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/ .

Electrical resistivity results from two regional airborne electromagnetic (AEM) surveys (Minsley et al. 2021, and Burton et al. 2021) over the Mississippi Alluvial Plain (MAP) were combined by the U.S. Geological Survey to produce three-dimensional (3D) gridded models and derivative hydrogeologic products. First, the base of the Mississippi River Valley Alluvial aquifer (MRVA) was updated using the AEM resistivity data, both borehole and manual picks, and a supervised machine learning algorithm. The 3D resistivity elevation grid was then intersected with the 2018 potentiometric surface and the new base of MRVA surface to isolate the saturated MRVA extent and generate estimates of the hydrogeologic framework and properties. The saturated aquifer thickness was calculated as the difference between the potentiometric surface elevation and the MRVA base elevation. The average electrical resistivity and facies classification of the saturated aquifer material were calculated for each 1 kilometer (km) x 1 km grid cell. See child item “Mississippi Alluvial Plain: Electrical Resistivity & Facies Classification Grids” for more details on the facies classes. Lastly, the degree of connectivity across the base of the MRVA, i.e. how likely the MRVA is hydraulically connected to deeper subcropping Tertiary units, was estimated through the vertically integrated electrical conductance (VIC) between different vertical offsets (+/- 5 meter (m), 10 m, 25 m) from the aquifer base. For example, for every 1 km x 1 km cell, the VIC for +/- 25 m is the result of integrating the electrical conductance values from all 5 m elevation layers between 25 above the MRVA base and 25 m below the MRVA base. Areas with high VIC values suggest there is low or minimal hydraulic connection across the MRVA base, while low VIC values indicate areas of high potential connection. All products were exported as raster images in Georeferenced Tagged Image File Format (GeoTIFF) files. Burton, B.L., Minsley, B.J., Bloss, B.R., and Kress, W.H., 2021, Airborne electromagnetic, magnetic, and radiometric survey of the Mississippi Alluvial Plain, November 2018 - February 2019: U.S. Geological Survey data release, https://doi.org/10.5066/P9XBBBUU. Minsley, B.J., James, S.R., Bedrosian, P.A., Pace, M.D., Hoogenboom, B.E., and Burton, B.L., 2021, Airborne electromagnetic, magnetic, and radiometric survey of the Mississippi Alluvial Plain, November 2019 - March 2020: U.S. Geological Survey data release, https://doi.org/10.5066/P9E44CTQ.

Electrical resistivity results from four regional airborne electromagnetic (AEM) surveys (Burton et al. 2024, Hoogenboom et al. 2023, Minsley et al. 2021, Burton et al. 2021) over the Mississippi Alluvial Plain (MAP) were combined by the U.S. Geological Survey (USGS) to produce three-dimensional (3D) gridded models and derivative hydrogeologic products. To calculate estimates of streambed properties across the MAP region, e.g. the relative connection potential between streams and the adjacent Mississippi River Valley Alluvial aquifer (MRVA), new 3D grids of electrical resistivity were generated for 2 meter (m) depth layers and only shallow depths (0-30 m). One grid was made with the horizontal dimension aligning with the 1 kilometer (km) x 1 km National Hydrogeologic Grid (NHG; Clark et al. 2018), and a second version was generated at a finer resolution of 100 m x 100 m, subdividing the NHG grid. Stream locations taken from the National Hydrograph Dataset Plus (NHDPlus) high resolution dataset were buffered with a 1.0 km radius and then intersected with both shallow 3D depth grids to isolate resistivity values immediately beneath or adjacent to streams. Twelve “facies classes” were defined to categorize materials expected to have similar hydrologic and geologic properties based on their electrical resistivity (i.e. low classes correspond to clays and silts with low permeability, and higher classes reflect larger grain sizes (sands, gravels) with expected higher permeability). The potential hydraulic connection through streambed sediments was estimated by calculating the vertically integrated electrical conductance (VIC) across each 2 m layer between 0 and 10 m depth. The shallow 3D resistivity and facies grids were exported in NetCDF format with an accompanying XML NetCDF Markdown Language metadata file. The streambed connectivity estimates were exported as raster images in Georeferenced Tagged Image File Format (GeoTIFF). Burton, B.L., Adams, R.F. Adams, Minsley, B.J., Pace, M.D.M., Kress, W.H., Rigby, J.R., and Bussell, A.M., 2024, Airborne electromagnetic, magnetic, and radiometric survey of the Mississippi Alluvial Plain, March 2018 and May - August 2021: U.S. Geological Survey data release, https://doi.org/10.5066/P9KPK3UJ. Hoogenboom, B.E., Minsley, B.J., James, S.R., and Pace, M.D., 2023, Airborne electromagnetic, magnetic, and radiometric survey of the Mississippi Alluvial Plain, Mississippi Embayment, and Gulf Coastal Plain, September 2021 - January 2022: U.S. Geological Survey data release, https://doi.org/10.5066/P93DO0EO. Burton, B.L., Minsley, B.J., Bloss, B.R., and Kress, W.H., 2021, Airborne electromagnetic, magnetic, and radiometric survey of the Mississippi Alluvial Plain, November 2018 - February 2019: U.S. Geological Survey data release, https://doi.org/10.5066/P9XBBBUU. Clark, B.R., Barlow, P.M., Peterson, S.M., Hughes, J.D., Reeves, H.W., and Viger, R.J., 2018, National-scale grid to support regional groundwater availability studies and a national hydrogeologic database: U.S. Geological Survey data release, https://doi.org/10.5066/F7P84B24. Minsley, B.J., James, S.R., Bedrosian, P.A., Pace, M.D., Hoogenboom, B.E., and Burton, B.L., 2021, Airborne electromagnetic, magnetic, and radiometric survey of the Mississippi Alluvial Plain, November 2019 - March 2020: U.S. Geological Survey data release, https://doi.org/10.5066/P9E44CTQ.

