20230310
09255100
1.0
FALSE
S_LABEL_LD
002
Projected
GCS_North_American_1983
Linear Unit: Foot_US (0.304801)
<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_Texas_North_Central_FIPS_4202_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",1968500.0],PARAMETER["False_Northing",6561666.666666666],PARAMETER["Central_Meridian",-98.5],PARAMETER["Standard_Parallel_1",32.13333333333333],PARAMETER["Standard_Parallel_2",33.96666666666667],PARAMETER["Latitude_Of_Origin",31.66666666666667],UNIT["Foot_US",0.3048006096012192],AUTHORITY["EPSG",2276]]</WKT><XOrigin>-129754698.88412645</XOrigin><YOrigin>-90847181.604881674</YOrigin><XYScale>35033917.985940121</XYScale><ZOrigin>0</ZOrigin><ZScale>1</ZScale><MOrigin>0</MOrigin><MScale>1</MScale><XYTolerance>0.0032808333333333331</XYTolerance><ZTolerance>2</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>102738</WKID><LatestWKID>2276</LatestWKID></ProjectedCoordinateSystem>
NAD_1983_StatePlane_Texas_North_Central_FIPS_4202_Feet
20240620
13501400
20240620
13501400
Esri ArcGIS 13.3.0.52636
S_LABEL_LD
sherman
gis
fema
flood
plain
2020
FEMA Flood Plain layer
Enterprise Geodatabase Feature Class
dataset
EPSG
5.3(9.0.0)
0
Simple
FALSE
0
TRUE
FALSE
S_LABEL_LD
Feature Class
0
OBJECTID
OBJECTID
OID
4
10
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
DFIRM_ID
DFIRM_ID
String
6
0
0
VERSION_ID
VERSION_ID
String
11
0
0
LEADER_ID
LEADER_ID
String
32
0
0
LABEL_TYPE
LABEL_TYPE
String
20
0
0
FIRM_PAN
FIRM_PAN
String
11
0
0
SCALE
SCALE
String
5
0
0
Shape
Shape
Geometry
8
0
0
Feature geometry.
Esri
Coordinates defining the features.
Shape.STLength()
Shape.STLength()
Double
0
0
0
20240620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