20230605
11171700
1.0
FGDC CSDGM Metadata
FALSE
Flood_CCVI
002
730011.615806
1263810.649583
552737.759990
944969.200591
1
Projected
GCS_North_American_1983
Linear Unit: Foot_US (0.304801)
NAD_1983_StatePlane_Connecticut_FIPS_0600_Feet
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20230131
12063500
20230131
17373000
150000000
5000
FGDC
Esri ArcGIS 12.9.4.32739
Flood_CCVI
1
-73.744044
-71.778699
42.054506
40.973882
This Flood Vulnerability Index for CCVI 2.0 was created by SLR Consulting for the Connecticut Institute for Resilience & Climate Adaptation (CIRCA) at the University of Connecticut. This layer represents the Flood Vulnerability Index covering the State of Connecticut. Each grid cell covers a 10 x10 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
Flood
Climate
Climate Change
Sensitivity
Adaptive Capacity
Exposure
File Geodatabase Feature Class
dataset
EPSG
5.3(9.0.0)
0
Simple
FALSE
0
TRUE
FALSE
Flood_CCVI
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
A unique identification number assigned to each grid cell.
CIRCA
GridSquareFeet
GridSquareFeet
Double
8
0
0
OID_
OID_
Integer
4
0
0
Water_Coverage
% of Cell in National Hydrography Layer
Double
8
0
0
Water_Coverage_70p
70% of Cell is in National Hydrography Layer
SmallInteger
2
0
0
Water_Coverage_85p
85% of Cell is in National Hydrography Layer
SmallInteger
2
0
0
PWS_NAME
Public Water Service Area
String
100
0
0
Owner_Name
Owner - Water Company Land
String
100
0
0
WATER_COMPANY_LAND_RANK
RANK Water Company Land
Integer
4
0
0
Public Water Service Area polygons were joined to the source grid. Ranking was determined by whether or not the grid cell intersected on the Public Water Service Area dataset.
CT Dept of Public Health
PCT_OS_SFHA_area
% Open Space in SFHA
Double
8
0
0
Sustainable_Score_for_CCVI
CIRCA Sustainability Score
Integer
4
0
0
RANK_PCT_OS_SFHA_area
RANK Open Space in SFHA
Integer
4
0
0
Open space data was clipped to the SFHA area. Clipped open space within the SFHA was then intersected with the source grid. Next, the area percentage within each grid cell was calculated. Cells were then ranked by their coverage.
The Nature Conservancy & CT DEEP (2022)
SewerService
Sewer Service Areas
String
100
0
0
Rank_SewerService
RANK Sewer Service Areas
Integer
4
0
0
Sewer Service Area polygons were spatially joined to the source grid. Grid cells were scored by the presence within a sewer service area.
CT DEEP
StormReady_Score_for_CCVI
CIRCA Storm Ready Score
Integer
4
0
0
CRS_Class
CRS Class
Integer
4
0
0
CRS_Score_for_CCVI
CIRCA CRS Score
Integer
4
0
0
Standards_Count
CIRCA Count of Regulatory Standards
Integer
4
0
0
AC_Social_GEOMEAN
GEOMEAN - Adaptive Capacity - Social
Double
8
0
0
RANK_Regulatory_Standards
RANK Regulatory Standards
Integer
4
0
0
CIRCA provided a town boundary file where each community was ranked by their participation as a StormReady Community, enrollment in FEMA's Community Rating Service program, or qualified for Low Impact Development points under the Sustainable CT Community program. Data was spatially joined to the source grid. Rank score was determined by the value at the center of the grid cell.
CIRCA
Public_Water_Service_Area
Public Water Service Area
String
100
0
0
RANK_Public_Water_Service_Area
RANK Public Water Service Area
Integer
4
0
0
Public Water Service Area polygons were joined to the source grid. Ranking was determined by whether or not the grid cell intersected on the Public Water Service Area dataset.
CT Water Plan, Dept. of Public Health
RANK_Proximity_to_Health_Care_Facility
RANK Proximity to Health Care 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.
CTDOT, Hospitals & Urgent Care Facilities (DEMHS)
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.
CT DOT, COGs
RANK_Major_Roadways
RANK Proximity to Major Roadways
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.
CTDOT Exits, DEMHS
Description_Resilient_Landscapes
Resilient Landscapes
String
100
0
0
RANK_Resilient_Landscapes
RANK Resilient Landscapes
Integer
4
0
0
Resilient Landscape data was spatially joined to the source grid. Rank scores were based on whether the cell intersected an area classified as Resilient Only or Vulnerable.
