BLM NV PLSSSpecialSurvey: 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 Digital Geologic-GIS Map of Great Basin National Park and Vicinity, Nevada is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) an ESRI file geodatabase (grba_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro 3.X map file (.mapx) file (grba_geology.mapx) and individual Pro 3.X layer (.lyrx) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) a readme file (grba_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (grba_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (grba_geology_metadata_faq.pdf). Please read the grba_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri.htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: Stanford University and the Stanford Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (grba_geology_metadata.txt or grba_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:24,000 and United States National Map Accuracy Standards features are within (horizontally) 12.2 meters or 40 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS Pro, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

This submission contains an ESRI map package (.mpk) with an embedded geodatabase for GIS resources used or derived in the Nevada Machine Learning project, meant to accompany the final report. The package includes layer descriptions, layer grouping, and symbology. Layer groups include: new/revised datasets (paleo-geothermal features, geochemistry, geophysics, heat flow, slip and dilation, potential structures, geothermal power plants, positive and negative test sites), machine learning model input grids, machine learning models (Artificial Neural Network (ANN), Extreme Learning Machine (ELM), Bayesian Neural Network (BNN), Principal Component Analysis (PCA/PCAk), Non-negative Matrix Factorization (NMF/NMFk) - supervised and unsupervised), original NV Play Fairway data and models, and NV cultural/reference data. See layer descriptions for additional metadata. Smaller GIS resource packages (by category) can be found in the related datasets section of this submission. A submission linking the full codebase for generating machine learning output models is available through the "Related Datasets" link on this page, and contains results beyond the top picks present in this compilation.

The data contained in this map reflects project location data supplied by SNC grantees for grants awarded by the Sierra Nevada Conservancy. Some implementation projects predate SNC’s current policy, beginning in 2017, to acquire polygons for all new projects. As a result project location data on this map consists of a mixture of both point and polygon grant locations. Additionally, some planning, education, and other grants were region wide. These are only represented by location points provided by the grantee as well. The layers in this map may update as our Governing Board awards new grants.

