This thematic map series provides the distribution of the various environmental mitigations across hydropower plants within the US.

A Collection of Contextual data for USA

This map draws attention to your thematic content by providing a neutral background with minimal colors, labels, and features. Only key information is represented to provide geographic context, allowing your data to come to the foreground. This light gray map supports any strong colors, creating a visually compelling map graphic which helps your reader see the patterns intended. This map was developed by Esri using HERE data, DeLorme basemap layers, OpenStreetMap contributors, Esri basemap data, and select data from the GIS user community. Worldwide coverage is provided from Level 0 (1:591M scale) through Level 13 (1:72k scale). In North America (Canada, Mexico, United States), Europe, India, South America and Central America, Africa, most of the Middle east, and Australia & New Zealand coverage is provided from Level 14 (1:36k scale) through Level 16 (1:9k scale). For more information on this map, including the terms of use, visit us online.

This thematic map series provides the distribution of selected fish species across hydropower plants within the US.

Multispectral remote sensing data acquired by Landsat 8 Operational Land Imager (OLI) sensor were analyzed using an automated technique to generate surficial mineralogy and vegetation maps of the conterminous western United States. Six spectral indices (e.g. band-ratios), highlighting distinct spectral absorptions, were developed to aid in the identification of mineral groups in exposed rocks, soils, mine waste rock, and mill tailings across the landscape. The data are centered on the Western U.S. and cover portions of Texas, Oklahoma, Kansas, the Canada-U.S. border, and the Mexico-U.S. border during the summers of 2013 – 2014. Methods used to process the images and algorithms used to infer mineralogical composition of surficial materials are detailed in Rockwell and others (2021) and were similar to those developed by Rockwell (2012; 2013). Final maps are provided as ERDAS IMAGINE (.img) thematic raster images and contain pixel values representing mineral and vegetation group classifications. Rockwell, B.W., 2012, Description and validation of an automated methodology for mapping mineralogy, vegetation, and hydrothermal alteration type from ASTER satellite imagery with examples from the San Juan Mountains, Colorado: U.S. Geological Survey Scientific Investigations Map 3190, 35 p. pamphlet, 5 map sheets, scale 1:100,000, http://doi.org/10.13140/RG.2.1.2769.9365. Rockwell, B.W., 2013, Automated mapping of mineral groups and green vegetation from Landsat Thematic Mapper imagery with an example from the San Juan Mountains, Colorado: U.S. Geological Survey Scientific Investigations Map 3252, 25 p. pamphlet, 1 map sheet, scale 1:325,000, http://doi.org/10.13140/RG.2.1.2507.7925. Rockwell, B.W., Gnesda, W.R., and Hofstra, A.H., 2021, Improved automated identification and mapping of iron sulfate minerals, other mineral groups, and vegetation from Landsat 8 Operational Land Imager Data: San Juan Mountains, Colorado, and Four Corners Region: U.S. Geological Survey Scientific Investigations Map 3466, scale 1:325,000, 51 p. pamphlet, https://doi.org/10.3133/sim3466/.

The 2022 cartographic boundary shapefiles are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. 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, 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 generalized boundaries for counties and equivalent entities are based on those as of January 1, 2022, primarily as reported through the Census Bureau's Boundary and Annexation Survey (BAS).

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Digital Map Market Size 2025-2029

The digital map market size is forecast to increase by USD 31.95 billion at a CAGR of 31.3% between 2024 and 2029.

The market is driven by the increasing adoption of intelligent Personal Digital Assistants (PDAs) and the availability of location-based services. PDAs, such as smartphones and smartwatches, are becoming increasingly integrated with digital map technologies, enabling users to navigate and access real-time information on-the-go. The integration of Internet of Things (IoT) enables remote monitoring of cars and theft recovery. Location-based services, including mapping and navigation apps, are a crucial component of this trend, offering users personalized and convenient solutions for travel and exploration. However, the market also faces significant challenges.
Ensuring the protection of sensitive user information is essential for companies operating in this market, as trust and data security are key factors in driving user adoption and retention. Additionally, the competition in the market is intense, with numerous players vying for market share. Companies must differentiate themselves through innovative features, user experience, and strong branding to stand out in this competitive landscape. Security and privacy concerns continue to be a major obstacle, as the collection and use of location data raises valid concerns among consumers.

