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  • Updated February 26, 2020 | Dataset date: Jan 1, 2013-Dec 31, 2013
    This dataset updates: As needed
    Flood extent in 2013 Original dataset title: Cambodia: Flood Extent in 2013
  • 1100+ Downloads
    Updated February 25, 2020 | Dataset date: Dec 10, 2019
    This dataset updates: Every month
    The INFORM Severity Index is a regularly updated, and easily interpreted model for measuring the severity of humanitarian crisis globally. It is a composite index, which brings together 31 core indicators, organised in three dimensions: impact, conditions of affected people, and complexity. All the indicators are scored on a scale of 1 to 5. These scores are then aggregated into components, the three dimensions (Impact, Conditions, Complexity), and the overall severity category based on the analytical framework. The three dimensions have been weighted according to their contribution to severity: impact of the crisis (20%); conditions of affected people (50%); complexity (30%). The weightings are currently a best estimate and will be refined using expert analysis and statistical methods. Each crisis will fall into 1 of 5 categories based on their score ranging from very low to high. ACAPS – an INFORM technical partner – is responsible for collection, cleaning, analysis and input of data into the model and the production of the final results. Read more on the GCSI methodology here: https://www.acaps.org/methodology/severity
  • 1000+ Downloads
    Updated February 5, 2020 | Dataset date: Jan 1, 2015-Oct 18, 2019
    This dataset updates: Every year
    The overall INFORM risk index identifies countries at risk from humanitarian crises and disasters that could overwhelm national response capacity. It is made up of three dimensions - hazards and exposure, vulnerability and lack of coping capacity. The INFORM initiative began in 2012 as a convergence of interests of UN agencies, donors, NGOs and research institutions to establish a common evidence-base for global humanitarian risk analysis. INFORM identifies the countries at a high risk of humanitarian crisis that are more likely to require international assistance. The INFORM model is based on risk concepts published in scientific literature and envisages three dimensions of risk: Hazards & Exposure, Vulnerability and Lack of Coping Capacity. The INFORM model is split into different levels to provide a quick overview of the underlying factors leading to humanitarian risk. The INFORM index supports a proactive crisis management framework. It will be helpful for an objective allocation of resources for disaster management as well as for coordinated actions focused on anticipating, mitigating, and preparing for humanitarian emergencies.
  • 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 estimated during the Integrated Context Analysis (ICA) run in Zimbabwe in 2015. Data source: UNEP/UNISDR Global Assessment of Risk (GAR), 2013. The key indicator used was the percentage of flood affected areas. Original dataset title: ICA Zimbabwe, 2015 - Flood Risk, 2013
  • Updated January 27, 2020 | Dataset date: Jan 1, 1998-Dec 31, 2013
    This dataset updates: As needed
    This layer contains information about the drought risk estimated during the Integrated Context Analysis (ICA) run in Zimbabwe in 2015. Data source: Water Requirement Satisfaction Index (WRSI) 2000-2013, Normalized Difference Vegetation Index (NDVI) 1998-2012. The key indicators used were the frequency of poor growing seasons and the recurrence of WRSI below the threshold, set to 59% (percentage of district area where poorer crop performance is a result of water stress conditions). Original dataset title: ICA Zimbabwe, 2015 - Drought Risk, 1998-2013
  • Updated January 27, 2020 | Dataset date: Jan 1, 2015-Dec 31, 2015
    This dataset updates: As needed
    This layer contains information about the natural shocks (floods and droughts) risk estimated during the Integrated Context Analysis (ICA) run in Zimbabwe in 2015. Data source: UNEP/UNISDR GAR 2013, WRSI 2000-2013, NDVI 1998-2012. Original dataset title: ICA Zimbabwe, 2015 - Natural Shocks Risk
  • Updated January 27, 2020 | Dataset date: Jan 1, 1998-Dec 31, 2011
    This dataset updates: As needed
    This layer contains information about the drought risk estimated during the Integrated Context Analysis (ICA) run in Tajikistan in 2015. Data source: Committee of Emergency Situations and Civil Defense (CoES CD), 1998-2011. The key indicator used for the analysis is the overall number of drought disasters. Original dataset title: ICA Tajikistan, 2015 - Drought Risk, 1998-2011
