County town, range, section, quarter/quarter, quarter polygons, town, range, section, government lot polygons, or private claim polygons.More Metadata

No matter where you are in Michigan, you can find public hunting land. This interactive map application that now works on mobile devices, contains the most up-to-date information to help you plan your next hunting trip, and includes both public hunting land, as well as private land open to the public for hunting.

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/ .

The first basin-wide map of large stands of invasive Phragmites australis (common reed) in the coastal zone was created through a collaboration between the U.S. Geological Survey and Michigan Tech Research Institute (Bourgeau-Chavez et al 2013). This data set represents a revised version of that map and was created using multi-temporal PALSAR data and Landsat images from 2016-2017. In addition to Phragmites distribution, the data sets shows several land cover types including urban, agriculture, forest, shrub, emergent wetland, forested wetland, and some based on the dominant plant species (e.g., Schoenoplectus, Typha). The classified map was validated using over 400 field visits.This map covers the coastal regions of Michgan along the southern portion Lake Huron including Saginaw Bay, Lake St. Clair, Lake Erie, and northeastern Ohio.

This dataset provides a land cover map focused on peatland ecosystems in the upper peninsula of Michigan. The map was produced at 12.5-m resolution using a multi-sensor fusion (optical and L-band SAR) approach with imagery from Landsat-5 TM and ALOS PALSAR collected between 2007 and 2011. A random forest classifier trained with polygons delineated from field data and aerial photography was used to determine pixel classes. Accuracy assessment based on field-sampled sites show high overall map accuracy (92%).

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

BY USING THIS WEBSITE OR THE CONTENT THEREIN, YOU AGREE TO THE TERMS OF USE. The recreation lands coverage is a single county wide coverage containing recreation land and educational institution information compiled from several sources including: the State of Michigan, Oakland County Parks & Recreation, Oakland County cities, villages, and townships (CVTs), school districts, and the Huron-Clinton Metropolitan Authority (HCMA). Polygons of the parcels are used to represent the recreation/education lands. The hard copy source formats included listings, maps, and aerial photography. Key attributes include: Name, Agency, Acres, and various activities associated with the feature.

A survey map of a small Eastern portion of Bruce Township and part of Sugar Island in Chippewa County, Michigan, measured in 1840 and 1845.

This data is intended as a reference material of street and alley vacations, but not designed for survey, accurate positioning, or legal documents. It is created as polygon feature class, vacation information based on field measurements, types of Right of Way, and citations of Journal of the Common Council (J.C.C.) and the plat Liber and Page is listed under the column titled 'Sub_Plat'. The paper maps of the Street and Alley Vacation, the raster layer version of those maps (Linen Map Markup Mosaic), and the Detroit parcel layer are used as base maps to create this data.

The street and alley vacations were recorded from 1831 to 2022 throughout the whole city, and it will be updated weekly. The existed and/or active street and alley vacations are ready to view, the authors are working on pending and historical records.

Spatial Reference: WGS 1984 Web Mercator Auxiliary Sphere

A web application showing how much land is protected in Michigan, and the reason it's protected. For methods, see the data layer link below.Data Layer: https://duinc.maps.arcgis.com/home/item.html?id=2b5858b776034c70bac56bb296652fedWeb Map: https://duinc.maps.arcgis.com/home/item.html?id=b4325008662a407fb5346e219801a569Data Manager: Jes SkillmanUpdate Frequency: No planned updates.Last Updated 2/12/2021

