This geologic map and preliminary cross sections of central and east Anchorage, Alaska, are based on previous mapping, limited new photointerpretation, and available subsurface data. Using PC-based Geographic Information System (GIS) software, the existing geologic map has been updated and simplified by adding recent fill deposits and combining units of similar genesis, composition, and age that are also recognizable in the subsurface. The GIS database consists of a USGS geologic map and over 4,000 geotechnical boreholes and water-well logs provided by numerous public and private sources. Geologic cross sections were developed by using GIS to project graphic lithologic logs into scaled vertical layouts along selected lines. Stratigraphic units were manually correlated using the log sections as guides. Identification and correlation of subsurface units are somewhat hampered by complex glacial geology, sparseness of deep boreholes, and significant variation in lithologic descriptions among many drillers. Although these limitations result in some generalized, undifferentiated geologic units, the differences among interpreted units are of the level desired by the geotechnical user community for highlighting engineering and seismic behavior.

The global high-precision map market is expected to witness a remarkable growth trajectory, expanding at a CAGR of over 20% during the forecast period from 2023 to 2030. In 2022, the market was valued at a substantial USD 2.5 billion and is projected to surpass a valuation of USD 12.3 billion by 2030. The surge in demand for autonomous vehicles and advanced driver assistance systems (ADAS) is serving as a primary driver for the market's growth. High-precision maps play a critical role in enabling these technologies by providing accurate and up-to-date information about the road environment. The high-precision map market is segmented based on type (centralized and crowdsourcing) and application (autonomous vehicles, ADAS, and others). Centralized maps are created and maintained by a central authority, while crowdsourcing involves the collection of data from multiple sources, including vehicles and sensors. The centralized segment currently holds a dominant market share due to its accuracy and reliability. However, crowdsourcing is gaining popularity as it offers a cost-effective and dynamic way to generate and update maps. Regionally, North America and Europe are expected to remain key markets for high-precision maps, while Asia-Pacific is anticipated to witness the fastest growth rate in the coming years.

Detailed land-cover mapping is essential for a range of research issues addressed by sustainability science, especially for questions posed of urban areas, such as those of the Central Arizona-Phoenix Long-Term Ecological Research (CAP LTER) program. This project provides a 1-meter land-cover mapping of the CAP LTER study area (greater Phoenix metropolitan area and surrounding Sonoran desert). The mapping is generated primarily using 2015 National Agriculture Imagery Program (NAIP) four-band data, with auxiliary GIS data used to improve accuracy. Auxiliary data include the 2015 cadastral parcel data, the 2014 USGS LiDAR data (1-meter), the 2014 Microsoft/OpenStreetMap Building Footprint data, the 2015 Street TIGER/Line, and a previous (2010) NAIP-based land-cover map of the study area (https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-cap&identifier=623). Among auxiliary data, building footprints and LiDAR data significantly improved the boundary detection of above-ground objects. Post-classification, manual editing was applied to minimize classification errors. As a result, the land-cover map achieves an overall accuracy of 94 per cent. The map contains eight land cover classes, including: (1) building, (2) asphalt, (3) bare soil and concrete, (4) tree and shrub, (5) grass, (6) water, (7) active cropland, and (8) fallow. When compared to the aforementioned, previous (2010) NAIP-based land-cover map for the study area, buildings and tree canopies are classified more accurately in this 2015 land-cover map.

This is a subset of World Biomass Image Layer to focus on Central Asia and Caucasus Region. Use this web map to visualize and understand the Biomass for that region. Use image layer for your analysis. Plants play a central role in the carbon cycle by absorbing carbon dioxide from the atmosphere and incorporating it in the structure of the plant. Globally living plants contain 500 billion metric tons of carbon, more than 60 times the amount of carbon released to the atmosphere by humans each year. Understanding the distribution of the carbon stored in living plants, known as biomass, is key to estimating the effects of land use change on the climate.Dataset SummaryThis layer provides access to a 1-km cell-sized raster with data on the density of carbon stored in living plants in metric tons per hectare for the year 2000. It was published by the Oak Ridge National Laboratory Carbon Dioxide Information Analysis Center in 2008.The authors of these data request that they be cited as:Ruesch, Aaron, and Holly K. Gibbs. 2008. New IPCC Tier-1 Global Biomass Carbon Map For the Year 2000. Available online from the Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, Oak Ridge, Tennessee.What can you do with this layer?This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS Desktop.This layer has query, identify, and export image services available. This layer is restricted to a maximum area of 16,000 x 16,000 pixels - an area 4,000 kilometers on a side or an area approximately the size of Europe. The Esri Insider Blog provides an introduction to the Ecophysiographic Mapping project.

