Month: May 2010

The Socio-spatial Distribution of Alcohol Outlets in Glasgow City

/ Matt Artz / 1 Comment

Health & Place, Volume 16, Issue 1, January 2010, Pages 167-172

Anne Ellaway, Laura Macdonald, Alasdair Forsyth, and Sally Macintyre

“Aims: The aim of this study was to examine the distribution of alcohol outlets by area deprivation across Glasgow, Scotland.

“Methods: All alcohol outlets were mapped and density per 1000 residents and proximity to nearest outlet calculated across quintiles of area deprivation.

“Results: The socio-spatial distribution of alcohol outlets varies by deprivation across Glasgow but not systematically. Some deprived areas contain the highest concentration while others in similar deprivation quintiles contain very few.

“Conclusions: Considerations of the local context are important in examining access to alcohol but more research is also required on purchasing behaviour.”

Using Remote Sensing and GIS for Damage Assessment after Flooding, the Case of Muscat, Oman after Gonu Tropical Cyclone 2007: Urban Planning Perspective

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REAL CORP 2010 Proceedings/Tagungsband, Vienna, 18-20 May 2010

Lotfy Kamal Azaz

“Natural Disasters occur frequently around the world, and their incidence and intensity seem to be increasing in recent years. The Disasters such as cyclones and floods often cause significant loss of life, large-scale economic and social impacts, and environmental damage. For example, Cyclone Gonu was the strongest tropical cyclone on record in the Arabian Sea, and tied for the strongest tropical cyclone on record in the northern Indian Ocean and was the strongest named cyclone in this basin. On June 5 2007 it made landfall on the eastern-most tip of Oman with winds of 150 km/h (90 mph). Gonu dropped heavy rainfall near the eastern coastline, reaching up to 610 mm (24 inches), which caused flooding and heavy damage. The cyclone caused about $4 billion in damage and nearly 50 deaths in Oman, where the cyclone was considered the nation’s worst natural disaster. Nowadays, we have access to data and techniques provided by remote sensing and GIS that have proven their usefulness in disaster management plan. Remote Sensing can assists in damage assessment monitoring, providing a quantitative base for relief operations. After that, it can be used to map the new situation and update the database used for the reconstruction of an area. Disaster management plan consists of two phases that takes place before disaster occurs, disaster prevention and disaster preparedness, a three phases that happens after the occurrence of a disaster i.e. disaster relief, rehabilitation and reconstruction. In the disaster rehabilitation phase GIS is used to organize the damage information and the post-disaster census information, and in the evaluation of sites for reconstruction. In this  study, two IKONOS satellite images of Muscat, Oman have been utilized; one image before the cyclone and one after. The two images have been geometrically corrected. Change detection has been applied to identify and assess the damages. The results of this study emphasize the importance of using remote sensing and GIS in damage assessment phase as part of effective Disaster Management Plan.”

Mapping Diversified Peri-urban Agriculture – Potential of Object-based Versus Per-field Land Cover/Land Use Classification

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Geocarto International, Volume 25, Issue 3 June 2010 , pages 171 – 186

Dionys Forster; Tobias Walter Kellenberger; Yves Buehler; Bernd Lennartz

“High spatial resolution satellite data contribute to improving land cover/land use (LCLU) classification in agriculture. A classification procedure based on Quickbird satellite image data was developed to map LCLU of diversified agriculture at sub-communal and communal level (7 km2). Segmentation performance of the panchromatic band in combination with high pass filters (HPF) was tested first. Accuracy of field boundary delineation was evaluated by an object-based segmentation, a per-field and a manual classification, along with a quantitative accuracy assessment. Sub-communal classification revealed an overall accuracy of 84% with a κ coefficient of 0.77 for the per-field vector segmentation compared to an overall accuracy of 56-60% and a κ coefficient of 0.37-0.42 for object-based approaches. Per-field vector segmentation was thus superior and used for LCLU classification at communal level. Overall accuracy scored 83% and the κ coefficient 0.7. In diversified agriculture, per-field vector segmentation and classification achieved higher classification results.”

Environmental Justice in Berlin: GIS-based Method Determining an Aggregated Index for Urban Planning

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REAL CORP 2010 Proceedings/Tagungsband, Vienna, 18-20 May 2010

Gesa Geißler, Birgit Kleinschmit, Robert Ahrberg, Battugs Erdenetsogt, Yvonne Heimann, Lisa Heinsch, Laura Hensel, Thomas Herff, Josephine Janke, Philipp Kaufmann, Miriam Kothe, Hendrikje Leutloff, Anja Manzke, Anke Rehhausen, Sebastian Schramm, Stefanie Töpper, Sebastian Unger, and Bartlomiej Wisniewski

“In the early nineties, a wide discussion about Environmental Justice has started among German health scientists, sociologists, and other academics. In this context, several studies focussing on the disproportional burden of discrete environmental hazards on different socio-economic groups were carried out.