This geospatial dataset depicts ownership patterns of forest land across Michigan, circa 2019. The data sources are listed below. The first seven sources of data supersede the final data source. The final data source is modeled from Forest Inventory and Analysis points from 2012-2017 and the most up-to-date publicly available boundaries of federal, state, and tribal lands.1.MI_State_Boundary_Census_Gov_2019.shp (State of MI boundary) clipped from cb_2019_us_state_500k from https://www.census.gov/geographies/mapping-files/time-series/geo/cartographic-boundary.html2.NPS_Land_Resources_Division_MI.shp clipped from NPS_-_Land_Resources_Division_Boundary_and_Tract_Data_Service-shp taken from https://public-nps.opendata.arcgis.com/datasets/nps-land-resources-division-boundary-and-tract-data-service/data?layer=1Published December 12, 2019This service depicts National Park Service tract and boundary data that was created by the Land Resources Division. NPS Director's Order #25 states: "Land status maps will be prepared to identify the ownership of the lands within the authorized boundaries of the park unit. These maps, showing ownership and acreage, are the 'official record' of the acreage of Federal and non-federal lands within the park boundaries. While these maps are the official record of the lands and acreage within the unit's authorized boundaries, they are not of survey quality and not intended to be used for survey purposes." As such this data is intended for use as a tool for GIS analysis. It is in no way intended for engineering or legal purposes. The data accuracy is checked against best available sources which may be dated and vary by location. NPS assumes no liability for use of this data. The boundary polygons represent the current legislated boundary of a given NPS unit. NPS does not necessarily have full fee ownership or hold another interest (easement, right of way, etc...) in all parcels contained within this boundary. Equivalently NPS may own or have an interest in parcels outside the legislated boundary of a given unit. In order to obtain complete information about current NPS interests both inside and outside a unit’s legislated boundary tract level polygons are also created by NPS Land Resources Division and should be used in conjunction with this boundary data. To download this data directly from the NPS go to https://irma.nps.gov/App/Portal/Home Property ownership data is compiled from deeds, plats, surveys, and other source data. These are not engineering quality drawings and should be used for administrative purposes only. The National Park Service (NPS) shall not be held liable for improper or incorrect use of the data described and/or contained herein. These data and related graphics are not legal documents and are not intended to be used as such. The information contained in these data is dynamic and may change over time. The data are not better than the original sources from which they were derived. It is the responsibility of the data user to use the data appropriately and consistent within the limitations of geospatial data in general and these data in particular. The related graphics are intended to aid the data user in acquiring relevant data; it is not appropriate to use the related graphics as data. The National Park Service gives no warranty, expressed or implied, as to the accuracy, reliability, or completeness of these data. It is strongly recommended that these data are directly acquired from an NPS server and not indirectly through other sources which may have changed the data in some way. Although these data have been processed successfully on a computer system at the National Park Service, no warranty expressed or implied is made regarding the utility of the data on another system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty. This disclaimer applies both to individual use of the data and aggregate use with other data. Terms of UseProperty ownership data is compiled from deeds, plats, surveys, and other source data. These are not engineering quality drawings and should be used for administrative purposes only. The National Park Service shall not be held liable for improper or incorrect use of the data described and/or contained herein. These data and related graphics are not legal documents and are not intended to be used as such. The