OHDR has published Natural Areas in Guinea on their website in support of the Ebola crisis. Data collected for the 2014 West Africa Ebola Response, an Activation of the Humanitarian OSM Team to provide map data to assist the response to this disease outbreak. OpenStreetMap offers an online map (and spatial database) which is updated by the minute. Various online maps are based on OpenStreetMap including Navigation tools such as OSRM. Tools and services allow data extracts for GIS specialists, Routable Garmin GPS data, Smartphone GPS navigation, and other device-compatible downloads. With an internet connection, regular syncing is possible with open access to the community contributed data as it comes in, with OpenStreetMap's bulk data downloads ideal for use offline. In addition, maps can also be printed to paper.Browse the Activation Area to get a feel for the data that is currently available. Different map styles including an Humanitarian style can be selected on the right side, and some data may not render (appear) on the map, but could be exported from the underlying database (See export section below).

The global Car GPS Navigation System market, valued at $15.91 billion in 2025, is projected to experience robust growth, exhibiting a compound annual growth rate (CAGR) of 10.03% from 2025 to 2033. This expansion is fueled by several key factors. The increasing adoption of smartphones with advanced navigation capabilities and the integration of GPS systems into infotainment systems are significant drivers. Furthermore, the rising demand for enhanced safety features, including real-time traffic updates and advanced driver-assistance systems (ADAS), is boosting market growth. Consumer preference for seamless navigation experiences and the growing popularity of connected cars are also contributing to market expansion. The market is segmented into hardware and software/services components, with software and services witnessing faster growth due to the increasing demand for subscription-based services, map updates, and advanced features like voice control and augmented reality navigation. While the market faces challenges like the increasing prevalence of built-in navigation systems in vehicles and the rise of smartphone-based navigation apps, the continuous innovation in GPS technology, including the integration of high-definition maps and artificial intelligence (AI)-powered features, will continue to drive market growth across key regions including North America (particularly the US), Europe (Germany and France being major contributors), and APAC (with China and Japan leading the way). The competitive landscape is characterized by a mix of established automotive component suppliers, technology companies, and specialized map providers. Companies like Robert Bosch GmbH, TomTom NV, and Garmin Ltd. hold significant market share, leveraging their expertise in hardware and software development. Apple Inc. and Google (although not explicitly listed) exert indirect influence through their integrated navigation systems on smartphones and their mapping technologies. The market witnesses intense competition driven by product differentiation through features, pricing strategies, and partnerships with automotive manufacturers. Risks include potential disruptions from technological advancements, economic fluctuations impacting consumer spending, and the increasing regulatory landscape concerning data privacy and security. The ongoing evolution of autonomous driving technology may present both opportunities and challenges, potentially reshaping the future of the car GPS navigation system market in the long term.

OpenStreetMap offers an online map (and spatial database) which is updated by the minute. Various online maps are based on OpenStreetMap including Navigation tools such as OSRM. Tools and services allow data extracts for GIS specialists, Routable Garmin GPS data, Smartphone GPS navigation, and other device-compatible downloads. With an internet connection, regular syncing is possible with open access to the community contributed data as it comes in, with OpenStreetMap's bulk data downloads ideal for use offline. In addition, maps can also be printed to paper.Browse the Activation Area to get a feel for the data that is currently available. Different map styles including an Humanitarian style can be selected on the right side, and some data may not render (appear) on the map, but could be exported from the underlying database (See export section below).

The wireless motorcycle GPS navigator market is experiencing robust growth, driven by increasing motorcycle ownership, a rising preference for advanced rider assistance systems (ADAS), and the growing popularity of adventure touring. The market's expansion is fueled by technological advancements leading to more user-friendly interfaces, improved mapping accuracy, and enhanced features like off-road navigation, turn-by-turn directions, and integration with smartphones and other devices. This segment benefits from the increasing demand for safer and more convenient motorcycle navigation solutions, replacing traditional paper maps and less sophisticated GPS devices. While precise market size data is unavailable, a conservative estimate considering the CAGR and market trends suggests a market valuation of approximately $500 million in 2025, projected to grow significantly over the forecast period (2025-2033). Key players such as Garmin, TomTom, and others are investing heavily in research and development to improve product functionality and enhance the overall user experience. This includes features like improved battery life, water resistance, and better integration with other motorcycle accessories. However, the market faces some restraints. The high initial cost of premium wireless motorcycle GPS navigators can deter price-sensitive buyers. Furthermore, concerns regarding battery life, durability in harsh weather conditions, and potential connectivity issues can influence purchasing decisions. The competitive landscape is dynamic, with established players and emerging companies vying for market share through product innovation and strategic partnerships. Successful companies will focus on delivering high-value, durable, and user-friendly products that cater to the specific needs of motorcycle riders, emphasizing features like off-road capabilities, route planning tools, and seamless integration with popular motorcycle apps. The market segmentation will likely see a rise in specialized navigators for specific motorcycle types (e.g., adventure, touring, sport bikes) leading to further market diversification.

