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TwitterThe 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/ .
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TwitterThis dataset is part of the Cadastral National Spatial Data Infrastructure (CadNSDI) publication dataset for rectangular and non‐rectangular Public Land Survey System (PLSS) data.
This dataset represents the GIS Version of the Public Land Survey System including both rectangular and non-rectangular surveys. The primary source for the data is cadastral survey records housed by the BLM supplemented with local records and geographic control coordinates from states, counties as well as other federal agencies such as the USGS and USFS. The data has been converted from source documents to digital form and transferred into a GIS format that is compliant with FGDC Cadastral Data Content Standards and Guidelines for publication. This data is optimized for data publication and sharing rather than for specific "production" or operation and maintenance. This data set includes the following: PLSS Fully Intersected (all of the PLSS feature at the atomic or smallest polygon level), 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 and Conflicted Areas (known areas of gaps or overlaps between Townships or state boundaries). The Entity-‐ Attribute section of this metadata describes these components in greater detail.
The CadNSDI or the Cadastral Publication Data Standard is the cadastral data component of the NSDI. This is the publication guideline for cadastral data that is intended to provide a common format and structure and content for cadastral information that can be made available across jurisdictional boundaries, providing a consistent and uniform cadastral data to meet business need that includes connections to the source information from the data stewards. The data stewards determine which data are published and should be contacted for any questions on data content or for additional information. The cadastral publication data is data provided by cadastral data producers in a standard form on a regular basis.
Cadastral publication data has two primary components, land parcel data and cadastral reference data. It is important to recognize that the publication data are not the same as the operation and maintenance or production data. The production data is structured to optimize maintenance processes, is integrated with internal agency operations and contains much more detail than the publication data. The publication data is a subset of the more complete production data and is reformatted to meet a national standard so data can be integrated across jurisdictional boundaries and be presented in a consistent and standard form nationally.
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TwitterThis dataset is known as Surface Management Agency (SMA) and was originally derived from the LAND dataset produced by the Arizona State Land Dept., Arizona Land Resource Information System (ALRIS). The LAND dataset was first started in 1984 and updated in the spring 1988 by the State Land Department Forestry Division and ALRIS. The original PLSS data is from the Department of Transportation (ADOT) and was digitized at 1:100,000 scale. The data was then projected into ARC/INFO format and edited using the procedures from the ASLD 'Land Status Map Digitizing Procedure' guide. The dataset covers the entire State of Arizona. Changes in federal agencies are done through the Bureau of Land Management (BLM). BLM incorporates the federal land changes such as the BLM, Forest Service, Bureau of Reclamation, Fish & Wildlife Service, National Park Service, etc. BLM and State of Arizona surface management is updated approximately every six months in a cooperative effort with the Arizona State Land Department (ASLD). In 2011, the BLM contracted with Premier Data Services to conflate the SMA with the latest and more accurate PLSS known as the Cadastral National Spatial Data Infrastructure (CadNSDI) which is the most accurate PLSS available. This procedure has greatly improved the locational accuracy of the SMA. For purposes of simplicity, the BLM has also reduced the complexity of the dataset by removing all data except for the surface management information.
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This data set is known as Surface Management Agency (SMA) and was originally derived from the LAND data set produced by the Arizona State Land Dept., Arizona Land Resource Information System (ALRIS). The LAND data set was first started in 1984 and updated in the spring 1988 by the State Land Department Forestry Division and ALRIS. The original PLSS data is from the Department of Transportation (ADOT) and was digitized at 1:100,000 scale. The data was then projected into ARC/INFO format and edited using the procedures from the ASLD 'Land Status Map Digitizing Procedure' guide. The data set covers the entire State of Arizona and includes surface management, the original plss, and county and state boundaries. Changes in federal agencies are done through the Bureau of Land Management (BLM). BLM incorporates the federal land changes such as the BLM, Forest Service, Bureau of Reclamation, Fish & Wildlife Service, National Park Service, etc. BLM and State of Arizona surface management is updated approximately every six months in a cooperative effort with the Arizona State Land Department (ASLDIn 2011, the BLM contracted with Premier Data Services to conflate the SMA with the latest and more accurate PLSS know as the Cadastral National Spatial Data Infrastructure (CadNSDI) which is the most accurate PLSS available. This procedure has greatly improved the locational accuracy of the SMA. For purposes of simplicity, the BLM has also reduced the complexity of the data set by removing all data except for the surface management information.
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TwitterLayer can be downloaded at: https://asu.maps.arcgis.com/home/item.html?id=0f3f2464210544868499f4f45af889ed#overviewThe U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released four National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, and 2011. These products provide spatially explicit and reliable information on the Nation’s land cover and land cover change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s land resources, the USGS has designed a new generation of NLCD products named NLCD 2016. The NLCD 2016 design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land cover and land cover change database from 2001 to 2016 at 2–3-year intervals. Comprehensive research was conducted and resulted in developed strategies for NLCD 2016: a streamlined process for assembling and preprocessing Landsat imagery and geospatial ancillary datasets; a multi-source integrated training data development and decision-tree based land cover classifications; a temporally, spectrally, and spatially integrated land cover change analysis strategy; a hierarchical theme-based post-classification and integration protocol for generating land cover and change products; a continuous fields biophysical parameters modeling method; and an automated scripted operational system for the NLCD 2016 production. The performance of the developed strategies and methods were tested in twenty World Reference System-2 path/row throughout the conterminous U.S. An overall agreement ranging from 71% to 97% between land cover classification and reference data was achieved for all tested area and all years. Results from this study confirm the robustness of this comprehensive and highly automated procedure for NLCD 2016 operational mapping. Questions about the NLCD 2016 land cover product can be directed to the NLCD 2016 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details.*This land cover layer was extracted from the United States land cover layer and reprojected to UTM12.
