SheepTrailing_Line
2253396.994800
2695700.950400
1200001.824200
1505496.688200
1
002
Projected
GCS_North_American_1983
Linear Unit: Meter (1.000000)
NAD_1983_Idaho_TM
<ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.5.0'><WKT>PROJCS["NAD_1983_Idaho_TM",GEOGCS["GCS_North_American_1983",DATUM["D_North_American_1983",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",2500000.0],PARAMETER["False_Northing",1200000.0],PARAMETER["Central_Meridian",-114.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",42.0],UNIT["Meter",1.0],AUTHORITY["EPSG",8826]]</WKT><XOrigin>-3120900</XOrigin><YOrigin>-13447900</YOrigin><XYScale>10000</XYScale><ZOrigin>0</ZOrigin><ZScale>1</ZScale><MOrigin>0</MOrigin><MScale>1</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>102605</WKID><LatestWKID>8826</LatestWKID></ProjectedCoordinateSystem>
20260914
13255800
20260914
13280100
20260827
16185400
1.0
FALSE
150000000
5000
dataset
State Data Administrator
U.S. Department of the Interior (DOI), Bureau of Land Management (BLM), Idaho State Office, Engineering and Geographic Sciences
State Data Administrator
208-373-4000
1387 South Vinnell Way
Boise
Idaho
83709-1657
US
blm_id_stateoffice@blm.gov
7:45 A.M. - 4:15 P.M., Mountain Time, Monday - Friday
20260914
ArcGIS Metadata
1.0
https://gbp-blm-egis.hub.arcgis.com/pages/idaho
Enterprise Geodatabase Feature Class
State Data Administrator
U.S. Department of the Interior (DOI), Bureau of Land Management (BLM), Idaho State Office, Engineering and Geographic Sciences
State Data Administrator
208-373-4000
1387 South Vinnell Way
Boise
Idaho
83709-1657
US
blm_id_stateoffice@blm.gov
7:45 A.M. - 4:15 P.M., Mountain Time, Monday - Friday
Name: State Data Administrator
Organization: U.S. Department of the Interior (DOI), Bureau of Land Management (BLM), Idaho State Office, Engineering and Geographic Sciences
Position: State Data Administrator
Role: Point of Contact
A-Z Index of U. S. Government Departments and Agencies
BLM
Bureau of Land Management
Department of the Interior
DOI
BLM-STATE
Idaho
BLM-THEME
Authorization
Management
Range
Bureau of Land Management Administrative Codes
Idaho State Office
ISO
National Geospatial-Intelligence Agency (NGA), Geopolitical Codes (Formerly Federal Information Processing Standard 10-4)
United States
US
USA
NONE
allotment
goat
grazing
pasture
sheep
1
-117.113105
-111.528807
44.750844
41.961433
BLM ID Sheep Trailing Routes Line
2022-05-05
One
U.S. Department of the Interior, Bureau of Land Management (BLM)
Bureau of Land Management
1387 South Vinnell Way, Boise, Idaho, 83709-1657, UNITED STATES
vector digital data
<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>This polygon feature class contains Bureau of Land Management (BLM) Idaho allotments and pastures that are categorized as having an authorization for trailing of goats or sheep in the BLM Rangeland Administration System (RAS) database. At the time of this RAS download (2010) there was no entry in RAS for the selection of Goat, only for sheep. A pasture is a sub-unit of a grazing allotment, each allotment is comprised of at least one pasture. In some cases, this layer identifies the BLM managed public land or other land associated with specific grazing allotments administered by the local BLM field office. Boundaries may be fences, arbitrary lines, or natural barriers. Agency management of polygons within this feature class is not specific to BLM; other agencies are also included. For more information contact us at blm_id_infoaccesscenter@blm.gov.</SPAN></P></DIV></DIV></DIV>
This feature class supports WO IM2010-011 requesting information to develop a GIS decision support tool for domestic sheep and goat management in wild sheep habitat. This Instruction Memorandum (IM) and Attachment 1 are included as enclosures to this metadata file. This data displays the linear overland routes taken to move domestic sheep between BLM allotments. It will aid in the administration of these grazing allotments under the Bureau of Land Management's grazing program, and also in scientific, integrated land use planning or other activities that would affect, or be affected by, livestock grazing. Additionally, it provides a visual display of the grazing allotment boundaries for base map production.
Rangeland Program Lead
Bureau of Land Management (BLM), Idaho State Office
Rangeland Program Lead
208-373-4000
1387 South Vinnell Way
Boise
Idaho
83709
US
id_so_information@blm.gov
7:45 A.M. - 4:15 P.M., Mountain Time, Monday - Friday
allotment
Authorization
biota
BLM
boundaries
Bureau of Land Management
Department of the Interior
DOI
goat
grazing
Idaho
Idaho State Office
ISO
Management
pasture
Range
sheep
United States
US
USA
<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>These data are provided by the 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.</SPAN></P></DIV></DIV></DIV>
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.
