The Minnesota DNR Toolbox and Hydro Tools provide a number of convenience geoprocessing tools used regularly by MNDNR staff. Many of these may be useful to the wider public. However, some tools may rely on data that is not available outside of the DNR. All tools require at least ArcGIS 10+.

If you create a GDRS using GDRS Manager and include this toolbox resource and MNDNR Quick Layers, the DNR toolboxes will automatically be added to the ArcToolbox window whenever Quick Layers GDRS Location is set to the GDRS location that has the toolboxes.

Toolsets included in MNDNR Tools V10:
- Analysis Tools
- Conversion Tools
- Division Tools
- General Tools
- Hydrology Tools
- LiDAR and DEM Tools
- Raster Tools
- Sampling Tools

These toolboxes are provided free of charge and are not warrantied for any specific use. We do not provide support or assistance in downloading or using these tools. We do, however, strive to produce high-quality tools and appreciate comments you have about them.

The State of Alaska and the Forest Service entered into a Challenge Cost-share agreement in June 2015, to complete a timber stand inventory in young-growth forest. This work supports collecting, analyzing, and using forest resource information to implement sound, sustainable forest management practices across Southeast Alaska, while offering training and developing job opportunites for rural residents in natural resource fields. This layer depicts a Thiessen display of the field-sampled plots, created using the ArcToolbox tool Create Thiessen Polygons (Analysis). Each Thiessen polygon contains only a single point input feature. Any location within a Thiessen polygon is closer to its associated point than to any other point input feature. See the ArcToolbox tool help for more details.

This dataset contains an ESRI Geotiff with 2 meter cell size representing the bathymetry of Grammanik Bank south of St. Thomas, US Virgin Islands.NOAA's NOS/NCCOS/CCMA Biogeography Team, in collaboration with NOAA vessel Nancy Foster and territory, federal, and private sector partners, acquired multibeam bathymetry data in the US Virgin Islands from 2/1/05 to 2/12/05. Data was acquired with a pole-mounted Reson 8101 ER multibeam echosounder (240 kHz) and processed by a NOAA contractor using CARIS HIPS v5.4 software. Data has all correctors applied (attitude, sound velocity) and has been reduced to mean lower low water (MLLW) using final approved tides and zoning from NOAA COOPS. Data is in UTM zone 20 north, datum NAD83. The processed CARIS data was used to generate a CARIS BASE surface based on swath angle. An ASCII XYZ file was exported from the BASE surface and opened in ESRI ArcMap 9 as an XY event. Then the ArcToolbox conversion tool 'Feature to Raster' was used to generate the final ESRI Geotiff.The project was conducted to meet IHO Order 1 and 2 accuracy standards, dependant on the project area and depth. All users should individually evaluate the suitability of this data according to their own needs and standards.

This dataset contains an ESRI Geotiff with 1 meter cell size representing the bathymetry of the Mid Shelf Reef south of St. Thomas, US Virgin Islands.NOAA's NOS/NCCOS/CCMA Biogeography Team, in collaboration with NOAA vessel Nancy Foster and territory, federal, and private sector partners, acquired multibeam bathymetry data in the US Virgin Islands from 2/1/05 to 2/12/05. Data was acquired with a pole-mounted Reson 8101 ER multibeam echosounder (240 kHz) and processed by a NOAA contractor using CARIS HIPS v5.4 software. Data has all correctors applied (attitude, sound velocity) and has been reduced to mean lower low water (MLLW) using final approved tides and zoning from NOAA COOPS. Data is in UTM zone 20 north, datum NAD83. The processed CARIS data was used to generate a CARIS BASE surface based on swath angle. An ASCII XYZ file was exported from the BASE surface and opened in ESRI ArcMap 9 as an XY event. Then the ArcToolbox conversion tool 'Feature to Raster' was used to generate the final ESRI Geotiff.The project was conducted to meet IHO Order 1 and 2 accuracy standards, dependant on the project area and depth. All users should individually evaluate the suitability of this data according to their own needs and standards.

