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  • 4100+ Downloads
    Updated July 21, 2019 | Dataset date: Jan 1, 1992-Jul 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.
  • 100+ Downloads
    Updated July 21, 2019 | Dataset date: May 15, 2012-Jul 15, 2018
    This dataset updates: Every week
    This dataset contains Food Prices data for Lao People's Democratic Republic. 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.
  • 2100+ Downloads
    Updated July 19, 2019 | Dataset date: Jan 1, 2011-Dec 31, 2018
    This dataset updates: Every year
    Data used to update country toplines in HDX. Contains data from World Bank's data portal.
  • 50+ Downloads
    Updated July 15, 2019 | Dataset date: Jan 1, 2018-Dec 31, 2018
    This dataset updates: Every three months
    This dataset is compiled from two categories of sources: (a) verified security events submitted to Insecurity Insight by 28 Aid in Danger partner agencies; and (b) publicly reported events identified by Insecurity Insight and published in the Aid in Danger Monthly News Brief. Events are categorised by date, country, type of organisation affected and event category, based on standard definitions.
  • 80+ Downloads
    Updated July 15, 2019 | Dataset date: Jan 1, 2018-Dec 31, 2018
    This dataset updates: Every year
    This dataset contains events in which an aid worker was involved in a road safety accident (RSA). Categorized by country.
  • 50+ Downloads
    Updated July 14, 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.
  • 800+ Downloads
    Updated July 11, 2019 | Dataset date: Jul 11, 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.
  • Updated July 9, 2019 | Dataset date: Jul 3, 2019
    This dataset updates: Every month
    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.
  • 10+ Downloads
    Updated July 9, 2019 | Dataset date: Jul 3, 2019
    This dataset updates: Every month
    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.
  • 20+ Downloads
    Updated July 9, 2019 | Dataset date: Jul 3, 2019
    This dataset updates: Every month
    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.
  • 40+ Downloads
    Updated July 8, 2019 | Dataset date: Jun 19, 2019
    This dataset updates: Every six 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.
  • Updated July 3, 2019 | Dataset date: Jul 3, 2019
    This dataset updates: Every month
    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.
  • Updated June 22, 2019 | Dataset date: Jan 1, 2010-Dec 31, 2018
    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.
  • Updated June 15, 2019 | Dataset date: Nov 16, 2015-Dec 31, 2027
    This dataset updates: Live
    List of aid activities by InterAction members in Laos. Source: http://ngoaidmap.org/location/gn_1655842
  • Updated May 28, 2019 | Dataset date: Jan 1, 2019-Dec 31, 2019
    This dataset updates: Every year
    Age and sex structures: WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. An overview of the data can be found in Tatem et al, and a description of the modelling methods used found in Tatem et al and Pezzulo et al. The 'Global per country 2000-2020' datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World for each year 2000-2020 structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The 'individual countries' datasets represent older efforts to map population age and sex counts for each country separately, using a set of tailored geospatial inputs and differing methods and time periods. The 'whole continent' datasets are mosaics of the individual countries datasets. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076).
  • Updated May 28, 2019 | Dataset date: Jan 1, 2014-Dec 31, 2018
    This dataset updates: Every year
    The health and survival of women and their new-born babies in low income countries is a key public health priority, but basic and consistent subnational data on the number of pregnancies to support decision making has been lacking. WorldPop integrates small area data on the distribution of women of childbearing age, age-specific fertility rates, still births and abortions to map the estimated distributions of pregnancies for each 1x1km grid square across all low and middle income countries. Further details on the methods can be found in Tatem et al and James et al.. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton). 2018. Lao Peoples Democratic Republic 1km Pregnancies. Version 2.0 2015 estimates of numbers of pregnancies per grid square, with national totals adjusted to match national estimates on numbers of pregnancies made by the Guttmacher Institute (http://www.guttmacher.org) DOI: 10.5258/SOTON/WP00615
  • Updated May 28, 2019 | Dataset date: Jan 1, 2014-Dec 31, 2018
    This dataset updates: Every year
    The health and survival of women and their new-born babies in low income countries is a key public health priority, but basic and consistent subnational data on the number of live births to support decision making has been lacking. WorldPop integrates small area data on the distribution of women of childbearing age and age-specific fertility rates to map the estimated distributions of births for each 1x1km grid square across all low and middle income countries. Further details on the methods can be found in Tatem et al. and James et al.. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton). 2018. Lao Peoples Democratic Republic 1km Births. Version 2.0 2015 estimates of numbers of live births per grid square, with national totals adjusted to match UN national estimates on numbers of live births (http://esa.un.org/wpp/). DOI: 10.5258/SOTON/WP00564
  • 30+ Downloads
