The original World Vector Shoreline (WVS) was a digital data file containing the shorelines, international boundaries, and country names of the world. WVS data were processed into NGA’s Vector Product Format in 1995, resulting in the highest resolution demarcation of coastline globally available, the World Vector Shoreline Plus. Six libraries exist, within this single worldwide database, at scales ranging from 1:250,000 to 1:120,000,000. Each library contains a Countries/Coastlines/Oceans (COC) coverage, including both line and area features such as coastlines, political boundary lines, and other lines of separation, administrative areas, and oceans. Each library also contains the following reference coverages: library reference (LIBREF), which gives an overview of the library; tile reference (TILEREF), which defines the tiling scheme for each library; and names placement (GAZETTE), which contains point features that represent the approximate centroid of each locality in the WVS Plus database. The maritime boundaries (MAB) and maritime boundaries supplemental (MBS) coverages contain maritime claims for each country as derived from the Maritime Claims Reference Manual, DOD 2005.1M, 2001. MAB and MBS are found only in the WVS250K library (1:250,000 scale). The bathymetry (BAT) coverage exists only in the WVS003M, WVS012M, and WVS040M libraries and contains depth contours and depth areas derived from the digital bathymetric database product. See the Vector Product Format (VPF) World Vector Shoreline (WVSPLUS) Draft Specification (MIL-PRF-89012A dated August 24, 1999) for a detailed product definition, and the VPF Military Standard (MIL-STD-2407) for more descriptions of VPF.

Tidal Datum: Mean high water (MHW)

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

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

These shoreline polygon data can be used to simplify data searches and data selections and to study the statistical characteristics of shorelines and land-masses.

From the vendor web pages at http://www.cartographic.com/products/gis/vpf/wvsplus.asp This product of unprecedented detail covers the entire Earth, covering the coastlines and international boundaries of every continent, including Antarctica. WVSPLUS is one database comprised of six libraries varying from 1:250,000 to 1:120,000,000 scales.These libraries, WVS250K, WVS001M, WVS003M, WVS012M, WVS040M, and WVS120M, represent the world at 1:250,000, 1:1,000,000, 1:3,000,000, 1:12,000,000, 1:40,000,000, and 1:120,000,000 scales respectively. Each library contains several thematic coverages: * Coastline/Countries/Ocean * Maritime Boundaries (for 1:250,000 scale only) * Supplemental Maritime Boundaries (for 1:250,000 scale only) * Bathymetry (for 1:40,000,000, 1:12,000,000 and 1:3,000,000 scales only) * Names Placement * Data QualityWVSPLUS data can be easily viewed or imported with a number of software programs including ESRI's suite of products (ArcInfo, ArcGIS, ArcView) and MapInfo.The original data structure is Vector Product Format (VPF) to US Military Standard (MIL-STD-2407), which is compliant with the international standard, Digital Geographic Information Exchange Standard (DIGEST) Annex C. The WVSPLUS feature and attribute content is defined in the US Military Specification MIL-PRF-89012A.

The Office of the Geographer’s Global Large Scale International Boundary Detailed Polygons file combines two datasets, the Office of the Geographer’s Large Scale International Boundary Lines and NGA shoreline data. The LSIB is believed to be the most accurate worldwide (non- W. Europe) international boundary vector line file available. The lines reflect U.S. government (USG) policy and thus not necessarily de facto control. The 1:250,000 scale World Vector Shoreline (WVS) coastline data was used in places and is generally shifted by several hundred meters to over a km. There are no restrictions on use of this public domain data. The Tesla Government PiX team performed topology checks and other GIS processing while merging data sets, created more accurate island shoreline in numerous cases, and worked closely with the US Dept. of State Office of the Geographer on quality control checks.

