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  • Updated 27 January 2020 | Dataset date: January 01, 2013-December 31, 2013
    This dataset updates: As needed
    This layer contains information about the rapid on-set shocks risk (floods and landslides) - by second-level administrative unit - estimated during the Integrated Context Analysis (ICA) run in Niger in 2017. Data source: UNEP/UNISDR GAR 2013. Cette couche contient informations regard le risque de chocs de déclanchement rapide (inondations et glissements de terrain) - par unité administrative de deuxième niveau - estimé pendant l'Analyse Integrée de Contexte (AIC) executé en Tchad en 2017. Source des données: UNEP/UNISDR GAR 2013. Original dataset title: ICA Chad, 2017 - Rapid On-Set Shock Risk, 2013
  • Updated 27 January 2020 | Dataset date: January 01, 2013-December 31, 2013
    This dataset updates: As needed
    This layer contains information about the landslide hazard estimated - by second-level administrative area - during the Integrated Context Analysis (ICA) run in Chad in 2017. Data source: UNEP/UNISDR GAR 2013. The main indicators used for the analysis were the percentage of department surface at landslide hazard, the maximum expected frequency of landslide events. Cette couche contient informations regard le risque des glissements de terraine - par unité administrative de deuxième niveau - estimé pendant l'Analyse Integrée de Contexte (AIC) exécuté en Tchad en 2017. Sources des données: UNEP/UNISDR GAR 2013. Les indicateurs principales utilisés pour l'analyse étaient la pourcentage de surface à risque des glissements de terraine et l'attente maximale attendue des glissements de terraine. Original dataset title: ICA Chad, 2017 - Landslide Risk, 2013
  • 10+ Downloads
    Updated 27 January 2020 | Dataset date: January 01, 2017-December 31, 2017
    This dataset updates: As needed
    This layer contains information about the final categorization resulting from the Integrated Context Analysis (ICA) performed in Chad in 2017, showing the areas of convergence of high levels of food insecurity recurrence and major propensity to natural shocks (floods, droughts and landslides). 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 Tchad en 2017, montrant les zones de convergence de niveaux elevés de récurrence d'insécurité alimentaire et propension aux chocs naturels (inondations, sècheresse et glissements de terrain). 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 Chad, 2017 - ICA Categories & Areas
  • 10+ Downloads
    Updated 27 January 2020 | Dataset date: January 01, 2009-December 31, 2009
    This dataset updates: As needed
    This layer contains information about the landslide risk - by livelihood zone - estimated during the Integrated Context Analysis (ICA) run in Burundi between 2014 and 2015. Data source: UNEP/UNISDR Global Assessment of Risk (GAR), 2009. The key indicators used for the analysis were the maximum expected frequency of landslide events and the percentage of surface affected by landslide risk. Cette couche contient informations regard le risque de glissements de terrain - par zones de moyens d'existence - estimé pendant l'Analyse Integrée de Contexte (AIC) executée au Burundi entre 2014 et 2015. Source des données: UNEP/UNISDR GAR, 2009. Les indicateurs principales utilisés pour l'analyse étaient la fréquence maximale de glissements de terrain et la pourcentage de surface à risque de glissements de terrain. Original dataset title: ICA Burundi, 2014 - Landslide Risk, 2009
  • Updated 27 January 2020 | Dataset date: January 01, 2014-December 31, 2014
    This dataset updates: As needed
    This layer contains information about the rapid on-set shocks risk (floods and landslides) - by livelihood zone - estimated during the Integrated Context Analysis (ICA) run in Burundi between 2014 and 2015. Data source: Stratégie Nationale de Prévention des Risques et de Gestion des Catastrophes – Plan d’Action National 2012-2015, UNEP/UNISDR GAR 2009. Cette couche contient informations regard le risque de chocs de déclanchement rapide (inondations et glissements de terrain) - par zones de moyens d'existence - estimé pendant l'Analyse Integrée de Contexte (AIC) executé au Burundi entre 2014 et 2015. Source des données: Stratégie Nationale de Prévention des Risques et de Gestion des Catastrophes – Plan d’Action National 2012-2015, UNEP/UNISDR GAR 2009. Original dataset title: ICA Burundi, 2014 - Rapid On-Set Shocks Risk
  • 10+ Downloads
    Updated 27 January 2020 | Dataset date: January 01, 2014-December 31, 2014
    This dataset updates: As needed