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TwitterThis 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
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TwitterThe purpose of this dataset is to fulfill the public and Government’s need to know which agency is managing Federal land in a given area. For example, there may be a need to know what agency is managing a certain tract of land for the purpose of paying permit fees, obtaining licenses, or becoming informed about current laws, regulations, and restrictions governing access to and use of the land. This dataset serves as a tool to determine and illustrate the boundaries of a particular Federal agency’s “managing” area and to quantify these areas in terms of geographic acreage. These data are public information and may be used by various organizations, agencies, units of government (i.e., Federal, state, county, and city), and other entities. The geographic acreages contained in this dataset are not derived from legal documents associated with title documents or survey records. Rather, they are computed by mathematical programs and are described in detail in the supplemental section of the definition document referenced at the end of this section.The data can be used for small scale (1:24,000 and smaller) analysis and cartographic products.SMA was originally derived from the land dataset produced by the Arizona State Land Dept (ASLD), and the Arizona Land Resource Information System (ALRIS). The land dataset was initiated in 1984 and updated in the spring of 1988 by the State Land Department Forestry Division and ALRIS. The data was then projected into ARC/INFO format and edited using the procedures from the ASLD Land Status Map Digitizing Procedure guide. The land dataset covers the entire State of Arizona and includes surface management, public land survey system (PLSS) provided by the Department of Transportation (ADOT), and county and state boundaries.
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TwitterThis map presents land cover and detailed topographic maps for the United States. It uses the USA Topographic Map service. The map includes the National Park Service (NPS) Natural Earth physical map at 1.24km per pixel for the world at small scales, i-cubed eTOPO 1:250,000-scale maps for the contiguous United States at medium scales, and National Geographic TOPO! 1:100,000 and 1:24,000-scale maps (1:250,000 and 1:63,000 in Alaska) for the United States at large scales. The TOPO! maps are seamless, scanned images of United States Geological Survey (USGS) paper topographic maps.
The maps provide a very useful basemap for a variety of applications, particularly in rural areas where the topographic maps provide unique detail and features from other basemaps.
To add this map service into a desktop application directly, go to the entry for the USA Topo Maps map service.
Tip: Here are some famous locations as they appear in this web map, accessed by including their location in the URL that launches the map:
The Statue of Liberty, New York
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Twitter7.5 Minute Digital Elevation Model for the state of Arizona. Digital Elevation Model (DEM) is the terminology adopted by the USGS to describe terrain elevation data sets in a digital raster form. The standard DEM consists of a regular array of elevations cast on a designated coordinate projection system. The DEM data are stored as a series of profiles in which the spacing of the elevations along and between each profile is in regular whole number intervals. The normal orientation of data is by columns and rows. Each column contains a series of elevations ordered from south to north with the order of the columns from west to east. The DEM is formatted as one ASCII header record (A-record), followed by a series of profile records (B-records) each of which include a short B-record header followed by a series of ASCII integer elevations per each profile. The last physical record of the DEM is an accuracy record (C-record). The DEM for 7.5-minute units correspond to the USGS 1:24000 scale topographic quadrangle map series for all of the United States and its territories. Each 7.5 minute DEM is based on 30- by 30-meter data spacing with Universal Transverse Mercator(UTM) projection. Each 7.5- by 7.5-minute block provides the same coverage as the standard USGS 7.5-minute map series.
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TwitterThis data set depicts federal lands having restrictions on access or activities -- that is, lands mangaed by the National Park Service, Defense Department, or Energy Department -- in western North America. The data set was created by reformatting and merging state- and province-based ownership data layers originally acquired from diverse sources (including state GAP programs, USBLM state offices and other sources). For each original dataset 3 additional fields, "Pub_Pvt", "CA_OWN", and "SOURCE" were added and populated based on the specific ownership information contained in the source data. The original coverages were then merged based on the "CA_OWN" field. Finally, NPS, DOD, and DOE lands were selected out of the ownership layer. All work was completed in AcMap 8.3. This product and all source data are available online from SAGEMAP: http://sagemap.wr.usgs.gov.
