Food and Agriculture Organization of the United Nations (2017). Food and Agriculture Organization Statistics: Food Security - Indicators from Household Surveys | Survey: Ghana - 1998-1999 | Breakdown: High dependency rate: Less than 70% dependency rat | Gender: Total | Indicator: Dietary energy consumption | Measure: Median, 1999. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. [Data-file]. Dataset-ID: 067-001-070. Dataset: Presents statistics for food security indicators by sociodemographic and socioeconomic characteristics of households. For definitions of each indicator, see the technical documentation. The time-series and cross-sectional data provided here are from the FAOSTAT database of the Food and Agriculture Organization of the United Nations. Statistics include measures related to the food supply; forestry; agricultural production, prices, and investment; and trade and use of resources, such as fertilizers, land, and pesticides. As available, data are provided for approximately 245 countries and 35 regional areas from 1961 through the present. The data are typically supplied by governments to FAO Statistics through national publications and FAO questionnaires. Official data have sometimes been supplemented with data from unofficial sources and from other national or international agencies or organizations. In particular, for the European Union member countries, with the exception of Spain, data obtained from EUROSTAT have been used. Category: Agriculture and Food, International Relations and Trade Source: Food and Agriculture Organization of the United Nations Established in 1945 as a specialized agency of the United Nations, the Food and Agricultural Organization’s mandate is to raise levels of nutrition, improve agricultural productivity, better the lives of rural populations, and contribute to the growth of the world economy. Staff experts in seven FAO departments serve as a knowledge network to collect, analyze, and disseminate data, sharing policy expertise with member countries and implementing projects and programs throughout the world aimed at achieving rural development and hunger alleviation goals. The Statistics Division of the Food and Agricultural Organization collates and disseminates food and agricultural statistics globally. http://www.fao.org/ Subject: Food Supply, Sociodemographic Characteristics, Social Development, Food Security

Food and Agriculture Organization of the United Nations datasets and classifications.

The food and agricultural trade dataset is collected, processed and disseminated by FAO according to the standard International Merchandise Trade Statistics (IMTS) Methodology. The data is mainly provided by UNSD, Eurostat, and other national authorities as needed. This source data is checked for outliers, trade partner data is used for…

Food and Agriculture Organization of the United Nations (2017). Food and Agriculture Organization Statistics: Food Security - Indicators from Household Surveys | Survey: Bangladesh - 2005 | Breakdown: Presence children under 5: Household with no child | Gender: Female-headed household | Indicator: Share of dietary energy consumption from protein | Measure: Number Observations, 2005. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. [Data-file]. Dataset-ID: 067-001-070. Dataset: Presents statistics for food security indicators by sociodemographic and socioeconomic characteristics of households. For definitions of each indicator, see the technical documentation. The time-series and cross-sectional data provided here are from the FAOSTAT database of the Food and Agriculture Organization of the United Nations. Statistics include measures related to the food supply; forestry; agricultural production, prices, and investment; and trade and use of resources, such as fertilizers, land, and pesticides. As available, data are provided for approximately 245 countries and 35 regional areas from 1961 through the present. The data are typically supplied by governments to FAO Statistics through national publications and FAO questionnaires. Official data have sometimes been supplemented with data from unofficial sources and from other national or international agencies or organizations. In particular, for the European Union member countries, with the exception of Spain, data obtained from EUROSTAT have been used. Category: Agriculture and Food, International Relations and Trade Source: Food and Agriculture Organization of the United Nations Established in 1945 as a specialized agency of the United Nations, the Food and Agricultural Organization’s mandate is to raise levels of nutrition, improve agricultural productivity, better the lives of rural populations, and contribute to the growth of the world economy. Staff experts in seven FAO departments serve as a knowledge network to collect, analyze, and disseminate data, sharing policy expertise with member countries and implementing projects and programs throughout the world aimed at achieving rural development and hunger alleviation goals. The Statistics Division of the Food and Agricultural Organization collates and disseminates food and agricultural statistics globally. http://www.fao.org/ Subject: Food Supply, Sociodemographic Characteristics, Social Development, Food Security

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 a fourth round of household survey in Colombia to monitor agricultural livelihoods and food security across the rural population. The survey was conducted between 23 January and 22 February 2023 across ten priority departments: Antioquia, Arauca, Bolívar, Boyacá, Cesar, Chocó, Córdoba, La Guajira, Nariño and Putumayo. The information was collected through computer-assisted telephone interviews. 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 information was collected through computer-assisted telephone interviews applied to a panel of informants corresponding to the third monitoring round conducted in July 2022. The final sample consisted of 2771 rural households surveyed in ten prioritized departments: Antioquia, Arauca, Bolívar, Boyacá, Cesar, Chocó, Córdoba, La Guajira, Nariño and Putumayo.

