National Wetland Inventory Update for Minnesota

This page last updated: 03/20/2017
Metadata created using Minnesota Geographic Metadata Guidelines


Go to Section:
1. Overview
2. Data Quality
3. Data Organization
4. Coordinate System
5. Attributes
6. Distribution - Get Data
7. Metadata Reference

Section 1 Overview
Originator Minnesota Department of Natural Resources, Ducks Unlimited, and St. Mary's University of Minnesota
Title National Wetland Inventory Update for Minnesota
Abstract The National Wetland Inventory (NWI) data for Minnesota are being updated through a multi-agency collaborative effort under leadership of the Minnesota Department of Natural Resources (MNDNR). The update is being conducted in geographic phases with data released for each region as it is finalized. This metadata record covers the first three geographic regions: northeast, east-central, and southern Minnesota. Major funding was provided by the Environmental and Natural Resources Trust Fund. The updated NWI classify wetlands according to the system developed by Cowardin et al. (1979). The data also contains a simplified plant community classification (SPCC) and a simplified hydrogeomorphic (HGM) classification. Quality assurance of the data included visual inspection, automated checks for attribute validity and topologic consistency, as well as a formal accuracy assessment based on an independent field verified data set. Further details on the methods employed can be found in the technical procedures document for this project located on the project website (www.dnr.state.mn.us/eco/wetlands/nwi_proj.html ). The updated NWI data are primarily based on spring aerial imagery acquired in 2011 and LiDAR elevation data as well as other modern ancillary data. These data are intended to replace the original 1980s NWI data. NWI data support effective wetland management, protection, and restoration. The data provide a baseline for assessing the effectiveness of wetland policies and management actions. These data are used at all levels of government, as well as by private industry and non-profit organizations for wetland regulation and management, land use and conservation planning, environmental impact assessment, and natural resource inventories.

EAST-CENTRAL: Operational support for wetland mapping and classification was provided by Ducks Unlimited (DU) and support for methods development and field validation were provided by the Remote Sensing and Geospatial Analysis Laboratory at the University of Minnesota. The DNR Resource Assessment Office provided additional support data processing, field checking, and quality control review. The east-central project area consists of 13 counties including: Anoka, Carver, Chisago, Dakota, Goodhue, Hennepin, Isanti, Ramsey, Rice, Scott, Sherburne, Washington, and Wright Counties. The updated wetland inventory area included complete coverage for all USGS quarter quadrangles that intersect any of these counties (about 7,150 square mile).The NWI classification process for east-central Minnesota consisted of three basic steps: 1) creation of image segments (polygons), 2) RandomForest classification of the segments, and 3) photo-interpretation/editing of the classified image segments.

NORTHEAST: Operational support for wetland mapping and classification was provided by Ducks Unlimited (DU) and support for methods development and field validation were provided by the Remote Sensing and Geospatial Analysis Laboratory at the University of Minnesota. The DNR Resource Assessment Office provided additional support data processing, field checking, and quality control review. The project area consists of 5 counties in northeast Minnesota including: Cook, Koochiching, Lake, St. Louis, and a portion of Carlton Counties. The project encompasses 1,097 USGS quarter quads covering an area of 14,330 square miles (17% of the state). The NWI classification process for northeast Minnesota consisted of three basic steps: 1) creation of image segments (polygons), 2) RandomForest classification of the segments, and 3) photo-interpretation of the classified image segments. Please note that a portion of Koochiching County was completed as a separate pilot project. Those data are not yet included in the greater northeast regional product and will be incorporated after their validation is complete.

SOUTHERN: Operational support for wetland mapping and classification was provided by Geospatial Services of St. Mary's University of Minnesota (SMUMN) and support for methods development and field validation were provided by the Remote Sensing and Geospatial Analysis Laboratory at the University of Minnesota. The MNDNR Resource Assessment Office provided additional support data processing, field checking, and quality control review. Major funding was provided by the Environmental and Natural Resources Trust Fund. The project area consists of 36 counties in southern Minnesota including: Big Stone, Blue Earth, Brown, Chippewa, Cottonwood, Dodge, Faribault, Fillmore, Freeborn, Houston, Jackson, Kandiyohi, Lac qui Parle, Le Sueur, Lincoln, Lyon, Martin, McLeod, Meeker, Mower, Murray, Nicollet, Nobles, Olmstead, Pipestone, Redwood, Renville, Rock, Sibley, Steele, Swift, Wabasha, Waseca, Watonwan, Winona, and Yellow Medicine Counties. The project encompasses 1,787 USGS quarter quads covering an area of 23,900 square miles (28% of the state). The NWI classification process for southern Minnesota relied on visual image interpretation and other geospatial techniques to identify and classify wetlands using remote sensing data.

