<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<metadata xml:lang="en">
<Esri>
<CreaDate>20260910</CreaDate>
<CreaTime>13033600</CreaTime>
<ArcGISFormat>1.0</ArcGISFormat>
<SyncOnce>TRUE</SyncOnce>
</Esri>
<dataIdInfo>
<idCitation>
<resTitle>BLM ID Range Improvement Line</resTitle>
</idCitation>
<searchKeys>
<keyword>biota</keyword>
<keyword>BLM</keyword>
<keyword>Boise District Office</keyword>
<keyword>Bruneau Field Office</keyword>
<keyword>Bureau of Land Management</keyword>
<keyword>Burley Field Office</keyword>
<keyword>Challis Field Office</keyword>
<keyword>Department of the Interior</keyword>
<keyword>DOI</keyword>
<keyword>farming</keyword>
<keyword>Four Rivers Field Office</keyword>
<keyword>ID</keyword>
<keyword>Idaho</keyword>
<keyword>Idaho Falls District Office</keyword>
<keyword>inlandWaters</keyword>
<keyword>Jarbidge Field Office</keyword>
<keyword>Management</keyword>
<keyword>Nevada</keyword>
<keyword>NV</keyword>
<keyword>Owyhee Field Office</keyword>
<keyword>Pocatello Field Office</keyword>
<keyword>Range</keyword>
<keyword>range improvement</keyword>
<keyword>Range Improvement Project System</keyword>
<keyword>RIPS</keyword>
<keyword>Salmon Field Office</keyword>
<keyword>Shoshone Field Office</keyword>
<keyword>structure</keyword>
<keyword>Twin Falls District Office</keyword>
<keyword>United States</keyword>
<keyword>Upper Snake Field Office</keyword>
<keyword>US</keyword>
<keyword>UT</keyword>
<keyword>Utah</keyword>
<keyword>Vegetation</keyword>
<keyword>Wildlife</keyword>
</searchKeys>
<idPurp>To show the location of range improvements on BLM-managed lands in Idaho. Currently, the line feature class has some data for all of the BLM field offices except the Coeur d'Alene and Cottonwood field offices. The intended use of all data in the BLM's GIS library is to support diverse activities including planning, management, maintenance, research, and interpretation.</idPurp>
<idAbs>&lt;div style='text-align:Left;font-size:12pt'&gt;&lt;div&gt;&lt;div&gt;&lt;p&gt;&lt;span&gt;This geodatabase of point, line and polygon features is an effort to consolidate all of the range improvement locations on BLM-managed land in Idaho into one database. Currently, the line feature class has some data for all of the BLM field offices except the Coeur d'Alene and Cottonwood field offices. Range improvements are structures intended to enhance rangeland resources, including wildlife, watershed, and livestock management. Examples of range improvements include water troughs, spring headboxes, culverts, fences, water pipelines, gates, wildlife guzzlers, artificial nest structures, reservoirs, developed springs, corrals, exclosures, etc. These structures were first tracked by the Bureau of Land Management (BLM) in the Job Documentation Report (JDR) System in the early 1960s, which was predominately a paper-based tracking system. In 1988 the JDRs were migrated into and replaced by the automated Range Improvement Project System (RIPS), and version 2.0 is currently being used today. It tracks inventory, status, objectives, treatment, maintenance cycle, maintenance inspection, monetary contributions and reporting. Not all range improvements are documented in the RIPS database; there may be some older range improvements that were built before the JDR tracking system was established. There also may be unauthorized projects that are not in RIPS. Official project files of paper maps, reports, NEPA documents, checklists, etc., document the status of each project and are physically kept in the office with management authority for that project area. In addition, project data is entered into the RIPS system to enable managers to access the data to track progress, run reports, analyze the data, etc. Before Geographic Information System technology most offices kept paper atlases or overlay systems that mapped the locations of the range improvements. The objective of this geodatabase is to migrate the location of historic range improvement projects into a GIS for geospatial use with other data and to centralize the range improvement data for the state. This data set is a work in progress and does not have all range improvement projects that are on BLM lands. Some field offices have not migrated their data into this database, and others are partially completed. New projects may have been built but have not been entered into the system. Historic or unauthorized projects may not have case files and are being mapped and documented as they are found. Many field offices are trying to verify the locations and status of range improvements with GPS, and locations may change or projects that have been abandoned or removed on the ground may be deleted. Attributes may be incomplete or inaccurate. This data was created using the standard for range improvements set forth in Idaho IM 2009-044, dated 6/30/2009. However, it does not have all of the fields the standard requires. Fields that are missing from the line feature class that are in the standard are: ALLOT_NO, MGMT_AGCY, ADMIN_ST, ADMIN_OFF, SRCE_AGCY, MAX_PDOP, MAX_HDOP, CORR_TYPE, RCVR_TYPE, GPS_TIME, UPDATE_STA, UNFILT_POS, FILT_POS, DATA_DICTI, GPS_LENGTH, GPS_3DLGTH, AVE_VERT_P, AVE_HORZ_P, WORST_VERT, WORST_HORZ and CONF_LEVEL. Several additional fields have been added that are not part of the standard: top_fence, btm_fence, admin_fo_line and year_checked. There is no National BLM standard for GIS range improvement data at this time. For more information contact us at blm_id_stateoffice@blm.gov.&lt;/span&gt;&lt;/p&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;</idAbs>
<idCredit>Bureau of Land Management (BLM), Idaho State Office</idCredit>
<resConst>
<Consts>
<useLimit>&lt;div style='text-align:Left;font-size:12pt'&gt;&lt;div&gt;&lt;div&gt;&lt;p&gt;&lt;span&gt;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.&lt;/span&gt;&lt;/p&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;</useLimit>
</Consts>
</resConst>
</dataIdInfo>
<Binary>
<Thumbnail>
<Data EsriPropertyType="PictureX">iVBORw0KGgoAAAANSUhEUgAAASwAAADICAYAAABS39xVAAAAAXNSR0IB2cksfwAAAAlwSFlzAAAO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</Data>
</Thumbnail>
</Binary>
</metadata>
