<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<metadata xml:lang="en">
<Esri>
<CreaDate>20260304</CreaDate>
<CreaTime>20570100</CreaTime>
<ArcGISFormat>1.0</ArcGISFormat>
<SyncOnce>TRUE</SyncOnce>
<MapLyrSync>TRUE</MapLyrSync>
</Esri>
<dataIdInfo>
<idCitation>
<resTitle>UndisturbedLands</resTitle>
</idCitation>
<idAbs>SDSU employed simple GIS methods primarily utilizing the South Dakota Farm Service Agency’s Common Land Unit (CLU) data layers from 2013, along with 2012 US Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) county mosaic aerial imagery, to evaluate approximately 22.6 million acres of land in the 44 counties that comprise eastern South Dakota. Mapping of this total project area was done in three distinct project phases from 2014 through 2016. We utilized the CLU data layer, queried to show current and former cropland, to first identify and remove any areas with a cropping history, regardless of current land use. We then employed a step by step analysis to analyze the remaining land in approximately one mi2 sections in order to identify and remove additional historic or current land disturbances. The remaining land tracts were then categorized as potentially ‘undisturbed grassland’ or ‘undisturbed woodland’ by simple reason of deduction. Finally, we removed all known water bodies larger than 40 acres as defined by the South Dakota Department of Game, Fish, and Parks’ (SDGFP) Statewide Water Bodies layer in order to gain a more accurate interpretation of the remaining undisturbed grassland/wetland complex.
Downloaded from https://openprairie.sdstate.edu/ --&gt; search Bauman, undisturbed</idAbs>
<searchKeys>
<keyword>ERT</keyword>
</searchKeys>
<idPurp>Potentially Undisturbed Lands for use within the ERT.</idPurp>
<idCredit>SDSU</idCredit>
<resConst>
<Consts>
<useLimit/>
</Consts>
</resConst>
</dataIdInfo>
<Binary>
<Thumbnail>
<Data EsriPropertyType="PictureX">/9j/4AAQSkZJRgABAQEAAAAAAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a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=
</Data>
</Thumbnail>
</Binary>
</metadata>
