20210716
11353100
1.0
FALSE
file://\\gisserver\GIS_Data\GIS Data\Surveyor\Baeten_Projects\MCCSC_Redistricting\MCCSC_Redistricting.gdb
Local Area Network
superbus_mapB_Dissolve
002
Copy "S:\Angela's Staff\Special Projects (SD)\Reprecincting\2021\2. Census 2020 Geography for IED\Census 2020 Geography for IED\18105\tl_2020_18105_tabblock20.shp" "S:\Angela's Staff\Special Projects (SD)\Reprecincting\2021\Monroe\Monroe Census Tiger Files\tl_2020_18105_tabblock20.shp" Shapefile #
FeatureClassToFeatureClass "C:\Users\sujeichm\Documents\Monroe Census Tiger Files\Monroe Census Tiger Files\tl_2020_18105_tabblock20.shp" C:\Users\sujeichm\Documents\ArcGIS\Projects\Data\Vector_gis.sde\DBO.Census_2020 Monroe_Census_Blocks_2020 # "STATEFP20 "STATEFP20" true true false 2 Text 0 0,First,#,C:\Users\sujeichm\Documents\Monroe Census Tiger Files\Monroe Census Tiger Files\tl_2020_18105_tabblock20.shp,STATEFP20,0,2;COUNTYFP20 "COUNTYFP20" true true false 3 Text 0 0,First,#,C:\Users\sujeichm\Documents\Monroe Census Tiger Files\Monroe Census Tiger Files\tl_2020_18105_tabblock20.shp,COUNTYFP20,0,3;TRACTCE20 "TRACTCE20" true true false 6 Text 0 0,First,#,C:\Users\sujeichm\Documents\Monroe Census Tiger Files\Monroe Census Tiger Files\tl_2020_18105_tabblock20.shp,TRACTCE20,0,6;BLOCKCE20 "BLOCKCE20" true true false 4 Text 0 0,First,#,C:\Users\sujeichm\Documents\Monroe Census Tiger Files\Monroe Census Tiger Files\tl_2020_18105_tabblock20.shp,BLOCKCE20,0,4;GEOID20 "GEOID20" true true false 15 Text 0 0,First,#,C:\Users\sujeichm\Documents\Monroe Census Tiger Files\Monroe Census Tiger Files\tl_2020_18105_tabblock20.shp,GEOID20,0,15;NAME20 "NAME20" true true false 10 Text 0 0,First,#,C:\Users\sujeichm\Documents\Monroe Census Tiger Files\Monroe Census Tiger Files\tl_2020_18105_tabblock20.shp,NAME20,0,10;MTFCC20 "MTFCC20" true true false 5 Text 0 0,First,#,C:\Users\sujeichm\Documents\Monroe Census Tiger Files\Monroe Census Tiger Files\tl_2020_18105_tabblock20.shp,MTFCC20,0,5;UR20 "UR20" true true false 1 Text 0 0,First,#,C:\Users\sujeichm\Documents\Monroe Census Tiger Files\Monroe Census Tiger Files\tl_2020_18105_tabblock20.shp,UR20,0,1;UACE20 "UACE20" true true false 5 Text 0 0,First,#,C:\Users\sujeichm\Documents\Monroe Census Tiger Files\Monroe Census Tiger Files\tl_2020_18105_tabblock20.shp,UACE20,0,5;UATYPE20 "UATYPE20" true true false 1 Text 0 0,First,#,C:\Users\sujeichm\Documents\Monroe Census Tiger Files\Monroe Census Tiger Files\tl_2020_18105_tabblock20.shp,UATYPE20,0,1;FUNCSTAT20 "FUNCSTAT20" true true false 1 Text 0 0,First,#,C:\Users\sujeichm\Documents\Monroe Census Tiger Files\Monroe Census Tiger Files\tl_2020_18105_tabblock20.shp,FUNCSTAT20,0,1;ALAND20 "ALAND20" true true false 14 Double 0 14,First,#,C:\Users\sujeichm\Documents\Monroe Census Tiger Files\Monroe Census Tiger Files\tl_2020_18105_tabblock20.shp,ALAND20,-1,-1;AWATER20 "AWATER20" true true false 14 Double 0 14,First,#,C:\Users\sujeichm\Documents\Monroe Census Tiger Files\Monroe Census Tiger Files\tl_2020_18105_tabblock20.shp,AWATER20,-1,-1;INTPTLAT20 "INTPTLAT20" true true false 11 Text 0 0,First,#,C:\Users\sujeichm\Documents\Monroe Census Tiger Files\Monroe Census Tiger Files\tl_2020_18105_tabblock20.shp,INTPTLAT20,0,11;INTPTLON20 "INTPTLON20" true true false 12 Text 0 0,First,#,C:\Users\sujeichm\Documents\Monroe Census Tiger Files\Monroe Census Tiger Files\tl_2020_18105_tabblock20.shp,INTPTLON20,0,12" #