This shapefile represents habitat suitability categories (High, Moderate, Low, and Non-Habitat) derived from a composite, continuous surface of sage-grouse habitat suitability index (HSI) values for Nevada and northeastern California during the winter season, and is a surrogate for habitat conditions during periods of cold and snow. Summary of steps to create Habitat Categories: HABITAT SUITABILITY INDEX: The HSI was derived from a generalized linear mixed model (specified by binomial distribution and created using ArcGIS 10.2.2) that contrasted data from multiple environmental factors at used sites (telemetry locations) and available sites (random locations). Predictor variables for the model represented vegetation communities at multiple spatial scales, water resources, habitat configuration, urbanization, roads, elevation, ruggedness, and slope. Vegetation data was derived from various mapping products, which included NV SynthMap (Petersen 2008, SageStitch (Comer et al. 2002, LANDFIRE (Landfire 2010), and the CA Fire and Resource Assessment Program (CFRAP 2006). The analysis was updated to include high resolution percent cover within 30 x 30 m pixels for Sagebrush, non-sagebrush, herbaceous vegetation, and bare ground (C. Homer, unpublished; based on the methods of Homer et al. 2014, Xian et al. 2015 ) and conifer (primarily pinyon-juniper, P. Coates, unpublished). The pool of telemetry data included the same data from 1998 - 2013 used by Coates et al. (2014); additional telemetry location data from field sites in 2014 were added to the dataset. The dataset was then split according calendar date into three seasons (spring, summer, winter). Winter included telemetry locations (n = 4862) from November to March. All age and sex classes of marked grouse were used in the analysis. Sufficient data (i.e., a minimum of 100 locations from at least 20 marked Sage-grouse) for modeling existed in 10 subregions for spring and summer, and seven subregions in winter, using all age and sex classes of marked grouse. It is important to note that although this map is composed of HSI values derived from the seasonal data, it does not explicitly represent habitat suitability for reproductive females (i.e., nesting and with broods). Insufficient data were available to allow for estimation of this habitat type for all seasons throughout the study area extent. A Resource Selection Function (RSF) was calculated for each subregion using R software (v 3.13) and using generalized linear models to derive model-averaged parameter estimates for each covariate across a set of additive models. Subregional RSFs were transformed into Habitat Suitability Indices, and averaged together to produce an overall statewide HSI whereby a relative probability of occurrence was calculated for each raster cell during the spring season. In order to account for discrepancies in HSI values caused by varying ecoregions within Nevada, the HSI was divided into north and south extents using a slightly modified flood region boundary (Mason 1999) that was designed to represent respective mesic and xeric regions of the state. North and south HSI rasters were each relativized according to their maximum value to rescale between zero and one, then mosaicked once more into a state-wide extent. HABITAT CATEGORIZATION: Using the same ecoregion boundaries described above, the habitat classification dataset (an independent data set comprising 10% of the total telemetry location sample) was split into locations falling within respective north and south regions. HSI values from the composite and relativized statewide HSI surface were then extracted to each classification dataset location within the north and south region. The distribution of these values were used to identify class break values corresponding to 0.5 (high), 1.0 (moderate), and 1.5 (low) standard deviations (SD) from the mean HSI. These class breaks were used to classify the HSI surface into four discrete categories of habitat suitability: High, Moderate, Low, and Non-Habitat. In terms of percentiles, High habitat comprised greater than 30.9 % of the HSI values, Moderate comprised 15 – 30.9%, Low comprised 6.7 – 15%, and Non-Habitat comprised less than 6.7%.The classified north and south regions were then clipped by the boundary layer and mosaicked to create a statewide categorical surface for habitat selection . Each habitat suitability category was converted to a vector output where gaps within polygons less than 1.2 million square meters were eliminated, polygons within 500 meters of each other were connected to create corridors and polygons less than 1.2 million square meters in one category were incorporated to the adjacent category. The final step was to mask major roads that were buffered by 50m (Census, 2014), lakes (Peterson, 2008) and urban areas, and place those masked areas into the non-habitat category. The existing urban layer (Census 2010) was not sufficient for our needs because it excluded towns with a population lower than 1,500. Hence, we masked smaller towns (populations of 100 to 1500) and development with Census Block polygons (Census 2015) that had at least 50% urban development within their boundaries when viewed with reference imagery (ArcGIS World Imagery Service Layer). REFERENCES: California Forest and Resource Assessment Program (CFRAP). 2006. Statewide Land Use / Land Cover Mosaic. [Geospatial data.] California Department of Forestry and Fire Protection, http://frap.cdf.ca.gov/data/frapgisdata-sw-rangeland-assessment_data.php Census 2010. TIGER/Line Shapefiles. Urban Areas [Geospatial data.] U.S. Census Bureau, Washington D.C., https://www.census.gov/geo/maps-data/data/tiger-line.html Census 2014. TIGER/Line Shapefiles. Roads [Geospatial data.] U.S. Census Bureau, Washington D.C., https://www.census.gov/geo/maps-data/data/tiger-line.html Census 2015. TIGER/Line Shapefiles. Blocks [Geospatial data.] U.S. Census Bureau, Washington D.C., https://www.census.gov/geo/maps-data/data/tiger-line.html Coates, P.S., Casazza, M.L., Brussee, B.E., Ricca, M.A., Gustafson, K.B., Overton, C.T., Sanchez-Chopitea, E., Kroger, T., Mauch, K., Niell, L., Howe, K., Gardner, S., Espinosa, S., and Delehanty, D.J. 2014, Spatially explicit modeling of greater sage-grouse (Centrocercus urophasianus) habitat in Nevada and northeastern California—A decision-support tool for management: U.S. Geological Survey Open-File Report 2014-1163, 83 p., http://dx.doi.org/10.3133/ofr20141163. ISSN 2331-1258 (online) Comer, P., Kagen, J., Heiner, M., and Tobalske, C. 2002. Current distribution of sagebrush and associated vegetation in the western United States (excluding NM). [Geospatial data.] Interagency Sagebrush Working Group, http://sagemap.wr.usgs.gov Homer, C.G., Aldridge, C.L., Meyer, D.K., and Schell, S.J. 2014. Multi-Scale Remote Sensing Sagebrush Characterization with Regression Trees over Wyoming, USA; Laying a Foundation for Monitoring. International Journal of Applied Earth Observation and Geoinformation 14, Elsevier, US. LANDFIRE. 2010. 1.2.0 Existing Vegetation Type Layer. [Geospatial data.] U.S. Department of the Interior, Geological Survey, http://landfire.cr.usgs.gov/viewer/ Mason, R.R. 1999. The National Flood-Frequency Program—Methods For Estimating Flood Magnitude And Frequency In Rural Areas In Nevada U.S. Geological Survey Fact Sheet 123-98 September, 1999, Prepared by Robert R. Mason, Jr. and Kernell G. Ries III, of the U.S. Geological Survey; and Jeffrey N. King and Wilbert O. Thomas, Jr., of Michael Baker, Jr., Inc. http://pubs.usgs.gov/fs/fs-123-98/ Peterson, E. B. 2008. A Synthesis of Vegetation Maps for Nevada (Initiating a 'Living' Vegetation Map). Documentation and geospatial data, Nevada Natural Heritage Program, Carson City, Nevada, http://www.heritage.nv.gov/gis Xian, G., Homer, C., Rigge, M., Shi, H., and Meyer, D. 2015. Characterization of shrubland ecosystem components as continuous fields in the northwest United States. Remote Sensing of Environment 168:286-300. NOTE: This file does not include habitat areas for the Bi-State management area and the spatial extent is modified in comparison to Coates et al. 2014

