14 datasets found
  1. K

    Tuscaloosa County, Alabama Parcels

    • koordinates.com
    csv, dwg, geodatabase +6
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    Tuscaloosa County, Alabama, Tuscaloosa County, Alabama Parcels [Dataset]. https://koordinates.com/layer/109490-tuscaloosa-county-alabama-parcels/
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    shapefile, pdf, geodatabase, mapinfo tab, kml, mapinfo mif, csv, geopackage / sqlite, dwgAvailable download formats
    Dataset authored and provided by
    Tuscaloosa County, Alabama
    Area covered
    Description

    Geospatial data about Tuscaloosa County, Alabama Parcels. Export to CAD, GIS, PDF, CSV and access via API.

  2. C

    GIS Mapping files

    • data.birminghamal.gov
    geojson, html, shp
    Updated Jan 9, 2019
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    Birmingham Planning & Engineering (2019). GIS Mapping files [Dataset]. https://data.birminghamal.gov/dataset/gis-mapping-files
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    html, shp, geojson, geojson(1853069), geojson(1539369), shp(444998), shp(377381)Available download formats
    Dataset updated
    Jan 9, 2019
    Dataset authored and provided by
    Birmingham Planning & Engineering
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Planning, Engineering & Permitting - GIS Mapping files

  3. a

    Montgomery GIS Viewer

    • opendata-citymgm.hub.arcgis.com
    • opendata.montgomeryal.gov
    Updated Oct 3, 2013
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    City of Montgomery ArcGIS Online (2013). Montgomery GIS Viewer [Dataset]. https://opendata-citymgm.hub.arcgis.com/datasets/montgomery-gis-viewer
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    Dataset updated
    Oct 3, 2013
    Dataset authored and provided by
    City of Montgomery ArcGIS Online
    Description

    The City of Montgomery GIS Web Viewer provides a glimpse into the GIS data available for Montgomery, Alabama. Managed by the City of Montgomery GIS Division, with cooperation from the Montgomery County Appraiser's Office. This application provides data discovery and mapping to the Public. A user can search for a location by Address, Parcel Number, or Owner Name. One can find Parcel information, Zoning, 2012 Imagery, Economic and Tax Incentive Zones, Political Districts, and More.

  4. a

    School Property

    • hub.arcgis.com
    • data-coa.opendata.arcgis.com
    • +1more
    Updated Nov 1, 2023
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    City of Auburn, Alabama (2023). School Property [Dataset]. https://hub.arcgis.com/maps/COA::school-property
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    Dataset updated
    Nov 1, 2023
    Dataset authored and provided by
    City of Auburn, Alabama
    Area covered
    Description

    Layer is of parcels owned by the Auburn City School Board.

    Similar data is maintained in the City Property layer in the Land Records folder, which has property owned by the various city entities.

    520F1B89-3BE3-4F6E-AA60-9966E4A620A8

  5. d

    Protected Areas Database of the United States (PAD-US)

    • search.dataone.org
    • datadiscoverystudio.org
    • +1more
    Updated Oct 26, 2017
    + more versions
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    US Geological Survey (USGS) Gap Analysis Program (GAP) (2017). Protected Areas Database of the United States (PAD-US) [Dataset]. https://search.dataone.org/view/0459986b-9a0e-41d9-9997-cad0fbea9c4e
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    Dataset updated
    Oct 26, 2017
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    US Geological Survey (USGS) Gap Analysis Program (GAP)
    Time period covered
    Jan 1, 2005 - Jan 1, 2016
    Area covered
    United States,
    Variables measured
    Shape, Access, Des_Nm, Des_Tp, Loc_Ds, Loc_Nm, Agg_Src, GAPCdDt, GAP_Sts, GIS_Src, and 20 more
    Description

    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/ .

  6. a

    AHC National Register Polygons

    • alabama-historic-preservation-gis-portal-alabama.hub.arcgis.com
    Updated Jul 14, 2023
    + more versions
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    eric.sipes (2023). AHC National Register Polygons [Dataset]. https://alabama-historic-preservation-gis-portal-alabama.hub.arcgis.com/datasets/aa48c7297da34b7d8ad1b46f3b4fa639
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    Dataset updated
    Jul 14, 2023
    Dataset authored and provided by
    eric.sipes
    Area covered
    Description

    The National Register (NR) of Historic Places is the nation's official list of cultural resources, 50 years or older, worthy of preservation. Authorized under the National Historic Preservation Act of 1966, the National Register is part of a nationwide program to coordinate and support public and private efforts to identify, evaluate, and protect our historic and archaeological places. The NR listing only recognizes a place's historic character and does not place restrictions on the property. For more information about the National Register of Historic Places in Alabama, please visit: https://ahc.alabama.gov/nationalregister.aspx Please note that properties that have restricted locations, such as some archaeological sites and/or underwater resources, may not appear on this map. Professionals that meet the Secretary of Interior's Standards for Cultural Resource Professionals may request access to those records by contacting our National Register Coordinator or our State Archaeologists.