NOTE: The layer files for this data have been set up to restrict drawing of the data when zoomed out beyond 1:100,000 scale for the east-central region and when zoomed out beyond 1:250,000 scale for the northeast and southern regions. This is, in part, to prevent problems with slow performance with this large dataset. However, the data have also been compressed to speed the drawing performance and this results in a terminal system instability in ArcMap version 10.2 when the east-central data are viewed zoomed out beyond about 1:100,000 scale (1:60,000 scale for the Cowardin symbolized layer). This does not affect the more recent versions of ArcMap such as ArcMap 10.2.2. It also does not affect uncompressed versions of the data.
Purpose The updated NWI data for east-central, northeast, and southern MN are primarily based on spring aerial imagery acquired in 2010 and 2011 and LiDAR elevation data as well as other modern ancillary data. These data are intended to replace the original 1980s NWI. NWI data support effective wetland management, protection, and restoration. The data provide a baseline for assessing the effectiveness of wetland policies and management actions. These data are used at all levels of government, as well as by private industry and non-profit organizations for wetland regulation and management, land use and conservation planning, environmental impact assessment, and natural resource inventories.
Time Period of Content Date 03/20/2017
Currentness Reference Based on 2010 and 2011 digital aerial photos. Time Period of Content Date indicates when dataset was last updated.
Progress Complete
Maintenance and Update Frequency None Planned
Spatial Extent of Data The project area consists of 5 counties in northeast, 13 counties in east-central, and 36 counties in southern Minnesota including: Anoka, Carver, Chisago, Cook, Dakota, Goodhue, Hennepin, Isanti, Ramsey, Rice, Scott, Sherburne, Washington, Wright, Big Stone, Blue Earth, Brown, Chippewa, Cottonwood, Dodge, Faribault, Fillmore, Freeborn, Houston, Jackson, Kandiyohi, Koochiching, Lac qui Parle, Lake, Le Sueur, Lincoln, Lyon, Martin, McLeod, Meeker, Mower, Murray, Nicollet, Nobles, Olmstead, Pipestone, Redwood, Renville, Rock, Sibley, St. Louis, Steele, Swift, Wabasha, Waseca, Watonwan, Winona, Yellow Medicine, and portions of Carlton. The project encompasses an area of 45,400 square miles (54% of the state).
Bounding Coordinates -96.862
-89.492
48.688
43.350
Place Keywords Minnesota
Theme Keywords Surface Water, Wetlands, Swamp, Marsh, Bog, Fen
Theme Keyword Thesaurus ISO 19115 Category
Access Constraints None
Use Constraints None
Contact Person Information Steve Kloiber, Wetlands Monitoring Coordinator
Minnesota Department of Natural Resources
Minnesota Department of Natural Resources
St. Paul, MN  55155-4025
Phone: 651-259-5164
Email: steve.kloiber@state.mn.us
Browse Graphic Click to view a data sample
Associated Data Sets

Section 2 Data Quality
Attribute Accuracy The source data was checked using standard review procedures. Attributes were checked by using visual inspection as well as automated verification routines.

1) EAST-CENTRAL ACCURACY TESTING

PHOTOINTERPRETATION ACCURACY

To assess the performance of the final deliverable provided by Ducks Unlimited with respect to the FGDC accuracy goals, the data were compared to an independently developed set of 901 photo-interpreted points (PI points). The points were selected by a stratified-random sampling process and classified using high-resolution stereo imagery (mostly 1-foot resolution), 3-meter LiDAR derived digital elevation models, and other ancillary data. The mapped wetland class (polygons) was associated with the validation class (points) using a spatial join process in ArcGIS. The distance to the nearest wetland-upland boundary was calculated for each point. Points inside of the 95% confidence interval of the positional uncertainty of the imagery were excluded from analysis (1.53 meters).

