20241018
15452200
1.0
FALSE
Top100IntersectionBuffers_Final
002
Projected
GCS_North_American_1983
Linear Unit: Foot_US (0.304801)
NAD_1983_StatePlane_Florida_North_FIPS_0903_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/3.2.0'><WKT>PROJCS["NAD_1983_StatePlane_Florida_North_FIPS_0903_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",0.0],PARAMETER["Central_Meridian",-84.5],PARAMETER["Standard_Parallel_1",29.58333333333333],PARAMETER["Standard_Parallel_2",30.75],PARAMETER["Latitude_Of_Origin",29.0],UNIT["Foot_US",0.3048006096012192],AUTHORITY["EPSG",2238]]</WKT><XOrigin>-125939000</XOrigin><YOrigin>-91453300</YOrigin><XYScale>3048.0060960121918</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>102660</WKID><LatestWKID>2238</LatestWKID></ProjectedCoordinateSystem>
20241018
15273900
20241018
15273900
Esri ArcGIS 13.2.2.49743
Top100IntersectionBuffers_Final
File Geodatabase Feature Class
dataset
EPSG
5.3(9.0.0)
0
Simple
FALSE
0
TRUE
FALSE
Top100IntersectionBuffers_Final
Feature Class
0
OBJECTID
Object ID
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.
ORIG_FID
ORIG_FID
Integer
4
0
0
Id
Id
Integer
4
0
0
LFROM
LFROM
Integer
4
0
0
LTO
LTO
Integer
4
0
0
RFROM
RFROM
Integer
4
0
0
RTO
RTO
Integer
4
0
0
LLOW
LLOW
Integer
4
0
0
LHIGH
LHIGH
Integer
4
0
0
RLOW
RLOW
Integer
4
0
0
RHIGH
RHIGH
Integer
4
0
0
PREMOD
PREMOD
String
20
0
0
PREDIR
PREDIR
String
4
0
0
PRETYPE
PRETYPE
String
20
0
0
NAME
NAME
String
60
0
0
POSTTYPE
POSTTYPE
String
20
0
0
POSTDIR
POSTDIR
String
4
0
0
POSTMOD
POSTMOD
String
20
0
0
ALIAS
ALIAS
String
60
0
0
COUNTYRTE
COUNTYRTE
String
10
0
0
STRTE
STRTE
String
10
0
0
STRTETYPE
STRTETYPE
String
20
0
0
FEDRTE
FEDRTE
String
10
0
0
FEDRTETYPE
FEDRTETYPE
String
20
0
0
ONEWAY
ONEWAY
String
10
0
0
LESN
LESN
Double
8
0
0
RESN
RESN
Integer
4
0
0
LCOMM
LCOMM
String
40
0
0
RCOMM
RCOMM
String
40
0
0
LCNTY
LCNTY
String
40
0
0
RCNTY
RCNTY
String
40
0
0
LSTATE
LSTATE
String
10
0
0
RSTATE
RSTATE
String
10
0
0
CLASS
CLASS
String
20
0
0
created_us
created_us
String
254
0
0
created_da
created_da
Date
8
0
0
last_edite
last_edite
String
254
0
0
last_edi_1
last_edi_1
Date
8
0
0
GlobalID
GlobalID
String
38
0
0
CREATION_D
CREATION_D
Date
8
0
0
CREATION_U
CREATION_U
String
50
0
0
MODIFY_DAT
MODIFY_DAT
Date
8
0
0
MODIFY_USE
MODIFY_USE
String
50
0
0
NO_MSAG
NO_MSAG
Integer
4
0
0
C1_EXCEPTI
C1_EXCEPTI
Integer
4
0
0
SURFACE
SURFACE
String
50
0
0
KIND
KIND
String
50
0
0
OWNER
OWNER
String
50
0
0
SPATIAL
SPATIAL
Integer
4
0
0
ATTRIBUTES
ATTRIBUTES
Integer
4
0
0
WIDTH
WIDTH
Integer
4
0
0
FULL_NAME
FULL_NAME
String
100
0
0
Shape_STLe
Shape_STLe
Double
8
0
0
CoordinatesX
X Coor
Single
4
0
0
CoordinatesY
Y Coor
Single
4
0
0
XYCombined
X, Y Comabo
String
255
0
0
JoinNum
JoinNum
SmallInteger
2
0
0
BUFF_DIST
BUFF_DIST
Double
8
0
0
ORIG_FID_1
ORIG_FID
Integer
4
0
0
sum_WeightedCrash
Sum WeightedCrash
Double
8
0
0
Point_Count
Count of Points
Integer
4
0
0
GEOID
GEOID
GUID
38
0
0
BufferIndex
Buffer Index Code
SmallInteger
2
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.
20241018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