Web mapping application containing parcel, address, and zoning information for Sioux Falls, South Dakota.The City of Sioux Falls Parcel Finder provides access to interactive parcel and address information such as parcel id, owner name, legal description, land use, easements, building photos, zoning, preliminary information, and more. In addition, Parcel Finder has the following features:Search by address, intersection, county parcel id, city parcel id, and owner name.Ability to select features.Selected features can be exported to a csv, or other file types.Layers in the layer list can be turned on and off, and reordered.The layer list, by default, contains the address layer that can be turned on to label the house/building number.Add data from the City of Sioux Falls data repository.Add data featuring Demographic and Lifestyle topics.Measuring tools are back!Drawing tools, allowing you to customize your map, suitable for printing.Expanding printing options.

This spatial data set provides information pertaining to the known land use and disturbance history for lands within the March 2018 administrative boundary of the North Unit of Badlands National Park, South Dakota. Land use and disturbance history presented here are not a comprehensive record of all potential land uses and disturbances but rather a record of known and documented land uses and disturbances based on the best available information. Additional land use and disturbance information may exist but due to time and budget constraints may not have been discovered during the research and development of this data set. The information in this data set was gathered through a variety of sources including but not limited to communication with National Park Service staff, historical documents, land patent records, online information searches, aerial imagery, historical photographs, and spatial data repositories. Data are presented as polygon features, each with a unique area number, its total area (in acres) and the percent of the park the area covers. Polygons were delineated based on existing GIS layers in park records, or, when these were not available, they were digitized using ESRI Arc Map 10.5.1 in conjunction with USDA Natural Resource Conservation Service NAIP orthoimagery based on written descriptions of locations (e.g., Township and Range Survey System) or maps in information sources. History of each polygon is described for one or more of five land use or disturbance types: cultivation, structures, excavation, grazing, and other disturbance. Each land use or disturbance type has six attribute fields. The first field indicates if there is evidence of the land use or disturbance type in the polygon. "Yes" indicates there is evidence and a

This data set depicts federal lands having restrictions on access or activities -- that is, lands mangaed by the National Park Service, Defense Department, or Energy Department -- in western North America. The data set was created by reformatting and merging state- and province-based ownership data layers originally acquired from diverse sources (including state GAP programs, USBLM state offices and other sources). For each original dataset 3 additional fields, "Pub_Pvt", "CA_OWN", and "SOURCE" were added and populated based on the specific ownership information contained in the source data. The original coverages were then merged based on the "CA_OWN" field. Finally, NPS, DOD, and DOE lands were selected out of the ownership layer. All work was completed in AcMap 8.3. This product and all source data are available online from SAGEMAP: http://sagemap.wr.usgs.gov.

Data are intended for use in rural areas and therefore do not include land cover in cities and towns. Land cover classes (tree cover, other land cover, or water) were mapped using an object-based image analysis approach and supervised classification. These data are designed for conducting geospatial analyses and for producing cartographic products. In particular, these data are intended to depict the location of tree cover in the county. The mapping procedures were developed specifically for agricultural landscapes that are dominated by annual crops, rangeland, and pasture and where tree cover is often found in narrow configurations, such as windbreaks and riparian corridors. Because much of the tree cover in agricultural areas of the United States occurs in windbreaks and narrow riparian corridors, many geospatial datasets derived from coarser-resolution satellite data (such as Landsat), do not capture these landscape features. This dataset is intended to address this particular data gap. These data can be downloaded by county at the Forest Service Research Data Archive. Nebraska: https://www.fs.usda.gov/rds/archive/catalog/RDS-2019-0038 South Dakota: https://www.fs.usda.gov/rds/archive/catalog/RDS-2022-0068 North Dakota: https://www.fs.usda.gov/rds/archive/catalog/RDS-2022-0067 A Kansas dataset was also developed using the same methods and is located at: Kansas data download: https://www.fs.usda.gov/rds/archive/catalog/RDS-2019-0052 Kansas map service: https://data-usfs.hub.arcgis.com/documents/high-resolution-tree-cover-of-kansas-2015-map-service/explore