This map presents transportation data, including highways, roads, railroads, and airports for the world.

The map was developed by Esri using Esri highway data; Garmin basemap layers; HERE street data for North America, Europe, Australia, New Zealand, South America and Central America, India, most of the Middle East and Asia, and select countries in Africa. Data for Pacific Island nations and the remaining countries of Africa was sourced from OpenStreetMap contributors. Specific country list and documentation of Esri's process for including OSM data is available to view.

The RV GPS navigation market is experiencing robust growth, driven by the increasing popularity of recreational vehicle travel and advancements in navigation technology. The market, estimated at $1.5 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 7% from 2025 to 2033, reaching an estimated market value of approximately $2.8 billion by 2033. This growth is fueled by several key factors. Firstly, the expanding RV ownership base, particularly amongst Baby Boomers and Gen X, is significantly boosting demand for specialized navigation solutions catering to the unique needs of RV drivers. Secondly, technological advancements such as improved map data, offline functionality, and integration with campsite reservation systems are enhancing user experience and driving adoption. Furthermore, the increasing adoption of larger RVs exceeding 7 inches in screen size reflects a preference for enhanced visibility and detailed map displays. Finally, the rise of connected car technologies and the integration of RV-specific features in GPS devices are further contributing to market expansion. However, market growth is not without its challenges. Pricing remains a significant restraint, particularly for high-end models with advanced features. The competitive landscape, with established players like Garmin and TomTom competing alongside smaller specialized companies, creates pressure on pricing and margins. Additionally, reliance on cellular data for certain features can pose a limitation for users in areas with limited or no network coverage. Despite these challenges, the long-term outlook for the RV GPS navigation market remains positive, fuelled by continuous technological innovation and the growing popularity of RV travel. The market segmentation based on screen size (≤7 inches and >7 inches) and application (leisure and commercial) provides valuable insights into evolving consumer preferences and specific niche opportunities. Regional analysis reveals North America and Europe as key markets, with strong growth potential in the Asia-Pacific region driven by increasing disposable incomes and adoption of recreational activities.

Mature Support Notice: This item is in mature support as of July 2021. A replacement item has not been identified at this time. Esri recommends updating your maps and apps to phase out use of this item.This map presents transportation data, including highways, roads, railroads, and airports for the world.The map was developed by Esri using Esri highway data; Garmin basemap layers; HERE street data for North America, Europe, Australia, New Zealand, South America and Central America, India, most of the Middle East and Asia, and select countries in Africa. Data for Pacific Island nations and the remaining countries of Africa was sourced from OpenStreetMap contributors. Specific country list and documentation of Esri's process for including OSM data is available to view.You can add this layer on top of any imagery, such as the Esri World Imagery map service, to provide a useful reference overlay that also includes street labels at the largest scales. (At the largest scales, the line symbols representing the streets and roads are automatically hidden and only the labels showing the names of streets and roads are shown). Imagery With Labels basemap in the basemap dropdown in the ArcGIS web and mobile clients does not include this World Transportation map. If you use the Imagery With Labels basemap in your map and you want to have road and street names, simply add this World Transportation layer into your map. It is designed to be drawn underneath the labels in the Imagery With Labels basemap, and that is how it will be drawn if you manually add it into your web map.

