This dataset holds all information related to FSM published on the Food and Agriculture Organization website

Abstract

The FAO has developed a monitoring system in 26 food crisis countries to better understand the impacts of various shocks on agricultural livelihoods, food security and local value chains. The Monitoring System consists of primary data collected from households on a periodic basis (more or less every four months, depending on seasonality). The FAO conducted the fourth round of DIEM household survey in Cameroon between 20 March and 8 April 2023 to assess agricultural livelihoods and food security. Data was collected through computer-assisted telephone interviews conducted by Geopoll, an implementing partner, in seven of Cameroon's ten regions (Adamawa, East, Far-North, North, North-West, West and South-West). A sample of 1466 households was reached. For more information, please go to https://data-in-emergencies.fao.org/pages/monitoring

Geographic coverage

National Coverage

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

Data was collected through computer-assisted telephone interviews conducted by Geopoll, an implementing partner, in seven of Cameroon's ten regions (Adamawa, East, Far-North, North, North-West, West and South-West). A sample of 1 466 households was reached. Data collection took place at the end of the dry season and at the start of the short rainy season in the West and North-West regions, during the dry season in the northern regions (Adamawa, North and Far-North), and at the start of the planting season in the other regions. The survey is representative at the regional level, and the sampling plan was designed with a margin of error of 8.5 per cent.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

A link to the questionnaire has been provided in the documentations tab.

Cleaning operations

The datasets have been edited and processed for analysis by the Needs Assessment team at the Office of Emergencies and Resilience, FAO, with some dashboards and visualizations produced. For more information, see https://data-in-emergencies.fao.org/pages/countries.

Malawi MW: Net Official Flows from UN Agencies: FAO data was reported at 0.180 USD mn in 2013. Malawi MW: Net Official Flows from UN Agencies: FAO data is updated yearly, averaging 0.180 USD mn from Dec 2013 (Median) to 2013, with 1 observations. Malawi MW: Net Official Flows from UN Agencies: FAO data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Malawi – Table MW.World Bank: Defense and Official Development Assistance. Net official flows from UN agencies are the net disbursements of total official flows from the UN agencies. Total official flows are the sum of Official Development Assistance (ODA) or official aid and Other Official Flows (OOF) and represent the total disbursements by the official sector at large to the recipient country. Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. OOF are transactions by the official sector whose main objective is other than development-motivated, or, if development-motivated, whose grant element is below the 25 per cent threshold which would make them eligible to be recorded as ODA. The main classes of transactions included here are official export credits, official sector equity and portfolio investment, and debt reorganization undertaken by the official sector at nonconcessional terms (irrespective of the nature or the identity of the original creditor).). UN agencies are United Nations includes the United Nations Children’s Fund (UNICEF), United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), World Food Programme (WFP), International Fund for Agricultural Development (IFAD), United Nations Development Programme(UNDP), United Nations Population Fund (UNFPA), United Nations Refugee Agency (UNHCR), Joint United Nations Programme on HIV/AIDS (UNAIDS), United Nations Regular Programme for Technical Assistance (UNTA), , United Nations Peacebuilding Fund (UNPBF), International Atomic Energy Agency (IAEA), Wolrd Health Organization (WHO), United Nations Economic Commission for Europe (UNECE), Food and Agriculture Organization of the United Nations (FAO), and International Labour Organization (ILO). Data are in current U.S. dollars.; ; Development Assistance Committee of the Organisation for Economic Co-operation and Development, Geographical Distribution of Financial Flows to Developing Countries, Development Co-operation Report, and International Development Statistics database. Data are available online at: www.oecd.org/dac/stats/idsonline.; Sum;

Abstract

The FAO has developed a monitoring system in 26 food crisis countries to better understand the impacts of various shocks on agricultural livelihoods, food security and local value chains. The Monitoring System consists of primary data collected from households on a periodic basis (more or less every four months, depending on seasonality).The FAO launched this second-round survey consisting of computer-assisted telephone interviews on 26 August 2021 to monitor agricultural livelihoods and food security in Mozambique. Data collection resumed on 6 October 2021, reaching 2206 households. For more information, please go to https://data-in-emergencies.fao.org/pages/monitoring

