Description: 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 absorb geodatabase help identify features of the landscape are that particularly vulnerable to/at risk of flooding as a result of major storms. (Highest priority areas are in red).Storm drains are designed to accommodate frequent storms. This model identifies high exceedance flood areas, areas prone to flooding of up to 2 feet during the 2, 5, and 10 year storms, within the New Orleans City limits where green infrastructure could mitigate stormwater flooding impacts.Priority was assigned as follows:Very High (5) = 2-year storm flood inundation zoneHigh (4) = 5-year storm flood inundation zoneModerate(3) = 10-year storm flood inundation zoneData 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.
Description: 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 connect geodatabasehelp explore priority areas of the city for connecting and expanding walk-bike corridors. (Highest priority areas are in red). CT07 idenitifies areas in the city that are more than 10-minute walk from public transportation as well as those areas with significant number of people that lack access to frequent public transit.Access to reliable and affordable public transportation is essential to enhancing quality of life as well as reducing green house emissions for a city's population. This model prioritizes areas where city residents are more than a 10 minute walk from available public transportation as well as areas where there is a need for additional public transportation. Areas more than a 10 minute walk from public transportation stop were assigned a very high priority value (5). Areas within a 10 minute walk of public transit where the max wait time is more than 60 minutues and that have a significant number of people was assigned high priority value of (4). Areas within a 10 minute walk of public transit where the max wait time is more than 30 minutues and that have a significant number of people was assigned moderate priority value of (3).Service Areas were derived using network analyst. Areas of significant population were determined using ESRI's 2014 Estimated Demographics and u=includes Population per square mile. Significant population was condisered population >= 6153. Frequency of transit was derived using the Better Bus Buffer tools developed by ESRI (https://github.com/Esri/public-transit-tools/tree/master/better-bus-buffers).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.
Description: 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.