The USGS Protected Areas Database of the United States (PAD-US) is the nation's inventory of protected areas, including public open space and voluntarily provided, private protected areas, identified as an A-16 National Geospatial Data Asset in the Cadastral Theme (http://www.fgdc.gov/ngda-reports/NGDA_Datasets.html). PAD-US is an ongoing project with several published versions of a spatial database of areas dedicated to the preservation of biological diversity, and other natural, recreational or cultural uses, managed for these purposes through legal or other effective means. The geodatabase maps and describes public open space and other protected areas. Most areas are public lands owned in fee; however, long-term easements, leases, and agreements or administrative designations documented in agency management plans may be included. The PAD-US database strives to be a complete “best available” inventory of protected areas (lands and waters) including data provided by managing agencies and organizations. The dataset is built in collaboration with several partners and data providers (http://gapanalysis.usgs.gov/padus/stewards/). See Supplemental Information Section of this metadata record for more information on partnerships and links to major partner organizations. As this dataset is a compilation of many data sets; data completeness, accuracy, and scale may vary. Federal and state data are generally complete, while local government and private protected area coverage is about 50% complete, and depends on data management capacity in the state. For completeness estimates by state: http://www.protectedlands.net/partners. As the federal and state data are reasonably complete; focus is shifting to completing the inventory of local gov and voluntarily provided, private protected areas. The PAD-US geodatabase contains over twenty-five attributes and four feature classes to support data management, queries, web mapping services and analyses: Marine Protected Areas (MPA), Fee, Easements and Combined. The data contained in the MPA Feature class are provided directly by the National Oceanic and Atmospheric Administration (NOAA) Marine Protected Areas Center (MPA, http://marineprotectedareas.noaa.gov ) tracking the National Marine Protected Areas System. The Easements feature class contains data provided directly from the National Conservation Easement Database (NCED, http://conservationeasement.us ) The MPA and Easement feature classes contain some attributes unique to the sole source databases tracking them (e.g. Easement Holder Name from NCED, Protection Level from NOAA MPA Inventory). The "Combined" feature class integrates all fee, easement and MPA features as the best available national inventory of protected areas in the standard PAD-US framework. In addition to geographic boundaries, PAD-US describes the protection mechanism category (e.g. fee, easement, designation, other), owner and managing agency, designation type, unit name, area, public access and state name in a suite of standardized fields. An informative set of references (i.e. Aggregator Source, GIS Source, GIS Source Date) and "local" or source data fields provide a transparent link between standardized PAD-US fields and information from authoritative data sources. The areas in PAD-US are also assigned conservation measures that assess management intent to permanently protect biological diversity: the nationally relevant "GAP Status Code" and global "IUCN Category" standard. A wealth of attributes facilitates a wide variety of data analyses and creates a context for data to be used at local, regional, state, national and international scales. More information about specific updates and changes to this PAD-US version can be found in the Data Quality Information section of this metadata record as well as on the PAD-US website, http://gapanalysis.usgs.gov/padus/data/history/.) Due to the completeness and complexity of these data, it is highly recommended to review the Supplemental Information Section of the metadata record as well as the Data Use Constraints, to better understand data partnerships as well as see tips and ideas of appropriate uses of the data and how to parse out the data that you are looking for. For more information regarding the PAD-US dataset please visit, http://gapanalysis.usgs.gov/padus/. To find more data resources as well as view example analysis performed using PAD-US data visit, http://gapanalysis.usgs.gov/padus/resources/. The PAD-US dataset and data standard are compiled and maintained by the USGS Gap Analysis Program, http://gapanalysis.usgs.gov/ . For more information about data standards and how the data are aggregated please review the “Standards and Methods Manual for PAD-US,” http://gapanalysis.usgs.gov/padus/data/standards/ .

This dataset combines the work of several different projects to create a seamless data set for the contiguous United States. Data from four regional Gap Analysis Projects and the LANDFIRE project were combined to make this dataset. In the northwestern United States (Idaho, Oregon, Montana, Washington and Wyoming) data in this map came from the Northwest Gap Analysis Project. In the southwestern United States (Colorado, Arizona, Nevada, New Mexico, and Utah) data used in this map came from the Southwest Gap Analysis Project. The data for Alabama, Florida, Georgia, Kentucky, North Carolina, South Carolina, Mississippi, Tennessee, and Virginia came from the Southeast Gap Analysis Project and the California data was generated by the updated California Gap land cover project. The Hawaii Gap Analysis project provided the data for Hawaii. In areas of the county (central U.S., Northeast, Alaska) that have not yet been covered by a regional Gap Analysis Project, data from the Landfire project was used. Similarities in the methods used by these projects made possible the combining of the data they derived into one seamless coverage. They all used multi-season satellite imagery (Landsat ETM+) from 1999-2001 in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform) to model natural and semi-natural vegetation. Vegetation classes were drawn from NatureServe's Ecological System Classification (Comer et al. 2003) or classes developed by the Hawaii Gap project. Additionally, all of the projects included land use classes that were employed to describe areas where natural vegetation has been altered. In many areas of the country these classes were derived from the National Land Cover Dataset (NLCD). For the majority of classes and, in most areas of the country, a decision tree classifier was used to discriminate ecological system types. In some areas of the country, more manual techniques were used to discriminate small patch systems and systems not distinguishable through topography. The data contains multiple levels of thematic detail. At the most detailed level natural vegetation is represented by NatureServe's Ecological System classification (or in Hawaii the Hawaii GAP classification). These most detailed classifications have been crosswalked to the five highest levels of the National Vegetation Classification (NVC), Class, Subclass, Formation, Division and Macrogroup. This crosswalk allows users to display and analyze the data at different levels of thematic resolution. Developed areas, or areas dominated by introduced species, timber harvest, or water are represented by other classes, collectively refered to as land use classes; these land use classes occur at each of the thematic levels. Raster data in both ArcGIS Grid and ERDAS Imagine format is available for download at http://gis1.usgs.gov/csas/gap/viewer/land_cover/Map.aspx Six layer files are included in the download packages to assist the user in displaying the data at each of the Thematic levels in ArcGIS. In adition to the raster datasets the data is available in Web Mapping Services (WMS) format for each of the six NVC classification levels (Class, Subclass, Formation, Division, Macrogroup, Ecological System) at the following links. http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Class_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Subclass_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Formation_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Division_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Macrogroup_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_Ecological_Systems_Landuse/MapServer

