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        <title>International Journal of Health Geographics - Most accessed articles</title>
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        <description>The most accessed research articles published by International Journal of Health Geographics</description>
        <dc:date>2012-01-12T00:00:00Z</dc:date>
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        <title>Crowdsourcing, citizen sensing and Sensor Web technologies for public and environmental health surveillance and crisis management: trends, OGC standards and application examples</title>
        <description>&apos;Wikification of GIS by the masses&apos; is a phrase-term first coined by Kamel Boulos in 2005, two years earlier than Goodchild&apos;s term &apos;Volunteered Geographic Information&apos;. Six years later (2005-2011), OpenStreetMap and Google Earth (GE) are now full-fledged, crowdsourced &apos;Wikipedias of the Earth&apos; par excellence, with millions of users contributing their own layers to GE, attaching photos, videos, notes and even 3-D (three dimensional) models to locations in GE. From using Twitter in participatory sensing and bicycle-mounted sensors in pervasive environmental sensing, to creating a 100,000-sensor geo-mashup using Semantic Web technology, to the 3-D visualisation of indoor and outdoor surveillance data in real-time and the development of next-generation, collaborative natural user interfaces that will power the spatially-enabled public health and emergency situation rooms of the future, where sensor data and citizen reports can be triaged and acted upon in real-time by distributed teams of professionals, this paper offers a comprehensive state-of-the-art review of the overlapping domains of the Sensor Web, citizen sensing and &apos;human-in-the-loop sensing&apos; in the era of the Mobile and Social Web, and the roles these domains can play in environmental and public health surveillance and crisis/disaster informatics. We provide an in-depth review of the key issues and trends in these areas, the challenges faced when reasoning and making decisions with real-time crowdsourced data (such as issues of information overload, &quot;noise&quot;, misinformation, bias and trust), the core technologies and Open Geospatial Consortium (OGC) standards involved (Sensor Web Enablement and Open GeoSMS), as well as a few outstanding project implementation examples from around the world.</description>
        <link>http://www.ij-healthgeographics.com/content/10/1/67</link>
                <dc:creator>Maged Kamel Boulos</dc:creator>
                <dc:creator>Bernd Resch</dc:creator>
                <dc:creator>David Crowley</dc:creator>
                <dc:creator>John Breslin</dc:creator>
                <dc:creator>Gunho Sohn</dc:creator>
                <dc:creator>Russ Burtner</dc:creator>
                <dc:creator>William Pike</dc:creator>
                <dc:creator>Eduardo Jezierski</dc:creator>
                <dc:creator>Kuo-Yu Slayer Chuang</dc:creator>
                <dc:source>International Journal of Health Geographics 2011, null:67</dc:source>
        <dc:date>2011-12-21T00:00:00Z</dc:date>
        <dc:identifier>doi:10.1186/1476-072X-10-67</dc:identifier>
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        <title>Open-Source Web-based Geographical Information System for health exposure assessment</title>
        <description>This paper presents the design and development of an open source web-based Geographical Information System allowing users to visualise, customise and interact with spatial data within their web browser. The developed application shows that by using solely Open Source software it was possible to develop a customisable web based GIS application that provides functions necessary to convey health and environmental data to experts and non-experts alike without the requirement of proprietary software.</description>
        <link>http://www.ij-healthgeographics.com/content/11/1/2</link>
                <dc:creator>Barry Evans</dc:creator>
                <dc:creator>Clive Sabel</dc:creator>
                <dc:source>International Journal of Health Geographics 2012, null:2</dc:source>
        <dc:date>2012-01-10T00:00:00Z</dc:date>
        <dc:identifier>doi:10.1186/1476-072X-11-2</dc:identifier>
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        <item rdf:about="http://www.ij-healthgeographics.com/content/10/1/45">
        <title>Web GIS in practice X: a Microsoft Kinect natural user interface for Google Earth navigation</title>