  7. d

    U.S. Geological Survey Gap Analysis Program- Land Cover Data v2.2.

    • datadiscoverystudio.org
    • data.globalchange.gov
    • +3more
    Updated May 21, 2018
    + more versions
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    (2018). U.S. Geological Survey Gap Analysis Program- Land Cover Data v2.2. [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/5943529b1b9043a397058fffe2a2440a/html
    Explore at:
    Dataset updated
    May 21, 2018
    Description

    description: 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; abstract: 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

  8. Remote Sensing and GIS data at 1km-grid over Chesapeake Bay used in “He et...

    • osti.gov
    • search.dataone.org
    Updated Jan 1, 2024
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    Environmental System Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) (United States) (2024). Remote Sensing and GIS data at 1km-grid over Chesapeake Bay used in “He et al. 2024, Effects of spatial variability in vegetation phenology, climate, landcover, biodiversity, topography, and soil property on soil respiration across a coastal ecosystem” [Dataset]. http://doi.org/10.15485/2326012
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    Dataset updated
    Jan 1, 2024
    Dataset provided by
    Department of Energy Biological and Environmental Research Program
    Office of Sciencehttp://www.er.doe.gov/
    Environmental System Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) (United States)
    COMPASS-FME
    Area covered
    Chesapeake Bay
    Description

    The package contains the data layers used in “He et al. 2024, Effects of spatial variability in vegetation phenology, climate, landcover, biodiversity, topography, and soil property on soil respiration across a coastal ecosystem”. The study aims to use multi-source remote sensing and GIS datasets to investigate the spatial heterogeneity and identify spatial zones with similar environmental characteristics and understand the primary driving factors affecting soil respiration within sub-ecosystems of the coastal ecosystem. We employed unsupervised hierarchical clustering analysis to identify spatial regions with distinct environmental characteristics, then determined the main driving factors using Random Forest regression and SHapley Additive exPlanations (SHAP). Spatial data layers include soil respiration, kernel Normalized Difference Vegetation Index (kNDVI) computed from Harmonized Landsat 8 and Sentinel-2 time series, climate variables from the Daymet dataset, land cover, biodiversity, topographical metrics, soil property, and tidal elevation.

  9. a

    AHC National Register DOE Points

    • alabama-historic-preservation-gis-portal-alabama.hub.arcgis.com
    Updated Jul 14, 2023
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    eric.sipes (2023). AHC National Register DOE Points [Dataset]. https://alabama-historic-preservation-gis-portal-alabama.hub.arcgis.com/datasets/f7436de4c3af4a28838f8ec3b148151d
    Explore at:
    Dataset updated
    Jul 14, 2023
    Dataset authored and provided by
    eric.sipes
    Area covered
    Description

    The National Register (NR) of Historic Places is the nation's official list of cultural resources, 50 years or older, worthy of preservation. Authorized under the National Historic Preservation Act of 1966, the National Register is part of a nationwide program to coordinate and support public and private efforts to identify, evaluate, and protect our historic and archaeological places. The NR listing only recognizes a place's historic character and does not place restrictions on the property. For more information about the National Register of Historic Places in Alabama, please visit: https://ahc.alabama.gov/nationalregister.aspx Please note that properties that have restricted locations, such as some archaeological sites and/or underwater resources, may not appear on this map. Professionals that meet the Secretary of Interior's Standards for Cultural Resource Professionals may request access to those records by contacting our National Register Coordinator or our State Archaeologists.

  10. d

    BLM ES AL PLSS Township Polygon.