This spatial data set provides information pertaining to the known land use and disturbance history for lands within the March 2018 administrative boundary of Wind Cave National Park, South Dakota. Land use and disturbance history presented here are not a comprehensive record of all potential land uses and disturbances but rather a record of known and documented land uses and disturbances based on the best available information. Additional land use and disturbance information may exist but due to time and budget constraints may not have been discovered during the research and development of this data set. The information in this data set was gathered through a variety of sources including but not limited to communication with National Park Service staff, historical documents, land patent records, online information searches, aerial imagery, historical photographs, and spatial data repositories. Data are presented as polygon features, each with a unique area number, its total area (in acres) and the percent of the park the area covers. Polygons were delineated based on existing GIS layers in park records, or, when these were not available, they were digitized using ESRI Arc Map 10.5.1 in conjunction with USDA Natural Resource Conservation Service NAIP orthoimagery based on written descriptions of locations (e.g., Township and Range Survey System) or maps in information sources. History of each polygon is described for one or more of five land use or disturbance types: cultivation, structures, excavation, grazing, and other disturbance. Each land use or disturbance type has six attribute fields. The first field indicates if there is evidence of the land use or disturbance type in the polygon. "Yes" indicates there is evidence and a

no abstract provided

Credit report of South Dakota Federal Property contains unique and detailed export import market intelligence with it's phone, email, Linkedin and details of each import and export shipment like product, quantity, price, buyer, supplier names, country and date of shipment.