ExportFeatures DBO.Monroe_Census_Blocks_2020 "G:\GIS Data\Surveyor\Baeten_Projects\MCCSC_Redistricting\MCCSC_Redistricting.gdb\censusblocks2020" # NOT_USE_ALIAS "STATEFP20 "STATEFP20" true true false 2 Text 0 0,First,#,DBO.Monroe_Census_Blocks_2020,STATEFP20,0,1;COUNTYFP20 "COUNTYFP20" true true false 3 Text 0 0,First,#,DBO.Monroe_Census_Blocks_2020,COUNTYFP20,0,2;TRACTCE20 "TRACTCE20" true true false 6 Text 0 0,First,#,DBO.Monroe_Census_Blocks_2020,TRACTCE20,0,5;BLOCKCE20 "BLOCKCE20" true true false 4 Text 0 0,First,#,DBO.Monroe_Census_Blocks_2020,BLOCKCE20,0,3;GEOID20 "GEOID20" true true false 15 Text 0 0,First,#,DBO.Monroe_Census_Blocks_2020,GEOID20,0,14;NAME20 "NAME20" true true false 10 Text 0 0,First,#,DBO.Monroe_Census_Blocks_2020,NAME20,0,9;MTFCC20 "MTFCC20" true true false 5 Text 0 0,First,#,DBO.Monroe_Census_Blocks_2020,MTFCC20,0,4;UR20 "UR20" true true false 1 Text 0 0,First,#,DBO.Monroe_Census_Blocks_2020,UR20,0,0;UACE20 "UACE20" true true false 5 Text 0 0,First,#,DBO.Monroe_Census_Blocks_2020,UACE20,0,4;UATYPE20 "UATYPE20" true true false 1 Text 0 0,First,#,DBO.Monroe_Census_Blocks_2020,UATYPE20,0,0;FUNCSTAT20 "FUNCSTAT20" true true false 1 Text 0 0,First,#,DBO.Monroe_Census_Blocks_2020,FUNCSTAT20,0,0;ALAND20 "ALAND20" true true false 8 Double 0 14,First,#,DBO.Monroe_Census_Blocks_2020,ALAND20,-1,-1;AWATER20 "AWATER20" true true false 8 Double 0 14,First,#,DBO.Monroe_Census_Blocks_2020,AWATER20,-1,-1;INTPTLAT20 "INTPTLAT20" true true false 11 Text 0 0,First,#,DBO.Monroe_Census_Blocks_2020,INTPTLAT20,0,10;INTPTLON20 "INTPTLON20" true true false 12 Text 0 0,First,#,DBO.Monroe_Census_Blocks_2020,INTPTLON20,0,11" #
ExportFeatures censusblocks2020 "G:\GIS Data\Surveyor\Baeten_Projects\MCCSC_Redistricting\MCCSC_Redistricting.gdb\censusblocks2020_join" # NOT_USE_ALIAS "STATEFP20 "STATEFP20" true true false 2 Text 0 0,First,#,censusblocks2020,STATEFP20,0,1;COUNTYFP20 "COUNTYFP20" true true false 3 Text 0 0,First,#,censusblocks2020,COUNTYFP20,0,2;TRACTCE20 "TRACTCE20" true true false 6 Text 0 0,First,#,censusblocks2020,TRACTCE20,0,5;BLOCKCE20 "BLOCKCE20" true true false 4 Text 0 0,First,#,censusblocks2020,BLOCKCE20,0,3;GEOID20 "GEOID20" true true false 15 Text 0 0,First,#,censusblocks2020,GEOID20,0,14;NAME20 "NAME20" true true false 10 Text 0 0,First,#,censusblocks2020,NAME20,0,9;MTFCC20 "MTFCC20" true true false 5 Text 0 0,First,#,censusblocks2020,MTFCC20,0,4;UR20 "UR20" true true false 1 Text 0 0,First,#,censusblocks2020,UR20,0,0;UACE20 "UACE20" true true false 5 Text 0 