20210224
08290700
1.0
FALSE
T2020_Census_Blocks_Yuba_County
002
0.000
Projected
GCS_North_American_1983
Linear Unit: Foot_US (0.304801)
<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/3.0.0'><WKT>PROJCS["NAD_1983_StatePlane_California_II_FIPS_0402_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",6561666.666666666],PARAMETER["False_Northing",1640416.666666667],PARAMETER["Central_Meridian",-122.0],PARAMETER["Standard_Parallel_1",38.33333333333334],PARAMETER["Standard_Parallel_2",39.83333333333334],PARAMETER["Latitude_Of_Origin",37.66666666666666],UNIT["Foot_US",0.3048006096012192],AUTHORITY["EPSG",2226]]</WKT><XOrigin>-115211800</XOrigin><YOrigin>-93821500</YOrigin><XYScale>1600</XYScale><ZOrigin>0</ZOrigin><ZScale>1</ZScale><MOrigin>0</MOrigin><MScale>1</MScale><XYTolerance>0.02</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>102642</WKID><LatestWKID>2226</LatestWKID></ProjectedCoordinateSystem>
NAD_1983_StatePlane_California_II_FIPS_0402_Feet
20221121
10051400
20221213
9582900
150000000
5000
ItemDescription
Esri ArcGIS 13.0.2.36056
2020 Census Blocks Yuba County
2020 Census Block Demographics for Yuba County. For use with the Census MAF/TIGER database, the Census data site, or with other statistical applications.
2020 Census Blocks for Yuba County.
This feature class contains Decennial Census P.L. 94-171 Redistricting Data.
Blocks are the smallest geographic unit available and are the basis for all other census geographic tabulations.
Census
2020
Block
demographic
population
SACOG
dem2020
<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>2020 Census Block Demographics for Yuba County.</SPAN></P><P><SPAN>Decennial Census 2020 includes tabulations of housing units, total population and adult population by race and by Hispanic or Latino origin, and total group quarters population. Data are summary statistics for population and housing from a "100% count." The Census Bureau attempts to survey or interview all known addresses. Geographies nationwide can be obtained from Census, with disaggregate geographic detail down to Block-level.</SPAN></P><P><SPAN>The Decennial Census PL94-171 reports summary statistics on population and housing for use in redistricting. The Census Bureau attempts to survey or interview all known addresses. Still, the data are subject to error. The errors derive from survey data collection (response errors, field follow-up for missing cases) and processing by the Census Bureau (geolocation of population and housing, data coding, compilation processes, and imputation of missing cases).</SPAN></P></DIV></DIV></DIV>
U.S. Census Bureau
<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>SACOG provides data as a public service. These data are provided "as-is." While every effort has been made to ensure the accuracy or correctness of these data, SACOG makes no warranty, expressed or implied, as to its accuracy or correctness and expressly disclaims liability for the accuracy thereof. In no event shall SACOG become liable to users of these data, or any other party, for any loss or damages, consequential or otherwise, including but not limited to time, money, or goodwill, arising from the use, operation or modification of the data. In using these data, users further agree to indemnify, defend, and hold harmless SACOG for any and all liability of any nature arising out of or resulting from the lack of accuracy or correctness of the data, or the use of the data. Users will not distribute these data to other potential users. Instead they will refer those users to SACOG for an independent dataset and documentation. To assist SACOG in the maintenance of the data, users should provide SACOG's GIS staff information concerning errors or discrepancies found in using the data.</SPAN></P></DIV></DIV></DIV>
Enterprise Geodatabase Feature Class
0.000
dataset
EPSG
5.3(9.0.0)
0
Simple
FALSE
0
TRUE
FALSE
T2020_Census_Blocks_Yuba_County
Feature Class
0
OBJECTID
OBJECTID
OID
4
10
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
Shape
Shape
Geometry
8
0
0
Feature geometry.
Esri
Coordinates defining the features.
