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  • 10+ Downloads
    Updated May 19, 2019 | Dataset date: May 19, 2019
    This dataset updates: Every day
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: building IS NOT NULL Features may have these attributes: name building building:levels building:materials addr:full addr:housenumber addr:street addr:city office This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 40+ Downloads
    Updated May 19, 2019 | Dataset date: May 19, 2019
    This dataset updates: Every day
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: waterway IS NOT NULL OR water IS NOT NULL OR natural IN ('water','wetland','bay') Features may have these attributes: name waterway covered width depth layer blockage tunnel natural water This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 20+ Downloads
    Updated May 19, 2019 | Dataset date: May 19, 2019
    This dataset updates: Every day
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: amenity IS NOT NULL OR man_made IS NOT NULL OR shop IS NOT NULL OR tourism IS NOT NULL Features may have these attributes: name amenity man_made shop tourism opening_hours beds rooms addr:full addr:housenumber addr:street addr:city This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 80+ Downloads
    Updated May 19, 2019 | Dataset date: May 19, 2019
    This dataset updates: Every day
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: highway IS NOT NULL Features may have these attributes: name highway surface smoothness width lanes oneway bridge layer This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 30+ Downloads
    Updated May 19, 2019 | Dataset date: Jan 1, 1999-Dec 31, 2017
    This dataset updates: Every year
    FAO statistics collates and disseminates food and agricultural statistics globally. The division develops methodologies and standards for data collection, and holds regular meetings and workshops to support member countries develop statistical systems. We produce publications, working papers and statistical yearbooks that cover food security, prices, production and trade and agri-environmental statistics.
  • 3600+ Downloads
    Updated May 19, 2019 | Dataset date: Jan 1, 1992-Apr 15, 2019
    This dataset updates: Every week
    This dataset contains Global Food Prices data from the World Food Programme covering foods such as maize, rice, beans, fish, and sugar for 76 countries and some 1,500 markets. It is updated weekly but contains to a large extent monthly data. The data goes back as far as 1992 for a few countries, although many countries started reporting from 2003 or thereafter.
  • 200+ Downloads
    Updated May 19, 2019 | Dataset date: Jan 15, 2003-Feb 15, 2019
    This dataset updates: Every week
    This dataset contains Food Prices data for Malawi. Food prices data comes from the World Food Programme and covers foods such as maize, rice, beans, fish, and sugar for 76 countries and some 1,500 markets. It is updated weekly but contains to a large extent monthly data. The data goes back as far as 1992 for a few countries, although many countries started reporting from 2003 or thereafter.
  • 2600+ Downloads
    Updated May 19, 2019 | Dataset date: May 19, 2019
    This dataset updates: Every day
    FTS publishes data on humanitarian funding flows as reported by donors and recipient organizations. It presents all humanitarian funding to a country and funding that is specifically reported or that can be specifically mapped against funding requirements stated in humanitarian response plans. The data comes from OCHA's Financial Tracking Service, is encoded as utf-8 and the second row of the CSV contains HXL tags.
  • 30+ Downloads
    Updated May 8, 2019 | Dataset date: Apr 30, 2019
    This dataset updates: Every two weeks
    Malawi 2019 Flood Response Who does What Where (4W) data. Data compiled by DoDMA based on ongoing humanitarian response by Government and humanitarian partners.
  • 60+ Downloads
    Updated May 2, 2019 | Dataset date: Jan 1, 2015-Dec 31, 2017
    This dataset updates: Every month
    The World Food Programme (WFP) launched the mobile Vulnerability Analysis and Mapping (mVAM) project in 2013, beginning in DRC and Somalia. mVAM uses mobile technology to track food security trends in real-time, providing high-frequency data that supports humanitarian decision-making. Data collection methods are tailored to the needs of each country that mVAM operates in. This dataset contains data from the mVAM databank covering various indicators (one per resource).
  • 20+ Downloads
    Updated April 26, 2019 | Dataset date: Oct 1, 2018
    This dataset updates: Every three months
    The population of the world, allocated to 1 arcsecond blocks. This refines CIESIN’s Gridded Population of the World project, using machine learning models on high-resolution worldwide Digital Globe satellite imagery. More information. There is also a tiled version of this dataset that may be easier to use if you are interested in many countries.
