Objective Assessment of Obesogenic Environments in Youth: Geographic Information System Methods and Spatial Findings from the Neighborhood Impact on Kids Study

American Journal of Preventive MedicineAmerican Journal of Preventive Medicine, May 2012, Vol. 42, No. 5

“Background: GIS-based walkability measures designed to explain active travel fail to capture “playability” and proximity to healthy food. These constructs should be considered when measuring potential child obesogenic environments.

“Purpose: The aim of this study was to describe the development of GIS-based multicomponent physical activity and nutrition environment indicators of child obesogenic environments in the San Diego and Seattle regions.

“Methods: Block group–level walkability (street connectivity, residential density, land-use mix, and retail floor area ratio) measures were constructed in each region. Multiple sources were used to enumerate parks (~900–1600 per region) and food establishments (~10,000 per region). Physical activity environments were evaluated on the basis of walkability and presence and quality of parks. Nutrition environments were evaluated based on presence and density of fast-food restaurants and distance to supermarkets. Four neighborhood types were defıned using high/low cut points for physical activity and nutrition environments defıned through an iterative process dependent on regional counts of fast-food outlets and overall distance to parks and grocery stores from census block groups where youth live.

Physical activity and nutrition environments—eligible block groups for San Diego County CA and King County WA

Physical activity and nutrition environments—eligible block groups for San Diego County CA and King County

“Results: To identify suffıcient numbers of children aged 6–11 years, high physical activity environment block groups had at least one high-quality park within 0.25 miles and were above median walkability, whereas low physical activity environment groups had no parks and were below median walkability. High nutrition environment block groups had a supermarket within 0.5 miles, and fewer than 16 (Seattle) and 31 (San Diego) fast-food restaurants within 0.5 miles.Lownutrition environments had either no supermarket, or a supermarket and more than 16 (Seattle) and 31 (San Diego) fast-food restaurants within 0.5 miles. Income, educational attainment, and ethnicity varied across physical activity and nutrition environments.

“Conclusions: These approaches to defıning neighborhood environments can be used to study physical activity, nutrition, and obesity outcomes. Findings presented in a companion paper validate these GIS methods for measuring obesogenic environments.”

A Landslide Expert System: Image Classification through Integration of Data Mining Approaches for Multi-category Analysis

International Journal of Geographical Information ScienceInternational Journal of Geographical Information Science, Volume 26, Issue 4, 2012

Shiuan Wan, Tsu-Chiang Lei & Tein-Yin Chou

“Remote Sensing (RS) data can assist in the classification of landscapes to identify landslides. Recognizing the relationship between landform/landscape and landslide areas is, however, complex. Soil properties, geomorphological, and groundwater conditions govern the instability of slopes. Previous study of Wan (2009; A spatial decision support system for extracting the core factors and thresholds for landslide susceptibility map. Engineering Geology, 108, 237–251) used the maximum-likelihood classifier to classify the multi-category landslide image data. Unfortunately, the classification does not consider the geomorphologic condition. Accordingly, a Landslide Expert System was developed to modify these problems. The system uses multi-date SPOT image data to develop the landslide database. The threshold slope which becomes vulnerable to landslides is obtained by the K-means method. Then, an innovative Data Mining technique – Discrete Rough Sets (DRS) – is applied to obtain the core variables and their relevant thresholds. Finally, the Expert Knowledge Translation Platform (EKTP) is used to create the rules for classification. This study used a new approach called ‘Rough Set Tree’ to demonstrate the performance of the approach. The classification of landslide vulnerable areas, bare land, rock, streams, and water-body is greatly improved.”

A GIS-based Software for Lifeline Reliability Analysis under Seismic Hazard

Computers & GeosciencesComputers & Geosciences, Volume 42, May 2012, Pages 37–46

A. Sevtap Selcuk-Kestel, H. Sebnem Duzgun, and Lutfi Oduncuoglu


  • A GIS-based software for lifeline reliability assessment in GeoTools environment is presented.
  • System reliability under seismic hazard is evaluated based on a network reliability algorithm.
  • The software gives thematic lifeline reliability map and reliability values in graphical form.
  • The software is tested and validated for an application taken from literature.

