20110517
09261100
1.0
FALSE
Census2010_Blocks_CoH
002
0.000
Projected
GCS_North_American_1983
NAD_1983_StatePlane_Texas_South_Central_FIPS_4204_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/2.8.0'><WKT>PROJCS["NAD_1983_StatePlane_Texas_South_Central_FIPS_4204_Feet",GEOGCS["GCS_North_American_1983",DATUM["D_North_American_1983",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic"],PARAMETER["False_Easting",1968500.0],PARAMETER["False_Northing",13123333.33333333],PARAMETER["Central_Meridian",-99.0],PARAMETER["Standard_Parallel_1",28.38333333333333],PARAMETER["Standard_Parallel_2",30.28333333333333],PARAMETER["Latitude_Of_Origin",27.83333333333333],UNIT["Foot_US",0.3048006096012192],AUTHORITY["EPSG",2278]]</WKT><XOrigin>-126725700</XOrigin><YOrigin>-77828800</YOrigin><XYScale>3048.0060960121914</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.0032808333333333335</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>102740</WKID><LatestWKID>2278</LatestWKID></ProjectedCoordinateSystem>
Linear Unit: Foot_US (0.304801)
20210819
09121100
20210819
09121100
ItemDescription
Esri ArcGIS 12.8.0.29751
Census2010_Blocks_CoH
002
City of Houston Census Block level housing, race and ethnicity data from the 2010 release of the PL94-171 redistricting data
pj23929
Disclaimer: In many instances census geography does not correspond to the boundaries of other feature classes maintained in COHGIS.
COHIGS data is prepared and made available for general reference purposes only and should not be used, or relied upon for specific applications, without independent verification. The City of Houston neither represents, nor warrants COHGIS data accuracy, or completeness, nor will the City of Houston accept liability of any kind in conjunction with its use.
<DIV STYLE="text-align:Left;"><DIV><DIV><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>This file contains the initial 2010 census population and housing data at the census block level for blocks defined as being in the City of Houston by the Census Bureau. The population and housing totals in this file represent summarizations of the 288 data items in the original census files. Specifically, populations are aggregated for Hispanic ethnicity and Non-Hispanic populations by 7 racial categories. These same aggregations are available for voting age populations (18 years and over). Housing data is limited to total, vacant and occupied units.</SPAN></SPAN></P><P STYLE="margin:0 0 0 0;"><SPAN /></P><P STYLE="margin:0 0 0 0;"><SPAN /></P><P><SPAN /></P></DIV></DIV></DIV>
File Geodatabase Feature Class
0.000
dataset
EPSG
6.11(9.0.0)
Simple
FALSE
0
TRUE
FALSE
0
Census2010_Blocks_CoH
Feature Class
0
Shape
Shape
Geometry
0
0
0
Feature geometry.
ESRI
Coordinates defining the features.
OBJECTID
OBJECTID
OID
4
0
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
GEOID
GEOID
String
254
0
0
STATE
STATE
String
254
0
0
COUNTY
COUNTY
String
254
0
0
PLACE
PLACE
String
254
0
0
TRACT
TRACT
String
254
0
0
BLKGRP
BLKGRP
String
254
0
0
BLOCK
BLOCK
String
254
0
0
NAME
NAME
String
254
0
0
POP100
POP100
Double
8
0
0
HU100
HU100
Double
8
0
0
TotPop
TotPop
Double
8
0
0
HispPop
HispPop
Double
8
0
0
NonHispPop
NonHispPop
Double
8
0
0
NHOneRace
NHOneRace
Double
8
0
0
NH_White
NH_White
Double
8
0
0
NH_Black
NH_Black
Double
8
0
0
NH_AmInd
NH_AmInd
Double
8
0
0
NH_Asian
NH_Asian
Double
8
0
0
NH_HawPacI
NH_HawPacI
Double
8
0
0
NH_Other
NH_Other
Double
8
0
0
NH_2orMore
NH_2orMore
Double
8
0
0
VAP_TotPop
VAP_TotPop
Double
8
0
0
VAP_HispPo
VAP_HispPo
Double
8
0
0
VAP_NonHis
VAP_NonHis
Double
8
0
0
VAP_NHOneR
VAP_NHOneR
Double
8
0
0
VAP_NH_Whi
VAP_NH_Whi
Double
8
0
0
VAP_NH_Bla
VAP_NH_Bla
Double
8
0
0
VAP_NH_AmI
VAP_NH_AmI
Double
8
0
0
VAP_NH_Asi
VAP_NH_Asi
Double
8
0
0
VAP_HawPac
VAP_HawPac
Double
8
0
0
VAP_NH_Oth
VAP_NH_Oth
Double
8
0
0
VAP_NH_2or
VAP_NH_2or
Double
8
0
0
TotHousing
TotHousing
Double
8
0
0
OccHU
OccHU
Double
8
0
0
VacantHU
VacantHU
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.
20210819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