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 ½ 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.

Geospatial data about Bernalillo County, New Mexico Parcels. Export to CAD, GIS, PDF, CSV and access via API.

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 ½ 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. 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.

This data set is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information. This data set consists of georeferenced digital map data and computerized attribute data. The map data are in a soil survey area extent format and include a detailed, field verified inventory of soils and miscellaneous areas that normally occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped. A special soil features layer (point and line features) is optional. This layer displays the location of features too small to delineate at the mapping scale, but they are large enough and contrasting enough to significantly influence use and management. The soil map units are linked to attributes in the National Soil Information System relational database, which gives the proportionate extent of the component soils and their properties.

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 ½ 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. 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.

The Protected Areas Database of the United States (PAD-US) is a geodatabase, managed by USGS GAP, that illustrates and describes public land ownership, management and other conservation lands, including voluntarily provided privately protected areas. The State, Regional and LCC geodatabases contain two feature classes. The PADUS1_3_FeeEasement feature class and the national MPA feature class. Legitimate and other protected area overlaps exist in the full inventory, with Easements loaded on top of Fee. Parcel data within a protected area are dissolved in this file that powers the PAD-US Viewer. As overlaps exist, GAP creates separate analytical layers to summarize area statistics for "GAP Status Code" and "Owner Name". Contact the PAD-US Coordinator for more information. The lands included in PAD-US are assigned conservation measures that qualify their intent to manage lands for the preservation of biological diversity and to other natural, recreational and cultural uses; managed for these purposes through legal or other effective means. The geodatabase includes: 1) Geographic boundaries of public land ownership and voluntarily provided private conservation lands (e.g., Nature Conservancy Preserves); 2) The combination land owner, land manager, management designation or type, parcel name, GIS Acres and source of geographic information of each mapped land unit 3) GAP Status Code conservation measure of each parcel based on USGS National Gap Analysis Program (GAP) protection level categories which provide a measurement of management intent for long-term biodiversity conservation 4) IUCN category for a protected area's inclusion into UNEP-World Conservation Monitoring Centre's World Database for Protected Areas. IUCN protected areas are defined as, "A clearly defined geographical space, recognized, dedicated and managed, through legal or other effective means, to achieve the long-term conservation of nature with associated ecosystem services and cultural values" and are categorized following a classification scheme available through USGS GAP; 5) World Database of Protected Areas (WDPA) Site Codes linking the multiple parcels of a single protected area in PAD-US and connecting them to the Global Community. As legitimate and other overlaps exist in the combined inventory GAP creates separate analytical layers to obtain area statistics for "GAP Status Code" and "Owner Name". PAD-US version 1.3 Combined updates include: 1) State, local government and private protected area updates delivered September 2011 from PAD-US State Data Stewards: CO (Colorado State University), FL (Florida Natural Areas Inventory), ID (Idaho Fish and Game), MA (The Commonwealth's Office of Geographic Information Systems, MassGIS), MO (University of Missouri, MoRAP), MT (Montana Natural Heritage Program), NM (Natural Heritage New Mexico), OR (Oregon Natural Heritage Program), VA (Department of Conservation and Recreation, Virginia Natural Heritage Program). 2) Select local government (i.e. county, city) protected areas (3,632) across the country (to complement the current PAD-US inventory) aggregated by the Trust for Public Land (TPL) for their Conservation Almanac that tracks the conservation finance movement across the country. 3) A new Date of Establishment field that identifies the year an area was designated or otherwise protected, attributed for 86% of GAP Status Code 1 and 2 protected areas. Additional dates will be provided in future updates. 4) A national wilderness area update from wilderness.net 5) The Access field that describes public access to protected areas as defined by data stewards or categorical assignment by Primary Designation Type. . The new Access Source field documents local vs. categorical assignments. See the PAD-US Standard Manual for more information: gapanalysis.usgs.gov/padus 6) The transfer of conservation measures (i.e. GAP Status Codes, IUCN Categories) and documentation (i.e. GAP Code Source, GAP Code Date) from PAD-US version 1.2 or categorical assignments (see PAD-US Standard) when not provided by data stewards 7) Integration of non-sensitive National Conservation Easement Database (NCED) easements from August 2011, July 2012 with PAD-US version 1.2 easements. Duplicates were removed, unless 'Stacked' = Y and multiple easements exist. 8) Unique ID's transferred from NCED or requested for new easements. NCED and PAD-US are linked via Source UID in the PAD-US version 1.3 Easement feature class. 9) Official (member and eligible) MPAs from the NOAA MPA Inventory (March 2011, www.mpa.gov) translated into the PAD-US schema with conservation measures transferred from PAD-US version 1.2 or categorically assigned to new protected areas. Contact the PAD-US Coordinator for documentation of categorical GAP Status Code assignments for MPAs. 10) Identified MPA records that overlap existing protected areas in the PAD-US Fee feature class (i.e. PADUS Overlap field in MPA feature class). For example, many National Wildlife Refuges and National Parks are also MPAs and are represented in the PAD-US MPA and Fee feature classes.

