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  • 40+ Downloads
    Time Period of the Dataset [?]: January 01, 2019-December 31, 2019 ... More
    Modified [?]: 24 October 2023
    Dataset Added on HDX [?]: 24 October 2023
    This dataset updates: Never
    This dataset is part of the data series [?]: WFP - Integrated Context Analysis ICA
    The ICA is a process of consultations supported by mapped-out data that produces a strategic plan describing where different combinations of programme themes are appropriate to achieve goals of reducing food insecurity and climate related shock risk. The ICA combines multi-year food security trends with natural shock risk data to highlight sub-national areas where different programme strategies make sense. Food security trend maps shows areas where safety nets can address regular food insecurity, and others where shocks make recovery more important. Climate-related natural shock risk maps show where DRR, preparedness and early warning efforts can complement food-security objectives. Atop this core foundation, mapped data on subjects including nutrition, gender, livelihoods and resilience can enrich theme-level strategic planning in which all pieces work together. The full group of ICA partners discuss these analytical results to arrive at strategic programmatic directions.
  • 10+ Downloads
    Time Period of the Dataset [?]: January 01, 2016-December 31, 2016 ... More
    Modified [?]: 24 October 2023
    Dataset Added on HDX [?]: 24 October 2023
    This dataset updates: Never
    This dataset is part of the data series [?]: WFP - Integrated Context Analysis ICA
    The ICA is a process of consultations supported by mapped-out data that produces a strategic plan describing where different combinations of programme themes are appropriate to achieve goals of reducing food insecurity and climate related shock risk. The ICA combines multi-year food security trends with natural shock risk data to highlight sub-national areas where different programme strategies make sense. Food security trend maps shows areas where safety nets can address regular food insecurity, and others where shocks make recovery more important. Climate-related natural shock risk maps show where DRR, preparedness and early warning efforts can complement food-security objectives. Atop this core foundation, mapped data on subjects including nutrition, gender, livelihoods and resilience can enrich theme-level strategic planning in which all pieces work together. The full group of ICA partners discuss these analytical results to arrive at strategic programmatic directions.
  • 6100+ Downloads
    Time Period of the Dataset [?]: January 01, 2000-October 01, 2023 ... More
    Modified [?]: 19 September 2023
    Confirmed [?]: 1 October 2023
    Dataset Added on HDX [?]: 15 January 2023
    This dataset updates: Every year
    The WorldRiskIndex is a statistical model that provides an assessment of the latent risk of 193 countries falling victim to a humanitarian disaster caused by extreme natural events and the negative impacts of climate change. Based on peer-reviewed concepts of risk, hazard and vulnerability, it is assumed that disaster risks are not solely shaped by the occurrence, intensity, and duration of extreme natural events, but that social factors, political conditions, and economic structures are equally responsible for whether disasters occur in the context of extreme natural events. Accordingly, both main spheres of disaster risk, exposure and vulnerability, are treated as equals. The WorldRiskIndex was initially developed in 2011 by the United Nations University Institute for Environment and Human Security (UNU-EHS) for Bündnis Entwicklung Hilft as a model with 27 indicators to analytically link and relate the two spheres of disaster risks – exposure to natural hazards such as earthquakes, storms or droughts, and societal capacities to respond to these kinds of events. The methodology of the WorldRiskIndex has been continuously revised and developed by the Institute for International Law of Peace and Armed Conflict (IFHV) since 2018. In 2022, a new, fully revised model of the WorldRiskIndex was published, enabling more accurate analyses by incorporating more than 100 high-quality indicators, new data sources, and more robust statistical methods, thus finally replacing the previously used model.