Methodology: Tesla Government’s Protected Internet Exchange (PiX) GIS team converted the LSIB linework and the island data provided by the State Department to polygons. The LSIB Admin 0 world polygons (Admin 0 polygons) were created by conflating the following datasets: Eurasia_Oceania_LSIB7a_gen_polygons, Africa_Americas_LSIB7a_gen_polygons, Africa_Americas_LSIB7a, Eurasia_LSIB7a, additional updates from LSIB8, WVS shoreline data, and other shoreline data from United States Government (USG) sources. The two simplified polygon shapefiles were merged, dissolved, and converted to lines to create a single global coastline dataset. The two detailed line shapefiles (Eurasia_LSIB7a and Africa_Americas_LSIB7a) were merged with each other and the coastlines to create an international boundary shapefile with coastlines. The dataset was reviewed for the following topological errors: must not self overlap, must not overlap, and must not have dangles. Once all topological errors were fixed, the lines were converted to polygons. Attribution was assigned by exploding the simplified polygons into multipart features, converting to centroids, and spatially joining with the newly created dataset. The polygons were then dissolved by country name. Another round of QC was performed on the dataset through the data reviewer tool to ensure that the conversion worked correctly. Additional errors identified during this process consisted of islands shifted from their true locations and not representing their true shape; these were adjusted using high resolution imagery whereupon a second round of QC was applied with SRTM digital elevation model data downloaded from USGS. The same procedure was performed for every individual island contained in the islands from other USG sources.
After the island dataset went through another round of QC, it was then merged with the Admin 0 polygon shapefile to form a comprehensive world dataset. The entire dataset was then evaluated, including for proper attribution for all of the islands, by the Office of the Geographer.

The first edition of the Antarctic Digital Database (ADD) coastline polygon dataset. A compilation of source data from eleven national mapping agencies at data scales no larger than 1:200,000/1:250:000. Polygon dataset was originally published on CD-ROM in 1993, in tiled Coverage format. Data has since been converted and merged to a single dataset and exported to shapefile and geopackage formats. Scale0 is the highest resolution that was produced. Each polygon has a surface attribute (CST00SRF) indicating the type of feature it represents, ie. ice shelf, ice tongue, land, ocean and rumple. For information on source of polygon delineations, refer to coincident features in the polyline dataset, Scale0 vector polylines of the Antarctic coastline v1.0. The ADD project was first proposed in 1990 by a Cambridge (UK) based consortium comprising British Antarctic Survey (BAS), Scott Polar Research Institute (SPRI) and the World Conservation Monitoring Centre (now UNEP World Conservation Monitoring Centre(UNEP-WCMC)). International participation in the project was agreed through the Scientific Committee on Antarctic Research (SCAR) and its Working Group on Geodesy and Geographic Information. The majority of data capture and data management was undertaken in Cambridge, UK. Work was initially funded by BAS and by The British Petroleum Company p.l.c (BP). Other contributing nations sponsored their own data capture through either their national mapping agencies or their Antarctic research organisations. BP had no commercial interest in the project and the information gained from this database was in the public domain. BAS, SPRI, WCMC and SCAR, by entering into this project with BP, in no way implied their acceptance or endorsement of any exploration activity for oil, gas or minerals in Antarctica. For full details on the dataset, please refer to the ADD Manual v1.0: https://nora.nerc.ac.uk/id/eprint/517623/.