        <description>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&amp;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, &amp; 3) that contains a &apos;Kinnogle installation package for Windows PCs&apos;. 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 &apos;use scenarios&apos; where such NUIs could prove useful in navigating a 3-D virtual globe, compared to conventional mouse/3-D mouse and keyboard-based interfaces.Additional file 1Installation package for Kinoogle (part 1 of 3). Compressed (zipped) archive containing Kinoogle&apos;s installation package for Microsoft Windows operating systems. Download and unzip the contents of Additional file 1, Additional file 2, and Additional file 3 to the same hard drive location, then run &apos;Additional_file.part1.exe&apos; from that location.Click here for fileAdditional file 2Installation package for Kinoogle (part 2 of 3). Compressed (zipped) archive containing Kinoogle&apos;s installation package for Microsoft Windows operating systems. Download and unzip the contents of Additional file 1, Additional file 2, and Additional file 3 to the same hard drive location, then run &apos;Additional_file.part1.exe&apos; from that location.Click here for fileAdditional file 3Installation package for Kinoogle (part 3 of 3). Compressed (zipped) archive containing Kinoogle&apos;s installation package for Microsoft Windows operating systems. Download and unzip the contents of Additional file 1, Additional file 2, and Additional file 3 to the same hard drive location, then run &apos;Additional_file.part1.exe&apos; from that location.Click here for file</description>
        <link>http://www.ij-healthgeographics.com/content/10/1/45</link>
                <dc:creator>Maged Kamel Boulos</dc:creator>
                <dc:creator>Bryan Blanchard</dc:creator>
                <dc:creator>Cory Walker</dc:creator>
                <dc:creator>Julio Montero</dc:creator>
                <dc:creator>Aalap Tripathy</dc:creator>
                <dc:creator>Ricardo Gutierrez-Osuna</dc:creator>
                <dc:source>International Journal of Health Geographics 2011, null:45</dc:source>
        <dc:date>2011-07-26T00:00:00Z</dc:date>
        <dc:identifier>doi:10.1186/1476-072X-10-45</dc:identifier>
                            <dc:title>A Microsoft Kinect natural user interface for Google Earth navigation</dc:title>
                            <dc:description>Depth sensors such as Microsoft Kinect and ASUS Xtion can 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.</dc:description>
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        <item rdf:about="http://www.ij-healthgeographics.com/content/3/1/1">
        <title>Towards evidence-based, GIS-driven national spatial health information infrastructure and surveillance services in the United Kingdom</title>
        <description>The term &quot;Geographic Information Systems&quot; (GIS) has been added to MeSH in 2003, a step reflecting the importance and growing use of GIS in health and healthcare research and practices. GIS have much more to offer than the obvious digital cartography (map) functions. From a community health perspective, GIS could potentially act as powerful evidence-based practice tools for early problem detection and solving. When properly used, GIS can: inform and educate (professionals and the public); empower decision-making at all levels; help in planning and tweaking clinically and cost-effective actions, in predicting outcomes before making any financial commitments and ascribing priorities in a climate of finite resources; change practices; and continually monitor and analyse changes, as well as sentinel events. Yet despite all these potentials for GIS, they remain under-utilised in the UK National Health Service (NHS). This paper has the following objectives: (1) to illustrate with practical, real-world scenarios and examples from the literature the different GIS methods and uses to improve community health and healthcare practices, e.g., for improving hospital bed availability, in community health and bioterrorism surveillance services, and in the latest SARS outbreak; (2) to discuss challenges and problems currently hindering the wide-scale adoption of GIS across the NHS; and (3) to identify the most important requirements and ingredients for addressing these challenges, and realising GIS potential within the NHS, guided by related initiatives worldwide. The ultimate goal is to illuminate the road towards implementing a comprehensive national, multi-agency spatio-temporal health information infrastructure functioning proactively in real time. The concepts and principles presented in this paper can be also applied in other countries, and on regional (e.g., European Union) and global levels.</description>
        <link>http://www.ij-healthgeographics.com/content/3/1/1</link>
                <dc:creator>Maged Kamel Boulos</dc:creator>
                <dc:source>International Journal of Health Geographics 2004, null:1</dc:source>
        <dc:date>2004-01-28T00:00:00Z</dc:date>
        <dc:identifier>doi:10.1186/1476-072X-3-1</dc:identifier>
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        <item rdf:about="http://www.ij-healthgeographics.com/content/10/1/66">
        <title>Where they live, how they play: Neighborhood greenness and outdoor physical activity among preschoolers
</title>
        <description>Background:
Emerging empirical evidence suggests exposure to &quot;green&quot; environments may encourage higher levels of physical activity among children. Few studies, however, have explored this association exclusively in pre-school aged children in the United States. We examined whether residing in neighborhoods with higher levels of greenness was associated with higher levels of outdoor physical activity among preschoolers. In addition, we also explored whether outdoor playing behaviors (e.g., active vs. quiet) were influenced by levels of neighborhood greenness independent of demographic and parental support factors.