OpenStreetMap offers an online map (and spatial database) which is updated by the minute. Various online maps are based on OpenStreetMap including Navigation tools such as OSRM. Tools and services allow data extracts for GIS specialists, Routable Garmin GPS data, Smartphone GPS navigation, and other device-compatible downloads. With an internet connection, regular syncing is possible with open access to the community contributed data as it comes in, with OpenStreetMap's bulk data downloads ideal for use offline. In addition, maps can also be printed to paper.Browse the Activation Area to get a feel for the data that is currently available. Different map styles including an Humanitarian style can be selected on the right side, and some data may not render (appear) on the map, but could be exported from the underlying database (See export section below).

The automotive navigation systems market is experiencing robust growth, driven by increasing vehicle production, rising consumer demand for advanced driver-assistance systems (ADAS), and the integration of navigation with infotainment systems. The market's expansion is fueled by the transition towards connected cars, incorporating features like real-time traffic updates, voice-activated navigation, and cloud-based mapping services. These advancements enhance user experience and safety, thereby increasing adoption rates across various vehicle segments, from passenger cars to commercial vehicles. While the market is dominated by established players like Robert Bosch, Denso, and Continental AG, emerging companies are innovating with features such as augmented reality navigation and improved map accuracy, leading to increased competition and market dynamism. The Asia-Pacific region is projected to be a key growth driver due to the rapid expansion of the automotive industry and rising disposable incomes in developing economies. However, factors like the increasing adoption of smartphone-based navigation solutions and the high initial cost of advanced navigation systems pose challenges to market growth. Despite these restraints, the long-term outlook for the automotive navigation systems market remains positive, with continued innovation and technological advancements expected to drive market expansion throughout the forecast period. The market's Compound Annual Growth Rate (CAGR) is estimated at 7% from 2025 to 2033, reflecting steady yet sustainable growth. This growth trajectory is projected based on several factors, including sustained growth in global vehicle sales, the continuing integration of advanced navigation features into new vehicle models, and ongoing improvements in map data and software functionalities. While economic fluctuations and shifts in consumer preferences can influence growth rates, the ongoing demand for enhanced safety and connectivity within automobiles will likely sustain market expansion throughout the forecast period. The market segmentation (not provided, but could be by vehicle type, navigation technology, or geographic region) will further refine market analysis and highlight specific growth areas within the industry. Further analysis could also benefit from examining government regulations impacting ADAS and connected car technologies, as these often directly influence the adoption rate of advanced navigation systems.

The global smart bike navigation computer market is experiencing robust growth, projected to reach a value of $454 million in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 5.6% from 2025 to 2033. This expansion is fueled by several key drivers. Firstly, the increasing popularity of cycling as a fitness activity and a sustainable mode of transportation is driving demand for sophisticated devices that enhance rider experience and safety. Secondly, technological advancements leading to improved GPS accuracy, longer battery life, enhanced mapping capabilities (including off-road navigation), and integration with fitness tracking apps are making these computers more appealing to a wider range of cyclists, from casual riders to serious athletes. Finally, the growing awareness of health and fitness is pushing consumers towards smart devices that offer comprehensive data tracking and performance analysis features. Key players like Garmin, Wahoo Fitness, and Polar are driving innovation and competition, leading to continuous product improvement and a wider range of price points to suit diverse consumer needs. However, market growth is not without its challenges. One significant restraint is the relatively high price point of premium smart bike navigation computers compared to basic cycling computers. This price sensitivity limits market penetration among budget-conscious consumers. Another challenge lies in the need for consistent software updates and accurate map data, which requires ongoing investment and maintenance from manufacturers. Furthermore, the market is becoming increasingly saturated with competitors, leading to intense competition and price pressure. Despite these restraints, the long-term outlook for the smart bike navigation computer market remains positive, driven by the continued growth of the cycling industry and ongoing technological advancements that enhance the user experience and functionality of these devices. Market segmentation will likely continue to evolve, with further specialization in features catering to specific cycling disciplines and rider preferences.