“Lifelines are vital networks, and it is important that those networks are still functional after major natural disasters such as earthquakes. Assessing reliability of lifelines requires spatial analysis of lifelines with respect to a given earthquake hazard map. In this paper, a GIS-based software for the spatial assessment of lifeline reliability which is developed by using GeoTools environment is presented. The developed GIS-based software imports seismic hazard and lifeline network layers and then creates a gridded network structure. Finally, it adopts a network reliability algorithm to calculate the upper and lower bounds for system reliability of the lifeline under seismic hazard. The software enables user visualizing the reliability values in graphical form as well as thematic lifeline reliability map with colors indicating reliability level along with the link and the overall network. It also provides functions for saving the analysis results in shape file format. The software is tested and validated for an application taken from literature which is a part of water distribution system of Bursa in Turkey. The developed GIS-based software module that creates GIS-based reliability map of the lifelines under seismic hazard is user friendly, modifiable, fast in execution time, illustrative and validated for the existing literature studies.”

Spatial and Temporal Variability of Atlantic Salmon (Salmosalar L.) Spawning Activity in Braided River Channels: A Preliminary Assessment

Aquatic Sciences - Research Across BoundariesAquatic Sciences – Research Across Boundaries, Published Online 02 March 2012

C. Soulsby, J. Grant, C. Gibbins, and I. A. Malcolm

“The distribution of Atlantic salmon redds was recorded during two spawning seasons (2005 and 2006) along a 4 km braided reach of the river Feshie in the Cairngorm mountains, Scotland. Within this complex reach, four main channels types were differentiated on the basis of geographical water sources, channel morphology and hydrochemistry: (1) the main braided channels of the river Feshie; (2) groundwater channels fed by seepage at the edge of the floodplain; (3) hillslope tributary channels and (4) mixed channels downstream of confluences of two or more of types 1–3. The 2005 season was characterised by high and variable flows. In total, 223 redds were observed which were mainly (64%) located in groundwater channels, with relatively few (9%) in the more extensive sections of main channel. The second year had much lower and more stable flows. Here, a total of 337 redds were observed. The largest number were again located in the groundwater channels (44%), though spawning was more evenly distributed in the other channel types, including the main river (19%). It is hypothesised that the apparently more suitable characteristics of groundwater-fed channels relate to a more stable, richer environment for embryo development and juvenile growth, whilst hydraulic conditions and sediment stability in the main channel may create more adverse conditions for successful recruitment.”

Extracting More Data from LiDAR in Forested Areas by Analyzing Waveform Shape

Remote Sensing, 2012, 4(3), 682-702

Thomas Adams, Peter Beets and Christopher Parrish

“Light Detection And Ranging (LiDAR) in forested areas is used for constructing Digital Terrain Models (DTMs), estimating biomass carbon and timber volume and estimating foliage distribution as an indicator of tree growth and health. All of these purposes are hindered by the inability to distinguish the source of returns as foliage, stems, understorey and the ground except by their relative positions. The ability to separate these returns would improve all analyses significantly. Furthermore, waveform metrics providing information on foliage density could improve forest health and growth estimates.

Bivariate frequency distribution of peak height of Gaussian curves fitted to deconvolved waveform LiDAR vs. height above ground.

Bivariate frequency distribution of peak height of Gaussian curves fitted to
deconvolved waveform LiDAR vs. height above ground.

“In this study, the potential to use waveform LiDAR was investigated. Aerial waveform LiDAR data were acquired for a New Zealand radiata pine plantation forest, and Leaf Area Density (LAD) was measured in the field. Waveform peaks with a good signal-to-noise ratio were analyzed and each described with a Gaussian peak height, half-height width, and an exponential decay constant. All parameters varied substantially across all surface types, ruling out the potential to determine source characteristics for individual returns, particularly those with a lower signal-to-noise ratio. However, pulses on the ground on average had a greater intensity, decay constant and a narrower peak than returns from coniferous foliage. When spatially averaged, canopy foliage density (measured as LAD) varied significantly, and was found to be most highly correlated with the volume-average exponential decay rate. A simple model based on the Beer-Lambert law is proposed to explain this relationship, and proposes waveform decay rates as a new metric that is less affected by shadowing than intensity-based metrics. This correlation began to fail when peaks with poorer curve fits were included.”