Results:
Higher levels of neighborhood greenness as measured by the Normalized Difference Vegetation Index (NDVI)  was associated with higher levels of outdoor playing time among  preschool-aged children in our sample. Specifically, a one unit increase in neighborhood greenness increased a child&apos;s outdoor playing time by approximately 3 minutes.    A dose-response relationship was observed between increasing levels of parental support for physical activity (e.g., time spent playing with children) and child outdoor physical activity (p&lt;0.01).
Conclusions:
Consistent with previous studies, neighborhood greenness influences physical activity behavior. However, for preschoolers, parental involvement may be more critical for improving physical activity levels.</description>
        <link>http://www.ij-healthgeographics.com/content/10/1/66</link>
                <dc:creator>Diana Grigsby-Toussaint</dc:creator>
                <dc:creator>Sang-Hyun Chi</dc:creator>
                <dc:creator>Barbara Fiese</dc:creator>
                <dc:source>International Journal of Health Geographics 2011, null:66</dc:source>
        <dc:date>2011-12-14T00:00:00Z</dc:date>
        <dc:identifier>doi:10.1186/1476-072X-10-66</dc:identifier>
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        <item rdf:about="http://www.ij-healthgeographics.com/content/7/1/64">
        <title>Spatial patterns of natural hazards mortality in the United States </title>
        <description>Background:
Studies on natural hazard mortality are most often hazard-specific (e.g. floods, earthquakes, heat), event specific (e.g. Hurricane Katrina), or lack adequate temporal or geographic coverage. This makes it difficult to assess mortality from natural hazards in any systematic way. This paper examines the spatial patterns of natural hazard mortality at the county-level for the U.S. from 1970&#8211;2004 using a combination of geographical and epidemiological methods.
Results:
Chronic everyday hazards such as severe weather (summer and winter) and heat account for the majority of natural hazard fatalities. The regions most prone to deaths from natural hazards are the South and intermountain west, but sub-regional county-level mortality patterns show more variability. There is a distinct urban/rural component to the county patterns as well as a coastal trend. Significant clusters of high mortality are in the lower Mississippi Valley, upper Great Plains, and Mountain West, with additional areas in west Texas, and the panhandle of Florida, Significant clusters of low mortality are in the Midwest and urbanized Northeast.
Conclusion:
There is no consistent source of hazard mortality data, yet improvements in existing databases can produce quality data that can be incorporated into spatial epidemiological studies as demonstrated in this paper. It is important to view natural hazard mortality through a geographic lens so as to better inform the public living in such hazard prone areas, but more importantly to inform local emergency practitioners who must plan for and respond to disasters in their community.</description>
        <link>http://www.ij-healthgeographics.com/content/7/1/64</link>
                <dc:creator>Kevin Borden</dc:creator>
                <dc:creator>Susan Cutter</dc:creator>
                <dc:source>International Journal of Health Geographics 2008, null:64</dc:source>
        <dc:date>2008-12-17T00:00:00Z</dc:date>
        <dc:identifier>doi:10.1186/1476-072X-7-64</dc:identifier>
                            <dc:title>Mapping US natural disasters </dc:title>
                            <dc:description>Quantifying mortality patterns caused by natural hazards at a local level can help inform communities about their relative risk and improve emergency planning, particularly in the most hazardous areas.</dc:description>
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        <item rdf:about="http://www.ij-healthgeographics.com/content/11/1/3">
        <title>US census unit population exposures to ambient air pollutants</title>
        <description>Background:
Progress has been made recently in estimating ambient PM2.5 (particulate matter with aerodynamic diameter &lt; 2.5 &#956;m) and ozone concentrations using various data sources and advanced modeling techniques, which resulted in gridded surfaces. However, epidemiologic and health impact studies often require population exposures to ambient air pollutants to be presented at an appropriate census geographic unit (CGU), where health data are usually available to maintain confidentiality of individual health data. We aim to generate estimates of population exposures to ambient PM2.5 and ozone for U.S. CGUs.