This data set represents the 2024 elk hunt area, herd unit, and regions boundaries for Wyoming. The layer was originally digitized at a scale of 1:100,000, using USGS 1:100,000 DRGs as a backdrop for heads up digitizing. Updates requested by Wyoming Game and Fish Biological Services were completed by selecting needed features from other layers, including roads, streams, HUCs, NAIP rasters and others. Hunt area boundary descriptions are part of hunting regulations, which are approved and published annually by the Wyoming Game and Fish Commission. When needed, the 2008 edition (1st Edition) of the Wyoming Road and Recreation Atlas (Benchmark Maps) was consulted for road and other information.NOTE: This layer of nonresident regions is derived from the hunt area layer by dissolving on the "Region" attribute (Dissolve_Field), and unchecking the box "Create multipart features (optional)". All of the same metadata is used from the hunt area layer except that the citation title is modified so that "Nonresident Region" replaces "Hunt Area". The "Dissolve" tool: ArcToolbox > Data Management Tools > Generalization.

This data set represents the 2025 deer hunt area, herd unit, and regions boundaries for Wyoming. The layer was originally digitized at a scale of 1:100,000, using USGS 1:100,000 DRGs as a backdrop for heads up digitizing. Updates requested by Wyoming Game and Fish Biological Services were completed by selecting needed features from other layers, including roads, streams, HUCs, NAIP 2009 rasters and others. Hunt area boundary descriptions are part of hunting regulations, which are approved and published annually by the Wyoming Game and Fish Commission. When needed, the 2008 edition (1st Edition) of the Wyoming Road and Recreation Atlas (Benchmark Maps) was consulted for road and other information.NOTE: A layer of herd units is derived from this hunt area layer by dissolving on the "MD_HERDUNIT" or ""WD_HERDUNIT" and "MD_HERDNAME" or ""WD_HERDNAME" attributes (Dissolve_Fields), and unchecking the box "Create multipart features (optional)". All of the same metadata is used from the hunt area layer except that the citation title is modified so that "Mule Deer Herd Unit" or "White-tailed Deer Herd Unit" replaces "Hunt Area". The "Dissolve" tool: ArcToolbox > Data Management Tools > Generalization.NOTE: A layer of nonresident regions is derived from this hunt area layer by dissolving on the "Region" attribute (Dissolve_Field), and unchecking the box "Create multipart features (optional)". All of the same metadata is used from the hunt area layer except that the citation title is modified so that "Nonresident Region" replaces "Hunt Area". The "Dissolve" tool: ArcToolbox > Data Management Tools > Generalization.

This dataset contains an ESRI Geotiff with 2 meter cell size representing the bathymetry of the a portion of the NPS's Salt River Bay National Historical Park and Ecological Reserve, north of St. Croix, US Virgin Islands.NOAA's NOS/NCCOS/CCMA Biogeography Team, in collaboration with NOAA vessel Nancy Foster and territory, federal, and private sector partners, acquired multibeam bathymetry data in the US Virgin Islands from 2/1/05 to 2/12/05. Data was acquired with a pole-mounted Reson 8101 ER multibeam echosounder (240 kHz) and processed by a NOAA contractor using CARIS HIPS v5.4 software. Data has all correctors applied (attitude, sound velocity) and has been reduced to mean lower low water (MLLW) using final approved tides and zoning from NOAA COOPS. Data is in UTM zone 20 north, datum NAD83. The processed CARIS data was used to generate a CARIS BASE surface based on swath angle. An ASCII XYZ file was exported from the BASE surface and opened in ESRI ArcMap 9 as an XY event. Then the ArcToolbox conversion tool 'Feature to Raster' was used to generate the final ESRI Geotiff.The project was conducted to meet IHO Order 1 and 2 accuracy standards, dependant on the project area and depth. All users should individually evaluate the suitability of this data according to their own needs and standards.

