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

Campgrounds on State Forest Land are public campgrounds located in the Michigan State Forest System. This layer shows the point locations of state forest campgrounds located throughout Michigan's Upper and northern Lower Peninsulas. This layer contains the location, name, and phone number for each campground.

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

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 southern portion of Lake Michigan.

This Michigan Department of Environment, Great Lakes, and Energy (EGLE) Wetland Inventory Map is intended to be used as one tool to assist in identifying wetlands and provides only potential and approximate location of wetlands and wetland conditions. EGLE produced this map from the following data obtained from other agencies or organizations.The National Wetland Inventory (NWI) conducted by the United States Fish and Wildlife Service through interpretation of aerial photos and topographic data. Land Cover as mapped by the Michigan Resource Inventory System (MIRIS), Michigan Department of Natural Resources, through interpretation of aerial photographs.Hydric Soils as mapped by the United States Department of Agriculture, Natural Resource Conservation Service (NRCS).This layer is not intended to be used to determine the specific locations and jurisdictional boundaries of wetland areas subject to regulation under Part 303, Wetlands Protection, of the Natural Resources and Environmental Protection Act, 1994 PA 451, as amended.Only an on-site evaluation performed by EGLE in accordance with Part 303 shall be used for jurisdictional determinations. A permit is required from EGLE to conduct certain activities in wetlands regulated under Part 303.More information regarding this layer, including how to obtain a copy can be accessed atwww.michigan.gov/wetlands.

Property Gateway is a leading-edge Internet tool built to provide free and fee-based online access to Oakland County's land and property information including tax parcel reports and maps. Reports and maps can be purchased via a credit card transaction; recurring users request a business account. Visit Property Gateway, HERE.

description: PLSS Townships and Sections dataset current as of unknown. Public Land Survey Sections - originally created from USGS Topographic Maps.; abstract: PLSS Townships and Sections dataset current as of unknown. Public Land Survey Sections - originally created from USGS Topographic Maps.

A survey map of islands in Lake George between Bruce Township and Sugar Island in Chippewa County, Michigan, measured in 1977.