Methods:
We converted 2001-2006 gridded data, generated by the U.S. Environmental Protection Agency (EPA) for CDC&apos;s (Centers for Disease Control and Prevention) Environmental Public Health Tracking Network (EPHTN), to census block group (BG) based on spatial proximities between BG and its four nearest grids. We used a bottom-up (fine to coarse) strategy to generate population exposure estimates for larger CGUs by aggregating BG estimates weighted by population distribution.
Results:
The BG daily estimates were comparable to monitoring data. On average, the estimates deviated by 2 &#956;g/m3 (for PM2.5) and 3 ppb (for ozone) from their corresponding observed values. Population exposures to ambient PM2.5 and ozone varied greatly across the U.S. In 2006, estimates for daily potential population exposure to ambient PM2.5 in west coast states, the northwest and a few areas in the east and estimates for daily potential population exposure to ambient ozone in most of California and a few areas in the east/southeast exceeded the National Ambient Air Quality Standards (NAAQS) for at least 7 days.
Conclusions:
These estimates may be useful in assessing health impacts through linkage studies and in communicating with the public and policy makers for potential intervention.</description>
        <link>http://www.ij-healthgeographics.com/content/11/1/3</link>
                <dc:creator>Yongping Hao</dc:creator>
                <dc:creator>Helen Flowers</dc:creator>
                <dc:creator>Michele Monti</dc:creator>
                <dc:creator>Judith Qualters</dc:creator>
                <dc:source>International Journal of Health Geographics 2012, null:3</dc:source>
        <dc:date>2012-01-12T00:00:00Z</dc:date>
        <dc:identifier>doi:10.1186/1476-072X-11-3</dc:identifier>
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        <item rdf:about="http://www.ij-healthgeographics.com/content/10/1/68">
        <title>Proximity of public elementary schools to major roads in Canadian urban areas</title>
        <description>Background:
Epidemiologic studies have linked exposure to traffic-generated air and noise pollution with a wide range of adverse health effects in children.  Children spend a large portion of time at school, and both air pollution and noise are elevated in close proximity to roads, so school location may be an important determinant of exposure.  No studies have yet examined the proximity of schools to major roads outside of the US.
Methods:
Data on public elementary schools in Canada&apos;s 10 most populous cities were obtained from online databases.  School addresses were geocoded and proximity to the nearest major road, defined using a standardized national road classification scheme, was calculated for each school.  Based on measurements of nitrogen oxide concentrations, ultrafine particle counts, and noise levels in three Canadian cities we conservatively defined distances &lt;75 m from major roads as the zone of primary interest.  Census data at the city and neighborhood levels were used to evaluate relationships between school proximity to major roads, urban density, and indicators of socioeconomic status.
Results:
Addresses were obtained for 1,556 public elementary schools, 95% of which were successfully geocoded.  Across all 10 cities, 16.3% of schools were located within 75 m of a major road, with wide variability between cities.  Schools in neighborhoods with higher median income were less likely to be near major roads (OR per $20,000 increase: 0.81; 95% CI: 0.65, 1.00), while schools in densely populated neighborhoods were more frequently close to major roads (OR per 1,000 dwellings/km2: 1.07; 95% CI: 1.00, 1.16).  Over 22% of schools in the lowest neighborhood income quintile were close to major roads, compared to 13% of schools in the highest income quintile.
