WFP - World Food Programme
Last updated on July 5, 2020
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Global Food Prices Data
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  • Updated April 17, 2020 | Dataset date: Jan 1, 2006-Dec 31, 2016
    This dataset updates: As needed
    This layer contains information about the recurrence of food insecurity estimated during the Integrated Context Analysis (ICA) run in Mozambique in 2017. Data source: Food Security and Nutrition baseline data (SETSAN) 2006-2009-2013, Mozambique Vulnerability Assessment Committee (VAC) 2012-2016. The main indicator used for the analysis was, for both the assessments used, the Food Consumption Score (FCS), considering households with poor and borderline food insecurity and a threshold set to 20% given that this highlights areas where at least 1 out of 5 households is food insecure. Original dataset title: ICA Mozambique, 2017 - Recurrence of Food Insecurity, 2006-2016
  • 10+ Downloads
    Updated April 17, 2020 | Dataset date: Jan 1, 2017-Dec 31, 2017
    This dataset updates: As needed
    This layer contains information about the final classification resulting from the Integrated Context Analysis (ICA) run in Mozambique in 2017, showing areas of convergence between high recurrence of food insecurity and propensity to natural shocks. It should be noted that, although not being the official categorization included in the Technical Paper, the shapefile contains also the different ICA categorizations resulting from combining the natural shock hazard score with SETSAN and VAC classifications separately. Original dataset title: ICA Mozambique, 2017 - ICA Categories & Areas
  • Updated April 17, 2020 | Dataset date: Jan 1, 2006-Dec 31, 2013
    This dataset updates: As needed
    This layer contains information about the estimates of food insecure population for long-term planning and the additional food insecure people in case of a major shock. Data source: SETSAN 2006-2009-2013. Original dataset title: ICA Mozambique, 2017 - Estimated Numbers of Food Insecure People, 2006-2013
  • 10+ Downloads
    Updated April 17, 2020 | Dataset date: Jan 1, 2001-Dec 31, 2012
    This dataset updates: As needed
    This layer contains information about the land degradation phenomenon observed during the Integrated Context Analysis (ICA) run in Mozambique in 2017. Data source: HQ OSEP GIS Analysis of NASA MODIS, 2001-2012. The main indicator used for the analysis was the percentage of district area that experienced deforestation in the time window examined. Original dataset title: ICA Mozambique, 2017 - Land Degradation, 2001-2012
  • Updated January 27, 2020 | Dataset date: Jan 1, 2013-Dec 31, 2013
    This dataset updates: As needed
    This layer contains information about the malnutrition levels - by first-level administrative unit - observed during the Integrated Context Analysis (ICA) run in Mozambique in 2017. Data source: SETSAN, 2013. The key indicator used for the analysis was the prevalence of stunting in children aged under 5 years, classified according to the classification for assessing severity of malnutrition provided by the World Health Organization (WHO). It should be noted that the shapefile also includes the figures about the prevalence of wasting in children aged under 5 years, indicator which has not been considered in the final version of the Technical Paper. Original dataset title: ICA Mozambique, 2017 - Prevalence of Stunting, 2013
  • 10+ Downloads
    Updated January 27, 2020 | Dataset date: Jan 1, 2002-Dec 31, 2015
    This dataset updates: As needed
    This layer contains information about the cereal production - by first-level administrative area - calculated during the Integrated Context Analysis (ICA) run in Mozambique in 2017. Data source: Ministry of Agriculture and Food Security (MASA), 2002-2015. The indicator used for the analysis is the quantity of millet, rice, sorghum and cassava - expressed in tons. Original dataset title: ICA Mozambique, 2017 - Cereal Production, 2002-2015
  • Updated April 17, 2020 | Dataset date: Mar 26, 2019
    This dataset updates: As needed
    This dataset is based on an extraction of OpenStreetMap. In addition, it contains access constraints status in the column "status" and is edited regularly with information received by partners.
  • 10+ Downloads
    Updated April 17, 2020 | Dataset date: Mar 29, 2019
    This dataset updates: As needed
    This dataset is based on an extraction of OpenStreetMap. In addition, it contains access constraints status in the column "status" and is edited regularly with information received by partners of the Logistics cluster in Mozambique. This dataset is the same as used on the Logistics Cluster Access Constraints map published here: https://logcluster.org/sector/cyclone-idai19
  • 10+ Downloads
    Updated January 27, 2020 | Dataset date: Mar 29, 2019
    This dataset updates: As needed
    Daily extract of Mozambique survey made by WFP to track access constraints
  • 10+ Downloads
    Updated January 27, 2020 | Dataset date: Mar 30, 2019
    This dataset updates: As needed
    This dataset shows the latest populated places data from OpenStreetMap and is constantly updated.