  • 800+ Downloads
    Updated April 21, 2019 | Dataset date: Jan 1, 2015-Dec 31, 2018
    This dataset updates: Every year
    This dataset contains verified submissions from our partner agencies and publicly-reported data for events in which an aid worker was assaulted or injured. Categorized by country.
  • Updated April 21, 2019 | Dataset date: Jan 1, 1997-Dec 31, 2019
    This dataset updates: Live
    The ACLED project codes reported information on the type, agents, exact location, date, and other characteristics of political violence events, demonstrations and select politically relevant non-violent events. ACLED focuses on tracking a range of violent and non-violent actions by political agents, including governments, rebels, militias, communal groups, political parties, external actors, rioters, protesters and civilians. Data contain specific information on the date, location, group names, interaction type, event type, reported fatalities and contextual notes.
  • 2700+ Downloads
    Updated April 18, 2019 | Dataset date: Oct 22, 2018
    This dataset updates: Every year
    Malawi administrative level 0 (country), 1 (region), 2 (district or city council), and 3 (traditional authority area) boundary polygon and line shapefiles and KMZ files and gazetteer. P-codes are based on the NSO Admin 3 code system. Some humanitarian actors are using an alternative 28-unit administrative level 2 (district) structure instead of the endorsed 32-unit structure. A lookup table is provided. These shapefiles are suitable for database or ArcGIS linkage to the Malawi administrative level 0-3 population statistics tables.
  • 700+ Downloads
    Updated April 18, 2019 | Dataset date: Sep 3, 2018
    This dataset updates: Every year
    Malawi administrative level 0 (country), 1 (region), 2 (district or city council), and 3 (traditional authority area) population statistics and gazetteer Some humanitarian actors are using an alternative 28-unit administrative level 2 (district) structure instead of the endorsed 32-unit structure. This dataset provides resources for both the 28-district and 32-district administrative level 2 (district) structures and the level 3 (traditional authority area) resources have P-codes for both. A lookup table is provided. These CSV tables are suitable for database or ArcGIS linkage to the Malawi administrative level 0-3 boundaries shapefiles.
  • Updated April 17, 2019 | Dataset date: Nov 16, 2015-Dec 31, 2027
    This dataset updates: Live
    List of aid activities by InterAction members in Malawi. Source: http://ngoaidmap.org/location/gn_927384
  • 1700+ Downloads
    Updated April 16, 2019 | Dataset date: Jan 1, 2017-Feb 28, 2019
    This dataset updates: Every month
    This dataset contains agency- and publicly-reported data for events in which an aid worker was killed, kidnapped, or arrested. Categorized by country.
  • 400+ Downloads
    Updated April 16, 2019 | Dataset date: Jan 24, 2019
    This dataset updates: Never
    Facebook has produced a model to help map global medium voltage (MV) grid infrastructure, i.e. the distribution lines which connect high-voltage transmission infrastructure to consumer-serving low-voltage distribution. The data found here are model outputs for six select African countries: Malawi, Nigeria, Uganda, DRC, Cote D’Ivoire, and Zambia. The grid maps are produced using a new methodology that employs various publicly-available datasets (night time satellite imagery, roads, political boundaries, etc) to predict the location of existing MV grid infrastructure. The model documentation and code are also available , so data scientists and planners globally can replicate the model to expand model coverage to other countries where this data is not already available. You can find the model code and documentation here: https://github.com/facebookresearch/many-to-many-dijkstra Note: current model accuracy is approximately 70% when compared to existing ground-truthed data. Accuracy can be further improved by integrating other locally-relevant information into the model and running it again. Resolution: geotiff is provided at Bing Tile Level 20
  • Updated April 5, 2019 | Dataset date: Jan 1, 2019-Jan 1, 2020
    This dataset updates: Live
    Live list of active aid activities for Malawi shared via the International Aid Transparency Initiative (IATI). Includes both humanitarian and development activities. More information on each activity (including financial data) is available from http://www.d-portal.org
  • 50+ Downloads
    Updated April 4, 2019 | Dataset date: Mar 26, 2019-Mar 31, 2019
    This dataset updates: Every month
    Malawi has experienced floods and sustained heavy rains caused by the tropical cyclone Idai weather system. IOM, in close coordination with the Government of Malawi through the Department of Disaster Management Affairs (DoDMA), conducted multi-sectoral location assessments in Chikwawa, Nsanje, Phalombe, Zomba districts. The dataset contains number of IDPs, households and their needs at sub-national level.