11/22/2024- County-wide road updates were completed in Golden Valley and Billings Counties. Intersecting routes throughout the state were cartographically realigned in preparation of MIRE intersections 6/27/2024 - The data was prepared for HPMS submittal which included updated 2023 AADT values and to keep certain segments consistent with HPMS segments, mainly sample sections and the NHS, values of "BOTH", "NHS" and "SAMPLE" were added to the field HPMS_ROUTE_ID to distinguish these segments from other segments. 3/19/2024 - Miscellaneous updates were done in Dunn County. County wide updates to Grand Forks and Golden Valley counties along with route realignments at intersections throughout the state.12/04/2023 - County wide updates to Walsh, Dunn and Grand Forks Counties and various updates to county/local roads throughout the state including street names in Westhope8/23/2023 - Function Class changes were updated in McLean and Mountrail Counties. Function Class updates also occurred in the cities of Fargo, Valley City, West Fargo and Williston. County-wide updates completed for: Towner, Cavalier, Pembina, Pierce, Benson, Ramsey. 2022 AADTs updated. A road was also removed in Bottineau County at the request off a landowner.5/19/22 - Dunn County contacted the NDDOT with data updates ,Rolette County was updated, and the 2021 AADT's were updated. 2/14/22 - Contacted by the Dunn County Road Dept., updates were made on newly paved road segments. 1/20/2022 - Since the August 2021 update, Morton, Stark, Hettinger, Bowman, Adams, Slope, Grant and Sioux Counties have been updated using 2020 imagery. Surface type has been checked and updated on all functionally classified roads statewide. Function Class changes have been made in the Bismarck/Mandan Metro, Grand Forks County and Burleigh County.6/15/21 - Since the 2019 update, trails and seldom used trails were updated statewide using 2018,and 2019 imagery. Steele, Traill and Griggs Counties have also been updated using 2020 imagery. Surface type has been checked and updated on all functionally classified roads statewide New roads added includes roads in the Fargo, West Fargo, Grand Forks, Jamestown, Bismarck, Mandan, Minot, Dickinson, Watford City and Williston. Ownership on Federal jurisdiction roads were also updated based on an dataset received for FHWA in conjunction with the HPMS submittal. HPMS (Highway Performance Monitoring System) fields were also added in an effort to integrate the roads county data into HPMS and MIRE (Model Inventory Roadway Elements). 9/14/20 - Added the following fields - AADT, AADT_YR, HPMS_MAINTENANCE_OPERATIONS, HPMS_THROUGH_LANES, FUNCTIONAL_CLASS (replaces FUNCTION_CLASS)8/13/19 - The following counties were updated by using a variety of aerial photography: Eddy, Foster and Barnes. Seldom used trails have been added to Barnes, Benson, Billings, Bottineau, and Bowman Counties. Mercer County had (2) 61STAvenues, this has been corrected.12/26/18 - The following counties have had their roads updated by a variety of aerial photography, McHenry, Wells, Kidder, Cass (with aid of Cass county website) and McKenzie (with aid of McKenzie County GIS Coordinator)8/14/18 - Counties updated using 2017 NAIP Imagery are Ward, Mountrail, Burke and Renville counties. Seldom used trails are also being digitized into the dataset. They are being added as counties are being checked, so it will take some time for all seldom used trails to be added statewide. Also since the last update, all local roads that are in the corporate boundaries have been broken at the boundaries so it is easier to query to determine which roads go with each community.5/21/18 - removed CITY_INT_ID column - no longer used because of CITY_FIPS and HPMS_URBAN_CODE attributes. Removed SERVICE_LEVEL field, never used/maintained.4/19/18 - added HPMS_OWNERSHIP and HPMS_FACILITY fields for HPMS submittal1/24/18 - added CITY_FIPS and HPMS_URBAN_CODE attributes/domains. These columns will replace CITY_INT_ID and SOURCE_ID columns (eventually).11/15/17 - Williams, Divide and Bottineau counties have been updated. Great effort has been taken to update attributes and QC null fields. Functional Classified roads in Bismarck and Mandan have been updated as have local roads in Bismarck, Mandan, Williston, Fargo – West Fargo and Minot. 1/25/17 - started to maintain roads in Esri's Road and Highways. The shapes now contain measures in miles along with the associated linear referencing/roads and highways fields. Removed INSET_ASSOC field and added COUNTY_FIPS field.Updates include the counties of Emmons, Logan, McIntosh, Lamoure, Dickey, Ransom, Sargent and Richland. These counties were updated using a combination of the available NAIP aerials, the DES aerials, and by car within the insets. In addition to these updates, the whole county dataset was edited using Data Reviewer checks. The checks ran included unnecessary nodes, non-linear segments, invalid geometry, Duplicate vertices with a tolerance of .5 meters, polyline closes of self, checked for cutbacks using a 15 degree minimum angle, checked for polyline length check using a distance less than 10 meters, checked for multipart lines, inspected dangles with a tolerance of 10 meters, and checked for orphans. All checks were inspected and fixed where appropriate.7/16/14 - updates include: Traill, Barnes, Stutsman, Kidder, Bowman, Slope, Stark, Hettinger, Adams, Grant, Sioux and Morton. These datasets were updated using a combination of the available NAIP aerials, the DES aerials, and by car within the insets.10/22/12 - city streets were updated in Bismarck, Dickinson, Minot and Williston. GIS data from the city of Bismarck was used to update Bismarck, GIS data and 2012 aerial photography was used to update the city of Williston, Minot’s city map and the 2010 aerial photography from Ward County was used to update Minot, and 2011 aerial photography and Dickinson’s "working" city map was used to update Dickinson. The counties updated were Williams, Burke, Bottineau, Mountrail, Ward, Wells, Eddy, Foster, Griggs, Steele, and Cass. At the time of this updated, approximately 50% of Stutsman and 50% of Traill Counties are updated. Williams, Bottineau, Ward, and Mountrail roads were inspected from the air and the 2009 NAIP photos were also used to assist the updates. The roads in Williams County were also recoded to match Williams County naming conventions. Williams County CADD map which is on the Williams county web site was used in updating the road names. In Ward County, the 2010 image from Ward County was used to assist in updating Ward County. The 2010 NAIP photos were used to update Wells, Eddy, Foster, Griggs and Steele Counties. Cass was updated with the assistance of the Cass County GIS layer and the 2011 Cass county imagery. 10/3/2011 - County roads were edited in the cities of Fargo, West Fargo, Horace, Minot, Bismarck, Devils Lake, Grafton, Williston, Valley City, and Dickinson. Also, a part of Ward and Mchenry Counties was edited and the county of Renville has been updated. The business routes through Bismarck and Jamestown were also edited. 5/9/2011 - Updated streets in Bismarck, Mandan, Jamestown, Dickinson, West Fargo ( not quite finished yet), and Valley City. Also, corrected the north - south roads in Township 144N Ranges 49 - 53 E, (in Traill County) 10/5/10 - The original Roads_County data was maintained in two separate ArcInfo coverages and then combined each year and exported to the NDHUB infrastructure. These two coverages have now been combined into one SDE feature class and is being edited within the SDE environment. The following changes have been made to feature class. Deleted all the A1 and A2 Fields so a person would have to hunt back and forth to find a road name. Road names consist of the following fields: RTE_ID, STR_TYP, SUF_DIR, & LAN_DIR. The CMC route numbers were moved from the A1_ prefixed fields to the CMC field to better track the CMC route. Created a County Highway field so we can enter the county road number. It consists of the counties name and number. This is still a work in progress. Created FS_RD_Number and FS_RD_Name fields to better track Forest Service roads. Created Bia-RD_Number and BIA_RD_Name fields to better track Bureau of Indian Affairs roads. The following field changes are used for NDDOT specific processes: Created a service level field which is something that may be used in the future. Currently it contains how Walsh County prioritizes their roads. Created a Through and Connecting Route field so we can so select routes through the towns and cities. This was created exclusively for the county base maps. Created an Inset Associated field. This was created so the information in the rd_misc would come into the county routes. In the future, it is planned to be deleted. 6/18/09 - Updated county routes from aerial observation and photo interpretation using 2003, 2005, 2006 NAIP photos and 2008 photography from Designs camera. Counties updated were Golden Valley, Billings, McKenzie, Dunn, Mercer, Oliver, McLean, Sheridan and Burleigh. City streets were rectified in these counties using the 2003 NAIP photos. Observations were performed by Steven Nelson. 4/17/08 - Updated road surface types in NE. Rolette, Pierce, Benson, Towner, Ramsey, Cavalier, Pembina, Walsh, Grand Forks and Nelson from the 2006 aerial observations by Dewaine Olson 2/13/07 - Updated via 2004 NAIP photos: Barnes, Cass, Eddy, Foster, Griggs, Kidder, Steele, Stutsman, Traill, Wells. Combined Misc Roads and County Roads. Blank fields mean unknown attribute. Use P_STREET_NAME for dynamic labeling. We are also in the process of removing all proposed roads. 12/28/05 - Counties updated: Emmons, Logan, Mcintosh, Lamoure, Dickey, Ransom, Sargent, Richland, Divide, Williams, Burke, Mountrail, Ward, Renville, Bottineau, and Mchenry This data came from the NDDOT's Mapping Section. The original data was digitized from hand scribed maps and registered