Geographic coverage

National coverage

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

This second-round survey was representative at the provincial (admin 1) level with a 95 percent confidence level and a 6 percent of margin of error, covering 10 out of the country’s 11 provinces. Only the province of Maputo City, the country’s capital city, was excluded since it is predominantly urban. Data were collected through computer-assisted telephone interviews between 26 August and 6 October 2021. A total of 2206 households were interviewed. Between 197 and 252 households were sampled per province.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Cleaning operations

The datasets have been edited and processed for analysis by the Needs Assessment team at the Office of Emergency and Resilience, FAO, with some dashboards and visualizations produced. For more information, see https://data-in-emergencies.fao.org/pages/countries.

Data appraisal

A link to the questionnaire has been provided in the documentations tab.

Abstract

The FAO has developed a monitoring system in 26 food crisis countries to better understand the impacts of various shocks on agricultural livelihoods, food security and local value chains. The Monitoring System consists of primary data collected from households on a periodic basis (more or less every four months, depending on seasonality). The FAO launched a Round 6 household survey in Bangladesh through the DIEM Monitoring System to monitor agricultural livelihoods and food security. The survey started on 7 September 2022, conducting computer-assisted telephone interviews (CATI) until 8 October 2022. The sixth-round survey in Bangladesh utilized random sampling techniques to reach a sample size of 2,546 households, representative at the division level. The survey targeted all eight divisions of the country: Barisal, Chittagong, Dhaka, Khulna, Mymensingh, Rajshahi, Rangpur, and Sylhet. For more information, please go to https://data-in-emergencies.fao.org/pages/monitoring

Geographic coverage

National coverage

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

For the household survey conducted in Bangladesh for the sixth round, a total of 2,546 households were interviewed. The sampling design involved representative sampling at the division level, targeting all eight divisions of the country: Barisal, Chittagong, Dhaka, Khulna, Mymensingh, Rajshahi, Rangpur, and Sylhet. Additionally, specific hotspots identified in the Bangladesh Delta Plan 2100 were targeted, including Barind and the Drought-Prone Areas, Chars, Chittagong Hill Tracts, Coastal Zone, Cross-Cutting Area, and Haor and the Flash Flood Areas. The sampling procedure, a stratified random sampling approach was employed to ensure representation across divisions and hotspots. Data collection involved computer-assisted telephone interviews conducted between 7 September and 8 October 2022.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

A link to the questionnaire has been provided in the documentation tab.

Cleaning operations

The datasets have been edited and processed for analysis by the Needs Assessment team at the Office of Emergencies and Resilience, FAO, with some dashboards and visualizations produced. For more information, see https://data-in-emergencies.fao.org/pages/countries.

Abstract

The FAO has developed a monitoring system in 26 food crisis countries to better understand the impacts of various shocks on agricultural livelihoods, food security and local value chains. The Monitoring System consists of primary data collected from households on a periodic basis (more or less every four months, depending on seasonality). This third-round survey was representative at national level, covering Liberia’s 15 counties. Data were collected through face-to-face interviews conducted between 9 September and 4 October 2021. The sampling approach was based on random sampling for household questionnaires. For more information, please go to https://data-in-emergencies.fao.org/pages/monitoring

Geographic coverage

National coverage

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

This round 3 survey was representative at national level, covering Liberia's 15 counties. Data were collected through face-to-face interviews conducted between 9 September and 4 October 2021. The sampling approach was based on random sampling for household questionnaires. The overall sampling included 1 800 households, 45 key informants, 45 agro-input vendors and 45 agri-input traders, totalling 1 935 interviews.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

A link to the questionnaire has been provided in the documentations tab.