The Nature Conservancy
F2022_Average_Disposable_Income
2022 Average Disposable Income (Esri)
Integer
4
0
0
RANK_DISPOSABLE_INCOME
RANK 2022 Average Disposable Income (Esri)
Integer
4
0
0
Using ESRI's Business Analyst for the Web extensions, census tracts containing average household disposable income were ranked using the Natural Breaks (Jenks) classification method. Census data was then spatially joined to the grid cells. For grid cells with multiple census tracts intersecting, an average of the two values were taken.
ESRI, U.S. Census Bureau
PCT_NO_VEHICLE
% Housing Units with No Vehicle Present
Double
8
0
0
RANK_No_Vehicle
RANK % Housing Units with No Vehicle Present
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_OWN_OCC
% Population in Owner-Occupied Housing Units
Double
8
0
0
RANK_PCT_OWN_OCC
RANK % Population in Owner-Occupied Housing Units
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
AC_Component_Score
COMPONENT SCORE - Adaptive Capacity
Double
8
0
0
AC_Community_Assets_GEOMEAN
GEOMEAN - Adaptive Capacity - Community Assets
Double
8
0
0
GridSquareFeet_1
Square Feet In Grid
Double
8
0
0
SLOSH_Zone
Storm Surge
Integer
4
0
0
SLOSH zones (1-4) from NOAA
FZ_MERGE_SRC
Source of Flood Zone Data
String
100
0
0
For this project multiple vintages of flood zone data were used.
RANK_Unmodified_FZ
RANK Unmodified Flood Zone (Contributor)
Integer
4
0
0
RANK_Downstream_FCD
RANK Downstream of Flood Control Dam (Contributor)
Integer
4
0
0
RANK_MODIFIED_FZ_MEDIAN
RANK Median CIRCA-Modified Flood Zone (Q3, DFIRM, Preliminary)
Double
8
0
0
Flood zone data was compiled from three sources - current FEMA flood zones, preliminary flood zones for Windham & New London Counties, and legacy Q3 data for Litchfield county were merged together to create an approximate statewide data set. Flood zones were ranked by type, and presence of floodway. Selected inland riverine flood zones that are protected by a dam had their scores modified. This merged and ranked flood zone layer was spatially joined to the source grid.
FEMA, CIRCA
GEOMEAN_EXP_CLIM
GEOMEAN - Exposure - Climate
Double
8
0
0
RANK_SLOSH
RANK Storm Surge
Integer
4
0
0
Four SLOSH files representing potential hurricane inundation for storms rated Category 1 through 4 were brought into the map. In the following order, using the "Select by Location" tool, cells from the source grid that intersected:
Category 4 inundation were assigned a rank of 2
Category 3 inundation were assigned a rank of 3
Category 2 inundation were assigned a rank of 4
Category 1 inundation were assigned a rank of 5
NOAA
RANK_SeaLevelRise
RANK CIRCA Sea Level Rise
Integer
4
0
0
CIRCA developed a ranked Sea Level Rise raster which was spatially joined to the source grid.
CIRCA
SOIL_DRAINAGE_MAJ_RANK
RANK Soil Drainage
Integer
4
0
0
Rankings (1-5) were assigned based on the soil drainage class. Soil drainage polygon layer was converted to a raster. ESRI's Zonal Statistics tool was used to determine the value that represented the majority rank of the raster cell, and then the raster was spatially joined to the source grid.
SSURGO Soil Drainage Class
SOILD_DRAINAGE_CODE_PCT90
Soil Drainage Code (Majority of Cell)
Integer
4
0
0
SoilDrainageDescription
Soil Drainage Description
String
100
0
0
ImpervPct
% Impervious Surface
Double
8
0
0
Erosion_Susceptibility_grid_Code
Erosion Susceptibility
Integer
4
0
0
RANK_Erosion_Susceptibility
RANK Erosion Susceptibility
Integer
4
0
0
Soils polygons were ranked by erodibility and then joined to the source grid. This dataset was developed in CIRCA's Coastal Vulnerability Index project.
DEEP, CVI, CIRCA
SHORELINE_CHANGE_RATE_RANK
RANK Shoreline Change Rate
Double
8
0
0
CIRCA provided shoreline change rate data from their Coastal Vulnerability Index project.
