Map showing public lands in Jackson County. The map document is 34 inches by 44 inches.

This dataset includes tax lots in Jackson County, Oregon.

The Florida Department of Revenue’s Property Tax Oversight(PTO) program collects parcel level Geographic Information System (GIS) data files every April from all of Florida’s 67 county property appraisers’ offices. This GIS data was exported from these file submissions in August 2025. The GIS parcel polygon features have been joined with thereal property roll (Name – Address – Legal, or NAL)file. No line work was adjusted between county boundaries.The polygon data set represents the information property appraisers gathered from the legal description on deeds, lot layout of recorded plats, declaration of condominium documents, recorded and unrecorded surveys.Individual parcel data is updated continually by each county property appraiser as needed. The GIS linework and related attributions for the statewide parcel map are updated annually by the Department every August. The dataset extends countywide and is attribute by Federal Information Processing Standards (FIPS) code.DOR reference with FIPS county codes and attribution definitions - https://fgio.maps.arcgis.com/home/item.html?id=ff7b985e139c4c7ba844500053e8e185If you discover the inadvertent release of a confidential record exempt from disclosure pursuant to Chapter 119, Florida Statutes, public records laws, immediately notify the Department of Revenue at 850-717-6570 and your local Florida Property Appraisers’ Office. Please contact the county property appraiser with any parcel specific questions: Florida Property Appraisers’ Offices:Alachua County Property Appraiser – https://www.acpafl.org/Baker County Property Appraiser – https://www.bakerpa.com/Bay County Property Appraiser – https://baypa.net/Bradford County Property Appraiser – https://www.bradfordappraiser.com/Brevard County Property Appraiser – https://www.bcpao.us/Broward County Property Appraiser – https://bcpa.net/Calhoun County Property Appraiser – https://calhounpa.net/Charlotte County Property Appraiser – https://www.ccappraiser.com/Citrus County Property Appraiser – https://www.citruspa.org/Clay County Property Appraiser – https://ccpao.com/Collier County Property Appraiser – https://www.collierappraiser.com/Columbia County Property Appraiser – https://columbia.floridapa.com/DeSoto County Property Appraiser – https://www.desotopa.com/Dixie County Property Appraiser – https://www.qpublic.net/fl/dixie/Duval County Property Appraiser – https://www.coj.net/departments/property-appraiser.aspxEscambia County Property Appraiser – https://www.escpa.org/Flagler County Property Appraiser – https://flaglerpa.com/Franklin County Property Appraiser – https://franklincountypa.net/Gadsden County Property Appraiser – https://gadsdenpa.com/Gilchrist County Property Appraiser – https://www.qpublic.net/fl/gilchrist/Glades County Property Appraiser – https://qpublic.net/fl/glades/Gulf County Property Appraiser – https://gulfpa.com/Hamilton County Property Appraiser – https://hamiltonpa.com/Hardee County Property Appraiser – https://hardeepa.com/Hendry County Property Appraiser – https://hendryprop.com/Hernando County Property Appraiser – https://hernandocountypa-florida.us/Highlands County Property Appraiser – https://www.hcpao.org/Hillsborough County Property Appraiser – https://www.hcpafl.org/Holmes County Property Appraiser – https://www.qpublic.net/fl/holmes/Indian River County Property Appraiser – https://www.ircpa.org/Jackson County Property Appraiser – https://www.qpublic.net/fl/jackson/Jefferson County Property Appraiser – https://jeffersonpa.net/Lafayette County Property Appraiser – https://www.lafayettepa.com/Lake County Property Appraiser – https://www.lakecopropappr.com/Lee County Property Appraiser – https://www.leepa.org/Leon County Property Appraiser – https://www.leonpa.gov/Levy County Property Appraiser – https://www.qpublic.net/fl/levy/Liberty County Property Appraiser – https://libertypa.org/Madison County Property Appraiser – https://madisonpa.com/Manatee County Property Appraiser – https://www.manateepao.gov/Marion County Property Appraiser – https://www.pa.marion.fl.us/Martin County Property Appraiser – https://www.pa.martin.fl.us/Miami-Dade County Property Appraiser – https://www.miamidade.gov/pa/Monroe County Property Appraiser – https://mcpafl.org/Nassau County Property Appraiser – https://ncpafl.com/Okaloosa County Property Appraiser – https://okaloosapa.com/Okeechobee County Property Appraiser – https://www.okeechobeepa.com/Orange County Property Appraiser – https://ocpaweb.ocpafl.org/Osceola County Property Appraiser – https://www.property-appraiser.org/Palm Beach County Property Appraiser – https://www.pbcgov.org/papa/index.htmPasco County Property Appraiser – https://pascopa.com/Pinellas County Property Appraiser – https://www.pcpao.org/Polk County Property Appraiser – https://www.polkpa.org/Putnam County Property Appraiser – https://pa.putnam-fl.com/Santa Rosa County Property Appraiser – https://srcpa.gov/Sarasota County Property Appraiser – https://www.sc-pa.com/Seminole County Property Appraiser – https://www.scpafl.org/St. Johns County Property Appraiser – https://www.sjcpa.gov/St. Lucie County Property Appraiser – https://www.paslc.gov/Sumter County Property Appraiser – https://www.sumterpa.com/Suwannee County Property Appraiser – https://suwannee.floridapa.com/Taylor County Property Appraiser – https://qpublic.net/fl/taylor/Union County Property Appraiser – https://union.floridapa.com/Volusia County Property Appraiser – https://vcpa.vcgov.org/Wakulla County Property Appraiser – https://mywakullapa.com/Walton County Property Appraiser – https://waltonpa.com/Washington County Property Appraiser – https://www.qpublic.net/fl/washington/Florida Department of Revenue Property Tax Oversight https://floridarevenue.com/property/Pages/Home.aspx