None, these data are considered public domain.
Esri ArcGIS 10.4.1.5686
true
-117.113105
-111.528807
44.750844
41.961433
publication date
2011-06-15
Bureau of Land Management (BLM), Idaho State Office
Last metadata review date: 20220505
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.
RAS does not contain a complete and correct listing of pasture numbers, as such pasture numbers are incomplete.
This document describes the national data standard for the Grazing Boundaries geospatial dataset. It is intended as a guideline for implementation. States may extend and expand upon this guideline in order to meet their specific needs, provided that when the data is pushed up to the national level, it will meet the minimum requirements as set forth in the Data Standard. The arc information and the feature level metadata will exist in the arc feature class. The Allotment information will exist within the Pastures dataset and as such the Allotments spatial dataset will be a derived product from Pastures.
The attribute data required is minimal, as the majority of the analysis information will come from the RAS database. The attribute ST_ALLOT_PAST in the ‘gra_past_poly’ table will serve as the unique national identifier that will allow connection to the existing RAS database.
The data for inclusion in this data set shall be collected in a known datum and coordinate system. The data stored on the EGIS server in Denver shall be stored in geographic coordinates for national layers using the Bureau standard NAD 83 datum rather than in a specific projection.
There are four tables in this implementation:
1. gra_past_arc represents the arc features that will define the polygons. These arcs will have the feature level metadata attributes shown assigned to them.
2. gra_past_poly represents the polygon features that show the boundaries for the pastures.
3. gra_allot_poly represents the polygon features that show the boundaries for the allotments.
4. gra_hist_allot_poly represents the polygon features that show historical allotments. Since the data in the RAS system is about allotments and pastures, where they are used, this is where the data connection between the geospatial feature data and the RAS application will be established.
This data is assumed to be correct, though no completeness tests were performed. Errors by omission and generalization may be present.
Data entry was performed using GPS data, comparison to DRG and NAIP imagery. Every effort was made to make the data accurate.
IDAHO BUREAU OF LAND MANAGEMENT FORM ID-9167 GEOSPATIAL DATA QUALITY ASSURANCE /QUALITY CONTROL AUTHORIZATION PAGE " GENERAL INFORMATION ABOUT THE DATASET
Full name of dataset: GoatSheepTrailing_INT_100K_POLY_2009 This verification covers data edits up to and including the following date:_9/2/2009 Purpose for review: Review of current BLM domestic sheep trailing routes.
2008-04-28
GIS Specialist
BLM Idaho State Office
GIS Specialist
208-373-4000
1387 S Vinnell Way
Boise
ID
83709
US
blm_id_stateoffice@blm.gov
IM 2010-011, Information Request for GIS Data on Domestic Sheep and Goats
UNITED STATES DEPARTMENT OF THE INTERIOR BUREAU OF LAND MANAGEMENT WASHINGTON, D.C. 20240 October 23, 2009 Excerpt from Attachment 1 - Gathering Spatial and Tabular Data:
This document describes what spatial and tabular data to be gathered, the final assembly standard, and the submission method. This includes direction on the creation of the GIS sheep feature classes and use of the RAS tabular data provided. With a join between the GIS spatial data and the RAS tabular data, the user will be able to identify spatially those allotments or pastures that meet the RAS ‘Sheep’ or ‘Goat’ criteria of this data request.
This document does not describe in detail how the GIS spatial data and the RAS tabular data will be assembled. There are many different ways to achieve the same results, so it will be left to the states to determine the best work flow to meet this standard. If there are questions on how to assemble the data to meet these standards, the states can contact either John Courtright, Idaho State Office, 208-373-3966 or John Reitsma at 303-236-1984.
STEP 1. Generation of the GIS spatial data.
FEATURE CLASS NAMING STANDARDS:
The GIS data consists of three feature classes:
RANGE_Sheep_Pasture_POLY
Includes all allotments or pastures as polygons that meet the criteria as ‘SHEEP’ or ‘GOAT’.
RANGE_Sheep_Trailing_POLY
Includes all allotments or pastures as polygons that are used to trail sheep or goats between other allotments or pastures.
RANGE_Sheep_Trailing_LINE
Identifies the overland route used to trail sheep or goats between allotments or pastures. Given that the overland route can be as narrow as a road to as wide as wandering, the route identifies the general path taken by the sheep or goats.
FEATURE CLASS CONTENT STANDARD:
The data standards for the polygon feature classes are found in the current national BLM grazing standard which is located at the following location;
http://web.blm.gov/data_mgt/standards/in_progress/grazing/index.htm
At this location the user can download both the ‘Implementation Guidelines’ and the Geodatabase XML file which contains the schema for the polygon feature classes.