0,First,#,censusblocks2020,UACE20,0,4;UATYPE20 "UATYPE20" true true false 1 Text 0 0,First,#,censusblocks2020,UATYPE20,0,0;FUNCSTAT20 "FUNCSTAT20" true true false 1 Text 0 0,First,#,censusblocks2020,FUNCSTAT20,0,0;ALAND20 "ALAND20" true true false 8 Double 0 0,First,#,censusblocks2020,ALAND20,-1,-1;AWATER20 "AWATER20" true true false 8 Double 0 0,First,#,censusblocks2020,AWATER20,-1,-1;INTPTLAT20 "INTPTLAT20" true true false 11 Text 0 0,First,#,censusblocks2020,INTPTLAT20,0,10;INTPTLON20 "INTPTLON20" true true false 12 Text 0 0,First,#,censusblocks2020,INTPTLON20,0,11;Shape_Length "Shape_Length" false true true 8 Double 0 0,First,#,censusblocks2020,Shape_Length,-1,-1;Shape_Area "Shape_Area" false true true 8 Double 0 0,First,#,censusblocks2020,Shape_Area,-1,-1" #
ExportFeatures censusblocks2020_join "G:\GIS Data\Surveyor\Baeten_Projects\MCCSC_Redistricting\MCCSC_Redistricting.gdb\censusblocks2020_studentstats" # NOT_USE_ALIAS "STATEFP20 "STATEFP20" true true false 2 Text 0 0,First,#,censusblocks2020_join,censusblocks2020_join.STATEFP20,0,1;COUNTYFP20 "COUNTYFP20" true true false 3 Text 0 0,First,#,censusblocks2020_join,censusblocks2020_join.COUNTYFP20,0,2;TRACTCE20 "TRACTCE20" true true false 6 Text 0 0,First,#,censusblocks2020_join,censusblocks2020_join.TRACTCE20,0,5;BLOCKCE20 "BLOCKCE20" true true false 4 Text 0 0,First,#,censusblocks2020_join,censusblocks2020_join.BLOCKCE20,0,3;GEOID20 "GEOID20" true true false 15 Text 0 0,First,#,censusblocks2020_join,censusblocks2020_join.GEOID20,0,14;NAME20 "NAME20" true true false 10 Text 0 0,First,#,censusblocks2020_join,censusblocks2020_join.NAME20,0,9;MTFCC20 "MTFCC20" true true false 5 Text 0 0,First,#,censusblocks2020_join,censusblocks2020_join.MTFCC20,0,4;UR20 "UR20" true true false 1 Text 0 0,First,#,censusblocks2020_join,censusblocks2020_join.UR20,0,0;UACE20 "UACE20" true true false 5 Text 0 0,First,#,censusblocks2020_join,censusblocks2020_join.UACE20,0,4;UATYPE20 "UATYPE20" true true false 1 Text 0 0,First,#,censusblocks2020_join,censusblocks2020_join.UATYPE20,0,0;FUNCSTAT20 "FUNCSTAT20" true true false 1 Text 0 0,First,#,censusblocks2020_join,censusblocks2020_join.FUNCSTAT20,0,0;ALAND20 "ALAND20" true true false 8 Double 0 0,First,#,censusblocks2020_join,censusblocks2020_join.ALAND20,-1,-1;AWATER20 "AWATER20" true true false 8 Double 0 0,First,#,censusblocks2020_join,censusblocks2020_join.AWATER20,-1,-1;INTPTLAT20 "INTPTLAT20" true true false 11 Text 0 0,First,#,censusblocks2020_join,censusblocks2020_join.INTPTLAT20,0,10;INTPTLON20 "INTPTLON20" true true false 12 Text 0 0,First,#,censusblocks2020_join,censusblocks2020_join.INTPTLON20,0,11;Shape_Length "Shape_Length" false true true 8 Double 0 0,First,#,censusblocks2020_join,censusblocks2020_join.Shape_Length,-1,-1;Shape_Area "Shape_Area" false true true 8 Double 0 0,First,#,censusblocks2020_join,censusblocks2020_join.Shape_Area,-1,-1;OBJECTID "OBJECTID" false true false 4 Long 0 9,First,#,censusblocks2020_join,total_stats_block_join.OBJECTID,-1,-1;GEOID20 "GEOID20" true true false 15 Text 0 0,First,#,censusblocks2020_join,total_stats_block_join.GEOID20,0,14;USER_school_year "school_year" true true false 4 Long 0 0,First,#,censusblocks2020_join,total_stats_block_join.USER_school_year,-1,-1;USER_Grade "Grade" true true false 8000 Text 0 0,First,#,censusblocks2020_join,total_stats_block_join.USER_Grade,0,7999;USER_Lunch "Lunch" true true false 8000 Text 0 0,First,#,censusblocks2020_join,total_stats_block_join.USER_Lunch,0,7999;FREQUENCY "FREQUENCY" true true false 4 Long 0 0,First,#,censusblocks2020_join,total_stats_block_join.FREQUENCY,-1,-1;COUNT_OBJECTID "COUNT_OBJECTID" true true false 4 Long 0 0,First,#,censusblocks2020_join,total_stats_block_join.COUNT_OBJECTID,-1,-1" #
SpatialJoin censusblocks2020_studentstats cenus_block_groups__a2Dissolve1 "G:\GIS Data\Surveyor\Baeten_Projects\MCCSC_Redistricting\MCCSC_Redistricting.gdb\censusblocks2020_SpatialJoin2" "Join one to many" KEEP_ALL "GEOID20 "GEOID20" true true false 15 Text 0 0,First,#,censusblocks2020_studentstats,GEOID20,0,14;NAME20 "NAME20" true true false 10 Text 0 0,First,#,censusblocks2020_studentstats,NAME20,0,9;GEOID20_1 "GEOID20" true true false 15 Text 0 0,First,#,censusblocks2020_studentstats,GEOID20_1,0,14;USER_school_year "school_year" true true false 4 Long 0 0,First,#,censusblocks2020_studentstats,USER_school_year,-1,-1;USER_Grade "Grade" true true false 8000 Text 0 0,First,#,censusblocks2020_studentstats,USER_Grade,0,7999;USER_Lunch "Lunch" true true false 8000 Text 0 0,First,#,censusblocks2020_studentstats,USER_Lunch,0,7999;FREQUENCY "FREQUENCY" true true false 4 Long 0 0,First,#,censusblocks2020_studentstats,FREQUENCY,-1,-1;COUNT_OBJECTID "COUNT_OBJECTID" true true false 4 Long 0 0,First,#,censusblocks2020_studentstats,COUNT_OBJECTID,-1,-1;Shape_Length "Shape_Length" false true true 8 Double 0 0,First,#,censusblocks2020_studentstats,Shape_Length,-1,-1;Shape_Area "Shape_Area" false true true 8 Double 0 0,First,#,censusblocks2020_studentstats,Shape_Area,-1,-1;AttendanceZone "Attendance Zone" true true false 255 Text 0 0,First,#,cenus_block_groups__a2Dissolve1,AttendanceZone,0,254;Shape_Length_1 "Shape_Length" false true true 8 Double 0 0,First,#,cenus_block_groups__a2Dissolve1,Shape_Length,-1,-1;Shape_Area_1 "Shape_Area" false true true 8 Double 0 0,First,#,cenus_block_groups__a2Dissolve1,Shape_Area,-1,-1" Within # # #
ExportFeatures censusblocks2020_SpatialJoin2 "G:\GIS Data\Surveyor\Baeten_Projects\MCCSC_Redistricting\MCCSC_Redistricting.gdb\mapA_blocks" # NOT_USE_ALIAS "Join_Count "Join_Count" true true false 4 Long 0 0,First,#,censusblocks2020_SpatialJoin2,Join_Count,-1,-1;TARGET_FID "TARGET_FID" true true false 4 Long 0 0,First,#,censusblocks2020_SpatialJoin2,TARGET_FID,-1,-1;JOIN_FID "JOIN_FID" true true false 4 Long 0 0,First,#,censusblocks2020_SpatialJoin2,JOIN_FID,-1,-1;GEOID20 "GEOID20" true true false 15 Text 0 0,First,#,censusblocks2020_SpatialJoin2,GEOID20,0,14;NAME20 "NAME20" true true false 10 Text 0 0,First,#,censusblocks2020_SpatialJoin2,NAME20,0,9;GEOID20_1 "GEOID20" true true false 15 Text 0 0,First,#,censusblocks2020_SpatialJoin2,GEOID20_1,0,14;USER_school_year "school_year" true true false 4 Long 0 0,First,#,censusblocks2020_SpatialJoin2,USER_school_year,-1,-1;USER_Grade "Grade" true true false 8000 Text 0 0,First,#,censusblocks2020_SpatialJoin2,USER_Grade,0,7999;USER_Lunch "Lunch" true true false 8000 Text 0 0,First,#,censusblocks2020_SpatialJoin2,USER_Lunch,0,7999;FREQUENCY "FREQUENCY" true true false 4 Long 0 0,First,#,censusblocks2020_SpatialJoin2,FREQUENCY,-1,-1;COUNT_OBJECTID "COUNT_OBJECTID" true true false 4 Long 0 0,First,#,censusblocks2020_SpatialJoin2,COUNT_OBJECTID,-1,-1;AttendanceZone "Attendance Zone" true true false 255 Text 0 0,First,#,censusblocks2020_SpatialJoin2,AttendanceZone,0,254;Shape_Length_1 "Shape_Length" true true false 8 Double 0 0,First,#,censusblocks2020_SpatialJoin2,Shape_Length_1,-1,-1;Shape_Area_1 "Shape_Area" true true false 8 Double 0 0,First,#,censusblocks2020_SpatialJoin2,Shape_Area_1,-1,-1;Shape_Length "Shape_Length" false true true 8 Double 0 0,First,#,censusblocks2020_SpatialJoin2,Shape_Length,-1,-1;Shape_Area "Shape_Area" false true true 8 Double 0 0,First,#,censusblocks2020_SpatialJoin2,Shape_Area,-1,-1" #
ExportFeatures mapA_blocks "G:\GIS Data\Surveyor\Baeten_Projects\MCCSC_Redistricting\MCCSC_Redistricting.gdb\superbus_map" # NOT_USE_ALIAS "Join_Count "Join_Count" true true false 4 Long 0 0,First,#,mapA_blocks,Join_Count,-1,-1;TARGET_FID "TARGET_FID" true true false 4 Long 0 0,First,#,mapA_blocks,TARGET_FID,-1,-1;JOIN_FID "JOIN_FID" true true false 4 Long 0 0,First,#,mapA_blocks,JOIN_FID,-1,-1;GEOID20 "GEOID20" true true false 15 Text 0 0,First,#,mapA_blocks,GEOID20,0,14;NAME20 "NAME20" true true false 10 Text 0 0,First,#,mapA_blocks,NAME20,0,9;GEOID20_1 "GEOID20" true true false 15 Text 0 0,First,#,mapA_blocks,GEOID20_1,0,14;USER_school_year "school_year" true true false 4 Long 0 0,First,#,mapA_blocks,USER_school_year,-1,-1;USER_Grade "Grade" true true false 8000 Text 0 0,First,#,mapA_blocks,USER_Grade,0,7999;USER_Lunch "Lunch" true true false 8000 Text 0 0,First,#,mapA_blocks,USER_Lunch,0,7999;FREQUENCY "FREQUENCY" true true false 4 Long 0 0,First,#,mapA_blocks,FREQUENCY,-1,-1;COUNT_OBJECTID "COUNT_OBJECTID" true true false 4 Long 0 0,First,#,mapA_blocks,COUNT_OBJECTID,-1,-1;AttendanceZone "Attendance Zone" true true false 255 Text 0 0,First,#,mapA_blocks,AttendanceZone,0,254;Shape_Length_1 "Shape_Length" true true false 8 Double 0 0,First,#,mapA_blocks,Shape_Length_1,-1,-1;Shape_Area_1 "Shape_Area" true true false 8 Double 0 0,First,#,mapA_blocks,Shape_Area_1,-1,-1;Shape_Length "Shape_Length" false true true 8 Double 0 0,First,#,mapA_blocks,Shape_Length,-1,-1;Shape_Area "Shape_Area" false true true 8 Double 0 0,First,#,mapA_blocks,Shape_Area,-1,-1" #