This dataset contains an ESRI Geotiff with 1 meter cell size representing the bathymetry of the north shore of St. Croix (Buck Island), US Virgin Islands.NOAA's NOS/NCCOS/CCMA Biogeography Team, in collaboration with NOAA vessel Nancy Foster and territory, federal, and private sector partners, acquired multibeam bathymetry data in the US Virgin Islands from 2/1/05 to 2/12/05. Data was acquired with a pole-mounted Reson 8101 ER multibeam echosounder (240 kHz) and processed by a NOAA contractor using CARIS HIPS v5.4 software. Data has all correctors applied (attitude, sound velocity) and has been reduced to mean lower low water (MLLW) using final approved tides and zoning from NOAA COOPS. Data is in UTM zone 20 north, datum NAD83. The processed CARIS data was used to generate a CARIS BASE surface based on swath angle. An ASCII XYZ file was exported from the BASE surface and opened in ESRI ArcMap 9 as an XY event. Then the ArcToolbox conversion tool 'Feature to Raster' was used to generate the final ESRI Geotiff. The project was conducted to meet IHO Order 1 and 2 accuracy standards, dependant on the project area and depth. All users should individually evaluate the suitability of this data according to their own needs and standards.

The State of Alaska and the Forest Service entered into a Challenge Cost-share agreement in June 2015, to complete a timber stand inventory in young-growth forest. This work supports collecting, analyzing, and using forest resource information to implement sound, sustainable forest management practices across Southeast Alaska, while offering training and developing job opportunites for rural residents in natural resource fields. This layer depicts a Thiessen display of the field-sampled plots, created using the ArcToolbox tool Create Thiessen Polygons (Analysis). Each Thiessen polygon contains only a single point input feature. Any location within a Thiessen polygon is closer to its associated point than to any other point input feature. See the ArcToolbox tool help for more details.

Ecoregions denote areas of general similarity in ecosystems and in the type quality, and quantity of environmental resources. The ecoregions shown here have been derived from the "Level III Ecoregions of the continental United States" GIS coverage created by the US Environmental Protection Agency. The useco polygon was converted to a shapefile in ArcToolbox using the "Feature Class To Shapefile" tool. The shapefile was reprojected from Albers Conical Equal Area to Oregon Lambert. The shapefile was clipped to the boundary of Oregon.

Ecoregions denote areas of general similarity in ecosystems and in the type quality, and quantity of environmental resources. The ecoregions shown here have been derived from the "Level III Ecoregions of the continental United States" GIS coverage created by the US Environmental Protection Agency. The useco polygon was converted to a shapefile in ArcToolbox using the "Feature Class To Shapefile" tool. The shapefile was reprojected from Albers Conical Equal Area to Oregon Lambert. The shapefile was clipped to the boundary of Oregon.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. The vector (polygon) map is in digital format within a geodatabase structure that allows for complex relationships to be established between spatial and tabular data, and allows much of the data to be accessed concurrently. Strict nomenclature was enforced for polygons and a unique name was assigned to each polygon. These reflected the verified physiognomic formation type by a prefix of representative letters (e.g., W = Woodland, SS = shrub savanna), followed by a number. Using ArcMap, polygon boundaries were buffered and excluded based on the distance equal to the radius of the selected plot size, positional accuracy of the map, and positional error of the GPS to be used by the assessment crew (Lea and Curtis 2010). The resulting polygons were converted to raster format and points were distributed using the “distribute spatially balanced points” function in ArcToolbox. This function uses the RRQRR algorithm (Theobald et al. 2007) to distribute spatially balanced points throughout the raster. Next, each point was buffered using the radius of the assigned plot size to create a circular area (see Figure 3-1) that was later used as a visual aid to delineate the survey area. These circular plot areas (polygons, essentially) and the plot centroids for all map classes were merged and assigned a unique identifier. All information was removed that could give an assessor any indication as to which class it belonged.

Abstract

The dataset was created by the Bioregional Assessment Programme. The History Field in this metadata statement describes how this dataset was created.