  • 40+ Downloads
    Time Period of the Dataset [?]: May 05, 2020-May 05, 2020 ... More
    Modified [?]: 15 September 2023
    Dataset Added on HDX [?]: 5 April 2021
    This dataset updates: Never
    This dataset is part of the data series [?]: Global Earthquake Model Foundation - Level 1 Exposure Data
    This data was developed as part of the Modelling Exposure Through Earth Observation Routines (METEOR) project and is a Level 1, or a global-quality exposure data set. Minimal country-specific data was collected. The data is intended for CAT modeling and loss estimation. Repurposing this data for any reason other than assessing risk is not recommended. The data presents the estimated number of buildings, building area, and rebuilding value at a 15-arcsecond grid resolution (approximately 500 meters at the equator). This data set is in point shapefile format where the points represent the centroids of the 15-arcsecond grid. The results were created through a process of spreading the number of buildings to the 15-arcsecond level by a statistical assessment of moderate resolution EO data, which is described in more detail in the dasymetric mapping lineage processing step. The estimated building count at any given area is a result of statistical processes and should not be mistaken as a building count. The structural classes of buildings used for risk assessment are estimated given the building wall, floor, and roof material classes surveyed through 2002 Population and Housing Census - Volume 1. Analytical report. Additionally, the data is provided in Open Exposure Data (OED) import format, as a pair of CSV files. One CSV file contains the location details, and the other is an "account" file that is filled with default information to satisfy OED format requirements. The OED input files are set to use "All perils" (i.e. "AA1"). All required OED account-related fields are populated with "1" by default (such as PortNumber, AccNumber, PolNumber). If you find this data useful please provide feedback via our questionnaire; it should take only a few minutes: https://forms.gle/DQjhE89CRegNKB3X8 Please see the METEOR project page for information about the METEOR Project: http://meteor-project.org/ Please see the METEOR map portal for interactive maps: https://maps.meteor-project.org/ For more information about the Open Exposure Data (OED) standard, please see https://github.com/OasisLMF/OpenDataStandards
  • 30+ Downloads
    Time Period of the Dataset [?]: January 01, 2016-December 31, 2016 ... More
    Modified [?]: 19 July 2023
    Dataset Added on HDX [?]: 19 July 2023
    This dataset updates: As needed
    Flood risk has been assessed based on data obtained from European Commission's Joint Research Centre. In this analysis, the amount of surface for each municipality that is in flood risk areas has been compiled. The hazard classification is determined using Jenks Natural Breaks Classification (or Optimization) system. The information is showed by country, department and municipality of Central America (Nicaragua, Honduras, Guatemala, El Salvador). For more information contact GIS4Tech: info@gis4tech.com. You can also visit the PREDISAN platform https://predisan.gis4tech.com/ca4 for detailed, accurate information.
  • 40+ Downloads
    Time Period of the Dataset [?]: January 01, 2019-December 31, 2019 ... More
    Modified [?]: 18 July 2023
    Dataset Added on HDX [?]: 18 July 2023
    This dataset updates: As needed
    Storm and hurricane risk has been assessed based on a database called IBTrACS obtained from the NOAA (National Centers for Environmental Information). The hazard classification is determined by the frequency of the events. The information is showed by country, department and municipality of Central America (Nicaragua, Honduras, Guatemala, El Salvador) For more information contact GIS4Tech: info@gis4tech.com. You can also visit the PREDISAN platform https://predisan.gis4tech.com/ca4 for detailed, accurate information.
  • Time Period of the Dataset [?]: June 01, 2022-July 31, 2022 ... More
    Modified [?]: 2 June 2023
    Dataset Added on HDX [?]: 13 September 2022
    This data is by request only
    This is the 2022 multisector needs assessment (MSNA) data set - a comprehensive household-level analysis covering all 18 states in Sudan.
  • 100+ Downloads
    Time Period of the Dataset [?]: May 05, 2017-March 28, 2024 ... More
    Modified [?]: 24 May 2023
    Dataset Added on HDX [?]: 12 September 2018
    This dataset updates: Never
    This dataset is part of the data series [?]: INFORM Models
    INFORM Guatemala is a municipal risk index that identifies risks, threats, vulnerabilities and response capacities in the 340 municipalities of Guatemala. The municipal risk index simplifies information about crisis risk and is comprised of 29 indicators representing the three dimensions of risk: hazard and exposure, vulnerability, and lack of coping capacity. The results of the Guatemala INFORM index will be used by the National Coordination System for Disaster Risk Reduction (CONRED) for its analysis of risk of humanitarian crisis and disasters, municipal response capacities and potential humanitarian needs. Government institutions, civil society and international cooperation organizations can also use the results to focus the design and implementation of development programs and projects. The Guatemala INFORM initiative is supported by UNICEF, OCHA and WFP.
