20241211
11570200
FALSE
all_lines_cleaned
002
Projected
GCS_GRS 1980(IUGG, 1980)
Linear Unit: Foot_US (0.304801)
Lambert_Conformal_Conic
<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["Lambert_Conformal_Conic",GEOGCS["GCS_GRS 1980(IUGG, 1980)",DATUM["D_unknown",SPHEROID["GRS80",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic"],PARAMETER["false_easting",1640416.666666667],PARAMETER["false_northing",0.0],PARAMETER["central_meridian",-120.5],PARAMETER["standard_parallel_1",45.83333333333334],PARAMETER["standard_parallel_2",47.33333333333334],PARAMETER["latitude_of_origin",45.33333333333334],UNIT["Foot_US",0.3048006096012192]]</WKT><XOrigin>-117498300</XOrigin><YOrigin>-98850300</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></ProjectedCoordinateSystem>
20240627
16140100
20240627
16140100
150000000
5000
1.0
ItemDescription
Esri ArcGIS 12.9.10.32739
all_lines_cleaned
This is a DRAFT of linear extent features to synthesize kelp data records across the state
linearextent
kelp
File Geodatabase Feature Class
dataset
0
Simple
FALSE
0
TRUE
FALSE
all_lines_cleaned
Feature Class
0
Shape
Shape
Geometry
0
0
0
Feature geometry.
Esri
Coordinates defining the features.
SITE_CODE
SITE_CODE
String
15
0
0
OBJECTID
OBJECTID_1
OID
4
0
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
Shape_Length
Shape_Length
Double
8
0
0
Length of feature in internal units.
Esri
Positive real numbers that are automatically generated.
20240627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