    This layer contains information about the combined natural shocks risk (flood, landslides and droughts) - by livelihood zone - estimated during the Integrated Context Analysis (ICA) run in Burundi between 2014 and 2015. Data source: Stratégie Nationale de Prévention des Risques et de Gestion des Catastrophes – Plan d’Action National 2012-2015, UNEP/UNISDR GAR 2009, HQ VAM Analysis of NDVI data 1999-2013. Cette couche contient informations regard le risque des chocs naturals combinés (inondations, glissements de terrain et sècheresse) - par zones de moyens d'existence - estimé pendant l'Analyse Integrée de Contexte (AIC) executé au Burundi entre 2014 et 2015. Source des données: Stratégie Nationale de Prévention des Risques et de Gestion des Catastrophes – Plan d’Action National 2012-2015, UNEP/UNISDR GAR 2009, HQ VAM Analyse de NDVI données. Original dataset title: ICA Burundi, 2014 - Natural Shocks Risk
  • Updated 27 January 2020 | Dataset date: January 01, 2012-December 31, 2012
    This dataset updates: As needed
    This layer contains information about the mudflow risk estimated during the Integrated Context Analysis (ICA) run in Armenia in 2016. The results are still valid for the purposes of the ICA update performed in 2017. Data source: Armenia Hydrometeorological Monitoring Service, 2012. The key indicators used for the analysis are the percentage of mudflow affected area and the overall level of mudflow risk Original dataset title: ICA Armenia, 2016 & 2017 - Mudflow Risk, 2012
  • 10+ Downloads
    Updated 27 January 2020 | Dataset date: January 01, 2013-December 31, 2013
    This dataset updates: As needed
    This layer contains information about the landslide risk estimated during the Integrated Context Analysis (ICA) run in Afghanistan in 2016. Data source: UNEP/UNISDR Global Assessment of Risk (GAR), 2013. The key indicators used for the analysis were the percentage of surface area affected by landslide risk and the maximum expected frequency of landslide events. Original dataset title: ICA Afghanistan, 2016 - Landslide Risk, 2013
  • Updated 27 January 2020 | Dataset date: January 01, 2016-December 31, 2016
    This dataset updates: As needed
    This layer contains information about the risk of rapid on-set shocks (floods and landslides) estimated during the Integrated Context Analysis (ICA) run in Afghanistan in 2016. Data source: NATO Global Hazard Model 2009, UNEP/UNISDR GAR 2013. Original dataset title: ICA Afghanistan, 2016 - Rapid On-Set Shocks Risk
  • 10+ Downloads
    Updated 27 January 2020 | Dataset date: January 01, 2016-December 31, 2016
    This dataset updates: As needed
    This layer contains information about the natural shocks risk (floods, droughts and landslides) estimated during the Integrated Context Analysis (ICA) run in Afghanistan in 2016. Data source: NATO GHM 2009, HQ VAM Analysis of CHIRPS RFE 2011-2015, UNEP/UNISDR GAR 2013, Original dataset title: ICA Afghanistan, 2016 - Natural Shocks Risk
  • 20+ Downloads
    Updated 27 January 2020 | Dataset date: January 01, 2013-December 31, 2013
    This dataset updates: As needed
    This layer contains information about the landslide hazard estimated during the Integrated Context Analysis (ICA) run in Afghanistan in 2019. Data source: UNEP/UNISDR Global Assessment of Risk (GAR), 2013. The key indicators used for the analysis were the percentage of surface area affected by landslide risk and the maximum expected frequency of landslide events. Original dataset title: ICA Afghanistan, 2019 - Landslide hazard, 2013
  • 10+ Downloads
    Updated 27 January 2020 | Dataset date: January 01, 2019-December 31, 2019
    This dataset updates: As needed
    This layer contains information about the severity of natural hazards (floods, drought and landslides) estimated during the Integrated Context Analysis (ICA) performed in Afghanistan in 2019. Data sources: GHM 2009, UNEP/UNISDR GAR 2013, HQ VAM Analysis of NDVI, NASA Terra MODIS 2013-2018. Original dataset title: ICA Afghanistan, 2019 - Natural shock hazard
  • 10+ Downloads
    Updated 27 January 2020 | Dataset date: January 01, 2019-December 31, 2019
    This dataset updates: As needed
    This layer contains information about the final classification deriving from the Integrated Context Analysis (ICA) run in Afghanistan in 2019, showing the areas of convergence between recurrence of total food insecurity and propensity to natural shocks (floods, landslides and drought). Original dataset title: ICA Afghanistan, 2019 - ICA Categories & Areas
  • 1900+ Downloads
    Updated 6 December 2019 | Dataset date: January 01, 2018-December 31, 2018
    This dataset updates: Every month
    1) Natural disaster events include avalanches, drought, earthquakes, flooding, heavy rainfall & snowfall, and landslides & mudflows as recorded by OCHA field offices based on assessments in the field. 2) A natural disaster incident is defined as an event that has affected (i.e. impacted) people, who may or may not require humanitarian assistance. 3) The information includes assessment figures from OCHA, ANDMA, IOM, Red Crescent Societies, national NGOs, international NGOs, and ERM. 4) The number of affected people and houses damaged or destroyed are based on the reports received. These figures may change as updates are received.