What will be the Size of the Digital Map Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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In the market, cartographic generalization and thematic mapping techniques are utilized to convey complex spatial information, transforming raw data into insightful visualizations. Choropleth maps and dot density maps illustrate distribution patterns of environmental data, economic data, and demographic data, while spatial interpolation and predictive modeling enable the estimation of hydrographic data and terrain data in areas with limited information. Urban planning and land use planning benefit from these tools, facilitating network modeling and location intelligence for public safety and emergency management.

Spatial regression and spatial autocorrelation analyses provide valuable insights into urban development trends and patterns. Network analysis and shortest path algorithms optimize transportation planning and logistics management, enhancing marketing analytics and sales territory optimization. Decision support systems and fleet management incorporate 3D building models and real-time data from street view imagery, enabling effective resource management and disaster response. The market in the US is experiencing robust growth, driven by the integration of Geographic Information Systems (GIS), Global Positioning Systems (GPS), and advanced computer technology into various industries.

How is this Digital Map Industry segmented?

The digital map industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Application

  Navigation
  Geocoders
  Others


Type

  Outdoor
  Indoor


Solution

  Software
  Services


Deployment

  On-premises
  Cloud


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  APAC

    China
    India
    Indonesia
    Japan
    South Korea


  Rest of World (ROW)

By Application Insights

The navigation segment is estimated to witness significant growth during the forecast period. Digital maps play a pivotal role in various industries, particularly in automotive applications for driver assistance systems. These maps encompass raster data, aerial photography, government data, and commercial data, among others. Open-source data and proprietary data are integrated to ensure map accuracy and up-to-date information. Map production involves the use of GPS technology, map projections, and GIS software, while map maintenance and quality control ensure map accuracy. Location-based services (LBS) and route optimization are integral parts of digital maps, enabling real-time navigation and traffic data.

Data validation and map tiles ensure data security. Cloud computing facilitates map distribution and map customization, allowing users to access maps on various devices, including mobile mapping and indoor mapping. Map design, map printing, and reverse geocoding further enhance the user experience. Spatial analysis and data modeling are essential for data warehousing and real-time navigation. The automotive industry's increasing adoption of connected cars and long-term evolution (LTE) technologies have fueled the demand for digital maps. These maps enable driver assistance applications,

