<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<metadata xml:lang="en">
<Esri>
<CreaDate>20260827</CreaDate>
<CreaTime>11194400</CreaTime>
<ArcGISFormat>1.0</ArcGISFormat>
<SyncOnce>TRUE</SyncOnce>
<scaleRange>
<minScale>150000000</minScale>
<maxScale>5000</maxScale>
</scaleRange>
</Esri>
<dataIdInfo>
<placeKeys>
<thesaName>
<resTitle>BLM-STATE</resTitle>
</thesaName>
<keyword>Colorado</keyword>
</placeKeys>
<themeKeys>
<thesaName>
<resTitle>BLM-THEME</resTitle>
</thesaName>
<keyword>Geospatial</keyword>
<keyword>Management</keyword>
</themeKeys>
<themeKeys>
<thesaName>
<resTitle>NONE</resTitle>
</thesaName>
<keyword>BLM</keyword>
<keyword>Bureau of Land Management</keyword>
<keyword>Department of the Interior</keyword>
<keyword>DOI</keyword>
<keyword>GTLF</keyword>
<keyword>roads</keyword>
<keyword>routes</keyword>
<keyword>trails</keyword>
</themeKeys>
<idCitation>
<resTitle>BLM Colorado Ground Transportation Linear Features Lines Routes</resTitle>
</idCitation>
<searchKeys>
<keyword>BLM</keyword>
<keyword>Bureau of Land Management</keyword>
<keyword>Colorado</keyword>
<keyword>Department of the Interior</keyword>
<keyword>DOI</keyword>
<keyword>Geospatial</keyword>
<keyword>GTLF</keyword>
<keyword>Management</keyword>
<keyword>roads</keyword>
<keyword>routes</keyword>
<keyword>trails</keyword>
<keyword>transportation</keyword>
</searchKeys>
<idPurp>The purpose of the GTLF data standard is to help support the BLM mission in a wide spectrum of subject areas. The GTLF data standard will also provide BLM programs with a better understanding of the impact of transportation on their programs. The national GTLF standard allows for the capture of data from the Travel Management Plan (TMP) as well as from observed route usage.</idPurp>
<idAbs>&lt;div style='text-align:Left;font-size:12pt'&gt;&lt;p&gt;&lt;span&gt;A national BLM GTLF data standard is essential for collecting the landscape-scale data necessary to identify management opportunities and challenges that may not be evident when managing smaller land areas. GTLF data not only serve the crucial function of improving BLM transportation planning, but is also invaluable to numerous other BLM programs affected by transportation (e.g. water and air quality, wildlife habitat fragmentation, engineering, realty, cultural resources).&lt;/span&gt;&lt;/p&gt;&lt;/div&gt;</idAbs>
<idCredit>BLM Colorado</idCredit>
<resConst>
<Consts>
<useLimit>These data are provided by Bureau of Land Management (BLM) 'as is' and might contain errors or omissions. The User assumes the entire risk associated with its use of these data and bears all responsibility in determining whether these data are fit for the User's intended use. The information contained in these data is dynamic and may change over time. The data are not better than the sources from which they were derived, and both scale and accuracy may vary across the data set. These data might not have the accuracy, resolution, completeness, timeliness, or other characteristics appropriate for applications that potential users of the data may contemplate. The User is encouraged to carefully consider the content of the metadata file associated with these data. These data are neither legal documents nor land surveys, and must not be used as such. Official records may be referenced at most BLM offices. Please report any errors in the data to the BLM office from which it was obtained. The BLM should be cited as the data source in any products derived from these data. Any Users wishing to modify the data should describe the types of modifications they have performed. The User should not misrepresent the data, nor imply that changes made were approved or endorsed by BLM. This data may be updated by the BLM without notification.</useLimit>
</Consts>
</resConst>
<resConst>
<LegConsts>
<useLimit>The BLM assumes no responsibility for errors or omissions. No warranty is made by the BLM as to the accuracy, reliability, or completeness of these data for individual use or aggregate use with other data; nor shall the act of distribution to contractors, partners, or beyond, constitute any such warranty for individual or aggregate data use with other data. Although these data have been processed successfully on computers of BLM, no warranty, expressed or implied, is made by BLM regarding the use of these data on any other system, or for general or scientific purposes, nor does the fact of distribution constitute or imply any such warranty. In no event shall the BLM have any liability whatsoever for payment of any consequential, incidental, indirect, special, or tort damages of any kind, including, but not limited to, any loss of profits arising out of the use or reliance on the geographic data or arising out of the delivery, installation, operation, or support by BLM.</useLimit>
<othConsts>None, these data are considered public domain.</othConsts>
</LegConsts>
</resConst>
<tpCat>
<TopicCatCd value="018">
</TopicCatCd>
</tpCat>
</dataIdInfo>
<Binary>
<Thumbnail>
<Data EsriPropertyType="PictureX">iVBORw0KGgoAAAANSUhEUgAAASwAAADICAYAAABS39xVAAAAAXNSR0IB2cksfwAAAAlwSFlzAAAO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</Data>
</Thumbnail>
</Binary>
<mdHrLv>
<ScopeCd value="005">
</ScopeCd>
</mdHrLv>
<mdDateSt Sync="TRUE">20260910</mdDateSt>
</metadata>