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 National Land Cover Database 2001 land cover layer was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of federal agencies (www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (EPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (FWS), the Bureau of Land Management (BLM) and the USDA Natural Resources Conservation Service (NRCS). One of the primary goals of the project is to generate a current, consistent, seamless, and accurate National Land cover Database (NLCD) circa 2001 for the United States at medium spatial resolution. This landcover map and all documents pertaining to it are considered "provisional" until a formal accuracy assessment can be conducted. For a detailed definition and discussion on MRLC and the NLCD 2001 products, refer to Homer et al. (2004) and http://www.mrlc.gov/mrlc2k.asp.The NLCD 2001 is created by partitioning the U.S. into mapping zones. A total of 66 mapping zones were delineated within the conterminous U.S. based on ecoregion and geographical characteristics, edge matching features and the size requirement of Landsat mosaics. Mapping zone 37B encompasses whole or portions of several states, including the states of Texas, Louisiana, and Mississippi. Questions about the NLCD mapping zone 37B can be directed to the NLCD 2001 land cover mapping team at the USGS/EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov.

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 map shows the approximate extent of overbank flooding in the Lower Mississippi River prior to extensive construction of levees. It was digitized from this map: https://fws.maps.arcgis.com/home/item.html?id=6941d5d2a1a84d05b771ef854a192d40 The original source map is derived from an online source (https://www.digitalcommonwealth.org/search/commonwealth:7h14b0450). Map of the alluvial valley of the Mississippi River from the head of St. Francis Basin to the Gulf of Mexico, showing lands subject to overflow, location of levees and trans-alluvial profiles. The map shows the landscape configuration and the approximate extent of overbank flooding before extensive construction of the levees in the early 1900s. The map was georectified using ERDAS Imagine and contemporary data sources. Edited (to correct position of panels) and georeferenced by Yvonne Allen (USFWS) to geographic NAD1927 using ArcGIS , 3rd order polynomial and 80 ground control points using lat lon grid.Online repo: https://www.sciencebase.gov/catalog/item/58f66491e4b0bd52222f7821

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

Mississippi Emergency Management Agency◄ ◄ Preparing for Tomorrow's Disasters Today ► ►MEMA ArcGIS Home ● GIS Awareness Center ● GIS Weather Center ● GIS Hurricane CenterThe mission of the Mississippi Emergency Management Agency is to safeguard Mississippi and its citizens by fostering a culture of preparedness, executing timely responses during disasters, and quickly restoring quality of life post-event.

