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  • 1000+ Downloads
    Updated July 3, 2019 | Dataset date: Jan 1, 2017-Dec 31, 2018
    This dataset updates: Every year
    The Safeguarding Health in Conflict Coalition (SHCC) is made up of 40 health provider organizations, humanitarian groups, human rights organizations, NGOs, and academic programs to take action to protect health workers and end attacks against them. This is our sixth report documenting attacks on health care in conflict countries around the world. This page is managed by SHCC member Insecurity Insight.
  • 30+ Downloads
    Updated June 28, 2019 | Dataset date: Dec 11, 2017
    This dataset updates: Live
    This map illustrates satellite-detected damage to infrastructure and roads in a portion of the city of Deir Ez Zor, Syrian Arab Republic and is derived from a full UNOSAT analysis of damage to Deir Ez Zor in 2017. Using satellite imagery acquired 9 November 2017, UNITAR - UNOSAT identified 6 destroyed bridges, 54 damaged road segments and 93 visible impact craters affecting roads. Approximately 169 structures corresponding to educational facilities, and 21 structures likely related to health facilities are also affected. UNOSAT analysis shows that there are 3 destroyed electricity towers south of the city. Note that sources of infrastructure data include various open source datasets which are likely incomplete, as well as visual review of satellite imagery by UNOSAT for certain features like towers. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.
  • 40+ Downloads
    Updated June 28, 2019 | Dataset date: Dec 5, 2017
    This dataset updates: Live
    This map illustrates satellite-detected damage to infrastructure and roads in the city of Ar Raqqa, Syrian Arab Republic and is derived from a full UNOSAT analysis of damage to Ar Raqqa in 2017. Using satellite imagery acquired 21 October 2017, UNITAR - UNOSAT identified 5 destroyed bridges, 74 damaged road segments and 94 visible impact craters affecting roads. Approximately 159 structures corresponding to educational facilities, and 26 structures likely related to health facilities are also affected. UNOSAT analysis shows that 8 water towers are completely destroyed and there is damage to one electric substation and a sewage treatment facility. Note that sources of infrastructure data include various open source datasets which are likely incomplete, as well as visual review of satellite imagery by UNOSAT for certain features like water towers. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.
  • 100+ Downloads
    Updated June 28, 2019 | Dataset date: Jan 31, 2019
    This dataset updates: As needed
    On 26 December 2018, exceptionally heavy rainfall caused severe flash flooding in Idleb and Aleppo governorates in north-west Syria. This area has a high proportion of displaced people and concentration of camps and sites, making it a region with a notably large vulnerable population. Hundreds of tents were reportedly swept away and concrete houses in camps collapsed. As a result of the flooding, thousands of people have been impacted
  • 200+ Downloads
    Updated June 28, 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, educator or health worker was killed, kidnapped, or arrested. Categorized by country.
  • 700+ Downloads
    Updated June 27, 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.
  • 50+ Downloads
    Updated June 26, 2019 | Dataset date: Jan 1, 2018-Dec 31, 2018
    This dataset updates: As needed
    This dataset covers events in which a health facility was damaged or destroyed by explosive weapon use in 2018. It will be regularly updated with additional details on the impact of explosive weapon use on health facilities. It is a sub-dataset of '2018 SHCC Attacks Data'.
  • 14000+ Downloads
    Updated June 19, 2019 | Dataset date: Jun 1, 2017
    This dataset updates: Every six months
    Syria Administrative boundaries for levels 0 - 4, with Arabic Names, English Names, and p-codes. Geodatabase maintains Arabic names better than shapefile Note that Admin 4 is the populated places layer. Admin Level 1= Governorate = Mohafaza Admin Level 2 = District = Mantika Admin Level 3 = Sub-district= Nahya Populated places = City or Village
  • 90+ Downloads
    Updated June 18, 2019 | Dataset date: Jan 1, 2016-Dec 31, 2018
    This dataset updates: As needed
    This is a compilation of datasets compiled from scraping the monthly fact sheets produced by the Whole of Syria Education Cluster.
