International boundaries provided by United Nations Clear Map. The United Nations Clear Map (hereinafter “Clear Map”) is a background reference web mapping service produced to facilitate “the issuance of any map at any duty station, including dissemination via public electronic networks such as Internet” and “to ensure that maps meet publication standards and that they are not in contravention of existing United Nations policies” in accordance with the in the Administrative Instruction on “Regulations for the Control and Limitation of Documentation – Guidelines for the Publication of Maps” of 20 January 1997 (http://undocs.org/ST/AI/189/Add.25/Rev.1) Clear Map is created for the use of the United Nations Secretariat and community. All departments, offices and regional commissions of the United Nations Secretariat including offices away from Headquarters using Clear Map remain bound to the instructions as contained in the Administrative Instruction and should therefore seek clearance from the UN Geospatial Information Section (formerly Cartographic Section) prior to the issuance of their thematic maps using Clear Map as background reference. Disclaimers: The designations employed and the presentation of material on this map do not imply the expression of any opinion whatsoever on the part of the Secretariat of the United Nations concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. Credits (Attribution) Produced by: United Nations Geospatial Contributor: UNGIS, UNGSC, Field Missions CONTACT US: Your feedback is appreciated and should be sent directly to: Email:Clearmap@un.org / gis@un.org (UNCLASSIFIED) © UNITED NATIONS 2018 More information on the United Nations Clear Map website at https://geoportal.dfs.un.org/arcgis/sharing/rest/content/items/541557fd0d4d42efb24449be614e6887/data

This is a PDF format map of the country, as released by the United Nations.

United Nations map (known as UNmap) is a worldwide geospatial database consisting of country and geographic name information on a global scale. The data is designed for the production of cartographic documents and maps, including their dissemination via public electronic networks, for the Secretariat of the United Nations.The United Nations maintains the Data as a courtesy to those who may choose to access the Data. The Data is provided “as is”, without warranty of any kind, either express or implied, including, without limitation, warranties of merchantability, fitness for a particular purpose and non-infringement.

Disclaimers: - The boundaries and names shown and the designations used on this map do not imply official endorsement or acceptance by the United Nations. - The designations employed and the presentation of material on this map do not imply the expression of any opinion whatsoever on the part of the Secretariat of the United Nations concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. - Dotted line represents approximately the Line of Control in Jammu and Kashmir agreed upon by India and Pakistan. - The final status of Jammu and Kashmir has not yet been agreed upon by the parties. - Final boundary between the Republic of Sudan and the Republic of South Sudan has not yet been determined. - Final status of the Abyei area is not yet determined. - A dispute exists between the Governments of Argentina and the United Kingdom of Great Britain and Northern Ireland concerning sovereignty over the Falkland Islands (Malvinas).

Generalization parametrisation for the data is developed based on the work of Douglas and Peucker (1973), Wang (1996) and the Polynomial Approximation with Exponential Kernel algorithm.The adequate generalized data should be used for the intended dissemination scale and not rely on software or platform-automated generalization as some specific geographic features are removed at scales. For instance, the region of Abyei is not included at the scale of 1:25 million but is included at lower scales.

Maps produced using this layer should be featured with the appropriate disclaimer depending on the shown area.

Source: United Nations International and Administrative Boundaries Resources

The guidance and associated data have been developed by the the United Nations Geospatial Information Section (formerly Cartographic Section) and should be intended as a practical implementation resource to ensure publication standards are met across the United Nations. In accordance with the Administrative Instruction of the Secretary-General of the United Nations (ST/AI/189/Add.25/Rev.1), and in particular "in view of the sensitive nature of cartographic documents,” users producing cartographic outputs must adhere to UN publication standards, referring to the "Guidance for the Publication of Maps" from the Geospatial Information Section of the UN (please find link for download in the Distribution section). The guidance provides the mandatory disclaimers, recommended policies, cartographic practices and representations, with particular attention to disputed areas and boundaries. The guidance document is confidential and is maintained as a courtesy to the United Nations Secretariat, and if applicable, the United Nations system. United Nations map (known as UNMap) is a worldwide geospatial database consisting of country and geographic name information on a global scale. Country names are based on the United Nations Terminology Database (UNTERM) following the names submitted by Member States to the United Nations Protocol and Liaison Office. The data is prepared to serve global mapping purposes, thus the relevant scale and purpose available are as follows: - Scale of 1:1 million suitable for mapping large provinces and small countries (e.g. Gambia) - Scale of 1:5 million suitable for mapping large countries (e.g. Sudan) - Scale of 1:25 million suitable for mapping the world FAO as UN Agency has been granted to consult the guidance and to access and use the associated geospatial information, provided that the data will not be redistributed outside the Organization. A step-by-step Guide on the Publication of Thematic Maps

