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  • 300+ Downloads
    Updated September 5, 2019 | Dataset date: Apr 27, 2015-Apr 28, 2015
    This dataset updates: Never
    Geodata of nepal earthquake damages as of 28 April 2015 shared publicly by NGA's Open Data Application.
  • 100+ Downloads
    Updated April 13, 2019 | Dataset date: Apr 8, 2019
    This dataset updates: Never
    This dataset contains the shapefile of health facility damages due to Tropical Cyclone Idai as at 8 April 2019
  • 30+ Downloads
    Updated April 9, 2019 | Dataset date: Oct 10, 2018-Oct 20, 2018
    This dataset updates: As needed
    About the dataset: Hurricane Michael was the third-most intense Atlantic hurricane to make landfall in the United States in terms of pressure. This dataset was collected from Twitter during Hurricane Michael. The dataset was processed and analyzed using the AIDR (http://aidr.qcri.org) platform. Dataset Description: This is a Twitter dataset collected during Hurricane Michael 2018. The data was collected, processed, and analyzed by the AIDR (http://aidr.qcri.org) platform using state-of-the-art machine learning techniques. The data includes the number of injured and dead people, infrastructure damage reports, missing or found people, urgent needs and donation offers for each hour. Due to Twitter TOS, we do not share full tweets content on HDX. Please contact us via HDX or on aidr.qcri@gmail.com to get tweet ids of the dataset along with a tool which can be used to rehydrate tweets from tweet ids.
  • 200+ Downloads
    Updated January 14, 2019 | Dataset date: Jan 1, 2012-Dec 31, 2012
    This dataset updates: Never
    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. 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.
  • 400+ Downloads
    Updated December 31, 2018 | Dataset date: Jan 1, 2013-Dec 31, 2013
    This dataset updates: Never
    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.
  • 200+ Downloads
    Updated December 18, 2018 | Dataset date: Jan 1, 2015-Dec 31, 2015
    This dataset updates: Never
    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.
  • 100+ Downloads
    Updated November 4, 2018 | Dataset date: Sep 20, 2017-Oct 3, 2017
    This dataset updates: Every year
    This resource is comprised of Twitter data collected and processed by the AIDR system during the 2017 hurricane Maria. The data contains information about number of people affected, injured, dead, reports of damages, missing people and so on. Please contact us if you need full dataset with tweets content.
  • 100+ Downloads
    Updated August 16, 2018 | Dataset date: Jul 11, 2012
    This dataset updates: Every year
    Floods damages assessment in Mauritania This table displays floods impacts in Mauritania in 2010.
  • 100+ Downloads
    Updated August 16, 2018 | Dataset date: Aug 9, 2012
    This dataset updates: Every year
    Floods damages assessment in Senegal in 2009. The Excel file represents floods damages in Senegal in 2009.
  • 20+ Downloads
    Updated August 16, 2018 | Dataset date: Apr 18, 2016
    This dataset updates: Never
    Damage data from Ecuador Government in google spreadsheets
  • 800+ Downloads
    Updated August 9, 2018 | Dataset date: Dec 26, 2016
    This dataset updates: Never
    This dataset contains: windspeeds of Typhoon Nina rainfall of Typhoon Nina Priority Index of Typhoon Nina The predicted priority index of Typhoon Nina is produced by a machine learning algorithm that was trained on five past typhoons: Haiyan, Melor, Hagupit and Rammasun and Haima, It uses base line data for the whole country, combined with impact data of windspeeds and rains, and trained on counts by the Philippine government on houses damaged and completely destroyed. The output is a weighted index between partially damaged and completely damaged, where partially damaged is counted as 25% of the completely damaged. This has proven to give he highest accuracy. The absolute number of houses damaged / people affected is insufficiently validated at the moment, and should just be used for further trainng and ground-truthing. Scoring The model has an best r2 score of 0.794933727 and an accuracy of 0.699470899 Data sources: Administrative boundaries (P_Codes) - Philippines Government; Published by GADM and UN OCHA (HDX) Census 2015 (population) - Philippine Statistics Authority; received from UN OCHA (HDX) Avg. wind speed (mph) - University College London Typhoon path - University College London Houses damaged - NDRRMC Rainfall - GPM Poverty - Pantawid pamilyang pilipino program (aggregated) Roof and wall materials New geographical features All the columns with feat_ indicates the importance of that feature, if not present that feature was not used. learn_matrix name of the learning matrix with the 5 typhoons run_name unique run name (pickle files and csv files have this name for this model) typhoon_to_predict name of a new typhoon to predict val_accuracy accuracy based on 10 categories of damage 0% 10% 20% … val_perc_down perc of underpredicted categories val_perc_up perc of overpredicted categories Val_best_score best r2 score Val_stdev_best_score error on best score based on the CV Val_score_test r2 score on the test set (this should be around +- 5% of the previus number to not overfit Val_mean_error_num_houses average error on the number of houses val_median_error_num_houses median val_std_error_num_houses std deviation of the errors (lower is better) Algorithm developed by 510.global the data innovation initiative of the Netherlands Red Cross.
