Key Figures
Data Completeness
3/26 Core Data 24 Datasets 11 Organisations Show legend
What is Data Completeness?
Data Completeness defines a set of core data that are essential for preparedness and emergency response. For select countries, the HDX Team and trusted partners evaluate datasets available on HDX and add those meeting the definition of a core data category to the Data Completeness board above. Please help us improve this feature by sending your feedback to hdx@un.org.
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Presence, freshness, and quality of dataset
  • Dataset fully matches criteria and is up-to-date
  • Dataset partially matches criteria and/or is not up-to-date
  • No dataset found matching the criteria
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Affected People
9 Datasets
Coordination & Context
6 Datasets
Food Security & Nutrition
3 Datasets
Geography & Infrastructure
6 Datasets
Health & Education
2 Datasets
Population & Socio-economic Indicators
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  • 10+ Downloads
    Updated October 14, 2015 | Dataset date: Sep 30, 2015
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for East Africa. It was last updated on September 30, 2015. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: easternafrica201507_ML1 Most likely food security outcome for July-September 2015 easternafrica201507_ML2 Most likely food security outcome for October-December 2015 Within the shapefiles, the food security outlook is contained in a field named as ML1 or ML2 according to the outlook period. The code itself is the IPC phase. Two additional codes are used: 66 = water 88 = parks, forests, reserves 99 = missing data (usually urban centers)
  • 10+ Downloads
    Updated October 14, 2015 | Dataset date: Jun 30, 2015
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for East Africa. It was last updated on June 30, 2015. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: eastafrica201304_ML1 Most likely food security outcome for April-June 2015 eastafrica201304_ML2 Most likely food security outcome for July-September 2015 Within the shapefiles, the food security outlook is contained in a field named as ML1 or ML2 according to the outlook period. The code itself is the IPC phase. Two additional codes are used: 66 = water 88 = parks, forests, reserves 99 = missing data (usually urban centers)
  • 10+ Downloads
    Updated October 14, 2015 | Dataset date: Apr 3, 2015
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for East Africa. It was last updated on April 03, 2015. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: eastafrica201304_ML1 Most likely food security outcome for January-March 2015 eastafrica201304_ML2 Most likely food security outcome for April-June 2015 Where xx is one of the region codes listed above. Within the shapefiles, the food security outlook is contained in a field named as ML1 or ML2 according to the outlook period. The code itself is the IPC phase. Two additional codes are used: 66 = water 88 = parks, forests, reserves 99 = missing data (usually urban centers)
  • 20+ Downloads
    Updated October 14, 2015 | Dataset date: Oct 1, 2014
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for East Africa. It was last updated on December 31, 2014. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: EA201304_ML1 Most likely food security outcome for October-December 2014 EA201304_ML2 Most likely food security outcome for January-March 2015 Within the shapefiles, the food security outlook is contained in a field named as ML1 or ML2 according to the outlook period. The code itself is the IPC phase. Two additional codes are used: 66 = water 88 = parks, forests, reserves 99 = missing data (usually urban centers)
  • 10+ Downloads
    Updated October 14, 2015 | Dataset date: Jul 1, 2014
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for East Africa. It was last updated on September 26, 2014. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: eastafrica201304_ML1 Most likely food security outcome for July-September 2014 eastafrica201304_ML2 Most likely food security outcome for October-December 2014 Within the shapefiles, the food security outlook is contained in a field named as ML1 or ML2 according to the outlook period. The code itself is the IPC phase. Two additional codes are used: 66 = water 88 = parks, forests, reserves 99 = missing data (usually urban centers)
  • 10+ Downloads
    Updated October 14, 2015 | Dataset date: Jul 17, 2014
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for East Africa. It was last updated on July 17, 2014. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: eastafrica201304_ML1 Most likely food security outcome for April-June 2014 eastafrica201304_ML2 Most likely food security outcome for July-September 2014 Within the shapefiles, the food security outlook is contained in a field named as ML1 or ML2 according to the outlook period. The code itself is the IPC phase. Two additional codes are used: 66 = water 88 = parks, forests, reserves 99 = missing data (usually urban centers)
  • 10+ Downloads
    Updated October 14, 2015 | Dataset date: Jan 1, 2014