The data were compared at two classification levels: level one compares the level of agreement between the two data sets for a two-class system of wetland versus upland, and level two compares the agreement between the data sets for the Cowardin wetland class-level. The producer's accuracy, the user's accuracy, and the overall accuracy were calculated for the level one (wetland-upland) classification. The level-two (Cowardin class) assessment calculated the overall accuracy.

Wetland-Upland Accuracy
Wetland Producer's Accuracy = 93%
Wetland User's Accuracy = 98%
Overall Wetland-Upland Accuracy = 93%

Wetland Class Accuracy
Overall Class Accuracy = 78%

Many of the classification differences between the two datasets were associated with confusion between the L1 system (limnetic) and L2 system (littoral) as well as confusion between aquatic bed (AB) and unconsolidated bottom (UB) classes. The limnetic-littoral boundary is generally defined by the 2-meter depth contour by the Cowardin system; however, data on water body depth is not universally available, so differentiating between these systems is difficult to do with precision. The difference between AB and UB systems is based on the presence macrophytic aquatic vegetation. Differentiation between these two classes is confounded by the dynamic nature of vegetation patterns. If these two classes of error are excluded from the analysis, the overall photo-interpreted wetland classification accuracy for the updated NWI would be 86%.

FIELD ACCURACY

The NWI is a map product derived from remote sensing. While remote sensing methods are the only practical means of wide-area mapping, these methods are somewhat limited in their ability to detect and classify certain feature types compared to a field-level assessment. To provide additional information regarding the reliability of the NWI for field-level use, the data were also compared to a set of validation data points mostly derived from field efforts. The Remote Sensing and Geospatial Analysis Laboratory at the University of Minnesota collected 915 field-based validation points in the summer of 2010. Sample points were located using a stratified-random sampling process. All field data were reviewed by the DNR wetland monitoring coordinator to check for obvious data errors. A ground-level assessment was made of wetland class and GPS coordinates were acquired using a Trimble Juno field computer. The geographic coordinate data were differentially corrected to improve accuracy. An additional 168 points were added by photo-interpreting high-resolution stereo imagery and other ancillary data to compliment the field data and ensure complete spatial distribution across the project area.

The mapped wetland class (polygons) was associated with the validation class (points) using a spatial join process in ArcGIS. The distance to the nearest wetland class boundary was calculated for each point. Points inside of the combined 95% confidence interval of the positional uncertainty of the imagery and the GPS were excluded (5.64 meters). The data were compared at two classification levels: level one compares the level of agreement between the two data sets for a two-class system of wetland versus upland, and level two compares the agreement between the data sets for the Cowardin wetland class-level. The producer's accuracy, the user's accuracy, and the overall accuracy were calculated for the level one (wetland-upland) classification. The level-two (Cowardin class) assessment calculated the overall accuracy.

Wetland-Upland Accuracy
Wetland Producer's Accuracy = 89%
Wetland User's Accuracy = 97%
Overall Wetland-Upland Accuracy = 89%

Wetland Class Accuracy
Overall Wetland Class Accuracy = 72%

As with the comparison to the PI points, many of the difference between the field classification and the mapped classification are related to the L1/L2 system and AB/UB classes. If these two classes of error are excluded from the analysis, the overall field wetland classification accuracy for the updated NWI would be 84%.


2) NORTHEASTERN ACCURACY TESTING

The data were compared to an independent set of validation points to assess their quality and accuracy. Validation points were selected by a stratified-random sampling process, classified through a field review conducted by the University of Minnesota, and reviewed by the DNR using 0.5-meter resolution imagery, 1-meter LiDAR derived digital elevation models, and other ancillary data. The mapped wetland class was associated with the validation class using a spatial join process in ArcGIS (points to polygons).

Points within 3 meters of a wetland boundary were excluded to prevent potential positional uncertainty in the field GPS and base aerial imagery from leading to apparent errors in classification accuracy. For the wetland-upland classification accuracy (level one) this left 800 validation points for testing. For testing of the Cowardin class accuracy (level two), points within 3 meters of a class boundary were excluded along with all upland points, leaving 456 wetland-only, validation points. The producer's accuracy, the user's accuracy, and the overall accuracy were calculated for the level one (wetland-upland) classification. The level-two (Cowardin class) assessment calculated the overall accuracy.

