This cartographic digital product is derived from the Atlas of Canada's wall map "The World" (MCR 0046) and "Le monde" (MCR 0046F) published in 2021. The World is a general reference political map focused on the names and international boundaries of sovereign and non-sovereign countries. The information is portrayed using the Winkel II projection at a scale of 1:29 000 000. The dataset includes international boundaries, populated places, and labelled major hydrographic and physical features. In the geodatabase the representation of political boundaries do not necessarily reflect the position of the Government of Canada on all international issues of recognition, sovereignty or jurisdiction; some of the populated places have seasonal populations, while others are research or military bases with no permanent populations; and, there are no attribute information in the geodatabase for the labelled hydrographic and physical features.

Natural Earth is a public domain map dataset available at 1:10m, 1:50m, and 1:110 million scales. Featuring tightly integrated vector and raster data, with Natural Earth you can make a variety of visually pleasing, well-crafted maps with cartography or GIS software.

Context

Map data from Natural Earth.

This data set contains the cultural and physical vector data sets only. It does not contain the raster format data. Cultural data contains map data on countries, states, boundaries, roads, railways, airports, ports, urban areas, etc.

Data are organized by scale, see here for details: - 110m: 1:110,000,000, suitable for schematic maps of the world on a postcard or as a small locator globe. - 50m: 1:50,000,000, suitable for making zoomed-out maps of countries and regions. Show the world on a tabloid size page. - 10m: 1:10,000,000, the most detailed. Suitable for making zoomed-in maps of countries and regions. Show the world on a large wall poster.

Acknowledgements

Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com.

This web map shows natural features point and polygon layers from OSM (OpenStreetMap) in India.OSM is a collaborative, open project to create a freely available and editable map of the world. Geographic information about streets, rivers, borders, points of interest and areas are collected worldwide and stored in a freely accessible database. Everyone can participate and contribute to OSM. The geographic information available on OSM relies entirely on volunteers or contributors.The attributes are given below:BeachCave EntranceCliffGlacierPeakSpringTreeVolcanoThese map layers are offered by Esri India Content. The content team updates the map layers quarterly. If you have any questions or comments, please let us know via content@esri.in.

The Bright Earth eAtlas Basemap dataset collection is a satellite-derived global map of the world at a 1:1M scale for most of the world and 1:200k scale for Australia. This map was inspired by Natural Earth II (NEII) and NASA's Blue Marble Next Generation (BMNG) imagery.

Its aim was to provide a basemap similar to NEII but with a higher resolution (~10x).

This basemap is derived from the following datasets: Blue Marble Next Generation 2004-04 (NASA), VMap0 coastline, Coast100k 2004 Australian coastline (GeoScience Australia), SRTM30 Plus v8.0 (UCSD) hillshading, Natural Earth Vector 10m bathymetry and coastline v2.0 (NE), gbr100 hillshading (JCU).

This dataset (World_Bright-Earth-e-Atlas-basemap) contains all the files required to setup the Bright Earth eAtlas basemap in a GeoServer. All the data files are stored in GeoTiffs or shapefiles and so can also be loaded into ArcMap, however no styling has been included for this purpose.

This basemap is small enough (~900 MB) that can be readily used locally or deployed to a GeoServer.

Base map aesthetics (added 28 Jan 2025)

The Bright Earth e-Atlas Basemap is a high-resolution representation of the Earth's surface, designed to depict global geography with clarity, natural aesthetics with bright and soft color tones that enhance data overlays without overwhelming the viewer. The land areas are based on NASA's Blue Marble imagery, with modifications to lighten the tone and apply noise reduction filtering to soften the overall coloring. The original Blue Marble imagery was based on composite satellite imagery resulting in a visually appealing and clean map that highlights natural features while maintaining clarity and readability. Hillshading has been applied across the landmasses to enhance detail and texture, bringing out the relief of mountainous regions, plateaus, and other landforms.

The oceans feature three distinct depth bands to illustrate shallow continental areas, deeper open ocean zones, and the very deep trenches and basins. The colors transition from light blue in shallow areas to darker shades in deeper regions, giving a clear sense of bathymetric variation. Hillshading has also been applied to the oceans to highlight finer structures on the seafloor, such as ridges, trenches, and other geological features, adding depth and dimensionality to the depiction of underwater topography.

At higher zoom levels prominent cities are shown and the large scale roads are shown for Australia.

Rendered Raster Version (added 28 Jan 2025)

A low resolution version of the dataset is available as a raster file (PNG, JPG and GeoTiff) at ~2 km and 4 km resolutions. These rasters are useful for applications where GeoServer is not available to render the data dynamically. While the rasters are large they represent a small fraction of the full detail of the dataset. The rastered version was produced using the layout manager in QGIS to render maps of the whole world, pulling the imagery from the eAtlas GeoServer. This imagery from converted to the various formats using GDAL. More detail is provided in 'Rendered-bright-earth-processing.txt' in the download and browse section.