  • 10+ Downloads
    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, 2018-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. Syrian Arab Republic 1km Pregnancies. Version 1.0 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/WP00631
  • Updated May 28, 2019 | Dataset date: Jan 1, 2018-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. Syrian Arab Republic 1km Births. Version 1.0 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/WP00580
  • 100+ 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
  • 20+ Downloads
    Updated May 15, 2019 | Dataset date: Sep 6, 2016
    This dataset updates: Never
    This map illustrates shelters in the area of the Rukban border crossing on the Syrian-Jordanian border. Using a satellite image collected by the Pleiades satellite on 02 September 2016, UNOSAT located 8,295 probable shelters along the Jordanian side of the border, 25 kilometers southwest of the Al Waleed crossing. This is an 26 percent increase in apparent shelters visible compared to the previous UNOSAT analysis done using an image collected 25 July 2016. Due to the small size and the irregularity of the shelters it is likely that some shelters may have been missed in this analysis, or some shelters were included erroneously. Due to the scale of this map and the lack of suitable border information at this scale, the border in this map has been excluded. This map is intended for field support and local authorities should be consulted for boundary information. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • 50+ Downloads
    Updated May 15, 2019 | Dataset date: Aug 22, 2016
    This dataset updates: Never
    This map illustrates the refugee settlement in Al Azraq, Jordan as seen by the WorldView-3 satellite on 30 June 2016. Analysis by UNITAR-UNOSAT of the satellite image indicates a total of 14,609 visible structures. This includes 4,389 infrastructure and support buildings as well as 10,220 shelters. Preparations are continuing so as to accommodate additional incoming refugees. The previous analysis done by UNOSAT using an image from 5 October 2015 detected a total of 14,227 infrastructure, support buildings and shelters. This is an increase of approximately 2.7%. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.
  • 50+ Downloads
    Updated May 15, 2019 | Dataset date: Aug 17, 2016
    This dataset updates: Never
    This map illustrates satellite-detected shelters and other buildings at the Al Zaatari refugee camp in Mafraq Governorate, Jordan. As of 30 June 2016 a total of 25,815 shelters were detected as well as 1,879 infrastructure and support buildings within the 534 hectares of the camp. Between 12 October 2015 and 30 June 2016 a total of 2,568 shelters were constructed, with even more removed, indicating an approximate 4.26% decrease in the number of shelters between 12 October 2015 and 30 June 2016. This is a preliminary analysis and has not yet been validated in the field; structure locations subject to a spatial error margin of +/- three meters. Shelters grouped under plastic sheeting were estimated by average household size and may be a source of error. Please send ground feedback to UNITAR-UNOSAT.
  • 100+ Downloads
    Updated May 15, 2019 | Dataset date: Dec 16, 2016
    This dataset updates: Never
    This map illustrates satellite-detected damage density in the city of Aleppo, Syrian Arab Republic. Satellite imagery acquired 18 September 2016, 01 May 2015, 26 April 2015, 23 May 2014, 23 September 2013, and 21 November 2010 was analyzed. UNITAR - UNOSAT identified a total of 35,722 affected structures, of which 4,773 were destroyed, 14,680 severely damaged, and 16,269 moderately damaged, as of 18 September 2016. This represents an increase of approximately 154.5% in total damage since the previous UNITAR-UNOSAT analysis done using images from 1 May 2015 and 26 April 2015. This analysis was done as part of the REACH initiative for the U.S. Office of Foreign Disaster Assistance. It is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.
  • 30+ Downloads
    Updated May 15, 2019 | Dataset date: Dec 20, 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. 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.
  • 50+ Downloads
    Updated May 15, 2019 | 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.