Originally produced by the Farm Security Administration, these are georeferenced aerial images from Morton County, North Dakota. Historic print images housed at the Mandan, North Dakota ARS Long-Term Agricultural Research facility were digitized, georeferenced, and processed for use in both professional and consumer level GIS applications, or in photo-editing applications. The original images were produced by the Farm Security Administration to monitor government compliance for farm land agreements. Current applications include assessing land use change over time with regard to erosion, land cover, and natural and man-made structures. Not for use in high precision applications. Resources in this dataset:Resource Title: 1938_AZY_3_89. File Name: 1938_AZY_3_89_0.zipResource Description: Contains IIQ, JPG, OVR, XML, AUX, and TIF files processed in ArcMap / ArcGIS that can be used in ArcGIS applications, or in other photo or geospatial applications. Resource Title: 1938 Mosaic Index. File Name: 1938_mosaic_index_1.zipResource Description: This is the index key for the 1938 Mandan aerial images from Morton County, ND. To find the geographic location for each uploaded 1938 image, consult this map. File titles are arranged as follows: Year_Area_Roll_Frame. The mosaic map displays Roll_Frame coordinates to correspond to these images. Contains TIF, OVR, JPG, AUX, IIQ, and XML files. Resource Title: 1938_AZY_5_113. File Name: 1938_AZY_5_113_2.zipResource Description: Contains IIQ, JPG, OVR, XML, AUX, and TIF files processed in ArcMap / ArcGIS.