  • 10+ Downloads
    Updated January 27, 2020 | Dataset date: Jun 16, 2017
    This dataset updates: As needed
    This dataset is an extraction of roads from OpenStreetMap data made by WFP following UNSDI-T standards. The data is updated in near-real time from OSM servers and include all latest updates. NOTE: this dataset doesn't include streets and pathways that have been published on a separate dataset (streets and pathways). More documentation on the whole process for extracting OpenStreetMap roads can be found here: http://geonode.wfp.org/documents/6823/download
  • Updated January 27, 2020 | Dataset date: Jun 16, 2017
    This dataset updates: As needed
    This dataset is an extraction of streets and pathways from OpenStreetMap data made by WFP that follow UNSDIT standards. The data is updated in near-real time from OSM servers and include all latest updates. NOTE: this dataset doesn't include main roads that have been published on a separate dataset (main roads). More documentation on the whole process for extracting OpenStreetMap roads can be found here: http://geonode.wfp.org/documents/6823/download
  • 10+ Downloads
    Updated April 17, 2020 | Dataset date: Apr 28, 2019
    This dataset updates: As needed
  • Updated January 27, 2020 | Dataset date: Aug 14, 2017
    This dataset updates: As needed
    This dataset is an extraction of roads from OpenStreetMap data made by WFP following UNSDI-T standards. The data is updated in near-real time from OSM servers and include all latest updates. NOTE: this dataset doesn't include streets and pathways that have been published on a separate dataset (streets and pathways). More documentation on the whole process for extracting OpenStreetMap roads can be found here: http://geonode.wfp.org/documents/6823/download
  • Updated January 27, 2020 | Dataset date: Aug 14, 2017
    This dataset updates: As needed
    This dataset is an extraction of streets and pathways from OpenStreetMap data made by WFP that follow UNSDIT standards. The data is updated in near-real time from OSM servers and include all latest updates. NOTE: this dataset doesn't include main roads that have been published on a separate dataset (main roads). More documentation on the whole process for extracting OpenStreetMap roads can be found here: http://geonode.wfp.org/documents/6823/download
  • Updated January 27, 2020 | Dataset date: Jan 1, 2013-Dec 31, 2013
    This dataset updates: As needed
    This layer contains information about the flood risk - by first-level administrative area - estimated during the Integrated Context Analysis (ICA) run in Mauritania in 2017. The analysis is the result of a joint effort between the Regional Bureau in Dakar (RBD) and the HQ GIS Unit and Programme division. Data sources: UNEP/UNISDR GAR 2013. The main indicators used for the analysis were the percentage of department surface at flood risk and the maximum expected frequency of flood events with a 100-year return period. Cette couche contient informations regard le risque d’inondations – par unité administrative de première niveau – estimé pendant l’Analyse Integrée du Contexte (AIC) executée en Mauritanie en 2017. L’analyse a été executée grâce à la collaboration entre le Bureau Régional de Dakar (RBD), l’unité GIS et la division de Programme au quartier générale du PAM. Source des données : UNEP/UNISDR GAR, 2013. Les indicateurs principaux utilisées pour l’analyse étaient la pourcentage de surface a risque d’inondation et l’attente maximale attendue des inondations. Original dataset title: ICA Mauritania, 2017 - Flood Risk, 2013
  • Updated January 27, 2020 | Dataset date: Jan 1, 1981-Dec 31, 2015
    This dataset updates: As needed
    This layer contains information about the drought risk - by first-level administrative area - estimated during the Integrated Context Analysis (ICA) run in Mauritania in 2017. The analysis is a joint effort between the Regional Bureau in Dakar (RBD), the HQ GIS Unit and Programme division. Data source: HQ VAM Analysis of NDVI data, 1981-2015. The main indicator used for the analysis was the number of poor growing seasons observed in the time window of interest. Cette couche contient informations regard le risque de sècheresse – par unité administrative de première niveau – estimée pendant l’Analyse Integrée du Contexte (AIC) executée en Mauritanie en 2017. L’analyse a été executée grâce à la collaboration entre le Bureau Régional de Dakar (RBD), l’unité GIS et la division de Programme au quartier générale du PAM. Source des données: HQ VAM Analyse des données NDVI, 1981-2015. L'indicateur principale utilisé pour l'analyse était le nombre de saisons qui ont connu un déficit hydrique (mauvaises saisons de croissance). Original dataset title: ICA Mauritania, 2017 - Drought Risk, 1981-2015
  • Updated January 27, 2020 | Dataset date: Jan 1, 2017-Dec 31, 2017
    This dataset updates: As needed
