mn_county_boun_ExportFeature28
002
189775.332039
761655.073439
4816305.370038
5472427.737000
1
0.000
Projected
GCS_North_American_1983
NAD_1983_UTM_Zone_15N
<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/3.1.0'><WKT>PROJCS["NAD_1983_UTM_Zone_15N",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",500000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-93.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0],AUTHORITY["EPSG",26915]]</WKT><XOrigin>-5120900</XOrigin><YOrigin>-9998100</YOrigin><XYScale>10000</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>26915</WKID><LatestWKID>26915</LatestWKID></ProjectedCoordinateSystem>
Linear Unit: Meter (1.000000)
20231030
14051900
20231030
14051900
1.0
Renee Johnson
DNR-Lands and Minerals
ITS 3
(651) 259-5396
(651) 296-5939
500 Lafayette Road - Box 45
St. Paul
MN
55155
renee.johnson@state.mn.us
20231030
ArcGIS Metadata
1.0
Hal Watson
DNR-MIS
GIS Database Coordinator
(651) 259-5508
(651) 297-4946
500 Lafayette Road, Box 11
St. Paul
MN
55155-4011
hal.watson@state.mn.us
See Online Linkage or Distribution Contact
bdry_counpy2
File Geodatabase Feature Class
Not Applicable
http://deli.dnr.state.mn.us/
0.5
mn_county_boun_ExportFeature28
Minnesota DNR - Minerals Division/Section of Wildlife
Minnesota DNR - MIS Bureau
Minnesota county boundaries derived from a combination of 1:24,000 scale PLS lines, 1:100,000 scale TIGER, 1:100,000 scale DLG, and 1:24,000 scale hydrography lines. At the time of its development (1993), the largest available scale data were assembled to create the layer.
Renee Johnson
DNR-Lands and Minerals
ITS 3
(651) 259-5396
(651) 296-5939
500 Lafayette Road - Box 45
St. Paul
MN
55155
renee.johnson@state.mn.us
http://jmaps.dnr.state.mn.us/gis/dp_datasample.jsp?mpid=22000003&ptid=2&fcid=1&lname=Minnesota County Boundaries
Minnesota
Minnesota counties, boundaries
Minnesota
Minnesota counties, boundaries
Access constraints: None
Use constraints: Use of the data are constrained only by the DNR GIS Data License Agreement
The Minnesota Department of Natural Resources makes no representation or warranties, express or implied, with respect to the reuse of data provided herewith, regardless of its format or the means of its transmission. There is no guarantee or representation to the user as to the accuracy, currency, suitability, or reliability of this data for any purpose. The user accepts the data 'as is', and assumes all risks associated with its use. By accepting this data, the user agrees not to transmit this data or provide access to it or any part of it to another party unless the user shall include with the data a copy of this disclaimer. The Minnesota Department of Natural Resources assumes no responsibility for actual or consequential damage incurred as a result of any user's reliance on this data.
Esri ArcGIS 13.1.3.41833
-97.269864
-89.397120
43.435384
49.404536
1
A multitude of source dates are associated with this data set, including those associated with the original GISMO, RKI, DLG, and TIGER data set development efforts. Work on the coverage was completed during the summer/fall of 1993. Attribute restructuring to ensure conformance with DNR PLS Coding standard performed in March 1996.
Unknown
1
Statewide
002
Data are topolocially correct using ARC/INFO 7.0.3. All polygons are closed and lines intersect where intended.
Data are topolocially correct using ARC/INFO 7.0.3. All polygons are closed and lines intersect where intended.
All Minnesota county lands are present, including off-shore islands in Lake Superior. The official state and international borders within Lake Superior are not included in this data set.
Source table BDRY_COUNPY2.DBF: Unknown
Source layer plsctne3: Not Applicable
Source layer plsctne3: Source accuracies vary greatly. PLS lines and coincident county boundaries range in expected offsets from 50 to 200 feet, with the smaller value being more common. The most significant offsets within this category are in the northeastern portion of the state where the USGS quad sources are most tentative with regards to section corner locations. County boundaries not coincident with PLS lines are typically from 1990 vintage TIGER data with many off-sets in the 100 foot range. The international boundary should be highly accurate as it was taken directly from legislative notes. The Lake Superior North Shore was from National Wetland Inventory and will typically exhibit off-sets of about 60 feet, with generally good depictions of the shore line character.