The USGS Protected Areas Database of the United States (PAD-US) is the nation's inventory of protected areas, including public land and voluntarily provided private protected areas, identified as an A-16 National Geospatial Data Asset in the Cadastre Theme ( https://communities.geoplatform.gov/ngda-cadastre/ ). The PAD-US is an ongoing project with several published versions of a spatial database including areas dedicated to the preservation of biological diversity, and other natural (including extraction), recreational, or cultural uses, managed for these purposes through legal or other effective means. The database was originally designed to support biodiversity assessments; however, its scope expanded in recent years to include all open space public and nonprofit lands and waters. Most are public lands owned in fee (the owner of the property has full and irrevocable ownership of the land); however, permanent and long-term easements, leases, agreements, Congressional (e.g. 'Wilderness Area'), Executive (e.g. 'National Monument'), and administrative designations (e.g. 'Area of Critical Environmental Concern') documented in agency management plans are also included. The PAD-US strives to be a complete inventory of U.S. public land and other protected areas, compiling “best available” data provided by managing agencies and organizations. The PAD-US geodatabase maps and describes areas using thirty-six attributes and five separate feature classes representing the U.S. protected areas network: Fee (ownership parcels), Designation, Easement, Marine, Proclamation and Other Planning Boundaries. An additional Combined feature class includes the full PAD-US inventory to support data management, queries, web mapping services, and analyses. The Feature Class (FeatClass) field in the Combined layer allows users to extract data types as needed. A Federal Data Reference file geodatabase lookup table (PADUS3_0Combined_Federal_Data_References) facilitates the extraction of authoritative federal data provided or recommended by managing agencies from the Combined PAD-US inventory. This PAD-US Version 3.0 dataset includes a variety of updates from the previous Version 2.1 dataset (USGS, 2020, https://doi.org/10.5066/P92QM3NT ), achieving goals to: 1) Annually update and improve spatial data representing the federal estate for PAD-US applications; 2) Update state and local lands data as state data-steward and PAD-US Team resources allow; and 3) Automate data translation efforts to increase PAD-US update efficiency. The following list summarizes the integration of "best available" spatial data to ensure public lands and other protected areas from all jurisdictions are represented in the PAD-US (other data were transferred from PAD-US 2.1). Federal updates - The USGS remains committed to updating federal fee owned lands data and major designation changes in annual PAD-US updates, where authoritative data provided directly by managing agencies are available or alternative data sources are recommended. The following is a list of updates or revisions associated with the federal estate: 1) Major update of the Federal estate (fee ownership parcels, easement interest, and management designations where available), including authoritative data from 8 agencies: Bureau of Land Management (BLM), U.S. Census Bureau (Census Bureau), Department of Defense (DOD), U.S. Fish and Wildlife Service (FWS), National Park Service (NPS), Natural Resources Conservation Service (NRCS), U.S. Forest Service (USFS), and National Oceanic and Atmospheric Administration (NOAA). The federal theme in PAD-US is developed in close collaboration with the Federal Geographic Data Committee (FGDC) Federal Lands Working Group (FLWG, https://communities.geoplatform.gov/ngda-govunits/federal-lands-workgroup/ ). 2) Improved the representation (boundaries and attributes) of the National Park Service, U.S. Forest Service, Bureau of Land Management, and U.S. Fish and Wildlife Service lands, in collaboration with agency data-stewards, in response to feedback from the PAD-US Team and stakeholders. 3) Added a Federal Data Reference file geodatabase lookup table (PADUS3_0Combined_Federal_Data_References) to the PAD-US 3.0 geodatabase to facilitate the extraction (by Data Provider, Dataset Name, and/or Aggregator Source) of authoritative data provided directly (or recommended) by federal managing agencies from the full PAD-US inventory. A summary of the number of records (Frequency) and calculated GIS Acres (vs Documented Acres) associated with features provided by each Aggregator Source is included; however, the number of records may vary from source data as the "State Name" standard is applied to national files. The Feature Class (FeatClass) field in the table and geodatabase describe the data type to highlight overlapping features in the full inventory (e.g. Designation features often overlap Fee features) and to assist users in building queries for applications as needed. 4) Scripted the translation of the Department of Defense, Census Bureau, and Natural Resource Conservation Service source data into the PAD-US format to increase update efficiency. 5) Revised conservation measures (GAP Status Code, IUCN Category) to more accurately represent protected and conserved areas. For example, Fish and Wildlife Service (FWS) Waterfowl Production Area Wetland Easements changed from GAP Status Code 2 to 4 as spatial data currently represents the complete parcel (about 10.54 million acres primarily in North Dakota and South Dakota). Only aliquot parts of these parcels are documented under wetland easement (1.64 million acres). These acreages are provided by the U.S. Fish and Wildlife Service and are referenced in the PAD-US geodatabase Easement feature class 'Comments' field. State updates - The USGS is committed to building capacity in the state data-steward network and the PAD-US Team to increase the frequency of state land updates, as resources allow. The USGS supported efforts to significantly increase state inventory completeness with the integration of local parks data in the PAD-US 2.1, and developed a state-to-PAD-US data translation script during PAD-US 3.0 development to pilot in future updates. Additional efforts are in progress to support the technical and organizational strategies needed to increase the frequency of state updates. The PAD-US 3.0 included major updates to the following three states: 1) California - added or updated state, regional, local, and nonprofit lands data from the California Protected Areas Database (CPAD), managed by GreenInfo Network, and integrated conservation and recreation measure changes following review coordinated by the data-steward with state managing agencies. Developed a data translation Python script (see Process Step 2 Source Data Documentation) in collaboration with the data-steward to increase the accuracy and efficiency of future PAD-US updates from CPAD. 2) Virginia - added or updated state, local, and nonprofit protected areas data (and removed legacy data) from the Virginia Conservation Lands Database, provided by the Virginia Department of Conservation and Recreation's Natural Heritage Program, and integrated conservation and recreation measure changes following review by the data-steward. 3) West Virginia - added or updated state, local, and nonprofit protected areas data provided by the West Virginia University, GIS Technical Center. For more information regarding the PAD-US dataset please visit, https://www.usgs.gov/gapanalysis/PAD-US/. For more information about data aggregation please review the PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual . A version history of PAD-US updates is summarized below (See https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-history for more information): 1) First posted - April 2009 (Version 1.0 - available from the PAD-US: Team pad-us@usgs.gov). 2) Revised - May 2010 (Version 1.1 - available from the PAD-US: Team pad-us@usgs.gov). 3) Revised - April 2011 (Version 1.2 - available from the PAD-US: Team pad-us@usgs.gov). 4) Revised - November 2012 (Version 1.3) https://doi.org/10.5066/F79Z92XD 5) Revised - May 2016 (Version 1.4) https://doi.org/10.5066/F7G73BSZ 6) Revised - September 2018 (Version 2.0) https://doi.org/10.5066/P955KPLE 7) Revised - September 2020 (Version 2.1) https://doi.org/10.5066/P92QM3NT 8) Revised - January 2022 (Version 3.0) https://doi.org/10.5066/P9Q9LQ4B Comparing protected area trends between PAD-US versions is not recommended without consultation with USGS as many changes reflect improvements to agency and organization GIS systems, or conservation and recreation measure classification, rather than actual changes in protected area acquisition on the ground.