A 1000 m * 1000m vector grid over the entire Bioregional Assessment Bioregions/Preminary Areas of Extent (using the boundary that is largest) starting at the whole km to ensure grid lines fall exactly on the whole km. The grid is in Australia Albers (GDA94) (EPSG 3577). This grid is intended as the template for standardized assessment units for the following bioregional assessment regions:

Hunter

Namoi

Clarence-Moreton

Galilee

Please note for the Gloucester subregion model a 500m grid ( GUID ) is proposed to be used as the standard assessment unit due to the finer resolution of the output models.

To facilitate processing speed and efficiency each of the above Bioregional Assessments have their own grid and extent created from this master vector grid template, (please see Lineage).

The unique ID field for each grid cell is AUID and starts from 1. The grid also has a column id and row for easy reference and processing.

Purpose

The GRID is an attempt to standardise (where possible) outputs of models from BA assessments and is a whole of BA template for the groundwater and potentially surface water teams of the above mentioned assessment areas.

Dataset History

The Vector grid was generated using the Fishnet tool in ArcGIS. The following fields were added:

AUID - Assessment Unit Unique Id

R001_C001 - A row and column id was calculated using the following python code in the field calculator in ArcGIS where 2685 is the number of rows in the grid and 2324 is the number of columns.

'R' + str(( !OID!-1)/2685).rjust(3, '0') + '_C' + str(( !OID!-1)%2324).rjust(3, '0')

A spatial index was added in ArcGIS 10.1 to increase processing and rendering speed using the Spatial index tool from the ArcToolbox.

The following parameters were used to generate the grid in the Create Fishnet tool in ArcGIS 10.1

Left: -148000

Bottom: -4485000

Fishnet Origin Coordinate

x Coordinate = -148000 Y Coordinate -4485000

Y-Axis Coordinate

X Coordinate -148000 Y Coordinate -4484990

Cell Height - 1000m

Cell Width - 1000m

Number of rows 0

Number of columns 0

Opposite corner: default

Geometry type: Polygon

Y

Dataset Citation

XXXX XXX (2016) BA ALL Assessment Units 1000m 'super set' 20160516_v01. Bioregional Assessment Source Dataset. Viewed 13 March 2019, http://data.bioregionalassessments.gov.au/dataset/6c1aa99e-c973-4472-b434-756e60667bfa.

The State of Alaska and the Forest Service entered into a Challenge Cost-share agreement in June 2015, to complete a timber stand inventory in young-growth forest. This work supports collecting, analyzing, and using forest resource information to implement sound, sustainable forest management practices across Southeast Alaska, while offering training and developing job opportunites for rural residents in natural resource fields. This layer depicts a Thiessen display of the field-sampled plots, created using the ArcToolbox tool Create Thiessen Polygons (Analysis). Each Thiessen polygon contains only a single point input feature. Any location within a Thiessen polygon is closer to its associated point than to any other point input feature. See the ArcToolbox tool help for more details.

This dataset contains an ESRI Geotiff with 2 meter cell size representing the bathymetry of an offshore portion of the NPS's Virgin Islands Coral Reef National Monument, south of St. John, US Virgin Islands.NOAA's NOS/NCCOS/CCMA Biogeography Team, in collaboration with NOAA vessel Nancy Foster and territory, federal, and private sector partners, acquired multibeam bathymetry data in the US Virgin Islands from 2/1/05 to 2/12/05. Data was acquired with a pole-mounted Reson 8101 ER multibeam echosounder (240 kHz) and processed by a NOAA contractor using CARIS HIPS v5.4 software. Data has all correctors applied (attitude, sound velocity) and has been reduced to mean lower low water (MLLW) using final approved tides and zoning from NOAA COOPS. Data is in UTM zone 20 north, datum NAD83. The processed CARIS data was used to generate a CARIS BASE surface based on swath angle. An ASCII XYZ file was exported from the BASE surface and opened in ESRI ArcMap 9 as an XY event. Then the ArcToolbox conversion tool 'Feature to Raster' was used to generate the final ESRI Geotiff.The project was conducted to meet IHO Order 1 and 2 accuracy standards, dependant on the project area and depth. All users should individually evaluate the suitability of this data according to their own needs and standards.

