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
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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.
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.
Esri
Positive real numbers that are automatically generated.
20230419
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