Increasing Spatial Detail of Burned Scar Maps Using IRS‑AWiFS Data for Mediterranean Europe

Remote Sensing, 2012, 4(3), 726-744

Fernando Sedano, Pieter Kempeneers, Peter Strobl, Daniel McInerney and Jesús San Miguel

“A two stage burned scar detection approach is applied to produce a burned scar map for Mediterranean Europe using IRS-AWiFS imagery acquired at the end of the 2009 fire season. The first stage identified burned scar seeds based on a learning algorithm (Artificial Neural Network) coupled with a bootstrap aggregation process. The second stage implemented a region growing process to extend the area of the burned scars. Several ancillary datasets were used for the accuracy assessment and a final visual check was performed to refine the burned scar product. Training data for the learning algorithm were obtained from MODIS-based polygons, which were generated by the Rapid Damage Assessment module of the European Forest Fire Information System. The map produced from this research is the first attempt to increase the spatial detail of current burned scar maps for the Mediterranean region. The map has been analyzed and compared to existing burned area polygons from the European Forest Fire Information System. The comparison showed that the IRS-AWiFS-based burned scar map improved the delineation of burn scars; in addition the process identified a number of small burned scars that were not detected on lower resolution sensor data. Nonetheless, the results do not clearly support the improved capability for the detection of smaller burned scars.

Snapshots in North-west Spain (ETRS89/LAEA projection) corresponding to: (A) Near infrared IRS-AWiFS; (B) EFFIS-RDA burned scar; (C) IRS-AWiFS-based burned scars.

Snapshots in North-west Spain (ETRS89/LAEA projection) corresponding to:
(A) Near infrared IRS-AWiFS; (B) EFFIS-RDA burned scar; (C) IRS-AWiFS-based
burned scars.

“A number of reasons can be provided for the under-detection of burned scars, these include: the lack of a full coverage and cloud free imagery, the time lag between forest fires and image acquisition date and the occurrence of fires after the image acquisition dates. On the other hand, the limited spectral information combined with the presence of undetected cloud shadows and shaded slopes are reasons for the over-estimation of small burned scars.”

A Spatial Analysis of Individual- and Neighborhood-Level Determinants of Malaria Incidence in Adults, Ontario, Canada

Emerging Infectious Diseases Journal, Volume 18, Number 5—May 2012

Rose Eckhardt, Lea Berrang-Ford, Nancy A. Ross, Dylan R. Pillai, and David L. Buckeridge

“Malaria, once endemic in Canada, is now restricted to imported cases. Imported malaria in Canada has not been examined recently in the context of increased international mobility, which may influence incidence of imported and autochthonous cases. Surveillance of imported cases can highlight high-risk populations and help target prevention and control measures. To identify geographic and individual determinants of malaria incidence in Ontario, Canada, we conducted a descriptive spatial analysis. We then compared characteristics of case-patients and controls.

Percentage of residents in a neighborhood reporting immigration from malaria-endemic areas, greater Toronto area, Ontario, Canada, 2008–2009.

Percentage of residents in a neighborhood reporting immigration from malaria-endemic areas, greater Toronto area, Ontario, Canada, 2008–2009. Red dots, malaria case-patients (positive test results); blue circles, controls (negative test results).

“Case-patients were significantly more likely to be male and live in low-income neighborhoods that had a higher proportion of residents who had emigrated from malaria-endemic regions. This method’s usefulness in clarifying the local patterns of imported malaria in Ontario shows its potential to help identify areas and populations at highest risk for imported and emerging infectious disease.”