Important Note: This item is in mature support as of May 2025 and will retire in December 2025.This map features land cover data represent a descriptive thematic surface for characteristics of the land's surface such as densities or types of developed areas, agricultural lands, and natural vegetation regimes. Land cover data are the result of a model, so a good way to think of the values in each cell are as the predominating value rather than the only characteristic in that cell.Land use and land cover data are critical and fundamental for environmental monitoring, planning, and assessment.This web map uses Terrain with Labels vector layers as its basemap.Dataset SummaryBaseVue 2013 is a commercial global, land use / land cover (LULC) product developed by MDA. BaseVue covers the Earth’s entire land area, excluding Antarctica. BaseVue is independently derived from roughly 9,200 Landsat 8 images and is the highest spatial resolution (30m), most current LULC product available. The capture dates for the Landsat 8 imagery range from April 11, 2013 to June 29, 2014. The following 16 classes of land use / land cover are listed by their cell value in this layer: Deciduous Forest: Trees > 3 meters in height, canopy closure >35% (<25% inter-mixture with evergreen species) that seasonally lose their leaves, except Larch.Evergreen Forest: Trees >3 meters in height, canopy closure >35% (<25% inter-mixture with deciduous species), of species that do not lose leaves. (will include coniferous Larch regardless of deciduous nature).Shrub/Scrub: Woody vegetation <3 meters in height, > 10% ground cover. Only collect >30% ground cover.Grassland: Herbaceous grasses, > 10% cover, including pasture lands. Only collect >30% cover.Barren or Minimal Vegetation: Land with minimal vegetation (<10%) including rock, sand, clay, beaches, quarries, strip mines, and gravel pits. Salt flats, playas, and non-tidal mud flats are also included when not inundated with water.Not Used (in other MDA products 6 represents urban areas or built up areas, which have been split here in into values 20 and 21).Agriculture, General: Cultivated crop landsAgriculture, Paddy: Crop lands characterized by inundation for a substantial portion of the growing seasonWetland: Areas where the water table is at or near the surface for a substantial portion of the growing season, including herbaceous and woody species (except mangrove species)Mangrove: Coastal (tropical wetlands) dominated by Mangrove speciesWater: All water bodies greater than 0.08 hectares (1 LS pixel) including oceans, lakes, ponds, rivers, and streamsIce / Snow: Land areas covered permanently or nearly permanent with ice or snowClouds: Areas where no land cover interpretation is possible due to obstruction from clouds, cloud shadows, smoke, haze, or satellite malfunctionWoody Wetlands: Areas where forest or shrubland vegetation accounts for greater than 20% of vegetative cover and the soil or substrate periodically is saturated with, or covered by water. Only used within the continental U.S.Mixed Forest: Areas dominated by trees generally greater than 5 meters tall, and greater than 20% of total vegetation cover. Neither deciduous nor evergreen species are greater than 75% of total tree cover. Only used within the continental U.S.Not UsedNot UsedNot UsedNot UsedHigh Density Urban: Areas with over 70% of constructed materials that are a minimum of 60 meters wide (asphalt, concrete, buildings, etc.). Includes residential areas with a mixture of constructed materials and vegetation where constructed materials account for >60%. Commercial, industrial, and transportation i.e., Train stations, airports, etc.Medium-Low Density Urban: Areas with 30%-70% of constructed materials that are a minimum of 60 meters wide (asphalt, concrete, buildings, etc.). Includes residential areas with a mixture of constructed materials and vegetation, where constructed materials account for greater than 40%. Commercial, industrial, and transportation i.e., Train stations, airports, etc.What can you do with this layer?This layer has query, identify, and export image services available. The layer is restricted to an 16,000 x 16,000 pixel limit, which represents an area of nearly 300 miles on a side. This layer is part of a larger collection of landscape layers that you can use to perform a wide variety of mapping and analysis tasks.\For more information, see the Landscape Layers group on ArcGIS Online.

The feature class MO_tradizioni_costumi_lin_1 represents the linear elements of local traditions and customs, acquired from the map of local traditions and customs, acquired on a scale of 1:25 000. The maps PTPAAV (Territorial Environmental Country Plan of Area Vasta) are a series of thematic maps drawn up since 1989 and finished and approved at the end of November 1991, are divided into territorial areas for a total of 8 areas identified on the regional territory. The work was carried out by several groups of technicians, a coordination group which established by circulars the standards to be used for the drafting of plans ranging from the thickness of the graph tip to the type of retino and the nuances to be used, and 8 design groups one for each area, which have created the maps trying to standardise spatial information as much as possible. The paperwork of this work was delivered to us in 2008 by the Environmental Heritage Office of the Molise Region. The latter already had scans of some thematic cards related to some areas, the missing ones and in the case of scans not found suitable for georeference, have been scanned. The mapping basis used by the working groups for the creation of PTPAAV maps was the IGM on a scale of 1:25,000. The feature class MO_tradizioni_costumi_lin_1 represents the linear elements of local traditions and customs, acquired from the map of local traditions and customs, acquired on a scale of 1:25 000. The maps PTPAAV (Territorial Environmental Country Plan of Area Vasta) are a series of thematic maps drawn up since 1989 and finished and approved at the end of November 1991, are divided into territorial areas for a total of 8 areas identified on the regional territory. The work was carried out by several groups of technicians, a coordination group which established by circulars the standards to be used for the drafting of plans ranging from the thickness of the graph tip to the type of retino and the nuances to be used, and 8 design groups one for each area, which have created the maps trying to standardise spatial information as much as possible. The paperwork of this work was delivered to us in 2008 by the Environmental Heritage Office of the Molise Region. The latter already had scans of some thematic cards related to some areas, the missing ones and in the case of scans not found suitable for georeference, have been scanned. The mapping basis used by the working groups for the creation of PTPAAV maps was the IGM on a scale of 1:25,000. The feature class MO_tradizioni_costumi_lin_1 represents the linear elements of local traditions and customs, acquired from the map of local traditions and customs, acquired on a scale of 1:25 000. The maps PTPAAV (Territorial Environmental Country Plan of Area Vasta) are a series of thematic maps drawn up since 1989 and finished and approved at the end of November 1991, are divided into territorial areas for a total of 8 areas identified on the regional territory. The work was carried out by several groups of technicians, a coordination group which established by circulars the standards to be used for the drafting of plans ranging from the thickness of the graph tip to the type of retino and the nuances to be used, and 8 design groups one for each area, which have created the maps trying to standardise spatial information as much as possible. The paperwork of this work was delivered to us in 2008 by the Environmental Heritage Office of the Molise Region. The latter already had scans of some thematic cards related to some areas, the missing ones and in the case of scans not found suitable for georeference, have been scanned. The mapping basis used by the working groups for the creation of PTPAAV maps was the IGM on a scale of 1:25,000.

