{"geometry": {"type": "Polygon", "coordinates": [[[8.500288, 4.771983], [7.462108, 4.412108], [7.082596, 4.464689], [6.698072, 4.240594], [5.898173, 4.262453], [5.362805, 4.887971], [5.033574, 5.611802], [4.325607, 6.270651], [3.57418, 6.2583], [2.691702, 6.258817], [2.749063, 7.870734], [2.723793, 8.506845], [2.912308, 9.137608], [3.220352, 9.444153], [3.705438, 10.06321], [3.60007, 10.332186], [3.797112, 10.734746], [3.572216, 11.327939], [3.61118, 11.660167], [3.680634, 12.552903], [3.967283, 12.956109], [4.107946, 13.531216], [4.368344, 13.747482], [5.443058, 13.865924], [6.445426, 13.492768], [6.820442, 13.115091], [7.330747, 13.098038], [7.804671, 13.343527], [9.014933, 12.826659], [9.524928, 12.851102], [10.114814, 13.277252], [10.701032, 13.246918], [10.989593, 13.387323], [11.527803, 13.32898], [12.302071, 13.037189], [13.083987, 13.596147], [13.318702, 13.556356], [13.995353, 12.461565], [14.181336, 12.483657], [14.577178, 12.085361], [14.468192, 11.904752], [14.415379, 11.572369], [13.57295, 10.798566], [13.308676, 10.160362], [13.1676, 9.640626], [12.955468, 9.417772], [12.753672, 8.717763], [12.218872, 8.305824], [12.063946, 7.799808], [11.839309, 7.397042], [11.745774, 6.981383], [11.058788, 6.644427], [10.497375, 7.055358], [10.118277, 7.03877], [9.522706, 6.453482], [9.233163, 6.444491], [8.757533, 5.479666], [8.500288, 4.771983]]]}, "_id": "AGMCAZMGC6UF916641381868806.52", "type": "Feature", "properties": {"url": "/group/nga", "name": "Nigeria"}, "id": "NGA"}
251
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10+ Downloads
Updated
March 8, 2016
| Dataset date: Feb 25, 2016
This dataset updates: Never
This map illustrates satellite-detected shelters and other buildings at the Minawao refugee settlement, Mayo-Tsanaga District, Far North Province in Cameroon as seen by the WorldView-2 satellite on 19 November 2015. UNOSAT analysed a total of 11,777 structures (9,390 tent shelters, 551 administrative buildings, 634 improvised shelters, and 1,202 semi-permanent shelters) within 502 hectares of the settlement area. Previous analysis from 10 March 2015 indicated 5, 220 shelters over 261 hectares and thus the updated analysis indicates an increase of approximately 126% on shelters and 93% in land occupied. Note that apparently adjoining, contiguous shelters were counted as a single shelter which may thus underestimate total number of shelters. This is a preliminary analysis & has not yet been validated in the field. Please send ground feedback to UNITAR/UNOSAT.
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2500+ Downloads
Updated
February 19, 2016
| Dataset date: Jul 1, 2014-Jan 28, 2016
This dataset updates: Never
Since May 2013, Nigeria has seen an intensification of conflict due to Boko Haram attacks in its north east states of Adamawa, Bauchi, Borno, Gombe, Taraba and Yobe. Insurgency and counter-insurgency have inevitably resulted in the displacement of people across the troubled states. In response to the need for accurate information on internally displaced persons (IDPs), the International Organization for Migration (IOM) began implementing the Displacement Tracking Matrix (DTM) project in July 2014. The objective of the project is to support the Government of Nigeria in establishing a comprehensive system to collect and disseminate data on IDPs by strengthening the capacity of the National Emergency Management Agency (NEMA), the State Emergency Management Agencies (SEMAs) and other humanitarian actors to conduct assessments on IDPs in a unified and systematized manner. The activities of the DTM project, which consist of conducting baseline assessments and registration for IDPs living in camps and host communities, are currently being carried out in Adamawa, Bauchi, Borno, Gombe, Taraba and Yobe. The information collected will contribute to the provision of a comprehensive profile of the IDP population in Nigeria which will be shared with all relevant stakeholders and will contribute towards enabling the government of Nigeria and humanitarian partners identify the needs of Nigeria’s displaced population and develop interventions for providing IDPs necessary assistance. The project is funded by the Office of Disaster Assistance of the United States Agency for International Development and the European Commission's Humanitarian Aid and Civil Protection Department.