Cleaning operations

The datasets have been edited and processed for analysis by the Needs Assessment team at the Office of Emergencies and Resilience, FAO, with some dashboards and visualizations produced. For more information, see https://data-in-emergencies.fao.org/pages/countries

Understanding how much inorganic fertilizer (referred to as fertilizer) is applied to different crops at national, regional and global levels is an essential component of fertilizer consumption analysis and demand projection. Good information on fertilizer use by crop (FUBC) is rarely available because it is difficult to collect and time-consuming to process and validate. To fill this gap, a first global FUBC report was published in 1992 for the 1990/1991 period, based on an expert survey conducted jointly by the Food and Agriculture Organization (FAO) of the UN, the International Fertilizer Development Center (IFDC) and the International Fertilizer Association (IFA). Since then, similar expert surveys have been carried out and published every two to four years in the main fertilizer-consuming countries. Since 2008 IFA has led these efforts and, to our knowledge, remains the only globally available data set on FUBC. This dataset includes data (in CSV format) from a survey carried out by IFA to represent the 2017–18 period as well as a collation of all historic FUBC data. Methods Latest fertilizer use by crop survey data During 2020-2022 IFA collected and standardized FUBC data for the 2017-18 period, primarily through a survey of various country correspondents. As of May 2022 this is the most recent survey for FUBC data. Country correspondents were selected based on their knowledge for estimating fertilizer use, average fertilizer application rates and areas of crops for N, P2O5 and K2O for their respective country, and access to any locally available farm data. Country correspondents were asked to complete the questionnaire with the greatest detail possible, or to provide data for the crop breakdown available in their country. The task of aligning the data with FAO crop area statistics was particularly challenging, and sometimes impossible. Even when correspondents were able to mostly follow the provided crop breakdown, crops that are minor in a country’s agriculture were often included in a group of crops or other crops. For example, for most EU countries, the data provided by Fertilizers Europe follow the crop breakdown that is specific to their own annual survey. In this crop breakdown, rice is grouped with rye, triticale and oats, soybean is grouped with sunflower and linseed, and cotton is not identified. Historic fertilizer use by crop survey data For historic FUBC data the following sources had data manually extracted from the original pdf documents into a standardized format: · FUBC report number 1: FAO et al. (1992) · FUBC report number 2: FAO et al. (1994) · FUBC report number 3: FAO et al. (1996) · FUBC report number 4: FAO et al. (1999) · FUBC report number 5: FAO et al. (2002) · FUBC report number 6: Heffer (2009) · FUBC report number 7: Heffer (2013) · FUBC report number 8: Heffer et al. (2017) References FAO, IFA, IFDC. 1992. Fertilizer use by crop 1. Rome, Italy: Food and Agriculture Organization of the United Nations, 82 p. FAO, IFA, IFDC. 1994. Fertilizer use by crop 2. Rome, Italy: Food and Agriculture Organization of the United Nations, 64 p. FAO, IFA, IFDC. 1996. Fertilizer use by crop 3. Rome, Italy: Food and Agriculture Organisation of the United Nations, 74 p. FAO, IFA, IFDC. 1999. Fertilizer use by crop 4. Rome, Italy: Food and Agriculture Organisation of the United Nations, 78 p. FAO, IFA, IFDC, IPI, PPI. 2002. Fertilizer use by crop 5. Rome, Italy.: Food and Agriculture Organization of the United Nations, 67 p. Heffer P. 2009. Assessment of Fertilizer Use by Crop at the Global Level 2006/07 – 2007/08. Paris, France: International Fertilizer Association, 11 p. https://www.ifastat.org/consumption/fertilizer-use-by-crop. Heffer P. 2013. Assessment of Fertilizer Use by Crop at the Global Level. Paris, France, 10 p. https://www.ifastat.org/consumption/fertilizer-use-by-crop. Heffer P, Gruere A, Roberts T. 2017. Assessment of fertiliser use by crop at the global level. Paris, France: International Fertilizer Association, Institute IPN, 19 p. https://www.ifastat.org/plant-nutrition.

The International Standard for country codes and codes for their subdivisions

The purpose of ISO 3166 is to define internationally recognized codes of letters and/or numbers that we can use when we refer to countries and their subdivisions. However, it does not define the names of countries – this information comes from United Nations sources (Terminology Bulletin Country Names and the Country and Region Codes for Statistical Use maintained by the United Nations Statistics Divisions).