US Census Bureau Cartographic Boundary File of county boundaries for each state in the Unites States.

From the US Census Bureau: "The cartographic boundary files are simplified representations of selected geographic areas from the Census Bureau’s MAF/TIGER geographic database. These boundary files are specifically designed for small scale thematic mapping."

This dataset combines the work of several different projects to create a seamless data set for the contiguous United States. Data from four regional Gap Analysis Projects and the LANDFIRE project were combined to make this dataset. In the northwestern United States (Idaho, Oregon, Montana, Washington and Wyoming) data in this map came from the Northwest Gap Analysis Project. In the southwestern United States (Colorado, Arizona, Nevada, New Mexico, and Utah) data used in this map came from the Southwest Gap Analysis Project. The data for Alabama, Florida, Georgia, Kentucky, North Carolina, South Carolina, Mississippi, Tennessee, and Virginia came from the Southeast Gap Analysis Project and the California data was generated by the updated California Gap land cover project. The Hawaii Gap Analysis project provided the data for Hawaii. In areas of the county (central U.S., Northeast, Alaska) that have not yet been covered by a regional Gap Analysis Project, data from the Landfire project was used. Similarities in the methods used by these projects made possible the combining of the data they derived into one seamless coverage. They all used multi-season satellite imagery (Landsat ETM+) from 1999-2001 in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform) to model natural and semi-natural vegetation. Vegetation classes were drawn from NatureServe's Ecological System Classification (Comer et al. 2003) or classes developed by the Hawaii Gap project. Additionally, all of the projects included land use classes that were employed to describe areas where natural vegetation has been altered. In many areas of the country these classes were derived from the National Land Cover Dataset (NLCD). For the majority of classes and, in most areas of the country, a decision tree classifier was used to discriminate ecological system types. In some areas of the country, more manual techniques were used to discriminate small patch systems and systems not distinguishable through topography. The data contains multiple levels of thematic detail. At the most detailed level natural vegetation is represented by NatureServe's Ecological System classification (or in Hawaii the Hawaii GAP classification). These most detailed classifications have been crosswalked to the five highest levels of the National Vegetation Classification (NVC), Class, Subclass, Formation, Division and Macrogroup. This crosswalk allows users to display and analyze the data at different levels of thematic resolution. Developed areas, or areas dominated by introduced species, timber harvest, or water are represented by other classes, collectively refered to as land use classes; these land use classes occur at each of the thematic levels. Raster data in both ArcGIS Grid and ERDAS Imagine format is available for download at http://gis1.usgs.gov/csas/gap/viewer/land_cover/Map.aspx Six layer files are included in the download packages to assist the user in displaying the data at each of the Thematic levels in ArcGIS. In adition to the raster datasets the data is available in Web Mapping Services (WMS) format for each of the six NVC classification levels (Class, Subclass, Formation, Division, Macrogroup, Ecological System) at the following links. http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Class_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Subclass_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Formation_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Division_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Macrogroup_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_Ecological_Systems_Landuse/MapServer