The Filled Land Surface Albedo Product for Southern Africa, which is generated from MOD43B3 Product (the official Terra/MODIS-derived Land Surface Albedo - http://geography.bu.edu/brdf/userguide/albedo.html ), is a subset of the global data set of spatially complete albedo maps computed for both white-sky and black-sky at 10 wavelengths. The data spatial extent is from approximately 5 degrees N to -30 degrees S latitude and 5 minutes E to 60 degrees E longitude and covers 7 sixteen day periods starting on July 11 through October 15, 2000.Map Products, containing spatially complete land surface albedo data, are generated at 1-minute resolution on an equal-angle grid. The maps are stored in separate HDF files for each wavelength, each 16-day period and each albedo type (white- and black-sky). Data belonging to black sky and white sky albedo have been zipped separately. This format allows the user to have flexibility to download and store only the data absolutely needed.The One-Minute Land Ecosystem Classification Product is a global (static map) data set of the International Geosphere-Biosphere Programme (IGBP) classification scheme stored on an equal-angle rectangular grid at 1-minute resolution. The dataset is generated from the official MODIS land ecosystem classification dataset, MOD12Q1 for year 2000, day 289 data (October 15, 2000). This dataset is used in generating the spatially complete albedo maps, but is also a stand-alone product designed for use by the user community. The Land Ecosystem Classification Map File product file is stored in Hierarchical Data Format (HDF).

This map shows the structural configuration on the top of the Cotton Valley Group in feet below sea level. The map was produced by calculating the difference between a datum at the land surface (either the kelly bushing elevation or the ground surface elevation) and the reported depth of the Cotton Valley Group. This resulted in 10,687 wells for which locations were available. After deleting the wells with obvious data problems, a total of 10,504 wells were used to generate the map. The data are provided as both lines and polygons, and the proprietary wells that penetrate the top of the Cotton Valley Group are graphically displayed as quarter-mile cells. The well information was initially retrieved from the IHS Energy Group, PI/Dwights PLUS Well Data on CD-ROM, which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary PI/Dwights PLUS Well Data. No proprietary data are displayed or included in the cell maps. The data from PI/Dwights PLUS Well Data are current as of April 2001.

These DEMs were produced from digitized contours at a cell resolution of 100 meters. Vector contours of the area were used as input to a software package that interpolates between contours to create a DEM representing the terrain surface. The vector contours had a contour interval of 25 feet. The data cover the BOREAS MSAs of the SSA and NSA and are given in a UTM map projection.

This dataset provides sediment transport and land accretion model results at Wax Lake Delta (WLD), Atchafalaya Basin, in coastal Louisiana, USA. Data were simulated over the Delta-X Spring 2021 (2021-03-21 to 2021-04-03) and Fall 2021 (2021-08-14 to 2021-08-27) campaigns and the results are presented as annualized land accretion rate map. The model results for these two short-term campaigns are used to calculate the 1-year upscale land accretion rate at WLD in post-processing, which is also provided in this dataset. Model results for these two short-term campaigns were derived using inputs from an ANUGA hydrodynamic model. The Matlab sediment transport and land accretion model used to derive these data employs sediment transport theory that models floc behavior using a non-cohesive sediment transport framework. Data are presented in NetCDF (*.nc) format.

This data set provides the spatial distributions of vegetation types, soil carbon, and physiographic features in the Toolik Lake area, Alaska. Specific attributes include vegetation, percent water, glacial geology, soil carbon, a digital elevation model (DEM), surficial geology and surficial geomorphology.

This web map shows one year change in NDVI from January 15, 2023 to January 20 2024 using 10m Sentinel-2 imagery. The first filter applied determines pine-only land cover as of the winter of 2022-2023. The second filter is a pine patch size filter (at 0.25ha resolution), and further restricts the display to dense pine. Also removed are mixed pine-hardwood stands with lower densities of pine hosts. Although clear cuts have been removed using extreme NDVI change values, silvicultural thinning and other management activities remain in the change image causing non-beetle pine decline. This dataset includes the accumulated mortality from both the southern pine beetle and the Ips beetle.Commission errors in this dataset regard NDVI decline due to silviculture activities, and from some pasture/grass/ag. It is the viewers responsibility to assess the cause of pine decline by toggling the pine change image with the background natural color satellite image, and visually interpret the cause of NDVI changeAccuracy assessment: 87% This research dataset requires field investigation to confirm cause and determine disturbance severity For the companion satellite image used to create this pine change layer, see - MS beetle kill 2024, satellite image, 01/20/2024State-scale visualization of the extent of this disturbance - https://usfs.maps.arcgis.com/home/item.html?id=920d454b40e6454eabeece3db66ad02bLegend - https://usfs.maps.arcgis.com/home/item.html?id=6be28644958346779180f8d07df56b33

