20210318
18303000
1.0
FALSE
arcgis_geodatabase.sde.WCMC015_SeagrassRichness2003_v1
Server=10.2.1.241; Service=sde:postgresql:10.2.1.241; Database=arcgis_geodatabase; User=sde; Version=sde.DEFAULT
ArcSDE Connection
002
-180.000015
181.833346
-48.666655
67.395175
1
Geographic
GCS_WGS_1984
Angular Unit: Degree (0.017453)
<GeographicCoordinateSystem xsi:type='typens:GeographicCoordinateSystem' 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/2.7.0'><WKT>GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433],AUTHORITY["EPSG",4326]]</WKT><XOrigin>-400</XOrigin><YOrigin>-400</YOrigin><XYScale>1111948722.2222219</XYScale><ZOrigin>0</ZOrigin><ZScale>1</ZScale><MOrigin>0</MOrigin><MScale>1</MScale><XYTolerance>8.983152841195215e-09</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><LeftLongitude>-180</LeftLongitude><WKID>4326</WKID><LatestWKID>4326</LatestWKID></GeographicCoordinateSystem>
CopyFeatures o:\f00_data\WCMC-015-GlobalSeagrassRichness2003\DownloadPack-WCMC015_SeagrassRichness2003_v1\01_Data\14_001_WCMC015_SeagrassRichness2003_v1.shp "C:\Users\Florencia\Documents\ArcGIS\Projects\Data Management\InternalPortal.sde\arcgis_geodatabase.sde.T14_001_WCMC015_SeagrassRichness2003_v1" # # # #
Rename "C:\Users\Florencia\Documents\ArcGIS\Projects\Data Management\InternalPortal.sde\arcgis_geodatabase.sde.T14_001_WCMC015_SeagrassRichness2003_v1" "C:\Users\Florencia\Documents\ArcGIS\Projects\Data Management\InternalPortal.sde\arcgis_geodatabase.sde.WCMC015_SeagrassRichness2003_v1" FeatureClass
20210318
19003700
20210318
19003700
1616093683439r6300951833842291
dataset
2021-03-18
Enterprise Geodatabase Feature Class
WCMC015_SeagrassRichness2003_v1
This dataset shows the global distribution of seagrass species richness, or global seagrass biodiversity.<br /><br />The boundaries do not represent actual ranges as seagrass are distributed in waters shallow enough for sunlight to penetrate. No surface area calculations should be attempted.
This dataset shows the global distribution of seagrass species richness, or global seagrass biodiversity
Green EP, Short FT (2003). World atlas of seagrasses. Prepared by UN Environment
World Conservation Monitoring Centre. Berkeley (California, USA): University of
California. 332 pp. URL: https://archive.org/details/worldatlasofseag03gree Data DOI: https://doi.org/10.34892/2dc6-1y45
Esri ArcGIS 12.7.0.26828
unep-wcmc
coastal
marine
blue carbon
seagrass
habitat
biodiversity
species richness
-180.000014624675
181.833345580035
-48.6666553748456
67.3951751770929
<p><a href='https://www.unep-wcmc.org/policies/general-data-license-excluding-wdpa#data_policy' target='_blank'><span style='mso-ansi-language:EN-GB'>UNEP-WCMC
General Data License (excluding WDPA)</span></a></p>
1
-180.000015
181.833346
67.395175
-48.666655
3709
EPSG
6.2(3.0.1)
T14_001_WCMC015_SeagrassRichness2003_v1
Feature Class
0
objectid
objectid
Internal feature number.
Esri
OID
4
10
0
Sequential unique whole numbers that are automatically generated.
id
id
Double
8
38
8
gridcode
gridcode
Double
8
38
8
st_area_sh
st_area_sh
Double
8
38
8
st_length_
st_length_
Double
8
38
8
st_area__1
st_area__1
Double
8
38
8
st_length1
st_length1
Double
8
38
8
shape
shape
Feature geometry.
Esri
Geometry
8
0
0
Coordinates defining the features.
st_area(shape)
st_area(shape)
Double
0
0
0
st_length(shape)
st_length(shape)
Double
0
0
0
Simple
FALSE
3709
TRUE
FALSE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