SummaryTo show the boundary of United States Congressional Districts for the City of Philadelphia. - Features updated: 10/23/2013- Attributes updated: 10/23/2013- Metadata updated 03/30/2015 - Update Frequency Boundaries reflect US 2012 Congressional Districts. When boundaries change, new layers will be created to reflect the new boundaries.- Public = YAbstractThis layer shows 2012 United States Congressional Districts established by redistricting from 2010 census after the Supreme Court unanimously approved the Legislative Reapportionment Commission's 2012 Revised Final Plan on May 08, 2013. The state of Pennsylvania is divided into 18 Congressional Districts. Currently, the city has or is part of 3 United States Congressional Districts. NOTE for GIS Users:- The boundaries of the this layer do NOT follow the City's Composite layer. This is done strictly due to Pennsylvania Redistricting which is governed by law. Data DevelopmentKey Attribute FieldsDistrict_N: Congressional District NumberCoordinate SystemSource Data: Lambert Conformal Conic, NAD 1983 StatePlane Pennsylvania South FIPS 3702 (US Feet)ArcGIS Online Export Data: GCS_WGS_1984, Decimal DegreeThematic MappingUse District_N for thematic mapping and labeling.Other InformationN/ACreditsPhiladelphia City Planning Commission1515 Arch Street, 13 FlPhiladelphia, PA 19102GIS Manager: Darshna Patel (215) 683-4611 and darshna.patel@phila.gov

description: This thematic map indicates the annual compound rate of total population change in the United States from 1990 to 2000. Total Population is the total number of residents in an area. Residence refers to the usual place where a person lives. Total Population for 2000 is from the U.S. Census 2000. Total Population for 1990 is from the 1990 U.S. Census adjusted to 2000 boundaries. The geography depicts states at greater than 25m scale, counties at 1m to 25m scale, Census Tracts at 250k to 1m scale, and Census Block Groups at less than 250k scale. The map has been designed to be displayed with semi-transparency of about 50% for overlay on other base maps, which is reflected in the legend for the map. For more information on this map, including the terms of use, visit us online.; abstract: This thematic map indicates the annual compound rate of total population change in the United States from 1990 to 2000. Total Population is the total number of residents in an area. Residence refers to the usual place where a person lives. Total Population for 2000 is from the U.S. Census 2000. Total Population for 1990 is from the 1990 U.S. Census adjusted to 2000 boundaries. The geography depicts states at greater than 25m scale, counties at 1m to 25m scale, Census Tracts at 250k to 1m scale, and Census Block Groups at less than 250k scale. The map has been designed to be displayed with semi-transparency of about 50% for overlay on other base maps, which is reflected in the legend for the map. For more information on this map, visit us online at http://goto.arcgisonline.com/maps/Demographics/USA_1990-2000_Population_ChangedemographicsUSA 1990-2000 Population ChangeBlock GroupsTractsCountiesStates

The map title is Forest Types. Map scale. North arrow pointing to the north. Map projection is Hammer-Aitoff. Border of Canada. Great Lakes Border for each theme category within Canada. Neat line around the map. Each theme category is identified by a number that corresponds to the legend. Legend is divided into six categories: West Coast forest, Montane forest, Taiga forest, Boreal forest, Mixed forest, No forest. Tactile maps are designed with Braille, large text, and raised features for visually impaired and low vision users. The Tactile Maps of Canada collection includes: (a) Maps for Education: tactile maps showing the general geography of Canada, including the Tactile Atlas of Canada (maps of the provinces and territories showing political boundaries, lakes, rivers and major cities), and the Thematic Tactile Atlas of Canada (maps showing climatic regions, relief, forest types, physiographic regions, rock types, soil types, and vegetation). (b) Maps for Mobility: to help visually impaired persons navigate spaces and routes in major cities by providing information about streets, buildings and other features of a travel route in the downtown area of a city. (c) Maps for Transportation and Tourism: to assist visually impaired persons in planning travel to new destinations in Canada, showing how to get to a city, and streets in the downtown area.