This is a PDF format map of the country, as released by the United Nations.

This is a PDF format map of the country, as released by the United Nations.

United Nations map (known as UNmap) is a worldwide geospatial database consisting of country and geographic name information on a global scale. The data is designed for the production of cartographic documents and maps, including their dissemination via public electronic networks, for the Secretariat of the United Nations.The United Nations maintains the Data as a courtesy to those who may choose to access the Data. The Data is provided “as is”, without warranty of any kind, either express or implied, including, without limitation, warranties of merchantability, fitness for a particular purpose and non-infringement.

Disclaimers: - The boundaries and names shown and the designations used on this map do not imply official endorsement or acceptance by the United Nations. - The designations employed and the presentation of material on this map do not imply the expression of any opinion whatsoever on the part of the Secretariat of the United Nations concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. - Dotted line represents approximately the Line of Control in Jammu and Kashmir agreed upon by India and Pakistan. - The final status of Jammu and Kashmir has not yet been agreed upon by the parties. - Final boundary between the Republic of Sudan and the Republic of South Sudan has not yet been determined. - Final status of the Abyei area is not yet determined. - A dispute exists between the Governments of Argentina and the United Kingdom of Great Britain and Northern Ireland concerning sovereignty over the Falkland Islands (Malvinas).

Generalization parametrisation for the data is developed based on the work of Douglas and Peucker (1973), Wang (1996) and the Polynomial Approximation with Exponential Kernel algorithm.The adequate generalized data should be used for the intended dissemination scale and not rely on software or platform-automated generalization as some specific geographic features are removed at scales. For instance, the region of Abyei is not included at the scale of 1:25 million but is included at lower scales.

Maps produced using this layer should be featured with the appropriate disclaimer depending on the shown area.

Source: United Nations International and Administrative Boundaries Resources

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/.

This is a PDF format map of the country, as released by the United Nations.

The table contains all the de jure neighbours of all the UN countries. Land and maritime borders (within 12 nautical miles) have been taken into account.

This is a PDF format map of the country, as released by the United Nations.

This is an excel mapping tool that was built based on Cuba administrative boundaries (admin2) - extracted from the GADM database (www.gadm.org), version 2.8, November 2015. Available on HDX: https://data.humdata.org/dataset/cuba-administrative-boundaries-levels-0-and-1-from-gadm). The population dataset is a sample data. The tool is built to help people to quickly map their datasets.

This vector dataset contains FAO processed administrative boundaries from multiple sources, produced in 2022 for the Hand-in-Hand Initiative Geospatial Platform publishing. The data was sourced and processed from the United Nations second administrative level boundaries (UN-SALB) programme, complemented with Hand-in-Hand Initiative and geospatial platform data from official geospatial data producers. Country boundaries are processed against UN official recognized borders (UN-map 2018), administrative subdivision checked for geometry a topology, validated, and corrected. Attributes are standardized to the UN-SALB programme schema and coding system. Processed by UN-FAO-CSI AgroInformatics geospatial analysis team, the data is used for thematic mapping, geospatially enabled statistics location-based integration, and Hand-in-Hand geospatial analysis (GIS-MCDA, suitability/location analysis, agricultural typologies, zonal statistics extraction).