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100+ Downloads
Updated
January 29, 2016
| Dataset date: Dec 31, 2015
This dataset updates: Never
The GAR15 global exposure database is based on a top-down approach where statistical information including socio-economic, building type, and capital stock at a national level are transposed onto the grids of 5x5 or 1x1 using geographic distribution of population data and gross domestic product (GDP) as proxies.
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300+ Downloads
Updated
December 8, 2015
| Dataset date: Oct 31, 2014-Jul 31, 2015
This dataset updates: Never
Maisha is VoicesAfrica’s online pan Africa study on lifestyle and viewpoints on various aspects of life. The research report covers the following information areas:
Income and expenditure
• If earn a personal income
• Share of wallet
• Whether overall expenditure has gone up, down, or remained the same compared to the previous year
Values
• Determinants of well being
• Aspects that have made life better/worse
• Threats to self and country
Role models
• Most admired personality
• Part of the world/Africa that offers greatest inspiration and hope
Africa unity
• If would support the integration of all African countries
Technology
• Devices used
• Device that has made life better/worse
• Device that has had greatest influence in life
Attitudes
• Response to statements on politics, insecurity, family, religion, sports, patriotism, economy, corruption, health, relationships, among others
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200+ Downloads
Updated
November 25, 2015
| Dataset date: Sep 14, 2015
This dataset updates: Every three months
The dataset represents the latest Severe Acute Malnutrition Prevalence available for the Sahel nine countries (Burkina Faso, Cameroon, Chad, the Gambia, Mali, Mauritania, Niger, Nigeria, Senegal).
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200+ Downloads
Updated
November 25, 2015
| Dataset date: Oct 1, 2015
This dataset updates: Never
Nigeria Admin Level 2 boundaries created by the Bill & Melinda Gates foundation. The boundaries were made by mapping all settlements, and then using the Ward Level 2 admin attributes and the ESRI Thiessen polygons tool to create boundaries at each admin level.
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600+ Downloads
Updated
November 24, 2015
| Dataset date: Feb 2, 2012
This dataset updates: Every year
The geodata represents the digital elevation model of Nigeria. Spatial resolution: 90 meters.
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600+ Downloads
Updated
November 24, 2015
| Dataset date: Feb 2, 2012
This dataset updates: Every year
The geodata represents the hydrography network of Nigeria. Scale: 1:1,000,000
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200+ Downloads
Updated
November 24, 2015
| Dataset date: Nov 1, 2012
This dataset updates: Never
The dataset represents the extent of floods in Nigeria from July to November 2012.
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2400+ Downloads
Updated
November 24, 2015
| Dataset date: Oct 21, 2014
This dataset updates: Every year
The dataset represents all settlements of Nigeria with codification of capitals.
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400+ Downloads
Updated
November 24, 2015
| Dataset date: Dec 5, 2014
This dataset updates: Every three months
Who, What, Where (3W) dataset on the Ebola response effort. Some entries have a maximum level of desegregation up to administrative level 3. The dataset contains data from Guinea, Liberia, Sierra Leone, and Nigeria.