Part of a set of digitized microfilm of manuscript maps of Iowa townships. Individual maps in the set may include: Native American villages and fields; the first farmsteads, town sites and fields established by settlers; networks of trails; distribution of rivers, woods, prairies, wetlands and springs; and survey data such as creator, date created, and date accepted.

2010 6" orthophotography for Jackson County, MO. DISCLAIMER: These maps are NOT SURVEY ACCURATE. Information is used for tax purposes only. DISCLAIMER OF ACCURACY AND WARRANTIES: Requestor shall and hereby does knowingly accept the data and Information "as-is" and the County expressly disclaims any representation or warranty as to the completeness or accuracy of the data or information. Further, the County expressly disclaims any representation or warranty as to the suitability of the data or information for any specific use intended by requestor. The Jackson County GIS Department maintains maps of ownership parcels for tax purposes. Maps are intended to show as accurately as possible the relationship of neighboring ownership parcels, but are not survey accurate. They reflect the status of the parcel map at the time of printing. RELEASE: Requestor expressly releases and agrees to hold the County, its officials, and its employees, harmless from any and all claims or damages arising out of the use of the data or information, the accuracy of the data or information, or any reliance on the data or information. Requestor expressly agrees to assume all risk for use and reliance on the data and information. Please contact (816) 881-4561 or gis@jacksongov.org for further information.

On November 23, 2011 the Jackson County Board of Commissioners adopted the Greater Bear Creek Valley Regional Plan ("Regional Plan") as an amendment to its comprehensive plan which establishes Urban Reserve Areas (URA) for Central Point, Eagle Point, Medford, Phoenix, and Talent. This amendment establishes URAs to accommodate planned residential, commercial and industrial growth to accommodate a doubling of the current population. In reaching this decision, Jackson County updated its population forecast in the acknowledged comprehensive plan, analyzed buildable land in the Bear Creek Valley, and revised comprehensive plan policies about future urban development.

This U.S. Geological Survey (USGS) data release provides a digital geospatial database for the Geologic map of Precambrian rocks of the Sierra Madre, Carbon County, Wyoming, and Jackson and Routt Counties, Colorado (Houston and Graff, 1994). Attribute tables and geospatial features (points, lines and polygons) conform to the Geologic Map Schema (USGS NCGMP, 2020) and represent the geologic map as published in USGS Miscellaneous Investigations Series Map I-2452. The 890,172-acre map area represents the geology at a publication scale of 1:50,000. References: Houston, R.S., and Graff, P.J., 1994, Geologic map of Precambrian rocks of the Sierra Madre, Carbon County, Wyoming, and Jackson and Routt counties, Colorado: U.S. Geological Survey Miscellaneous Investigations Series Map I-2452, scale 1:50,000, https://doi.org/10.3133/i2452. U.S. Geological Survey National Cooperative Geologic Mapping Program, 2020, GeMS (Geologic Map Schema) - A standard format for the digital publication of geologic maps: U.S. Geological Survey Techniques and Methods, book 11, chap. B10, 74 p., https://doi.org//10.3133/tm11B10.