Conclusions:
A substantial fraction of students at public elementary schools in Canada, particularly students attending schools in low income neighborhoods, may be exposed to elevated levels of air pollution and noise while at school.  As a result, the locations of schools may negatively impact the healthy development and academic performance of a large number of Canadian children.</description>
        <link>http://www.ij-healthgeographics.com/content/10/1/68</link>
                <dc:creator>Ofer Amram</dc:creator>
                <dc:creator>Rebecca Abernethy</dc:creator>
                <dc:creator>Michael Brauer</dc:creator>
                <dc:creator>Hugh Davies</dc:creator>
                <dc:creator>Ryan Allen</dc:creator>
                <dc:source>International Journal of Health Geographics 2011, null:68</dc:source>
        <dc:date>2011-12-21T00:00:00Z</dc:date>
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        <item rdf:about="http://www.ij-healthgeographics.com/content/4/1/22">
        <title>Web GIS in practice III: creating a simple interactive map of England&amp;apos;s Strategic Health Authorities using Google Maps API, Google Earth KML, and MSN Virtual Earth Map Control</title>
        <description>This eye-opener article aims at introducing the health GIS community to the emerging online consumer geoinformatics services from Google and Microsoft (MSN), and their potential utility in creating custom online interactive health maps. Using the programmable interfaces provided by Google and MSN, we created three interactive demonstrator maps of England&apos;s Strategic Health Authorities. These can be browsed online at http://www.healthcybermap.org/GoogleMapsAPI/ &#8211; Google Maps API (Application Programming Interface) version, http://www.healthcybermap.org/GoogleEarthKML/ &#8211; Google Earth KML (Keyhole Markup Language) version, and http://www.healthcybermap.org/MSNVirtualEarth/ &#8211; MSN Virtual Earth Map Control version. Google and MSN&apos;s worldwide distribution of &quot;free&quot; geospatial tools, imagery, and maps is to be commended as a significant step towards the ultimate &quot;wikification&quot; of maps and GIS. A discussion is provided of these emerging online mapping trends, their expected future implications and development directions, and associated individual privacy, national security and copyrights issues. Although ESRI have announced their planned response to Google (and MSN), it remains to be seen how their envisaged plans will materialize and compare to the offerings from Google and MSN, and also how Google and MSN mapping tools will further evolve in the near future.</description>
        <link>http://www.ij-healthgeographics.com/content/4/1/22</link>
                <dc:creator>Maged Kamel Boulos</dc:creator>
                <dc:source>International Journal of Health Geographics 2005, null:22</dc:source>
        <dc:date>2005-09-21T00:00:00Z</dc:date>
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        <title>Mapping the evolution of &apos;food deserts&apos; in a Canadian city: Supermarket accessibility in London, Ontario, 1961-2005</title>
        <description>Background:
A growing body of research suggests that the suburbanization of food retailers in North America and the United Kingdom in recent decades has contributed to the emergence of urban &apos;food deserts&apos;, or disadvantaged areas of cities with relatively poor access to healthy and affordable food. This paper explores the evolution of food deserts in a mid-sized Canadian city (London, Ontario) by using a geographic information system (GIS) to map the precise locations of supermarkets in 1961 and 2005; multiple techniques of network analysis were used to assess changing levels of supermarket access in relation to neighbourhood location, socioeconomic characteristics, and access to public transit.
Results:
The findings indicate that residents of inner-city neighbourhoods of low socioeconomic status have the poorest access to supermarkets. Furthermore, spatial inequalities in access to supermarkets have increased over time, particularly in the inner-city neighbourhoods of Central and East London, where distinct urban food deserts now exist.
Conclusion:
Contrary to recent findings in larger Canadian cities, we conclude that urban food deserts exist in London, Ontario. Policies aimed at improving public health must also recognize the spatial, as well as socioeconomic, inequities with respect to access to healthy and affordable food. Additional research is necessary to better understand how supermarket access influences dietary behaviours and related health outcomes.</description>
        <link>http://www.ij-healthgeographics.com/content/7/1/16</link>
                <dc:creator>Kristian Larsen</dc:creator>
                <dc:creator>Jason Gilliland</dc:creator>
                <dc:source>International Journal of Health Geographics 2008, null:16</dc:source>
        <dc:date>2008-04-18T00:00:00Z</dc:date>
        <dc:identifier>doi:10.1186/1476-072X-7-16</dc:identifier>
                            <dc:title>Supermarkets key to good nutrition </dc:title>
                            <dc:description>Urban food deserts have spatial as well as socioeconomic causes and these should be considered when developing public health strategies designed to overcome nutritional inequities in city communities. </dc:description>
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        <prism:issn>1476-072X</prism:issn>
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        <prism:startingPage>16</prism:startingPage>
        <prism:publicationDate>2008-04-18T00:00:00Z</prism:publicationDate>
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