Wetland-Upland Accuracy
Wetland Producer's Accuracy = 84%
Wetland User's Accuracy = 97%
Overall Wetland-Upland Accuracy = 86%

Wetland Class Accuracy
Overall Class Accuracy = 69%

Many of the classification differences between the two datasets were associated with confusion between the L1 system (limnetic) and L2 system (littoral) as well as confusion between aquatic bed (AB) and unconsolidated bottom (UB) classes. The limnetic-littoral boundary is generally defined by the 2.5-meter depth contour by the Cowardin system; however, data on water body depth is not universally available, so differentiating between these systems is difficult to do with precision. The difference between AB and UB systems is based on the presence macrophytic aquatic vegetation. Differentiation between these two classes is confounded by the dynamic nature of vegetation patterns. If these two classes of error are excluded from the analysis, the overall photo-interpreted wetland classification accuracy for the updated NWI would be 71%.


3) SOUTHERN ACCURACY TESTING

The data were compared to an independent set of validation points to assess their quality and accuracy. Validation points were selected by a stratified-random sampling process, classified through a field review conducted by the University of Minnesota, and reviewed by the DNR using 0.5-meter resolution imagery, 1-meter LiDAR derived digital elevation models, and other ancillary data. The mapped wetland class was associated with the validation class using a spatial join process in ArcGIS (points to polygons).

Points within 5 meters of a wetland boundary were excluded to prevent potential positional uncertainty in the field GPS and base aerial imagery from leading to apparent errors in classification accuracy. For the wetland-upland classification accuracy (level one) this left 2210 validation points for testing. For testing of the Cowardin class accuracy (level two), points within 5 meters of a class boundary were excluded along with all upland points, leaving 481 wetland-only, validation points. The producer's accuracy, the user's accuracy, and the overall accuracy were calculated for the level one (wetland-upland) classification. The level-two (Cowardin class) assessment calculated the overall accuracy.

Wetland-Upland Accuracy
Wetland Producer's Accuracy = 89%
Wetland User's Accuracy = 94%
Overall Wetland-Upland Accuracy = 94%

Wetland Class Accuracy
Overall Class Accuracy = 83%

Many of the classification differences between the two datasets were associated with confusion between the L1 system (limnetic) and L2 system (littoral) as well as confusion between aquatic bed (AB) and unconsolidated bottom (UB) classes. The limnetic-littoral boundary is generally defined by the 2.5-meter depth contour by the Cowardin system; however, data on water body depth is not universally available, so differentiating between these systems is difficult to do with precision. The difference between AB and UB systems is based on the presence macrophytic aquatic vegetation. Differentiation between these two classes is confounded by the dynamic nature of vegetation patterns. If these two classes of error are excluded from the analysis, the overall photo-interpreted wetland classification accuracy for the updated NWI would be 86%.
Logical Consistency Polygon and chain-node topology are present. Every polygon has a label.
Completeness This data set represents the extent of wetlands and deepwater habitats that can be determined with the use of remotely sensed data and within the timeframe for which the layer was produced. The accuracy of image interpretation depends on the quality of the imagery, the experience of the image analysts, the amount and quality of the collateral data, and the amount of ground truth verification work conducted.
Horizontal Positional Accuracy The base imagery used to develop the NWI data has a horizontal RMSE of 1.53 meters for the east-central region, 2.01 meters for the northeast region, and 0.82 meters for the southern region. Wetland boundaries typically exist along a gradient of hydrology, soils, and vegetation and determining precise locations can be difficult even in the field.
Vertical Positional Accuracy Not Applicable
Lineage 1) EAST-CENTRAL REGION

Input Data
MN DNR Spring Aerial Imagery 2010 - 0.5 meter
MN DNR Spring Aerial Imagery 2010/11 - 0.3 meter
Farm Service Agency NAIP Imagery 2008, 2009, 2010 - 1 meter
MN DNR LiDAR Data - 3 meter
USGS National Elevation Data - 10 meter
Alaska Satellite Facility - 10 meter
USDA SSURGO Soils
Metropolitan Mosquito Control District Wetland Data
MN DNR Minnesota County Biological Survey Native Plant Communities
USFWS National Wetland Inventory
USGS National Hydrography Data
MN DNR Public Water Inventory
MN DNR Streams
FEMA Floodplains

Step 1 - Field Data Acquisition
Field training data for photo interpretation projects is extremely important in order to guide the interpretation. The field training data for the east-central project area served three purposes: 1) provided field experience for staff members updating the Minnesota NWI in the local wetland identification and classification, 2) gathered images for use in a guidebook for wetland photo interpretation, and 3) collected training data for the creation of a potential wetlands layer using a Random Forest classification. Within the project area, 12 quads with wetlands representative of those found in the project area were selected for field verification. These quads included urban, residential, and rural areas.

