20230421 10060600 1.0 FGDC CSDGM Metadata FALSE Heat_CCVI_Projected 002 Projected GCS_North_American_1983 Linear Unit: Foot_US (0.304801) NAD_1983_StatePlane_Connecticut_FIPS_0600_Feet <ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.0.0'><WKT>PROJCS[&quot;NAD_1983_StatePlane_Connecticut_FIPS_0600_Feet&quot;,GEOGCS[&quot;GCS_North_American_1983&quot;,DATUM[&quot;D_North_American_1983&quot;,SPHEROID[&quot;GRS_1980&quot;,6378137.0,298.257222101]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic&quot;],PARAMETER[&quot;False_Easting&quot;,999999.999996],PARAMETER[&quot;False_Northing&quot;,499999.999998],PARAMETER[&quot;Central_Meridian&quot;,-72.75],PARAMETER[&quot;Standard_Parallel_1&quot;,41.2],PARAMETER[&quot;Standard_Parallel_2&quot;,41.86666666666667],PARAMETER[&quot;Latitude_Of_Origin&quot;,40.83333333333334],UNIT[&quot;Foot_US&quot;,0.3048006096012192],AUTHORITY[&quot;EPSG&quot;,2234]]</WKT><XOrigin>-119756300</XOrigin><YOrigin>-96342500</YOrigin><XYScale>3048.0060960121928</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.0032808333333333331</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>102656</WKID><LatestWKID>2234</LatestWKID></ProjectedCoordinateSystem> 20230419 14235400 20230419 14235400 150000000 5000 FGDC Esri ArcGIS 13.0.3.36057 Heat_CCVI_Projected Final Heat Vulnerability grid for CCVI 2.0 created by SLR Consulting for the Connecticut Institute for Resilience & Climate Adaptation (CIRCA). This layer represents the Final Heat Vulnerability covering the State of Connecticut. Each grid cell covers a 10x10 acre area, and represents the aggregation of many contributing layers or factors. Dataset was completed in January 2023. Updates in November 2024. Data created by SLR Consulting, with guidance and support from CIRCA. The following employees were key contributors to the projects success. SLR Consulting: Meghan McGaffin, Conner Dickes, Noah Slovin, Jon Philipsborn CIRCA: David Murphy, Yaprak Onat, Mary Buchanan, Jon Truscinski, Nicole Govert CIRCA CCVI CT Vulnerability SLR Heat Climate Climate Change Sensitivity Adaptive Capacity Exposure File Geodatabase Feature Class dataset EPSG 5.3(9.0.0) 0 Simple FALSE 0 TRUE FALSE Heat_CCVI_Projected Feature Class 0 OBJECTID OBJECTID OID 4 0 0 Internal feature number. Esri Sequential unique whole numbers that are automatically generated. GRID_ID GRID_ID Integer 4 0 0 Unique identifier number assigned to each grid cell. GridSquareFeet GridSquareFeet Double 8 0 0 SLR_Water_Coverage_1 % of Cell in National Hydrography Layer Double 8 0 0 SLR_Water_Coverage_70p 70% of Cell is in National Hydrography Layer SmallInteger 2 0 0 SLR_Water_Coverage_85p 85% of Cell is in National Hydrography Layer SmallInteger 2 0 0 Tract Tract Double 8 0 0 RANK_Prox_Bus_Hub RANK Proximity to Bus Hub Integer 4 0 0 Used a CTDOT street centerline and Esri's Network Analyst extension to create a driveshed network covering the state of CT. Used point class containing bus hubs, bus stations, and transit stations to create polygons of 0-0.5, 0.5-3, 3-5, >5-mile service areas. Service area polygons were then spatially joined with the source grid. Ranks were determined by the driveshed distance contained within the cell. US DOT Bureau of Transportation Statistics, CT DOT RANK_COOLING_CENTERS RANK Proximity to Cooling Centers Integer 4 0 0 Used a CTDOT street centerline and Esri's Network Analyst extension to create a driveshed network covering the state of CT. Used point class of cooling centers to create polygons representing 0-0.5, 0.5-3, 3-5, >5 mile service areas. Service area polygons were used in a spatial join with the source grid to determine ranking of cell. CIRCA provided MMI_Town Town String 100 0 0 AC_SOCIAL_IG_GEOMEAN GEOMEAN - Adaptive Capacity - Social Double 8 0 0 PCT_NO_HEALTH_INSURANCE % No Health Insurance (Population) Double 8 0 0 RANK_NO_HEALTH_INSURANCE RANK Percent No Health Insurance Integer 4 0 0 Census data was ranked at the tract level by the Natural Breaks (Jenks) method. Census data was then spatially joined to the grid cells. B27010 Census ACS 2015-2019 5-year Estimates RANK_Owner_Occ_Housing RANK % Owner Occupied Housing Units (Population) Integer 4 