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.

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 fifth round of the Data in Emergencies Monitoring household survey (DIEM-Monitoring) in the Niger between 9 November and 8 December 2022 to assess agricultural livelihoods and food security. Data were collected in a face-to-face survey in all regions of Niger (Agadez, Diffa, Dosso, Maradi, Tahoua, Tillabéry and Zinder), with the exception of the urban region of Niamey. Between 234 and 281 households were selected in each region, for a total sample of 1762 households. Data was collected during the harvest period (December 2022). 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 were collected in a face-to-face survey in all regions of Niger (Agadez, Diffa, Dosso, Maradi, Tahoua, Tillabéry and Zinder), with the exception of the urban region of Niamey. Between 234 and 281 households were selected in each region, for a total sample of 1762 households.

Mode of data collection

Face-to-face [f2f]

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

Admin2 boundaries (second level admin divisions)

The Administrative Boundaries used by the Data in Emergencies Hub are the result of a collection of international and subnational divisions currently used by FAO country offices for mapping and reporting purposes. With only a few exceptions, they are mostly derived from datasets published on The Humanitarian Data Exchange (OCHA). The dataset consists of national boundaries, first subdivision and second subdivision for Sure! Here's the reformatted list as requested:

Afghanistan, Angola, Bangladesh, Burkina Faso, Burundi, Cambodia, Cameroon, Central African Republic, Chad, Colombia, Comoros, Democratic Republic of the Congo, Ecuador, El Salvador, Federated States of Micronesia, Ghana, Guatemala, Haiti, Honduras, Iraq, Kingdom of Tonga, Kiribati, Kyrgyzstan, Lao People's Democratic Republic, Lebanon, Liberia, Libya, Madagascar, Malawi, Mali, Mauritania, Mozambique, Myanmar, Namibia, Nepal, Niger, Nigeria, Pakistan, Palestine, Philippines, Republic of the Marshall Islands, Saint Lucia, Samoa, Senegal, Sierra Leone, Solomon Islands, Somalia, South Sudan, Sri Lanka, Sudan, Suriname, Syrian Arab Republic, Tajikistan, Thailand, Timor-Leste, Togo, Tuvalu, Uganda, Ukraine, Venezuela, Vietnam, Yemen, and Zimbabwe.

This bar chart displays books by publication date using the aggregation count. The data is filtered where the book publisher is The Food and Agriculture Organization of the United Nations. The data is about books.

Food and Agriculture Organization of the United Nations (2017). Food and Agriculture Organization Statistics: Environment - Pesticide Use | Country: Italy | Item: Pesticides | Element: Active ingredient use in Arable Land & Permanent Crops - tonnes per 1000 Ha, 1990-2010. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. [Data-file]. Dataset-ID: 067-001-051. Dataset: Reports pesticide use on arable and permanent crop area (tonnes/1000 hectare). The time-series and cross-sectional data provided here are from the FAOSTAT database of the Food and Agriculture Organization of the United Nations. Statistics include measures related to the food supply; forestry; agricultural production, prices, and investment; and trade and use of resources, such as fertilizers, land, and pesticides. As available, data are provided for approximately 245 countries and 35 regional areas from 1961 through the present. The data are typically supplied by governments to FAO Statistics through national publications and FAO questionnaires. Official data have sometimes been supplemented with data from unofficial sources and from other national or international agencies or organizations. In particular, for the European Union member countries, with the exception of Spain, data obtained from EUROSTAT have been used. Category: Natural Resources and Environment, Agriculture and Food Source: Food and Agriculture Organization of the United Nations Established in 1945 as a specialized agency of the United Nations, the Food and Agricultural Organization’s mandate is to raise levels of nutrition, improve agricultural productivity, better the lives of rural populations, and contribute to the growth of the world economy. Staff experts in seven FAO departments serve as a knowledge network to collect, analyze, and disseminate data, sharing policy expertise with member countries and implementing projects and programs throughout the world aimed at achieving rural development and hunger alleviation goals. The Statistics Division of the Food and Agricultural Organization collates and disseminates food and agricultural statistics globally. http://www.fao.org/ Subject: Agricultural Production, Crops, Pesticides, Agriculture

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.

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.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 the first round of the system, from June to November 2020, more than 40,000 interviews have been completed in more than 20 countries. Data are used to guide strategic decisions, to design programmes and to inform analytical processes such as the IPC.The present dashboard shows the portion of data referring to Livestock Production from Colombia, Liberia, DRC, Sierra Leone, Niger, Somalia, Zimbabwe and Mali.

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.