This dataset is a compilation of county parcel data from Minnesota counties that have opted-in for their parcel data to be included in this dataset.

It includes the following 59 counties that have opted-in as of the publication date of this dataset: Aitkin County, Anoka County, Becker County, Benton County, Big Stone County, Carlton County, Carver County, Cass County, Chippewa County, Chisago County, Clay County, Clearwater County, Cook County, Crow Wing County, Dakota County, Douglas County, Fillmore County, Grant County, Hennepin County, Houston County, Isanti County, Itasca County, Jackson County, Koochiching County, Lac qui Parle County, Lake County, Lake of the Woods County, Lyon County, Marshall County, McLeod County, Mille Lacs County, Morrison County, Mower County, Murray County, Norman County, Olmsted County, Otter Tail County, Pennington County, Pipestone County, Polk County, Pope County, Ramsey County, Red Lake County, Renville County, Rice County, Scott County, Sherburne County, St. Louis County, Stearns County, Steele County, Stevens County, Traverse County, Wabasha County, Waseca County, Washington County, Wilkin County, Winona County, Wright County, and Yellow Medicine County.

If you represent a county not included in this dataset and would like to opt-in, please contact Heather Albrecht (Heather.Albrecht@hennepin.us), co-chair of the Minnesota Geospatial Advisory Council (GAC)’s Parcels and Land Records Committee's Open Data Subcommittee. County parcel data does not need to be in the GAC parcel data standard to be included. MnGeo will map the county fields to the GAC standard.

County parcel data records have been assembled into a single dataset with a common coordinate system (UTM Zone 15) and common attribute schema. The county parcel data attributes have been mapped to the GAC parcel data standard for Minnesota: https://www.mngeo.state.mn.us/committee/standards/parcel_attrib/parcel_attrib.html

This compiled parcel dataset was created using Python code developed by Minnesota state agency GIS professionals, and represents a best effort to map individual county source file attributes into the common attribute schema of the GAC parcel data standard. The attributes from counties are mapped to the most appropriate destination column. In some cases, the county source files included attributes that were not mapped to the GAC standard. Additionally, some county attribute fields were parsed and mapped to multiple GAC standard fields, such as a single line address. Each quarter, MnGeo provides a text file to counties that shows how county fields are mapped to the GAC standard. Additionally, this text file shows the fields that are not mapped to the standard and those that are parsed. If a county shares changes to how their data should be mapped, MnGeo updates the compilation. If you represent a county and would like to update how MnGeo is mapping your county attribute fields to this compiled dataset, please contact us.

This dataset is a snapshot of parcel data, and the source date of the county data may vary. Users should consult County websites to see the most up-to-date and complete parcel data.

There have been recent changes in date/time fields, and their processing, introduced by our software vendor. In some cases, this has resulted in date fields being empty. We are aware of the issue and are working to correct it for future parcel data releases.

The State of Minnesota makes no representation or warranties, express or implied, with respect to the use or reuse of data provided herewith, regardless of its format or the means of its transmission. THE DATA IS PROVIDED “AS IS” WITH NO GUARANTEE OR REPRESENTATION ABOUT THE ACCURACY, CURRENCY, SUITABILITY, PERFORMANCE, MECHANTABILITY, RELIABILITY OR FITINESS OF THIS DATA FOR ANY PARTICULAR PURPOSE. This dataset is NOT suitable for accurate boundary determination. Contact a licensed land surveyor if you have questions about boundary determinations.

DOWNLOAD NOTES: This dataset is only provided in Esri File Geodatabase and OGC GeoPackage formats. A shapefile is not available because the size of the dataset exceeds the limit for that format. The distribution version of the fgdb is compressed to help reduce the data footprint. QGIS users should consider using the Geopackage format for better results.

