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The Trust for Public Land’s Climate-Smart Cities Program is founded on the principle that to respond to climate change, cities must restore natural functions of the land by weaving green elements into the built environment. The Climate Smart Cities Program helps cities meet the challenges through the development of spatial data and decision support tools that translate the goals from a city’s strategic climate planning into priority sites for green infrastructure development. The Climate Smart Cities Program categorizes these strategies under the climate objectives of Connect, Cool, Absorb, and Protect. The rasters in the climate equity geodatabase help explore demographic and socioeconomic data of populations that are particularly vulnerable to the impacts of climate change. (Highest priority areas are in red). This model identifies socially vulnerable populations based on the percent of people age 25 and older in a block group that do not have a high school diploma. Block groups with populations without a high school degree were broken into 0 to 5 priority classes using a natural breaks slice classification. The break points for the moderate to high priority classes were as follows:Moderate (3) = 18% to 25%Moderate to High (4) = 25.1% to 40%High (5) = 40.1% to 89%Block groups with less than 100 people and parks and natural areas were removed.The model is based on data collected for the EPA Environmental Justice Screening Tool. "EPA should pay particular attention to the vulnerabilities of these populations because they have historically been exposed to a combination of physical, chemical, biological, social, and cultural factors that have imposed greater environmental burdens on them than those imposed on the general population. (http://www.epa.gov/sites/production/files/2015-05/documents/ejscreen_technical_document_20150505.pdf)"Data interpretation:5 = Very High Priority for Green Infrastructure4 = High Priority for Green Infrastructure 3 = Medium Priority for Green Infrastructure 0-2 = Low ValueValues 3, 4, and 5 should be used when assessing highest prioritization from the model. |