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for East Africa. It was last updated on August 07, 2014. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: eastafrica201304_ML1 Most likely food security outcome for January-March 2014 eastafrica201304_ML2 Most likely food security outcome for April-June 2014 Within the shapefiles, the food security outlook is contained in a field named as ML1 or ML2 according to the outlook period. The code itself is the IPC phase. Two additional codes are used: 66 = water 88 = parks, forests, reserves 99 = missing data (usually urban centers)
  • 10+ Downloads
    Updated October 14, 2015 | Dataset date: Nov 14, 2013
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for East Africa. It was last updated on November 14, 2013. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: eastafrica201304_ML1 Most likely food security outcome for October-December 2013 eastafrica201304_ML2 Most likely food security outcome for January-March 2014 Where xx is one of the region codes listed above. Within the shapefiles, the food security outlook is contained in a field named as ML1 or ML2 according to the outlook period. The code itself is the IPC phase. Two additional codes are used: 66 = water 88 = parks, forests, reserves 99 = missing data (usually urban centers)
  • 10+ Downloads
    Updated October 14, 2015 | Dataset date: Jul 14, 2013
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for East Africa. It was last updated on July 14, 2013. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: eastafrica201304_ML1 Most likely food security outcome for July-September 2013 eastafrica201304_ML2 Most likely food security outcome for October-December 2013 Within the shapefiles, the food security outlook is contained in a field named as ML1 or ML2 according to the outlook period. The code itself is the IPC phase. Two additional codes are used: 66 = water 88 = parks, forests, reserves 99 = missing data (usually urban centers)
  • 10+ Downloads
    Updated October 14, 2015 | Dataset date: Jan 14, 2013
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for East Africa. It was last updated on January 14, 2013. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: eastafrica201304_ML1 Most likely food security outcome for January-March 2013 eastafrica201304_ML2 Most likely food security outcome for April-June 2013 Within the shapefiles, the food security outlook is contained in a field named as ML1 or ML2 according to the outlook period. The code itself is the IPC phase. Two additional codes are used: 66 = water 88 = parks, forests, reserves 99 = missing data (usually urban centers)
  • Updated August 10, 2015 | Dataset date: Aug 8, 2014
    This dataset updates: Never
    This map illustrates satellite-detected areas of flood affected land as detected by RADARSAT-2 imagery acquired 08 August 2014 in Khartoum State, Sudan. The area surrounding Khartoum City and Umdurman was inundated by floods caused by heavy rains. Areas to the South of Umdurman seem to have been flooded and many other areas including Umdaba and East Nile seem to suffer from waters and/or muds. It is likely that flood waters have been systematically underestimated along highly vegetated areas along main river banks, and within built-up urban areas because of the characteristics of the satellite data used. This analysis has not yet been validated in the field. Please send ground feedback to UNITAR /UNOSAT.
  • Updated August 10, 2015 | Dataset date: Aug 19, 2014
    This dataset updates: Never
    This map illustrates satellite-detected areas of flood affected land as detected in satellite imagery acquired by the Pleiades satellite on 14 August 2014 in Khartoum State, Sudan. The area surrounding Khartoum City and Umdurman was inundated by floods caused by heavy rains. Areas to the South of Umdurman seem to have been flooded and many other areas including Um Baba and Khartoum Bahri seem to be affected by varying levels of water and saturated soils. The flooded area over Khartoum has decreased slightly in some areas, however the higher resolution of the Pleiades shows more smaller standing bodies of water that were likely overlooked by previous sensors. It is likely that flood waters have been systematically underestimated along highly vegetated areas along main river banks, and within built-up urban areas because of the characteristics of the satellite data used. This analysis has not yet been validated in the field. Please send ground feedback to UNITAR /UNOSAT
  • This map illustrates satellite-detected areas of flood affected land as detected in satellite imagery acquired by the TerraSAR-X satellite on 10 August 2014 in Khartoum State, Sudan. The area surrounding Khartoum City was inundated by floods caused by heavy rains. The area to the northeast of Khartoum City is affected by varying levels of water and/or saturated soils. It is likely that flood waters have been systematically underestimated along highly vegetated areas along main river banks, and within built-up urban areas because of the characteristics of the satellite data used. This analysis has not yet been validated in the field. Please send ground feedback to UNITAR / UNOSAT.