ABSTRACT: The U.S. Geological Survey (USGS) Upper Midwest Environmental Sciences Center (UMESC) has produced the Vegetation Spatial Database Coverage (vegetation map) for the Acadia National Park Vegetation Mapping Project, USGS-NPS Vegetation Mapping Program (VMP). The vegetation map is of Acadia National Park (NP) and extended environs, providing 99,693 hectares (246,347 acres) of map data. Of this coverage, 52,872 hectares (130,650 acres) is non-vegetated ocean, bay, and estuary (53% of coverage). Acadia NP comprises 19,276 hectares (47,633 acres) of the total data coverage area (19%, 40% not counting ocean and estuary data). Over 7,120 polygons make up the coverage, each with map class description and, for vegetation classes, physiognomic feature information. The spatial database provides crosswalk information to all National Vegetation Classification System (NVCS) floristic and physiognomic levels, and to other established classification systems (NatureServe's U.S. Terrestrial Ecological System Classification, Maine Natural Community Classification, and the USGS Land Use and Land Cover Classification). This mapping project has identified 53 NVCS associations (vegetation communities) at Acadia National Park through analyses of vegetation sample data. These associations are represented in the map coverage with 33 map classes. With all vegetation types, land use classes, and park specific categories combined, 57 map classes define the ground features within the project area (58 classes including the class for no map data). Each polygon within the spatial database map is identified with one of these map classes. In addition, physiognomic modifiers are added to map classes representing vegetation to describe the vegetation structure within a polygon (density, pattern, and height). The spatial database was produced from the interpretation of spring 1997 1:15,840-scale color infrared aerial photographs. The standard minimum mapping unit (MMU) applied is 0.5 hectares (1.25 acres). The interpreted data were transferred and automated using base maps produced from USGS digital orthophoto quadrangles. The finished spatial database is a single seamless coverage, projected in Universal Transverse Mercator, Zone 19, with datum in North American Datum of 1983. The estimated overall thematic accuracy for vegetation map classes is 80%.

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.

ABSTRACT: The data set consists of a LBA study area subset of the IGBP DISCover Data Set. The DISCover data set is one data set contained within the Global Land Cover Characteristics Data Base. The U.S. Geological Survey (USGS), the University of Nebraska-Lincoln (UNL), and the European Commission's Joint Research Centre (JRC) have generated a 1-km resolution global land cover characteristics data base for use in a wide range of environmental research and modeling applications. The global land cover characteristics data base was developed on a continent-by-continent basis. All continental data bases share the same map projections (Interrupted Goode Homolosine and Lambert Azimuthal Equal Area), have 1-km nominal spatial resolution, and are based on 1-km Advanced Very High Resolution Radiometer (AVHRR) data spanning April 1992 through March 1993. Each data base contains unique elements based on the geographic aspects of the specific continent. In addition, a core set of derived thematic maps produced through the aggregation of seasonal land cover regions are included in each continental data base. The continental data bases are combined to make six global data sets, each representing a different landscape based on a particular classification legend. The following derived data sets are included in the global land cover data base: * Global Ecosystems (Olson, 1994a, 1994b) * IGBP Land Cover Classification (Belward, 1996) * U.S. Geological Survey Land Use/Land Cover System(Anderson & others, 1976) * Simple Biosphere Model (Sellers and others, 1986) * Simple Biosphere 2 Model (Sellers and others, 1996) * Biosphere-Atmosphere Transfer Scheme (Dickinson and others, 1986) The legends for each of these derived data sets can be found in the documentation accompanying the data. For a description of the methodology for the global data base, see the global readme file found under the EROS Data Center DAAC home page (http://edcwww.cr.usgs.gov/landdaac/glcc/glcc.html).