As part of the NSTA’s published 2017/18 Activity Plan, the NSTA is publishing a set of regional geological maps for the Central North Sea and Moray Firth areas of the UKCS. These maps represent the first set of deliverables from a 3 year contract with Lloyd’s Register (LR) to produce a series of maps and associated databases for the whole of the UKCS. All data released with this set of geological maps is public domain data. The project has, however, benefited from a number of additional third party data sources which have been used to help inform final maps and/or derive interpreted products. These include the 21st Century Roadmap Palaeozoic project (which is now available in the public domain), PGS’s North Sea Digital Atlas, research data from the University of Aberdeen, CGG’s Target database and relevant products available via the BGS’s Offshore Geoindex. TGS are gratefully acknowledged for providing joined digital log data from LogLinePlus to enable the production of sand flag curves. Schlumberger, TGS and BP are acknowledged for providing additional seismic data to help QC interpretation carried out within the project and CDA are also kindly acknowledged for their support in downloading and providing much of the released well data to LR as part of this project. Due to the high level, regional nature of the project, the maps are being produced for the main geological time intervals e.g. Paleocene, Lower Cretaceous, Upper Jurassic. Each time interval includes the following products:

Depth structure maps Isochore maps Subcrop & supercrop maps Structural elements maps Depositional facies maps Reservoir distribution maps Source rock maps Well penetration maps Hydrocarbon occurrence maps

The products published here include:

a series of layered PDF documents which provide explanations of the various maps and datasets that have been produced plus a set of stratigraphic and petroleum systems charts. an ArcGIS project containing all of the maps and associated data. NSTA web feature services (WFSs) have been included in the map document in this delivery. They replace the use of a shapefile or feature class to represent block, licence and quadrant data. By using a WFS, the data is automatically updated when it becomes available via the NSTA digital copies of the sand flags (.las format) digital copies of the depth and thickness grids produced in the project (.xyz format)

The Census Data Hub allows you to create your own maps through ArcGIS Online. ArcGIS Online is a cloud-based mapping and analysis solution used to make maps, to analyse data, and to share and collaborate. This guide will show you how to create your own map that reflects and analyses your data of interest.Topics covered include: Creating a map:Finding the dataLabelingStylingDisplaying percentagesAdd detail to an area of interest on your map:Adding a new theme table layer to your mapLayer selectionFilteringFinding the distribution of households built in 2016 or later by Electoral DivisionExporting a map to PDF

The HD Live Map market is experiencing robust growth, projected to reach a market size of $1279 million in 2025 and exhibiting a remarkable Compound Annual Growth Rate (CAGR) of 24.8% from 2025 to 2033. This expansion is fueled by several key market drivers, including the increasing adoption of Advanced Driver-Assistance Systems (ADAS) and autonomous driving technologies in both commercial and military applications. The rising demand for precise and real-time location data for improved navigation, safety, and traffic management further contributes to this growth. Technological advancements, such as the development of high-resolution sensor technologies and improved data processing capabilities, are enhancing the accuracy and reliability of HD Live Maps, making them an indispensable component of next-generation vehicle systems. The market is segmented by crowdsourcing and centralized models, reflecting the varied approaches to data acquisition and map creation. Furthermore, application-based segmentation highlights the significant roles of commercial and military sectors, with the former encompassing automotive, logistics, and ride-sharing applications, while the latter emphasizes defense and security operations. Leading players such as TomTom, Google, Alibaba (AutoNavi), and Baidu are actively investing in R&D and strategic partnerships to consolidate their market positions. The competitive landscape is dynamic, with established players and emerging technology firms competing to deliver superior map data and services. The geographical distribution of the HD Live Map market is diverse, with North America and Asia Pacific expected to dominate due to significant investments in autonomous vehicle technology and robust infrastructure development. Europe is also a significant market, driven by strong government support for technological innovation and the growing adoption of connected car services. The market growth will be influenced by factors such as government regulations related to autonomous driving, the cost of data acquisition and processing, and the increasing integration of HD Live Maps into various smart city initiatives. The ongoing development of 5G networks and the rise of IoT devices are also expected to further stimulate market growth in the coming years. Continuous improvement in map accuracy and detail, coupled with wider industry adoption, will remain pivotal to the market's sustained expansion throughout the forecast period.