    • datadiscoverystudio.org
    Updated Jun 8, 2018
    + more versions
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    (2018). BLM ES AL PLSS Township Polygon. [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/68ab111b334946eea222e64e7abbf6ab/html
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    Dataset updated
    Jun 8, 2018
    Description

    description: This data represents the GIS Version of the Public Land Survey System including both rectangular and non-rectangular survey data. The rectangular survey data are a reference system for land tenure based upon meridian, township/range, section, section subdivision and government lots. The non-rectangular survey data represent surveys that were largely performed to protect and/or convey title on specific parcels of land such as mineral surveys and tracts. The data are largely complete in reference to the rectangular survey data at the level of first division. However, the data varies in terms of granularity of its spatial representation as well as its content below the first division. Therefore, depending upon the data source and steward, accurate subdivision of the rectangular data may not be available below the first division and the non-rectangular minerals surveys may not be present. At times, the complexity of surveys rendered the collection of data cost prohibitive such as in areas characterized by numerous, overlapping mineral surveys. In these situations, the data were often not abstracted or were only partially abstracted and incorporated into the data set. These PLSS data were compiled from a broad spectrum or sources including federal, county, and private survey records such as field notes and plats as well as map sources such as USGS 7 minute quadrangles. The metadata in each data set describes the production methods for the data content. This data is optimized for data publication and sharing rather than for specific "production" or operation and maintenance. A complete PLSS data set includes the following: PLSS Townships, First Divisions and Second Divisions (the hierarchical break down of the PLSS Rectangular surveys) PLSS Special surveys (non-rectangular components of the PLSS) Meandered Water, Corners, Metadata at a Glance (which identified last revised date and data steward) and Conflicted Areas (known areas of gaps or overlaps or inconsistencies). The Entity-Attribute section of this metadata describes these components in greater detail. The second division of the PLSS is quarter, quarter-quarter, sixteenth or government lot division of the PLSS. The second and third divisions are combined into this feature class as an intentional de-normalization of the PLSS hierarchical data. The polygons in this feature class represent the smallest division to the sixteenth that has been defined for the first division. For example In some cases sections have only been divided to the quarter. Divisions below the sixteenth are in the Special Survey or Parcel Feature Class. In the Public Land Survey System a Township refers to a unit of land, that is nominally six miles on a side, usually containing 36 sections.; abstract: This data represents the GIS Version of the Public Land Survey System including both rectangular and non-rectangular survey data. The rectangular survey data are a reference system for land tenure based upon meridian, township/range, section, section subdivision and government lots. The non-rectangular survey data represent surveys that were largely performed to protect and/or convey title on specific parcels of land such as mineral surveys and tracts. The data are largely complete in reference to the rectangular survey data at the level of first division. However, the data varies in terms of granularity of its spatial representation as well as its content below the first division. Therefore, depending upon the data source and steward, accurate subdivision of the rectangular data may not be available below the first division and the non-rectangular minerals surveys may not be present. At times, the complexity of surveys rendered the collection of data cost prohibitive such as in areas characterized by numerous, overlapping mineral surveys. In these situations, the data were often not abstracted or were only partially abstracted and incorporated into the data set. These PLSS data were compiled from a broad spectrum or sources including federal, county, and private survey records such as field notes and plats as well as map sources such as USGS 7 minute quadrangles. The metadata in each data set describes the production methods for the data content. This data is optimized for data publication and sharing rather than for specific "production" or operation and maintenance. A complete PLSS data set includes the following: PLSS Townships, First Divisions and Second Divisions (the hierarchical break down of the PLSS Rectangular surveys) PLSS Special surveys (non-rectangular components of the PLSS) Meandered Water, Corners, Metadata at a Glance (which identified last revised date and data steward) and Conflicted Areas (known areas of gaps or overlaps or inconsistencies). The Entity-Attribute section of this metadata describes these components in greater detail. The second division of the PLSS is quarter, quarter-quarter, sixteenth or government lot division of the PLSS. The second and third divisions are combined into this feature class as an intentional de-normalization of the PLSS hierarchical data. The polygons in this feature class represent the smallest division to the sixteenth that has been defined for the first division. For example In some cases sections have only been divided to the quarter. Divisions below the sixteenth are in the Special Survey or Parcel Feature Class. In the Public Land Survey System a Township refers to a unit of land, that is nominally six miles on a side, usually containing 36 sections.

  11. d

    BLM ES AL PLSS First Division Polygon.

    • datadiscoverystudio.org
    Updated May 21, 2018
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    (2018). BLM ES AL PLSS First Division Polygon. [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/c28d228efeb24db881f11fb30a6ffa79/html
    Explore at:
    Dataset updated
    May 21, 2018
    Description

