<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<metadata xml:lang="en">
<Esri>
<CreaDate>20191105</CreaDate>
<CreaTime>13225800</CreaTime>
<ArcGISFormat>1.0</ArcGISFormat>
<SyncOnce>TRUE</SyncOnce>
<DataProperties>
<lineage>
<Process Date="20191105" Time="132258" ToolSource="c:\program files\arcgis\pro\Resources\ArcToolbox\toolboxes\Data Management Tools.tbx\CopyFeatures">CopyFeatures fl_hexs "Q:\SACSIM19\Integration Data Summary\ILUT GIS\ILUT GIS.gdb\hex_w_wtdavgs_20191105" # # # #</Process>
<Process Date="20191105" Time="132300" ToolSource="c:\program files\arcgis\pro\Resources\ArcToolbox\toolboxes\Data Management Tools.tbx\AddField">AddField "Q:\SACSIM19\Integration Data Summary\ILUT GIS\ILUT GIS.gdb\hex_w_wtdavgs_20191105" mixidx_propl_awtdavg "Float (single precision)" # # # # NULLABLE NON_REQUIRED #</Process>
</lineage>
</DataProperties>
</Esri>
<dataIdInfo>
<idAbs/>
<searchKeys>
<keyword>ppa</keyword>
<keyword>hex</keyword>
<keyword>mix index</keyword>
</searchKeys>
<idPurp>Process:
1 - get each parcel's mix index for 1mi radius
2 - based on intersection, get area-weighted average mix index for each hex.</idPurp>
<idCredit/>
<resConst>
<Consts>
<useLimit/>
</Consts>
</resConst>
<idCitation>
<resTitle>Mix Index Testing</resTitle>
</idCitation>
</dataIdInfo>
<Binary>
<Thumbnail>
<Data EsriPropertyType="PictureX">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</Data>
</Thumbnail>
</Binary>
</metadata>