Using codes saves time and avoids errors as instead of using a country’s name (which will change depending on the language being used), we can use a combination of letters and/or numbers that are understood all over the world.

This dataset contains ISO 3166-1 alpha-3 codes -a three-letter country codes

We advice that unless absolutely necessary, use the M49 Code list instead of the ISO3

Abstract

The FAO has developed a monitoring system in 26 food crisis countries to better understand the impacts of various shocks on agricultural livelihoods, food security and local value chains. The Monitoring System consists of primary data collected from households on a periodic basis (more or less every four months, depending on seasonality). The FAO Yemen Country Office, with technical support from DIEM conducted the fifth high-frequency monitoring survey, which is focused on quick-changing indicators related to shocks and food security. Data collection took place from 23 Aug – 1 Sep 2023 with 2472 households in all 22 governorates of Yemen via Computer Assisted Telephone Interviews and using Random Digit Dialing. The sample is representative at the national and governorate level. For more information, please go to https://data-in-emergencies.fao.org/pages/monitoring

Geographic coverage

National coverage

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

Data collection took place from 23 Aug – 1 Sep 2023 with 2472 households in all 22 governorates of Yemen via Computer Assisted Telephone Interviews and using Random Digit Dialing. The sample is representative at the national and governorate level with a 95% confidence level and a 10% precision. This high-frequency monitoring survey is a rapid assessment of the food security situation in Yemen aimed at informing early warning systems and decision-makers. It did not collect any data on agriculture, agricultural livelihoods or needs.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

A link to the questionnaire has been provided in the documentations tab.

Cleaning operations

The datasets have been edited and processed for analysis by the DIEM team at the Office of Emergencies and Resilience, FAO, with some dashboards and visualizations produced. For more information, see https://data-in-emergencies.fao.org/pages/countries.

The Food and Agriculture Organization of the United Nations (FAO) has developed a monitoring system in 26 food crisis countries to better understand the impacts of various shocks on agricultural livelihoods, food security and local value chains.
The Monitoring System consists of primary data collected from households on a periodic basis (more or less every four months, depending on seasonality). Data are collected through Computer-Assisted Telephone Interviews (CATI) and in-person surveys where the circumstances allow for field access.
As the system is developed, the information collected and analyzed is being used to guide strategic decisions, to design programmes and to inform analytical processes such as the Integrated Phase Classification (IPC) and the Humanitarian Needs Overview (HNO).
At the core of the system is a standardized household questionnaire administered to around 150,000 households per year across the 26 countries. Standardization permits comparisons across time and space, considerably enhancing the utility of the data for decision makers. At minimum the household data are representative at Admin 1 level (e.g. province, or region) and in frequent cases at Admin 2 level (e.g. district). Core funding for this initiative comes from the United States Agency for International Development (USAID). The initiative also benefits from support from the European Union and FAO’s Special Fund for Emergency and Rehabilitation (SFERA). In each aggregated field, the values indicate the frequencies of the different responses, expressed as a weighted percentage of the total sample. The present datasets represents aggregated data referring to household interviews performed after December 2022. At every new survey data release, after cleaning and validation phases, aggregated data is appended to the present dataset.

For real-time updates, for accessing archived data and for additional survey-specific information, please visit the DIEM Hub: https://data-in-emergencies.fao.org/

View the column descriptions here. Metadata available here. Questionnaires used for data collection available here. Reference administrative boundaries (levels 0, 1 and 2) available here in GIS format.

The Global Land Cover-SHARE (GLC-SHARE) is a new land cover database at the global level created by FAO, Land and Water Division in partnership and with contribution from various partners and institutions.

It provides a set of major thematic land cover layers resulting by a combination of “best available” high resolution national, regional and/or sub-national land cover databases with the weighted average land cover information derived from large-scale available datasets. The database is produced with a resolution of 30 arc second (1km). The approach implemented is based on the utilization of the Land Cover Classification System (LCCS) and SEEA (System of Environmental-Economic Accounting) legend systems for the harmonization of the various global, regional and national land cover legends.