Vector polygon map data of property parcels from Las Vegas, Nevada, containing 794,465 features.

Property parcel GIS map data consists of detailed information about individual land parcels, including their boundaries, ownership details, and geographic coordinates.

Property parcel data can be used to analyze and visualize land-related information for purposes such as real estate assessment, urban planning, or environmental management.

Available for viewing and sharing as a map in a Koordinates map viewer. This data is also available for export to DWG for CAD, PDF, KML, CSV, and GIS data formats, including Shapefile, MapInfo, and Geodatabase.

CDFW BIOS GIS Dataset, Contact: Bob Kingman, Description: According to GreenInfo Network and the California Department of Fish and Game, the blue oak woodland used to define a portion of the Sierra Nevada Conservancy's western boundary was delineated using referenced vegetation and imagery data. To display the Sierra Nevada Conservancy boundary.

Nevada sand dunes.

Very incomplete, compilation in progress. Most relevant features south of latitude 39°-40°N have been captured, and attributes populated when known. North of that, only features visible on the 1998 GAP Land Cover 30-m grid data have been captured in rough form, and review, capture, refinement, and attribution of mapped features remains to be done.

When complete, these data will include all sand dune features depicted on current 1:100,000 topographic maps, plus some major features depicted only on 1:24,000 topographic maps. Compilation began by on-screen capture of sand dune areas depicted in the 1998 Nevada GAP Land Cover 30-m grid data. The 1:100,000 DRG topographic maps covering Nevada were then reviewed on-screen in series from south to north and from east to west. Boundaries of GAP-indicated features were refined, and all other mapped dune features were digitized on-screen and attributed. In some cases, major known dune features were captured and/or further refined using 1:24,000 DRG topographic maps.

Source: http://heritage.nv.gov/gis/gis.htm#downloads

Tax rate area boundaries and related data based on changes filed with the Board of Equalization per Government Code 54900 for the specified assessment roll year. The data included in this map is maintained by the California State Board of Equalization and may differ slightly from the data published by other agencies. BOE_TRA layer = tax rate area boundaries and the assigned TRA number for the specified assessment roll year; BOE_Changes layer = boundary changes filed with the Board of Equalization for the specified assessment roll year; Data Table (C##_YYYY) = tax rate area numbers and related districts for the specified assessment roll year

Clark County Planned Land Use. This data is maintained by the Clark County Comprehensive Planning Department.

