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  • 100+ Downloads
    Updated January 30, 2018 | Dataset date: May 2, 2018
    This dataset updates: Every year
    Personas que han sido afectadas por arma de fuego, arma blanca, objeto contundente, estrangulamiento, linchamiento, otros.
  • 100+ Downloads
    Updated January 30, 2018 | Dataset date: May 2, 2016
    This dataset updates: Every year
    El indicador contiene la información sobre el avance de la deforestación de los bosques en Guatemala y el avance en el rescate o reforestación de los bosques.
  • 200+ Downloads
    Updated January 25, 2018 | Dataset date: May 2, 2016
    This dataset updates: Every year
    Los indicadores contienen los eventos naturales ocurridos desde 1530 a 2015 sobre erupciones, terremotos, sismos, hundimientos, grietas, derrumbes y eventos sobre ventarrones, correntadas, desbordamientos, temporales ,inundación, lluvias, sequías, huracanes, heladas, tempestades. Toda la información esta desagregada a nivel municipal.
  • 1600+ Downloads
    Updated December 13, 2017 | Dataset date: Dec 31, 2016
    This dataset updates: Every year
    Detail cases of acute malnutrition in children under 5 years by department and municipality year 2016.
  • 1500+ Downloads
    Updated December 13, 2017 | Dataset date: Dec 31, 2014
    This dataset updates: Every year
    Detail cases of acute malnutrition in children under 5 years by department and municipality year 2014.
  • 1600+ Downloads
    Updated November 30, 2017 | Dataset date: Dec 31, 2015
    This dataset updates: Every year
    Detail cases of acute malnutrition in children under 5 years by department and municipality year 2015.
  • 2400+ Downloads
    Updated November 29, 2017 | Dataset date: Jan 1, 2008-Jun 30, 2017
    This dataset updates: Every year
    Incidentes atendidos por la CONRED del año 2008 al año 2017 , en todo el territorio de Guatemala, con estadísticas de personas y viviendas, tipo de evento segun la clasificación de la CONRED, Departamento, Municipio y centros poblados.
  • This map illustrates satellite-detected surface water extent in the northern part of Guatemala covering Chisec, Coban Ixcan and Sayaxche municipalities, using a Sentinel-1 satellite image acquired on the 09 October 2017. Sentinel-1 imagery acquired on 3 and 5 October 2017 was used as pre crisis imagery. UNITAR-UNOSAT analysis shows an expansion of water of ~ 4,600 has over the analyzed municipalities, being Sayaxche the municipality that was affected the most with an expansion of flood waters of ~ 3,200 Ha. The exact limit of flood waters is uncertain because of the low spatial resolution of the satellite data used for this analysis. Please send ground feedback to UNITAR - UNOSAT.
  • 200+ Downloads
    Updated August 29, 2017 | Dataset date: Jan 29, 2016-Aug 4, 2016
    This dataset updates: Never
    Within 24 hours of the World Health Organization declaring the Zika virus a global health emergency, RIWI began a study in 9 countries across the Americas capturing over 30,000 respondents. Data collection targeted respondents' knowledge of Zika virus transmission mechanisms and confidence in government health agencies to treat and contain the epidemic. The data was collected using RIWI's patented Random Domain Intercept Technology™ (RDIT).
  • 600+ Downloads
    Updated September 23, 2016 | Dataset date: Sep 15, 2016
    This dataset updates: Never
    Epidemiological update on Zika Virus, week of 15 September 2016
  • 500+ Downloads
    Updated June 21, 2016 | Dataset date: Apr 21, 2016
    This dataset updates: Every three months
    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.
  • 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.
  • 300+ Downloads
    Updated November 24, 2015 | Dataset date: Dec 31, 2002
    This dataset updates: Never
    Proyección de población 2000 al 2050, por sexo.
  • 500+ Downloads
    Updated November 24, 2015 | Dataset date: Jan 1, 2012-Dec 31, 2012
    This dataset updates: Never
    Incidentes atendidos por la CONRED en el año 2012, en todo el territorio de Guatemala, con estadísticas de personas y viviendas, el tipo de evento y la clasificación de la CONRED, Departamento y Municipio y en algunos centros poblados.
  • 10+ Downloads
    Updated October 13, 2015 | Dataset date: Jan 1, 2013
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for Central America and The Caribbean. 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 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)
  • Updated October 13, 2015 | Dataset date: Apr 1, 2013
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for Central America and The Caribbean. It was last updated on May 15, 2014. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: LAC201304_ML1 Most likely food security outcome for April-June 2013 LAC201304_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)
  • Updated October 13, 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: 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)
  • Updated October 13, 2015 | Dataset date: Oct 1, 2013
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for Central America and The Caribbean. 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 13, 2015 | Dataset date: Jan 1, 2014
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for Central America and The Caribbean. 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)
  • Updated October 13, 2015 | Dataset date: Apr 1, 2014
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for Central America and The Caribbean. It was last updated on April 2014. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: xx201404_ML1 Most likely food security outcome for April-June 2014 xx201404_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 13, 2015 | Dataset date: Jul 1, 2014
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for Central America and The Caribbean. It was last updated on September 30, 2014. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: LAC201304_ML1 Most likely food security outcome for July-September 2014 LAC201304_ML2 Most likely food security outcome for October-December 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)
  • 20+ Downloads
    Updated October 13, 2015 | Dataset date: Oct 1, 2015
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for Central America and The Caribbean. 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: LAC201304_ML1 Most likely food security outcome for October-December 2014 LAC201304_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)
  • Updated October 13, 2015 | Dataset date: Mar 31, 2015
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for Central America and The Caribbean. It was last updated on March 31, 2015. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: LAC201304_ML1 Most likely food security outcome for January-March 2015 LAC201304_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)
  • 10+ Downloads
    Updated October 13, 2015 | Dataset date: Oct 8, 2015
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for Central America and The Caribbean. It was last updated on October 08, 2015. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: LAC201304_ML1 Most likely food security outcome for July-September 2015 LAC201304_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)
  • Updated October 13, 2015 | Dataset date: Jul 1, 2015
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for Central America and The Caribbean. It was last updated on July 01, 2015. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: LAC201304_ML1 Most likely food security outcome for April-June 2015 LAC201304_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)