Step 2 - Image Segmentation
The input to the eCognition segmentation process is a tiff layer stack and the raw spring 2010 aerial imagery. The NED 10 meter DEM was resampled to 3 meter resolution after the derived products were created. The SSURGO soils derived products were converted to raster format and added in the stack. All layers were clipped to the spring 2010 aerial image boundary. The final tiff layer stack consisted of the following layers:
1) Combined Curvature
2) Planimetric Curvature
3) Profile Curvature
4) TPI 15
5) TPI 20
6) CTI
7) Palsar
8) SSURGO Hydric Percentage
9) SSURGO Water Regime
10) DEM

Step 3 - Random Forest Classification
The output of the segmentation process consists of two shapefiles; a polygon shapefile of the segments and a point shapefile of the centroids of the polygons. The polygons and points were related using a unique identification number (ID). The point file contains all of the descriptive information from the polygon segments and was used as the input into the random forest classification. Topology was built for the image segments and any issues are corrected. Additional fields (attribute, comments, field verified) were added to the image segments for the photo interpretation process. A random forest classification was run using the point file and training data (described in section 6 above). The random forest classification classified each point based on the training data and assigned a confidence value to each classification. The resulting classification was then joined to the polygons using the unique ID.

Step 4 - Photo interpretation
The classified segments were then used to enhance a more traditional photo interpretation of the imagery. Each of the segments was viewed, edited (merged with neighboring segments of the same class or cut to exclude an area), and assigned a final NWI classification using a variety of imagery and data. A custom object inspector was created to incorporate the information from the random forest classification as well as the soils and Radar classifications. Once a quarter quad was completed, the segments were dissolved based on NWI attribute and run through a quality control process that checks for overlaps, gaps and approved NWI codes.

Step 5 - Draft Data Review
The draft version of the NWI classification for the quarter quad was sent to the MN DNR for review. Once the review was completed, the quarter quad was merged into a seamless state-wide layer. The final NWI layer for the east-central project area was projected to Albers equal area projection for delivery to the U.S. Fish and Wildlife Service.

For more detailed information on the process for east-central Minnesota, please see the technical documentation at files.dnr.state.mn.us/eco/wetlands/nwi_ecmn_technical_documentation.pdf .

These data underwent a minor revision between July 25, 2014 and August 8, 2014. Requested edits since the initial release of the data were compiled into a geodatabase. The data steward reviewed 81 requested edits. Most of the edit requests were submitted by the USFWS National Standards and Support Team through a post-project review. Seventy-three (73) edit requests were accepted and eight (8) edit requests were rejected. Of the accepted edit requests, 53 of these involved adding small wetlands or parts of wetlands (min = 0.03 acres, max = 10.5 acres, mean = 0.89 acres) that were missed in the initial release, four edits involved a change of wetland class, and 16 edits involved a deletion of some portion of a wetland (min = 3.5 acre, max = 10.6 acres, mean = 0.66 acres).
The geometry of the updated data were checked using the Check Geometry tool from ArcGIS and any errors found were fixed using the Repair Geometry tool. A topology was created and the data were checked for gaps and overlaps. All gaps and overlaps were resolved. Finally, the USFWS QAQC tool was run on the data.