ExportFeatures superbus_map "G:\GIS Data\Surveyor\Baeten_Projects\MCCSC_Redistricting\MCCSC_Redistricting.gdb\superbus_map_export" # NOT_USE_ALIAS "Join_Count "Join_Count" true true false 4 Long 0 0,First,#,superbus_map,superbus_map.Join_Count,-1,-1;TARGET_FID "TARGET_FID" true true false 4 Long 0 0,First,#,superbus_map,superbus_map.TARGET_FID,-1,-1;JOIN_FID "JOIN_FID" true true false 4 Long 0 0,First,#,superbus_map,superbus_map.JOIN_FID,-1,-1;GEOID20 "GEOID20" true true false 15 Text 0 0,First,#,superbus_map,superbus_map.GEOID20,0,14;NAME20 "NAME20" true true false 10 Text 0 0,First,#,superbus_map,superbus_map.NAME20,0,9;GEOID20_1 "GEOID20" true true false 15 Text 0 0,First,#,superbus_map,superbus_map.GEOID20_1,0,14;USER_school_year "school_year" true true false 4 Long 0 0,First,#,superbus_map,superbus_map.USER_school_year,-1,-1;USER_Grade "Grade" true true false 8000 Text 0 0,First,#,superbus_map,superbus_map.USER_Grade,0,7999;USER_Lunch "Lunch" true true false 8000 Text 0 0,First,#,superbus_map,superbus_map.USER_Lunch,0,7999;FREQUENCY "FREQUENCY" true true false 4 Long 0 0,First,#,superbus_map,superbus_map.FREQUENCY,-1,-1;COUNT_OBJECTID "COUNT_OBJECTID" true true false 4 Long 0 0,First,#,superbus_map,superbus_map.COUNT_OBJECTID,-1,-1;AttendanceZone "Attendance Zone" true true false 255 Text 0 0,First,#,superbus_map,superbus_map.AttendanceZone,0,254;Shape_Length_1 "Shape_Length" true true false 8 Double 0 0,First,#,superbus_map,superbus_map.Shape_Length_1,-1,-1;Shape_Area_1 "Shape_Area" true true false 8 Double 0 0,First,#,superbus_map,superbus_map.Shape_Area_1,-1,-1;Shape_Length "Shape_Length" false true true 8 Double 0 0,First,#,superbus_map,superbus_map.Shape_Length,-1,-1;Shape_Area "Shape_Area" false true true 8 Double 0 0,First,#,superbus_map,superbus_map.Shape_Area,-1,-1;OBJECTID "OBJECTID" false true false 4 Long 0 9,First,#,superbus_map,superbus_map_lunchstats_join.OBJECTID,-1,-1;GEOID20 "GEOID20" true true false 15 Text 0 0,First,#,superbus_map,superbus_map_lunchstats_join.GEOID20,0,14;FREQUENCY "FREQUENCY" true true false 4 Long 0 0,First,#,superbus_map,superbus_map_lunchstats_join.FREQUENCY,-1,-1;SUM_FREQUENCY "SUM_FREQUENCY" true true false 8 Double 0 0,First,#,superbus_map,superbus_map_lunchstats_join.SUM_FREQUENCY,-1,-1" #
ExportFeatures superbus_map_export "G:\GIS Data\Surveyor\Baeten_Projects\MCCSC_Redistricting\MCCSC_Redistricting.gdb\superbus_mapB" # NOT_USE_ALIAS "Join_Count "Join_Count" true true false 4 Long 0 0,First,#,superbus_map_export,Join_Count,-1,-1;TARGET_FID "TARGET_FID" true true false 4 Long 0 0,First,#,superbus_map_export,TARGET_FID,-1,-1;JOIN_FID "JOIN_FID" true true false 4 Long 0 0,First,#,superbus_map_export,JOIN_FID,-1,-1;GEOID20 "GEOID20" true true false 15 Text 0 0,First,#,superbus_map_export,GEOID20,0,14;NAME20 "NAME20" true true false 10 Text 0 0,First,#,superbus_map_export,NAME20,0,9;GEOID20_1 "GEOID20" true true false 15 Text 0 0,First,#,superbus_map_export,GEOID20_1,0,14;USER_school_year "school_year" true true false 4 Long 0 