  • 900+ Downloads
    Updated 10 November 2019 | Dataset date: January 01, 2016-October 29, 2016
    This dataset updates: Every year
    1) Natural disaster events include avalanches,earthquake, flooding, heavy rainfall & snowfall, and landslides & mudflows as recorded by OCHA field offices and IOM Afghanistan Humanitarian Assistance Database (HADB). 2) A natural disaster incident is defined as an event that has affected (i.e. impacted) people, who may or may not require humanitarian assistance. 3) HADB information is used as a main reference and supplemented by OCHA Field Office reports for those incidents where information is not available from the HADB. OCHA information includes assessment figures from OCHA, ANDMA, Red Crescent Societies, national NGOs, international NGOs, and ERM. 4) The number of affected people and houses damaged or destroyed are based on the reports received. These figures may change as updates are received.
  • 1700+ Downloads
    Updated 10 November 2019 | Dataset date: April 25, 2015-April 25, 2015
    This dataset updates: Every year
    Geodata of landslides from earthquake on 25 April, 2015. East of Dharapani, Manang District, Nepal (50 Kilometers Northwest of Epicenter)
  • 1800+ Downloads
    Updated 10 November 2019 | Dataset date: January 01, 2017-December 31, 2017
    This dataset updates: Every year
    1) Natural disaster events include avalanches, earthquakes, flooding, heavy rainfall & snowfall, and landslides & mudflows as recorded by OCHA field offices based on assessments in the field. 2) A natural disaster incident is defined as an event that has affected (i.e. impacted) people, who may or may not require humanitarian assistance. 3) The information includes assessment figures from OCHA, ANDMA, IOM, Red Crescent Societies, national NGOs, international NGOs, and ERM. 4) The number of affected people and houses damaged or destroyed are based on the reports received. These figures may change as updates are received.
  • 300+ Downloads
    Updated 10 November 2019 | Dataset date: January 01, 2014-December 31, 2014
    This dataset updates: Every year
    1) Natural disaster events include avalanches, extreme winter conditions, flooding, heavy rainfall, landslides & mudflows, and extreme weather (sandstorms, hail, wind, etc) as recorded by OCHA field offices and IOM Afghanistan Humanitarian Assistance Database (HADB). 2) A natural disaster incident is defined as an event that has affected (i.e. impacted) Afghans, who may or may not require humanitarian assistance. 3) HADB information is used as a main reference and supplemented by OCHA Field Office reports for those incidents where information is not available from the HADB. OCHA information includes assessment figures from OCHA, ANDMA, Red Crescent Societies, national NGOs, international NGOs, and ERM.
  • 100+ Downloads
    Updated 10 June 2019 | Dataset date: May 25, 2019-May 25, 2019
    This dataset updates: As needed
    Database of Global Landslide Catalog from NASA collected from 1970 - 2019. It was generated using news feeds and is mostly capturing rain-induced landslide events. More information on metadata and original update source here: https://catalog.data.gov/dataset/global-landslide-catalog-export
  • This map illustrates satellite-detected landslide and flood water extent in Peshghor village and surrounding areas in Khenj District, Panjshir Province, Afghanistan as seen on Sentinel-2 satellite imagery, 10 m resolution, collected on 13 July 2018, one day after the disaster happened. The landslides and floodwaters hit villages downstream because of the break-up of the natural banks of the dam. As a result, Peshghor and surrounding villages have been cut off and damages have been reported on structures and buildings. Within the current map extent Saricha primary road is potentially affected by the landslides and the overflow of Panjshir River. Around 198 buildings are located within areas affected by the landslide and 9 within areas affected by the floods. Due to the resolution of the satellite imagery, the extent of landslide and floodwaters may be underestimated and as a consequence, the number of buildings potentially affected. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.