CIRCA
RANK_impervious
RANK Impervious Surface
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)
ers_sum_max
Max Erosion Rate
Double
8
0
0
PoolPctCover
% Coverage Elevation Pooling
Double
8
0
0
GEOMEAN_Physical
GEOMEAN - Exposure - Physical
Double
8
0
0
RANK_Elevation_Pooling
RANK Elevation Pooling
Integer
4
0
0
Ran "Fill" tool on DEM (CT 2016 Lidar). Used Raster Math to subtract the filled DEM from the original DEM and created a Difference Raster. ESRI's Zonal Statistics tool was used to calculate the SUM of the Difference Raster. Difference Raster was spatially joined to the source grid.
CT 2016 Lidar
COMPONENT_Exposure
COMPONENT SCORE - Exposure
Double
8
0
0
Census_Tract_Full_GEOID
Census Tract GEOID
String
100
0
0
Town
Town Name
String
50
0
0
S0101_C02_002E_PCT_UNDER_5
% Under 5 (Population)
Double
8
0
0
MEDIAN_INCOME
Median Income (Households)
Integer
4
0
0
RANK_Median_Income
RANK Household Median Income
Integer
4
0
0
Census data was ranked at the tract level by the Natural Breaks (Jenks) method. Census tracts were then spatially joined to the source grid.
S1901_C01_012E: Census ACS 2015-2019 5-year Estimates
SPEAKS_ENGLISH_LESS_THAN_VE
Speaks English Less than Very Well (Population)
Double
8
0
0
RANK_SPEAKS_ENGLISH_LESS_THAN_VE
RANK 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 tracts were then spatially joined to the source grid.
S0601_C01_026E: Census ACS 2015-2019 5-year Estimates
PCT_NON_WHITE
% Non White (Population)
Double
8
0
0
RANK_NON_WHITE
RANK Non-White Population
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
PCT_OVER_5_DISABILITY
% Over 5 with a Disability (Population)
Double
8
0
0
RANK_PCT_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 tracts were then spatially joined to the source grid.
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_OVER_25_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 tracts were then spatially joined to the source grid.
S0601_C01_033E: Census ACS 2015-2019 5-year Estimates
PCT_OVER_65
% Over 65 (Population)
Double
8
0
0
RANK_PCT_OVER_65
RANK Percent Over 65
Integer
4
0
0
Census data was ranked at the tract level by the Natural Breaks (Jenks) method. Census tracts were then spatially joined to the source grid.
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_PCT_OVER_65_LIVE_ALONE
RANK Percent Over 65 Live Alone (Households)
Integer
4
0
0
Census data was ranked at the tract level by the Natural Breaks (Jenks) method. Census tracts were then spatially joined to the source grid.
B25011 Census ACS 2015-2019 5-year Estimates
PCT_SINGLE_PARENT_HH
% Single Parent Households (Households)
Double
8
0
0
RANK_PCT_SINGLE_PARENT_HH
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
Sensitivity_Social_GEOMEAN
GEOMEAN - Sensitivity - Social
Double
8
0
0
RANK_PCT_UNDER_5
RANK Percent Population Under 5
Integer
4
0
0
Census data was ranked at the tract level by the Natural Breaks (Jenks) method. Census tracts were then spatially joined to the source grid.
S0101_C02_002E: Census ACS 2015-2019 5-year Estimates
PCT_UNEMPLOYED
% Unemployed
Double
8
0
0
RANK_PCT_UNEMPLOYED
RANK Percent Population Unemployed
Integer
4
0
0
Census data was ranked at the tract level by the Natural Breaks (Jenks) method. Census tracts were then spatially joined to the source grid.
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 tracts were then spatially joined to the source grid.
S0101: Census ACS 2015-2019 5-year Estimates
PCT_BELOW_185POVERTY
% Living Below 185% Federal Poverty Level
Double
8
0
0
RANK_PCT_BELOW_185POVERTY
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 tracts were then spatially joined to the source grid.
S1701_C01_041E: Census ACS 2015-2019 5-year Estimates
BuildingPCT
% Building Coverage
Double
8
0
0
RANK_BROWNFIELDS
RANK Brownfields
Integer
4
0
0
Points of brownfields sites were used to select any building footprints that contained a brownfield point. Those buildings were then used to assess if the brownfield intersected any drinking watersheds or SFHA, and ranked accordingly. Buildings were then spatially joined to the source grid.