This resource was developed by the U.S. Geological Survey (USGS) in partnership with Esri and the Marine Biodiversity Observation Network (MBON). These data were developed as part of a Group on Earth Observations (GEO) initiative called GEO Ecosystems (GEO ECO), and is associated with a GEO ECO task to develop global coastal ecosystems data. The data allows for the visualization and query of any stretch of coastline on Earth, except for Antarctica. The underlying data are 4 million 1 km or shorter coastal segments, each of which is attributed with values from ten ecological settings variables representing the adjacent ocean, the adjacent land, and the coastline itself.The 4 million coastal segments were classified into 81,000 coastal segment units (CSUs) using the Coastal and Marine Ecosystem Classification Standard (CMECS). Each distinct CSU is a segment with a unique combination of the classes of values of the ten ecological settings variables. The 4 million segments were also clustered into a set of 16 global groups of coastlines which are similar in the aggregate ecological setting described by the ten variables.See this video for an animation showing ECU coverage and classification.Reference:Sayre, R., K. Butler, K. VanGraafeiland, S. Breyer, D. Wright, C. Frye, D. Karagulle, M. Martin, J. Cress, T. Allen, R. Allee, R. Parsons, B. Nyberg, M. Costello, F. Muller-Karger, and P. Harris. 2021. Earth's coastlines. In Wright, D. and C. Harder (eds), GIS For Science, Volume 3: Maps for Saving the Planet. Esri Press, Redlands, California.Sayre, R., S. Noble, S. Hamann, R. Smith, D. Wright, S. Breyer, K. Butler, K. Van Graafeiland, C. Frye, D. Karagulle, D. Hopkins, D. Stephens, K. Kelly, Z, basher, D. Burton, J. Cress, K. Atkins, D. van Sistine, B. Friesen, B. Allee, T. Allen, P. Aniello, I Asaad, M. Costello, K. Goodin, P. Harris, M. Kavanaugh, H. Lillis, E. Manca, F. Muller-Karger, B. Nyberg, R. Parsons, J. Saarinen, J. Steiner, and A. Reed. 2018. A new 30 meter resolution global shoreline vector and associated global islands database for the development of standardized global ecological coastal units. Journal of Operational Oceanography – A Special Blue Planet Edition. DOI:10.1080/1755876X.2018.1529714.Contacts:Roger Sayre, U.S. Geological Survey

This polygon shapefile represents the boundary between island ponds and islands at low resolution. Low represents an 80 percent reduction in size and quality from the intermediate resolution layer. The Global Self-consistent, Hierarchical, High-resolution Geography (GSHHG) Database is a high-resolution geography data set amalgamated from three data bases in the public domain. This layer is part of GSHHG Version 2.3.3. The World Vector Shorelines (WVS) is the basis for shorelines except for Antarctica while the CIA World Data Bank (WDBII) is the basis for lakes, although there are instances where differences in coastline representations necessitated adding WDBII islands to GSHHG. The WDBII source also provides all political borders and rivers. GSHHG data have undergone extensive processing and should be free of internal inconsistencies such as erratic points and crossing segments. Atlas of the Cryosphere (AC) provides the basis for Antarctica coastlines. The shorelines are constructed entirely from hierarchically arranged closed polygons.

These shoreline polygon data can be used to simplify data searches and data selections and to study the statistical characteristics of shorelines and land-masses.

These shoreline polygon data can be used to simplify data searches and data selections and to study the statistical characteristics of shorelines and land-masses.

These shoreline polygon data can be used to simplify data searches and data selections and to study the statistical characteristics of shorelines and land-masses.

The first edition of the Antarctic Digital Database (ADD) coastline polyline dataset. A compilation of source data from eleven national mapping agencies at data scales no larger than 1:200,000/1:250:000. Line dataset was originally published on CD-ROM in 1993, in tiled Coverage format. Data has since been converted merged to a single dataset and exported to shapefile and geopackage formats. Scale0 is the highest resolution that was produced. The ADD project was first proposed in 1990 by a Cambridge (UK) based consortium comprising British Antarctic Survey (BAS), Scott Polar Research Institute (SPRI) and the World Conservation Monitoring Centre (now UNEP World Conservation Monitoring Centre (UNEP-WCMC)). International participation in the project was agreed through the Scientific Committee on Antarctic Research (SCAR) and its Working Group on Geodesy and Geographic Information. The majority of data capture data management was undertaken in Cambridge, UK. Work was initially funded by BAS and by The British Petroleum Company p.l.c (BP). Other contributing nations sponsored their own data capture through either their national mapping agencies or their Antarctic research organisations. BP had no commercial interest in the project and the information gained from this database was in the public domain. BAS, SPRI, WCMC and SCAR, by entering into this project with BP, in no way implied their acceptance or endorsement of any exploration activity for oil, gas or minerals in Antarctica. For full details on the dataset, please refer to the ADD Manual v1.0: https://nora.nerc.ac.uk/id/eprint/517623/.

Data as of March 8, 2013. These boundary lines were derived from the World Vector Shoreline dataset and match up with the 2013 detailed LSIB polygons.