  • 20+ Downloads
    Updated 21 June 2018 | Dataset date: April 13, 2017-April 13, 2017
    This dataset updates: Never
    This map illustrates areas potentially affected by the mudflow, extracted from a Pleiades and GeoEye-1 satellite images acquired on the 10 April 2017 over Mocoa city and its outskirts, in Putumayo Department, Colombia. Inside some neighbourhoods of the city of Mocoa, flood waters and mudflow have receded compared with previous analysis performed by UNOSAT using an image from 4 April 2017. The situation as of 10 April 2017 reveals: 22 km of roads seem potentially affected and about 1,300 buildings are within areas which are still experiencing floods and mud flow. It is likely that flood waters and mudflow could have been systematically under or overestimated along highly vegetated areas and within built-up urban areas. This analysis has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • 50+ Downloads
    Updated 28 April 2017 | Dataset date: April 12, 2017-April 12, 2017
    This dataset updates: Never
    Following a large mudflow that hit the city of Mocoa (Department of Putumayo, Colombia) on 31 March 2017 as a consequence of the heavy rains, the International Charter Space and Major Disasters has been activated upon the request of the National Unit for Disaster Risk Management (UNGRD) / Unidad Nacional para la Gestion del Riesgo de Desastres, IDEAM. In response to this emergency, UNITAR-UNOSAT has carried out satellite based damage analysis to assess (visible) building structural damage caused by mudflows. This map illustrates satellite-detected damaged structures including building damage density in Mocoa city and its surroundings. Analysis has been undertaken by using post satellite imagery acquired by Pleiades and Geoeye-1 satellites on the 7 and 10 April 2017 and pre satellite images acquired by Worldview-2 & 1 satellites on the 21 December 2016 and 26 December 2013. As result of UNOSAT satellite analysis, a total of 1,082 buildings were detected as damaged of which 736 observed as destroyed or washed out by mudflow and 346 observed as severely damaged. Due to the pronounced incident angle and cloud cover of the satellite images, UNITAR-UNOSAT has also used orthophotos collected by Corpoamazonia in order to validate satellite based analysis. Orthophotos and additional baseline data were provided by OSM Humanitarian Mapping Unit and UMAIC (Unidad de Manejo y Analisis de Informacion de Colombia) who is also providing information management coordination support for this event. Kindly note that the number of damaged structures could have been underestimated due to the parameters of the images. This analysis has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • 10+ Downloads
    Updated 28 April 2017 | Dataset date: April 07, 2017-April 07, 2017
    This dataset updates: Never
    This map illustrates satellite-detected water bodies and inundated areas in Mocoa city, Putumayo department in Colombia as seen on Resourcesat-2 satellite imagery collected 04 April 2017. Heavy rainfall in the area caused flooding, landslides and mudflow that affected the city. UNOSAT extracted a water index from the satellite image to determine areas of standing water as well as soils with varying levels of water content (i.e. mud). Within the city of Mocoa and the current map extent, about 18 km of roads are potentially affected. About 2900 buildings are within areas which experienced floods and mudflow. It is likely that flood waters and inundation have been systematically underestimated along highly vegetated areas and within built-up urban areas because of the special characteristics of the satellite data used. This analysis has not yet been validated in the field. Please send ground feedback to UNITAR /UNOSAT.
  • 20+ Downloads
    Updated 27 April 2017 | Dataset date: April 13, 2017-April 13, 2017
    This dataset updates: Never
    Posterior al deslizamiento de tierra que sembró el caos en la ciudad de Mocoa (Departamento de Putumayo, Colombia) el 31 de marzo de 2017 como consecuencia de las fuertes lluvias, el International Charter Space & Major Disasters fue activado bajo la petición de la Unidad Nacional para la Gestión del Riesgo de Desastres, IDEAM. En respuesta a la emergencia, UNITAR-UNOSAT ha llevado a cabo análisis visible de daño en las edificaciones causado por el deslizamiento de tierra, usando imágenes satelitales de alta resolución. Este mapa ilustra edificaciones dañadas detectadas en imágenes satelitales y la densidad de daño asociada en la ciudad de Mocoa y sus alrededores. El análisis ha sido conducido utilizando como imágenes post emergencia las adquiridas por los satélites Pleiades y GeoEye-1 el 7 y el 10 de abril de 2017 y como imágenes pre emergencia las adquiridas por los satélites WorldView-2 y WorldView-1 en las fechas del 21 de diciembre de 2016 y 26 de diciembre de 2013. El resultado del análisis conducido por UNOSAT revela un total de 1,082 edificaciones dañadas, de las cuales 736 aparecen como destruidas en la imagen o arrastradas por el deslizamiento de tierra y 346 presentan daño severo. Debido al acusado ángulo y la cobertura de nubes de las imágenes satelitales, UNITAR-UNOSAT ha utilizado orthophotos colectadas por Corpoamazonia como fuente auxiliar de validación del análisis realizado con las imágenes satélites. Las orthophotos y otros datos secundarios fueron provistos por OpenStreetMap & la Unidad de Mapeo Humanitario y UMAIC (Unidad de Manejo y Análisis de Información de Colombia), quienes también han provisto apoyo en la coordinación y gestión de la información durante esta emergencia. Por favor, note que el número de estructuras dañadas ha podido ser infra-estimado como consecuencia de los parámetros de las imágenes satelitales utilizadas. Este es un análisis preliminar que aún no ha sido validado en el terreno. Por favor, envíen sus comentarios a UNITAR-UNOSAT.