For the RANGE_Sheep_Pasture_POLY and the RANGE_Sheep_Trailing_POLY feature classes, include the following fields:
Column Name Column Description Mandatory
ALLOT_NO Allotment Number Y
ALLOT_NAME Allotment Name N
PAST_NO Pasture Number 1
PAST_NAME Pasture Name N
GIS_ACRES GIS Calculated acres Y
ADMIN_ST State Administering the allotment Y
ADM_OFC_CD Administrative Office Code Y
ADM_UNIT_CD Administrative Unit Code Y
ST_ALLOT Concatenation of State and Allotment number Y
ST_ALLOT_PAST Concatenation of State, Allotment and Pasture 2
1. If the State only goes to the allotment level then they do NOT need to include a PAST_NO entry, however if the state goes to the pasture level then they will need to populate the PAST_NO column.
2. If the State only goes to the allotment level then they do NOT need to include a ST_ALLOT_PAST entry, however if the state goes to the pasture level then they will need to populate the ST_ALLOT_PAST column.
For the RANGE_Sheep_Trailing_LINE line feature class include the following fields:
Column Name Data Format Column Description Mandatory
TRAIL_NAME Char(50) Trail name or identifier Y
GIS_MILES Double GIS calculated miles Y
FEATURE CLASS METADATA AND DISTRIBUTION REQUIREMENTS:
Feature classes should contain only those allotments, pastures or routes that meet the criteria identified in the IM. The feature classes will conform to the current BLM standards for projection and datum and the feature classes will contain full metadata describing the feature class and all processes used in the generation of the feature classes. When completed the feature classes will be loaded into either a file geodatabase or personal geodatabase titled <State_Name>_SHEEP_2009_Distribution and then winzipped into a single file. The final winzipped file will be sent to XXX.
2009-10-23
Range Specialist
BLM, WO IM 2010-011
Range Specialist
208-373-4000
1387 S Vinnell Way
Bosie
ID
83709
US
blm_id_stateoffice@blm.gov
The BLM National Operations Center (NOC) Rangeland Application System Staff prepared three spreadsheets. This feature class contains allotments and pasture that met the criteria of authorized goat or sheep grazing in the allotment. These spreadsheets were converted to a MS Access database which was then joined to the Idaho pastures feature class on allotment. Where a pasture was identified in RAS it was then linked to the pasture in the GIS data. Where a pasture was not identified in the spreadsheet then all pastures within the allotment were included. This data was presented to the Idaho District Offices who reviewed the data to ensure that all allotments and pastures were properly identified in both the RAS data and the GIS data. The GIS data was then compared again to the RAS data to ensure that all of the RAS allotments and pastures were accounted for.
2009-11-30
John C.
Idaho State Office, Bureau of Land Management
GIS Analyst
208-373-4000
Idaho State Office
1387 S. Vinnell Way
Bureau of Land Management
Boise
ID
83709
US
blm_id_stateoffice@blm.gov
M - F, 8:00 - 4:30
The sheep trailing routes were provided by the BLM District and Field Offices and were consolidated into a single feature class.
2011-08-01
John Courtright
Idaho State Office, Bureau of Land Management
GIS Analyst
208-373-3950
Idaho State Office
Bureau of Land Management
1387 S. Vinnell Way
Boise
ID
83709
US
blm_id_stateoffice@blm.gov
M - F, 8 AM to 4:30 PM
Contact the Supervisor of the Geographic Sciences.
65
EPSG
9.5.1(10.8.0)
BLM ID Sheep Trailing Routes line
Sheep trailing lines
BLM ID
Feature Class
65
OBJECTID
Internal feature number.
ESRI
OBJECTID
OID
4
0
0
Sequential unique whole numbers that are automatically generated.
TRAIL_NAME
Trail name
BLM ID
TRAIL_NAME
String
50
0
0
Sequential unique whole numbers that are automatically generated.
GIS_MILES
GIS generated linear measure
miles
GIS_MILES
Double
8
0
0
Sequential unique whole numbers that are automatically generated.
GlobalID
GlobalID
GlobalID
38
0
0
Software generated unique ID.
Shape
Feature geometry.
ESRI
Shape
Geometry
0
0
0
Coordinates defining the features.
Shape.STLength()
Shape.STLength()
Double
0
0
0
Length of feature in internal units.
These fields hold the identity of the administering Field Office name (fo) and District Office name (do) for an allotment. These fields are designed to be concatenated to create the full office code of the administering BLM office, e.g. for the Four Rivers Field Office in the Boise District of Idaho BLM:
state = ID
admin_do = 1
admin_fo = 100
concatenated together = ID1100
Simple
FALSE
65
TRUE
FALSE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