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  • OCHA ROAP
    Updated September 19, 2017 | Dataset date: Sep 18, 2017
    Data as of September 19, 2017. The dataset contains the location (lat/lon), type, and estimated population of the Undocumented Myanmar Nationals in and around Cox's Bazar, Bangladesh. The dataset is updated regularly. The source is the Inter-Sector Coordination Group in Cox's Bazar.
    • XLS
    • XLSX
    • This dataset updates: Every day
  • OCHA ROAP
    Updated September 19, 2017 | Dataset date: Jan 1, 2015
    This is the full Administrative dataset for Bangladesh. It includes administrative level 0 (nation), 1 (division), 2 (district), 3 (upazila), and 4 (union) polygons and lines. All units have two PCODES. For each administrative level 'X', the 'admXcode_old' is the original 'GEOCODE11' PCODE and the one most commonly used in country. The GEOCODE15 incorporates Mymensingh Division which was created in 2015. Also note that administrative level 4 (union) is available in two versions. One includes inland water areas, the other includes only land areas.
  • OCHA ROAP
    Updated September 19, 2017 | Dataset date: Sep 19, 2017
    This shape file contains the outline of the camps, settlements, and sites where Rohingya refugees are staying in Cox's Bazar, Bangladesh.
    • ZIP
    • This dataset updates: Every week
  • OCHA FTS
    Updated September 19, 2017 | Dataset date: Sep 19, 2017
    FTS publishes data on humanitarian funding flows as reported by donors and recipient organizations. It presents all humanitarian funding to a country and funding that is specifically reported or that can be specifically mapped against funding requirements stated in humanitarian response plans. The data comes from OCHA's Financial Tracking Service, is encoded as utf-8 and the second row of the CSV contains HXL tags.
    • CSV
    • 60+ Downloads
    • This dataset updates: Every day
  • OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: waterway IS NOT NULL OR water IS NOT NULL OR natural IN ('water','wetland','bay') Features may have these attributes: name waterway covered width depth layer blockage tunnel natural water This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: building IS NOT NULL Features may have these attributes: name building building:levels building:materials addr:full addr:housenumber addr:street addr:city office This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: amenity IS NOT NULL OR man_made IS NOT NULL OR shop IS NOT NULL OR tourism IS NOT NULL Features may have these attributes: name amenity man_made shop tourism opening_hours beds rooms addr:full addr:housenumber addr:street addr:city This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • Humanitarian OpenStreetMap Team (HOT)
    Updated September 18, 2017 | Dataset date: Sep 18, 2017
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: highway IS NOT NULL Features may have these attributes: name highway surface smoothness width lanes oneway bridge layer This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • This map illustrates satellite-detected surface water extent in the central and northern parts of Bangladesh using a Sentinel-1 satellite image acquired on the 22 August 2017. The total analysed area is about 4,284,431 ha. In this analysed area; 1,099,369 ha (39%) of lands are likely affected. These lands are mainly cropland irrigated and rainfed areas and estimated to 1,039,350 ha. The population exposure analysis using WorldPop data shows that ~10,000,000 people are potentially affected by floods in the analysed zone: ~5,400,000 are located in Dhaka Division and ~2,750,000 in Rajshahi Division. Please note that for visualization purposes the analyzed area is wider than the extent of this map.This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • This map illustrates satellite-detected surface water extent in the central and southern parts of Bangladesh using a Sentinel-1 satellite image acquired on the 22 August 2017. In the analysed area; 608,747 ha of lands are likely affected. These lands are mainly cropland irrigated and rainfed areas and estimated to 475,000 ha. The population exposure analysis using WorldPop data shows that ~6,400,000 people are potentially affected by floods in the analysed zone: ~2,300,000 are located in Chittagong Division and ~2,170,000 in Dhaka Division. Please note that for visualization purposesanalyzed area is wider than the extent of this map. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • This map illustrates satellite-detected surface water extent in the northern part of Bangladesh using a TerraSAR-X satellite image acquired on the 16 August 2017. In the analysed area; 221,915 ha of lands are likely affected. The population exposure analysis using WorldPop data shows that 2,143,586 people are potentially affected by floods in this analysed zone: ~1,800,000 are located in Rangpur Division and ~280,000 in Dhaka Division. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • WorldPop
    Updated September 6, 2017 | Dataset date: Jan 1, 2015
    These datasets provide estimates of population counts for each 100 x 100m grid cell in the country for various years. Please refer to the metadata file and WorldPop website (www.worldpop.org) for full information.