information contained in these data is dynamic and may change over time. The data are not better than the original sources from which they were derived. It is the responsibility of the data user to use the data appropriately and consistent within the limitations of geospatial data in general and these data in particular. The related graphics are intended to aid the data user in acquiring relevant data; it is not appropriate to use the related graphics as data. The National Park Service gives no warranty, expressed or implied, as to the accuracy, reliability, or completeness of these data. It is strongly recommended that these data are directly acquired from an NPS server and not indirectly through other sources which may have changed the data in some way. Although these data have been processed successfully on a computer system at the National Park Service, no warranty expressed or implied is made regarding the utility of the data on another system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty. This disclaimer applies both to individual use of the data and aggregate use with other data.3.Isle Royale.shp only Isle Royale clipped from MI_State_Boundary_Census_Gov_2019.shp4.FWSInterest_MI.shp (U.S. Fish and Wildlife Service) clipped from FWSInterest from FWSInterest_Apr2020.zipfrom https://www.fws.gov/gis/data/CadastralDB/index_cadastral.html (being moved on 6/26/2020)Use inttype1 = OThis data layer depicts lands and waters administered by the U.S. Fish and Wildlife Service (USFWS) in North America, U.S. Trust Territories and Possessions. It may also include inholdings that are not administered by USFWS. The primary source for this information is the USFWS Realty program.5.surfaceownership_MI.shp (U.S. National Forest Service) clipped from S_USA.SurfaceOwnership.gdb and downloaded fromhttps://data.fs.usda.gov/geodata/edw/datasets.phphttps://data.fs.usda.gov/geodata/edw/datasets.php?xmlKeyword=surfaceownershiprefreshed May 26, 2020Used NFSLandU_4 field and surfaceO_3 and surfaceO_3 to identify NFS parcelsAn area depicting ownership parcels of the surface estate. Each surface ownership parcel is tied to a particular legal transaction. The same individual or organization may currently own many parcels that may or may not have been acquired through the same legal transaction. Therefore, they are captured as separate entities rather than merged together. This is in contrast to Basic Ownership, in which the surface ownership parcels having the same owner are merged together. Basic Ownership provides the general user with the Forest Service versus non-Forest Service view of land ownership within National Forest boundaries. Surface Ownership provides the land status user with a current snapshot of ownership within National Forest boundaries.6.MichiganDNR_02062020.shp (State of Michigan) from the State of MI delivered @ email on 5/14/2020Has State forests, State Wildlife areas, and State parks.7.The previous public ownership layers supersede this Sass et al. (2020) layer.In Sass et al. (2020), the nonforest areas are masked out.Identification_Information:Citation:Citation_Information:Originator: Sass, Emma M.Originator: Butler, Brett J.Originator: Markowski-Lindsay, Marla Publication_Date: 2020Title:Estimated distribution of forest ownership across the conterminous United States – geospatial datasetGeospatial_Data_Presentation_Form: raster digital dataPublication_Information:Publication_Place: Fort Collins, COPublisher: Forest Service Research Data ArchiveEight values of ownership type:1 = Family (Private): Owned by families, individuals, trusts, estates, family partnerships, and other unincorporated groups of individuals that own forest land. FIACode 45.2 = Corporate (Private): Owned by corporations. FIA Code 41.3 = TIMO/REIT (Private): Owned by Timber Investment Management Organizations or Real Estate Investment Trusts. Included in FIA Code 414 = Other Private (Private): Owned by conservation and natural resource organizations, unincorporated partnerships and associations. FIA Codes 42-43.5 = Federal (Public): Owned by the federal government. FIA Codes 11-13, 21-25.6 = State (Public): Owned by a state government. FIA Code 31.7 = Local (Public): Owned by a local government. FIA Code 32.8 = Tribal: Owned by Native American tribes. FIA Code 44.8.FIA inventory units developed by FIA, 2020