  • 40+ Downloads
    Updated May 15, 2019 | Dataset date: Jan 3, 2017
    This dataset updates: Never
    This map illustrates satellite-detected damage in the city of Idlib, Syrian Arab Republic. Using satellite imagery acquired 01 August 2016, 06 April 2015, 02 May 2014, and 15 September 2013 UNITAR - UNOSAT identified a total of 1,267 affected structures within the city. Approximately 278 of these were destroyed, 353 severely damaged, and 636 moderately damaged. While much of the city was damaged by 06 April 2015, 768 structures were newly damaged and 39 structures experienced an increase in damage between that date and 01 August 2016. This analysis was done as part of the REACH initiative for the U.S. Office of Foreign Disaster Assistance. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.
  • 10+ Downloads
    Updated May 15, 2019 | Dataset date: Jan 3, 2017
    This dataset updates: Never
    This map illustrates satellite-detected damage in a portion of the city of Deir Ez Zor, Syrian Arab Republic. Using satellite imagery acquired 25 May 2016, 10 May 2015, 13 May 2014, and 24 October 2013, UNITAR - UNOSAT identified a total of 4,673 affected structures within the city. Approximately 802 of these were destroyed, 1,410 severely damaged, and 2,461 moderately damaged. While much of the city was damaged by 10 May 2015, 1,389 structures were newly damaged and 66 structures experienced an increase in damage between that date and 25 May 2016. This analysis was done as part of the REACH initiative for the U.S. Office of Foreign Disaster Assistance. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.
  • 10+ Downloads
    Updated May 15, 2019 | Dataset date: Jan 6, 2017
    This dataset updates: Never
    This map illustrates satellite-detected damage density in the city of Idlib, Syrian Arab Republic. Using satellite imagery acquired 06 April 2015, 02 May 2014, 15 September 2013, and 22 March 2010 UNITAR - UNOSAT identified a total of 545 affected structures within the city. Approximately 176 of these were destroyed, 180 severely damaged, and 189 moderately damaged. While much of the city was damaged by 02 May 2014, 249 structures were newly damaged and 5 structures experienced an increase in damage between that date and 06 April 2015. This analysis was done as part of the REACH initiative for the U.S. Office of Foreign Disaster Assistance. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.
  • 20+ Downloads
    Updated May 15, 2019 | Dataset date: Jan 6, 2017
    This dataset updates: Never
    This map illustrates satellite-detected damage density in the city of Idlib, Syrian Arab Republic. Using satellite imagery acquired 01 August 2016, 06 April 2015, 02 May 2014, and 15 September 2013 UNITAR - UNOSAT identified a total of 1,267 affected structures within the city. Approximately 278 of these were destroyed, 353 severely damaged, and 636 moderately damaged. While much of the city was damaged by 06 April 2015, 768 structures were newly damaged and 39 structures experienced an increase in damage between that date and 01 August 2016. This analysis was done as part of the REACH initiative for the U.S. Office of Foreign Disaster Assistance. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.
  • 20+ Downloads
    Updated May 15, 2019 | Dataset date: Jan 6, 2017
    This dataset updates: Never
    This map illustrates satellite-detected damage density in the city of Deir Ez Zor, Syrian Arab Republic. Using satellite imagery acquired 10 May 2015, 13 May 2014, 24 October 2013, and 05 December 2010 UNITAR - UNOSAT identified a total of 3,435 affected structures within the city. Approximately 538 of these were destroyed, 1,153 severely damaged, and 1,744 moderately damaged. While much of the city was damaged by 13 May 2014, 349 structures were newly damaged and 70 structures experienced an increase in damage between that date and 10 May 2015. This analysis was done as part of the REACH initiative for the U.S. Office of Foreign Disaster Assistance. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.
  • 10+ Downloads
    Updated May 15, 2019 | Dataset date: Jan 17, 2017
    This dataset updates: Never
    This map illustrates satellite-detected damage density in the city of Hama, Hama Governorate, Syria. Using satellite imagery acquired 05 March 2014, 26 September 2013, and 06 August 2010, UNITAR - UNOSAT identified a total of 5,224 affected structures, of which 4,664 were destroyed, 215 severely damaged, and 345 moderately damaged. This analysis does not include pre-war military bases and facilities. This analysis was done as part of the REACH initiative for the U.S. Office of Foreign Disaster Assistance. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.