This dataset supports the publication “Geophysical insights into Paleoproterozoic tectonics along the southern margin of the Superior Province, central Upper Peninsula, Michigan, USA.” At a 1:100,000 scale, these data are in a geologic database in the Geologic Map Schema (GeMS) which includes spatial feature classes and non-spatial tables that contain the geologic information presented in figure 8 and S3 of appendix A, the supplemental map of the publication.

The Central Mojave Vegetation Polygons shapefile represents areas of the Mojave Desert classified into vegetation classes or alliances representative of the area from 1997-1999. The classification of these areas were derived from context gathered in the field data, photographs and additional satellite imagery that is not included in this data release. The original map coverage was preserved and released as a shapefile (mojave_veg_polygons.shp). In contrast to the Special Features Points vegetation classifications (described in the Special Features Points shapefile metadata record and ScienceBase item), the Central Mojave Vegetation Polygons were designated by vegetation alliances that extended 5 hectares or more. Map labels represent alliances and groups of alliances as described by the National Vegetation Classification, as it existed at that time. Each map unit is labeled by a primary land cover type and a secondary type where applicable. In addition, the source of data for labeling each map unit is also identified in the attribute table for each map unit. The metadata record (Mojave-Vegetation-Mapping_Mojave-Veg-Polygons-Metadata.xml), the Mojave vegetation polygons shapefile (zipped shapefile, mojave_veg_polygons.zip) and the label codes sheet that provides context for the vegetation classifications (LabelCodes.csv) are all included as attachments on the Mojave Vegetation Polygons ScienceBase item.

NCED is currently involved in researching the effectiveness of anaglyph maps in the classroom and are working with educators and scientists to interpret various Earth-surface processes. Based on the findings of the research, various activities and interpretive information will be developed and available for educators to use in their classrooms. Keep checking back with this website because activities and maps are always being updated. We believe that anaglyph maps are an important tool in helping students see the world and are working to further develop materials and activities to support educators in their use of the maps.

This website has various 3-D maps and supporting materials that are available for download. Maps can be printed, viewed on computer monitors, or projected on to screens for larger audiences. Keep an eye on our website for more maps, activities and new information. Let us know how you use anaglyph maps in your classroom. Email any ideas or activities you have to ncedmaps@umn.edu

Anaglyph paper maps are a cost effective offshoot of the GeoWall Project. Geowall is a high end visualization tool developed for use in the University of Minnesota's Geology and Geophysics Department. Because of its effectiveness it has been expanded to 300 institutions across the United States. GeoWall projects 3-D images and allows students to see 3-D representations but is limited because of the technology. Paper maps are a cost effective solution that allows anaglyph technology to be used in classroom and field-based applications.

Maps are best when viewed with RED/CYAN anaglyph glasses!

A note on downloading: "viewable" maps are .jpg files; "high-quality downloads" are .tif files. While it is possible to view the latter in a web-browser in most cases, the download may be slow. As an alternative, try right-clicking on the link to the high-quality download and choosing "save" from the pop-up menu that results. Save the file to your own machine, then try opening the saved copy. This may be faster than clicking directly on the link to open it in the browser.

