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

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.

Future Land Use Map approved by the Mobile Planning Commission on August 15, 2024. The future land use map depicts the desired types, intensity and spatial arrangement of the City’s land uses to achieve the vision described in Map for Mobile. The land use designations are defined in the Future Land Use Plan (FLUP).

This dataset consists of a map depicting the landcover of the Natchez Trace Parkway. The mapping output was created using mosaiced color infrared aerial photography of the Parkway. The map shows the distribution of 18 landcover classes based on the National Vegetation Classification Standard. Ground-based vegetation classification was provided by the National Park Service (NPS). The mapping output delineates grasses, road-developed areas, scrub-shrub, shrubland, plantation, water bodies, areas of white oak, oak, pine-oak, pine-cedar, pine-sweetgum, sweetgum (including sweetgum-oak), scattered trees, swamp forest, irregular classes, aquatic vegetation, invasive species, canopy gaps, and clouds.

Total mapped area includes a 100 m buffer outside the park boundary. 235 digital orthophoto quarter quadrangles (DOQQs) were required to cover the entire 715 km long Parkway. For ease of use, the DOQQs were grouped into 11 mosaics, each covering a section of the Parkway. At the request of the NPS, each mosaic was divided into ten tiles to allow for efficient loading on less robust computers.

This dataset defines the symbology for the landcover map of the Natchez Trace Parkway. The map shows the distribution of 18 landcover classes based on the National Vegetation Classification Standard. Ground-based vegetation classification was provided by National Park Service (NPS). The mapping output and layer delineate grasses, road-developed areas, scrub-shrub, shrubland, plantation, water bodies, areas of white oak, oak, pine-oak, pine-cedar, pine-sweetgum, sweetgum (including sweetgum-oak), scattered trees, swamp forest, irregular classes, aquatic vegetation, invasive species, canopy gaps, and clouds. Mapped classes that have been digitized are noted with an asterisk (*) in the legend.

This story map is a part of the General Land Office (GLO) Record of the Week (ROTW) project. Each week, the BLM ES will release a story map as a part of the GLO ROTW Project. This project was initiated by BLM Eastern States to share unique records from the GLO Records collection. This story map details the role of Selma, Alabama in the Civil Rights Movement.

Multispectral imagery of the state of Alabama is available from the Geological Survey of Alabama for the time period of 1972-1984. Imagery from the Landsat multispectral scanner (MSS) is available as prints or transparencies for all bands (with selected color composites avaliable) at an approximate scale of 1:1,000,000. MSS data is collected in four spectral bands ranging from 0.5 to 1.1 micrometer with a ground resolution of about 80m.

    Images available from Skylab 3 and 4 include 9 x 9 prints and
    transparencies at 1:750,000 (skylab 3) and 1:500,000 (skylab 4).
    These images were taken in 1973 and are along three tracks; northeast
    from New Orleans, LA to South Carolina, northeast from Pensacola, FL
    to Columbus, GA, and from Pearl River, Jackson MI to Pensacola, FL.
    The multispectral photographic facility onboard Skylab provided
    imagery in several wavelength bands ranging from 0.5 to 0.9
    Micrometers. This camera system provided ground resolution of
    approximately 40 m in visible wavelengths to 75 m in the infrared.

    A variety of high and low altitude aircraft imagery of Alabama is also
    available from the Geological Survey of Alabama. Microfiche images of
    MSS/TM imagery of North America since 1986 (landsat browse imagery)
    are also available. Similar imagery for other locations and time
    periods is available from the Eros Data Center.

This data set contains the 1996-era and 2005-era classifications for Alabama, a subset of zone 46, and can be used to analyze change. This imagery was collected as part of the Multi-Resolution Land Characteristics program in a multi-agency effort to provide baseline multi-scale environmental characteristics and to monitor environmental change. This data set utilized 72 full or partial Landsat 5 and 7 scenes which were analyzed according to the Coastal Change Analysis Program (C-CAP) protocol to determine land cover.

From the Flood Risk Non-Regulatory Database that went into effect June 5, 2020. For more information, visit FEMA.gov Flood Maps.Flood Hazard Zones: The FIRM is the basis for floodplain management, mitigation, and insurance activities for the National Flood Insurance Program (NFIP). Insurance applications include enforcement of the mandatory purchase requirement of the Flood Disaster Protection Act, which "... requires the purchase of flood insurance by property owners who are being assisted by Federal programs or by Federally supervised, regulated or insured agencies or institutions in the acquisition or improvement of land facilities located or to be located in identified areas having special flood hazards," Section 2 (b) (4) of the Flood Disaster Protection Act of 1973. In addition to the identification of Special Flood Hazard Areas (SFHAs), the risk zones shown on the FIRMs are the basis for the establishment of premium rates for flood coverage offered through the NFIP. The DFIRM Database presents the flood risk information depicted on the FIRM in a digital format suitable for use in electronic mapping applications. The DFIRM database is a subset of the Digital FIS database that serves to archive the information collected during the FIS.The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The DFIRM Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA). The file is georeferenced to earth's surface using the UTM projection and coordinate system. The specifications for the horizontal control of DFIRM data files are consistent with those required for mapping at a scale of 1:12,000.Flood Hazard Boundary Line: Boundary line dividing Special Flood Hazard Area Zones and boundary dividing Special Flood Hazard Areas of different Base Flood Elevations, flood Depths or flood velocities.Flood Hazard BFE: Location and attributes for base flood elevations lines shown on DFIRM. This line layer was converted to a polygon by COM GIS department.Flood Hazard Cross Section: Location and attributes for cross-section lines in the area covered by the DFIRM.Flood Hazard Map Index: Location and attributes for DFIRM hardcopy map panels.Use limitationsThe hardcopy FIRM and DFIRM and the accompanying FISs are the official designation of SFHAs and Base Flood Elevations (BFEs) for the NFIP. For the purposes of the NFIP, changes to the flood risk information published by FEMA may only be performed by FEMA and through the mechanisms established in the NFIP regulations (44 CFR Parts 59-78). These digital data are produced in conjunction with the hardcopy FIRMs and generally match the hardcopy map exactly. However the hardcopy flood maps and flood profiles are the authoritative documents for the NFIP. Acknowledgement of FEMA would be appreciated in products derived from these data.