<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<metadata xml:lang="en">
<Esri>
<CreaDate>20221216</CreaDate>
<CreaTime>07245000</CreaTime>
<ArcGISFormat>1.0</ArcGISFormat>
<SyncOnce>TRUE</SyncOnce>
<scaleRange>
<minScale>625000</minScale>
<maxScale>5000</maxScale>
</scaleRange>
<ArcGISProfile>ItemDescription</ArcGISProfile>
</Esri>
<dataIdInfo>
<idPurp>2010 Census Blocks for the SACOG Region. For use with the Census MAF/TIGER database, the Census data site, or with other statistical applications.</idPurp>
<idAbs>&lt;DIV STYLE="text-align:Left;"&gt;&lt;DIV&gt;&lt;DIV&gt;&lt;P&gt;&lt;SPAN&gt;March 2011&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;2010 Census blocks for the six counties in the SACOG region. Counties included are El Dorado, Placer, Sacramento, Sutter, Yolo, and Yuba. Census geographies are created ahead of each decennial census to tabulate census data. The geographic files are released ahead of data releases. Blocks are the smallest geographic unit available and are the basis for all other census geographic tabulations.&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;Updates occur with each decennial census. This dataset will remain as is. A new dataset will be released for the 2020 census.&lt;/SPAN&gt;&lt;/P&gt;&lt;/DIV&gt;&lt;/DIV&gt;&lt;/DIV&gt;</idAbs>
<idCredit>U.S. Census Bureau</idCredit>
<idCitation>
<resTitle>Census Blocks 2010 - SACOG Region</resTitle>
</idCitation>
<searchKeys>
<keyword>boundary</keyword>
<keyword>2010</keyword>
<keyword>census</keyword>
<keyword>block</keyword>
<keyword>census block</keyword>
<keyword>bndy2010</keyword>
<keyword>SACOG</keyword>
</searchKeys>
<resConst>
<Consts>
<useLimit>&lt;DIV STYLE="text-align:Left;"&gt;&lt;DIV&gt;&lt;DIV&gt;&lt;P&gt;&lt;SPAN&gt;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.&lt;/SPAN&gt;&lt;/P&gt;&lt;/DIV&gt;&lt;/DIV&gt;&lt;/DIV&gt;</useLimit>
</Consts>
</resConst>
</dataIdInfo>
<mdHrLv>
<ScopeCd value="005"/>
</mdHrLv>
<mdDateSt Sync="TRUE">20221216</mdDateSt>
<Binary>
<Thumbnail>
<Data EsriPropertyType="PictureX">/9j/4AAQSkZJRgABAQEAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a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</Data>
</Thumbnail>
</Binary>
</metadata>