World Map: 3-D map that highlights oceanic bathymetry and plate boundaries.

Continental United States: 3-D grayscale map of the Lower 48.

Western United States: 3-D grayscale map of the Western United States with state boundaries.

Regional Map: 3-D greyscale map stretching from Hudson Bay to the Central Great Plains. This map includes the Western Great Lakes and the Canadian Shield.

Minnesota Map: 3-D greyscale map of Minnesota with county and state boundaries.

Twin Cities: 3-D map extending beyond Minneapolis and St. Paul.

Twin Cities Confluence Map: 3-D map highlighting the confluence of the Mississippi and Minnesota Rivers. This map includes most of Minneapolis and St. Paul.

Minneapolis, MN: 3-D topographical map of South Minneapolis.

Bassets Creek, Minneapolis: 3-D topographical map of the Bassets Creek watershed.

North Minneapolis: 3-D topographical map highlighting North Minneapolis and the Mississippi River.

St. Paul, MN: 3-D topographical map of St. Paul.

Western Suburbs, Twin Cities: 3-D topographical map of St. Louis Park, Hopkins and Minnetonka area.

Minnesota River Valley Suburbs, Twin Cities: 3-D topographical map of Bloomington, Eden Prairie and Edina area.

Southern Suburbs, Twin Cities: 3-D topographical map of Burnsville, Lakeville and Prior Lake area.

Southeast Suburbs, Twin Cities: 3-D topographical map of South St. Paul, Mendota Heights, Apple Valley and Eagan area.

Northeast Suburbs, Twin Cities: 3-D topographical map of White Bear Lake, Maplewood and Roseville area.

Northwest Suburbs, Mississippi River, Twin Cities: 3-D topographical map of North Minneapolis, Brooklyn Center and Maple Grove area.

Blaine, MN: 3-D map of Blaine and the Mississippi River.

White Bear Lake, MN: 3-D topographical map of White Bear Lake and the surrounding area.

Maple Grove, MN: 3-D topographical map of the NW suburbs of the Twin Cities.

Minnesota River: 3-D topographical map of the Minnesota River Valley highlighting the river bend in Mankato.

St. Croix River: 3-D topographical map of the St. Croix extending from Taylors Falls to the Mississippi confluence.

Mississippi River, Lake Pepin: 3-D topographical map of the confluence of Chippewa Creek and the Mississippi River.

Red Wing, MN: 3-D topographical map of Redwing, MN on the Mississippi River.

Winona, Minnesota: 3-D topographical map of Winona, MN highlighting the Mississippi River.

Cannon Falls, MN: 3-D topographical map of Cannon Falls area.

Rochester, MN: 3-D topographical map of Rochester and the surrounding area.

Northfield, MN: 3-D topographical map of Northfield and the surrounding area.

St. Louis River, MN: 3-D map of the St. Louis River and Duluth, Minnesota.

Lake Itasca, MN: 3-D map of the source of the Mississippi River.

Elmore, MN: 3-D topographical map of Elmore, MN in south-central Minnesota.

Glencoe, MN: 3-D topographical map of Glencoe, MN.

New Prague, MN: 3-D topographical map of the New Prague in south-central Minnesota.

Plainview, MN: 3-D topographical map of Plainview, MN.

Waterville-Morristown: 3-D map of the Waterville-Morris area in south-central Minnesota.

Eau Claire, WI: 3-D map of Eau Claire highlighting abandon river channels.

Dubuque, IA: 3-D topographical map of Dubuque and the Mississippi River.

Londonderry, NH: 3-D topographical map of Londonderry, NH.

Santa Cruz, CA: 3-D topographical map of Santa Cruz, California.

Crater Lake, OR: 3-D topographical map of Crater Lake, Oregon.

Mt. Rainier, WA: 3-D topographical map of Mt. Rainier in Washington.

Grand Canyon, AZ: 3-D topographical map of the Grand Canyon.

District of Columbia: 3-D map highlighting the confluence of the rivers and the Mall.