The major benefit of the GLC-SHARE product is its capacity to preserve the existing and available high resolution land cover information at the regional and country level obtained by spatial and multi-temporal source data, integrating them with the best synthesis of global datasets.

Preliminary validation campaign was performed using 1000 random points statistically distributed over each land cover classes.

The database is distributed in the following eleven layers, in raster format (GeoTIFF ), whose pixel values represent the percentage of density coverage in each pixel of the land cover type. The dominant layer, representing the value of the dominant land cover type, is also available along with a legend in LYR ESRI format. Finally, information on each layer's source is retrievable in sources layer, by joining the raster values with an Excel table.

The FGGD extreme poverty map is a global vector datalayer at scale 1:5 000 000. The map depicts the differences among countries with respect to the national population estimated to be living in extreme poverty as of the latest year for which data was available in 2005. Data have been compiled by FAO from data reported in World Bank, WDI Online, as of April 2005.

Data publication: 2007-06-25

Supplemental Information:

This dataset is contained in Module 3 "Socio-economics and nutrition indicators" of Food Insecurity, Poverty and Environment Global GIS Database (FGGD) (FAO, 2007).

Contact points:

Metadata Contact: FAO-Data

Resource Contact: Mirella Salvatore

Resource constraints:

copyright

Online resources:

Share of population living in extreme poverty, by country, varying years

FAO statistics collates and disseminates food and agricultural statistics globally. The division develops methodologies and standards for data collection, and holds regular meetings and workshops to support member countries develop statistical systems. We produce publications, working papers and statistical yearbooks that cover food security, prices, production and trade and agri-environmental statistics.

Abstract

The FAO has developed a monitoring system in 26 food crisis countries to better understand the impacts of various shocks on agricultural livelihoods, food security and local value chains. The Monitoring System consists of primary data collected from households on a periodic basis (more or less every four months, depending on seasonality). This fourth-round survey in Somalia reached 2950 households, approximately 160 agricultural households per region. All the regions of Somalia were targeted for data collection except Banadir. Therefore, 17 out of 18 regions were surveyed. The surveys were conducted from 7 April 2022 to 27 May 2022 through computer-assisted telephone interviews (CATI). The delay in data collection was due to the Eid holidays and political instability. For more information, please go to https://data-in-emergencies.fao.org/pages/monitoring

Geographic coverage

National coverage

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

This fourth-round survey utilized panel data and random digital dialing (RDD) techniques reaching 2950 households, approximately 160 agricultural households per region. Nugaal, Sanaag and Middle Juba regions were not representative at a regional level because there were fewer than 90 households interviewed in each of these regions. All the regions of Somalia were targeted for data collection except Banadir. Therefore, 17 out of 18 regions were surveyed.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Cleaning operations

The datasets have been edited and processed for analysis by the Needs Assessment team at the Office of Emergency and Resilience, FAO, with some dashboards and visualizations produced. For more information, see https://data-in-emergencies.fao.org/pages/countries.

FAO Agriculture and Fair Trade in Pacific Island Countries. This desk study has been prepared by Winnie Fay Bell and comments were kindly provided by the Pacific Regional Organic Task Force in May 2009

View the column descriptions here: https://hqfao.maps.arcgis.com/sharing/rest/content/items/4f2e483703434349b01101a13acd783e/data

The Office of Emergency and Resilience (OER) of the Food and Agriculture Organization (FAO) is piloting a monitoring system to better understand the impacts of COVID-19 and other shocks on food supply, agricultural livelihoods and food security in a number of food crisis countries. This project is supported by the United States Agency for International Development (USAID).