July 2016: Minor changes were made to the attribute table and associated look up tables for completeness and consistency with the northeast and southern datasets.
Changes include:
- adding a missing ATTRIBUTE code (PEM1) to the ecmn_cowardin_circ39_lut and ecmn_cowardin_extended tables
- resolving a discrepancy between ATTRIBUTE codes and SPCC_DESC descriptions in the ecmn_cowardin_spcc_lut table

March 2017: Minor changes were made to the attribute table and associated look up tables to comply with USFWS standards.
Changes include:
- Dropped the 'h - Diked/Impounded' Special Modifier for any 'K - Artificially Flooded' Water Regime; replacing any 'Kh' in the ATTRIBUTE field with just 'K'
- This included 4 codes affecting 302 polygons (L2UBKh, PABKh, PEM1Kh, PUBKh)
- Made associated updates to those 4 codes in look up tables: ecmn_cowardin_circ39_lut, ecmn_cowardin_extended, ecmn_cowardin_spcc_lut

2) NORTHEAST REGION

Input Data
MN DNR Spring Aerial Imagery 2009 - 0.5 meter
MN DNR Spring Aerial Imagery 2009 - 0.3 meter
Farm Service Agency NAIP Imagery 2008, 2009, 2010, 2013 - 1 meter
MN DNR LiDAR Data - 3 meter
USDA SSURGO Soils
MN DNR Minnesota County Biological Survey Native Plant Communities
MN DNR Forest Stand Inventory
USFWS National Wetland Inventory
USGS National Hydrography Data
MN DNR Public Water Inventory
MN DNR Streams
FEMA Floodplains

Step 1 - Field Verification
The field training data for the northeast project area served three purposes: 1) to train the interpreters though on-the-ground experience, 2) as site based photos for inclusion in the photo interpretation guide, and 3) to provide quality assurance data for review. The field verification occurred at three different times: fall 2013, spring 2014, and fall 2014. Field verification was completed by DU and MN DNR Resource Assessment staff. The original NWI was used to identify wetland types to field visit for the fall of 2013. A stratified sample of the wetland types was selected based on accessibility and efficiency. A determination of the proper code was made by a consensus of the image interpreters. In cases of confusion, the MN DNR and FWS NWI coordinator were consulted.

Step 2 - Image Segmentation
The input to the eCognition segmentation process is a tiff layer stack and the raw spring 2009 aerial imagery. The DEM and the LiDAR DEM derivatives were processed for each of the 94 buffered HUC10 watershed boundaries. These products were then mosaicked and clipped to the northeast project area boundary, and became input rasters for the layerstacks. The LAS rasters were created from the filtered LAS datasets that intersected each of the 94 watersheds (original extent is the quarter quarter-quad LAS tiles), mosaicked and then clipped to the northeast project area boundary to produce 80 watershed rasters. (This means that the LiDAR derivatives from the DEM were clipped and processed for the full extent of all the original 94 buffered watersheds.) A DEM "No Data" mask was created for each watershed and used to define the area of interest (AOI) as part of the image segmentation process. The final tiff layer stack consisted of the following layers:
1) DEM
2) DEM No Data Mask
3) Slope
4) TPI
5) CTI
6) Average Elevation of 1st Returns
7) Average Intensity of Bare Earth Returns

Step 3 - Photo interpretation
The photo interpreters viewed the segments over the spring 2009 imagery to identify wetland segments. The photo interpreters used the spring imagery, professional knowledge, photointerpretation guide, as well as the summer imagery to assign the NWI code. Additional data layers (e.g. USGS DRG, SSURGO soils, DEM and other LiDAR-derived products) were also available to assist with the NWI classification. Adjacent segments of the same class were merged. Segments that have multiple wetland classes or combine wetland and upland classes were cut into separate polygons to conform to the NWI class boundary. Each watershed of the USGS HUC 10 tiling scheme was interpreted systematically until the entire area had been completed.

Step 4 - Draft Data Review
The draft version of the NWI classification was provided to the MN DNR for review via webservice as well as periodic download of a file geodatabase. The primary data review was provided by the DNR Resource Assessment Office with additional review from MNIT@DNR and the USFWS regional NWI coordinator. Once the review was completed, the data were merged into a seamless state-wide layer.

For more detailed information on the process for northeast Minnesota, please see the technical documentation at files.dnr.state.mn.us/eco/wetlands/nwi_nemn_technical_documentation.pdf .

