accurate and updated maps of paddy rice are needed for studies of food security and environmental problems. We selected a wheat-rice double-cropped area from fragmented landscapes along the rural-urban complex (Jiangsu Province, China) and explored the potential utility of integrating time series optical images (Landsat-8, MODIS) and radar images (PALSAR) in mapping paddy rice planting areas. We first identified several main types of non-cropland land cover and then identified paddy rice fields by selecting pixels that were inundated only during paddy rice flooding periods. These key temporal windows were determined based on MODIS Land Surface Temperature and vegetation indices. The resultant paddy rice map was evaluated using regions of interest (ROIs) drawn from multiple high-resolution images, Google Earth, and in-situ cropland photos. The estimated overall accuracy and Kappa coefficient were 89.8% and 0.79, respectively. In comparison with the National Land Cover Data (China) from 2010, the resultant map better detected changes in the paddy rice fields and revealed more details about their distribution. These results demonstrate the efficacy of using images from multiple sources to generate paddy rice maps for two-crop rotation systems.

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…

CAMPways: constrained alignment framework for the comparative analysis of a pair of metabolic pathways.

PubMed

Abaka, Gamze; Bıyıkoğlu, Türker; Erten, Cesim

2013-07-01

Given a pair of metabolic pathways, an alignment of the pathways corresponds to a mapping between similar substructures of the pair. Successful alignments may provide useful applications in phylogenetic tree reconstruction, drug design and overall may enhance our understanding of cellular metabolism. We consider the problem of providing one-to-many alignments of reactions in a pair of metabolic pathways. We first provide a constrained alignment framework applicable to the problem. We show that the constrained alignment problem even in a primitive setting is computationally intractable, which justifies efforts for designing efficient heuristics. We present our Constrained Alignment of Metabolic Pathways (CAMPways) algorithm designed for this purpose. Through extensive experiments involving a large pathway database, we demonstrate that when compared with a state-of-the-art alternative, the CAMPways algorithm provides better alignment results on metabolic networks as far as measures based on same-pathway inclusion and biochemical significance are concerned. The execution speed of our algorithm constitutes yet another important improvement over alternative algorithms. Open source codes, executable binary, useful scripts, all the experimental data and the results are freely available as part of the Supplementary Material at http://code.google.com/p/campways/. Supplementary data are available at Bioinformatics online.

Forecasting Zika Incidence in the 2016 Latin America Outbreak Combining Traditional Disease Surveillance with Search, Social Media, and News Report Data

PubMed Central

McGough, Sarah F.; Brownstein, John S.; Hawkins, Jared B.; Santillana, Mauricio

2017-01-01

Background Over 400,000 people across the Americas are thought to have been infected with Zika virus as a consequence of the 2015–2016 Latin American outbreak. Official government-led case count data in Latin America are typically delayed by several weeks, making it difficult to track the disease in a timely manner. Thus, timely disease tracking systems are needed to design and assess interventions to mitigate disease transmission. Methodology/Principal Findings We combined information from Zika-related Google searches, Twitter microblogs, and the HealthMap digital surveillance system with historical Zika suspected case counts to track and predict estimates of suspected weekly Zika cases during the 2015–2016 Latin American outbreak, up to three weeks ahead of the publication of official case data. We evaluated the predictive power of these data and used a dynamic multivariable approach to retrospectively produce predictions of weekly suspected cases for five countries: Colombia, El Salvador, Honduras, Venezuela, and Martinique. Models that combined Google (and Twitter data where available) with autoregressive information showed the best out-of-sample predictive accuracy for 1-week ahead predictions, whereas models that used only Google and Twitter typically performed best for 2- and 3-week ahead predictions. Significance Given the significant delay in the release of official government-reported Zika case counts, we show that these Internet-based data streams can be used as timely and complementary ways to assess the dynamics of the outbreak. PMID:28085877

Using Google Location History to track personal exposure to air pollution

NASA Astrophysics Data System (ADS)

Marais, E. A.; Wiedinmyer, C.

2017-12-01

Big data is increasingly used in air pollution research to monitor air quality and develop mitigation strategies. Google Location History provides an archive of geolocation and time information from mobile devices that can be used to track personal exposure to air pollution. Here we demonstrate the utility of Google Location History for assessing true exposure of individuals to air pollution hazardous to human health in an increasingly mobile world. We use the GEOS-Chem chemical transport model at coarse resolution (2° × 2.5°; latitude × longitude) to calculate and sample surface concentrations of fine particle mass (PM2.5) and ozone concentrations at the same time and location of each of six volunteers for 2 years (June 2015 to May 2017) and compare this to annual mean PM2.5 and ozone estimated at their postal addresses. The latter is synonymous with Global Burden of Disease studies that use a static population distribution map. We find that mobile PM2.5 is higher than static PM2.5 for most (five out of six) volunteers and can lead to a 10% increase in the risk for ischemic heart disease and stroke mortality. The difference may be more if instead a high resolution CTM or an abundant air quality monitoring network is used. There is tremendous potential to exploit geolocation and time data from mobile devices for cohort health studies and to determine best practices for limiting personal exposure to air pollution.

