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  • Time Period of the Dataset [?]: May 30, 2022-May 30, 2022 ... More
    Modified [?]: 28 June 2022
    Dataset Added on HDX [?]: 28 June 2022
    This dataset updates: Never
    UNOSAT code: FL20220526GUY This map illustrates cumulative satellite-detected water using VIIRS in Guyana between 25 to 29 May 2022 compared with the period from 20 to 24 May 2022. Within the cloud free analyzed areas of about 205,000 km2, a total of about 3,900 km2 of lands appear to be affected with flood waters. Water extent appears to have increased of about 1,200 km2 since the period between 20 to 24 may 2022. Based on Worldpop population data and the maximal flood water coverage, ~22,000 people are potentially exposed or living close to flooded areas. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to the United Nations Satellite Centre (UNOSAT).
  • Time Period of the Dataset [?]: May 30, 2022-May 30, 2022 ... More
    Modified [?]: 28 June 2022
    Dataset Added on HDX [?]: 28 June 2022
    This dataset updates: Never
    UNOSAT code: FL20220526GUY This map illustrates satellite-detected surface waters along the Rupununi river in Upper Takutu-Upper Essequibo Region of Guyana as observed from a Sentinel-1 image acquired on 26 May 2022 at 09:45 UTC. Within the analyzed area of about 14,000 km2, a total of about 320 km2 of lands were observed as flooded. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to the United Nations Satellite Centre (UNOSAT). Important note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas
  • Time Period of the Dataset [?]: August 19, 2021-August 19, 2021 ... More
    Modified [?]: 18 February 2022
    Dataset Added on HDX [?]: 18 February 2022
    This dataset updates: Never
    UNOSAT code: FL20210817GUY This map illustrates satellite-detected surface waters in the Upper Takutu-Upper Essequibo Regions of Guyana using NOAA-VIIRS between 12th and 16th of August 2021. Within the analysed area of about 24,462 km2, a total of about 1417 km2 of lands were observed as flooded. Based on Worldpop spatial demographic data,approximately 2153 people are exposed or living close to flooded areas. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • Time Period of the Dataset [?]: June 24, 2021-June 24, 2021 ... More
    Modified [?]: 18 February 2022
    Dataset Added on HDX [?]: 18 February 2022
    This dataset updates: Never
    UNOSAT code: FL20210520GUY This map illustrates satellite-detected surface waters along the Mazaruni river in Cuyuni-Mazaruni Region of Guyana as observed from Sentinel-1 radar image acquired on 23 June 2021 at 22:15 UTC. Within the analyzed area of about 480 km2, the water extent appears to have decreased of about 3 km2 since 9 June 2021. This is a preliminary analysis that has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT. Important note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.
  • Time Period of the Dataset [?]: June 14, 2021-June 14, 2021 ... More
    Modified [?]: 18 February 2022
    Dataset Added on HDX [?]: 18 February 2022
    This dataset updates: Never
    UNOSAT code: FL20210520GUY This map illustrates satellite-detected surface waters along the Rupununi river in Upper Takutu-Upper Essequibo Region of Guyana as observed from Sentinel-1 image acquired on 12 June 2021 at 09:45 UTC. Within the analyzed area of about 6,500 km2, a total of about 235 km2 of lands were observed as flooded and the road about 26 km are potentially affected by the floods. This is a preliminary analysis that has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT. Important note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.
  • Time Period of the Dataset [?]: June 11, 2021-June 11, 2021 ... More
    Modified [?]: 18 February 2022
    Dataset Added on HDX [?]: 18 February 2022
    This dataset updates: Never
    UNOSAT code: FL20210520GUY This map illustrates satellite-detected surface waters in Guyana as observed from a Joint VIIRS-ABI flood product acquired on 6 & 8 June 2021. Within the analyzed cloud free zones of about 140,000 km2, a total of about 2,000 km2 of lands appear to be flooded. The overall water extent as detected on the 8 June 2021 appears to have decreased of about 1,000 km2 since 6 June 2021. Based on Worldpop population data and the detected surface waters, about 30,000 people are potentially exposed or living close to flooded areas. The potentially exposed population is mainly located in the Region 6 with ~10,000 people and Region 2 & 5 with ~6,000 people each. This is a preliminary analysis that has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • Time Period of the Dataset [?]: June 10, 2021-June 10, 2021 ... More
    Modified [?]: 18 February 2022
    Dataset Added on HDX [?]: 18 February 2022
    This dataset updates: Never
    UNOSAT code: FL20210520GUY This map illustrates satellite-detected surface waters along the Mazaruni river in Cuyuni-Mazaruni Region of Guyana as observed from RCM-2 radar image acquired on 09 June 2021 at 22:17 UTC. Within the analyzed area of about 700 km2, a total of about 4 km2 of lands were observed as flooded. This is a preliminary analysis that has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT. Important note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.