  • Updated August 10, 2015 | Dataset date: Aug 11, 2014
    This dataset updates: Never
    This map illustrates satellite-detected areas of flood affected land as detected in satellite imagery acquired by the TerraSAR-X satellite on 09 August 2014 in Khartoum State, Sudan. The area surrounding Khartoum City and Umdurman was inundated by floods caused by heavy rains. Areas to the South of Umdurman seem to have been flooded and many other areas including Umdaba and East Nile seem to be affected by varying levels of water and saturated soils. The flooded area over Khartoum city has decreased slightly since the previous analysis using an image from 8 August 2014. It is likely that flood waters have been systematically underestimated along highly vegetated areas along main river banks, and within built-up urban areas because of the characteristics of the satellite data used. This analysis has not yet been validated in the field. Please send ground feedback to UNITAR /UNOSAT.
  • Updated August 10, 2015 | Dataset date: Aug 20, 2014
    This dataset updates: Never
    This map illustrates satellite-detected areas of flood affected land as detected in satellite imagery acquired by the Pleiades satellite on 19 August 2014 in Khartoum State, Sudan. The area surrounding Khartoum City and Umdurman was inundated by floods caused by heavy rains. Areas to the South of Umdurman seem to have been flooded and many other areas including Um Baba and Khartoum Bahri seem to be affected by varying levels of water and saturated soils. The flooded area over Khartoum has decreased slightly in some areas, however there also appears to be an increase in others. This increase is potentially saturated soils and not necessarily standing water. It is likely that flood waters have been systematically underestimated along highly vegetated areas along main river banks, and within built-up urban areas because of the characteristics of the satellite data used. This analysis has not yet been validated in the field. Please send ground feedback to UNITAR /UNOSAT
  • Updated August 10, 2015 | Dataset date: Jul 21, 2014
    This dataset updates: Never
    This map illustrates satellite-detected structures at the Shagarab 1 refugee camp in al Qadarif Province, Sudan as seen on 09 December 2013 by the WorldView-2 satellite. This camp lies about 70 km South-East of New Halfa and 105 km North-East of Al Qadarif city. UNOSAT analyzed a total of 6,242 structures in the 209 ha of the camp. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR / UNOSAT.
  • Updated August 10, 2015 | Dataset date: Jul 21, 2014
    This dataset updates: Never
    This map illustrates satellite-detected structures at the Shagarab 2 refugee camp in al Qadarif Province, Sudan as seen on 09 December 2013 by the WorldView-2 satellite. This camp lies about 76 km South-East of New Halfa and 100 km North-East of Al Qadarif city. UNOSAT analyzed a total of 4,606 structures in the 218 ha of the camp. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR / UNOSAT.
  • 10+ Downloads
    Updated August 10, 2015 | Dataset date: Jul 21, 2014
    This dataset updates: Never
    This map illustrates satellite-detected structures at Um Gargour refugee camp in Al Qadrif province, Sudan as seen on 05 January 2014 by the WorldView-2 satellite. This camp lies 58 km North-East from Al Qadarif city and 90 km South New Halfa. UNOSAT analyzed a total of 4,471 structures in the 206 ha of the camp. This is a preliminary analysis & has not yet been validated in the field. Please send ground feedback to UNITAR / UNOSAT.