<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<metadata xml:lang="en">
<Esri>
<CreaDate>20230718</CreaDate>
<CreaTime>18503000</CreaTime>
<ArcGISFormat>1.0</ArcGISFormat>
<SyncOnce>TRUE</SyncOnce>
<MapLyrSync>TRUE</MapLyrSync>
</Esri>
<dataIdInfo>
<idCitation>
<resTitle>EDW_PADUS_01</resTitle>
</idCitation>
<idAbs>A map service on the www depicting protected areas for the US. This data is intended for read-only use. The PAD-US feature classes were developed by the Forest Service for submission to the Protected Areas Database of the United States (PAD-US). It is the official inventory of public parks and other protected open space. With more than 3 billion acres in 150,000 holdings, the spatial data in PAD-US represents public lands held in trust by thousands of national, State and regional/local governments, as well as non-profit conservation organizations. PAD-US is published by the U.S. Geological Survey Gap Analysis Program (GAP). GAP produces data and tools that help meet critical national challenges such as biodiversity, conservation, recreation, public health, climate change adaptation, and infrastructure investment. USFS PAD-US data is pulled weekly from USFS Lands data. This dataset is more current than the combined annual update of PAD-US from USGS GAP. &lt;a href='https://data.fs.usda.gov/geodata/edw/datasets.php?xmlKeyword=padus'&gt;PADUS Metadata&lt;/a&gt;</idAbs>
<searchKeys>
<keyword>PADUS</keyword>
<keyword>Protected Areas Database</keyword>
<keyword>Proclamation</keyword>
<keyword>Designation</keyword>
<keyword>Easement</keyword>
<keyword>Fee</keyword>
<keyword>NFS Lands</keyword>
<keyword>USDA Forest Service</keyword>
<keyword>ALP Land Dataset</keyword>
<keyword>Land Status</keyword>
</searchKeys>
<idPurp>PADUS</idPurp>
<idCredit>US Forest Service Enterprise Map Services Program</idCredit>
<resConst>
<Consts>
<useLimit/>
</Consts>
</resConst>
</dataIdInfo>
<Binary>
<Thumbnail>
<Data EsriPropertyType="PictureX">iVBORw0KGgoAAAANSUhEUgAAASwAAADICAYAAABS39xVAAAAAXNSR0IB2cksfwAAAAlwSFlzAAAO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</Data>
</Thumbnail>
</Binary>
</metadata>