Change Log 2025-01-28: Added two rendered raster versions of the dataset at 21600x10800 and 10400x5400 pixels in size in PNG, JPG and GeoTiff format. Added

Matched boundary lines and polygons with names attributes for countries and sovereign states. Includes dependencies (French Polynesia), map units (U.S. Pacific Island Territories) and sub-national map subunits (Corsica versus mainland Metropolitan France).

Context

I created this dataset to train a network to generate realistic looking terrain maps based on simple color region codings. You can see some samples of the result here: https://www.reddit.com/r/MachineLearning/comments/7dwj1q/p_fun_project_mspaint_to_terrain_map_with_gan/

Content

This is a dataset of 1360 image pairs. The ground truth image is a random 512x512 pixel crop of terrain from a global map of the Earth. The second image is a color quantized and mode filtered version of the base image to create a very simple terrain region mapping composed of five colors. The five colors correspond to terrain types as follows: blue - water, grey - mountains, green - forest/jungle/marshland, yellow - desert/grassland/glacier, brown - hills/badlands.

1 Overview World Administrative Boundaries are available from various sources (UN, WHO, Global Administrative Areas [GADM], Natural Earth, World Bank). We would like to have the most accurate one with a reasonable size for an interactive world map in a Data Exploration Application, called CLIMINET. We provide a complete Geospatial Data that covers at least all 249 countries in the international ISO 3166-1 standard. We aim to maintain a reasonable data size, with countries' boundaries as accurate as possible, to ensure FLUIDITY in data visualization applications. The data are optimized for efficient performance and smooth interactions in interactive world maps for the best possible user experience. 2. Data Overview Number of Spatial Features: 275 countries/territories Data Sources: Compiled from multiple sources to ensure completeness and precision (WHO, Global Administrative Areas [GADM]) CRS Options: WGS84 [EPSG:4326] World Robinson (1963) [ESRI:54030] World Winkel-Tripel (Winkel III) - (1921) [ESRI:54042] Data Level: Level 0 (Countries) File Format: GeoJSON File Size: WGS84 [EPSG:4326]: 18.86 MB World Robinson (1963) [ESRI:54030]: 30.91 MB World Winkel-Tripel (Winkel III) - (1921) [ESRI:54042]: 30.90 MB 3. Data Revision Date The data were last updated on 2024-12-19. For further information on data structure and implementation, refer to the metadata files.

Natural Earth is a public domain map dataset available at 1:10, 1:50 and 1:110 million scales. Featuring tightly integrated vector and raster data, with Natural Earth you can make a variety of visually pleasing, well-crafted maps with cartography or GIS software.

Note: this map service is being replaced by a new set of feature layers, please use these instead:Historical Tsunami EventsTsunami ObservationsSignificant EarthquakesSignificant Volcanic EventsVolcano LocationsCurrent DARTs and Retrospective BPR DeploymentsHistorical MarigramsTsunami-Capable Tide StationsPlate BoundariesNatural hazards such as earthquakes, tsunamis, and volcanoes affect both coastal and inland areas. Long-term data from these events can be used to establish the past record of natural hazard event occurrences, which is important for planning, response, and mitigation of future events. NOAA's National Centers for Environmental Information (NCEI) plays a major role in post-event data collection. The data in this archive is gathered from scientific and scholarly sources, regional and worldwide catalogs, tide gauge reports, individual event reports, and unpublished works. For more information, please see: https://www.ncei.noaa.gov/products/natural-hazardsTo view this service in an interactive mapping application, please see the Global Natural Hazards Data Viewer (NOAA GeoPlatform entry).

This map is a fun visualisation of New Year's Eve celebrations around the world. Cities are the points in this map, which were sourced from Natural Earth. Cartographically, it was created by using Esri's dark basemap and using a firework .GIF as the point symbol. The Time Aware Esri application was used to display the points across time.

Shapefile created using satellite-derived land cover data and shaded relief presented with a light, natural palette suitable for making thematic and reference maps. Natural Earth I is available with ocean bottom data, or without. File size: 10,800 x 5,400 pixels.

Coloring based on land cover.

World land boundaries (disputed borders and treaty demarcation lines etc) at 1:10 million scale.

Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com.

Natural Earth is a public domain map dataset available at 1:10m, 1:50m, and 1:110 million scales. Featuring tightly integrated vector and raster data, with Natural Earth you can make a variety of visually pleasing, well-crafted maps with cartography or GIS software.

Natural Earth was built through a collaboration of many volunteers and is supported by NACIS (North American Cartographic Information Society).

Natural Earth Vector comes in ESRI shapefile format, the de facto standard for vector geodata. Character encoding is Windows-1252.