March 2017: Minor changes were made to the attribute table and associated look up tables to comply with USFWS standards.
Changes include:
- Dropped the 'h - Diked/Impounded' Special Modifier for any 'K - Artificially Flooded' Water Regime; replacing any 'Kh' in the ATTRIBUTE field with just 'K'
- This included 8 codes affecting 308 polygons (L1UBKh, L2UBKh, PABKh, PEM1Kh, PFO1Kh, PSS1Kh, PSS1/EM1Kh, PUBKh)
- Made associated updates to those 8 codes in look up tables: nemn_cowardin_circ39_lut, nemn_cowardin_extended, nemn_cowardin_spcc_lut
- Dropped the 'FO5' part for any 'PSS3/FO5Bg' ATTRIBUTE category to be simply 'PSS3Bq'
- Dropped the 'PSS3/FO5Bq' code in look up tables: nemn_cowardin_circ39_lut, nemn_cowardin_extended, nemn_cowardin_spcc_lut
- Added the 'PSS3/FO5Bq' count (188) to 'PSS3Bq' (9408) in nemn_cowardin_extended look up table

3) SOUTHERN REGION

Input Data
MNDNR Spring Aerial Imagery 2011 - 0.5 meter
Farm Service Agency NAIP Imagery 2008, 2009, 2010 - 1 meter
MNDNR LiDAR Data - 1 meter
USDA SSURGO Soils
MNDNR Minnesota County Biological Survey Native Plant Communities
USFWS National Wetland Inventory
USGS National Hydrography Data
MNDNR Public Water Inventory
MNDNR Streams
FEMA Floodplains

Step 1 - Field Data Acquisition
Field training data for photo interpretation projects was acquired to guide the interpretation. The field training data for the southern project area served two primary purposes; 1) provided field experience for staff members in identification and classification of local wetlands, and 2) gathered images for use in a guidebook for wetland photo interpretation signatures. Approximately 470 wetland sites were visited over three separate excursions (spring 2013, fall 2014, and spring 2014). Sites were selected using the following criteria; 1) representative of the variety of wetland types and imagery signatures, 2) spatially distributed across the entire project area, and 3) consideration of site accessibility.

Step 2 - Data Preprocessing
The MNDNR Resource Assessment Office generated several derivatives from the LiDAR and soils data as an aid in photo-interpretation. These data were provided to SMUMN along with MNDNR spring aerial imagery from 2011 and FSA summer aerial imagery from 2008, 2009, and 2010. Data derivatives included:
1) Slope
2) Curvature
3) Topographic Position Index
4) Compound Topographic Index
5) SSURGO Hydric Percentage
6) SSURGO Water Regime

Step 3 - Wetland Delineation and Classification
Working in county-level tiles, photo-interpreters systematically panned through the imagery looking for identifiable wetland signatures. Wetland boundaries were digitized wetland boundaries on-screen primarily using the spring aerial imagery and LiDAR data in ArcGIS. Each polygon was assigned a wetland classification using a variety of imagery and other ancillary data. Once a work area (county tile) was completed, the attribute for the simplified HGM class was added.

Step4 - Initial Quality Control
Photo-interpreters performed frequent self reviews, checking for errors. This was followed by review by a QAQC specialist. The data were checked to ensure only allowable wetland classes were assigned. Features smaller than the minimum mapping unit were deleted or merged. Adjacent polygons with the same class were merged. The entire data set was visually inspected at 1:10,000 scale to look for classification errors using a system of signature matching. Linework was reviewed at 1:5,000 scale. An automated topology check was performed to identify and fix errors such as gaps and overlaps.

Step 5 - Draft Data Review
The draft version of the NWI classification were posted via web-mapping service for the MNDNR and other project stakeholders to review. Review comments were forwarded to SMUMN to address. Additional field checks were performed for selected sites to provide additional feedback to the photo-interpreters.

Step 6 - Final Processing
Once the review was completed and any required edits made, the data from the county tiles were edge-matched to create a seamless coverage for the entire project area. The NWI verification tool from the USFWS was run on the data repeating many of the automated checks previously performed. All identified errors were fixed and then the final validation was performed.

For more detailed information on the process for southern Minnesota, please see the technical documentation at files.dnr.state.mn.us/eco/wetlands/nwi_smn_technical_documentation.pdf .