“The present paper reviews a method to index several Environmental Justice factors within planning areas of Berlin. In order to examine the current status, the spatial distribution of thermal comfort, green spaces and emissions of PM10 and NOx has been determined, using a GIS-based analysis. These results were then related to data on the social status. The various outcomes show a complex relation between social status and exposure to environmental quality, but reveal a tendency of disproportional distribution, prejudicing groups of lower social status.

“In order to develop a planning area based measure of Environmental Justice, the analysed factors were aggregated into a single environmental impact factor and combined with the associated social status. Finally, possibilities of integrating this factor into urban planning in Berlin were identified.”

Automatic Cluster Identification for Environmental Applications using the Self-organizing Maps and a New Genetic Algorithm

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Geocarto International, Volume 25, Issue 1 February 2010, pages 53 – 69

Tonny J. Oyana and Dajun Dai

“A rapid increase of environmental data dimensionality emphasizes the importance of developing data-driven inductive approaches to geographic analysis. This article uses a loosely coupled strategy to combine the technique of self-organizing maps (SOM) with a new genetic algorithm (GA) for automatic identification of clusters in multidimensional environmental datasets. In the first stage, we employ the well-known classic SOM because it is able to handle the dimensional interactions and capture the number of clusters via visualization; and thus provide extraordinary insights into original data. In the second stage, this new GA rigorously delineates the cluster boundaries using a flexibly oriented elliptical search window. To test this approach, one synthetic and two real-world datasets are employed. The results confirm a more robust and reliable approach that provides a better understanding and interpretation of massive multivariate environmental datasets, thus maximizing our insights. Other key benefits include the fact that it provides a computationally fast and efficient environment to accurately detect clusters, and is highly flexible. In a nutshell, the article presents a computational approach to facilitate knowledge discovery of massive multivariate environmental datasets; as we are too familiar with their accelerating growth rate.”

The Longevity Pattern in Emilia Romagna: A Spatio-temporal Analysis

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Paper submitted to SIS 2010

Giulia Roli, Rossella Miglio, Rosella Rettaroli, and Alessandra Samoggia

“In this paper, we investigate the pattern of longevity in Emilia Romagna, a North-Eastern region of Italy, at a municipality level. We consider a modified version of Centenarian Rate in two different periods. Spatio-temporal modeling is used to tackle at both periods the random variations in the occurrence of long-lived individuals, due to the rareness of such events in small areas. This method allows to exploit the spatial proximity smoothing the observed data, as well as to control for the effects of a set of regressors. As a result, clusters of areas characterized by extreme indexes of longevity are well identified and the temporal evolution of the phenomenon can be depicted. In addition, we evaluate the effects of the structure of mortality on the cohort of long-lived subjects in the second period. A spatial analysis is carried out by including the territorial patterns of mortality in a longitudinal perspective. We control for the major causes of death in order to deepen the analysis of the observed geographical differences.”

A Spatial Analysis of Health-related Resources in Three Diverse Metropolitan Areas

/ Matt Artz / 1 Comment

Health Place, 2010 May 15

Smiley MJ, Diez Roux AV, Brines SJ, Brown DG, Evenson KR, and Rodriguez DA

“Few studies have investigated the spatial clustering of multiple health-related resources. We constructed 0.5 mile kernel densities of resources for census areas in New York City, NY (n=819 block groups), Baltimore, MD (n=737), and Winston-Salem, NC (n=169). Three of the four resource densities (supermarkets/produce stores, retail areas, and recreational facilities) tended to be correlated with each other, whereas park density was less consistently and sometimes negatively correlated with others. Blacks were more likely to live in block groups with multiple low resource densities. Spatial regression models showed that block groups with higher proportions of black residents tended to have lower supermarket/produce, retail, and recreational facility densities, although these associations did not always achieve statistical significance. A measure that combined local and neighboring block group racial composition was often a stronger predictor of resources than the local measure alone. Overall, our results from three diverse U.S. cities show that health-related resources are not randomly distributed across space and that disadvantage in multiple domains often clusters with residential racial patterning.”

Advancing the Science of Climate Change

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…a new study from the National Research Council…

“The compelling case that climate change is occurring and is caused in large part by human activities is based on a strong, credible body of evidence, says Advancing the Science of Climate Change, one of the new books. While noting that there is always more to learn and that the scientific process is never “closed,” the book emphasizes that multiple lines of evidence support scientific understanding of climate change.