Ireland: 3-D grayscale map of Ireland.

New Jersey: 3-D grayscale map of New Jersey.

SP Crater, AZ: 3-D map of random craters in the San Francisco Mountains.

Mars Water Features: 3-D grayscale map showing surface water features from Mars.

|:Area::::::| Number of PCTs | Number of Sites | PCT user accuracy weighted by number of sites | +-----------+-----------------------+----------------------+---------------------------------------------------------------+

The Strip Maps of Central Phoenix collection comprises 10 sheets divided into a total of 30 segments centering on Central Avenue, three of which are oriented north-south and seven of which are oriented east-west. Each map shows numbered land plots with dimensions, smaller side streets, and significant public buildings along the main streets. Created in 1929 by the William H. Becker Engineering Company and published by Phoenix Blue Print Company, the maps were originally in ten long strips. However, due to deterioration of the thin paper and folding while in storage, the sheets separated at the creases causing small fragments and breaks in the digitization. The polygon features on the map represent the segments of each sheet. While the main streets depicted on these maps still exist, many side streets have been moved, constructed over, or renamed.

Physiographic maps for the CIS and Baltic States (CIS_BS), Mongolia, China and Taiwan Province of China. Between the three regions (China, Mongolia, and CIS_BS countries) DCW boundaries were introduced. There are no DCW boundaries between Russian Federation and the rest of the new countries of the CIS_BS. The original physiographic map of China includes the Chinese border between India and China, which extends beyond the Indian border line, and the South China Sea islands (no physiographic information is present for islands in the South China Sea). The use of these country boundaries does not imply the expression of any opinion whatsoever on the part of FAO concerning the legal or constitutional states of any country, territory, or sea area, or concerning delimitation of frontiers. The Maps visualize the items LANDF, HYPSO, SLOPE that correspond to Landform, Hypsometry and Slope.

This web map contains reference data points with specific site information on vegetation dominance type and tree size for the Tongass National Forest to provide up-to-date and more complete information about vegetative communities, structure, and patterns across the project area. Reference data for this project came from numerous sources including: 1) Forest Service field crews collecting vegetation information specific to this project; 2) GO field crews collecting vegetation information for this project; 3) helicopter survey data; 4) Young-Growth Inventory data; 5) legacy data from previous Forest Service survey plots and the Forest Inventory and Analysis (FIA) program (FIA data are not included in this database); 6) legacy data from the prior Yakutat vegetation mapping project; and 7) image interpretation. This database contains reference data collected by GO staff for the Central Tongass Existing Vegetation Type Map. Tongass National Forest personnel collected most of the ground data that was targeted for this mapping effort using a variety of means—primarily by foot using existing trail and road infrastructure, or by boat—to collect samples that capture the diversity of vegetation across the project area. Helicopter survey data were collected over the course of three weeks in July 2024 for the Northern Tongass, with the goal of reaching difficult to access areas. The Young-Growth Inventory information was leveraged as reference data from actively managed forest stands. Legacy data was cross-referenced with the classification key to label each plot with a vegetation type. All sites were reviewed within the context of their corresponding segment using high-resolution imagery. For more detailed information on reference data methodology please see the Central and Northern Tongass Existing Vegetation Project Report.

This Data Release contains geospatially-enabled geological data to accompany the Geologic Map of the Central Beaverhead Mountains, Lemhi County, Idaho, and Beaverhead County, Montana. This map portrays detailed geology of the central Beaverhead Mountains, printable at 1:50,000 scale. These data were collected between 1997 and 2017, and synthesized to provide significant new stratigraphic and structural data and interpretations. Generalized basin geology compiled from sources on both sides of the range is combined with newly mapped bedrock geology to better integrate geologic development of the map area.

