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<p>This analysis, done in support of the Proctor Creek Health Impact project, produced a grid showing where green infrastructure would likely have the highest benefit. The grid analysis, based on a publican by GreenLaw* was carried out as follows. First, spatial data was gathered and/or generated for metrics, that may correlate with or compound health or environmental outcomes associated with flooding or extreme heat events. Secondly, a grid of evenly sized squares was created and overlain on the study area and the presence of each metric was measured within each cell (percent area or mean value). Finally, to normalize the data values, the summed values were classified into five equal quantiles, with values of 1 to 5, each containing about 20% of the total counts. The quantiles were summed and then classified into quantiles. If the metric is conversely proportional to the outcome–for example, higher NDVI values are inversely related to the impacts of an extreme heat event–then the quantile values were reversed. The grid cells with the highest quantile values (e.g., quantiles 5 and 4) are likely a good place for targeting green infrastructure efforts and thus warrant closer inspection. These areas are ostensibly places where green infrastructure would provide the most environmental mitigation and/or offer the highest benefit to the population. *Green Law. (2012) The Patterns of Pollution: A Report on the Demographics of Pollution in Metro Atlanta.</p>
Proctor CreekHeat Related IllnessExtreme Heat EventsAtlantaGeorgiaGreen Infrastructure
This analysis, done in support of the Proctor Creek Health Impact project, produced a grid showing where green infrastructure would likely have the highest benefit. The grid analysis, based on a publican by GreenLaw* was carried out as follows. First, spatial data was gathered and/or generated for metrics, that may correlate with or compound health or environmental outcomes associated with flooding or extreme heat events. Secondly, a grid of evenly sized squares was created and overlain on the study area and the presence of each metric was measured within each cell (percent area or mean value). Finally, to normalize the data values, the summed values were classified into five equal quantiles, with values of 1 to 5, each containing about 20% of the total counts. The quantiles were summed and then classified into quantiles. If the metric is conversely proportional to the outcome–for example, higher NDVI values are inversely related to the impacts of an extreme heat event–then the quantile values were reversed. The grid cells with the highest quantile values (e.g., quantiles 5 and 4) are likely a good place for targeting green infrastructure efforts and thus warrant closer inspection. These areas are ostensibly places where green infrastructure would provide the most environmental mitigation and/or offer the highest benefit to the population. *Green Law. (2012) The Patterns of Pollution: A Report on the Demographics of Pollution in Metro Atlanta
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