  • 200+ Downloads
    Updated March 24, 2019 | Dataset date: Oct 11, 2018
    This dataset updates: Never
    African Economic Outlook, 1993-2050
  • 200+ Downloads
    Updated March 24, 2019 | Dataset date: Feb 5, 2018
    This dataset updates: Never
    The AFDB Statistical Data Portal has been developed in response to the increasing demand for statistical data and indicators relating to African Countries. The Portal provides multiple customized tools to gather indicators, analyze them, and export them into multiple formats. With the Data Portal, you can visualize Socio-Economic indicators over a period of time, gain access to presentation-ready graphics and perform comprehensive analysis on a Country and Regional level
  • 200+ Downloads
    Updated March 15, 2019 | Dataset date: Mar 13, 2019
    This dataset updates: Never
    For the floods in Southern Malawi of March 2019, we have combined flood extent maps (Sentinel) with HRSL settlement/population grid. This results in a calculation of # of affected buildings/people per district. The results is shared through maps and in a shapefile. 1. Data sources Sentinel 1 Imagery from 7th of March 2017 Sentinel 2 Imagery from 10th/12th/14th of March 2017 HRSL population data Facebook Connectivity Lab and Center for International Earth Science Information Network - CIESIN - Columbia University. 2016. High Resolution Settlement Layer (HRSL). Source imagery for HRSL © 2016 DigitalGlobe. Accessed 9 March 2019. 2. Good to know The flood extent for Nsanje district was separately added on March 14th, to the existing flood extent for the main area from March 12th. 3. Methodology A. Flood Extent Based on SAR The following steps were used to detect flood extent(water/no water). In SNAP tool the raw data downloaded from sci-hub Copernicus was processed to calibrate image for atmospheric correction, spike filter and terrain correction(This is mainly for Sentinel 1 data). Finally defining water no water based on a threshold applied on the corrected image. Defining a threshold is always a challenge in SAR image analysis for flood detection, we collected data from the field to define this threshold. For Sentinel 2 as a first step cloud filter was calculated by applying a combined threshold on Band 2 and Band 10. The cloud mask shown in the figure below didn’t capture shadows of clouds, these were miss interpreted by the flood algorithm as water/flood. To correct this areas with more cloud cover were clipped out with a polygon. To define water no water based on sentinel data we used NDWI index, the treshold is adjusted based on data collected from the field Validation points were collected by Field team tested different values and check if the threshold identified fits with observation. The complete methodology how to detect flooding based on Sentinel 1 data and SNAP toolbox is documented in ESA website. B. Affected People To calculate number of affected people per each admin level, flood extent map is combined with HRSL population data. This is done in two steps: First, in step 1, we calculate a raster, which multiplies the population grid with the flood grid, such that we are left with only "population in flooded area". This is done using raster calculator where population density raster was multiplied by flood extent raster, which has a value of 0 for no flood and 1 for flood areas. Note that the flood extent grid was first resampled to match it to the population grid. This whole exercise is repeated for settlement/buildings instead of population. Step 2: We apply zonal statistics per TA to calculate total number of buildings/people affected in each admin level. For each Admin level2 estimated number of affected people and affected houses are plotted in the map. The zonal statistics data used for plotting can be found in the shape file.
  • 500+ Downloads
    Updated March 11, 2019 | Dataset date: Jan 1, 2017-Dec 31, 2017
    This dataset updates: Every year
    Attacks on educational staff and facilities in 2017. This dataset contains agency- and publicly-reported data for events in which affected the provision of education. Categorized by country.
  • 100+ Downloads
    Updated February 27, 2019 | Dataset date: Nov 21, 2018
    This dataset updates: Never
    Shapefile contains admin 1 boundaries for countries in East and southern Africa