    Updated May 28, 2019 | Dataset date: Jan 1, 2000-Dec 31, 2020
    This dataset updates: Every year
    WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. An overview of the data can be found in Tatem et al, and a description of the modelling methods used found in Stevens et al. The 'Global per country 2000-2020' datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World for each year 2000-2020. These efforts necessarily involved some shortcuts for consistency. The 'individual countries' datasets represent older efforts to map populations for each country separately, using a set of tailored geospatial inputs and differing methods and time periods. The 'whole continent' datasets are mosaics of the individual countries datasets WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00645
  • 10+ Downloads
    Updated May 15, 2019 | Dataset date: Aug 4, 2017
    This dataset updates: Never
    This map illustrates the satellite-detected water extent in the District of Sanamay, Attapeu Province, in the southwestern part of Lao People's Democratic Republic after the tropical storm SONCA-17. The UNITAR-UNOSAT analysis used a Sentinel-1 satellite image acquired on the 30 July 2017 and detected several areas with potentially standing waters. In the district of Sanamxay ~5,225 ha are likely flooded.This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • This map illustrates the satellite-detected water extent in the Phonhong & Viengkham Districts, Vientiane Province, in the northwestern part of Lao People’s Democratic Republic after the tropical storm SONCA-17. The UNITAR-UNOSAT analysis used a Sentinel-1 satellite image acquired on the 1 August 2017 and detected several areas with potentially standing waters. In the district of Phonhong 2,045 ha are likely flooded and in the district of Viengkham 1,077 ha. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • This UNOSAT LIVE map integrates geo-spatial data in support of response efforts following Tropical Cyclone SONCA-17, after it made landfall in Laos on 26 July 2017. More specifically, it was created with the aim of supporting a food security field assessment carried out by World Food Programme on the ground. Up-to-date, comprehensive satellite image derived flood analyses are displayed, together with photos automatically uploaded from the UN-ASIGN smartphone app. Additional supporting GIS data are also included on the map.
  • This map illustrates the satellite-detected water extent in the district of Khamkeuth in Borikhamxay province, in the central-northern part of Lao People’s Democratic Republic after the tropical storm SONCA-17. The UNITAR-UNOSAT analysis used a Sentinel-1 satellite image acquired on the 11 August 2017 and detected several areas with potentially standing waters. In the district of Khamkeuth ~2,441 ha are likely flooded. Kindly note, the district of Khamkeuth has been partially analyzed due to the image does not cover the full district. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • This map illustrates the satellite-detected water extent in the District of Khongxedone, Salavan Province, in the southwestern part of Lao People’s Democratic Republic after the tropical storm SONCA-17. The UNITAR-UNOSAT analysis used a Sentinel-1 satellite image acquired on the 30 July 2017 and detected several areas with potentially standing waters. In the district of Khongxedone ~2,921 ha are likely flooded mostly affecting the central part of the district along the “Xe Don” river. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • This map illustrates the satellite-detected surface waters extent in Sanamxay district, Attapeu province, as observed from the Radarsat-2 radar image acquired on 24 July 2018. The previous day, the Xe-Namnoy dam collapsed, inducing flash floods along the Vang Ngao river and affecting several villages located 50 km downstream. Within the analysed area 14,692 ha of surface waters were detected after the heavy rains that happened on 22 July and as well the collapse of the dam. Several villages and surrounding agricultural fields seems to be inundated. The villages of Ban Hinlat, Ban Thaseangchan, Ban Mai and Ban Samong-tai seems to be the most affected ones. It is likely that flood waters have been systematically underestimated along highly vegetated areas, along the main riverbanks and within built-up urban areas because of the special characteristics of the used satellite data. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.
  • This map illustrates the evolution of satellite-detected surface waters in Sanamxay district, Attapeu province, as observed from the Radarsat-2 radar image acquired on 24 July 2018 and compared with a Radsarsat-2 image acquired on 10 July 2018. As of 10 July 2018, flooded areas and saturated soils were already visible, due to the heavy rains that happened previously to the collapse of the dam. As well, the reservoir controlled by the dam was full of water. As of 24 July 2018, an additional surface of 5,826 ha of inundated areas were detected, representing an increase of the surface waters of 66%, due to the collapse of the dam. At this date, the reservoir that was controlled by the dam has decreased in its size. Several villages and surrounding agricultural fields seems to be inundated. The villages of Ban Hinlat, Ban Thaseangchan, Ban Mai and Ban Samong-tai seems to be the most affected ones. It is likely that flood waters have been systematically underestimated along highly vegetated areas, along the main riverbanks and within built-up urban areas because of the special characteristics of the used satellite data. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.