“The core phenomenon, scientific questions, and hypotheses have been examined thoroughly and have stood firm in the face of serious debate and careful evaluation of alternative explanations, the book says.”

Atmosphere, Climate, and Weather Papers at the 2010 ESRI International User Conference

/ Matt Artz

Real-World Applications of GIS in Meteorology

  • The Colorado Statewide Snow Avalanche Path GIS Database and Project
  • Effect of Surface Characteristics on Tornado Vortex Signatures

Software and Hardware Tools for Climatology and Meteorology

  • An Open Geospatial Consortium Standards-based Arctic Climatology Sensor Network Prototype
  • Using Mobile Devices for Enhanced Storm Damage Surveys
  • Mapping and Animating Air Masses with Python and ArcObjects

From the Wet Side: Marine Climatology and Climate Impacts

  • Integration of Hurricane Model with Socio-Economic Data
  • HabitatSpace – to visualize/analyze climate change effects in 3-D
  • Analysis and Visualisation of Atmospheric and Marine Meteorology Information

Panel Discussion: Atmosphere 2.0

  • This discussion will focus on how atmospheric and environmental sciences are now using mapping to engage the public, mostly by citizen generated content.

Obesity Remains an Economic Issue, Seattle Obesity Study Finds

/ Matt Artz

Ensuring access to healthy, affordable foods is a top priority in tackling the obesity epidemic in the United States. Over the course of the last six months, the Institute of Medicine, United States Department of Agriculture, The White House and First Lady Michelle Obama have taken an interest in improving access to affordable and nutritious foods. Here in Seattle, Adam Drewnowski, UW professor of epidemiology, and his team are tackling the same issue. Remember the “fat zip codes” that predicted obesity rates from a few years ago? Drewnowski and his team were the brains behind that, as well as last summer’s study which showed that grocery prices in Seattle varied greatly between one supermarket chain and another.

Now, researchers at the UW Center for Public Health Nutrition, UW Urban Form Lab and the Nutritional Sciences Program in the School of Public Health are asking: “Who buys what foods, why, where, and for how much?”

The answers might surprise you. Most studies have used distance to the nearest supermarket as the best predictor of whether people have good diets and better health. But Drewnowski and team say that’s not true. “Six out of seven people shopped for food outside their immediate neighborhood,” he said “The closest supermarket for most people was less than a mile away, but people chose the market that was more than three miles away.” Driving further to save money on groceries is common. For that reason, physical proximity to a supermarket may not, by itself, assure a healthy diet. “Money does matter,” Drewnowski said.

Areas where access to healthy affordable foods is scarce have become known as “food deserts.” Seattle, however, is well-supplied with supermarkets, grocery stores, farmers markets and other vendors, said Drewnowski. “We do not see evidence of significant food deserts,” he said. In comparison with other areas in the state, public transportation is also prevalent and accessible, so people can take a bus to a supermarket or grocery store with relative ease.

Researchers combined a telephone survey, modeled on the Centers for Disease Control and Prevention (CDC) Behavioral Risk Factors Surveillance System, with new geo-coding techniques and methods of spatial analysis for the new study.

Economic access has also become a primary research focus in public health nutrition, including the work by Drewnowski and team. Supermarket chains have specific demographics–consumers differ by age, education, income, health, and even obesity rates. “The county-wide obesity rate in 2007 was 19.8 percent, but our research found that the obesity rate was only four percent among Whole Foods and PCC shoppers,” said Drewnowski. “Consumers who shop at most area supermarket chains have obesity rates at 25 percent and higher. Clearly, not all supermarkets are the same and economic access is determined by price.”

UW researchers recently discussed the Seattle Obesity Study results at “Shopping for Health” conference, which brought together public health agencies, academicians, supermarket representatives and policymakers from Seattle, King County and Washington state. Additional findings include:

  • New ways to identify underserved areas (“food deserts”) in Washington state that are most in need of resources
  • New ways to identify healthy, affordable and sustainable foods
  • The Seattle Atlas, or SEATTLAS, of all food sources, including supermarkets, grocery stores, and fast food restaurants
  • Food purchases and expenditures, diet quality and weight/ obesity
  • Insights from similar studies conducted in New York City.

“We plan to explore how local data can best be used in new initiatives to improve access to healthy, affordable foods in Seattle, King County and throughout Washington state,” said Drewnowski. “As part of the dialogue, it is extremely important that the food industry be part of the solution and we welcomed their presence at this recent gathering,” he said. “We hope to provide the local answer to the question that the federal government is trying to address. And we want to make sure our public health initiatives and programs are backed by research and science.”

[Source: University of Washington press release]