Mature Support Notice: This item is in mature support as of July 2021. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version. This map is designed to be used as a general reference map for informational and educational purposes as well as a basemap by GIS professionals and other users for creating web maps and web mapping applications.To launch a web map containing this map layer, click here.The map was developed by National Geographic and Esri and reflects the distinctive National Geographic cartographic style in a multi-scale reference map of the world. The map was authored using data from a variety of leading data providers, including Garmin, HERE, UNEP-WCMC, NASA, ESA, USGS, and others.This reference map includes administrative boundaries, cities, protected areas, highways, roads, railways, water features, buildings and landmarks, overlaid on shaded relief and land cover imagery for added context. The map includes global coverage down to ~1:144k scale and more detailed coverage for North America down to ~1:9k scale. Here's a ready-to-use web map that uses the National Geographic World Map as its basemap. Map Note: Although small-scale boundaries, place names and map notes were provided and edited by National Geographic, boundaries and names shown do not necessarily reflect the map policy of the National Geographic Society, particularly at larger scales where content has not been thoroughly reviewed or edited by National Geographic.Data Notes: The credits below include a list of data providers used to develop the map. Below are a few additional notes:Reference Data: National Geographic, Esri, Garmin, HERE, INCREMENT P, NRCAN, METILand Cover Imagery: NASA Blue Marble, ESA GlobCover 2009 (Copyright notice: © ESA 2010 and UCLouvain)Protected Areas: IUCN and UNEP-WCMC (2011), The World Database on Protected Areas (WDPA) Annual Release. Cambridge, UK: UNEP-WCMC. Available at: www.protectedplanet.net.Ocean Data: GEBCO, NOAA

Mature Support Notice: This item is in mature support as of July 2021. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version. This worldwide street map presents highway-level data for the world down to ~1:72k. Street-level data down to ~1:4k includes the United States; most of Canada; Japan; Europe; much of Russia; Australia and New Zealand; India; most of the Middle East; South America; Central America; and Africa. Coverage in select urban areas is provided down to ~1:2k and ~1:1k. Full coverage at ~1:2k and ~1:1k is available in the contiguous United States and Hawaii. This comprehensive street map includes highways, major roads, minor roads, one-way arrow indicators, railways, water features, cities, parks, landmarks, building footprints, and administrative boundaries, overlaid on shaded relief for added context. Alignment of boundaries is a presentation of the feature provided by our data vendors and does not imply endorsement by Esri or any governing authority.The street map was developed by Esri using Esri basemap data, Garmin basemap layers, U.S. Geological Survey (USGS) elevation data, Intact Forest Landscape (IFL) data for the world; HERE data from ~1:288k with ~1:1k for Africa, Europe and Russia, Australia and New Zealand, North America, the Middle East, South America, and Central America; and MapmyIndia data for India from ~1:288k with ~1:1k. Data for Africa from ~1:288k to ~1:4k (~1:2k and ~1:1k in select areas) was sourced from OpenStreetMap contributors. Specific country list and documentation of Esri's process for including OSM data is available to view. For details on data sources in this map service, view the list of Contributors for the World Street Map. In addition, some of the data in the World Street map service has been contributed by the GIS community. For details, see the Community Maps Program.Tip: Here are some cities as they appear in the Streets web map. Each of these URLs launches the web map and contains location information to take you to a particular city: Bangkok, Bogota, Berlin, Hong Kong, Paris, Perth, Tokyo

This dataset consists of digital geologic data for the Dry Valley Hydrographic area, Nevada and California. It was compiled from individual 1:250,000-scale geologic data for Washoe County, Nevada, 1:62,500-scale geologic data for the Chilcoot and Doyle 15' quadrangles in California and the results of field mapping within the study area in 2004. A revised geologic map was needed in the study area because the available published maps have large discrepancies between the reported geologic units along the state line. The 2004 field mapping was confined to an area approximately 2000 feet east and west of the California/Nevada state line and about 1.5 miles north and south of Dry Valley Creek. No attempt was made to resolve discrepancies between the published maps in the area outside of the designated mapping area.

The discrepancies between geologic units in the previously published maps directly affect flow calculations used in the water budget for Dry Valley. The geologic unit involved in the greatest discrepancy is a non-welded rhyolitic tuff. Contacts between this unit and Quaternary basin-fill sediments were refined based on field mapping and sampling; and aerial photography. During mapping, low hills along the southern side of the valley floor 0.5 to 1.3 miles east of the state line mapped as Quaternary alluvium by previous efforts were recognized as non-welded rhyolitic tuff. In the locations described above, the non-welded tuff is distinguished by a lag deposit of yellow and red rhyolitic gravel at land surface. In the sub-surface, reached by digging, the tuff is weathered to a dense clay. Outcrops of the tuff with faint bedding planes were located in washes. Sample points, outcrops, and contacts between the tuff and unconsolidated sediments were located in the field using a handheld Garmin GPS unit (model GPS76).