  • 90+ Downloads
    Time Period of the Dataset [?]: May 19, 2017-March 28, 2024 ... More
    Modified [?]: 24 May 2023
    Dataset Added on HDX [?]: 13 September 2018
    This dataset updates: Never
    This dataset is part of the data series [?]: INFORM Models
    The sub national INFORM model for Caucasus and Central Asia was initiated by the Regional Inter-Agency Standing Committee (IASC) Task Force for Caucasus and Central Asia and is managed by OCHA. The INFORM model is being used to support coordinated preparedness actions. Partners hope to use the model to improve cooperation between humanitarian and development actors in managing risk and building resilience across the region.
  • 100+ Downloads
    Time Period of the Dataset [?]: March 28, 2018-March 28, 2024 ... More
    Modified [?]: 24 May 2023
    Dataset Added on HDX [?]: 12 September 2018
    This dataset updates: Never
    This dataset is part of the data series [?]: INFORM Models
    The INFOM Honduras tool has been implemented and will be updated by the Permanent Contingency Commission (COPECO). COPECO and other government institutions will jointly implement the INFORM initiative in the context of the National Risk Management System (SINAGER). The national Humanitarian Network, Civil Society Organizations, Academic institutions, and the Association of Municipalities of Honduras (AMHON) will also collaborate with the initiative.
  • 60+ Downloads
    Time Period of the Dataset [?]: May 01, 2023-May 01, 2024 ... More
    Modified [?]: 14 May 2023
    Dataset Added on HDX [?]: 14 May 2023
    This dataset updates: Every year
    The Bangladesh INFORM model provides a solid baseline for risk indexing and monitoring in each of Bangladesh’s 64 districts (2nd administrative tier) and 553 Upazilas and/or Thanas (3rd administrative tier). The index has been developed under coordination of Ministry of Disaster Management and Relief of the Government of Bangladesh and United Nations Resident Coordinator office in Bangladesh, with support from UNDRR.
  • 40+ Downloads
    Time Period of the Dataset [?]: February 01, 2022-February 01, 2027 ... More
    Modified [?]: 23 February 2023
    Dataset Added on HDX [?]: 23 February 2023
    This dataset updates: Never
    This file contains shapefiles depicting the extent of 5-, 25-, and 100- year flood recurrence events. This data was created by the World Bank and should be credited as follows: Plan d’Élaboration propre basée sur les données de la Banque Mondiale: Inondation de Récurrence (5 ans / 25 ans / 100 ans)
  • 2500+ Downloads
    Time Period of the Dataset [?]: January 01, 1902-December 31, 2018 ... More
    Modified [?]: 16 January 2023
    Dataset Added on HDX [?]: 16 January 2023
    This dataset updates: Never
    The Global Drought Hazard project is a collection of spatial raster datasets that provide access to statistical extreme value analyses of the Standardised Precipitation Evapotranspiration Index (6-month SPEI) to identify high risk areas on a global scale. The source data are monthly spatial raster datasets from the Climatology and Climate Services Laboratory's Global SPEI Database for the period from January 1902 to December 2018. Each raster dataset has a spatial resolution of about 0.5 degrees, the values of which we converted into time series for each grid cell. These time series are used to model the number of months above selected SPEI thresholds (e.g. SPEI -1.5 or lower) for a range of return periods (e.g. 100 years) via Poisson-Generalized Pareto Point Process models.
  • 100+ Downloads
    Time Period of the Dataset [?]: June 01, 2022-July 31, 2022 ... More
    Modified [?]: 27 November 2022
    Confirmed [?]: 30 May 2023
    Dataset Added on HDX [?]: 13 September 2022
    This dataset updates: Every year
    This is the 2022 multisector needs analysis data (MSNA) - a comprehensive household-level analysis covering all states in Sudan.
  • 100+ Downloads
    Time Period of the Dataset [?]: November 01, 2021-November 01, 2021 ... More
    Modified [?]: 15 September 2022
    Dataset Added on HDX [?]: 14 September 2022
    This dataset updates: Never
    This file contains the the Sudan admin2 level localities with data of the climate hazards in the country (flood affected by year and overall risk/severity and drought risk/severity.
