mn_county_boun_ExportFeature23
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
13444600
20231030
13444600
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_ExportFeature23
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.
Economic Development
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_ExportFeature23
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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