    This layer contains information about the natural shock risk (floods and droughts) - by first-level administrative unit - estimated during the Integrated Context Analysis (ICA) performed in Mauritania in 2017. The analysis was a joint effort between the Regional Bureau in Dakar (RBD), the HQ GIS Unit and Programme division. Data sources: UNEP/UNISDR GAR 2013, HQ VAM Analysis of CHIRPS Rainfall Estimates (RFE) 1981-2015. Cette couche contient informations regard le risque des chocs naturels (inondations et sècheresse) - par unité administrative de première niveau - estimé pendant l’Analyse Integrée du Contexte (AIC) executée en Mauritanie en 2017. L’analyse a été executée grâce à la collaboration entre le Bureau Régional de Dakar (RBD), l’unité GIS et la division de Programme au quartier générale du PAM. Source des données : UNEP/UNISDR GAR 2013, HQ VAM Analyse des données CHIRPS d’estimation des precipitations 1981-2015. Original dataset title: ICA Mauritania, 2017 - Natural Shock Risk
  • Updated January 27, 2020 | Dataset date: Jan 1, 2011-Dec 31, 2015
    This dataset updates: As needed
    This layer contains information about the food security trend analysis - by first-level administrative unit - used for the purposes of the Integrated Context Analysis (ICA) run in Mauritania in 2017. The analysis was a joint effort between the Regional Bureau in Dakar (RBD) and the HQ GIS Unit and Programme division. Data source: Food Security Monitoring System (FSMS), 2011-2015. The main indicator used for the analysis was the Food Consumption Score (FCS), with a threshold - referring to poor and borderline households - set to 20%. Cette couche contient les données d’une analyse de tendance de la sécurité alimentaire – par unité administrative de première niveau – employée pendant l’Analyse Integrée du Contexte (AIC) executée en Mauritanie en 2017. L’analyse a été executée grâce à la collaboration entre le Bureau Régional de Dakar (RBD), l’unité GIS et la division de Programme au quartier générale du PAM. Source des données: Food Security Monitoring System (FSMS), 2011-2015. L’indicateur principale utilisé pour l’analyse était le score de consommation alimentaire faible et limite, avec un seuil fixé à 20%. Original dataset title: ICA Mauritania, 2017 - Recurrence of Food Insecurity, 2011-2015
  • Updated January 27, 2020 | Dataset date: Jan 1, 2017-Dec 31, 2017
    This dataset updates: As needed
    This layer contains information about the final categorization resulting from the Integrated Context Analysis (ICA) performed in Mauritania in 2017, showing the areas of convergence of high levels of food insecurity recurrence and major propensity to natural shocks (floods and droughts). The analysis was a joint effort between the Regional Bureau in Dakar (RBD) and HQ GIS unit and Programme division. Cette couche contient informations regard la classification finale résultant de l'Analyse Integrée de Contexte (AIC) executée en Mauritanie en 2017, montrant les zones de convergence de niveaux elevés de récurrence d'insécurité alimentaire et propension aux chocs naturels (inondations et sècheresse). L’analyse a été executée grâce à la collaboration entre le Bureau Régional de Dakar (RBD), l’unité GIS et la division de Programme au quartier générale du PAM. Original dataset title: ICA Mauritania, 2017 - ICA Categories & Areas
  • Updated January 27, 2020 | Dataset date: Jan 1, 2011-Dec 31, 2015
    This dataset updates: As needed
    This layer contains information about the numbers of food insecure people - by first-level administrative unit - estimated for the purposes of the Integrated Context Analysis (ICA) run in Mauritania in 2017. The analysis was a joint effort between the Regional Bureau in Dakar (RBD) and the HQ GIS Unit and Programme division. Data source: Food Security Monitoring System (FSMS), 2011-2015. The main indicators used for the analysis are the percentage of food insecure population for long-term planning, the most vulnerable food insecure people and the additional population figures in case of a major shock. Cette couche contient informations regard les nombres de personnes exposées à l'insécurité alimentaire - par unité administrative de première niveau - employées pendant l'Analyse Integrée du Contexte (AIC) executée en Mauritanie en 2017. L’analyse a été executée grâce à la collaboration entre le Bureau Régional de Dakar (RBD), l’unité GIS et la division de Programme au quartier générale du PAM. Source des données: Food Security Monitoring System (FSMS), 2011-2015. Les indicateurs principaux utilisés pour l'analyse étaient la pourcentage de population exposée à l'insécurité alimentaire pour la planification à long-terme, la population la plus vulnerable et le nombre de personnes supplémentaires en cas de choc. Original dataset title: ICA Mauritania, 2017 - Estimated Numbers of Food Insecure People, 2011-2015