This 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.

Baca Property, Sandoval County, N.M. Schlumberger Depth Sounds Line D

A digital orthophoto is a georeferenced image prepared from aerial imagery, or other remotely-sensed data in which the displacement within the image due to sensor orientation and terrain relief has been removed. Orthophotos combine the characteristics of an image with the geometric qualities of a map. Orthoimages show ground features such as roads, buildings, and streams in their proper positions, without the distortion characteristic of unrectified aerial imagery. Digital orthoimages produced and used within the Forest Service are developed from imagery acquired through various national and regional image acquisition programs. The resulting orthoimages, also known as orthomaps, can be directly applied in remote sensing, GIS and mapping applications. They serve a variety of purposes, from interim maps to references for earth science investigations and analysis. Because of the orthographic property, an orthoimage can be used like a map for measurement of distances, angles, and areas with scale being constant everywhere. Also, they can be used as map layers in GIS or other computer-based manipulation, overlaying, and analysis. An orthoimage differs from a map in a manner of depiction of detail; on a map only selected detail is shown by conventional symbols, whereas on an orthoimage all details appear just as in original aerial or satellite imagery.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoServiceFor complete information, please visit https://data.gov.

description: This data has been collected by the U.S. Bureau of Land Management (BLM) in New Mexico at the New Mexico State Office. The initial data source is the statewide Public Land Survey System (PLSS) coverage for the state of New Mexico, generated at the BLM New Mexico State Office. Additional data was onscreen-digitized from BLM Cadastral Survey Plats and Master Title Plats, or tablet-digitized from 1:24,000 paper maps. This revision reflects boundary adjustments made in the Albuquerque area to more accurately reflect boundaries as depicted on USGS 1:24,000 topographic maps. Note for Shapefiles: Shapefiles have been created from coverages using the "Export Coverage to Shapefile" function in ArcGIS 8.3. All occurrences of "#" and "-" in INFO item names are replaced with an underscore character. This includes COVER# and COVER-ID, which become "COVER_" and "COVER_ID". Additionally, the Shapefile format only allows 10 characters in item names, so long item names are truncated. To avoid duplicate names, the items are truncated and assigned consecutive numbers. For example, in a coverage called CITY_STREET the items "CITY_STREET#" and "CITY_STREET-ID" become "CITY_STRE" and "CITY_STR_1" .; abstract: This data has been collected by the U.S. Bureau of Land Management (BLM) in New Mexico at the New Mexico State Office. The initial data source is the statewide Public Land Survey System (PLSS) coverage for the state of New Mexico, generated at the BLM New Mexico State Office. Additional data was onscreen-digitized from BLM Cadastral Survey Plats and Master Title Plats, or tablet-digitized from 1:24,000 paper maps. This revision reflects boundary adjustments made in the Albuquerque area to more accurately reflect boundaries as depicted on USGS 1:24,000 topographic maps. Note for Shapefiles: Shapefiles have been created from coverages using the "Export Coverage to Shapefile" function in ArcGIS 8.3. All occurrences of "#" and "-" in INFO item names are replaced with an underscore character. This includes COVER# and COVER-ID, which become "COVER_" and "COVER_ID". Additionally, the Shapefile format only allows 10 characters in item names, so long item names are truncated. To avoid duplicate names, the items are truncated and assigned consecutive numbers. For example, in a coverage called CITY_STREET the items "CITY_STREET#" and "CITY_STREET-ID" become "CITY_STRE" and "CITY_STR_1" .