The lack of geographic and thematic maps of coral reefs limits our understanding of reefs and our ability to assess change. The U.S. Geological Survey (USGS) has the capability to compile digital image mosaics that are useful for creating detailed map products. Image maps covering the shallow near-shore coastal waters have been produced for several of the main Hawaiian Islands, including Hawai i, Maui, Moloka i, and O ahu and are presented in JPEG2000 (.jp2) format.

The digital-image mosaics were generated by first scanning historical aerial photographs at 1.0 meter-per-pixel resolution. The individually scanned digital images were tone- and color-matched and then combined together using spatial matching. Separately, black and white digital orthophoto quads (DOQs) of the same areas were then combined with shaded-relief images generated from lidar bathymetry data. The resulting black and white shaded-relief images covering both near-shore coastal waters and on-land areas became the geometric masters for the mosaics generated from the aerial photographs. The aerial-photograph mosaics were geometrically corrected to overlay the master data set by using hundreds of image-to-image geometric control points and slaving the mosaic onto the DOQ-lidar master.

This portion of the data release contains image mosaics generated using digitized 1:24K natural color photographs collected in June 2000 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). These four image mosaics have 1.0 meter-per-pixel resolution, and intermittently cover approximately 53 km (33 mi) of shallow, coastal waters along the west, Kona coast, of the island of Hawai i, including (from north to south) the Kawaihae, Waikoloa, Kukio, and Kailua-Kona areas. Each digital image mosaic area is downloadable as a separate zip file (_1m.zip) that contains two versions of the image mosaic one with and one without a lidar bathymetry shaded-relief image digitally combined with the aerial photography mosaic results. The shaded-relief image was derived using airborne SHOALS (Scanning Hydrographic Operational Lidar Survey) lidar (LIght Detection And Ranging) data collected for the U.S. Geological Survey (USGS) by the U.S. Army Corp of Engineers (USACE) in April 1999. Also included in each zip file is a lower-resolution browse graphic of each image mosaic and associated metadata.

A joint venture involving the National Atlas programs in Canada (Natural Resources Canada), Mexico (Instituto Nacional de Estadística y Geografía), and the United States (U.S. Geological Survey), as well as the North American Commission for Environmental Cooperation, has led to the release (June 2004) of several new products: an updated paper map of North America, and its associated geospatial data sets and their metadata. These data sets are available online from each of the partner countries for download. The North American Atlas data are standardized geospatial data sets at 1:10,000,000 scale. A variety of basic data layers (e.g., roads, railroads, populated places, political boundaries, hydrography, bathymetry, sea ice and glaciers) have been integrated so that their relative positions are correct. This collection of data sets forms a base with which other North American thematic data may be integrated. Any data outside of Canada, Mexico, and the United States of America included in the North American Atlas data sets is strictly to complete the context of the data. The North American Atlas - Glaciers data set shows areas of permanent ice found on the North America landmass including Greenland and shows areas of land found within glaciers. No distinction is made between major glaciers, ice fields, and the Greenland ice cap. The only permanent ice shown on land areas outside of North America and Greenland is in Iceland.This is a revised version of the 2004 data set. Files Download

To provide processed satellite images of key areas along the U. S.-Mexico border for use in a broad spectrum of studies. Landsat data have been used by government, commercial, industrial, civilian, and educational communities in the U.S. and worldwide. They are being used to support a wide range of applications in such areas as global change research, agriculture, forestry, geology, resources management, geography, mapping, water quality, and oceanography. Landsat data have potential applications for monitoring the conditions of the Earth's land surface.

The passage of the North American Trade Agreement (NAFTA), establishment of the Border Environmental Cooperation Commission as well as the EPA U.S./Mexico Border XXI Program has focused attention to the environmental social-cultural, and economic conditions in the United States-Mexico frontier and to the enhanced necessity of a binational, transborder approach in addressing problems. Towards this end, this U.S.-Mexico borderlands Thematic Mapper selection is designed to be utilized as fundamental part of a basic geographic information system database for natural resource, environmental, and land-management studies.