FILEID
File Identification
String
255
0
0
SUMLEV
Summary Level
Double
8
38
8
GEOID
Geographic Record Identifier
String
255
0
0
GEOCODETract
GEOCODE Tract
String
255
0
0
GEOCODEBlockGroup
GEOCODE BlockGroup
String
255
0
0
GEOCODEBlock
GEOCODE Block
String
255
0
0
STATE
State (FIPS)
Double
8
38
8
COUNTY
County (FIPS)
Double
8
38
8
COUNTYCC
FIPS County Class Code
String
255
0
0
COUNTYNS
County (NS)
Double
8
38
8
PLACE
Place (FIPS)
Double
8
38
8
PLACECC
FIPS Place Class Code
String
255
0
0
PLACENS
Place (NS)
Double
8
38
8
TRACT
Census Tract
Double
8
38
8
BLKGRP
Block Group
Double
8
38
8
Block
Block
Double
8
38
8
CBSA
Metropolitan Statistical Area/Micropolitan Statistical Area
Double
8
38
8
MEMI
Metropolitan/Micropolitan Indicator
Double
8
38
8
CSA
Combined Statistical Area
Double
8
38
8
UA
Urban Area
String
255
0
0
UATYPE
Urban Area Type
String
255
0
0
UR
Urban/Rural
String
255
0
0
ZCTA
ZIP Code Tabulation Area (5-Digit)
String
255
0
0
SDELM
School District (Elementary)
Double
8
38
8
SDSEC
School District (Secondary)
Double
8
38
8
SDUNI
School District (Unified)
Double
8
38
8
PUMA
Public Use Microdata Area
String
255
0
0
BASENAME
Area Base Name
Double
8
38
8
NAME
Area Name-Legal/Statistical Area Description (LSAD) Term-Part In
String
255
0
0
POP100
Population Count (100%)
Double
8
38
8
HU100
Housing Unit Count (100%)
Double
8
38
8
Population
Total Population
Double
8
38
8
Population18_P3
Total population 18 years and over
Double
8
38
8
HispanicOrigin
Total__Hispanic or Latino
Double
8
38
8
NotHispanic
Total__Not Hispanic or Latino
Double
8
38
8
NH_Wht
Total__Not Hispanic or Latino__Population of one race__White alone
Double
8
38
8
NH_Blk
Total__Not Hispanic or Latino__Population of one race__Black or African American alone
Double
8
38
8
NH_Ind
Total__Not Hispanic or Latino__Population of one race__American Indian and Alaska Native alone
Double
8
38
8
NH_Asn
Total__Not Hispanic or Latino__Population of one race__Asian alone
Double
8
38
8
NH_Hwn
Total__Not Hispanic or Latino__Population of one race__Native Hawaiian and Other Pacific Islander alone
Double
8
38
8
NH_Oth
Total__Not Hispanic or Latino__Population of one race__Some Other Race Alone
Double
8
38
8
NH_2
Total__Not Hispanic or Latino__Population of two or more races
Double
8
38
8
Housing_Units
Total Housing Units
Double
8
38
8
HU_Occupied
Total__Occupied Housing Units
Double
8
38
8
HU_Vacant
Total__Vacant Housing Units
Double
8
38
8
GQ_Institutional_Pop
Total__Institutionalized population
Double
8
38
8
GQ_Inst_CFAdult
Total__Institutionalized population__Correctional facilities for Adults
Double
8
38
8
GQ_Inst_Juvenile
Total__Institutionalized population__Juvenile facilities
Double
8
38
8
GQ_Inst_Nursing
Total__Institutionalized population__Nursing facilities/Skilled-nursing facilities
Double
8
38
8
GQ_Inst_Oth
Total__Institutionalized population__Other institutional facilities
Double
8
38
8
GQ_NonInst_Pop
Total__Noninstitutionalized population
Double
8
38
8
GQ_NonInst_Student
Total__Noninstitutionalized population__College/University student housing
Double
8
38
8
GQ_NonInst_Military
Total__Noninstitutionalized population__Military quarters
Double
8
38
8
GQ_NonInst_Oth
Total__Noninstitutionalized population__Other noninstitutional facilities
Double
8
38
8
Shape.STArea()
Shape.STArea()
Double
0
0
0
Shape.STLength()
Shape.STLength()
Double
0
0
0
20221213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