TITLE: Motor Vehicle Crashes, New Mexico, 2020- NMCRASHDATA2020

SUMMARY: All motor vehicle crashes locations in New Mexico updated for the year 2020, with information about injuries and other characteristics.

SOURCE: NM Department of Transportation; geocoded by NMDOT and UNM TRU

NOTE: POINT FILE. N=45,915; Geocoded by NMDOT-TRU

FEATURE SERVICE: https://nmcdc.maps.arcgis.com/home/item.html?id=5d9a0e1e56ec4b60bc115f9fdbf26c09

PREPARED BY: M.A. SEELEY, NMCDC

2020

VARIABLE DEFINITION

UCRnumber CRASH REPORT NUMBER

CrashDate CRASH DATE

Year CRASH YEAR

Month MONTH

CrashTime TIME OF CRASH

Hour HOUR OF CRASH

Day DAY OF WEEK

Agency LAW ENFORCEMENT AGENCY

County COUNTY

City CITY

AStreet PRIMARY STREET

Bstreet SECONDARY STREET

Landmark LANDMARK/LOCATION

GIS_Route GIS-DERIVED ROUTE NAME

GIS_Milepo GIS-DERIVED MILEPOST

Dir CRASH DIRECTION

Ldir DIRECTION FROM INTERSECTION OR LANDMARK

Distance DISTANCE FROM LANDMARK

Measure DISTANCE FROM LANDMARK MEASUREMENT UNIT

Severity CRASH SEVERITY

Killed NUMBER OF PEOPLE KILLED IN CRASH

ClassA NUMBER OF PEOPLE WITH SUSPECTED SERIOUS INJURIES (CLASS A) IN CRASH

ClassB NUMBER OF PEOPLE WITH SUSPECTED MINOR INJURIES (CLASS B) IN CRASH

ClassC NUMBER OF PEOPLE WITH POSSIBLE INJURIES (CLASS C) IN CRASH

TOTINJFAT NUMBER OF PEOPLE INJURED (CLASS A+B+C) IN CRASH

Unhurt NUMBER OF PEOPLE NOT INJURED (CLASS O) IN CRASH

Total TOTAL NUMBER OF PEOPLE IN CRASH

nVeh NUMBER OF VEHICLES, BICYCLES, AND PEDESTRIANS INVOLVED

PeopleMV NUMBER OF PEOPLE IN MOTOR VEHICLES

NoPeopleMV NUMBER OF PEOPLE NOT IN MOTOR VEHICLES

Mvinv NUMBER OF MOTOR VEHICLES INVOLVED

HarmOcc FIRST HARMFUL EVENT OCCURRED

Class CRASH CLASSIFICATION

Analysis CRASH ANALYSIS

HarmEvent FIRST HARMFUL EVENT

HarmAnalys FIRST HARMFUL EVENT - ANALYSIS

1HarmLoc FIRST HARMFUL EVENT – LOCATION

1HarmImpac FIRST HARMFUL EVENT – MANNER OF IMPACT

1HarmCrash FIRST HARMFUL EVENT – MANNER OF CRASH

Weather WEATHER

AddWeather ADDITIONAL WEATHER

LIGHTING LIGHTING

HitRun HIT AND RUN CRASH

ALCinv ALCOHOL INVOLVEMENT

DRUGinv DRUG INVOLVEMENT

PEDinv PEDESTRIAN INVOLVEMENT

MCinv MOTORCYCLE INVOLVEMENT

PECinv PEDALCYCLE INVOLVEMENT

TRKinv HEAVY TRUCK INVOLVEMENT

COMMinv COMMERICAL MOTOR VEHICLE INVOLVEMENT

SCHBUSinv SCHOOL BUS DIRECT INVOLVEMENT

HAZMATinv HAZARDOUS MATERIAL INVOLVEMENT

NONLOCinv INVOLVEMENT OF NON-LOCAL DRIVER

STHWYprop STATE HIGHWAY DEPT. PROPERTY

RoadSystem ROAD SYSTEM: URBAN, RURAL OR RURAL INTERSTATE

MaxDam MAXIMUM VEHICLE DAMAGE

WorkZone WORK ZONE

WRKZNtype WORK ZONE - TYPE

WRKZNloc WORK ZONE – LOCATION

RoadCharac ROAD CHARACTER

RoadGrade ROAD GRADE

Intersect INTERSECTION TYPE

Relation RELATION TO JUNCTION

Secondary SECONDARY CRASH

Tribal TRIBAL JURISDICTION

GIS_Reserv GIS-DERIVED RESERVATION

GIS_STHWY GIS-DERIVED STATE HIGHWAY TRANSPORTATION DISTRICT

GIS_STPol GIS-DERIVED STATE POLICE DISTRICT

GIS_HWMain GIS-DERIVED STATE HIGHWAY MAINTENANCE DISTRICT

GIS_UTMX GIS-DERIVED UTM X COORDINATE

GIS_UTMY GIS-DERIVED UTM Y COORDINATE

GIS_Lat GIS-DERIVED LATITUDE COORDINATE

GIS_Long GIS-DERIVED LONGITUDE COORDINATE

ORIGLat ORIGINAL LATITUDE

ORIGLong ORIGINAL LONGITUDE

UCRorig ORIGINAL UCR NUMBER

CaseNumber CASE NUMBER

StationRep STATION REPORT

TRACSdata TRACS DATA