This dataset contains an ESRI Geotiff with 1 meter cell size representing the bathymetry of an inshore portion of the NPS's Virgin Islands Coral Reef National Monument, south of St. John, US Virgin Islands.NOAA's NOS/NCCOS/CCMA Biogeography Team, in collaboration with NOAA vessel Nancy Foster and territory, federal, and private sector partners, acquired multibeam bathymetry data in the US Virgin Islands from 2/1/05 to 2/12/05. Data was acquired with a pole-mounted Reson 8101 ER multibeam echosounder (240 kHz) and processed by a NOAA contractor using CARIS HIPS v5.4 software. Data has all correctors applied (attitude, sound velocity) and has been reduced to mean lower low water (MLLW) using final approved tides and zoning from NOAA COOPS. Data is in UTM zone 20 north, datum NAD83. The processed CARIS data was used to generate a CARIS BASE surface based on swath angle. An ASCII XYZ file was exported from the BASE surface and opened in ESRI ArcMap 9 as an XY event. Then the ArcToolbox conversion tool 'Feature to Raster' was used to generate the final ESRI Geotiff.The project was conducted to meet IHO Order 1 and 2 accuracy standards, dependant on the project area and depth. All users should individually evaluate the suitability of this data according to their own needs and standards.

Dataset description-br /- This dataset is a recalculation of the Copernicus 2015 high resolution layer (HRL) of imperviousness density data (IMD) at different spatial/territorial scales for the case studies of Barcelona and Milan. The selected spatial/territorial scales are the following: * a) Barcelona city boundaries * b) Barcelona metropolitan area, Àrea Metropolitana de Barcelona (AMB) * c) Barcelona greater city (Urban Atlas) * d) Barcelona functional urban area (Urban Atlas) * e) Milan city boundaries * f) Milan metropolitan area, Piano Intercomunale Milanese (PIM) * g) Milan greater city (Urban Atlas) * h) Milan functional urban area (Urban Atlas)-br /- In each of the spatial/territorial scales listed above, the number of 20x20mt cells corresponding to each of the 101 values of imperviousness (0-100% soil sealing: 0% means fully non-sealed area; 100% means fully sealed area) is provided, as well as the converted measure into squared kilometres (km2). -br /- -br /- -br /- Dataset composition-br /- The dataset is provided in .csv format and is composed of: -br /- _IMD15_BCN_MI_Sources.csv_: Information on data sources -br /- _IMD15_BCN.csv_: This file refers to the 2015 high resolution layer of imperviousness density (IMD) for the selected territorial/spatial scales in Barcelona: * a) Barcelona city boundaries (label: bcn_city) * b) Barcelona metropolitan area, Àrea metropolitana de Barcelona (AMB) (label: bcn_amb) * c) Barcelona greater city (Urban Atlas) (label: bcn_grc) * d) Barcelona functional urban area (Urban Atlas) (label: bcn_fua)-br /- _IMD15_MI.csv_: This file refers to the 2015 high resolution layer of imperviousness density (IMD) for the selected territorial/spatial scales in Milan: * e) Milan city boundaries (label: mi_city) * f) Milan metropolitan area, Piano intercomunale milanese (PIM) (label: mi_pim) * g) Milan greater city (Urban Atlas) (label: mi_grc) * h) Milan functional urban area (Urban Atlas) (label: mi_fua)-br /- _IMD15_BCN_MI.mpk_: the shareable project in Esri ArcGIS format including the HRL IMD data in raster format for each of the territorial boundaries as specified in letter a)-h). -br /- Regarding the territorial scale as per letter f), the list of municipalities included in the Milan metropolitan area in 2016 was provided to me in 2016 from a person working at the PIM. -br /- In the IMD15_BCN.csv and IMD15_MI.csv, the following columns are included: * Level: the territorial level as defined above (a)-d) for Barcelona and e)-h) for Milan); * Value: the 101 values of imperviousness density expressed as a percentage of soil sealing (0-100%: 0% means fully non-sealed area; 100% means fully sealed area); * Count: the number of 20x20mt cells corresponding to a certain percentage of soil sealing or imperviousness; * Km2: the conversion of the 20x20mt cells into squared kilometres (km2) to facilitate the use of the dataset.