CT DEEP
FloodZone
Flood Zone (Input to Critical Facilities)
String
100
0
0
RANK_Critical_Facilites
RANK Critical Facilities
Integer
4
0
0
Critical facility points were ranked based on their proximity to flood zones. The points were then spatially joined to the source grid.
Natural Hazard Mitigation Plans, COGs, DEMHS
RANK_RAILROAD_STATIONS
RANK Railroad Stations
Integer
4
0
0
The building footprints of railroad stations were identified. The railroad stations were ranked based on their proximity to flood zones. The building footprints were then spatially joined to the source grid.
CT Open Data - joined to building footprints
RASTERVALU_ROADWAY
Roadway Sum (Roadway Classification)
Integer
4
0
0
Label_Flood_Zone
Flood Zone (Not Buffered)
String
100
0
0
RANK_Railways_in_SFHA
RANK Railways in SFHA
Integer
4
0
0
Railways were intersected with a custom flood zone layer comprised of current & preliminary flood zones, and historical Q3 data. The flood zone layer was used to split the railway lines. Rank score was based on the type of flood zone that the rail line passes through. Ranked railways were then spatially joined with the source grid.
CT DEEP, FEMA, CIRCA
RANK_Septic_Areas
RANK Septic Areas
Integer
4
0
0
The Sewer Service Area polygon was erased from a polygon of the CT boundary to create a Septic Area layer and given a rank of 5 as "assumed septic". Septic Area was spatially joined to the source grid.
CT DEEP, CT DPH, SLR
PCT_PW_SHFA
% Private Wells in Relation to SFHA
Double
8
0
0
RANK_PCT_PW_SHFA
RANK Private Wells in Relation to SFHA
Integer
4
0
0
Parcels from the DPH Private Well mapping project were intersected with the SFHA. The percentage of the parcel area within the SFHA was then calculated and used to assign a rank score. The layer was then spatially joined to the source grid and ranked based on value at the center of the grid cell.
CT DWVARP
RANK_BD
RANK Building Density
Integer
4
0
0
Building features were intersected with the source grid. Next, the percentage of building area coverage was calculated for each grid cell. Rank scores were determined by the percent coverage.
CT ECO 2012 Impervious Surface
GEOMEAN_SEN_CA
GEOMEAN - Sensitivity - Community Assets
Double
8
0
0
SHPO_Count
# of SHPO Designated Resources per cell
Integer
4
0
0
RANK_SHPO
RANK SHPO Designated Historic Resources
Integer
4
0
0
Count of historic resource points within each grid cell was calculated by using a spatial join with the source grid. Rank scores were determined by number of points intersecting the cell.
SHPO, Dewberry
RANK_PWSW
RANK Public Water Supply Watersheds
Integer
4
0
0
Public Water Supply Watersheds were ranked based on the presence of land owned by a water utility within the watershed. Grid cells that had ranks of 3 and 5 were averaged which created the rank class of 4.
DPH watersheds (WUCC/DPH) and the CT DEEP water layer
Critical_Habitat_Type
Critical Habitat Type
String
100
0
0
RANK_Critical_Habitat
RANK Critical Habitat
Integer
4
0
0
Critical habitat polygons were spatially joined to the source grid. Grid cells are ranked based on the presence of a critical habitat area within the cell.
CT DEEP
RANK_Bus_Hubs
RANK Proximity to Bus Hubs
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.
Bureau of Transportation Statistics, SLR
RANK_ROADWAY
RANK Roadway Classification
Integer
4
0
0
CTDOT road polylines were ranked by generalized functional class. Ranked polylines were then converted into a raster (200 x 200ft). Zonal Statistics were used to calculate the SUM of all the road rasters in each grid cell. Polyline raster was spatially joined to the source grid.
CT DOT
Flood_Vulnerability_Score_Raw
FLOOD VULNERABILITY SCORE RAW
Double
8
0
0
Flood_Vuln_Score_Normalized
FLOOD VULNERABILITY SCORE NORMALIZED
Double
8
0
0
Sensitivity_Component_Score
COMPONENT SCORE - Sensitivity
Double
8
0
0
ShapeArea
ShapeArea
Double
8
0
0
ShapeLength
ShapeLength
Double
8
0
0
Shape
Shape
Geometry
0
0
0
Feature geometry.
Esri
Coordinates defining the features.
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.
20230131
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