20181022
05252100
1.0
FALSE
CensusTract_Variables_Working
002
Projected
GCS_WGS_1984
Linear Unit: Meter (1.000000)
WGS_1984_Web_Mercator_Auxiliary_Sphere
<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/3.4.0'><WKT>PROJCS["WGS_1984_Web_Mercator_Auxiliary_Sphere",GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Mercator_Auxiliary_Sphere"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",0.0],PARAMETER["Standard_Parallel_1",0.0],PARAMETER["Auxiliary_Sphere_Type",0.0],UNIT["Meter",1.0],AUTHORITY["EPSG",3857]]</WKT><XOrigin>-20037700</XOrigin><YOrigin>-30241100</YOrigin><XYScale>10000</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>102100</WKID><LatestWKID>3857</LatestWKID></ProjectedCoordinateSystem>
20250422
10370500
20250422
10370500
Esri ArcGIS 13.4.0.55405
CensusTract_Variables_Working
File Geodatabase Feature Class
dataset
EPSG
6.18.3(9.3.1.2)
0
Simple
FALSE
0
TRUE
FALSE
CensusTract_Variables_Working
Feature Class
0
OBJECTID
Object ID
OID
4
0
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
Shape
Shape
Geometry
0
0
0
Feature geometry.
Esri
Coordinates defining the features.
GEOID
Geographic Identifier - FIPS Code
String
11
0
0
ALAND
Area of Land (Square Meters)
Double
8
0
0
AWATER
Area of Water (Square Meters)
Double
8
0
0
NAME
Name
String
255
0
0
B01001_001E
Total Population
Integer
4
0
0
B01001_001M
Total Population - Margin of Error
Double
8
0
0
B01001_calc_numLT18E
Population Less Than 18 Years
Integer
4
0
0
B01001_calc_numLT18M
Population Less Than 18 Years - Margin of Error
Integer
4
0
0
B01001_calc_pctLT18E
Percent of Population that is Less Than 18 Years
Double
8
0
0
B01001_calc_pctLT18M
Percent of Population that is Less Than 18 Years - Margin of Error
Double
8
0
0
B01001_calc_numGE65E
Population 65 Years and Over
Integer
4
0
0
B01001_calc_numGE65M
Population 65 Years and Over - Margin of Error
Integer
4
0
0
B01001_calc_pctGE65E
Percent of Population that is 65 Years and Over
Double
8
0
0
B01001_calc_pctGE65M
Percent of Population that is 65 Years and Over - Margin of Error
Double
8
0
0
B01001_calc_numDependE
Population in Dependent Age Groups (under 18 and 65+)
Integer
4
0
0
B01001_calc_numDependM
Population in Dependent Age Groups (under 18 and 65+) - Margin of Error
Integer
4
0
0
B01001_calc_pctDependE
Percent of Population in Dependent Age Groups (under 18 and 65+)
Double
8
0
0
B01001_calc_pctDependM
Percent of Population in Dependent Age Groups (under 18 and 65+) - Margin of Error
Double
8
0
0
Area_Acres
Area Acres
Double
8
0
0
Total_Subsidized_Units
Total Subsidized Units
Integer
4
0
0
Subsidized_Units_per_Pop
Subsidized Units per Population
Double
8
0
0
Pct_Sub_of_Aff
Percent of Affordable Units Funded by LIHTC
Double
8
0
0
Rent_Below50AMI
Renters Below 50% AMI
Integer
4
0
0
Pct_Below50AMI_Sub
Percent of Households Below 50% AMI in Subsidized Housing
Double
8
0
0
Div_Score
Housing Diversity Score
Double
8
0
0
Substandard
Substandard Housing Score
Double
8
0
0
Inc_Req
Income Required to Afford Median Rent
Integer
4
0
0
Med_Rent_Inc
Median Renter Income
Integer
4
0
0
Income_Diff
Actual Income Minus Required Income to Afford Median Rent
Integer
4
0
0
Displ_Risk
Displacement Risk Score
Double
8
0
0
Rent_Gap
Rent_Gap
Integer
4
0
0
Rent_Chng
Rent_Chng
Double
8
0
0
HmVal_Chng
HmVal_Chng
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.
20250422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