  • 60+ Downloads
    Time Period of the Dataset [?]: January 01, 1909-June 23, 2022 ... More
    Modified [?]: 12 July 2022
    Dataset Added on HDX [?]: 12 July 2022
    This dataset updates: As needed
    Haiti natural disaster incidents dating from 1909 up to 2022.
  • 200+ Downloads
    Time Period of the Dataset [?]: January 01, 2021-December 31, 2022 ... More
    Modified [?]: 30 June 2022
    Dataset Added on HDX [?]: 14 April 2021
    This dataset updates: Every year
    This dataset is made for planning purposes. It contains the number of people potentially at risk of hazards (floods, disease outbreaks and conflict) in Sudan.
  • 30+ Downloads
    Time Period of the Dataset [?]: October 22, 2021-April 01, 2022 ... More
    Modified [?]: 10 May 2022
    Dataset Added on HDX [?]: 10 May 2022
    This dataset updates: As needed
    This data sets contains a shapefile with the building footprint of Wad Sherifey Refugee Settlement, Kassala, Sudan. Wad Sherifey is a refugee camp located in the East of Sudan along the Mareb River. During the past year refugees fleeing from conflict have arrived and settled in the area, partly within flood prone areas of the Mareb River. Already vulnerable and displaced, now additionally facing the risk of floods. Actors like the Red Cross Red Crescent Climate Centre and MFS manage projects in this region, and OSM data sets like this support the expansion of anticipatory action (acting before a disaster happens www.anticipation-hub.org/) to those most affected by conflict and climate. The area was selected for OSM mapping through a methodology to identify & prioritize high-risk and unmapped areas within a country for OSM mapping (StoryMap: https://arcg.is/1eqOXj) The data was collected through an HOT OSM task (https://tasks.hotosm.org/projects/11685), which was created in collaboration with MFS and led by the Netherland Red Cross’ Missing Maps Team. The task was completed (mapped & validated) in April 2022. The satellite imagery used for the mapping was from late August 2021 and provided by MFS.
  • Time Period of the Dataset [?]: December 22, 2020-December 25, 2020 ... More
    Modified [?]: 14 April 2022
    Dataset Added on HDX [?]: 15 December 2023
    This dataset updates: As needed
    This dataset is part of the data series [?]: ICPAC - Somalia Tropical Cyclones Paths
    This layer shows the movement path of 2020 Tropical Cyclone Gati in Somalia. TC Gati originated from the Bay of Bengal and became the strongest ever documented tropical storm to hit Somalia. It made landfall at Ras Hafun (Northeast of Somalia) with maximum sustained winds of 170Km/hr and was classified as a Category 2 storm. Tropical Cyclone Gati was the strongest storm ever recorded in the northern Indian Ocean and wreaked unimaginable damage on people and property. GATI left a trail of destruction across Bari and Sanaag regions of Somalia, disproportionately affecting coastal communities. Authorities estimated about 180,000 people (30,000 households) to have been affected in Puntland Regional State, with 42,000 people (7,000 households) displaced and at least eight people killed and unknown number injured, with considerable damage reported to infrastructure, livelihoods, and social services (telecommunication, electricity, roads, schools). Resultant flooding burst the sewerage system and increased the risk of diseases among the affected population. The worst hit areas were Baargaal, Foocaar, Garduush, Hurdiya, and Xaafuun, Foocaar, Garduush and Garan Hoose were worst hit villages in the Indian Ocean, Bosaso / Qandala in the Gulf of Aden, and Baarmadowe. 