BY USING THIS WEBSITE OR THE CONTENT THEREIN, YOU AGREE TO THE TERMS OF USE. The DevelopmentAuthority polygon feature class identifies certain types of entities that encourage development/redevelopment in designated areas. This feature class currently represents Downtown Development Authorities (DDA), Tax Increment Finance Authorities (TIFA), and Local Development Finance Authorities (LDFA); however, it will also depict Corridor Improvement Authorities (CIA) and Brownfield Redevelopment Authorities (BRA) in the future. These five types of authorities have the ability to capture tax increment financing (TIF). The features were digitized using legal descriptions, parcel lists, and maps that were provided to the State of Michigan Office of the Great Seal and/or Oakland County Equalization by the authority. The key attributes are Name (official name of the authority), Type (the type of development authority), and DevelopmentPlan (yes/no indicating if the feature represents an area that is part of a development plan and can caputre tax increment financing).Tax Increment Financing is a tool used to promote redevelopment and community improvement projects by channeling funding toward projects in targeted areas. TIF is captured from the increase of property values from a base year. Millage rates from taxing jurisdictions are applied to the increased value. The resulting tax revenue is directed to the authority, rather than the appropriate jurisdiction. Beginning in 1994, taxing jurisdictions have the option to "opt out" of having its taxes captured by the authority. Also since 1994, school taxes may no longer be captured unless they are necessary to make payments on existing eligible obligations. For more information about TIF, see Michigan Department of Treasury's Tax Increment Financing FAQ web page at http://www.michigan.gov/treasury/0,1607,7-121-3218---F,00.html. The State of Michigan has adopted enabling legislation to allow TIF through five types of authorities. Each type of authority has a focus relating to development/redevelopment: Downtown Development Authority (PA 197 of 1975) Correct and prevent deterioration in business districtsEncourage historic preservationPromote economic growth of the districts Tax Increment Finance Authority (PA 450 of 1980)Prevent urban deteriorationEncourage economic development and activityEncourage neighborhood revitalization and historic preservationClosed to new applicants since 1987Allows the development of virtually any type of land use Local Development Finance Authority (PA 281 of 1986)Encourage local developmentPromote conditions of employmentPromote economic growthLimited to business activities involving:ManufacturingAgricultural processingHigh-technology activitiesEnergy productionBusiness incubators Brownfield Redevelopment Authority (PA 381 of 1996)Promote revitalization, redevelopment, and reuse of certain propertyFocus on tax reverted, blighted, or functionally obsolete propertyMDEQ must approve brownfield redevelopment areas Corridor Improvement Authority (PA 281 of 2005)Correct and prevent deterioration in business districtsEncourage historic preservationPromote economic growth of the districtsMust be adjacent to a road classified as an arterial or collectorThese quasi-public entities are created by resolution through a community's governing body. CIA and LDFA boundaries may cross municipal boundaries. In the case of these multi-jurisdictional authorities, both communities must pass resolutions establishing authority. There is currently only one Joint LDFA (Cities of Southfield and Troy) and there are no CIAs in Oakland County. When the community establishes the authority, it must also define the geographic boundaries in which it will operate. DDAs and CIAs are authorized to levy and collect taxes through a special assessment on all properties within the authority boundary. After the authority and its boundaries are established, the authority creates a tax increment financing and development plan. The plan estimates the amount of tax increment financing that will be captured and lists specific projects on which it will be spent. It also defines the development area where the tax increment financing and projects will occur. The development area must be completely within the authority boundary; however, it may be coincident with the authority boundary. An authority may contain multiple development areas, each with its own development and tax increment financing plan. BRAs normally designate development areas as a one or two parcels for a specific development project, while the other types of authorities define development areas as a larger area. Also, LDFAs are only allowed to capture TIF from parcels in a permitted use, such as manufacturing. There may be both eliglible and inelgible parcels within a development area; however, the inelgible parcels do not participate in TIF capture. The base year used to calculate the amount of tax increment financing is set when the development plan is adopted. If the development plan is expanded at a later date, the base year could be reset for the entire development area or the capture could be calculated using multiple base years. The source for the base year was the tax billing code used by Oakland County Equalization. When no tax billing code was available (for communities that don't use the county's assessing system), the community was contacted to obtain the base year. When two separate authorities overlap, each authority can establish overlapping development areas. The authority that first created the development area has first claim on tax increment financing capture. Authority boundaries are represented using multiple features when the development area is not coincident with the authority boundary. One feature represents the development area and a second feature represents the remainder of the authority district that is not part of the development area. Multiple features are also used to represent authorities that have multiple development areas or development areas that have multiple base years. Brownfield Redevelopment Authorities are unique in that the authority boundaries are generally defined as the entire municipality. For this reason, the non-development areas of BRA's have been excluded from this data. The following list shows communities in Oakland County that have established a BRA: City of Auburn Hills City of Birmingham City of Farmington City of Farmington Hills City of Ferndale City of Hazel Park Charter Township of Highland Village of Holly City of Madison Heights Village of Milford County of Oakland City of Oak Park City of Pontiac City of Rochester City of Rochester Hills Charter Twp of Royal Oak City of Royal Oak City of Southfield City of Troy Charter Township of Waterford Source documents for the boundary of each feature were obtained from the State of Michigan Office of the Great Seal, Oakland County Equalization, and the Oakland County Treasurer's office. These could be in the form of a legal description, parcel list, and/or map. For several boundaries, multiple sources were available and conflicted with each other. When this occurred, hierarchy was given to the legal description, then a parcel list, over the map, and the conflict is noted in the Comments field. However, if a parcel was shown in a parcel list, but not described in the authority based on the legal description, then it was still shown in the authority.It should also be noted that legal descriptions were not digitized using exact coordinate geometry. Instead, features were created by referencing the legal description to snap vertices to parcels, right-of-way, section corners, subdivisions, and lots. Features digitized from a legal description or map included road and railroad rights-of-way as it was described or shown in the document.For vague legal descriptions and parcel lists, right-of-way was addressed uniquely for each authority. Some source documents had statements that all or half of the surrounding right-of-way is to be included in the boundary, but some did not address right-of-way at all. In these cases, right-of-way was addressed distinctly for each authority based on the type of authority and the source documents with the method used recorded in the Comments field. The data will be updated on an "as needed" basis when authorities amend their development plans or new authorities are established. Oakland County Equalization and the Oakland County Treasurer's Office will notify and forward the source documents of necessary revisions to Oakland County Planning and Economic Development Services who is the custodian of the feature class. Communities will be contacted annually to verify that the districts have not changed without the knowledge of county departments. In particular, county departments may not be aware of BRA development projects when no TIF is captured. Lastly, because the tax parcel feature class is revised periodically and it is important for the features to be coincident with the tax parcel feature class, the development authority feature class will also be updated annually to correct conflicts due to parcel shifting.