no abstract provided

description:

This data layer depicts North Dakota Game and Fish Department Pronghorn Antelope Range Map.

The purpose of the data is to provide a comprehensive list and spatial location of North Dakota Pronghorn Antelope Range Map. This dataset is primarily used as a framework data layer for use in GIS and other mapping applications and does not represent a land survey of the range.

Constraints:
Not to be used for navigation, for informational purposes only. See Game and Fish disclaimer for more information.

This data layer depicts North Dakota Game and Fish Department Pronghorn Antelope Range Map.

The purpose of the data is to provide a comprehensive list and spatial location of North Dakota Pronghorn Antelope Range Map. This dataset is primarily used as a framework data layer for use in GIS and other mapping applications and does not represent a land survey of the range.

Constraints:
Not to be used for navigation, for informational purposes only. See Game and Fish disclaimer for more information.

This series of three-period land use land cover (LULC) datasets (1975, 2000, and 2013) aids in monitoring change in West Africa’s land resources (exception is Tchad at 4 kilometers). To monitor and map these changes, a 26 general LULC class system was used. The classification system that was developed was primarily inspired by the “Yangambi Classification†(Trochain, 1957). This fairly broad class system for LULC was used because the classes can be readily identified on Landsat satellite imagery. A visual photo-interpretation approach was used to identify and map the LULC classes represented on Landsat images. The Rapid Land Cover Mapper (RLCM) was used to facilitate the photo-interpretation using Esri’s ArcGIS Desktop ArcMap software. Citation: Trochain, J.-L., 1957, Accord interafricain sur la définition des types de végétation de l’Afrique tropicale: Institut d’études centrafricaines.

The National Park Service (NPS), in conjunction with the Biological Resources Division (BRD) of the U.S. Geological Survey (USGS), has implemented a program to "develop a uniform hierarchical vegetation methodology" at a national level. The program will also create a geographic information system (GIS) database for the parks under its management. The purpose of the data is to document the state of vegetation within the NPS service area during the 1990's, thereby providing a baseline study for further analysis at the Regional or Service-wide level. The vegetation at Jewel Cave National Monument was mapped using 1:16,000 scale U.S. Forest Service Color Aerial Photography acquired August 22, 1993. The mapping classification used two separate classification systems. All natural vegetation used the National Vegetation Classification System (NVCS) as a base. The vegetation classification was created after extensive on site sampling and numerical analysis. The vegetation map units were derived from the vegetation classification. Other non-natural or cultural mapping units used the Anderson Level II classification system. The mapped area includes a buffer around the Monument boundary.

This mapping effort originates from a long-term vegetation monitoring program that is part of a larger Inventory and Monitoring (I&M) program started by the National Park Service (NPS). I&M goals are, among others, to map the vegetation of all national parks and monuments and provide a baseline inventory of vegetation. The I&M program currently works in close cooperation with the Biological Resources Division (BRD) of the United States Geological Survey (USGS). The USGS/BRD continues overall management and oversight of all ongoing mapping efforts in close cooperation with the NPS.

The purposes of the mapping effort are varied and include the following: Provides support for NPS Resources Management. Promotes vegetation-related research for both NPS and USGS/BRD. Provides support for NPS Planning and Compliance. Adds to the information base for NPS Interpretation. Assists in NPS Operations.

The location of the mapping is Jewel Cave National Monument and about a 2 mile environs around Monument Boundaries - Black Hills, South Dakota.