0 0 Census data was ranked at the tract level by the Natural Breaks (Jenks) method. Census data was then spatially joined to the grid cells. DP04: Census ACS 2015-2019 5-year Estimates RANK_SHELTERS RANK Proximity to Shelter Integer 4 0 0 Used a CTDOT street centerline and Esri's Network Analyst extension to create a driveshed network covering the state of CT. Used point class of shelters to create polygons representing 0-0.5, 0.5-3, 3-5, >5 mile service areas. Service area polygons were used in a spatial join with the source grid to determine ranking of cell. COG provided data supplemented with Homeland Security data, Town websites RANK_Swimming_ACCESS Swimming Area Access subRANK Integer 4 0 0 RANK_Swimming_DISTANCE Swimming Area Distance subRANK Integer 4 0 0 RANK_SWIMMING_AREA_WEIGHT RANK Proximity to Swimming Areas Integer 4 0 0 Used a CTDOT street centerline and Esri's Network Analyst extension to create a driveshed network covering the state of CT. Used point class of swimming areas to create polygons representing 0-0.5, 0.5-3, 3-5, >5-mile service areas. Service area polygons were used in a spatial join with the source grid to determine ranking of cell. DEEP, DPH, CIRCA RANK_Prox_Healthcare_Fac RANK Proximity to Healthcare Facility Integer 4 0 0 Used a CTDOT street centerline and Esri's Network Analyst extension to create a driveshed network covering the state of CT. Used point class of healthcare facilities to create polygons representing 0-0.5, 0.5-3, 3-5, >5-mile service areas. Service area polygons were used in a spatial join with the source grid to determine ranking of cell based on driveshed distance and public accessibility to the swimming location. HSIP Hospitals & Urgent Care Faculties AC_Ecological_IG_GEOMEAN GEOMEAN - Adaptive Capacity - Ecological Double 8 0 0 NDVI_Input NDVI Input Value Double 8 0 0 RANK_NDVI RANK NDVI Integer 4 0 0 CIRCA developed an NDVI raster which was spatially joined to the source grid. ESRI's Zonal Statistics tool was used to calculate mean NDVI value for each grid cell. The NDVI values were ranked using the Natural Breaks (Jenks) classification method. CIRCA provided PCT_Tree_Cover % Tree Cover Integer 4 0 0 RANK_TREE_COVER_PCT RANK Percent Tree Cover Integer 4 0 0 USFS raster layer depicting percent tree canopy coverage was spatially joined to the source grid. The median value of the tree coverage within the grid cell was used to determine the rank score through the Natural Breaks (Jenks) classification method. USFS 2016 Percent Tree Canopy AC_Comp_Score COMPONENT SCORE - Adaptive Capacity Double 8 0 0 SLR_PCT_OUTSIDE_EMPLOYMENT % Total Outside Employment Double 8 0 0 PCT_WELL_COVERAGE % Private Well Coverage Double 8 0 0 RANK_Privatre_Well_Coverage RANK Private Well Coverage Integer 4 0 0 Parcels from the DPH Private Well mapping project were joined with the source grid. The percentage of the grid cell that is covered by a parcel with a private well was used to assign a rank score. CT DWVARP PCT_PUB_HSING % Public Housing Units by Tract Integer 4 0 0 RANK_Pub_Housing RANK Public Housing Units by Tract Integer 4 0 0 Census data was ranked at the tract level by the Natural Breaks (Jenks) method. Census data was then spatially joined to the grid cells. US Dept of Housing and Urban Development & B25001 Census ACS 2015-2019 5-year Estimates Median_AGE Median Building Age by Tract Integer 4 0 0 RANK_Med_Bldg_Age RANK Median Building Age by Tract Integer 4 0 0 Census data was ranked at the tract level by the Natural Breaks (Jenks) method. Then the census tracts were spatially joined to the building footprints layer to transfer the median age and rank score to the building footprints. Those footprints were then spatially joined to the source grid to eliminate false drivers in areas where there are no buildings within a census tract. B25035_001E: Census ACS 2015-2019 5-year Estimates GEOMEAN_sensitivity_Built GEOMEAN - Sensitivity - Built Double 8 0 0 RANK_Asthma RANK Asthma Integer 4 0 0 Confidential public health data was provided at the census tract level. CIRCA ranked the layer which was spatially joined to the source grid. CT DPH, CIRCA provided MEDIAN_INCOME Median Income (Households) Integer 4 0 0 RANK_Median_Income RANK Median Income Integer 4 0 0 Census data was ranked at the tract level by the Natural Breaks (Jenks) method. Census data was then spatially joined to the grid cells. S1901_C01_012E: Census ACS 2015-2019 5-year Estimates PCT_BELOW_185POVERTY % Living Below 185% Federal Poverty Level Double 8 0 0 RANK_Pct_Below_poverty_level RANK Percent Living Below 185% Federal Poverty Level Integer 4 0 0 Census data was ranked at the tract level by the Natural Breaks (Jenks) method. Census data was then spatially joined to the grid cells. S1701_C01_041E: Census ACS 2015-2019 5-year Estimates SPEAKS_ENGLISH_LESS_THAN % Speaks English Less than Very Well (Population) Double 8 0 0 RANK_Eng_less_very_well RANK Percent Speaks English Less than Very Well Integer 4 0 0 Census data was ranked at the tract level by the Natural Breaks (Jenks) method. Census data was then spatially joined to the grid cells. S0601_S0601_C01_026E: Census ACS 2015-2019 5-year Estimates PCT_NO_VEHICLE % No Vehicle Double 8 0 0 RANK_Pct_No_Vehicle RANK Percent No Vehicle Integer 4 0 0 Census data was ranked at the tract level by the Natural Breaks (Jenks) method. Census data was then spatially joined to the grid cells. DP04: Census ACS 2015-2019 5-year Estimates PCT_NON_WHITE % Non White (Population) Double 8 0 0 RANK_Non_White RANK Non White Integer 4 0 0 The percent of white-only population was totaled for each census tract. That value was subtracted from 100 to generate the percentage of minorities per tract. Census data was ranked at the tract level by the Natural Breaks (Jenks) method. Census data was then spatially joined to the grid cells. S0601_C01_022E: Census ACS 2015-2019 5-year Estimates ImpervPct % Impervious Surface Coverage Double 8 0 0 RANK_Pct_Outside_Employment RANK Percent Total Outside Employment Integer 4 0 0 Employment point data by number of jobs per census tract was downloaded from On the Map and joined to the census tracts. The sum of jobs in Agriculture, Forestry, Fishing, Hunting, Mining, Quarrying, Oil & Gas Extraction, and Construction were taken as a percentage of total jobs. The percentage of outside employment was ranked at the tract level by the Natural Breaks (Jenks) method. Census data was then spatially joined to the grid cells. US Census OnTheMap PCT_OVER_5_DISABILITY % Over 5 with a Disability (Population) Double 8 0 0 RANK_Over_5_Disability RANK Over 5 with a Disability Integer 4 0 0 Census data was ranked at the tract level by the Natural Breaks (Jenks) method. Census data was then spatially joined to the grid cells. B18101: Census ACS 2015-2019 5-year Estimates OVER_25_NO_HS_DIPLOMA % Over 25 without a High School Diploma (Population) Double 8 0 0 RANK_Pct_Over25_No_HS_Diploma RANK Percent Over 25 without a High School Diploma Integer 4 0 0 Census data was ranked at the tract level by the Natural Breaks (Jenks) method. Census data was then spatially joined to the grid cells. S0601_C01_033E: Census ACS 2015-2019 5-year Estimates PCT_OVER_65 % Over 65 (Population) Double 8 0 0 RANK_Pct_Over65 RANK Percent Over 65 Integer 4 0 0 Census data was ranked at the tract level by the Natural Breaks (Jenks) method. Census data was then spatially joined to the grid cells. S0101_C02_030E: Census ACS 2015-2019 5-year Estimates PCT_OVER_65_LIVE_ALONE % Over 65 Living Alone (Households) Integer 4 0 0 RANK_Over65_Living_alone RANK Percent Over 65 Living Alone Integer 4 0 0 Census data was ranked at the tract level by the Natural Breaks (Jenks) method. Census data was then spatially joined to the grid cells. B25011 Census ACS 2015-2019 5-year Estimates PCT_SINGLE_PARENT_HH % Single Parent Households (Households) Double 8 0 0 RANK_Pct_Single_Parent_Household RANK Percent Single Parent Household Integer 4 0 0 Census data was ranked at the tract level by the Natural Breaks (Jenks) method. Census data was then spatially joined to the grid cells. DP02 Census ACS 2015-2019 5-year Estimates PCT_UNDER_5 % Under 5 (Population) Double 8 0 0 RANK_Pct_Under5 RANK Percent Under 5 Integer 4 0 0 Census data was ranked at the tract level by the Natural Breaks (Jenks) method. Census data was then spatially joined