  • 100+ Downloads
    Updated July 30, 2018 | Dataset date: Dec 30, 2013
    This dataset updates: Never
    Household-level dataset for the Shelter Cluster Needs Assessment Baseline (December 2013) following Typhoon Haiyan in the Philippines.
  • 500+ Downloads
    Updated July 16, 2018 | Dataset date: Oct 1, 2015
    This dataset updates: Every year
    Disaster loss and damage data for Colombia at several levels of disaggregation
  • 80+ Downloads
    Updated May 29, 2018 | Dataset date: May 29, 2018
    This dataset updates: Every year
    Health Facility Building Damage Status - data source from DFAT, CARDNO, WHO, NDOH and ICRC
  • 100+ Downloads
    Updated May 13, 2018 | Dataset date: May 10, 2018
    This dataset updates: Every year
    Datasets and map of dam break near solai in Kenya on May 9th 2018.
  • 900+ Downloads
    Updated December 18, 2017 | Dataset date: Jan 27, 2014
    This dataset updates: Never
    Counts of damage and casualties from official data sets
  • 500+ Downloads
    Updated July 16, 2017 | Dataset date: Jan 1, 2016-Oct 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.
  • 300+ Downloads
    Updated June 29, 2017 | Dataset date: Aug 31, 2016
    This dataset updates: Never
    On the 26th of October 2015, a large scale earthquake caused shelter damage throughout much of northern and central Afghanistan. During August 2016, the REACH Initiative (supported by ACTED, AfghanAid and People in Need) conducted a shelter response evaluation in 3 districts of Afghanistan on behalf of the Shelter Cluster. The aim of the assessment was to evaluate shelter interventions and locate possible intervention gaps in order to inform the shelter cluster of Afghanistan of the current shelter context and needs of earthquake affected families. The assessment consisted of three specific areas of investigation: 1. To monitor change in sheltering conditions for families 2. To evaluate the value of various shelter interventions in allowing families to recover and to identify possible gaps 3. To determine recovery limitations and successes relating to vulnerable groups
  • 100+ Downloads
    Updated May 12, 2017 | Dataset date: Oct 27, 2016
    This dataset updates: Every day
    This is an extraction of the WFP global obstacles dataset (https://data.humdata.org/dataset/global-obstacles) for Haiti showing obstacles after Hurricane Matthew. The dataset will refresh by itself as data is edited on our side, so it means it will always contain the most up-to-date data we have on the Logistics Cluster/WFP side, even though the date on hdx is showing an earlier date. Sources of information come mainly from Social Media compiled by local Haitian Bloggers: https://umap.openstreetmap.fr/fr/map/cyclone-matthew-haiti_105242#9/18.8166/-72.5290 The dataset is the one used to produce the Logistics Cluster Access Constraints map: http://www.logcluster.org/sector/hurrimat16
  • 50+ Downloads
    Updated December 27, 2016 | Dataset date: Dec 19, 2016
    This dataset updates: Never
    This map illustrates the percentage of buildings damaged in the city of Aleppo, Syrian Arabic Republic, as determined by satellite imagery analysis. Using satellite imagery acquired 18 September 2016, 01 May 2015, 26 April 2015, 23 May 2014, 23 September 2013, and 21 November 2010, UNOSAT identified a total of 33,521 damaged structures within the extent of this map. These damaged structures are compared with total numbers of buildings found in a pre-conflict satellite image collected in 2009 to determine the percentage of damaged buildings across the city. Based on this analysis and in the map extent, in 19 neighborhoods the number of damaged buildings is more than 40%. The most damaged is Al Aqabeh with 65.61% of buildings damaged and the most significant change since UNOSAT’s 2015 analysis is Khalidiyeh, which increased in percentage damage from 4.20% to 55.80%. Note that this analysis considers only damage in residential areas and excludes industrial areas. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.
  • 900+ Downloads
    Updated November 15, 2016 | Dataset date: Oct 24, 2016
    This dataset updates: Never
    NDRRMC report of October 28th 2016
  • 100+ Downloads
    Updated October 6, 2016 | Dataset date: Oct 5, 2016
    This dataset updates: Every day
    Includes Assessment, two shapefiles: basemaps
  • 600+ Downloads
    Updated October 4, 2016 | Dataset date: Oct 1, 2015
    This dataset updates: Every year
    Disaster loss and damage dataset for Sri Lanka
  • 700+ Downloads
    Updated October 4, 2016 | Dataset date: Oct 1, 2015
    This dataset updates: Every year
    Disaster loss and damage dataset for Senegal
  • 500+ Downloads
    Updated October 4, 2016 | Dataset date: Oct 1, 2015
    This dataset updates: Every year
    Disaster loss and damage dataset for Niger