Jewel Cave National Monument was responsible for obtaining permission from adjacent land owners for property access for sampling purposes. Most of the private lands were under some form of grazing or farming. Consequently, sampling on these lands was not necessary. The remainder of the lands within the mapping area are U.S. Forest Service Lands so permission was not necessary. To reduce duplicating previous work and to help in our effort we collected existing vegetation reports and maps from the staff at Jewel Cave National Monument. These materials were referenced during the mapping process and the information contained in them was incorporated where it was deemed useful. Because soils also affect the distribution of vegetation, soil maps and soil descriptions were also obtained as reference. These were not converted to a digital file. Digital elevation models (DEM) were obtained to create slope and aspect maps that helped in determining vegetation community distribution. The sampling approach used in this mapping effort was typical of small park sampling, where all polygons within the park boundary are sampled. Two levels of field data gathering were conducted in this park; plots and observations. Plots represented the most intensive sampling of the landscape and used TNC's 'Plot Form'. Observations consisted of brief descriptions and were designed to obtain a quick overview of the landscape without spending a large amount of time at each sample site. Observation points used the 'Observation Form' data sheet. Examples of both 'Plot' and 'Observation' forms are included in the companion report by TNC. Initially, plots were used to describe the vegetation of the park. A total of 28 plots were obtained from July 29 through August 1, 1996. These plots were used by TNC to describe the vegetation associations found within the park. These descriptions are in the companion report by TNC. Map Validation A field trip was conducted in May of 1997 to assess the initial mapping effort and to refine map classes.

Information for this metadata was obtained from the site "http://biology.usgs.gov/npsveg/jeca/metajecaspatial.html" and put into NASA Directory Interchange Format.

State Government Tax Collections, Property Taxes in North Dakota was 5818.00000 Thous. of $ in January of 2024, according to the United States Federal Reserve. Historically, State Government Tax Collections, Property Taxes in North Dakota reached a record high of 5818.00000 in January of 2024 and a record low of 1133.00000 in January of 1988. Trading Economics provides the current actual value, an historical data chart and related indicators for State Government Tax Collections, Property Taxes in North Dakota - last updated from the United States Federal Reserve on July of 2025.

Mineral resource occurrence data covering the world, most thoroughly within the U.S. This database contains the records previously provided in the Mineral Resource Data System (MRDS) of USGS and the Mineral Availability System/Mineral Industry Locator System (MAS/MILS) originated in the U.S. Bureau of Mines, which is now part of USGS. The MRDS is a large and complex relational database developed over several decades by hundreds of researchers and reporters. While database records describe mineral resources worldwide, the compilation of information was intended to cover the United States completely, and its coverage of resources in other countries is incomplete. The content of MRDS records was drawn from reports previously published or made available to USGS researchers. Some of those original source materials are no longer available. The information contained in MRDS was intended to reflect the reports used as sources and is current only as of the date of those source reports. Consequently MRDS does not reflect up-to-date changes to the operating status of mines, ownership, land status, production figures and estimates of reserves and resources, or the nature, size, and extent of workings. Information on the geological characteristics of the mineral resource are likely to remain correct, but aspects involving human activity are likely to be out of date.

The Web-enabled Landsat Data (WELD) project is collaboration between the United States Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center and academic partner South Dakota State University Geographic Information Science Center of Excellence. It is funded by NASA's Making Earth System Data Records for Use in Research Environments, with significant USGS cost sharing.

This resource is a repository of the annual subsurface drainage (so-called "Tile Drainage") maps for the Bois de Sioux Watershed (BdSW), Minnesota and the Red River of the North Basin (RRB), separately. The RRB maps cover a 101,500 km2 area in the United States, which overlies portions of North Dakota, South Daokta, and Minnesota. The maps provide annual subsurface drainage system maps for recent four years, 2009, 2011, 2014, and 2017 (In 2017, the subsurface drainage maps including the Sentinel-1 Synthetic Aperture Radar as an additional input are also provided). Please see Cho et al. (2019) in Water Resources Research (WRR) for full details.

Map Metadata (Proj=longlat +datum=WGS84) Raster value key: 0 = NoData, masked by non-agricultural areas (e.g. urban, water, forest, or wetland land) and high gradient cultivated crop areas (slope > 2%) based on the USGS National Land Cover Dataset (NLCD) and the USGS National Elevation Dataset 1 = Undrained (UD) 2 = Subsurface Drained (SD)

Preferred citation: Cho, E., Jacobs, J. M., Jia, X., & Kraatz, S. (2019). Identifying Subsurface Drainage using Satellite Big Data and Machine Learning via Google Earth Engine. Water Resources Research, 55. https://doi.org/10.1029/2019WR024892

Corresponding author: Eunsang Cho (ec1072@wildcats.unh.edu)