July 2016: Minor changes were made to the attribute table and associated look up tables for completeness and consistency with the northeast and east-central datasets.
Changes include:
- adding 51 missing ATTRIBUTE codes to the smn_cowardin_circ39_lut table
- resolving discrepancies between ATTRIBUTE codes and SPCC_DESC descriptions in the smn_cowardin_spcc_lut table

March 2017: Minor changes were made to the attribute table and associated look up tables to comply with USFWS standards.
Changes include:
- Dropped the 'h - Diked/Impounded' Special Modifier for any 'K - Artificially Flooded' Water Regime; replacing any 'Kh' in the ATTRIBUTE field with just 'K'
- This included 1 codes affecting 2 polygons (PUBKh)
- Made associated updates to that code in look up tables: smn_cowardin_circ39_lut, smn_cowardin_extended, smn_cowardin_spcc_lut

Section 3 Spatial Data Organization (not used in this metadata)

Section 4 Coordinate System
Horizontal Coordinate Scheme Universal Transverse Mercator
UTM Zone Number 15
Horizontal Datum NAD83
Horizontal Units meters
Cell Width 0.000100
Cell Height 0.000100

Section 5 Attributes
Overview
Detailed Citation
Table Detail:
NWI_UTM - Reference: Cowardin et al. 1979 (U.S. Fish and Wildlife Service)
Field NameValid ValuesDefinitionDefinition Source
OBJECTID
-
Internal feature number.ESRI
Shape
-
Feature geometry.ESRI
ATTRIBUTE
-
Alphanumeric code identifying the wetland classification of the polygonhttp://www.fws.gov/wetlands/Data/Wetland-Codes.html
WETLAND_TYPE
-
General description of the wetland classification.http://www.fws.gov/wetlands/Data/Wetland-Codes.html
ACRES
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Area of the polygon in acres.Calculated in an UTM zone 15 projection using ESRI's geometry calculator.
HGM_CODE
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Hydrogeomorphic classification codehttp://www.dnr.state.mn.us/eco/wetlands/nwi_proj.html
HGM_NAME
-
Full HGM namehttp://www.dnr.state.mn.us/eco/wetlands/nwi_proj.html
SPCC_DESCenumeratedSimplified Plant Community Classificationhttp://www.dnr.state.mn.us/eco/wetlands/nwi_proj.html
Seasonally Flooded Basin
Wet Meadow
Shallow Marsh
Deep Marsh
Shallow Open Water Community
Peatland
Shrub Wetland
Hardwood Wetland
Coniferous Swamp
Non-Vegetated Aquatic Community
COW_CLASS1
-
Wetland class from the Cowardin codehttp://www.fws.gov/wetlands/Data/Wetland-Codes.html
CIRC39_CLASS
-
Circular 39 wetland classhttp://www.fws.gov/wetlands/documents/classification-of-wetlands-and-deepwater-habitats-of-the-united-states.pdf
HGM_LL_DESC
-
Landscape position and landform from the HGM classhttp://www.dnr.state.mn.us/eco/wetlands/nwi_proj.html
Shape_Length
-
Length of feature in internal units.ESRI
Shape_Area
-
Area of feature in internal units squared.ESRI


Section 6 Distribution
Publisher Minnesota Department of Natural Resources (DNR)
Publication Date 04/30/2015
Contact Person Information Zeb Thomas, GIS Data Systems Coordinator
Minnesota DNR - MIS/GIS Unit
500 Lafayette Rd
Saint Paul, MN  55155
Phone: 651-259-5637
Email: zeb.thomas@state.mn.us
Distributor's Data Set Identifier water_nat_wetlands_inv_2009_2014
Distribution Liability The Minnesota Department of Natural Resources General Geographic Data License Agreement is online: www.dnr.state.mn.us/sitetools/data_software_license.html
Ordering Instructions Visit the web site noted in the online linkage section, or send an email to the Distribution Contact listed in this metadata record
Online Linkage I AGREE to the notice in "Distribution Liability" above. Clicking to agree will either begin the download process or link to download information. See "Ordering Instructions" above for details.

Section 7 Metadata Reference
Metadata Date 03/20/2017
Contact Person Information Steve Kloiber, Wetland Monitoring Coordinator
Minnesota Department of Natural Resources
500 Lafayette Road
St. Paul, MN  55155
Phone: 651-259-5164
Email: steve.kloiber@state.mn.us
Metadata Standard Name Minnesota Geographic Metadata Guidelines
Metadata Standard Version 1.2
Metadata Standard Online Linkage http://www.mngeo.state.mn.us/committee/standards/mgmg/metadata.htm


This page last updated: 03/20/2017
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