  • Time Period of the Dataset [?]: December 06, 2019-December 08, 2020 ... More
    Modified [?]: 14 April 2022
    Dataset Added on HDX [?]: 15 December 2023
    This dataset updates: As needed
    This dataset is part of the data series [?]: ICPAC - Somalia Tropical Cyclones Paths
    This layer shows movement path of 2019 Tropical Cyclone Pawan in Somalia. A Tropical Storm initially named 06A formed in the northern Indian Ocean and later developed into a Tropical Cyclone named Pawan after sustaining wind speeds of more than 39mph (48kph) and heavy rain for two days. TC Pawan spread its clouds as far northwest as Oman and Yemen on its way to Somalia. It made landfall in Somalia on 7th December 2019 on the Coastal side of Puntland (Bossaso, Garowe).   The worst hit areas by 2019 TC Pawan included Nugaal Region (Eyl and Dangorayo Districts), Karkaar (Qardho District) and Bari Region (Alula, Iskushuban, and Baargaal Districts) who are under Garowe Somalia Red Crescent Society (SRCS) Branch) and the Coastal villages of Hafun, Iskushuban, Baargaal, Quandala and Alula Districts in Bari Region (under Bosasso SRCS Branch). Other areas affected include the coastal villages in Bari Region including Hafun, Iskushuban, Baargaal, Quandala and Alula districts. Most affected households needed urgent humanitarian assistance as they were already living in dire conditions prior to the crisis. The destruction and flooding caused by TC Pawan increased the vulnerability of communities and heightened the impact of the ever -challenging climatic extremes. The assessment estimated that 35,600 households, representing a population of 213,600 people had been affected. The assessment further estimated the affected population to represented 60-70% of the entire Bari and Nugaal Regions.
  • Time Period of the Dataset [?]: May 19, 2018-May 20, 2018 ... More
    Modified [?]: 14 April 2022
    Dataset Added on HDX [?]: 15 December 2023
    This dataset updates: As needed
    This dataset is part of the data series [?]: ICPAC - Somalia Tropical Cyclones Paths
    This layer shows the movement path of 2018 Tropical Cyclone Sagar. Cyclone Sagar made landfall in north-western Somaliland on 19 May, 2018. It was a very rare cyclone in the Gulf of Aden. The storm moved with wind gusts of up to 120 km/hour that delivered a year’s worth of rain to some areas, that is between 150 and 200mm in some parts of the north. UNICEF was among the first to respond following the powerful tropical cyclone which caused death and widespread destruction in Hargeisa, Somaliland. As per UNICEF reports, some 170,000 were affected by Cyclone Sagar which hit the coast of north-western Somaliland and Djibouti on 18th May 2018 bringing heavy rains leading to flooding and adverse impacts. On 19th May 2018, Cyclone Sagar made landfall in western Somaliland, impacting close to 170,000 people, mainly in Awdal region. The floods in the south and the cyclone in the north destroyed crops, destroyed shelters and social service infrastructure, including water, health, nutrition, and education facilities. The Somaliland authorities estimated 50 people died and seven were still missing. In Somaliland, at least 16 people died in Galbeed and Awdal, where the cyclone made landfall. Three quarters of the livestock were killed along with major damage of water systems and health facilities and 39 schools were damaged or destroyed with a major impact on children.   By the end of 2018, more than 5.7 million people required basic health services, including critical needs in maternal and child health.
  • Time Period of the Dataset [?]: November 07, 2015-November 09, 2015 ... More
    Modified [?]: 14 April 2022
    Dataset Added on HDX [?]: 15 December 2023
    This dataset updates: As needed
    This dataset is part of the data series [?]: ICPAC - Somalia Tropical Cyclones Paths
    This layer shows the movement path for 2015 Tropical Cyclone Megh. Following Tropical Cyclone Chapala, new tropical cyclone Megh originated from the Arabian Sea causing even more rains in parts of Bari region in Puntland and Somaliland. The storm produced a maximum windspeed of 110knots. Areas affected included: Af Kalahay, Alula, Bareda, BiyoCade, Boolimoog, Dhurbo, Fagoora, Geesalay, Murcanyo, Sayn Weyn, Sayn Yar, Toxin and Xaabo. Re-estimated population figures after Tropical Megh, showed 4.9 million people were in need of assistance, 308,700 children under-5 were acutely malnourished, of which 55,800 were severely malnourished and 1.1 million remain in a protracted internal displacement situation.