The DSL SWI Soils dataset represents two selected subsets of the USDA NRCS gNATSGO dataset for Oregon. The “SWI Predominantly Hydric Soil Map Units” layer represents soil map units that are comprised of greater than 50 percent hydric soil components. The Agate-Winlo Soil Map Units layer is associated with vernal pools in Jackson County. These two subsets indicate areas where unmapped wetlands may be present for the purpose of planning, scoping projects, and coordination with DSL.The gridded National Soil Survey Geographic Database (gNATSGO) is a USDA-NRCS-SPSD composite database that provides complete coverage of the best available soils information for all areas of the United States and Island Territories. It was created by combining data from the Soil Survey Geographic Database (SSURGO), State Soil Geographic Database (STATSGO2), and Raster Soil Survey Databases (RSS) into a single seamless ESRI file geodatabase.Consult the gNATSGO home page for more information: https://www.nrcs.usda.gov/resources/data-and-reports/gridded-national-soil-survey-geographic-database-gnatsgo and the web soil survey: http://websoilsurvey.sc.egov.usda.gov/App/HomePage.htm.NRCS description of SSURGO Database:The SSURGO database contains information about soil as collected by the National Cooperative Soil Survey over the course of a century. The information can be displayed in tables or as maps and is available for most areas in the United States and the Territories, Commonwealths, and Island Nations served by the USDA-NRCS. The information was gathered by walking over the land and observing the soil. Many soil samples were analyzed in laboratories. The maps outline areas called map units. The map units describe soils and other components that have unique properties, interpretations, and productivity. The information was collected at scales ranging from 1:12,000 to 1:63,360. More details were gathered at a scale of 1:12,000 than at a scale of 1:63,360. The mapping is intended for natural resource planning and management by landowners, townships, and counties. Some knowledge of soils data and map scale is necessary to avoid misunderstandings.The maps are linked in the database to information about the component soils and their properties for each map unit. Each map unit may contain one to three major components and some minor components. The map units are typically named for the major components. Examples of information available from the database include available water capacity, soil reaction, electrical conductivity, and frequency of flooding; yields for cropland, woodland, rangeland, and pastureland; and limitations affecting recreational development, building site development, and other engineering uses.SSURGO datasets consist of map data, tabular data, and information about how the maps and tables were created. The extent of a SSURGO dataset is a soil survey area, which may consist of a single county, multiple counties, or parts of multiple counties. SSURGO map data can be viewed in the Web Soil Survey or downloaded in ESRI® Shapefile format. The coordinate systems are Geographic. Attribute data can be downloaded in text format that can be imported into a Microsoft® Access® database.https://www.nrcs.usda.gov/resources/data-and-reports/soil-survey-geographic-database-ssurgoNRCS description of STATSGO2 Database:The Digital General Soil Map of the United States or STATSGO2 is a broad-based inventory of soils and non-soil areas that occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped of 1:250,000 in the continental U.S., Hawaii, Puerto Rico, and the Virgin Islands and 1:1,000,000 in Alaska. The level of mapping is designed for broad planning and management uses covering state, regional, and multi-state areas. The U.S. General Soil Map is comprised of general soil association units and is maintained and distributed as a spatial and tabular dataset.The U.S. General Soil Map was developed by the National Cooperative Soil Survey and supersedes the State Soil Geographic (STATSGO) dataset. The dataset was created by generalizing more detailed soil survey maps. Where more detailed soil survey maps were not available, data on geology, topography, vegetation, and climate were assembled and related to Land Remote Sensing Satellite (LANDSAT) images. Soils of similar areas were studied, and the probable classification and extent of the soils were determined.Map unit composition was determined by transecting or sampling areas on the more detailed maps and then statistically expanding the data to characterize the whole map unit.The dataset consists of georeferenced, vector and tabular data. The map data were collected in 1- by 2-degree topographic quadrangle units and merged into a seamless national dataset. The dataset is distributed in state, territorial, and national extents. The spatial units are linked to attributes in the tabular data, which give the proportionate extent of the component soils and their properties.The tabular data contains estimates of physical and chemical soil properties, soil interpretations, and static and dynamic metadata. Most of the tabular data exists in the database as a range of values for soil properties. The values depict the range for the geographic extent of the map unit. For most properties, the data include high, low, and representative values.Spatial data are available in ESRI® shapefile format. Spatial reference is decimal degrees, World Geodetic System 1984 (WGS84). Tabular data are available as ASCII text files (.txt). Fields are pipe delimited, and text is double-quote delimited. A Microsoft® Access® template database is available for use with the tabular data.https://www.nrcs.usda.gov/resources/data-and-reports/description-of-statsgo2-databaseCitation: Soil Survey Staff, Natural Resources Conservation Service, United States Department of Agriculture. Web Soil Survey. Available online at. http://websoilsurvey.nrcs.usda.gov/