These data were collected under a cooperative agreement between the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of seafloor geology are important first steps toward protecting fish habitat, delineating marine resources, and assessing environmental changes due to natural or human impacts. The project is focused on the inshore waters of coastal Massachusetts, primarily in water depths of 5 to 30 meters (m) deep. Data collected for the mapping cooperative have been released in a series of USGS Open-File Reports (http://woodshole.er.usgs.gov/project-pages/coastal_mass/). The data collected in the study area in Buzzards Bay, Massachusetts, include high-resolution geophysics (bathymetry, backscatter intensity, and seismic reflection) and ground validation (sediment samples, video tracklines, and bottom photographs). The geophysical data are released in USGS Open-File Report 2012-1002, High-Resolution Geophysical Data from the Inner Continental Shelf: Buzzards Bay, Massachusetts (http://pubs.usgs.gov/of/2012/1002/). The sampling data have not been prepared for publication yet. The geophysical data were collected during four separate surveys conducted between 2004 and 2011 (National Oceanic and Atmospheric Administration (NOAA) survey H11319 (in 2004; bathymetry only) and USGS surveys 2009-002-FA, 2010-004-FA, and 2011-004-FA)) and cover 410 square kilometers of the inner continental shelf. More information about the individual USGS surveys conducted as part of the Buzzards Bay project can be found on WHCS Field Activity Web pages: 2009-002-FA: http://woodshole.er.usgs.gov/operations/ia/public_ds_info.php?fa=2009-002-FA 2010-004-FA: http://woodshole.er.usgs.gov/operations/ia/public_ds_info.php?fa=2010-004-FA 2011-004-FA: http://woodshole.er.usgs.gov/operations/ia/public_ds_info.php?fa=2011-004-FA Information about the NOAA survey can be found at: H11319: http://surveys.ngdc.noaa.gov/mgg/NOS/coast/H10001-H12000/H11319/DR/

Abstract

A multi-stage cluster survey was conducted in two rural rice-producing regions in Bangladesh in 2007-2008 as the initial project of a HarvestPlus multi-stage research program to determine the potential impact of zinc-biofortified rice on the zinc and health status among children in Bangladesh who are at risk of zinc deficiency. The project protocol “Assessment of rice intakes and total dietary zinc intakes in rural Bangladesh” was conducted in collaboration with the University of California, Davis and the International Centre for Diarrhoeal Disease Research, Bangladesh (ICDDR,B). The dataset contains dietary information for the primary caregivers of the children, who were women of reproductive age, non-pregnant, and non-lactating.

Geographic coverage

Sub-national coverage, only rural areas.

Analysis unit

Individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

Within each Upazila, all villages or mauzas identified by the 2001 census were included in the sampling universe. During the first sampling stage, 25 clusters (mauzas or villages) were selected from each study site using systematic sampling with probability of selection proportional to estimated population size. Twenty-four clusters in each district were included in the study; an extra cluster was selected for each district in case logistical considerations made recruitment impossible in a cluster. The extra cluster was used in both sites.

At the second stage of sampling, ten households within each cluster were selected using a global positioning system (GPS) sampling method. Digital maps were obtained from the local government or created by walking the boundaries of the cluster with a local guide and a Garmin Etrex Venture hand-held GPS device (Olathe, KS). Each digital map was overlaid with a grid that had lines at 1-sec intervals, so each square on the grid corresponded to a specific set of GPS coordinates. Random pairs of row numbers and column letters were generated in a spreadsheet, each of which corresponded to one square on the grid. The random pairs were tested sequentially until two squares that fell within the boundaries of the cluster digital map were identified as starting points. Two separate starting points were selected to allow estimation of within-cluster variance. A random transect direction for each starting point was generated. In the field, the medical officers in charge of study recruitment used the handheld GPS device to locate the two randomly-selected starting points within each cluster and to follow the designated transect line. Moving along the transect line, the first five distinct households, each from a separate bari (extended family compound composed of one or more houses in the same area) with a child 24-48 months of age were identified and invited to participate in the study. This was then repeated at the second starting point for each cluster.