This dataset is a raster format GeoTIFF representing the percentage of density in each pixel of the crop land coverage. It is part of the Global Land Cover-SHARE (GLC-SHARE) database at the global level created by FAO, Land and Water Division in partnership and with contribution from various partners and institutions.

The crop land dataset includes the following crop classes: herbaceous crops, woody crops and multiple or layered crops.

Herbaceous Crops: The class is composed of a main layer of cultivated herbaceous plants (graminoids or forbs). It includes herbaceous crops used for hay. All the non-perennial crops that do not last for more than two growing seasons and crops like sugar cane where the upper part of the plant is regularly harvested while the root system can remain for more than one year in the field are included in this class.

Woody Crops: The class is composed of a main layer of permanent crops (trees and/or shrub crops) and includes all types of orchards and plantations (fruit trees, coffee and tea plantation, oil palms, rubber plantation, Christmas trees etc.).

Multiple or Layered crops: This class combine different land cover situations:

• Two layers of different crops (woody + herbaceous): A common case is the presence of one layer of woody crops (trees or shrubs) and another layer of herbaceous crop, such as for wheat fields with olive trees in the Mediterranean area and intense horticulture, oasis or typical coastal African agriculture were herbaceous fields are covered by palm trees, etc.

• Presence of one important layer of natural vegetation (mainly trees) that cover one layer of cultivated crops: A typical example are coffee plantations shadowed by natural trees in the equatorial area of Africa.

Supplemental Information:

GLC-SHARE 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. 01-Artificial Surfaces 02-CropLand 03-Grassland 04-Tree Covered Area 05-Shrubs Covered Area 06-Herbaceous vegetation, aquatic or regularly flooded 07-Mangroves 08-Sparse vegetation 09-BareSoil 10-Snow and glaciers 11-Waterbodies

Contact points:

Metadata Contact: FAO GIS Manager

Resource Contact: Land and Water Officer FAO-NRL

Data lineage:

The land cover database is validated only using the high resolution remote sensing imagery present in Google Earth.

Resource constraints:

Reproduction and dissemination of material contained in GLC-SHARE Beta-Release v1.0 or educational, research, personal or other noncommercial purposes are authorized without any prior written permission from the copyright holders, provided FAO are fully acknowledged. No part of GLC-SHARE Beta-Release v1.0 data may be downloaded, stored in a retrieval system or transmitted by any means for resale or other commercial purposes without written permission of the copyright holders. If any information or resources on this site are attributed to a site or source external to FAO permission to use must be sought with FAO.

The designations employed and the presentation of material in this information product do not imply the expression of any opinion whatsoever on the part of the Food and Agriculture Organization of the United Nations (FAO) concerning the legal or development status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. FAO declines all responsibility for errors or deficiencies in the database or software or in the documentation accompanying it, for program maintenance and upgrading as well as for any damage that may arise from them. FAO also declines any responsibility for updating the data and assumes no responsibility for errors and omissions in the data provided. Users are, however, kindly asked to report any errors or deficiencies in this product to FAO.

Online resources:

Download: GLC-Share - Crop land

Download: GLC-Share - Sources

Download: GLC-Share report

This dataset is about books. It has 1 row and is filtered where the book publisher is Food and Agriculture Organization of the United Nations, Trade and Markets Division. It features 7 columns including author, publication date, language, and book publisher.

Food Security Indicators for Antigua and Barbuda.

Contains data from the FAOSTAT bulk data service.

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.

Agricultural Producer Prices (APP) are prices received by farmers for their produce at the farm gate; i.e. at the point where the commodity leaves the farm. APP do not cover the costs after the farm gate; e.g. transportation cost from the farm gate to the nearest market or first point of sale, warehousing costs, processing costs and market charges (if any) for selling the produce. FAOSTAT gives free access to food and agriculture data for over 245 countries and territories and covers all FAO regional groupings from 1961 to the most recent year available. Annual APP data are provided from 1991 to the previous year for over 160 countries and about 200 commodities, and monthly APP data are provided from January 2010 to December of the previous year for over 60 countries and about 200 commodities. APP are used, along with production data, to estimate value of production for a country, by commodity and in total, as well as Producer Price Indexes, which measure price inflation. APP also enable analysts to analyse price transmission and volatility.

Version 1.1 of a thematic grid of Land Use Systems (LUS) and its attributes with a spatial resolution of 5 arc minutes or 0.083333 decimal degrees. This dataset is developed in the framework of the LADA project (Land degradation Assessment in Drylands) by the Land Tenure and Management Unit of the Food and Agriculture Organization of the United Nations and is copyright of FAO/UNEP GEF. The LUS map implementation is based on a innovative methodology combining more than 10 global datasets. Due to the map generation method, the quality of the map can never be uniform. The overall quality of the map depends heavily on the individual quality of the data for the different countries.