The data release for the geologic map of the Salmon National Forest and vicinity, east-central Idaho, is a Geologic Map Schema (GeMS)-compliant version that updates the GIS files for the geologic map published in U.S. Geological Survey (USGS) Geologic Investigations Series Map I-2765 (Evans and Green, 2003). The updated digital data present the attribute tables and geospatial features (points, lines and polygons) in the format that meets GeMS requirements. This data release presents the geologic map as shown on the plates and captured in geospatial data for the published map. Minor errors, such as mistakes in line decoration or differences between the digital data and the map image, are corrected in this version. The database represents the geology for the 11,265 square kilometer, geologically complex Salmon National Forest in two plates, at a publication scale of 1:100,000. The map covers primarily Lemhi County, but also includes minor parts of Beaverhead, Custer, Idaho, Ravalli and Valley Counties. New geologic mapping was undertaken between 1990 and 2002 and synthesized with older published maps, providing significant stratigraphic and structural data, age data for intrusive rocks, and interpretations of geologic development. These GIS data supersede those in the interpretive report: Evans, K.V., Green, G.N., 2003, Geologic Map of the Salmon National Forest and Vicinity, East-Central Idaho: U.S. Geological Survey Geologic Investigations Series Map I-2765, scale 1:100,000, https://doi.org/10.3133/i2765.

The Alaska Mapping Initiative is a U.S. Geological Survey program to support and improve maps and digital map data for Alaska, bringing Alaska topographic map and digital map data quality in line with the conterminous United States.The goal of the Alaska Mapping Initiative (AMI) is to acquire and enhance foundational digital map layers such as elevation, surface water, and boundaries that will be used to produce new US Topo maps for Alaska. This multi-year mapping initiative will improve The National Map's Alaska data to benefit high-priority applications in safety, planning, research, and resource management. The USGS is coordinating with the State of Alaska and multiple Federal agencies to accomplish these tasks through partnerships such as the Alaska Statewide Digital Mapping Initiative and the Alaska Mapping Executive Committee.

As part of the NSTA’s published 2017/18 Activity Plan, the NSTA is publishing a set of regional geological maps for the Central North Sea and Moray Firth areas of the UKCS. These maps represent the first set of deliverables from a 3 year contract with Lloyd’s Register (LR) to produce a series of maps and associated databases for the whole of the UKCS. All data released with this set of geological maps is public domain data. The project has, however, benefited from a number of additional third party data sources which have been used to help inform final maps and/or derive interpreted products. These include the 21st Century Roadmap Palaeozoic project(which is now available in the public domain), PGS’s North Sea Digital Atlas, research data from the University of Aberdeen, CGG’s Target database and relevant products available via the BGS’s Offshore Geoindex. TGS are gratefully acknowledged for providing joined digital log data from LogLinePlus to enable the production of sand flag curves. Schlumberger, TGS and BP are acknowledged for providing additional seismic data to help QC interpretation carried out within the project and CDA are also kindly acknowledged for their support in downloading and providing much of the released well data to LR as part of this project. Due to the high level, regional nature of the project, the maps are being produced for the main geological time intervals e.g. Paleocene, Lower Cretaceous, Upper Jurassic. Each time interval includes the following products:

Depth structure maps Isochore maps Subcrop & supercrop maps Structural elements maps Depositional facies maps Reservoir distribution maps Source rock maps Well penetration maps Hydrocarbon occurrence maps

The products published here include:

a series of layered PDF documents which provide explanations of the various maps and datasets that have been produced plus a set of stratigraphic and petroleum systems charts. an ArcGIS project containing all of the maps and associated data. NSTA web feature services (WFSs) have been included in the map document in this delivery. They replace the use of a shapefile or feature class to represent block, licence and quadrant data. By using a WFS, the data is automatically updated when it becomes available via the NSTA digital copies of the sand flags (.las format) digital copies of the depth and thickness grids produced in the project (.xyz format)

The Perry-Castañeda Library Map Collection (PCL 1.306) is a general collection of more than 250,000 maps covering all areas of the world. Many of the maps are included in the University of Texas Library Catalog. More than 11,000 map images from the collection are also available online via this link. Maps were produced by the U.S. Central Intelligence Agency, unless otherwise indicated. Maps dated 1976 were taken from The Indian Ocean Atlas, published by the Central Intelligence Agency.