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

The Great River Environmental Action Team (GREAT) was a federal/state multi-agency cooperative program established in the late 1970's to evaluate current resource management practices and develop management strategies for the Upper Mississippi River (UMR). One of the problems facing the GREAT project was the lack of available information on many of the river's components. One project implemented by GREAT was the creation of a land cover/land use (LCU) database derived from color infrared aerial photography collected in 1975. Mississippi River Pools 3 through 10 were photographed at a scale of 1:9,600, and Lock and Dam 10 to the Ohio River were photographed at a scale of 1:24,000. The program's photo interpreters delineated whatever features could be viewed on the photos, using a minimum mapping unit that was less than half an acre. A contractor was hired to transfer the photo overlays for Pools 3 through 14 onto 1:24,000-scale USGS quadrangles, then automate the data using the geographic information system (GIS) program PIOS. The data were also distributed as map books that contained 1:6,000-scale enlargements of the photos and their overlays. During the data transfer process; the contractor hired to automate the data generalized it to a 2.5 acre minimum mapping unit. Documentation archived by the GREAT project described this automation process as; some polygons smaller than 2.5 acres and linear features were incorporated into nearby polygons. Others were manually enlarged so that the data contained within would be preserved. All generalizations were made in accordance with the guidelines established for the GREAT projects. The digital data sets were then enhanced by the GREAT project. Unfortunately no record of the enhancements or an archive of the original digital dataset are known to exist. The enhanced digital data, copies of the aerial photo overlays, copies of most of the map books, and some of the photos themselves were archived and preserved by the various agencies that participated in the GREAT project. These data were then passed to the Upper Midwest Environmental Sciences Center (UMESC) in the late 1980's and 1990's when the center became the administrator for the Upper Mississippi River System's Long Term Resource Monitoring Program (LTRMP). Comparisons of the archived digital data set to the photos and their overlays displayed discrepancies that were difficult to document. The 1975 data set is viewed by many as an important baseline data set, so in 1999 UMESC decided to use the archived photo overlays to (1) address the data discrepancies by reautomating Pools 3 through 14, and (2) complete the data set by automating Lock and Dam 14 to the Ohio River.

These data are part of a larger USGS project to develop an updated geospatial database of mines, mineral deposits and mineral regions in the United States. Mine and prospect-related symbols, such as those used to represent prospect pits, mines, adits, dumps, tailings, etc., hereafter referred to as “mine” symbols or features, are currently being digitized on a state-by-state basis from the 7.5-minute (1:24,000-scale) and the 15-minute (1:48,000 and 1:62,500-scale) archive of the USGS Historical Topographic Maps Collection, or acquired from available databases (California and Nevada, 1:24,000-scale only). Compilation of these features is the first phase in capturing accurate locations and general information about features related to mineral resource exploration and extraction across the U.S. To date, the compilation of 500,000-plus point and polygon mine symbols from approximately 67,000 maps of 22 western states has been completed: Arizona (AZ), Arkansas (AR), California (CA), Colorado (CO), Idaho (ID), Iowa (IA), Kansas (KS), Louisiana (LA), Minnesota (MN), Missouri (MO), Montana (MT), North Dakota (ND), Nebraska (NE), New Mexico (NM), Nevada (NV), Oklahoma (OK), Oregon (OR), South Dakota (SD), Texas (TX), Utah (UT), Washington (WA), and Wyoming (WY). The process renders not only a more complete picture of exploration and mining in the western U.S., but an approximate time line of when these activities occurred. The data may be used for land use planning, assessing abandoned mine lands and mine-related environmental impacts, assessing the value of mineral resources from Federal, State and private lands, and mapping mineralized areas and systems for input into the land management process. The data are presented as three groups of layers based on the scale of the source maps. No reconciliation between the data groups was done.