20220120
08290300
1.0
FALSE
MiamiFlood
002
Projected
GCS_NAD_1983_2011
Linear Unit: Foot_US (0.304801)
NAD_1983_2011_StatePlane_Oklahoma_North_FIPS_3501_Ft_US
<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/2.9.0'><WKT>PROJCS["NAD_1983_2011_StatePlane_Oklahoma_North_FIPS_3501_Ft_US",GEOGCS["GCS_NAD_1983_2011",DATUM["D_NAD_1983_2011",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic"],PARAMETER["False_Easting",1968500.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-98.0],PARAMETER["Standard_Parallel_1",35.56666666666667],PARAMETER["Standard_Parallel_2",36.76666666666667],PARAMETER["Latitude_Of_Origin",35.0],UNIT["Foot_US",0.3048006096012192],AUTHORITY["EPSG",6553]]</WKT><XOrigin>-121323100</XOrigin><YOrigin>-94209400</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>103133</WKID><LatestWKID>6553</LatestWKID></ProjectedCoordinateSystem>
20220120
08381500
20220120
08381500
Esri ArcGIS 12.9.0.32739
MiamiFlood
$#%^ggcc@
FloodZone
File Geodatabase Feature Class
dataset
EPSG
8.2.10(10.3.1)
0
Simple
FALSE
0
TRUE
FALSE
MiamiFlood
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.
FLD_ZONE
FLD_ZONE
String
17
0
0
ZONE_SUBTY
ZONE_SUBTY
String
72
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.
20220120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