Natural Earth Vector includes features corresponding to the following:

Cultural Vector Data Thremes:

• Countries: matched boundary lines and polygons with names attributes for countries and sovereign states. Includes dependencies (French Polynesia), map units (U.S. Pacific Island Territories) and sub-national map subunits (Corsica versus mainland Metropolitan France).
• Disputed areas and breakaway regions - From Kashmir to the Elemi Triangle, Northern Cyprus to Western Sahara.
• First order admin (provinces, departments, states, etc.): internal boundaries and polygons for all but a few tiny island nations. Includes names attributes and some statistical groupings of the same for smaller countries.
• Populated places: point symbols with name attributes. Includes capitals, major cities and towns, plus significant smaller towns in sparsely inhabited regions. We favor regional significance over population census in determining rankings.
• Urban polygons: derived from 2002-2003 MODIS satellite data.
• Parks and protected areas: US National Park Service units.
• Pacific nation groupings: boxes for keeping these far-flung islands tidy.
• Water boundary indicators: partial selection of key 200-mile nautical limits, plus some disputed, treaty, and median lines.

Physical Vector Data Themes:

• Coastline: ocean coastline, including major islands. Coastline is matched to land and water polygons.
• Land: Land polygons including major islands
• Ocean: Ocean polygon split into contiguous pieces.
• Minor Islands: additional small ocean islands ranked to two levels of relative importance.
• Reefs: major coral reefs from WDB2.
• Physical region features: polygon and point labels of major physical features.
• Rivers and Lake Centerlines: ranked by relative importance. Includes name and line width attributes. Don’t want minor lakes? Turn on their centerlines to avoid unseemly data gaps.
• Lakes: ranked by relative importance, coordinating with river ranking. Includes name attributes.
• Glaciated areas: polygons derived from DCW, except for Antarctica derived from MOA. Includes name attributes for major polar glaciers.
• Antarctic ice shelves: derived from 2003-2004 MOA. Reflects recent ice shelf collapses.
• Bathymetry: nested polygons at 0, -200, -1,000, -2,000, -3,000, -4,000, -5,000, -6,000, -7,000, -8,000, -9,000,and -10,000 meters. Created from SRTM Plus.
• Geographic lines: Polar circles, tropical circles, equator, and International Date Line.
• Graticules: 1-, 5-, 10-, 15-, 20-, and 30-degree increments. Includes WGS84 bounding box.

This political map of the World shows national boundaries, country names, and major ocean features.

Countries distinguish between metropolitan (homeland) and independent and semi-independent portions of sovereign states. If you want to see the dependent overseas regions broken out (like in ISO codes, see France for example), use map units instead.Each country is coded with a world region that roughly follows the United Nations setup.Includes some thematic data from the United Nations, U.S. Central Intelligence Agency, and elsewhere.DisclaimerNatural Earth Vector draws boundaries of countries according to defacto status. We show who actually controls the situation on the ground. Please feel free to mashup our disputed areas (link) theme to match your particular political outlook.

World coastline intended for use at 1:10 million scales.

Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com.

The Geographic Names Information System (GNIS) actively seeks data from and partnerships with Government agencies at all levels and other interested organizations. The GNIS is the Federal standard for geographic nomenclature. The U.S. Geological Survey developed the GNIS for the U.S. Board on Geographic Names, a Federal inter-agency body chartered by public law to maintain uniform feature name usage throughout the Government and to promulgate standard names to the public. The GNIS is the official repository of domestic geographic names data; the official vehicle for geographic names use by all departments of the Federal Government; and the source for applying geographic names to Federal electronic and printed products of all types. See http://geonames.usgs.gov for additional information.