Download .zipThe C, D Law Coal Permit Maps county coverage sets were developed using the original mine maps for over 2500 coal mining and reclamation permits issued under Ohio law and finalized (i.e. operations completed) between 1975 and December 2002.

Ohio started issuing coal mining licenses in the 1940s. The earliest license and permit requirements were minimal and did not include submittal of a map or other delineation of the mined area. Significant changes to legal requirements are reflected by the alphabetical designation of each subsequent law revision, i.e., earlier A-law permits (circa 1966) through contemporary D-law permits. The ODNR-Division of Mineral Resources Management (DMRM) has attempted to create as complete a database as possible from available archive records, however, research has identified missing permit files. Thus, this GIS data is known to be incomplete due to the loss of archival records.

The C and D law permit maps were scanned at a density of 200 dots per inch (dpi). The scanned image was then heads-up digitized using Microstation computer aided design software (CAD) to create design files grouped by county location. Data captured within the design file includes permit boundary, affected boundary, test hole locations, and associated attributes. The design file was then "placed-to-ground" using ODNR Division of Geological Survey's "ODNR Land Sub-division Background Design Files" NAD83 State Plane coverages and DOQQ aerial images obtained through the Ohio Geographically Referenced Information Program (OGRIP)/Ohio Department of Administrative Services. The design file was then converted to ARC/INFO coverage and projected to State Plane Ohio Coordinates, NAD83:

Projected coordinate system name: NAD_1983_StatePlane_Ohio_South_FIPS_3402_Feet

Geographic coordinate system name: GCS_North_American_1983

A complete county coverage set consists of five data files for the permit area, affected area, and test hole locations. For example, the coverage for Athens County includes:

athens_c_permitted (Athens County, C-permit area polygons) athens_c_affected (Athens County, C-permit affected area polygons) athens_d_permitted (Athens County, D- permit area polygons) athens_d_affected (Athens County, D-permit affected area polygons) athens_testholes (Athens County, Test Hole points)

In addition to the ArcView shape files in the county data sets, the scanned TIF images for source documents are available at DMRM. The scanned mine map depicts information about the operations conducted, environmental resources, and extracted coal resources. If more detailed information is desired, the available archival record for each captured permit can be accessed at either the State Archives at the Ohio Historical Society or the ODNR-DMRM central office.Contact Information:GIS Support, ODNR GIS ServicesOhio Department of Natural ResourcesDivision of Mineral Resources ManagementAbandoned Mine Land Program2045 Morse Rd, Bldg I-2Columbus, OH, 43229Telephone: 614-265-6462Email: gis.support@dnr.ohio.gov Data Update Frequency: As Needed

This data set is intended for use as a reference map layer for GIS maps and applications. Tax codes are used to calculate the assessor's taxing rate on a specific parcel based on the taxing districts that represent it. In GIS, this dataset is used to create Fire District boundaries, School District boundaries, and City Limits. These data are continually being updated by County Cartography.

Download .zipThe B Law Coal Permit Maps county coverage sets were developed using the original mine maps for coal mining and reclamation permits issued under Ohio law from 1973 through 1976. Approximately 1285 B-Permits were issued during this time period, however, only approximately 414 records could be located and captured at this time. The Division of Mineral Resources Management will continue to search for missing B permit archival records as resources allow; additional B permit data may be added to this existing coverage in the future.