The objective of this project is to use a multi-disciplinary, three-tiered approach to assess the geothermal resource and determine the feasibility of implementing a large-scale, direct-use facility for the Hawthorne Army Depot (HAD) and the various town and county facilities in Hawthorne, Nevada. This assessment directly targets a geothermal resource recently characterized by the Navy Geothermal Program Office (GPO) as part of a focused exploration and development campaign. This dataset includes the GIS data related to geophysics.

The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The primary legal divisions of most States are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, and municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four States (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their States. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities. The 2010 Census boundaries for counties and equivalent entities are as of January 1, 2010, primarily as reported through the Census Bureau's Boundary and Annexation Survey (BAS).

© U.S. Census Bureau, 2010-2011, and Nevada Legislative Counsel Bureau, 2011-2013

All data displayed on this map is near real-time. There are two ways in which this happens: Web service based data and a mobile mapping application called Field Maps. Web services are updated regularly ranging from every minute to once a month. All web services in this map are refreshed automatically to ensure the latest data being provided is displayed. Data collected through the use of Field Maps is done so by firefighters on the ground. The Field Maps application is consuming, creating, and editing data that are stored in ArcGIS Online. These data are then fed directly in to this map. To learn more about these web mapping technologies, visit the links below:Web ServicesArcGIS Field MapsArcGIS OnlineWeb Services used in this map:(visit link to learn more about each service)IRWIN - A central hub that orchestrates data between various fire reporting applications. When a new incident is created and/or updated by a dispatch center or other fire reporting system, it is then displayed on the map using the Integrated Reporting of Wildland-Fire Information (IRWIN) service. Automatically refreshes every five minutes:Fires by Cause - Any incident that has occurred year to date displayed by cause.ArcGIS Online/Field Maps - Part of the Esri Geospatial Cloud, ArcGIS Online and Collector enables firefighters to use web maps created in ArcGIS Online on mobile devices using the Collector application to capture and edit data on the fireline. Data may be captured and edited in both connected and disconnected environments. When data is submitted back to the web service in ArcGIS Online, it is then checked for accuracy and approved for public viewing.Fire Perimeter - Must be set to 'Approved' and 'Public' to be displayed on the map. Automatically refreshes every five minutes.

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

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

This map layer depicts the Sierra Nevada Conservancy's, Watershed Improvement Program Administrative Boundaries, which are known as Watershed Assessment Areas (AA) including the Tahoe Basin, which is not located within the SNC's boundary.

Nevada Places.

The source data were downloaded in late 1999 from the U.S. Geological Survey's Geographic Names Information System (GNIS), and nominally represent all named features on 1:24,000 (or largest available scale) U.S.G.S. topographic maps in Nevada. See the GNIS online metadata for further information on scope, origin, and production. Feature coordinates were used with ArcView® to create a corresponding shapefile. Attribute fields representing location data already available to us as separate GIS data sets (such as map quadrangles, counties, etc.), or representing other data that we had no need or ability to interpret or use, were removed for compactness. A single field (see CLASS below) was then added and populated to provide a higher level of classification for the feature types included, to facilitate representation on map legends and other data uses.

Source: http://heritage.nv.gov/gis/gis.htm#downloads

Zoning for all Entities in Southern Nevada. Clark County, Las Vegas, North Las Vegas, Boulder City, Mesquite and Henderson zoning are combined in this service.

Geospatial data about Clark County, Nevada Easements. Export to CAD, GIS, PDF, CSV and access via API.

Disclaimer of Liability: The user of this application and data assumes all responsibility and risk for the use of both. Under no circumstances, including negligence, shall the Nevada Department of Transportation, or its employees be liable for any DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY or CONSEQUENTIAL DAMAGES, or LOST PROFITS that result from the use, misuse, or inability to use the application and data. Nor shall the Nevada Department of Transportation, or its employees be liable for any damages resulting from or related to reliance, mistakes, omissions, interruptions, deletion of files, computer viruses, errors, defects, or any failure of performance, communications failure, theft, destruction or unauthorized access to the application and data.