    description: This data represents the GIS Version of the Public Land Survey System including both rectangular and non-rectangular survey data. The rectangular survey data are a reference system for land tenure based upon meridian, township/range, section, section subdivision and government lots. The non-rectangular survey data represent surveys that were largely performed to protect and/or convey title on specific parcels of land such as mineral surveys and tracts. The data are largely complete in reference to the rectangular survey data at the level of first division. However, the data varies in terms of granularity of its spatial representation as well as its content below the first division. Therefore, depending upon the data source and steward, accurate subdivision of the rectangular data may not be available below the first division and the non-rectangular minerals surveys may not be present. At times, the complexity of surveys rendered the collection of data cost prohibitive such as in areas characterized by numerous, overlapping mineral surveys. In these situations, the data were often not abstracted or were only partially abstracted and incorporated into the data set. These PLSS data were compiled from a broad spectrum or sources including federal, county, and private survey records such as field notes and plats as well as map sources such as USGS 7 minute quadrangles. The metadata in each data set describes the production methods for the data content. This data is optimized for data publication and sharing rather than for specific "production" or operation and maintenance. A complete PLSS data set includes the following: PLSS Townships, First Divisions and Second Divisions (the hierarchical break down of the PLSS Rectangular surveys) PLSS Special surveys (non-rectangular components of the PLSS) Meandered Water, Corners, Metadata at a Glance (which identified last revised date and data steward) and Conflicted Areas (known areas of gaps or overlaps or inconsistencies). The Entity-Attribute section of this metadata describes these components in greater detail. The PLSS First Division is commonly the section. This is the first set of divisions for a PLSS Township.; abstract: This data represents the GIS Version of the Public Land Survey System including both rectangular and non-rectangular survey data. The rectangular survey data are a reference system for land tenure based upon meridian, township/range, section, section subdivision and government lots. The non-rectangular survey data represent surveys that were largely performed to protect and/or convey title on specific parcels of land such as mineral surveys and tracts. The data are largely complete in reference to the rectangular survey data at the level of first division. However, the data varies in terms of granularity of its spatial representation as well as its content below the first division. Therefore, depending upon the data source and steward, accurate subdivision of the rectangular data may not be available below the first division and the non-rectangular minerals surveys may not be present. At times, the complexity of surveys rendered the collection of data cost prohibitive such as in areas characterized by numerous, overlapping mineral surveys. In these situations, the data were often not abstracted or were only partially abstracted and incorporated into the data set. These PLSS data were compiled from a broad spectrum or sources including federal, county, and private survey records such as field notes and plats as well as map sources such as USGS 7 minute quadrangles. The metadata in each data set describes the production methods for the data content. This data is optimized for data publication and sharing rather than for specific "production" or operation and maintenance. A complete PLSS data set includes the following: PLSS Townships, First Divisions and Second Divisions (the hierarchical break down of the PLSS Rectangular surveys) PLSS Special surveys (non-rectangular components of the PLSS) Meandered Water, Corners, Metadata at a Glance (which identified last revised date and data steward) and Conflicted Areas (known areas of gaps or overlaps or inconsistencies). The Entity-Attribute section of this metadata describes these components in greater detail. The PLSS First Division is commonly the section. This is the first set of divisions for a PLSS Township.

  12. d

    Mineral Resources Data System

    • search.dataone.org
    • data.wu.ac.at
    Updated Oct 29, 2016
    + more versions
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    U.S. Geological Survey (2016). Mineral Resources Data System [Dataset]. https://search.dataone.org/view/3e55bd49-a016-4172-ad78-7292618a08c2
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    Dataset updated
    Oct 29, 2016
    Dataset provided by
    USGS Science Data Catalog
    Authors
    U.S. Geological Survey
    Area covered
    Variables measured
    ORE, REF, ADMIN, MODEL, STATE, COUNTY, DEP_ID, GANGUE, MAS_ID, REGION, and 29 more
    Description

    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.

  13. d

    BLM ES AL PLSS Conflicted Areas Polygon.

    • datadiscoverystudio.org
    Updated May 19, 2018
    + more versions
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    (2018). BLM ES AL PLSS Conflicted Areas Polygon. [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/6bbc559e8644413f97b376457cd982f4/html
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    Dataset updated
    May 19, 2018
    Description