This data set provides a land use/land cover map of the Ji-Parana River Basin in the state of Rondonia, Brazil produced from the digital classification of eight Landsat 7-ETM+ scenes from 1999 acquired from the Tropical Rain Forest Information Center (TRFIC) at Michigan State University. Nine land cover classes covering the Ji-Parana Basin were identified. There is one GeoTiff file with this data set.

This dataset provides the spatial distribution of vegetation types, soil carbon, and physiographic features in the Imnavait Creek area, Alaska. Specific attributes include vegetation, percent water, glacial geology, soil carbon, a digital elevation model (DEM), surficial geology and surficial geomorphology. Data are also provided on the research grids for georeferencing. The map data are from a variety of sources and encompass the period 1970-06-01 to 2015-08-31.

BY USING THIS WEBSITE OR THE CONTENT THEREIN, YOU AGREE TO THE TERMS OF USE. A spatial representation of Tax Parcels. Key attributes include KeyPIN. The KeyPIN is the unique parcel identification number used to link the tax parcel to the parcel attributes which are stored and maintained in Oakland County land records.There is no definite accuracy related to parcel boundaries. The information shown on these maps is for representation purposes only and is not intended to be a legally recorded map or survey. The information was compiled from a number of sources including recorded deeds, plats, tax maps surveys and other public records and data. Users of this data should consult the information sources listed above for verification of the information.

This dataset comes from the Department of Licensing and Regulatory Affairs' Office of Land Survey and Remonumentation (OLSR). See Act 345 of 1990: State Survey and Remonumentation Act for more information.The system of record was queried for approved locations where grid coordinates were provided. Records with coordinates outside the state's geographical boundary were retained (34 locations). The columns "DMS LAT" and "DMS LONG" were added to the extraction table and populated with data from fields "Latitude N" and "Longitude W" and formatted to DMS2. The data was exported as feature class using geoprocessing tool "Convert Coordinate Notation," geographic coordinate system WGS 1984 Web Mercator (auxiliary sphere).This dataset was last updated June 6, 2022, with quarterly updates to begin in 2023.More Metadata

This map presents the percentage of Coastal Wetlands that are protected for each state or province in the Great Lakes Basin (except Québec, due to data limitations). The percentages vary from a high of 91% to a low of 4%, but the number of coastal wetland acres also varies widely. The five states with the highest total wetland acreage have protected between 37% and 54% of coastal wetlands, while Ontario has protected 17%. *Coastal Wetlands defined here as connected to the Great Lakes and >2 ha (5 acres) in size.Data SourcesWe used the following database for coastal wetland area:Great Lakes Coastal Wetlands 2004 Polygons (Great Lakes Coastal Wetland Consortium): https://www.glc.org/wp-content/uploads/2016/10/CWC-GreatLakesCoastalWetlandsInventory-Metadata.pdf We used the following databases for protected area: Nature Conservancy Canada (data agreement) Commission for Environmental Cooperation (databasin.org)- Canada Protected Terrestrial Areas 2012 (Ontario)Ontario GeoHub- Ontario Federal Protected Lands (Ontario) 2018:PAD-US (Protected Areas Database of the U.S.) 2018. CARL (Conservation and Recreation Lands) 2017. Feature Service for Conservation and Recreation Lands in the Great Lakes Atlantic Region (Wisconsin, Michigan, Ohio, Indiana, Iowa). This layer contains fee lands, preserves, designated lands and other protected lands. This layer does not contain easements.Consultations with regional land experts (The Nature Conservancy GIS Managers) for the states of Michigan, Ohio, Indiana, Illinois and Wisconsin.

The Tropical Rain Forest Information Center (TRFIC) is part of NASA's Federation of Earth Science Information Partners. TRFIC is led by scientists at the Basic Science and Remote Sensing Initiative (BSRSI) at Michigan State University in partnership with the Radar Science Group at the Jet Propulsion Laboratory.

TRFIC provides up-to-date information on tropical forest resources -- their status, the rate at which they are disappearing, current scientific research results, policy-related issues, and more. Data holdings include a large archive of Landsat imagery data, forest cover maps produced from Landsat imagery, derived products which depict the spatial extent and rate of deforestation, and special information services, including the Rain forest Report Card.

TRFIC's major focus is on tropical forests of South America (Brazilian Amazon) and Southeast Asia (Indochina), although data holdings also include imagery for North America, Africa, and other regions.

TRFIC map products for the Brazilian Amazon include forest cover, major classification types, percent of deforestation, vegetation and transition ecosystem classes, and mean carbon per vegetation type for the Legal Amazon Basin, and forest cover maps for the following states: Acre, Amapa, Amazonas, Maranhao, MatoGrosso, Para, Rondonia, Roraima, and Tocantins.

TRFIC map products for Southeast Asia include forest cover maps for Indochina and forest cover maps for component countries (i.e., Cambodia, Loas, Myanmar, Thailand, and Vietnam).

Derived TRFIC data products for Brazilian Amazon and Indochina produced from the analysis of Landsat MSS and TM satellite data show land use and land cover change in these regions. The following data values exist in the derived data sets: forest, deforested, regrowing forest, water, cloud, and cloud shadow.

This data set is a change analysis of 1996-era C-CAP land cover and 2001-era C-CAP land cover for the State of Michigan, in the Great Lakes Region of the U.S. This product contains the land cover information for both dates and can be recoded to show changed areas, unchanged areas, areas of gain for a particular land cover class, and areas of loss.