Open Geoscience Database

NASA Astrophysics Data System (ADS)

Bashev, A.

2012-04-01

Currently there is an enormous amount of various geoscience databases. Unfortunately the only users of the majority of the databases are their elaborators. There are several reasons for that: incompaitability, specificity of tasks and objects and so on. However the main obstacles for wide usage of geoscience databases are complexity for elaborators and complication for users. The complexity of architecture leads to high costs that block the public access. The complication prevents users from understanding when and how to use the database. Only databases, associated with GoogleMaps don't have these drawbacks, but they could be hardly named "geoscience" Nevertheless, open and simple geoscience database is necessary at least for educational purposes (see our abstract for ESSI20/EOS12). We developed a database and web interface to work with them and now it is accessible at maps.sch192.ru. In this database a result is a value of a parameter (no matter which) in a station with a certain position, associated with metadata: the date when the result was obtained; the type of a station (lake, soil etc); the contributor that sent the result. Each contributor has its own profile, that allows to estimate the reliability of the data. The results can be represented on GoogleMaps space image as a point in a certain position, coloured according to the value of the parameter. There are default colour scales and each registered user can create the own scale. The results can be also extracted in *.csv file. For both types of representation one could select the data by date, object type, parameter type, area and contributor. The data are uploaded in *.csv format: Name of the station; Lattitude(dd.dddddd); Longitude(ddd.dddddd); Station type; Parameter type; Parameter value; Date(yyyy-mm-dd). The contributor is recognised while entering. This is the minimal set of features that is required to connect a value of a parameter with a position and see the results. All the complicated data treatment could be conducted in other programs after extraction the filtered data into *.csv file. It makes the database understandable for non-experts. The database employs open data format (*.csv) and wide spread tools: PHP as the program language, MySQL as database management system, JavaScript for interaction with GoogleMaps and JQueryUI for create user interface. The database is multilingual: there are association tables, which connect with elements of the database. In total the development required about 150 hours. The database still has several problems. The main problem is the reliability of the data. Actually it needs an expert system for estimation the reliability, but the elaboration of such a system would take more resources than the database itself. The second problem is the problem of stream selection - how to select the stations that are connected with each other (for example, belong to one water stream) and indicate their sequence. Currently the interface is English and Russian. However it can be easily translated to your language. But some problems we decided. For example problem "the problem of the same station" (sometimes the distance between stations is smaller, than the error of position): when you adding new station to the database our application automatically find station near this place. Also we decided problem of object and parameter type (how to regard "EC" and "electrical conductivity" as the same parameter). This problem has been solved using "associative tables". If you would like to see the interface on your language, just contact us. We should send you the list of terms and phrases for translation on your language. The main advantage of the database is that it is totally open: everybody can see, extract the data from the database and use them for non-commercial purposes with no charge. Registered users can contribute to the database without getting paid. We hope, that it will be widely used first of all for education purposes, but professional scientists could use it also.

The Utility of an Online Convenience Panel for Reaching Rare and Dispersed Populations.

PubMed

Sell, Randall; Goldberg, Shoshana; Conron, Kerith

2015-01-01

Gaps in data collection systems, as well as challenges associated with gathering data from rare and dispersed populations, render current health surveillance systems inadequate to identify and monitor efforts to reduce health disparities. Using sexual and gender minorities we investigated the utility of using a large nonprobability online panel to conduct rapid population assessments of such populations using brief surveys. Surveys of the Google Android Panel (four assessing sexual orientation and one assessing gender identity and sex assigned at birth) were conducted resulting in invitation of 53,739 application users (37,505 of whom viewed the invitation) to generate a total of 34,759 who completed screening questions indicating their sexual orientation, or gender identity and sex at birth. Where possible we make comparisons to similar data from two population-based surveys (NHIS and NESARC). We found that 99.4% to 100.0% of respondents across our Google Android panel samples completed the screening questions and 97.8% to 99.2% of those that consented to participate in our surveys indicated they were "OK" with the content of surveys that assessed sexual orientation and sex/gender. In our Google Android panel samples there was a higher percentage of sexual minority respondents than in either NHIS or NESARC with 7.4% of men and 12.4% of women reporting gay, lesbian or bisexual identities. The proportion sexual minority was 2.8 to 5.6 times higher in the Google Android panel samples than was found in the 2012 NHIS sample, for men and women, respectively. The percentage of "transgender" identified individuals in the Google sample was 0.7%, which is similar to 0.5% transgender identified through the Massachusetts BRFSS, and using a transgender status item we found that 2.0% of the overall sample fit could be classified as transgender. The Google samples sometimes more closely approximated national averages for ethnicity and race than NHIS.