-br /- -br /- -br /- Further information on the Dataset-br /- This dataset is the result of a combination between different databases of different types and that have been downloaded from different sources. Below, I describe the main steps in data management that resulted in the production of the dataset in an Esri ArcGIS (ArcMap, Version 10.7) project.-br /- 1. The high resolution layer (HRL) of the imperviousness density data (IMD) for 2015 has been downloaded from the official website of Copernicus. At the time of producing the dataset (April/May 2021), the 2018 version of the IMD HRL database was not yet validated, so the 2015 version was chosen instead. The type of this dataset is raster. 2. For both Barcelona and Milan, shapefiles of their administrative boundaries have been downloaded from official sources, i.e. the ISTAT (Italian National Statistical Institute) and the ICGC (Catalan Institute for Cartography and Geology). These files have been reprojected to match the IMD HRL projection, i.e. ETRS 1989 LAEA. 3. Urban Atlas (UA) boundaries for the Greater Cities (GRC) and Functional Urban Areas (FUA) of Barcelona and Milan have been checked and reconstructed in Esri ArcGIS from the administrative boundaries files by using a Eurostat correspondence table. This is because at the time of the dataset creation (April/May 2021), the 2018 Urban Atlas shapefiles for these two cities were not fully updated or validated on the Copernicus Urban Atlas website. Therefore, I had to re-create the GRC and FUA boundaries by using the Eurostat correspondence table as an alternative (but still official) data source. The use of the Eurostat correspondence table with the codes and names of municipalities was also useful to detect discrepancies, basically stemming from changes in municipality names and codes and that created inconsistent spatial features. When detected, these discrepancies have been checked with the ISTAT and ICGC offices in charge of producing Urban Atlas data before the final GRC and FUA boundaries were defined.-br /- Steps 2) and 3) were the most time consuming, because they required other tools to be used in Esri ArcGIS, like spatial joins and geoprocessing tools for shapefiles (in particular dissolve and area re-calculator in editing sessions) for each of the spatial/territorial scales as indicated in letters a)-h). -br /- Once the databases for both Barcelona and Milan as described in points 2) and 3) were ready (uploaded in Esri ArcGIS, reprojected and their correctness checked), they have been ‘crossed’ (i.e. clipped) with the IMD HRL as described in point 1) and a specific raster for each territorial level has been calculated. The procedure in Esri ArcGIS was the following: * Clipping: Arctoolbox - Data management tools - Raster - Raster Processing - Clip. The ‘input’ file is the HRL IMD raster file as described in point 1) and the ‘output’ file is each of the spatial/territorial files. The option "Use Input Features for Clipping Geometry (optional)” was selected for each of the clipping. * Delete and create raster attribute table: Once the clipping has been done, the raster has to be recalculated first through Arctoolbox - Data management tools - Raster - Raster properties - Delete Raster Attribute Table and then through Arctoolbox - Data management tools - Raster - Raster properties - Build Raster Attribute Table; the "overwrite" option has been selected. -br /- -br /- Other tools used for the raster files in Esri ArcGIS have been the spatial analyst tools (in particular, Zonal - Zonal Statistics). As an additional check, the colour scheme of each of the newly created raster for each of the spatial/territorial attributes as per letters a)-h) above has been changed to check the consistency of its overlay with the original HRL IMD file. However, a perfect match between the shapefiles as per letters a)-h) and the raster files could not be achieved since the raster files are composed of 20x20mt cells.-br /- The newly created attribute tables of each of the raster files have been exported and saved as .txt files. These .txt files have then been copied in the excel corresponding to the final published dataset.