Attribute Lineage for source table BDRY_COUNPY2.DBF: Some attribute table restructuring was performing during the GIS Core Library development effort in March 1996. This entailed bringing in selected fields from the county cross-reference table, including county names and county abbreviations.
0
None
EPSG
6.11(3.0.1)
dataset
Simple
FALSE
0
TRUE
FALSE
0
mn_county_boun_ExportFeature28
Feature Class
0
OBJECTID_1
OBJECTID_1
OID
4
0
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
Shape
Shape
Geometry
0
0
0
Feature geometry.
ESRI
Coordinates defining the features.
OBJECTID
OBJECTID
Integer
4
0
0
CTY_NAME
CTY_NAME
String
255
0
0
CTY_NAME_1
CTY_NAME
String
20
0
0
F2_1_2___Equity
2.1.2 _ Equity
Double
8
0
0
F2_3_1___Equity
2.3.1 _ Equity
Double
8
0
0
F3_4_1___Equity
3.4.1 _ Equity
Double
8
0
0
F3_4_2___Equity
3.4.2 _ Equity
Double
8
0
0
F3_5_2___Equity
3.5.2 _ Equity
Integer
4
0
0
F3_6_1_Equity
3.6.1 Equity
Integer
4
0
0
F3_7_2_Transportation
3.7.2 Transportation
Integer
4
0
0
F3_8_1_Equity
3.8.1 Equity
Integer
4
0
0
F3_9_1_Equity
3.9.1 Equity
Double
8
0
0
F3_b_1_Equity
3.b.1 Equity
Double
8
0
0
F3_b_3_Equity
3.b.3 Equity
Integer
4
0
0
F3_d_2_Equity
3.d.2 Equity
Double
8
0
0
F4_1_2_Equity
4.1.2 Equity
Double
8
0
0
F4_2_2_Equity
4.2.2 Equity
Double
8
0
0
F5_5_2_Equity
5.5.2 Equity
Double
8
0
0
F6_3_2_Water
6.3.2 Water
Double
8
0
0
F7_1_2_Energy
7.1.2 Energy
Double
8
0
0
F8_5_2_Economic_Development
8.5.2 Economic Development
Double
8
0
0
F9_2_2_Economic_Development
9.2.2 Economic Development
Double
8
0
0
F10_5_1_Equity
10.5.1 Equity
Integer
4
0
0
F11_2_1_Transportation
11.2.1 Transportation
Integer
4
0
0
F11_3_2_Economic_Development
11.3.2 Economic Development
Double
8
0
0
F11_6_2_Economic_Development
11.6.2 Economic Development
Double
8
0
0
F11_b_2_Economic_Development
11.b.2 Economic Development
Integer
4
0
0
F13_2_1_Economic_Development
13.2.1 Economic Development
Double
8
0
0
F13_2_2_Economic_Development
13.2.2 Economic Development
Double
8
0
0
F14_1_1_Water
14.1.1 Water
Double
8
0
0
F15_1_1_Green_Infrastructure
15.1.1 Green Infrastructure
Double
8
0
0
F16_2_1_Equity
16.2.1 Equity
Double
8
0
0
F16_7_2_Economic_Development
16.7.2 Economic Development
Double
8
0
0
F17_6_1_Economic_Development
17.6.1 Economic Development
Double
8
0
0
F17_16_1_Eonomic_Development
17.16.1 Eonomic Development
Double
8
0
0
F17_17_1_Economic_Development
17.17.1 Economic Development
Double
8
0
0
Shape_Length
Shape_Length
Double
8
0
0
Length of feature in internal units.
Esri
Positive real numbers that are automatically generated.
Shape_Area
Shape_Area
Double
8
0
0
Area of feature in internal units squared.
ESRI
Positive real numbers that are automatically generated.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