Use this country model layer when performing analysis within a single country. This layer displays a single global land cover map that is modeled by country for the year 2050 at a pixel resolution of 300m. ESA CCI land cover from the years 2010 and 2018 were used to create this prediction.Variable mapped: Projected land cover in 2050.Data Projection: Cylindrical Equal AreaMosaic Projection: Cylindrical Equal AreaExtent: Global Cell Size: 300mSource Type: ThematicVisible Scale: 1:50,000 and smallerSource: Clark UniversityPublication date: April 2021What you can do with this layer?This layer may be added to online maps and compared with the ESA CCI Land Cover from any year from 1992 to 2018. To do this, add Global Land Cover 1992-2018 to your map and choose the processing template (image display) from that layer called “Simplified Renderer.” This layer can also be used in analysis in ecological planning to find specific areas that may need to be set aside before they are converted to human use.Links to the six Clark University land cover 2050 layers in ArcGIS Living Atlas of the World:There are three scales (country, regional, and world) for the land cover and vulnerability models. They’re all slightly different since the country model can be more fine-tuned to the drivers in that particular area. Regional (continental) and global have more spatially consistent model weights. Which should you use? If you’re analyzing one country or want to make accurate comparisons between countries, use the country level. If mapping larger patterns, use the global or regional extent (depending on your area of interest). Land Cover 2050 - GlobalLand Cover 2050 - RegionalLand Cover 2050 - CountryLand Cover Vulnerability to Change 2050 GlobalLand Cover Vulnerability to Change 2050 RegionalLand Cover Vulnerability to Change 2050 CountryWhat these layers model (and what they don’t model)The model focuses on human-based land cover changes and projects the extent of these changes to the year 2050. It seeks to find where agricultural and urban land cover will cover the planet in that year, and what areas are most vulnerable to change due to the expansion of the human footprint. It does not predict changes to other land cover types such as forests or other natural vegetation during that time period unless it is replaced by agriculture or urban land cover. It also doesn’t predict sea level rise unless the model detected a pattern in changes in bodies of water between 2010 and 2018. A few 300m pixels might have changed due to sea level rise during that timeframe, but not many.The model predicts land cover changes based upon patterns it found in the period 2010-2018. But it cannot predict future land use. This is partly because current land use is not necessarily a model input. In this model, land set aside as a result of political decisions, for example military bases or nature reserves, may be found to be filled in with urban or agricultural areas in 2050. This is because the model is blind to the political decisions that affect land use.Quantitative Variables used to create ModelsBiomassCrop SuitabilityDistance to AirportsDistance to Cropland 2010Distance to Primary RoadsDistance to RailroadsDistance to Secondary RoadsDistance to Settled AreasDistance to Urban 2010ElevationGDPHuman Influence IndexPopulation DensityPrecipitationRegions SlopeTemperatureQualitative Variables used to create ModelsBiomesEcoregionsIrrigated CropsProtected AreasProvincesRainfed CropsSoil ClassificationSoil DepthSoil DrainageSoil pHSoil TextureWere small countries modeled?Clark University modeled some small countries that had a few transitions. Only five countries were modeled with this procedure: Bhutan, North Macedonia, Palau, Singapore and Vanuatu.As a rule of thumb, the MLP neural network in the Land Change Modeler requires at least 100 pixels of change for model calibration. Several countries experienced less than 100 pixels of change between 2010 & 2018 and therefore required an alternate modeling methodology. These countries are Bhutan, North Macedonia, Palau, Singapore and Vanuatu. To overcome the lack of samples, these select countries were resampled from 300 meters to 150 meters, effectively multiplying the number of pixels by four. As a result, we were able to empirically model countries which originally had as few as 25 pixels of change.Once a selected country was resampled to 150 meter resolution, three transition potential images were calibrated and averaged to produce one final transition potential image per transition. Clark Labs chose to create averaged transition potential images to limit artifacts of model overfitting. Though each model contained at least 100 samples of "change", this is still relatively little for a neural network-based model and could lead to anomalous outcomes. The averaged transition potentials were used to extrapolate change and produce a final hard prediction and risk map of natural land cover conversion to Cropland and Artificial Surfaces in 2050.39 Small Countries Not ModeledThere were 39 countries that were not modeled because the transitions, if any, from natural to anthropogenic were very small. In this case the land cover for 2050 for these countries are the same as the 2018 maps and their vulnerability was given a value of 0. Here were the countries not modeled:AndorraAntigua and BarbudaBarbadosCape VerdeComorosCook IslandsDjiboutiDominicaFaroe IslandsFrench GuyanaFrench PolynesiaGibraltarGrenadaGuamGuyanaIcelandJan MayenKiribatiLiechtensteinLuxembourgMaldivesMaltaMarshall IslandsMicronesia, Federated States ofMoldovaMonacoNauruSaint Kitts and NevisSaint LuciaSaint Vincent and the GrenadinesSamoaSan MarinoSeychellesSurinameSvalbardThe BahamasTongaTuvaluVatican CityIndex to land cover values in this dataset:The Clark University Land Cover 2050 projections display a ten-class land cover generalized from ESA Climate Change Initiative Land Cover. 1 Mostly Cropland2 Grassland, Scrub, or Shrub3 Mostly Deciduous Forest4 Mostly Needleleaf/Evergreen Forest5 Sparse Vegetation6 Bare Area7 Swampy or Often Flooded Vegetation8 Artificial Surface or Urban Area9 Surface Water10 Permanent Snow and Ice

This dataset contains geometry data for the countries of the world together with their names and country codes in various formats. The primary use case is choropleths, color-coded maps. The data can be read as a pandas DataFrame with geopandas and plotted with matplotlib. See the starter notebook for an example how to do it.

The data was created by Natural Earth. It is in public domain and free to use for any purpose at the time of this writing; you might want to check their Terms of Use.

Photo by KOBU Agency on Unsplash