In 11 of 48 clusters (23%) logistics made it impossible to recruit from two starting points, so all households in these clusters were recruited from just one starting point. During the initial contact with a potential study household, the field staff collected basic household intake information. If an eligible child was identified, and the household agreed to participate in the study, consent was obtained using the Bangla version of the consent form, and the intake interview was continued. The names, ages, and dates of birth of the selected children, other children (aged 5 years or younger), mother, and father were obtained. The ages of the selected children were verified by checking the immunization cards. The exact day of the birth month was unknown for nine of the selected children and '15' was imputed for the day; for one of the selected children the month and day of birth were unknown so the age was not calculated. The first diet study was scheduled during the next week. Approximately 92% of the originally selected eligible households agreed to participate in the study. The sample size in each of the two districts was 240 selected children. Data were available from 239 households in Trishal because the forms for one household were lost during transit from the field site to ICDDR,B.

Mode of data collection

Face-to-face [f2f]

This record describes multibeam echosounder data collected on RV Investigator voyage IN2021_E01 titled "Equipment Calibrations and Trials #1". The voyage took place between November 10 and November 14, 2021, departing from Hobart (TAS) and arriving in Hobart (TAS).

The purpose of this voyage was to undertake post port-period equipment calibrations and commissioning, sea trials and personnel training. These objectives included testing the new piston coring system and performing annual GSM equipment calibrations.

The following primary GSM tasks were undertaken: • EK60 & EK80 calibration at anchor (White Rock, Derwent River) • Backscatter calibration lines across calibration sites/lines 1 & 4 (in Storm Bay) • EM710 & EM122 multibeam systems standard patch test calibrations (Latency, Roll, Pitch & Yaw) • Mapping of a bathymetry reference surface in a water depth of 150 m with the EM710 • Testing of Valeport SVX-2 deep water sound velocity probe to 3000 m • Personnel training and inter-organisation skills transfer (AAD)

This dataset is published with the permission of CSIRO. Not to be used for navigational purposes.

The dataset contains bathymetry grids of 5m to 210m resolution of Storm Bay, produced from the processed EM122 and EM710 bathymetry data. Lineage: Multibeam data was logged from the EM’s in Kongsberg’s proprietary *.all format and was converted to be processed within CARIS HIPS and SIPS version 11.4.2. Data were imported into the HIPS project using EM Height and the vessel file appropriate for either the EM122 or EM710. GPS tide was applied using the EGM2008 model, EGM_2008_1Min_Aust_WGS84.csar. TPU values were computed using Measured Sound Velocity = 0.5 and Surface Sound Velocity= 0.1. The raw files were analysed for noise and cleaned either manually or using a trial of the new ADMIRALTY GAM automated sonar noise classifier (i.e., noise filter) in Caris. This service uses AI and Machine Learning to identify noise in bathymetry data. In some cases, the GAM ‘filter’ removed too much data, in which case rejected soundings were manually re-accepted by the analyst.

The data was gridded at multiple resolutions in python Caris batch script using a Depth filter Vs Resolution guideline derived from AusSeabed Multibeam guidelines v2 and further inspected for outliers. Final raster products are available in L3 folder of this collection. Final processed data were also exported per line as GSF and ASCII format and available in the L2 folder of this collection.

One dataset containing 153 point measurements of supraglacial debris thickness on Khumbu Glacier, Nepal. Measurements were made by manual excavation in 2014 and 2015 by Morgan Gibson and Ann Rowan.

The dataset is included here in two formats; (1) a delimited text file, and (2) a .kmz file for Google Earth. The data in each file are identical. A Google Earth map showing an overview of the data coverage is also included as a jpg.

The debris thickness to the ice surface was measured as the distance to the ice from a horizontal reference placed on the unmodified surrounding surface bridging the excavation. Debris thickness data are reported to the nearest 0.1 m. Where debris thickness is given as 1.0 m this indicates that this is the minimum value and it was not possible to excavate to the debris–ice interface. Latitude and longitude were recorded with a handheld Garmin GPS.