This dataset contains an ESRI Geotiff with 1 meter cell size representing the bathymetry of the south shore of St. John, US Virgin Islands. Due to the large file size of the St. John project area, it was divided into four component grids for improved manageability, named STJ_1m_grid1, STJ_1m_grid2, STJ_1m_grid3, and STJ_1m_grid4 from west to east.NOAA's NOS/NCCOS/CCMA Biogeography Team and NOAA/NOS/OCS/HSD personnel, in collaboration with NOAA vessel Nancy Foster and territory, federal, and private sector partners, acquired multibeam bathymetry data in the US Virgin Islands from 2/18/04 to 3/5/04. Data was acquired with a pole-mounted Reson 8101 ER multibeam echosounder (240 kHz) and processed by a NOAA contractor using CARIS HIPS v5.4 software. Data has all correctors applied (attitude, sound velocity) and has been reduced to mean lower low water (MLLW) using final approved tides from NOAA COOPS. Data is in UTM zone 20 north, datum WGS84. The processed CARIS data was used to generate a CARIS BASE surface based on swath angle with footprint size 3*3. An ASCII XYZ file was exported from the BASE surface and opened in ESRI ArcMap 9 as an XY event. Then the ArcToolbox conversion tool 'Feature to Raster', with cell size 1, was used to generate the final ESRI Geotiff. While the project was conducted to meet IHO Order 2 accuracy standards, there is a roll artifact (averaging 0.5m high) in the dataset that the user should take into consideration when performing any analysis.

This data set represents the 2025 elk hunt area, herd unit, and regions boundaries for Wyoming. The layer was originally digitized at a scale of 1:100,000, using USGS 1:100,000 DRGs as a backdrop for heads up digitizing. Updates requested by Wyoming Game and Fish Biological Services were completed by selecting needed features from other layers, including roads, streams, HUCs, NAIP rasters and others. Hunt area boundary descriptions are part of hunting regulations, which are approved and published annually by the Wyoming Game and Fish Commission. When needed, the 2008 edition (1st Edition) of the Wyoming Road and Recreation Atlas (Benchmark Maps) was consulted for road and other information.NOTE: A layer of herd units is derived from this hunt area layer by dissolving on the "HERDUNIT" and "HERDNAME" attributes (Dissolve_Fields), and unchecking the box "Create multipart features (optional)". All of the same metadata is used from the hunt area layer except that the citation title is modified so that "Herd Unit" replaces "Hunt Area". The "Dissolve" tool: ArcToolbox > Data Management Tools > Generalization.NOTE: A layer of nonresident regions is derived from this hunt area layer by dissolving on the "Region" attribute (Dissolve_Field), and unchecking the box "Create multipart features (optional)". All of the same metadata is used from the hunt area layer except that the citation title is modified so that "Nonresident Region" replaces "Hunt Area". The "Dissolve" tool: ArcToolbox > Data Management Tools > Generalization.

This data set represents the 2021 Rocky Mountain goat hunt area and herd unit boundaries for Wyoming. The layer was originally digitized at a scale of 1:100,000, using USGS 1:100,000 DRGs as a backdrop for heads up digitizing. Updates are currently done by selecting needed features from other layers, including roads, streams, HUCs, etc. Huntarea boundary descriptions are part of hunting regulations, which are approved and published annually by the Wyoming Game and Fish Commission. When needed, the 2008 edition (First Edition) of the Wyoming Road and Recreation Atlas (Benchmark Maps) was consulted for road information.NOTE: A layer of herd units is derived from this hunt area layer by dissolving on the "HERDUNIT" and "HERDNAME" attributes (Dissolve_Fields), and unchecking the box "Create multipart features (optional)". All of the same metadata is used from the hunt area layer except that the citation title is modified so that "Herd Unit" replaces "Hunt Area". The "Dissolve" tool: ArcToolbox > Data Management Tools > Generalization.