  • Time Period of the Dataset [?]: June 08, 2021-June 08, 2021 ... More
    Modified [?]: 18 February 2022
    Dataset Added on HDX [?]: 18 February 2022
    This dataset updates: Never
    UNOSAT code: FL20210520GUY This map illustrates satellite-detected surface waters along the Berbice river in Upper Demerara-Berbice Region of Guyana as observed from RCM-2 radar image acquired on 07 June 2021 at 22:21 UTC. Within the analyzed area of about 38,000 ha, a total of about 48 ha of lands were observed as flooded. This is a preliminary analysis that has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT. Important note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.
  • Time Period of the Dataset [?]: June 07, 2021-June 07, 2021 ... More
    Modified [?]: 18 February 2022
    Dataset Added on HDX [?]: 18 February 2022
    This dataset updates: Never
    UNOSAT code: FL20210520GUY This map illustrates cumulative floods using NOAA20-VIIRS data in Guyana between the 2nd and the 6th of June 2021. Within the analyzed cloud free zones of about 200,000 km2, a total of about 5,000 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 80,000 people are potentially exposed or living close to flooded areas. The potentially exposed population is mainly located in the Region 6 with ~22,000 people, Region 3 with ~19,000 and Region 5 with ~15,000 people. This is a preliminary analysis that has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • 50+ Downloads
    Time Period of the Dataset [?]: December 23, 2015-December 23, 2015 ... More
    Modified [?]: 30 October 2018
    Dataset Added on HDX [?]: 23 December 2015
    This dataset updates: Never
    This dataset is part of the data series [?]: HDX - Daily Summaries of Precipitation Indicators
    This dataset contains the daily summaries on base stations across Guyana. The four indicators included are: * TPCP: Total precipitation * MXSD: Maximum snow depth * TSNW: Total snow fall * EMXP: Extreme maximum daily precipitation Indicators are compiled by the National Centers for Environmental Information (NCEI), which is administrated by National Oceanic and Atmospheric Administration (NOAA) an organization part of the United States government. NOAA has access to data collected from thousands of base stations around the world, which collect data periodically on weather and climate conditions. This dataset contains the latest 5 years of available data.
  • 50+ Downloads
    Time Period of the Dataset [?]: January 01, 1950-December 31, 2050 ... More
    Modified [?]: 28 September 2018
    Dataset Added on HDX [?]: 28 September 2018
    This dataset updates: Never
    The urban indicators data available here are analyzed, compiled and published by UN-Habitat’s Global Urban Observatory which supports governments, local authorities and civil society organizations to develop urban indicators, data and statistics. Urban statistics are collected through household surveys and censuses conducted by national statistics authorities. Global Urban Observatory team analyses and compiles urban indicators statistics from surveys and censuses. Additionally, Local urban observatories collect, compile and analyze urban data for national policy development. Population statistics are produced by the United Nations Department of Economic and Social Affairs, World Urbanization Prospects.
  • 100+ Downloads
    Time Period of the Dataset [?]: September 15, 2016-September 15, 2016 ... More
    Modified [?]: 23 September 2016
    Dataset Added on HDX [?]: 23 September 2016
    This dataset updates: Never
    Epidemiological update on Zika Virus, week of 15 September 2016
  • 30+ Downloads
    Time Period of the Dataset [?]: December 31, 2015-December 31, 2015 ... More
    Modified [?]: 29 January 2016
    Dataset Added on HDX [?]: 14 January 2016
    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.