  • Updated January 27, 2020 | Dataset date: Jan 1, 1998-Dec 31, 2011
    This dataset updates: As needed
    This layer contains information about the flood risk estimated during the Integrated Context Analysis (ICA) run in Tajikistan in 2015. Data source: Committee of Emergency Situations and Civil Defense (CoES CD), 1998-2011. The key indicator used for the analysis was the overall number of flood disasters. Original dataset title: ICA Tajikistan, 2015 - Flood Risk, 1998-2011
  • Updated January 27, 2020 | Dataset date: Jan 1, 1998-Dec 31, 2011
    This dataset updates: As needed
    This layer contains information about the mudflow risk estimated during the Integrated Context Analysis (ICA) run in Tajikistan in 2015. Data source: Committee of Emergency Situations and Civil Defense (CoES CD), 1998-2011. The key indicator used for the analysis was the overall number of mudflow/flash flood disasters. Original dataset title: ICA Tajikistan, 2015 - Mudflow Risk, 1998-2011
  • Updated January 27, 2020 | Dataset date: Jan 1, 1998-Dec 31, 2011
    This dataset updates: As needed
    This layer contains information about the natural shocks risk (floods, mudflows and droughts) estimated during the Integrated Context Analysis (ICA) run in Tajikistan in 2015. Data source: Committee of Emergency Situations and Civil Defense (CoES CD), 1998-2011. Original dataset title: ICA Tajikistan, 2015 - Natural Shocks Risk, 1998-2011
  • Updated January 27, 2020 | Dataset date: Jan 1, 2018-Dec 31, 2018
    This dataset updates: As needed
    This layer contains information about the natural shock risk (floods and droughts) estimated during the Integrated Context Analysis (ICA) performed in Sudan in 2018. Data sources: UNEP/UNISDR GAR 2013, HQ VAM Analysis of CHIRPS Rainfall Estimates (RFE) 1982-2017. Original dataset title: ICA Sudan, 2018 - Natural Shock Risk
  • Updated January 27, 2020 | Dataset date: Jan 1, 1998-Dec 31, 2011
    This dataset updates: As needed
    This layer contains information about the rapid on-set shocks risk (floods & mudflows) estimated during the Integrated Context Analysis (ICA) run in Tajikistan in 2015. Data source: Committee of Emergency Situations and Civil Defense (CoES CD), 1998-2011. Original dataset title: ICA Tajikistan, 2015 - Rapid On-Set Shocks Risk, 1998-2011
  • Updated January 27, 2020 | Dataset date: Jan 1, 2011-Dec 31, 2011
    This dataset updates: As needed
    This layer contains information about the flood risk - by second-level administrative area - estimated during the Integrated Context Analysis (ICA) run in South Sudan in 2016. Data sources: UNEP/UNISDR GAR 2011. The main indicators used for the analysis were the percentage of district surface at flood risk and the maximum expected frequency of flood events with a 100-year return period. Original dataset title: ICA South Sudan, 2016 - Flood Risk, 2011
  • Updated January 27, 2020 | Dataset date: Jan 1, 1998-Dec 31, 2014
    This dataset updates: As needed
    This layer contains information about the drought risk - by second-level administrative area - estimated during the Integrated Context Analysis (ICA) run in South Sudan in 2016. Data source: HQ VAM Analysis of NDVI data, 1998-2014. The main indicators used for the analysis were the most prelevant number of poor growing seasons and the percentage of surface area affected by one or more poor growing seasons. Original dataset title: ICA South Sudan, 2016 - Drought Risk, 1998-2014
  • 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 second-level administrative area - estimated during the Integrated Context Analysis (ICA) run in Sudan in 2018. Data sources: UNEP/UNISDR, GAR 2013. The main indicators used for the analysis were the percentage of district surface at flood risk and the maximum expected frequency of flood events with a 100-year return period. Original dataset title: ICA Sudan, 2018 - Flood Risk, 2013
  • Updated January 27, 2020 | Dataset date: Jan 1, 2013-Dec 31, 2013
    This dataset updates: As needed
    This layer contains information about the landslide risk estimated during the Integrated Context Analysis (ICA) run in Sierra Leone in 2017. Data sources: UNEP/UNISDR GAR 2013. The main indicators used for the analysis were the maximum expected frequency of landslide events with a 100-year return period and the percentage of district surface at landslide risk. Original dataset title: ICA Sierra Leone, 2017 - Landslide Risk, 2013
  • Updated January 27, 2020 | Dataset date: Jan 1, 1982-Dec 31, 2017
    This dataset updates: As needed