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OpenStreetMap offers an online map (and spatial database) which is updated by the minute. Various online maps are based on OpenStreetMap including Navigation tools such as OSRM. Tools and services allow data extracts for GIS specialists, Routable Garmin GPS data, Smartphone GPS navigation, and other device-compatible downloads. With an internet connection, regular syncing is possible with open access to the community contributed data as it comes in, with OpenStreetMap's bulk data downloads ideal for use offline. In addition, maps can also be printed to paper.Browse the Activation Area to get a feel for the data that is currently available. Different map styles including an Humanitarian style can be selected on the right side, and some data may not render (appear) on the map, but could be exported from the underlying database (See export section below).

Important Note: This item is in mature support as of July 2021. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version.This map layer 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. The dark gray map supports bright colors, creating a visually compelling map graphic which helps your reader see the patterns intended.The World Dark Gray Base is designed to be drawn on top of this base map and provides selected city labels throughout the world. This web map lets you view the Dark Gray Base with the Reference layer drawn on top. See this blog for more information on how to use the canvas maps: Esri Canvas Maps Part I: Author Beautiful Web Maps With Our New Artisan Basemap Sandwich. The map shows populated places, water, roads, urban areas, parks, building footprints, and administrative boundaries. Alignment of boundaries is a presentation of the feature provided by our data vendors and does not imply endorsement by Esri or any governing authority. This map was compiled by Esri using HERE data, Garmin basemap layers, and Esri basemap data. The basemap includes boundaries, administrative labels, and major roads worldwide from 1:591M scale to 1:577k scale. More detailed coverage is included in North America, Europe, Africa, South America and Central America, the Middle East, India, Australia, and New Zealand down to the 1:9k scale. Data for select areas of Africa and Pacific Island nations from ~1:288k to ~1:9k was sourced from OpenStreetMap contributors. Specific country list and documentation of Esri's process for including OSM data is available to view.In addition, some of the data in the World Dark Gray Base map layer has been contributed by the GIS community. For details, see the Community Maps Program. For details on data sources in this map layer, view the list of Contributors for the World Dark Gray Base map.

This layer was last updated August 2016. The map presents country boundaries; first-order (State/Province) internal administrative boundaries for most countries; second-order administrative boundaries for the United States (counties), Canada, India, New Zealand, and Europe, South America, and Africa; and place-names for the world. Alignment of boundaries is a presentation of the feature provided by our data vendors and does not imply endorsement by Esri or any governing authority. The map was developed by Esri using administrative and cities data from Esri, HERE, and Garmin basemap layers for the world. Data for India sourced from MapmyIndia from ~1:288k and ~1:144k. Data for select areas is provided by the GIS Community. You can contribute your data to this service and have it served by Esri. For details on the users who contributed data for this map via the Community Maps Program, view the list of Contributors for the World Boundaries and Places Map. Data for select areas of Africa and Pacific Island nations was sourced from OpenStreetMap contributors. Specific country list and documentation of Esri's process for including OSM data is available to view.This layer is designed for use with maps with lighter backgrounds, such as the World Shaded Relief map, as you can see in this Shaded Relief web map which includes the World Boundaries and Places Alternate and the World Reference Overlay layers which you can turn on in order to compare their utility as reference overlays. A different version of this map is also available, the World Boundaries and Places layer, which is designed for overlaying on basemaps with darker backgrounds, such as the World Imagery map.Scale Range: 1:591,657,528 down to 1:144,448Coordinate System: Web Mercator Auxiliary Sphere (WKID 102100)Tiling Scheme: Web Mercator Auxiliary SphereMap Service Name: World_Boundaries_and_Places_AlternateArcGIS Desktop/Explorer URL: http://services.arcgisonline.com/arcgis/servicesArcGIS Server Manager and Web ADF URL: http://server.arcgisonline.com/arcgis/services/Reference/World_Boundaries_and_Places_Alternate/MapServerREST URL for ArcGIS Web APIs: http://server.arcgisonline.com/ArcGIS/rest/services/Reference/World_Boundaries_and_Places_Alternate/MapServerSOAP API URL: http://services.arcgisonline.com/ArcGIS/services/Reference/World_Boundaries_and_Places_Alternate/MapServer?wsdl