The Utility of an Online Convenience Panel for Reaching Rare and Dispersed Populations

PubMed Central

Sell, Randall; Goldberg, Shoshana; Conron, Kerith

2015-01-01

Gaps in data collection systems, as well as challenges associated with gathering data from rare and dispersed populations, render current health surveillance systems inadequate to identify and monitor efforts to reduce health disparities. Using sexual and gender minorities we investigated the utility of using a large nonprobability online panel to conduct rapid population assessments of such populations using brief surveys. Surveys of the Google Android Panel (four assessing sexual orientation and one assessing gender identity and sex assigned at birth) were conducted resulting in invitation of 53,739 application users (37,505 of whom viewed the invitation) to generate a total of 34,759 who completed screening questions indicating their sexual orientation, or gender identity and sex at birth. Where possible we make comparisons to similar data from two population-based surveys (NHIS and NESARC). We found that 99.4% to 100.0% of respondents across our Google Android panel samples completed the screening questions and 97.8% to 99.2% of those that consented to participate in our surveys indicated they were “OK” with the content of surveys that assessed sexual orientation and sex/gender. In our Google Android panel samples there was a higher percentage of sexual minority respondents than in either NHIS or NESARC with 7.4% of men and 12.4% of women reporting gay, lesbian or bisexual identities. The proportion sexual minority was 2.8 to 5.6 times higher in the Google Android panel samples than was found in the 2012 NHIS sample, for men and women, respectively. The percentage of “transgender” identified individuals in the Google sample was 0.7%, which is similar to 0.5% transgender identified through the Massachusetts BRFSS, and using a transgender status item we found that 2.0% of the overall sample fit could be classified as transgender. The Google samples sometimes more closely approximated national averages for ethnicity and race than NHIS. PMID:26641840

How Turkish radiology residents access information related to their profession in this social media and smartphone era.

PubMed

Ozutemiz, Can; Dicle, Oguz; Koremezli, Nevin

2015-01-01

To evaluate the frequency of mobile technology and social media usage among radiology residents and their access to professional information. A questionnaire consisting of 24 questions prepared using Google Drive was sent via e-mail to 550 radiology residents throughout the country. Of the 176 participating residents, 74 completed the survey via the internet, and 102 completed it at three different national radiology meetings. Response rates and its relationship with responses given to different questions were assessed. Hundred two male and 74 female residents participated in the survey. 141 (81.3%) residents thought that they had appropriate internet access in their department. The number of residents using a smartphone was 153 (86.9%). The android operating system (70, 45.8%) was the preferred operating system of respondants. Only 24 (15.7%) of the smartphone users thought that there were enough radiology related applications. "Radiology assistant" (18.9%), "Radiopedia" (7.8%) and "Radiographics" (7.8%) were the most utilized applications. Of the smartphone users, 87(56.9%) stated that they used cell phones in order to find radiological information, and the most used web pages were Google (165, 93.8%), Radiopaedia.org (129, 73.3%), Radiologyassistant.nl (135, 76.7%), and Pubmed (114, 64.8%). Social media usages were as follows: None (10, 5.7%), Facebook (139, 79%), Twitter (55, 31.3%), Google + (51, 29%) and YouTube (44, 25%). While smartphone usage rates among the residents were high, the use of radiology specific applications was not common. Social media usage was very common among residents.

Improving fieldwork by using GIS for quantitative exploration, data management and digital mapping

NASA Astrophysics Data System (ADS)

Marra, Wouter; Alberti, Koko; van de Grint, Liesbeth; Karssenberg, Derek

2016-04-01

Fieldwork is an essential part of teaching geosciences. The essence of a fieldwork is to study natural phenomena in its proper context. Fieldworks dominantly utilize a learning-by-experiencing learning style and are often light on abstract thinking skills. We introduce more of the latter skills to a first-year fieldwork of several weeks by using Geographical Information Systems (GIS). We use simple techniques as the involved students had no prior experience with GIS. In our project, we introduced new tutorials prior to the fieldwork where students explored their research area using aerial photos, satellite images, an elevation model and slope-map using Google Earth and QGIS. The goal of these tutorials was to get acquainted with the area, plan the first steps of the fieldwork, and formulate hypotheses in form of a preliminary map based on quantitative data. During the actual fieldwork, half of the students processed and managed their field data using GIS, used elevation data as additional data source, and made digital geomorphological maps. This was in contrast to the other half of the students that used classic techniques with paper maps. We evaluated the learning benefits by two questionnaires (one before and one after the fieldwork), and a group interview with students that used GIS in the field. Students liked the use of Google Earth and GIS, and many indicate the added value of using quantitative maps. The hypotheses and fieldwork plans of the students were quickly superseded by insights during the fieldwork itself, but making these plans and hypotheses in advance improved the student's ability to perform empirical research. Students were very positive towards the use of GIS for their fieldwork, mainly because they experienced it as a modern and relevant technique for research and the labour market. Tech-savvy students were extra motivated and explored additional methods. There were some minor technical difficulties with using GIS during the fieldwork, but these can be solved by focussing the preparatory tutorials on what to expect during the fieldwork. We did not observe a significant difference in the quality of the products created by students between both groups since both digital and classic maps show a large range of aesthetic and scientific quality. To conclude, we had a positive experience with our first attempt to add GIS components to a classic fieldwork. The main benefit is that students use quantitative data which provides a different view on the fieldwork area and triggers abstract thinking. Future plans include using the student's field data in a web-gis app to allow easy remote supervision and using digital maps in the field.