The 1:250,000 scale World Vector Shoreline (WVS) coastline data is generally shifted by several hundred meters to over a km. To simplify the polygons, the ArcGIS Simplify Polygon tool was used, using the Bend Simplify algorithm with a maximum allowable offset of 3 miles. Topology was then corrected for any errors produced by the simplification process. For convenience, the dataset is broken out into regions: (1) Africa, (2) Asia and Russia, (3) Europe and Southwest Asia, (4) North America, (5) Oceania, and (6) South America. In the zip file, there is also a global dataset (approximately 24 MBs) that includes all the data.

There are no restrictions on use of this public domain data. This dataset will be updated as needed and is current as of March 08, 2013.

The Prototype Global Shoreline Data set (satellite derived high water line) in work at NGA has been acquired from orthorectified NASA, 2000 era, LANDSAT GeoCover (multispectral imagery). As the prototype effort progresses, NGA will begin compilation of a new version of the World Vector Shoreline.The research and development component of NGA, InnoVision Directorate, studied the best approach for acquiring shoreline data using LANDSAT 7 multispectral imagery and developed a technique using the Short-Wave Infra-Red (SWIR) bands to define the land–water interface. This new shoreline is an approximation of the high water line; it is NOT a mean high water line since the source data have not been tide-coordinated. As segments of the prototype version are accepted from the contractor, these segments are being made available in the interest of supporting outside users who may have immediate application for these higher-resolution data. The file was downloaded as polyline for multiple regions (14-16) to cover the entire Caribbean. The original polyline file had several gaps representing river outlets. These gaps were connected by straight lines by John Knowles of the Nature Conservancy. The file was then converted into a polygon.

This 1:2 million shoreline was downloaded from the National Geophysical Data Center (NGDC) produced by NOAA Satellite and Information Service at http://rimmer.ngdc.noaa.gov/mgg/coast/getcoast.html.The shoreline was created from the World Data Bank II. (Fair Resolution. World Wide Coverage. This data is suitable for map scales of 2,000,000 or smaller. Also contains international and internal political boundaries and rivers.)The CIA World DataBank II is a collection of world map data, consisting of vector descriptions of land outlines, rivers, and political boundaries. This highly compressed binary version was created by the U.S. government in the 1980s.http://www.evl.uic.edu/pape/data/WDB/

CoastSeg: Beach transects and beachface slope database v2.0

Coastal shoreline-normal transects, to support shoreline extraction from satellite imagery, and tidal correction of CoastSeg-derived shoreline time-series and other shoreline data, as well as miscellaneous analyses of coastal shoreline data.

These data work with the software package CoastSeg https://github.com/SatelliteShorelines/CoastSeg. More details are available on the project's website https://satelliteshorelines.github.io/CoastSeg/

These transecst are not comprehensive in coverage, representing the best available data known to us at this time, and are provided to the user as a courtesy, but each user has the option (and is encouraged) to develop and use their own transects.

Transects data

1. id: unique ID code

2. slope: beach face slope, for tidal correction of transect-based data3. distance: distance in degrees between slope datum location and transect location4. feature_x: transect location x5. feature_y: transect location y6. nearest_x: nearest slope location x7. nearest_y: nearest slope location y

Note that beach slopes are not available for every transect location. A value of NULL is used in those (relatively rare) locations.

Beach face slope and transect data have been derived from:

1. Doran, K.S., Long, J.W., Birchler, J.J., Brenner, O.T., Hardy, M.W., Morgan, K.L.M, Stockdon, H.F., and Torres, M.L., 2017, Lidar-derived beach morphology (dune crest, dune toe, and shoreline) for U.S. sandy coastlines (ver. 4.0, October 2020): U.S. Geological Survey data release, https://doi.org/10.5066/F7GF0S0Z.