BY USING THIS WEBSITE OR THE CONTENT THEREIN, YOU AGREE TO THE TERMS OF USE. A spatial representation of generalized Oakland County community master plans. These polygons were digitized from each of Oakland's 62 community's future land use map in their master plan. The data was completed in March of 2006 and will be updated as each community amends their plan. The key attribute is Composite Plan representing generalized, countywide future land uses.This data depicts a future land use based on each community's master plan as currently adopted. The data will be updated each time a community amends their master plan. Below is a list recording the master plan and date of adoption that was used to digitize each community. Township of Addison Addison Township Land Use Master Plan - 7/9/2002 City of Auburn Hills City of Auburn Hills Master Land Use Plan - 11/7/2002 Auburn Hills Opkyke Road Corridor Study - 2/1/2007 Auburn Hills Collier Road Area Land Use Study - 1/3/2008 City of Berkley City of Berkley, Michigan Master Plan Update - 1/23/2007 Village of Beverly Hills Village of Beverly Hills Master Plan - 3/28/2007 Village of Bingham Farms Village of Bingham Farms Master Plan - 9/13/2004 City of Birmingham The Birmingham Plan - 1/1/1979 Township of Bloomfield Charter Township of Bloomfield Master Plan Update - 3/26/2007 City of Bloomfield Hills Master Plan of Land Use City of Bloomfield Hills - 8/11/1987 Township of Brandon Brandon Township Land Use Plan Update - 3/14/2000 City of the Village of Clarkston Master Plan City of the Village of Clarkston - 8/4/1997City of Clawson Downtown Clawson Framework Urban Design Plan - 11/1/2004 Master Plan City of Clawson - 1/23/1990 Township of Commerce Commerce Charter Township Master Plan 2003 - 6/28/2004 Commerce Charter Township Master Plan Amendment - 11/27/2006 City of Farmington Master Plan City of Farmington - 2/1/1998 City of Farmington Hills Master Plan for Future Land Use City of Farmington Hills - 3/28/1996 City of Fenton Holly Township Master Plan - 11/10/2003 (Used the Holly Township Master Plan because Fenton's was unavailable) City of Ferndale City of Ferndale Land Use Plan - 6/1/1998 Village of Franklin Franklin Village Master Plan Update - 10/15/1997 Township of Groveland Master Plan for Future Land Use - 5/9/2005 City of Hazel Park Master Plan, Hazel Park Michigan - 3/21/2000 Township of Highland Highland Township Comprehensive Land Use Plan 2000-2020 - 7/6/2000 South Milford Road Corridor Micro-Area Analysis - 4/13/2005 East Highland Commercial District Micro Area Analysis - 12/19/2002 West Highland Micro-Area Analysis - 8/2/2001 North Hickory Ridge Road Micro-Area Analysis - 12/7/2006 Township of Holly Holly Township Master Plan - 11/10/2003 Village of Holly Village of Holly Master Plan - 1/24/2007 City of Huntington Woods Huntington Woods Master Plan - 12/17/2007 Township of Independence Independence Township Vision 2020 Master Plan - 12/9/1999 City of Keego Harbor City of Keego Harbor Comprehensive Master Plan - 9/5/2002 City of Lake Angelus City of Lake Angelus Master Plan - 7/25/1994 Village of Lake Orion Master Plan 2002-2022 - 1/6/2003 Amendment #1 to Lake Orion Master Plan - 3/3/2008 City of Lathrup Village The Lathrup Village Plan - 1/1/1981 Village of Leonard Master Plan Village of Leonard - 10/17/1991 Township of Lyon Charter Township of Lyon Master Plan - 3/27/2006 City of Madison Heights Madison Heights Master Plan: 1990, 2000, 2010 - 10/16/1990 Madison Heights Future Land Use Plan Amendment - 5/15/2007 Township of Milford Charter Township of Milford Land Use Plan Update - 5/27/1999 Village of Milford Village of Milford Master Plan - 3/1/1998 City of Northville City of Northville Master Plan - 2/22/2000 City of Novi City of Novi Master Plan for Land Use 2004 - 12/1/2004 City of Novi Master Plan for Land Use Amendments - 4/16/2008 Township of Novi None (Does not have a Master Plan, assumed to be Single Family Residential) City of Oak Park City of Oak Park Master Plan - 9/9/1996 City of Oak Park Master Plan Addition - Unknown Township of Oakland Oakland Charter Township A Community Master Plan - 1/4/2005 City of Orchard Lake Village Master Plan City of Orchard Lake Village - 6/6/2006 Township of Orion Orion Township Master Plan - 5/7/2003 Lapeer Road Master Plan Update - 4/19/2006 Village of Ortonville The Ortonville Plan - 1/1/1980 Township of Oxford Charter Township of Oxford Master Plan - 7/14/2005 Village of Oxford Village of Oxford Master Plan - 5/10/2005 City of Pleasant Ridge City of Pleasant Ridge Community Master Plan - 9/1/1999 City of Pontiac Pontiac 2010 A New Reality - 12/4/1991 City of Rochester Master Plan: 2000 City of Rochester - 6/3/2000 Downtown Development Area MP amendment - 5/2/2005 City of Rochester Hills Rochester Hills Master Land Use Plan 2007 - 2/6/2007 Township of Rose Master Plan Rose Township - 7/7/2005 City of Royal Oak Master Plan City of Royal Oak - 8/24/1999 Township of Royal Oak A Vision for the Year 2010 Master Plan 1996 Update - 12/11/1996 City of South Lyon Master Plan of Future Land Use City of South Lyon - 1/10/2002 City of Southfield Southfield Master Plan - 1/1/1988 Township of Southfield Southfield Township Master Plan - 11/25/2002 Township of Springfield Springfield Township Master Plan - 3/7/2002 City of Sylvan Lake Sylvan Lake Master Plan 2005 - 4/10/2007 City of Troy City of Troy Future Land Use Plan - 1/8/2002 City of Walled Lake City of Walled Lake Master Plan - 8/1/2002 Township of Waterford Waterford Master Plan 2003-2023 - 1/2/2003 Township of West Bloomfield West Bloomfield Township 2005 Master Land Use Plan Update - 7/26/2005 Township of White Lake White Lake Township Master Plan - 10/6/2006 City of Wixom City of Wixom Master Plan - 8/9/2005 Village of Wolverine Lake Village of Wolverine Lake Land Use Plan - 12/4/1985 Every category identified on the future land use map within each master plan was translated into a composite value. For example, one community may have two commercial districts- Local Commerical and General Commercial. Another community may have three commercial districts- Neighborhood Commercial, Hi-Tech Office, and Retail Commercial. A wide range of uses could be included in these categories, but for the purpose of this feature class, they are all translated into "Commercial/Office." In some cases a category on community's future land use map could not be translated into a single composite category. When this occurred, areas were manually translated into the appropriate generalized category. For example, a Public Lands class on a community's map would be manually translated into the Public/Institutional and Recreation/Conservation composite categories.

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.

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.

More Metadata

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 existing wetlands that are in a protected status by sub-lake unit (reporting unit) for each Great Lake, as determined by the LAMPs for each lake. Lakes Michigan, Huron, Erie and Ontario report by sub-lake units. Lake Superior reports by watersheds.*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.

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 map of Michigan's unchanged land cover ca. 1800.

