20230424
10380500
1.0
FALSE
over85Num
002
913174.999355
1067382.508606
120128.274951
272844.293823
1
0.000
Projected
GCS_NAD_1983_2011
Linear Unit: Meter (1.000000)
NAD_1983_2011_StatePlane_New_York_Long_Island_FIPS_3104
<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/2.9.0'><WKT>PROJCS["NAD_1983_2011_StatePlane_New_York_Long_Island_FIPS_3104",GEOGCS["GCS_NAD_1983_2011",DATUM["D_NAD_1983_2011",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic"],PARAMETER["False_Easting",300000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-74.0],PARAMETER["Standard_Parallel_1",40.66666666666666],PARAMETER["Standard_Parallel_2",41.03333333333333],PARAMETER["Latitude_Of_Origin",40.16666666666666],UNIT["Meter",1.0],AUTHORITY["EPSG",6538]]</WKT><XOrigin>-36588100</XOrigin><YOrigin>-29425600</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>103116</WKID><LatestWKID>6538</LatestWKID></ProjectedCoordinateSystem>
20230508
13415100
20230508
13415100
150000000
5000
external
8a4090e01f5f57bf9facfa428fb5afb
New York City Department of City Planning (DCP)
120 Broadway, 31st Floor
New York
NY
10271
DCPopendata@planning.nyc.gov
True
New York City Department of City Planning (DCP)
Vulnerability score for proportion of population with a disability.
<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Census Tracts from the 2020 US Census for New York City clipped to the shoreline. These boundary files are derived from the US Census Bureau's TIGER project and have been geographically modified to fit the New York City base map. Because some census tracts are under water not all census tracts are contained in this file, only census tracts that are partially or totally located on land have been mapped in this file.</SPAN></P></DIV></DIV></DIV>
Department of City Planning (DCP)
New York City Census Tracts (2020 US Census)
external
8a4090e01f5f57bf9facfa428fb5afb
New York City Department of City Planning (DCP)
120 Broadway, 31st Floor
New York
NY
10271
DCPopendata@planning.nyc.gov
True
New York City Department of City Planning (DCP)
1/23/2023
2/13/2023
23A
Advanced GIS
<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>This dataset is being provided by the Department of City Planning (DCP) on DCP’s website for informational purposes only. DCP does not warranty the completeness, accuracy, content, or fitness for any particular purpose or use of the dataset, nor are any such warranties to be implied or inferred with respect to the dataset as furnished on the website. DCP and the City are not liable for any deficiencies in the completeness, accuracy, content, or fitness for any particular purpose or use the dataset, or applications utilizing the dataset, provided by any third party.</SPAN></P></DIV></DIV></DIV>
external
8a4090e01f5f57bf9facfa428fb5afb
New York City Department of City Planning (DCP)
120 Broadway, 31st Floor
New York
NY
10271
DCPopendata@planning.nyc.gov
True
New York City Department of City Planning (DCP)
Esri ArcGIS 12.9.4.32739
1
-74.257159
-73.699215
40.915568
40.496010
nyct2020
Feature Class
0
OBJECTID
OBJECTID
OID
4
0
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
CTLabel
The census tract identifier for the polygon. Each census tract number is unique to its borough.
String
7
CTLabel
0
0
BoroCode
Borough of census tract.
1
Manhattan
2
Bronx
3
Brooklyn
4
Queens
5
Staten Island
String
1
BoroCode
0
0
BoroName
Borough Name.
String
32
BoroName
0
0
CT2020
String value of the census tract number.
String
6
CT2020
0
0
BoroCT2020
Merged string of borough code and census tract number.
String
7
BoroCT2020
0
0
CDEligibil
Community Development Block Grant Eligibility.
String
1
CDEligibil
0
0
Shape
Feature geometry.
ESRI
Coordinates defining the features.
Shape
Geometry
0
0
0
SHAPE_Area
Area of feature in internal units squared.
ESRI
Positive real numbers that are automatically generated.
Shape_Area
Double
8
0
0
NTA2020
Neighborhood Tabulation Area Code
String
6
NTA2020
0
0
CDTA2020
Community District Tabulation Area code
String
4
CDTA2020
0
0
CDTANAME
Community District Tabulation Area name
String
75
CDTANAME
0
0
GEOID
Full Census Tract number including the FIPS state and county code
String
11
GEOID
0
0
Shape_Leng
Shape_Leng
Double
8
0
0
GEO_ID
GEO_ID
Double
8
0
0
GEOID_1
GEOID
Double
8
0
0
age_pop
age_pop
Integer
4
0
0
pop_85
pop_85
Integer
4
0
0
prop_over85
prop_over85
String
8000
0
0
race_pop
race_pop
Integer
4
0
0
reclass_85
reclass_85
Double
8
0
0
vulnerability
vulnerability
Double
8
0
0
dis_prop
dis_prop
Double
8
0
0
reclass_dis2
reclass_dis2
Double
8
0
0
no_hs_prop
no_hs_prop
Double
8
0
0
reclass_no_hs_2
reclass_no_hs_2
Double
8
0
0
pov_prop
pov_prop
Double
8
0
0
reclass_pov_2
reclass_pov_2
Double
8
0
0
reclass_black_2
reclass_black_2
Double
8
0
0
black_prop
black_prop
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.
NTAName
Neighborhood Tabulation Area Name
String
75
NTAName
0
0
File Geodatabase Feature Class
0.000
dataset
EPSG
8.2.10(10.3.1)
0
Simple
FALSE
0
TRUE
FALSE
20230508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