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Investments in neighborhood built environments could increase physical activity and overall health. Disproportionate distribution of these changes in advantaged neighborhoods could inflate health disparities. Little information exists on where changes are occurring. This paper aims to 1) identify changes in the built environment in neighborhoods and 2) investigate associations between high levels of change and sociodemographic characteristics. Using Geographic Information Systems, neighborhood land-use, local destinations (for walking, social engagement, and physical activity), and sociodemographics were characterized in 2000 and 2010 for seven U.S. cities. Linear and change on change models estimated associations of built environment changes with baseline (2000) and change (2010-2000) in sociodemographics. Spatial patterns were assessed using Global Moran's I to measure overall clustering of change and Local Moran's I to identify statistically significant clusters of high increases surrounded by high increases (HH). Sociodemographic characteristics were compared between HH cluster and other tracts using Analysis of Variance (ANOVA). We observed small land-use changes but increases in the destination types. Greater increases in destinations were associated with higher percentage non-Hispanic whites, percentage households with no vehicle, and median household income. Associations were present for both baseline sociodemographics and changes over time. Greater increases in destinations were associated with lower baseline percentage over 65 but higher increases in percentage over 65 between 2000 and 2010. Global Moran's indicated changes were spatially clustered. HH cluster tracts started with a higher percentage non-Hispanic whites and higher percentage of households without vehicles. Between 2000 and 2010, HH cluster tracts experienced increases in percent non-Hispanic white, greater increases in median household income, and larger decreases in percent of households without a vehicle. Changes in the built environment are occurring in neighborhoods across a diverse set of U.S. metropolitan areas, but are patterned such that they may lead to increased health disparities over time.

BACKGROUND: Land surface temperature (LST) and percent surface imperviousness (SI), both derived from satellite imagery, have been used to characterize the urban heat island effect, a phenomenon in which urban areas are warmer than non-urban areas. OBJECTIVES: We aimed to assess the correlations between LSTs and SI images with actual temperature readings from a ground-based network of outdoor monitors. METHODS: We evaluated the relationships among a) LST calculated from a 2009 summertime satellite image of the Detroit metropolitan region, Michigan; b) SI from the 2006 National Land Cover Data Set; and c) ground-based temperature measurements monitored during the same time period at 19 residences throughout the Detroit metropolitan region. Associations between these ground-based temperatures and the average LSTs and SI at different radii around the point of the ground-based temperature measurement were evaluated at different time intervals. Spearman correlation coefficients and corresponding p-values were calculated. RESULTS: Satellite-derived LST and SI values were significantly correlated with 24-hr average and August monthly average ground temperatures at all but two of the radii examined (100 m for LST and 0 m for SI). Correlations were also significant for temperatures measured between 0400 and 0500 hours for SI, except at 0 m, but not LST. Statistically significant correlations ranging from 0.49 to 0.91 were observed between LST and SI. CONCLUSIONS: Both SI and LST could be used to better understand spatial variation in heat exposures over longer time frames but are less useful for estimating shorter-term, actual temperature exposures, which can be useful for public health preparedness during extreme heat events. KEY WORDS: epidemiology, ground truthing, heat, Landsat satellite, land surface temperature, remote sensing, surface imperviousness, temperature, urban areas. Environ Health Perspect 121:925-931 (2013). http://dx.doi.org/10.1289/ehp.1206176 [Online 7 June 2013], Introduction Use of thermal remote sensing and advanced spatial modeling are emerging trends in environmental epidemiology and public health. Geospatial technologies provide a valuable resource to assist public health practitioners [...]

Global climate change is increasing the frequency of heat waves, hot weather, and temperature variability, which contribute to mortality and illness. Baseline information on local efforts to reduce heat vulnerability, including public advisories; minimizing greenhouse gas emissions; and mitigating urban heat islands, is lacking. We designed a survey about local government programs to prevent health problems and reduce heat exposure during heatwaves and administered it to 285 US communities. Of 70 respondents, 26 indicated that excessive heat events are a significant issue for the local government; 30 had established preventive programs. Local government leadership and public health impacts of heat were cited most frequently as extremely important determinants of preventive programs, followed by implementation costs, economic impacts of hot weather, and greenhouse gas emissions mitigation. Cool paving materials and vegetated roofs were common heat mitigation strategies. Fact sheets and case studies were desired guidance for protecting communities during hot weather. New partnerships and financial resources are needed to support more widespread local action to prevent adverse health consequences of climate change and promote environmental sustainability. [ABSTRACT FROM AUTHOR]