For this crosswalk, we selected the NLCD (2011 version) and the Canadian SOLRIS 2.0 because they were created from imagery collected in approximately the same time framesand because they were comparable to the 2001 NLCD and the 2000 SOLRIS v1.2. However, a comparable layer from the same time period was not available for Northern Ontario. While the 2005-2011 Far North Land Cover 1.4 was available, it did not cover the entire extent of the 2000 PLO, and the classification scheme was very different from the 2000 PLO. This made it difficult to compare the two datasets as there were large differences in the distribution of classes due to classification scheme and mapping differences, resulting in artificially high land cover change statistics (see Far North Land Cover Data Specifications Version 1.4). As a result, we have incorporated the 2000 PLO for Northern Ontario, but will reevaluate the crosswalk as new data becomes available. To process these data, we first clipped each input data layer by the extent of the Great Lakes states and the Province of Ontario. Next, we reclassified the raster values using the Reclassify tool, changing the original values to crosswalked values. Next we projected the data into the standardized projection used by the Great Lakes Aquatic Habitat Framework (GLAHF) USA Contiguous Albers Equal Area Conic USGS projection and resampled the pixel size to 30 meters, the standard projection and pixel size for the Great Lakes Aquatic Habitat Framework (GLAHF). We then created a mosaic using Mosaic to New Raster, incorporating the waters of the Great Lakes as the value “1†, using the shoreline of the watersheds in the GLAHF Hydrology Data Package V1 as a mask. Land cover/land use codes: 1 = Great Lakes Waters; 11 = Water; 2 = Developed; 31 = Barren Land; 41 = Deciduous Forest; 42 = Evergreen Forest; 43 = Evergreen Forest; 43 = Mixed Forest; 52 = Scrub/Shrub; 71 = Grassland/Herbaceous; 8 = Agriculture; 90 = Forested Wetland; 95 = Emergent Wetland; 98 = Other/Undefined.

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 units of this map were determined through stereoscopic interpretation of aerial photographs supported by field sampling and ecological analysis. The vegetation boundaries were identified on the photographs by means of the photographic signatures and collateral information on slope, hydrology, geography, and vegetation in accordance with the Standardized National Vegetation Classification System (October 1995). The mapped vegetation reflects conditions that existed during the specific year and season that the aerial photographs were taken (spring - 1996 and fall - 1994). There is an inherent margin of error in the use of aerial photography for vegetation delineation and classification.

The purpose of this spatial data is to provide the National Park Service the necessary tools to wisely manage the natural resources within this park system. Several parks, representing different regions, environmental conditions, and vegetation types, were chosen by BRD to be part of the prototype phase of the program. The initial goal of the prototype phase is to "develop, test, refine, and finalize the standards and protocols" to be used during the production phase of the project. This includes the development of a standardized vegetation classification system for each park and the establishment of photointerpretation, field, and accuracy assessment procedures. Isle Royale National Park was initially identified as one of the prototypes within the National Park System for the USGS-NPS Vegetation Mapping Program. Isle Royale National Park was established March 3, 1931 and was also designated as an International Biosphere Reserve in 1980. The park contains approximately 571,790 acres of land and water (893 square miles) of which 133,782 acres is land and the rest is open water of Lake Superior as well as inland lakes and ponds. Isle Royale National Park is an archipelago of islands located in the northwestern region of Lake Superior close to the United States-Canada border. The main island, Isle Royale, consists of a series of ridges and valleys running the length of the island and is surrounded by approximately 200 smaller islands. The primary methods of transportation on the island are hiking and boating. Isle Royale National Park was authorized on March 3, 1931; it was formally established in 1940, and officially dedicated in 1946. Most of the park's land area (98%) was designated as a Wilderness area in October 1976, and later additions increased the total Wilderness to 99% of the park. The park was designated an International Biosphere Reserve in 1980.

Isle Royale National Park is an archipelago of islands located in the northwestern region of Lake Superior close to the United States-Canada border. The park is located about 60 miles northwest of Michigan.s Keweenaw Peninsula, about 22 miles east of Grand Portage, Minnesota, and about 35 miles southeast of Thunder Bay, Ontario.

Information for this metadata was obtained from the site "http://biology.usgs.gov/npsveg/isro/metaisrospatial.html" and converted to NASA Directory Interchange Format.

The 2019 cartographic boundary KMLs are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. The records in this file allow users to map the parts of Urban Areas that overlap a particular county. After each decennial census, the Census Bureau delineates urban areas that represent densely developed territory, encompassing residential, commercial, and other nonresidential urban land uses. In general, this territory consists of areas of high population density and urban land use resulting in a representation of the ""urban footprint."" There are two types of urban areas: urbanized areas (UAs) that contain 50,000 or more people and urban clusters (UCs) that contain at least 2,500 people, but fewer than 50,000 people (except in the U.S. Virgin Islands and Guam which each contain urban clusters with populations greater than 50,000). Each urban area is identified by a 5-character numeric census code that may contain leading zeroes. The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities. The generalized boundaries for counties and equivalent entities are as of January 1, 2010.