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TwitterThe EnviroAtlas Phoenix, AZ Meter-Scale Urban Land Cover (MULC) data and map were generated from USDA NAIP (National Agricultural Imagery Program) four band (red, green, blue and near-infrared) aerial photography taken from June through September, 2010 at 1 m spatial resolution. Seven land cover classes were mapped: water, impervious surfaces, soil and barren land, trees and forest, shrubs, grass and herbaceous non-woody vegetation, and agriculture. An accuracy assessment using a completely random sampling of 598 land cover reference points yielded an overall user's accuracy (MAX) of 69.2% and an overall fuzzy user's accuracy of 75.4%. The area mapped includes the entirety of the Central Arizona-Phoenix Long-Term Ecological Research (CAP-LTER) area, which was classified by the Environmental Remote Sensing and Geoinformatics Lab (ERSG) at Arizona State University. The land cover dataset also includes an area of approximately 625 square kilometers which is located north of Phoenix. This section was classified by the EPA land cover classification team. This dataset was produced by the Environmental Remote Sensing and Geoinformatics Lab (ERSG) at Arizona State University and the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).
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TwitterU.S. Government Workshttps://www.usa.gov/government-works
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Annual (1986-2020) land-use/land cover maps at 30-meter resolution of the Tucson metropolitan area, Arizona and the greater Santa Cruz Watershed including Nogales, Sonora, Mexico. Maps were created using a combination of Landsat imagery, derived transformation and indices, texture analysis and other ancillary data fed to a Random Forest classifier in Google Earth Engine. The maps contain 13 classes based on the National Land Cover Classification scheme and modified to reflect local land cover types. Data are presented as a stacked, multi-band raster with one "band" for each year (Band 1 = 1986, Band 2 = 1987 and so on). Note that the year 2012 was left out of our time series because of lack of quality Landsat data. A color file (.clr) is included that can be imported to match the color of the National Land Cover Classification scheme. This data release also contains two JavaScript files with the Google Earth Engine code developed for pre-processing Landsat imagery and for image ...
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TwitterThis data set is known as Surface Management Agency (SMA) and was originally derived from the LAND data set produced by the Arizona State Land Dept., Arizona Land Resource Information System (ALRIS). The LAND data set was first started in 1984 and updated in the spring 1988 by the State Land Department Forestry Division and ALRIS. The original PLSS data is from the Department of Transportation (ADOT) and was digitized at 1:100,000 scale. The data was then projected into ARC/INFO format and edited using the procedures from the ASLD 'Land Status Map Digitizing Procedure' guide. The data set covers the entire State of Arizona and includes surface management, the original plss, and county and state boundaries. Changes in federal agencies are done through the Bureau of Land Management (BLM). BLM incorporates the federal land changes such as the BLM, Forest Service, Bureau of Reclamation, Fish & Wildlife Service, National Park Service, etc. BLM and State of Arizona surface management is updated approximately every six months in a cooperative effort with the Arizona State Land Department (ASLDIn 2011, the BLM contracted with Premier Data Services to conflate the SMA with the latest and more accurate PLSS know as the Cadastral National Spatial Data Infrastructure (CadNSDI) which is the most accurate PLSS available. This procedure has greatly improved the locational accuracy of the SMA. For purposes of simplicity, the BLM has also reduced the complexity of the data set by removing all data except for the surface management information.
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TwitterState Trust Parcels
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TwitterThis dataset has been created to meet the needs of the research community of Arizona State University. Apart from purely vizualization purposes (i.e. displaying the data on various maps) it can potentially be used for spatial modeling. The data consist of engineering-quality contours, also known as isolines, created from the NED 10-meter Digital Elevation Model subset to the extent somewhat exceeding Cetral Arizona - Phoenix LTER. Contours ( lines connecting points of equal height above sea level) are drawn at 15 meter intervals with the base set at 145 m of elevation. Contours are an exact interpretation of the grid surface model and may sometimes appear blocky looking, may cross, appear to intersect, or form an unclosed branching line. All these are valid engineering-quality interpretations of the elevation surface that cartographers typically modify (smooth) for aesthetic purposes.
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TwitterThis EnviroAtlas dataset describes the percentage of each block group that is classified as impervious, forest, agriculture, and green space. Forest is combination of trees and forest. Green space is a combination of trees and forest, grass and herbaceous, and agriculture. This dataset also includes the area per capita for each block group for impervious, forest, and green space land cover. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas ) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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OpenData showing Tribal Trust Lands, Public Lands from Yavapai County, AZ. Published in Central AZ State Plane Coordinate System. No definition queries. This is replacing the existing OpenData that was originally published from the County web server (yavapaiaz.gov) and has been moved to the Yavapai County ArcGIS Online Organization. This is a AGOL VIEW of public land use (land ownership) created weekly from a dissolve of tax parcels and updated to the web service. This is being hosted on ArcGIS Online as a web service VIEW. This data was intended for general location mapping purposes and is not suitable for legal, engineering, or surveying purposes. This is Yavapai County OpenData, https://data-yavgis.opendata.arcgis.com/.
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TwitterOnline digital geological map database of Arizona created by the Bureau of Land Mangement and Arizona Geologic Survey.
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TwitterThese 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 â mineâ 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.
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TwitterU.S. Government Workshttps://www.usa.gov/government-works
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This is map 2 of a 7-map series depicting the Havasu Travel Management Area (TMA) as administered by the Bureau of Land Management. Travel is restricted to designated roads and trails as defined in the map.
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TwitterThe 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/ .