<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<metadata xml:lang="en">
<Esri>
<CreaDate>20171107</CreaDate>
<CreaTime>10490800</CreaTime>
<ArcGISFormat>1.0</ArcGISFormat>
<SyncOnce>TRUE</SyncOnce>
<DataProperties>
<itemProps>
</itemProps>
</DataProperties>
</Esri>
<dataIdInfo>
<idAbs>Panchromatic Landsat GLS image service created from the Global Land Survey (GLS) data from epochs 2000, 2005 &amp; 2010. GLS datasets are created by the United States Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA) using Landsat images. This service includes imagery from Landsat 4, Landsat 5 TM and Landsat 7 ETM, at 15 meter resolution. Using on-the-fly processing, the raw DN values are transformed to scaled (0 - 10000) apparent reflectance values and then different enhancement renderings are applied.</idAbs>
<searchKeys>
<keyword>Pan</keyword>
<keyword> Panchromatic</keyword>
<keyword> GLS</keyword>
<keyword> Landsat</keyword>
<keyword> imagery</keyword>
<keyword> temporal</keyword>
</searchKeys>
<idPurp>Landsat GLS 15m Panchromatic images, including various selectable functions with different enhancement renderings.
</idPurp>
<idCredit>Esri, USGS, AWS, NASA</idCredit>
<resConst>
<Consts>
<useLimit>This work is licensed under the Esri Master License Agreement.</useLimit>
</Consts>
</resConst>
<idCitation>
<resTitle>Pan</resTitle>
</idCitation>
</dataIdInfo>
<Binary>
<Thumbnail>
<Data EsriPropertyType="PictureX">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</Data>
</Thumbnail>
</Binary>
</metadata>