Ohio started issuing coal mining licenses in the 1940s. The earliest license and permit requirements were minimal and sometimes did not include submittal of a map or other delineation of the mined area. Significant changes to legal requirements are reflected by the alphabetical designation of each subsequent law revision, i.e., earlier A-law permits (circa 1966) through contemporary D-law permits. The ODNR-Division of Mineral Resources Management (DMRM) has attempted to create as complete a database as possible from available archive records, however, research has identified missing permit files. Thus, this GIS data is known to be incomplete due to the loss of archival records.

The B law permit maps were scanned at a density of 200 dots per inch (dpi). The scanned image was then heads-up digitized using Microstation computer aided design software (CAD) to create design files grouped by county location. Data captured within the design file includes permit boundary, affected boundary, test hole locations, and associated attributes. The design file was then "placed-to-ground" using ODNR Division of Geological Survey's "ODNR Land Subdivision Background Design Files" NAD83 State Plane coverages and DOQQ aerial images obtained through the Ohio Geographically Referenced Information Program (OGRIP)/Ohio Department of Administrative Services. The design file was then converted to ARC/INFO coverage and projected to State Plane Ohio Coordinates, NAD83:

Projected coordinate system name: NAD_1983_StatePlane_Ohio_South_FIPS_3402_Feet

Geographic coordinate system name: GCS_North_American_1983

A complete county coverage set consists of three data files for the permit area, affected area, and test hole locations. For example, the coverage for Belmont County includes:

belmont_b_permitted (Belmont County, B-permit area polygons) belmont_b _affected (Belmont County, B-permit affected area polygons) belmont_testholes_b (Belmont County, Test Hole points)

In addition to the ArcView shape files in the county data sets, the scanned TIF images for source documents are available at DMRM. The scanned mine map depicts information about the operations conducted, environmental resources, and extracted coal resources. If more detailed information is desired, the available archival record for each captured permit can be accessed at either the State Archives at the Ohio Historical Society or the ODNR-DMRM central office.Contact Information:GIS Support, ODNR GIS ServicesOhio Department of Natural ResourcesDivision of Mineral Resources ManagementAbandoned Mine Land Program2045 Morse Rd, Bldg I-2Columbus, OH, 43229Telephone: 614-265-6462Email: gis.support@dnr.ohio.gov Data Update Frequency: As Needed

This service is intended to work with the Medford Land Information (MLI) mapping application. It includes a tax lots layer for the City of Medford covering the same extent as the TRAKiT database and site address points for Jackson County.

