20210224
09372000
1.0
ISO 19139 Metadata Implementation Specification
FALSE
IMA_GIS.DBO.Toba_IMA_202101_pWGS84_2019_Litoral_Data_Tobago_2011_2015
002
735784.000000
769725.000000
1232530.000000
1252593.000000
1
0.001
Server=imaarcgis; Service=sde:sqlserver:imaarcgis\sqlexpress; Database=IMA_GIS; Version=dbo.DEFAULT
ArcSDE Connection
Projected
GCS_WGS_1984
Linear Unit: Meter (1.000000)
WGS_1984_UTM_Zone_20N
<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["WGS_1984_UTM_Zone_20N",GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-63.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0],AUTHORITY["EPSG",32620]]</WKT><XOrigin>-5120900</XOrigin><YOrigin>-9998100</YOrigin><XYScale>10000</XYScale><ZOrigin>0</ZOrigin><ZScale>1</ZScale><MOrigin>0</MOrigin><MScale>1</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>32620</WKID><LatestWKID>32620</LatestWKID></ProjectedCoordinateSystem>
FeatureClassToFeatureClass C:\GEODATA\01_Data\01_GIS\03_Hydrosphere\Physical\Waves\202101_Toba_IMA_pWGS84_Litoral_Data_Tobago_2011_2015.shp "C:\ArcPro Projects\IMA GIS\webadmin@IMA_GIS@imaarcgis.sde" Toba_IMA_202101_pWGS84_2019_Litoral_Data_Tobago_2011_2015 # "stn_id "stn_id" true true false 16 Double 6 15,First,#,C:\GEODATA\01_Data\01_GIS\03_Hydrosphere\Physical\Waves\202101_Toba_IMA_pWGS84_Litoral_Data_Tobago_2011_2015.shp,stn_id,-1,-1;stn_desc "stn_desc" true true false 254 Text 0 0,First,#,C:\GEODATA\01_Data\01_GIS\03_Hydrosphere\Physical\Waves\202101_Toba_IMA_pWGS84_Litoral_Data_Tobago_2011_2015.shp,stn_desc,0,254;accu "accu" true true false 254 Text 0 0,First,#,C:\GEODATA\01_Data\01_GIS\03_Hydrosphere\Physical\Waves\202101_Toba_IMA_pWGS84_Litoral_Data_Tobago_2011_2015.shp,accu,0,254;POINT_X "POINT_X" true true false 19 Double 0 0,First,#,C:\GEODATA\01_Data\01_GIS\03_Hydrosphere\Physical\Waves\202101_Toba_IMA_pWGS84_Litoral_Data_Tobago_2011_2015.shp,POINT_X,-1,-1;POINT_Y "POINT_Y" true true false 19 Double 0 0,First,#,C:\GEODATA\01_Data\01_GIS\03_Hydrosphere\Physical\Waves\202101_Toba_IMA_pWGS84_Litoral_Data_Tobago_2011_2015.shp,POINT_Y,-1,-1;WH_Mean "WH_Mean" true true false 16 Double 6 15,First,#,C:\GEODATA\01_Data\01_GIS\03_Hydrosphere\Physical\Waves\202101_Toba_IMA_pWGS84_Litoral_Data_Tobago_2011_2015.shp,WH_Mean,-1,-1;WH_Rng "WH_Rng" true true false 254 Text 0 0,First,#,C:\GEODATA\01_Data\01_GIS\03_Hydrosphere\Physical\Waves\202101_Toba_IMA_pWGS84_Litoral_Data_Tobago_2011_2015.shp,WH_Rng,0,254;WH_STD "WH_STD" true true false 16 Double 6 15,First,#,C:\GEODATA\01_Data\01_GIS\03_Hydrosphere\Physical\Waves\202101_Toba_IMA_pWGS84_Litoral_Data_Tobago_2011_2015.shp,WH_STD,-1,-1;WH_Dir "WH_Dir" true true false 254 Text 0 0,First,#,C:\GEODATA\01_Data\01_GIS\03_Hydrosphere\Physical\Waves\202101_Toba_IMA_pWGS84_Litoral_Data_Tobago_2011_2015.shp,WH_Dir,0,254;BH_Mean "BH_Mean" true true false 16 Double 6 15,First,#,C:\GEODATA\01_Data\01_GIS\03_Hydrosphere\Physical\Waves\202101_Toba_IMA_pWGS84_Litoral_Data_Tobago_2011_2015.shp,BH_Mean,-1,-1;BH_Rng "BH_Rng" true true false 254 Text 0 0,First,#,C:\GEODATA\01_Data\01_GIS\03_Hydrosphere\Physical\Waves\202101_Toba_IMA_pWGS84_Litoral_Data_Tobago_2011_2015.shp,BH_Rng,0,254;BH_STD "BH_STD" true true false 16 Double 6 15,First,#,C:\GEODATA\01_Data\01_GIS\03_Hydrosphere\Physical\Waves\202101_Toba_IMA_pWGS84_Litoral_Data_Tobago_2011_2015.shp,BH_STD,-1,-1;BP_Mean "BP_Mean" true true false 16 Double 6 15,First,#,C:\GEODATA\01_Data\01_GIS\03_Hydrosphere\Physical\Waves\202101_Toba_IMA_pWGS84_Litoral_Data_Tobago_2011_2015.shp,BP_Mean,-1,-1;BP_Rng "BP_Rng" true true false 254 Text 0 0,First,#,C:\GEODATA\01_Data\01_GIS\03_Hydrosphere\Physical\Waves\202101_Toba_IMA_pWGS84_Litoral_Data_Tobago_2011_2015.shp,BP_Rng,0,254;BP_STD "BP_STD" true true false 16 Double 6 15,First,#,C:\GEODATA\01_Data\01_GIS\03_Hydrosphere\Physical\Waves\202101_Toba_IMA_pWGS84_Litoral_Data_Tobago_2011_2015.shp,BP_STD,-1,-1;ID "ID" true true false 16 Double 6 15,First,#,C:\GEODATA\01_Data\01_GIS\03_Hydrosphere\Physical\Waves\202101_Toba_IMA_pWGS84_Litoral_Data_Tobago_2011_2015.shp,ID,-1,-1" #
20220913
18303900
20220913
18303900
Microsoft Windows Server 2016 Technical Preview Version 10.0 (Build 17763) ; Esri ArcGIS 12.9.3.32739
Litoral_Data_Tobago_2011_2015
1
-60.841109
-60.528983
11.323234
11.139522
litoral
funfamental data
waterbodies
Shows the litoral data of Tobago between 2011 - 2015
Enterprise Geodatabase Feature Class
0.001
dataset
EPSG
9.8.8(3.0.1)
0
Simple
FALSE
0
TRUE
FALSE
IMA_GIS.DBO.Toba_IMA_202101_pWGS84_2019_Litoral_Data_Tobago_2011_2015
Feature Class
0
OBJECTID
OBJECTID
OID
4
10
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
Shape
Shape
Geometry
8
0
0
Feature geometry.
Esri
Coordinates defining the features.
stn_id
stn_id
Double
8
15
6
stn_desc
stn_desc
String
254
0
0
accu
accu
String
254
0
0
POINT_X
POINT_X
Double
8
38
8
POINT_Y
POINT_Y
Double
8
38
8
WH_Mean
WH_Mean
Double
8
15
6
WH_Rng
WH_Rng
String
254
0
0
WH_STD
WH_STD
Double
8
15
6
WH_Dir
WH_Dir
String
254
0
0
BH_Mean
BH_Mean
Double
8
15
6
BH_Rng
BH_Rng
String
254
0
0
BH_STD
BH_STD
Double
8
15
6
BP_Mean
BP_Mean
Double
8
15
6
BP_Rng
BP_Rng
String
254
0
0
BP_STD
BP_STD
Double
8
15
6
ID
ID
Double
8
15
6
20220913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