    This layer contains information about the drought risk - by second-level administrative area - estimated during the Integrated Context Analysis (ICA) run in Sudan in 2018. Data source: HQ VAM Analysis of Chirps Rainfall Estimates (RFE), 1982-2017. The main indicators used for the analysis were the number of poor growing seasons observed in the time window of interest and the inter-annual rainfall variability. Original dataset title: ICA Sudan, 2018 - Drought Risk, 1982-2017
  • 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 second-level administrative area - estimated during the Integrated Context Analysis (ICA) run in Senegal 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 deuxième niveau – estimée pendant l’Analyse Integrée du Contexte (AIC) executée en Senegal 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 à risque d’inondation et l’attente maximale attendue des inondations. Original dataset title: ICA Senegal, 2017 - Flood Risk, 2013
  • 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) estimated during the Integrated Context Analysis (ICA) performed in Senegal 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) estimé pendant l’Analyse Integrée du Contexte (AIC) executée en Senegal 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 Senegal, 2017 - Natural Shocks Risk
  • Updated January 27, 2020 | Dataset date: Jan 1, 2016-Dec 31, 2016
    This dataset updates: As needed
    This layer contains information about the natural shock risk (floods and droughts) estimated during the Integrated Context Analysis (ICA) performed in South Sudan in 2016. Data sources: UNEP/UNISDR GAR 2011, HQ VAM Analysis of NDVI data, 1998-2012. Original dataset title: ICA South Sudan, 2016 - Natural Shock Risk
  • Updated January 27, 2020 | Dataset date: Jan 1, 2002-Dec 31, 2012
    This dataset updates: As needed
    This layer contains information about the occurrence of tropical storms above Category 3 - according to the Saffir-Simpson scale and by second-level administrative area - used for the purposes of the Integrated Context Analysis (ICA) run in the Philippines in 2014. Data source: National Oceanic and Atmospheric Administration (NOAA) IBTrACS, 2002-2012. The main indicator used for the analysis was the number of times that a province was hit, in the time frame of interest, by a tropical storm above Category 3. Original dataset title: ICA Philippines, 2014 - Tropical Storm (above Category 3) Occurrence, 2002-2012
  • Updated January 27, 2020 | Dataset date: Jan 1, 2014-Dec 31, 2014
    This dataset updates: As needed
    This layer contains information about the average flood risk - by second-level administrative area - used for the purposes of the Integrated Context Analysis (ICA) run in the Philippines in 2014. Data source: National Household Targeting System and Mines and Geosciences Bureau. The main indicator used for the analysis was the average flood risk by barangay reaggregated by province level. Original dataset title: ICA Philippines, 2014 - Flood Risk, 2014
  • 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 estimated during the Integrated Context Analysis (ICA) run in Sierra Leone in 2017. Data source: UNEP/UNISDR GAR 2013, EMDAT 1996-2015. The main indicators used for the analysis were the percentage of district surface at flood risk and the historical frequency of flood events. Original dataset title: ICA Sierra Leone, 2017 - Flood Risk, 2013
  • Updated January 27, 2020 | Dataset date: Jan 1, 2014-Dec 31, 2014
    This dataset updates: As needed
    This layer contains information about the average landslide risk - by second-level administrative area - used for the purposes of the Integrated Context Analysis (ICA) run in the Philippines in 2014. Data source: National Household Targeting System and Mines and Geosciences Bureau. The main indicator used for the analysis was the average flandslide risk by barangay reaggregated by province level. Original dataset title: ICA Philippines, 2014 - Average Landslide Risk, 2014
  • 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 second-level administrative area - estimated during the Integrated Context Analysis (ICA) run in Senegal 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 Chirps Rainfall Estimates (RFE), 1981-2015. The main indicator used for the analysis was the maximum 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 deuxième niveau – estimée pendant l’Analyse Integrée du Contexte (AIC) executée en Senegal 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 CHIRPS d’estimation des precipitations, 1981-2015. L'indicateur principale utilisé pour l'analyse était le nombre maximale de saisons qui ont connu un déficit hydrique (mauvaises saisons de croissance). Original dataset title: ICA Senegal, 2017 - Drought Risk, 1981-2015