2. Kilian Vos. (2023). Time-series of shoreline change along the Pacific Rim (v1.4) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7758183

3. Andrew Short. (2022). Sediment size dataset for Australia [Data set]. In Australian Coastal Systems (0.1, p. XXV, 1241). Springer Cham. https://doi.org/10.5281/zenodo.7127186

4. Vos, Kilian, Wen, Deng, Harley, Mitchell D., Turner, Ian L., & Splinter, Kristen D. (2022). Beach-face slope dataset for Australia (Version 2) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7272538

5. Gibbs, A.E., Ohman, K.A., Coppersmith, R., and Richmond, B.M., 2017, National Assessment of Shoreline Change: A GIS compilation of updated vector shorelines and associated shoreline change data for the north coast of Alaska, U.S. Canadian border to Icy Cape: U.S. Geological Survey data release, https://doi.org/10.5066/F72Z13N1.

6. Himmelstoss, E.A., Kratzmann, M., Hapke, C., Thieler, E.R., and List, J., 2010, The National Assessment of Shoreline Change: A GIS Compilation of Vector Shorelines and Associated Shoreline Change Data for the New England and Mid-Atlantic Coasts: U.S. Geological Survey Open-File Report 2010-1119, available at https://pubs.usgs.gov/of/2010/1119/.

7. Snyder, A.G., and Gibbs, A.E., 2019, National assessment of shoreline change: A GIS compilation of updated vector shorelines and associated shoreline change data for the north coast of Alaska, Icy Cape to Cape Prince of Wales: U.S. Geological Survey data release, https://doi.org/10.5066/P9H1S1PV

8. Romine, B.M., Fletcher, C.H., Genz, A.S., Barbee, M.M., Dyer, Matthew, Anderson, T.R., Lim, S.C., Vitousek, Sean, Bochicchio, Christopher, and Richmond, B.M., 2012, National Assessment of Shoreline Change: A GIS compilation of vector shorelines and associated shoreline change data for the sandy shorelines of Kauai, Oahu, and Maui, Hawaii: U.S. Geological Survey Open-File Report 2011-1009, available online at https://pubs.usgs.gov/of/2011/1009/.

9. Gibbs, A.E., Jones, B.M., and Richmond, B.M., 2020, A GIS compilation of vector shorelines and coastal bluff edge positions, and associated rate-of-change data for Barter Island, Alaska: U.S. Geological Survey data release, https://doi.org/10.5066/P9CRBC5I.

10. Sturdivant, E.J., Zeigler, S.L., Gutierrez, B.T., and Weber, K.M., 2019, Barrier island geomorphology and shorebird habitat metrics–Sixteen sites on the U.S. Atlantic Coast, 2013–2014: U.S. Geological Survey data release, https://doi.org/10.5066/P9V7F6UX.

Additional contributions:

1. Sean Vitousek, USGS

Bounding boxes

These supporting files are the bounding boxes of vector datasets used by the program to attribute transects data

shorelines_bounding_boxes.csv

transects_bounding_boxes.csv

usa_shorelines_bounding_boxes.geojson

world_reference_shorelines_bboxes.geojson

Reference shoreline data is from Sayre et al. (2018)

Sayre, R., Noble, S., Hamann, S., Smith, R., Wright, D., Breyer, S., Butler, K., Van Graafeiland, K., Frye, C., Karagulle, D. and Hopkins, D., 2019. A new 30 meter resolution global shoreline vector and associated global islands database for the development of standardized ecological coastal units. Journal of Operational Oceanography, 12(sup2), pp.S47-S56.

Shoreline change analysis is an important environmental monitoring tool for evaluating coastal exposure to erosion hazards, particularly for vulnerable habitats such as coastal wetlands where habitat loss is problematic world-wide. The increasing availability of high-resolution satellite imagery and emerging developments in analysis techniques support the implementation of these data into coastal management, including shoreline monitoring and change analysis. Geospatial shoreline data were created from a semi-automated methodology using WorldView (WV) satellite data between 2013 and 2020. The data were compared to contemporaneous field-surveyed Real-time Kinematic (RTK) Global Position System (GPS) data collected by the Grand Bay National Estuarine Research Reserve and digitized shorelines from U.S. Department of Agriculture National Agriculture Imagery Program (NAIP) orthophotos. Field data for shoreline monitoring sites was also collected to aid interpretation of results. This data release contains digital vector shorelines, shoreline change calculations for all three remote sensing data sets, and field surveyed data. The data will aid managers and decision-makers in the adoption of high-resolution satellite imagery into shoreline monitoring activities, which will increase the spatial scale of shoreline change monitoring, provide rapid response to evaluate impacts of coastal erosion, and reduce cost of labor-intensive practices. For further information regarding data collection and/or processing methods, refer to the associated journal article (Smith and others, 2021).