0,First,#,superbus_map_export,USER_school_year,-1,-1;USER_Grade "Grade" true true false 8000 Text 0 0,First,#,superbus_map_export,USER_Grade,0,7999;USER_Lunch "Lunch" true true false 8000 Text 0 0,First,#,superbus_map_export,USER_Lunch,0,7999;FREQUENCY "FREQUENCY" true true false 4 Long 0 0,First,#,superbus_map_export,FREQUENCY,-1,-1;COUNT_OBJECTID "COUNT_OBJECTID" true true false 4 Long 0 0,First,#,superbus_map_export,COUNT_OBJECTID,-1,-1;AttendanceZone "Attendance Zone" true true false 255 Text 0 0,First,#,superbus_map_export,AttendanceZone,0,254;Shape_Length_1 "Shape_Length" true true false 8 Double 0 0,First,#,superbus_map_export,Shape_Length_1,-1,-1;Shape_Area_1 "Shape_Area" true true false 8 Double 0 0,First,#,superbus_map_export,Shape_Area_1,-1,-1;OBJECTID_1 "OBJECTID" true true false 4 Long 0 0,First,#,superbus_map_export,OBJECTID_1,-1,-1;GEOID20_12 "GEOID20" true true false 15 Text 0 0,First,#,superbus_map_export,GEOID20_12,0,14;FREQUENCY_1 "FREQUENCY" true true false 4 Long 0 0,First,#,superbus_map_export,FREQUENCY_1,-1,-1;SUM_FREQUENCY "SUM_FREQUENCY" true true false 8 Double 0 0,First,#,superbus_map_export,SUM_FREQUENCY,-1,-1;Shape_Length "Shape_Length" false true true 8 Double 0 0,First,#,superbus_map_export,Shape_Length,-1,-1;Shape_Area "Shape_Area" false true true 8 Double 0 0,First,#,superbus_map_export,Shape_Area,-1,-1" #
Dissolve superbus_mapB "G:\GIS Data\Surveyor\Baeten_Projects\MCCSC_Redistricting\MCCSC_Redistricting.gdb\superbus_mapB_Dissolve" AttendanceZone # MULTI_PART DISSOLVE_LINES #
Projected
GCS_North_American_1983
Linear Unit: Foot_US (0.304801)
NAD_1983_StatePlane_Indiana_West_FIPS_1302_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/3.3.0'><WKT>PROJCS["NAD_1983_StatePlane_Indiana_West_FIPS_1302_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["Transverse_Mercator"],PARAMETER["False_Easting",2952750.0],PARAMETER["False_Northing",820208.3333333333],PARAMETER["Central_Meridian",-87.08333333333333],PARAMETER["Scale_Factor",0.9999666666666667],PARAMETER["Latitude_Of_Origin",37.5],UNIT["Foot_US",0.3048006096012192],AUTHORITY["EPSG",2966]]</WKT><XOrigin>-15495200</XOrigin><YOrigin>-45615400</YOrigin><XYScale>3048.0060960121928</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.0032808333333333331</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>2245</WKID><LatestWKID>2966</LatestWKID></ProjectedCoordinateSystem>
20251021
15401300
20251021
15401300
Microsoft Windows 10 Version 10.0 (Build 26100) ; Esri ArcGIS 13.3.0.52636
superbus_mapB_Dissolve
File Geodatabase Feature Class
dataset
EPSG
6.3(9.0.0)
0
Simple
FALSE
0
TRUE
FALSE
superbus_mapB_Dissolve
Feature Class
0
OBJECTID
OBJECTID
OID
4
0
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
Shape
Shape
Geometry
0
0
0
Feature geometry.
Esri
Coordinates defining the features.
AttendanceZone
Attendance Zone
String
255
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.
20251021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