This dataset is updated weekly. Last Update 17 Nov. 2014
Note: If your humanitarian organization would like to make a correction or update the dataset, please contact the OCHA focal point for the respective country. Contacts can be found at
https://wca.humanitarianresponse.info/fr/emergencies/virus-ebola
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800+ Downloads
Updated
November 24, 2015
| Dataset date: Apr 2, 2015
This dataset updates: Every six months
Ebola outbreak time series data at national and sub national levels since March 2014. Data compiled manually from a number of published reports. Updated by OCHA ROWCA every working day.
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20+ 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:
westafrica201304_ML1 Most likely food security outcome for July-September 2015
westafrica201304_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)
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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:
westafrica201304_ML1 Most likely food security outcome for April-June 2015
westafrica201304_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)
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20+ Downloads
Updated
October 14, 2015
| Dataset date: Mar 25, 2015
This dataset updates: Never
This Archive contains shapefiles for FEWS NET Food Security Outlook for West Africa.
It was last updated on March 25, 2015. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity.
The two shapefiles represent the two analytic periods:
westafrica201304_ML1 Most likely food security outcome for January-March 2015
westafrica201304_ML2 Most likely food security outcome for April-June 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)
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10+ 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 West Africa.
It was last updated on November 13, 2014. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity.
The two shapefiles represent the two analytic periods:
WA201304_ML1 Most likely food security outcome for October-December 2014
WA201304_ML2 Most likely food security outcome for January-March 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)
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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 West Africa.
It was last updated on September 29, 2014. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity.
The two shapefiles represent the two analytic periods:
WA201304_ML1 Most likely food security outcome for July-September 2014
WA201304_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)
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10+ Downloads
Updated
October 14, 2015
| Dataset date: Apr 1, 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:
WA201304_ML1 Most likely food security outcome for April-June 2014
WA201304_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)
-
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 January 19, 2014. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity.
The two shapefiles represent the two analytic periods:
xx201401_ML1 Most likely food security outcome for January-March 2014
xx201401_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)
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10+ Downloads
Updated
October 14, 2015
| Dataset date: Oct 1, 2013
This dataset updates: Never
This Archive contains shapefiles for FEWS NET Food Security Outlook for West 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:
xx201304_ML1 Most likely food security outcome for October-December 2013
xx201304_ML2 Most likely food security outcome for January-March 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)
-
Updated
October 14, 2015
| Dataset date: Jul 1, 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:
xx201304_ML1 Most likely food security outcome for July-September 2013
xx201304_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: Apr 1, 2013
This dataset updates: Never
This Archive contains shapefiles for FEWS NET Food Security Outlook for West Africa.
It was last updated on June 14, 2013. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity.
The two shapefiles represent the two analytic periods:
xx201304_ML1 Most likely food security outcome for April-June 2013
xx201304_ML2 Most likely food security outcome for July-September 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)
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30+ Downloads
Updated
October 14, 2015
| Dataset date: Jan 1, 2013
This dataset updates: Never
This Archive contains shapefiles for FEWS NET Food Security Outlook for West 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:
xx201304_ML1 Most likely food security outcome for January-March 2013
xx201304_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)
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90+ Downloads
Updated
September 21, 2015
This dataset updates: Never
The Open Humanitarian Data Repository contains a comprehensive repository of openly available GIS baseline data for the Ebola Outbreak in West-Africa.
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200+ Downloads
Updated
August 28, 2015
| Dataset date: Jan 1, 2013-Apr 1, 2014
This dataset updates: Never
Here we provide version 1 Flowminder (
www.flowminder.org) human mobility models for West Africa, together with WorldPop population density data for the region, to support ongoing efforts to control the ebola outbreak. Before downloading any data, please read the documention carefully as it provides details on the datasets and models provided through the links below. The mobility data refer to estimated patterns before the Ebola outbreak and should be interpreted with caution for Ebola affected countries as mobility patters are known to have changed.
Additional discussion by the authors around the use of mobile operator data for epidemilogical research see:
http://currents.plos.org/outbreaks/article/containing-the-ebola-outbreak-the-potential-and-challenge-of-mobile-network-data/