Population density per pixel at 100 metre resolution. WorldPop provides estimates of numbers of people residing in each 100x100m grid cell for every low and middle income country. Through ingegrating cencus, survey, satellite and GIS datasets in a flexible machine-learning framework, high resolution maps of population counts and densities for 2000-2020 are produced, along with accompanying metadata. DATASET: Alpha version 2010 and 2015 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates and remaining unadjusted. REGION: Africa SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator) PROJECTION: Geographic, WGS84 UNITS: Estimated persons per grid square MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743. FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) FILENAMES: Example - AGO10adjv4.tif = Angola (AGO) population count map for 2010 (10) adjusted to match UN national estimates (adj), version 4 (v4). Population maps are updated to new versions when improved census or other input data become available.

This map is part of SDGs Today. Please see sdgstoday.orgThe Voluntary National Reviews (VNRs) aim to facilitate the sharing of experiences, including successes, challenges, and lessons learned, with the goal of accelerating the implementation of the 2030 Agenda. They also help to strengthen governments’ policies and institutions and mobilize multi-stakeholder support and partnerships for the Sustainable Development Goals. VNRs are country‐led, prepared by governments in a consultative, inclusive, and participatory process involving all sectors and levels of government, civil society, private sector, members of Parliament, and other institutions. The UN Sustainable Development Knowledge Platform collects key documents and information on countries that have participated in VNRs as part of their Voluntary National Reviews Database. This dataset represents the countries that have participated in VNRs since 2016. Further information on the process of conducting VNRs can be found in the Handbook for the Preparation of Voluntary National Reviews. Questions on VNRs can be submitted through the contact form for the Sustainable Development Knowledge Platform.

This dataset represents the second-level administrative unit 'States' of Nigeria. The dataset was prepared by the Office of the Surveyor General of the Federation, Federal Surveys of Nigeria in February 2022 to Second Administrative Level Boundaries (SALB) Program of United Nations. The reference scale for this Geospatial data is equivalent to 1:1,000,000 scale, or larger scale. Data was downloaded from UN-SALB site in June 2022, feature topology/geometry was corrected, international borders validated against the United Nations official borders (United Nations Geospatial Information Section - UN-Map 2018). The dataset is part of FAO's Hand-in-Hand (HiH) second administrative level boundaries 2022 dataset series, published on the HiH Geospatial Platform for thematic mapping, integration of geospatially enabled statistics, zonal statistics extraction, and used for HiH initiative geospatial analysis (GIS-MCDA, suitability/location analysis, agricultural typologies).

Boundaries of the World.The boundaries, and names shown and designations used on maps, tables, documents, and databases do not imply official endorsement or acceptance by the United Nations.The boundaries dataset is suitable at the scale of 1 : 1 million.

This is a PDF format map of the country, as released by the United Nations.

Population density per pixel at 100 metre resolution. WorldPop provides estimates of numbers of people residing in each 100x100m grid cell for every low and middle income country. Through ingegrating cencus, survey, satellite and GIS datasets in a flexible machine-learning framework, high resolution maps of population counts and densities for 2000-2020 are produced, along with accompanying metadata. DATASET: Alpha version 2010 and 2015 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/) and remaining unadjusted. REGION: Africa SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator) PROJECTION: Geographic, WGS84 UNITS: Estimated persons per grid square MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743. FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) FILENAMES: Example - AGO10adjv4.tif = Angola (AGO) population count map for 2010 (10) adjusted to match UN national estimates (adj), version 4 (v4). Population maps are updated to new versions when improved census or other input data become available.

GlobCover is a European Space Agency (ESA) initiative which began in 2005 in partnership with the Joint Research Center, European Environmental Agency, UN Food and Agricultural Organization, UN Environment Programme, Global Observation of Forest Cover and Land Cover Dynamics, and International Geosphere-Biosphere Programme. The aim of the project was to develop a service capable of delivering global composites and land cover maps using observations from the 300 meter MERIS sensor on board the ENVISAT satellite mission. ESA makes land cover maps available covering 2 periods: December 2004 - June 2006 and January - December 2009. GlobCover products come with a thematic legend compatible with the UN Land Cover Classification System (LCCS).Data in this layer was generated using MERIS images which were classified using both a supervised (human-verified) and unsupervised (automated)classification algorithm applied at two different seasonal time steps to create land cover classes based on both spectral and temporal properties of land cover. The labeling procedure is automated and based on the GlobCover 2005 (v2.2) land cover map. Several decision rules have been defined with the help of international land cover experts to create unique labels for each class.