A digital orthophoto is a georeferenced image prepared from aerial imagery, or other remotely-sensed data in which the displacement within the image due to sensor orientation and terrain relief has been removed. Orthophotos combine the characteristics of an image with the geometric qualities of a map. Orthoimages show ground features such as roads, buildings, and streams in their proper positions, without the distortion characteristic of unrectified aerial imagery. Digital orthoimages produced and used within the Forest Service are developed from imagery acquired through various national and regional image acquisition programs. The resulting orthoimages, also known as orthomaps, can be directly applied in remote sensing, GIS and mapping applications. They serve a variety of purposes, from interim maps to references for earth science investigations and analysis. Because of the orthographic property, an orthoimage can be used like a map for measurement of distances, angles, and areas with scale being constant everywhere. Also, they can be used as map layers in GIS or other computer-based manipulation, overlaying, and analysis. An orthoimage differs from a map in a manner of depiction of detail; on a map only selected detail is shown by conventional symbols, whereas on an orthoimage all details appear just as in original aerial or satellite imagery.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoServiceFor complete information, please visit https://data.gov.

A digital orthophoto is a georeferenced image prepared from aerial imagery, or other remotely-sensed data in which the displacement within the image due to sensor orientation and terrain relief has been removed. Orthophotos combine the characteristics of an image with the geometric qualities of a map. Orthoimages show ground features such as roads, buildings, and streams in their proper positions, without the distortion characteristic of unrectified aerial imagery. Digital orthoimages produced and used within the Forest Service are developed from imagery acquired through various national and regional image acquisition programs. The resulting orthoimages, also known as orthomaps, can be directly applied in remote sensing, GIS and mapping applications. They serve a variety of purposes, from interim maps to references for earth science investigations and analysis. Because of the orthographic property, an orthoimage can be used like a map for measurement of distances, angles, and areas with scale being constant everywhere. Also, they can be used as map layers in GIS or other computer-based manipulation, overlaying, and analysis. An orthoimage differs from a map in a manner of depiction of detail; on a map only selected detail is shown by conventional symbols, whereas on an orthoimage all details appear just as in original aerial or satellite imagery.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoServiceFor complete information, please visit https://data.gov.

Predios digital, Cd Juárez, Chih

© IMIP. (Instituto Municipal de Investigación y Planeación) This layer is a component of New Template.

Debris flows, debris avalanches, mud flows and lahars are fast-moving landslides that occur in a wide variety of environments throughout the world. They are particularly dangerous to life and property because they move quickly, destroy objects in their paths, and can strike with little warning. The purpose of this map is to show where debris flows have occurred in the conterminous United States and where these slope movements might be expected in the future.