The monitoring system consists of primary data collected from households and key informants (including agricultural inputs vendors, food traders and agriculture extension officers) on a periodic basis (more or less every 3 months). Data are mainly collected through Computer-Assisted Telephone Interviews (CATI). In-person surveys are conducted where the circumstances allow for field access. During each round of the system, more than 40,000 interviews have been completed in more than 20 countries. In order to associate each round of data collection with the dates it was performed, refer to the calendar available here: https://covid-19-data-hqfao.hub.arcgis.com/pages/rounds_calendar

Data are used to guide strategic decisions, to design programmes and to inform analytical processes such as the IPC.

The present dataset contains information derived from household interviews from the following countries: Afghanistan, Colombia, DRC, Liberia, Mali, Niger, Sierra Leone, Somalia, Yemen, Zimbabwe.

This dataset contains a list of the countries affected by the El Niño as at April 21, 2016 as reported jointly by FAO, the Global Food Security Cluster and WFP on 21 April 2016 in the 2015-2016 El Niño: WFP and FAO Overview update. According to the World Bank, El Niño is likely to have a negative impact in more isolated local food markets, and many countries are already facing increased food prices. Food Security Cluster partners have implemented preparedness activities and are responding in countries where the effects of El Niño have materialised, such as Ethiopia, Papua New Guinea, Malawi and throughout Central America. In Southern Africa, many areas have seen the driest October-December period since at least 1981, and some 14 million people in the region are already facing hunger, which adds to fears of a spike in the numbers of the food insecure later this year through 2017.

This database contains the volume of aquatic species caught by country or area, by species items, by FAO major fishing areas, and year, for all commercial, industrial, recreational and subsistence purposes. The harvest from mariculture, aquaculture and other kinds of fish farming is also included.

Abstract

The FAO has developed a monitoring system in 26 food crisis countries to better understand the impacts of various shocks on agricultural livelihoods, food security and local value chains. The Monitoring System consists of primary data collected from households on a periodic basis (more or less every four months, depending on seasonality). The Food and Agriculture Organization of the United Nations (FAO) conducted the fourth round of the Data in Emergencies household survey (DIEM-Monitoring) in Chad between 16 December 2022 and 10 January 2023 to assess agricultural livelihoods and food security. Data was collected through face-to-face surveys in the provinces of Kanem, Lac, Moyen-Chari, Logone Occidental, Moyen-Kebbi Est and Wadi Fira. A total of 5310 households were interviewed. Data collection took place after the rainy season, during the harvest period. For more information, please go to https://data-in-emergencies.fao.org/pages/monitoring

Geographic coverage

National coverage

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey for Phase 4 was developed in partnership with INSEED to achieve representation at the administrative level 2, drawing upon the 2009 General Census of Population and Housing (RGPH 2) and incorporating a 3.5% estimated annual growth rate. Selection criteria, aligned with FAO standards and in collaboration with SISAAP, prioritized vulnerability as identified in the Harmonized Framework outcome analysis, particularly for communities in levels 3 and 4 within Sahelian and Sudanian zones, and factored in the FAO's operational presence. This selection also considered regions significantly affected by the floods in 2022. The methodology employed a two-stage probability sampling, designating villages as the primary sampling units and households as the secondary units.

The methodology stipulated a cluster size of 12, necessitating a minimum of 22 village clusters, resulting in a sample size of 264 per stratum. Consequently, the survey encompassed 5,808 households across 22 departments, ensuring representativeness at the admin 2 level for the designated provinces. For more details on the sampling procedure, consult the methodology document attached in the documentations tab.

Mode of data collection

Face-to-face paper [f2f]

Research instrument

A link to the questionnaire has been provided in the documentations tab.

Cleaning operations

The datasets have been edited and processed for analysis by the Needs Assessment team at the Office of Emergencies and Resilience, FAO, with some dashboards and visualizations produced. For more information, see https://data-in-emergencies.fao.org/pages/countries.

The FGGD coastal and country boundaries of the world is a global datalayer that is available in both vector and raster formats, with a vector scale of 1:5 000 000 and a raster resolution of 5 arc-minutes. It contains coastal and country boundaries from Digital Soil Map of the World, updated to 2005 according to internationally-recognised changes reported by the UN Geographic Information Working Group (DPKO/UNCS).