to the grid cells. S0101_C02_002E: Census ACS 2015-2019 5-year Estimates PCT_UNEMPLOYED % Unemployed Double 8 0 0 RANK_Pct_Unemployed RANK Percent Unemployed Integer 4 0 0 Census data was ranked at the tract level by the Natural Breaks (Jenks) method. Census data was then spatially joined to the grid cells. DP03_0005PE: Census ACS 2015-2019 5-year Estimates POP_DENSITY Population Density (Population per Square Mile) Integer 4 0 0 RANK_Pop_Density RANK Population Density Integer 4 0 0 Census data was ranked at the tract level by the Natural Breaks (Jenks) method. Census data was then spatially joined to the grid cells. S0101: Census ACS 2015-2019 5-year Estimates RANK_Heat_Stress RANK Heat Stress Integer 4 0 0 Confidential public health data was provided at the census tract level. CIRCA ranked the layer which was spatially joined to the source grid. CT DPH, CIRCA provided GEOMEAN_Sensitivity_Social GEOMEAN - Sensitivity - Social Double 8 0 0 Max_LST Max Land Surface Temp (Kelvin) Double 8 0 0 RANK_Max_LST RANK Max Land Surface Temp (Kelvin) Integer 4 0 0 CIRCA developed a Land Surface Temperature (LST) raster. The LST raster was spatially joined to the source grid. ESRI's Zonal Statistics tool was used to calculate mean LST value for each grid cell. The mean LST values were ranked using the Natural Breaks (Jenks) classification method. CIRCA provided Roadway_Usage_Class_Score Roadway Usage Classification Score (Simulating Traffic Emissions) Integer 4 0 0 RANK_ROADWAY_CLASS_JENKS RANK Roadway Usage Classification Integer 4 0 0 1. CT DOT road network shapefile was split by road class, with each class assigned an ID between 1-7 2. A 10x10 foot-resolution Distance Raster was created for each road class 3. Raster Calculator consolidated all the Distance Rasters by the following equation: RoundUp(5.35 * (((1/(1+""%Class1Distance%"")) + (1/(2+""%Class2Distance%"")) + (1/(3+""%Class3Distance%"")) + (1/(4+""%Class4Distance%"")) + (1/(5+""%Class5Distance%"")) + (1/(6+""%Class6Distance%"")) + (1/(7+""%Class7Distance%""))))) Each raster cell value reflects combined proximity (ranked 1 to 10) to all road classes; higher-class roads have larger impact. 4. ESRI's Zonal Statistics tool was used to assign each grid cell a value based on MAX value of Consolidated Distance raster. 5. The MAX value were ranked using the Natural Breaks (Jenks) classification method. CT DOT BuildingPCT Percent Building Density Coverage Double 8 0 0 RANK_Impervious_Surface RANK Impervious Surface Coverage Integer 4 0 0 Building and Pavement features were merged into a single Impervious Surface polygon layer. Source grid was intersected with Impervious Surface layer. Next, percentage of impervious surface within each grid cell was calculated. Cells were then ranked by their coverage. CT ECO 2012 Impervious Surface Shape Shape Geometry 0 0 0 Feature geometry. Esri Coordinates defining the features. RANK_Building_Density RANK Building Density Coverage Integer 4 0 0 Building features were intersected with the source grid. Next, the percent of building area coverage was calculated for each grid cell. Rank scores were determined by the percent coverage. CT ECO 2012 Impervious Surface Emissivity Emissivity Input Value Double 8 0 0 RANK_EMISSIVITY RANK Emissivity Integer 4 0 0 CIRCA developed an Emissivity raster. The Emissivity raster was spatially joined to the source grid. ESRI's Zonal Statistics tool was used to calculate mean Emissivity value for each grid cell. The mean values were ranked using the Natural Breaks (Jenks) classification method. CIRCA provided GEOMEAN_Exposure_Physical GEOMEAN - Exposure - Physical Double 8 0 0 COMPONENT_Score_Exposure COMPONENT SCORE - Exposure Double 8 0 0 COMPONENT_Score_Sensitivity COMPONENT SCORE - Sensitivity Double 8 0 0 Vulnerability_Score_RAW HEAT VULNERABILITY SCORE RAW Double 8 0 0 Vulnerability_Score_Norm HEAT VULNERABILITY SCORE NORMALIZED Double 8 0 0 Shape_Length Shape_Length Double 8 0 0 Length of feature in internal units. Esri Positive real numbers that are automatically generated. Shape_Area Shape_Area Double 8 0 0 Area of feature in internal units squared. 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