    description: This data represents the GIS Version of the Public Land Survey System including both rectangular and non-rectangular survey data. The rectangular survey data are a reference system for land tenure based upon meridian, township/range, section, section subdivision and government lots. The non-rectangular survey data represent surveys that were largely performed to protect and/or convey title on specific parcels of land such as mineral surveys and tracts. The data are largely complete in reference to the rectangular survey data at the level of first division. However, the data varies in terms of granularity of its spatial representation as well as its content below the first division. Therefore, depending upon the data source and steward, accurate subdivision of the rectangular data may not be available below the first division and the non-rectangular minerals surveys may not be present. At times, the complexity of surveys rendered the collection of data cost prohibitive such as in areas characterized by numerous, overlapping mineral surveys. In these situations, the data were often not abstracted or were only partially abstracted and incorporated into the data set. These PLSS data were compiled from a broad spectrum or sources including federal, county, and private survey records such as field notes and plats as well as map sources such as USGS 7 minute quadrangles. The metadata in each data set describes the production methods for the data content. This data is optimized for data publication and sharing rather than for specific "production" or operation and maintenance. A complete PLSS data set includes the following: PLSS Townships, First Divisions and Second Divisions (the hierarchical break down of the PLSS Rectangular surveys) PLSS Special surveys (non-rectangular components of the PLSS) Meandered Water, Corners, Metadata at a Glance (which identified last revised date and data steward) and Conflicted Areas (known areas of gaps or overlaps or inconsistencies). The Entity-Attribute section of this metadata describes these components in greater detail. The conflicted areas feature class is a depiction of known overlaps or gaps resulting from two or more different surveys of the same area, this may also include an indication of canceled or suspended surveys.; abstract: This data represents the GIS Version of the Public Land Survey System including both rectangular and non-rectangular survey data. The rectangular survey data are a reference system for land tenure based upon meridian, township/range, section, section subdivision and government lots. The non-rectangular survey data represent surveys that were largely performed to protect and/or convey title on specific parcels of land such as mineral surveys and tracts. The data are largely complete in reference to the rectangular survey data at the level of first division. However, the data varies in terms of granularity of its spatial representation as well as its content below the first division. Therefore, depending upon the data source and steward, accurate subdivision of the rectangular data may not be available below the first division and the non-rectangular minerals surveys may not be present. At times, the complexity of surveys rendered the collection of data cost prohibitive such as in areas characterized by numerous, overlapping mineral surveys. In these situations, the data were often not abstracted or were only partially abstracted and incorporated into the data set. These PLSS data were compiled from a broad spectrum or sources including federal, county, and private survey records such as field notes and plats as well as map sources such as USGS 7 minute quadrangles. The metadata in each data set describes the production methods for the data content. This data is optimized for data publication and sharing rather than for specific "production" or operation and maintenance. A complete PLSS data set includes the following: PLSS Townships, First Divisions and Second Divisions (the hierarchical break down of the PLSS Rectangular surveys) PLSS Special surveys (non-rectangular components of the PLSS) Meandered Water, Corners, Metadata at a Glance (which identified last revised date and data steward) and Conflicted Areas (known areas of gaps or overlaps or inconsistencies). The Entity-Attribute section of this metadata describes these components in greater detail. The conflicted areas feature class is a depiction of known overlaps or gaps resulting from two or more different surveys of the same area, this may also include an indication of canceled or suspended surveys.

  14. a

    Rutherford County Historic Structures Lookup App

    • rutherfordcountygis-rcgis.hub.arcgis.com
    Updated Aug 22, 2017
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    Rutherford County GIS (2017). Rutherford County Historic Structures Lookup App [Dataset]. https://rutherfordcountygis-rcgis.hub.arcgis.com/items/b0481352a43442de87bc2080d0f166c6
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    Dataset updated
    Aug 22, 2017
    Dataset authored and provided by
    Rutherford County GIS
    Area covered
    Description

    In 1980, historic preservation students from Middle Tennessee State University were given the opportunity to conduct a historic property survey in Rutherford County, Tennessee. They drove the city streets and county roads looking for any buildings (houses, barns, smokehouses, schools, churches, etc.) that were at least 50 years old and older. The students took photographs and recorded four-page surveys for every historic site they encountered. Thirty years later, in the winter of 2010, the Rutherford County Archives Department received a grant from the Tennessee Historical Commission to revisit this survey and make the information available to the public.

    The Rutherford County Archives employed students to digitize the photographs and data forms from the original survey. The students re-drove the roads and updated al the photographs taken in 1980. It was interesting to see how much has changed in Rutherford County in the past thirty years, but also how much has been preserved!

    For more information about the Rutherford County Historic Property Survey, please contact Rutherford County Archives at 615-867-4609 or archives@rutherfordcountytn.gov

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    Learn how you can add new datasets to our index.

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Tuscaloosa County, Alabama, Tuscaloosa County, Alabama Parcels [Dataset]. https://koordinates.com/layer/109490-tuscaloosa-county-alabama-parcels/

Tuscaloosa County, Alabama Parcels

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shapefile, pdf, geodatabase, mapinfo tab, kml, mapinfo mif, csv, geopackage / sqlite, dwgAvailable download formats
Dataset authored and provided by
Tuscaloosa County, Alabama
Area covered
Description

Geospatial data about Tuscaloosa County, Alabama Parcels. Export to CAD, GIS, PDF, CSV and access via API.

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