These data provide an accurate high-resolution shoreline compiled from imagery of PORT OF PANAMA CITY, FL . This vector shoreline data is based on an office interpretation of imagery that may be suitable as a geographic information system (GIS) data layer. This metadata describes information for both the line and point shapefiles. The NGS attribution scheme 'Coastal Cartographic Object Attribute Source Table (C-COAST)' was developed to conform the attribution of various sources of shoreline data into one attribution catalog. C-COAST is not a recognized standard, but was influenced by the International Hydrographic Organization's S-57 Object-Attribute standard so the data would be more accurately translated into S-57. This resource is a member of https://www.fisheries.noaa.gov/inport/item/39808

Data file: W_USA_Oregon_Washington_ref_shoreline.geojson

Region: California/Oregon border to Washington/Canada border

Data fields:

1. MEAN_SIG_WAVEHEIGHT
2. TIDAL_RANGE
3. CHLOROPHYLL
4. TURBIDITY
5. TEMP_MOISTURE
6. EMU_PHYSICAL
7. REGIONAL_SINUOSITY
8. GHM
9. MAX_SLOPE %
10. OUTFLOW_DENSITY
11. ERODIBILITY
12. LENGTH_GEO
13. ch_label
14. river_label
15. sinuosity_label
16. slope_label
17. tidal_label
18. turbid_label
19. wave_label
20. CSU_Descriptor
21. CSU_ID

The data originally come from https://rmgsc.cr.usgs.gov/outgoing/ecosystems/Global/USGSEsriGlobalCoastalSegmentsv1.mpk

The data are described in the following publication

Roger Sayre, Suzanne Noble, Sharon Hamann, Rebecca Smith, Dawn Wright, Sean Breyer, Kevin Butler, Keith Van Graafeiland, Charlie Frye, Deniz Karagulle, Dabney Hopkins, Drew Stephens, Kevin Kelly, Zeenatul Basher, Devon Burton, Jill Cress, Karina Atkins, D. Paco Van Sistine, Beverly Friesen, Rebecca Allee, Tom Allen, Peter Aniello, Irawan Asaad, Mark John Costello, Kathy Goodin, Peter Harris, Maria Kavanaugh, Helen Lillis, Eleonora Manca, Frank Muller-Karger, Bjorn Nyberg, Rost Parsons, Justin Saarinen, Jac Steiner & Adam Reed (2019) A new 30 meter resolution global shoreline vector and associated global islands database for the development of standardized ecological coastal units, Journal of Operational Oceanography, 12:sup2, S47-S56, DOI: 10.1080/1755876X.2018.1529714

ABSTRACT

A new 30-m spatial resolution global shoreline vector (GSV) was developed from annual composites of 2014 Landsat satellite imagery. The semi-automated classification of the imagery was accomplished by manual selection of training points representing water and non-water classes along the entire global coastline. Polygon topology was applied to the GSV, resulting in a new characterisation of the number and size of global islands. Three size classes of islands were mapped: continental mainlands (5), islands greater than 1 km² (21,818), and islands smaller than 1 km² (318,868). The GSV represents the shore zone land and water interface boundary, and is a spatially explicit ecological domain separator between terrestrial and marine environments. The development and characteristics of the GSV are presented herein. An approach is also proposed for delineating standardised, high spatial resolution global ecological coastal units (ECUs). For this coastal ecosystem mapping effort, the GSV will be used to separate the nearshore coastal waters from the onshore coastal lands. The work to produce the GSV and the ECUs is commissioned by the Group on Earth Observations (GEO), and is associated with several GEO initiatives including GEO Ecosystems, GEO Marine Biodiversity Observation Network (MBON) and GEO Blue Planet.

https://www.tandfonline.com/doi/full/10.1080/1755876X.2018.1529714

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.