Data was compiled from published sources by US Geological Survey geoscientists Mark J. Mihalasky, Susan M. Hall and Robert A. Zielinski. This dataset was provided to the U.S. Energy Information Administration in February of 2019 to facilitate updating of national uranium resource distribution maps. The location of uranium provinces, districts and select important deposits located outside of these broader regions was taken from a variety of sources listed alphabetically below.Adams S.S.; Smith R.B., 1981, Geology and recognition criteria for sandstone uranium deposits in mixed fluvial-shallow marine sedimentary sequences, South Texas; U.S. Department of Energy Report GJBX-4(81), 145 p.Colorado Geological Survey, 2018, Uranium Districts – Colorado; published on the Colorado Geological Survey website at http://coloradogeologicalsurvey.org/energy-resources/uranium2/map/.Chenoweth, W.L., 1980, Uranium in Colorado; Rocky Mountain Association of Geologists, 1980 Symposium, p. 217-224Gloyn, R.W.; Bon, R.L.; Wakefield, S.; Krahulec, K., 2005, Uranium and vanadium map of Utah; Map 215, Utah Department of Natural Resources, Utah Geological Survey, 1:750,000 scale, 1 sheet. Metadata download at: https://gis.utah.gov/data/energy/uranium/Gregory R.W., 2016, Uranium: Geology and Applications; Wyoming State Geological Survey Public Information Circular No 46, 36 p.Keith, S.B.; Gest, D.E.; DeWitt, E; 1983, Metallic mineral districts of Arizona; Arizona Bureau of Geology and Mineral Technology, Geological Survey Branch, Tucson, AZ, 1:1,000,000 scale, 1 sheetKyle L, Beahm D, 2013, NI 43-101 preliminary economic assessment update (revised), Coles Hill uranium property, Pittsylvania County, VA USA; prepared by Lyntek Incorporated, Lakewood, CO; 2013, 126 p. Figure 1.1.McLemore, V.T. and Chenoweth, W.L., 1989, Uranium resources in New Mexico; New Mexico Bureau of Mines and Minerals Resources, Resource Map 18, 36 p. Available at: https://geoinfo.nmt.edu/faq/mining/home.html

A digital orthophoto is a georeferenced image prepared from aerial imagery, or other remotely-sensed data in which the displacement within the image due to sensor orientation and terrain relief has been removed. Orthophotos combine the characteristics of an image with the geometric qualities of a map. Orthoimages show ground features such as roads, buildings, and streams in their proper positions, without the distortion characteristic of unrectified aerial imagery. Digital orthoimages produced and used within the Forest Service are developed from imagery acquired through various national and regional image acquisition programs. The resulting orthoimages, also known as orthomaps, can be directly applied in remote sensing, GIS and mapping applications. They serve a variety of purposes, from interim maps to references for earth science investigations and analysis. Because of the orthographic property, an orthoimage can be used like a map for measurement of distances, angles, and areas with scale being constant everywhere. Also, they can be used as map layers in GIS or other computer-based manipulation, overlaying, and analysis. An orthoimage differs from a map in a manner of depiction of detail; on a map only selected detail is shown by conventional symbols, whereas on an orthoimage all details appear just as in original aerial or satellite imagery.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoServiceFor complete information, please visit https://data.gov.

The Lands pdf represent the location and project number of NMDOT Construction projects.

This polygon feature class represents the spatial extent and boundaries for BLM Grazing Allotments.

A digital orthophoto is a georeferenced image prepared from aerial imagery, or other remotely-sensed data in which the displacement within the image due to sensor orientation and terrain relief has been removed. Orthophotos combine the characteristics of an image with the geometric qualities of a map. Orthoimages show ground features such as roads, buildings, and streams in their proper positions, without the distortion characteristic of unrectified aerial imagery. Digital orthoimages produced and used within the Forest Service are developed from imagery acquired through various national and regional image acquisition programs. The resulting orthoimages, also known as orthomaps, can be directly applied in remote sensing, GIS and mapping applications. They serve a variety of purposes, from interim maps to references for earth science investigations and analysis. Because of the orthographic property, an orthoimage can be used like a map for measurement of distances, angles, and areas with scale being constant everywhere. Also, they can be used as map layers in GIS or other computer-based manipulation, overlaying, and analysis. An orthoimage differs from a map in a manner of depiction of detail; on a map only selected detail is shown by conventional symbols, whereas on an orthoimage all details appear just as in original aerial or satellite imagery.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoServiceFor complete information, please visit https://data.gov.