20260211
09111700
1.0
FALSE
ResProperty_Near_Stations
002
Projected
GCS_North_American_1983
Linear Unit: Foot_US (0.304801)
NAD_1983_StatePlane_Maryland_FIPS_1900_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/3.6.0'><WKT>PROJCS["NAD_1983_StatePlane_Maryland_FIPS_1900_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",1312333.333333333],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-77.0],PARAMETER["Standard_Parallel_1",38.3],PARAMETER["Standard_Parallel_2",39.45],PARAMETER["Latitude_Of_Origin",37.66666666666666],UNIT["Foot_US",0.3048006096012192],AUTHORITY["EPSG",2248]]</WKT><XOrigin>-121067600</XOrigin><YOrigin>-95498600</YOrigin><XYScale>3048.0060960121905</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.00328083333333333</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>102685</WKID><LatestWKID>2248</LatestWKID></ProjectedCoordinateSystem>
20260211
09111700
20260211
09111700
Esri ArcGIS 13.6.0.59527
Residential Near Stations
Single-Family Residential properties within a half mile of a Metro, MARC or Purple Line stations.
File Geodatabase Feature Class
dataset
EPSG
5.3(9.0.0)
0
Simple
FALSE
0
TRUE
FALSE
ResProperty_Near_Stations
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.
ACCT
ACCT
String
8
0
0
DISTRICT
DISTRICT
SmallInteger
2
0
0
SUBDIV
SUBDIV
SmallInteger
2
0
0
LOT
LOT
String
3
0
0
BLOCK
BLOCK
String
3
0
0
PARCEL
PARCEL
String
4
0
0
GENLZONE
GENLZONE
String
2
0
0
SPECZONE
SPECZONE
String
10
0
0
LEGALDESC
LEGALDESC
String
70
0
0
LAND_USE_CODE
LAND_USE_CODE
SmallInteger
2
0
0
OWNER
OWNER
String
34
0
0
PREM_NUM
PREM_NUM
String
5
0
0
PREM_DIR
PREM_DIR
String
1
0
0
PREM_SUFFIX
PREM_SUFFIX
String
1
0
0
PREM_STNAME
PREM_STNAME
String
18
0
0
PREM_STTYPE
PREM_STTYPE
String
4
0
0
PREM_CITY
PREM_CITY
String
22
0
0
PREM_ZIP
PREM_ZIP
String
9
0
0
MAILADDR1
MAILADDR1
String
34
0
0
MAILADDR2
MAILADDR2
String
34
0
0
MAILADDR3
MAILADDR3
String
34
0
0
MAILCITY
MAILCITY
String
22
0
0
MAILSTATE
MAILSTATE
String
2
0
0
MAILZIP
MAILZIP
String
9
0
0
TAX_CLASS
TAX_CLASS
SmallInteger
2
0
0
EXEMPT_CLASS_ST
EXEMPT_CLASS_ST
SmallInteger
2
0
0
EXEMPT_CODE_ST
EXEMPT_CODE_ST
String
1
0
0
EXEMPT_CODE_PRKG
EXEMPT_CODE_PRKG
String
1
0
0
PROP_LAND_FCV
PROP_LAND_FCV
Integer
4
0
0
PROP_IMPR_FCV
PROP_IMPR_FCV
Integer
4
0
0
ASSESSED_VAL
ASSESSED_VAL
Integer
4
0
0
ACRES
ACRES
Double
8
0
0
FEET
FEET
Double
8
0
0
DWEL_UNITS
DWEL_UNITS
SmallInteger
2
0
0
NUM_STORIES
NUM_STORIES
SmallInteger
2
0
0
YEAR_BUILT
YEAR_BUILT
SmallInteger
2
0
0
CREATE_DATE
CREATE_DATE
Integer
4
0
0
TRANSFER_DATE
TRANSFER_DATE
Integer
4
0
0
RECYC_AREA
RECYC_AREA
String
3
0
0
RECYC_UNITS
RECYC_UNITS
SmallInteger
2
0
0
REF_AREA
REF_AREA
String
3
0
0
REF_UNITS
REF_UNITS
SmallInteger
2
0
0
GROSS_FL_AREA
GROSS_FL_AREA
Integer
4
0
0
PLAT_NO
PLAT_NO
String
6
0
0
CONDO_UNIT
CONDO_UNIT
String
6
0
0
MUNI_CODE
MUNI_CODE
String
2
0
0
LIBER
LIBER
Integer
4
0
0
FOLIO
FOLIO
SmallInteger
2
0
0
TAXMAP
TAXMAP
String
6
0
0
CREATION_DATE
CREATION_DATE
Date
8
0
0
UPDATE_DATE
UPDATE_DATE
Date
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.
20260211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