  • Time Period of the Dataset [?]: November 02, 2015-November 06, 2015 ... More
    Modified [?]: 14 April 2022
    Dataset Added on HDX [?]: 15 December 2023
    This dataset updates: As needed
    This dataset is part of the data series [?]: ICPAC - Somalia Tropical Cyclones Paths
    This layer shows the movement path of 2015 Tropical Cyclone Chapala. On Monday 2 November 2015, Tropical Cyclone Chapala made a landfall in Yemen; however, its effects were also felt across the Gulf of Aden in Somalia where extensive rainfall was experienced in the Northern Bari region in Bosaso district, Puntland. The storm reached maximum wind speed of 130knots.  According to a joint inter-agency rapid assessment more than 500 families (4,000 people) were affected by Tropical Cyclones Chapala and Megh, most affected lived in Gardaful Region, Puntland. No human loss of life was reported, but the rainfall and waves destroyed people’s homes, washed fishing boats and nets, killed livestock (an estimated 3,000 sheep and goats, as well as 200 camels) and caused damage/destruction to public infrastructure including hospitals, roads and schools. It was also estimated that 4,000 people were displaced, with 1,129 people being worst affected, having lost their homes and livelihoods (business, fishing boats, engines and nets), which were swept away by waves. It was reported that there had been extensive damage/destruction to people’s livelihoods, with 80 per cent of villages in Alula and 60 per cent of villages in Af Kalahay Bareda, BiyoCade, Boolimoog, Dhurbo, Fagoora, Geesalay, Murcanyo, Murcanyo, Sayn Weyn, Sayn Yar, Toxiin and Xaabo experiencing loss of livestock and damage to crops and fisheries.  
  • Time Period of the Dataset [?]: November 08, 2010-November 13, 2010 ... More
    Modified [?]: 14 April 2022
    Dataset Added on HDX [?]: 15 December 2023
    This dataset updates: As needed
    This dataset is part of the data series [?]: ICPAC - Somalia Tropical Cyclones Paths
    This layer shows the movement path of Tropical Cyclone 03A. 2013 TC03A formed off the north-east coast of Somalia across the Indian Ocean, moving directly towards the coast of the country in the following days. The storm produced a wind speed of 74 kph (46 mph) and (100-200)mm of rain. It caused heavy rains with flooding and gale force winds in the Somali region of Puntland. The cyclone caused loss of human lives and the destruction of assets including livestock and fishing boats, destroyed numerous settlements, service centers, roads, schools, communication and electrical installations. The most affected areas included, Dangorayo, Bandar Beyla, Garowe and Eyl districts. Other areas affected include the coastal villages in Bari region including Hafun, Iskushuban, Bargal, Qandala and Allula districts.  It was estimated that overall, 142,380 persons were affected by the disasters, with 8,523 households being worst hit and 1,435 households having lost all their livestock. It was also reported that there were approximately 80 deaths mostly of children and the elderly who were most vulnerable to hypothermia and exposure. Makeshift structures for pastoralists were conspicuously absent or just frames, likely destroyed or damaged by high winds and rains. Numerous water sources were flooded, no longer serviceable or contaminated in some areas. There were unconfirmed disease outbreaks and contamination of water sources from decaying animal remains. Thousands of livestock were reported dead as a consequence of icy rain, which was noted in the aerial assessment. FAO estimated 800,000 livestock were in the affected area. Anecdotal evidence suggested a less than 10 per cent survival rate for livestock in the hardest hit areas.
  • Time Period of the Dataset [?]: October 23, 2012-October 26, 2012 ... More
    Modified [?]: 14 April 2022
    Dataset Added on HDX [?]: 15 December 2023
    This dataset updates: As needed
    This dataset is part of the data series [?]: ICPAC - Somalia Tropical Cyclones Paths
    This layer shows the movement path of 2012 TC Murjan. The cyclonic storm, Murjan formed over the south Arabian Sea in association with an active inter tropical convergence zone during last week of October 2012. It was the first cyclone over the north Indian Ocean during this year. Moving west southwestwards, it crossed Somalia's coast between 1700 and 1800 UTC of 25th October near lat. 9.80N and 50.80E. Though the Ocean Heat Content was less over the southwest Arabian Sea (50-80 KJ/cm2) and further less near Somalia's coast (less than 50 KJ/cm2) as well as SST (26-280C), the system could maintain its intensity of cyclonic storm till landfall, basically due to low to moderate vertical wind shear.   After the landfall, due to land interaction, it weakened into a deep depression over coastal Somalia at 1800 UTC of 25th October. It further weakened into a depression over Somalia in the morning of 26th October while moving west-southwest wards.