Zimbabwe - Humanitarian Data Exchange

African Financial Survey Database, 2016

African Development Bank Group

200+ Downloads

Time Period of the Dataset [?]: July 08, 2016-July 08, 2016 ... More

This dataset updates: Never

African Financial Survey Database, 2005-2014

XLSX

Economic Community of Central African States Statistics, 2013

African Development Bank Group

100+ Downloads

Time Period of the Dataset [?]: August 22, 2013-August 22, 2013 ... More

This dataset updates: Never

Economic Community of Central African States Statistics, 2013

XLSX

AfDB Country Policy and Institutional Assessment, 2013

African Development Bank Group

100+ Downloads

Time Period of the Dataset [?]: April 22, 2014-April 22, 2014 ... More

This dataset updates: Never

AfDB Country Policy and Institutional Assessment, 2013

XLSX

African Development Bank, Food Security, December 2011

African Development Bank Group

100+ Downloads

Time Period of the Dataset [?]: December 08, 2011-December 08, 2011 ... More

This dataset updates: Never

African Development Bank, Food Security, January 1960 - December 2011

CSV

African Development Bank, Food Security, Prices, Monthly, December 2011

African Development Bank Group

100+ Downloads

Time Period of the Dataset [?]: December 08, 2011-December 08, 2011 ... More

This dataset updates: Never

African Development Bank, Food Security, Prices, Monthly, January 1980 - December 2011

CSV

African Port Statistics, 2013

African Development Bank Group

300+ Downloads

Time Period of the Dataset [?]: July 16, 2013-July 16, 2013 ... More

This dataset updates: Never

African Port Statistics, 2005-2009

XLSX

WFP and FAO Overview of Countries Affected by the El Niño

HDX

100+ Downloads

Time Period of the Dataset [?]: April 21, 2016-April 21, 2016 ... More

This dataset updates: Never

This dataset contains a list of the countries affected by the El Niño as at April 21, 2016 as reported jointly by FAO, the Global Food Security Cluster and WFP on 21 April 2016 in the 2015-2016 El Niño: WFP and FAO Overview update. According to the World Bank, El Niño is likely to have a negative impact in more isolated local food markets, and many countries are already facing increased food prices. Food Security Cluster partners have implemented preparedness activities and are responding in countries where the effects of El Niño have materialised, such as Ethiopia, Papua New Guinea, Malawi and throughout Central America. In Southern Africa, many areas have seen the driest October-December period since at least 1981, and some 14 million people in the region are already facing hunger, which adds to fears of a spike in the numbers of the food insecure later this year through 2017.

CSV
GeoJSON

GAR15 Global Exposure Dataset for Zimbabwe

United Nations Office for Disaster Risk Reduction (UNDRR)

40+ Downloads

Time Period of the Dataset [?]: December 31, 2015-December 31, 2015 ... More

This dataset updates: Never

This dataset is part of the data series [?]: UNDRR - GAR15 Global Exposure

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.

SHP

Food Insecurity Mapping - Southern Africa (July - September 2015)

HDX

20+ Downloads

Time Period of the Dataset [?]: July 01, 2015-July 01, 2015 ... More

This dataset updates: Never

This dataset is part of the data series [?]: HDX - Food Insecurity Mapping

This Archive contains shapefiles for FEWS NET Food Security Outlook for Southern Africa. It was last updated on August 19, 2015. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: SA201304_ML1 Most likely food security outcome for July-September 2015 SA201304_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)

SHP

Food Insecurity Mapping - Southern Africa (April - June 2015)

HDX

Time Period of the Dataset [?]: June 01, 2015-June 01, 2015 ... More

This dataset updates: Never

This dataset is part of the data series [?]: HDX - Food Insecurity Mapping

This Archive contains shapefiles for FEWS NET Food Security Outlook for Southern Africa. It was last updated on June 01, 2015. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: southernafrica201304_ML1 Most likely food security outcome for April-June 2015 southernafrica201304_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)

SHP

Food Insecurity Mapping - Southern Africa (January - March 2015)

HDX

10+ Downloads

Time Period of the Dataset [?]: February 10, 2015-February 10, 2015 ... More

This dataset updates: Never

This dataset is part of the data series [?]: HDX - Food Insecurity Mapping

This Archive contains shapefiles for FEWS NET Food Security Outlook for Southern Africa. It was last updated on February 10, 2015. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: southernafrica201304_ML1 Most likely food security outcome for January-March 2015 southernafrica201304_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).

SHP

Food Insecurity Mapping - Southern Africa (October - December 2014)

HDX

Time Period of the Dataset [?]: October 01, 2014-October 01, 2014 ... More

This dataset updates: Never

This dataset is part of the data series [?]: HDX - Food Insecurity Mapping

This Archive contains shapefiles for FEWS NET Food Security Outlook for Southern 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: southernafrica201304_ML1 Most likely food security outcome for October-December 2014 southernafrica201304_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).