  • Updated January 27, 2020 | Dataset date: Jan 1, 2001-Dec 31, 2012
    This dataset updates: As needed
    This layer contains information about the land degradation phenomenon - by first-level administrative area - observed for the purposes of the Integrated Context Analysis (ICA) run in Mauritania in 2017. The analysis was a joint effort between the Regional Bureau in Dakar (RBD) and the HQ GIS Unit and Programme division. Data sources: HQ OSEP GIS Analysis of NASA MODIS 2001-2013, WorldClim 1970-2000, FAO data and NASA SRTM Digital Elevation Model. The main indicators used for the analysis were the average ecological changes observed between 2001 and 2012 and the percentage of erosion-prone surface. Cette couche contient les données necessaires pour determiner le niveau de dégradation des terres – par unité administrative de première niveau – observé pendant l’Analyse Integrée du Contexte (AIC) executée en Mauritanie en 2017. L’analyse a été executée grâce à la collaboration entre le Bureau Régional de Dakar (RBD), l’unité GIS et la division de Programme au quartier générale du PAM. Source des données: HQ OSEP GIS Analyse des données NASA MODIS 2001-2013, WorldClim 1970-2000, FAO et NASA SRTM Digital Elevation Model. Les indicateurs principaux utilisés pour l'analyse étaient les changements moyens de couverture du sol observés entre 2001 et 2012 et la pourcentage de surface ayant une propension à l'érosion significative. Original dataset title: ICA Mauritania, 2017 - Land Degradation, 2001-2012
  • Updated January 27, 2020 | Dataset date: Jan 1, 2011-Dec 31, 2015
    This dataset updates: As needed
    This layer contains information about the malnutrition levels - by first-level administrative unit - used for the purposes of the Integrated Context Analysis (ICA) run in Mauritania i 2017. The analysis was a joint effort between the Regional Bureau in Dakar (RBD) and HQ GIS Unit and Programme division. Data source: Food Security Monitoring System (FSMS) & Standardized Monitoring and Assessment of Relief and Transitions (SMART), 2011-2015. The main indicator used for the analysis was the average prevalence of Global Acute Malnutrition (GAM), classified according to the guidelines suggested by the World Health Organization (WHO). Cette couche contient informations regard les niveaux de malnutrition – par unité administrative de première niveau – observés pendant l’Analyse Integrée du Contexte (AIC) executée en Niger entre 2017 et 2018. L’analyse a été executée grâce à la collaboration entre le Bureau Régional de Dakar (RBD), l’unité GIS et la division de Programme au quartier générale du PAM. Source des données: Food Security Monitoring System (FSMS) & Standardized Monitoring and Assessment of Relief and Transitions (SMART), 2011-2015. L’indicateur principale utilisé pour l’analyse était la prévalence moyenne de Malnutrition Aigüe Globale (MAG), classifiée selon les normes et la gamme de valeurs classés de l’OMS 2006. Original dataset title: ICA Mauritania, 2017 - Prevalence of Global Acute Malnutrition, 2011-2015
  • Updated January 27, 2020 | Dataset date: Jan 1, 2016-Dec 31, 2016
    This dataset updates: As needed
    This layer contains information about the projected population figures - by first-level administrative area - estimated for the purposes of the Integrated Context Analysis (ICA) run in Mauritania in 2017. Data source: WFP Mauritania Country Office, 2016. The main indicator used for the analysis was the projected population figures for 2016. Cette couche contient informations regard le nombre de personne projeté - par unité administrative première niveau - utilisé par l'Analyse Integrée du Contexte (AIC) executée en Mauritanie en 2017. Source des données: WFP Bureau du Pays, 2016. L'indicateur principale utilisé pour l'analyse était le la population projetée en 2016 par unité administrative de deuxième niveau. Original dataset title: ICA Mauritania, 2017 - Projected Population, 2016
  • Updated January 27, 2020 | Dataset date: Jan 1, 2013-Dec 31, 2013
    This dataset updates: As needed
    This layer contains information about the most predominant livelihood zones - by first-level administrative area - identified during the Integrated Context Analysis (ICA) run in Mauritania in 2017. The analysis was a joint effort between the Regional Bureau in Dakar (RBD) and the HQ GIS Unit and Programme division. Data source: Fewsnet, 2013. Cette couche contient informations regard les zones de moyens d’existence prédominant – par unité administrative de première niveau – identifiées pendant l’Analyse Integrée du Contexte (AIC) executée en Mauritanie en 2017. L’analyse a été executée grâce à la collaboration entre le Bureau Régional de Dakar (RBD), l’unité GIS et la division de Programme au quartier générale du PAM. Source des données: Fewsnet, 2013. Original dataset title: ICA Mauritania, 2017 - Most Predominant Livelihood Zones, 2013