A feature service is also available here: https://gis.ducks.org/datasets/duinc::minnesota-restorable-wetlandsHISTORY: In October 2000, a Restorable Wetlands Working Group formed to begin mapping all of the restorable wetlands in the glaciated tallgrass Prairie Pothole Region of Minnesota and Iowa. Today, fewer than 10% of the original wetlands - once of unparalleled importance to continental waterbird populations - are left in existence. Fortunately, wetlands once drained for agriculture may be restored to many of their historic functions. Restoration of multiple wetland functions is of utmost effectiveness when focused at priority restoration landscapes, therefore data on the historic distribution of wetlands is an integral part of developing strategic regional habitat restoration plans.Opportunistic wetland restorations often fail to attain out expectations for wetland function. Nevertheless, between $70 - $100,000,000 are spent annually in Minnesota for wetland restoration. A strategic plan for wetland restoration can make these expenditures more effective; however, a strategic wetland restoration plan requires a priori information on the distribution and extent of restorable wetlands. The collective goal of the Restorable Wetlands Working Group is the eventual development of a set of multi-agency decision support tools that collectively comprise a comprehensive environmental management plan for wetlands - all based on the same base data layers and developed in joint consultation. An effort is underway to delineate restorable wetlands in all intensively farmed areas of MN and IA.A pilot project determined the best technique to map drained wetlands in agricultural landscapes was photointerpretation. This pilot project evaluated the accuracy of three potential delineation techniques: digital hydric soils databases, digital elevation models, and manual stereoscopic photointerpretation on high-altitude color infrared aerial photographs. The project covered nearly 4,000 square miles of different land forms and wetland characteristics. After mapping was completed, some 1,500 drained wetlands were observed in the field to assess the accuracy of each technique. Only photointerpretation provided reliable results.One area that fell into the pilot study was the Okabena quadrangle in east-central Jackson County in Minnesota. Okabena vividly illustrates the potential of humans to alter the natural landscape. While Okabena historically encompassed more than 8,940 acres of depressional wetland - 27% of the total area of Okabena - after nearly 100 years of agricultural drainage only 1,280 acres of those original wetlands remain, representing an 86% reduction. When empirical models used to estimate duck pairs on individual wetlands are applied to the change from historic to current wetland habitat within Okabena, they estimate a 92% reduction in the habitat potential for common dabbling duck species.The Okabena quadrangle's wetland density once exceeded that of most of the remaining U.S. Prairie Pothole Region. Without strong incentives for wetland conservation and effective methods to delineate high-priority landscapes for restoration, the Okabena quadrangle foretells one possible future for much of the mixed-grass Prairie Pothole Region further west.The Final Status map was completed in 2012.Contact Information:Rex JohnsonUnited States Fish and Wildlife Service21932 State Highway 210Fergus Falls, MN 56537(218) 736-0606rex_johnson@fws.govPhotointerpretationNational Aerial Photography Program (NAPP) (1:40,000 scale) color infrared (CIR) photographs acquired in April and May, 1991 and 1992, were viewed in stereo pairs at 5X magnification using a Cartographic Engineering stereoscope. A Mylar overlay was mounted on one photo of each stereo pair and a rectangular work area was delineated on the overlay comprising one-quarter of a USGS 7.5 min topographic quadrangle. A minimum of 4 fiduciary marks were placed on the overlay to enable geographic rectification of digital data covering the work area. One fiduciary mark was placed at the corner of the US Geological Survey (USGS) 7.5 min quadrangle and others at conspicuous road intersections near the other 3 corners of the work area. Drained depressional wetlands were delineated on the Mylar overlay within the work area using a 6X0 (.13 mm diameter) rapidograph pen and indelible ink. Collateral data was consulted during the delineation process. These data consisted of published county soil surveys and descriptions of hydric soils, USDA Farm Service Agency compliance slides (aerial 35 mm slides) acquired in 1993 (immediately after a period of intense precipitation), USGS 7.5 min topographic maps, and National Wetlands Inventory (NWI) maps. Black and white NAPP photographs (1:40,000 scale) acquired primarily in August and September, 1996, were reviewed and rejected as collateral data because they were acquired under dry conditions.Other specific photointerpretation protocols were:1. All drained depressional wetlands, regardless of size, were delineated.2. NWI-delineated wetlands with a Ad@ (partially drained) modifier in the classification code were not delineated unless the original delineation failed to encompass the complete historic wetland area.3. NWI-delineated wetlands that did not contain a Ad@ modifier in the classification code were delineated if the original delineation did not include the entire historic wetland area.4. Wetlands identified on NWI maps which did not exhibit wetland characteristics (i.e. hydrology, hydrophytes, etc) on new (1992) CIR photography were delineated even if no evidence of drainage was apparent.5. Wetlands not delineated on NWI maps, and in cropland, were delineated.6. Wetlands not delineated on NWI maps, and in grassland, were not delineated unless evidence of drainage was observed on the aerial photo.7. Wetlands not delineated on NWI maps, and in trees, were not delineated.Tolerances:Scanned line data were converted to a polygon using a 6 m fuzzy tolerance. Open polygons were manually closed and cleaned with a 1.2 m fuzzy tolerance which was used for all subsequent data processing.Datafile Description and Attribute Definitions[County_Name]_nwx - National Wetlands Inventory delineations (see https://www.fws.gov/program/national-wetlands-inventory/wetlands-mapper for NWI delineation standards). Note: Wetland classifications in these data often differ slightly from the original NWI classification. NWI wetland classifications were simplified for these data by removing mixed classes and multiple special modifiers, and by standardizing letter case. In each case of mixed classes and multiple special modifiers, the first class or special modifier was retained.AttributesRestorable - 0 = Islands and the Universal Polygon100 = Restorable depressional wetland delineated using protocols described aboveCounty Name – The name of the county in which the center of the polygon is located.State Name – The name of the state.FIPS – The FIPS code.