SHP

Food Insecurity Mapping - Southern Africa (July - September 2014)

HDX

Time Period of the Dataset [?]: July 01, 2014-July 01, 2014 ... More

This dataset updates: Never

This dataset is part of the data series [?]: HDX - Food Insecurity Mapping

This Archive contains shapefiles for FEWS NET Food Security Outlook for Southern 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: southernafrica201307_ML1 Most likely food security outcome for July-September 2014 southernafrica201407_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).

SHP

Food Insecurity Mapping - Southern Africa (April - June 2014)

HDX

Time Period of the Dataset [?]: April 01, 2014-April 01, 2014 ... More

This dataset updates: Never

This dataset is part of the data series [?]: HDX - Food Insecurity Mapping

This Archive contains shapefiles for FEWS NET Food Security Outlook for Southern 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: southernafrica201304_ML1 Most likely food security outcome for April-June 2014 southernafrica201304_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).

SHP

Food Insecurity Mapping - Southern Africa (January - March 2014)

HDX

10+ Downloads

Time Period of the Dataset [?]: January 01, 2014-January 01, 2014 ... More

This dataset updates: Never

This dataset is part of the data series [?]: HDX - Food Insecurity Mapping

This Archive contains shapefiles for FEWS NET Food Security Outlook for Southern 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: southernafrica201401_ML1 Most likely food security outcome for January-March 2014 southernafrica201401_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)

SHP

Food Insecurity Mapping - Southern Africa (October - December 2015)

HDX

Time Period of the Dataset [?]: October 01, 2015-October 01, 2015 ... More

This dataset updates: Never

This dataset is part of the data series [?]: HDX - Food Insecurity Mapping

This Archive contains shapefiles for FEWS NET Food Security Outlook for Southern Africa. It was last updated on February 05, 2016. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: SA201304_ML1 Most likely food security outcome for October-December 2015 SA201304_ML2 Most likely food security outcome for January-March 2016 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).

SHP

Food Insecurity Mapping - Southern Africa (July - September 2013)

HDX

Time Period of the Dataset [?]: July 01, 2013-July 01, 2013 ... More

This dataset updates: Never

This dataset is part of the data series [?]: HDX - Food Insecurity Mapping

This Archive contains shapefiles for FEWS NET Food Security Outlook for Southern 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: southernafrica201307_ML1 Most likely food security outcome for July-September 2013 southernafrica201307_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)

SHP

Food Insecurity Mapping - Southern Africa (April - June 2013)

HDX

Time Period of the Dataset [?]: June 01, 2013-June 01, 2013 ... More

This dataset updates: Never

This dataset is part of the data series [?]: HDX - Food Insecurity Mapping

This Archive contains shapefiles for FEWS NET Food Security Outlook for Southern 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: southernafrica201304_ML1 Most likely food security outcome for April-June 2013 southernafrica201304_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)

SHP

Food Insecurity Mapping - Southern Africa (January - March 2013)

HDX

Time Period of the Dataset [?]: January 01, 2013-January 01, 2013 ... More

This dataset updates: Never

This dataset is part of the data series [?]: HDX - Food Insecurity Mapping

This Archive contains shapefiles for FEWS NET Food Security Outlook for Southern 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: southernafrica201304_ML1 Most likely food security outcome for January-March 2013 southernafrica201304_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)

SHP

Geodata of Update: Flood Water over Tokwe Mukorsi Dam, Masvingo Province, Zimbabwe

United Nations Satellite Centre (UNOSAT)

10+ Downloads

Time Period of the Dataset [?]: February 19, 2014-February 19, 2014 ... More

This dataset updates: Never

This map illustrates satellite-detected water bodies at the Tokwe Mukorsi Dam, Masvingo Province, Zimbabwe, as imaged by TerraSAR-X on 18 February 2014. The flooded area above the dam has decreased slightly since the previous analysis using an image from 11 February 2014 and currently encompasses about 2,278 ha. It is likely that flood waters have been systematically underestimated along highly vegetated areas along main river banks because of the special characteristics of the satellite data used. This analysis has not yet been validated in the field. Please send ground feedback to UNITAR /UNOSAT.

KMZ
SHP

Geodata of Submerged Homesteads At Tokwe Mukorsi Dam, Masvingo Province, Zimbabwe

United Nations Satellite Centre (UNOSAT)

10+ Downloads

Time Period of the Dataset [?]: February 13, 2014-February 13, 2014 ... More

This dataset updates: Never

This map illustrates water bodies at the Tokwe Mukorsi Dam, Masvingo Province, Zimbabwe, as detected by TerraSAR-X on 11 February 2014. The flooded area above the dam has greatly increased due to recent heavy rains and currently encompasses about 2,300 ha. Using a WorldView-1 image acquired on 2 January 2012, UNOSAT located a total of 751 structures in 143 homestead locations that would be submerged by the current flood water extent. It is likely that flood waters have been systematically underestimated along highly vegetated areas along main river banks because of the special characteristics of the satellite data used. This analysis has not yet been validated in the field. Please send ground feedback to UNITAR /UNOSAT.

KMZ