  • Internal Displacement Monitoring Centre (IDMC)
    Updated September 6, 2017 | Dataset date: Jan 1, 2008-Dec 31, 2016
    Internally displaced persons are defined according to the 1998 Guiding Principles (http://www.internal-displacement.org/publications/1998/ocha-guiding-principles-on-internal-displacement) as people or groups of people who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of armed conflict, or to avoid the effects of armed conflict, situations of generalized violence, violations of human rights, or natural or human-made disasters and who have not crossed an international border. "New Displacement" refers to the number of new cases or incidents of displacement recorded, rather than the number of people displaced. This is done because people may have been displaced more than once. "People Displaced" refers to the number of people living in displacement as of the end of each year. Contains data from IDMC's data portal.
    • JSON
    • This dataset updates: Every day
  • HDX
    Updated September 5, 2017 | Dataset date: Jan 1, 1950-Dec 31, 2050
    Contains data from World Health Organization's data portal covering various indicators (one per resource).
    • CSV
    • This dataset updates: Every year
  • HDX
    Updated September 5, 2017 | Dataset date: Jan 1, 2011-Dec 31, 2016
    Data used to update country toplines in HDX. Contains data from World Bank's data portal.
    • CSV
    • This dataset updates: Every year
  • HDX
    Updated September 5, 2017 | Dataset date: Jan 1, 1960-Dec 31, 2016
    Contains data from World Bank's data portal covering various economic and social indicators (one per resource).
    • JSON
    • This dataset updates: Every year
  • WFP - World Food Programme
    Updated August 21, 2017 | Dataset date: May 13, 2015
    The Food Consumption Score (FCS) dataset is based on the FCS indicator, which assigns a food security score based on food consumption and diets. This data is available sub-nationally for 38 countries, such as Nepal and Sierra Leone.
    • CSV
    • 200+ Downloads
    • This dataset updates: Every month
  • This map illustrates satellite-detected surface water extent in the central part of Bangladesh using a Sentinel-1 satellite image acquired on the 12 August 2017 with a total surface of 4,280,650 ha. In this analyzed area; 1,644,983 ha (38%) of lands are likely affected. These lands are are mainly cropland irrigated and rainfed areas and estimated to 1,576,351 ha. The population exposure analysis using WorldPop data shows that ~17,000,000 people are potentially affected by floods in the analysed zone: ~8,400,000 are located in Dhaka Division and ~5,750,000 in Rajshahi Division. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • In this analysis we have combined several data sources around the floods in Bangladesh in August 2017. Visualization See attached map for a map visualization of this analysis. See http://bit.ly/2uFezkY for a more interactive visualization in Carto. Situation Currently, in Bangladesh many water level measuring stations measure water levels that are above danger levels. This sets in triggers in motion for the partnership of the 510 Data Intitiative and the Red Cross Climate Centre to get into action. Indicators and sources In the attached map, we combined several sources: Locations of waterlevel stations and their respective excess water levels (cms above danger level) at 14/08/2017 (Source: http://www.ffwc.gov.bd/index.php/googlemap?id=20) Population density in Bangladesh to quickly see where many people live in comaprison to these higher water-level stations. (Source: http://www.worldpop.org.uk/data/summary/?doi=10.5258/SOTON/WP00018 >> the People per hectare 2015 UN-adjusted totals file is used.) Vulnerability Index: we constructed a Vulnerability Index (0-10) based on two sources. First poverty incidence was collected from Worldpop (Source: http://www.worldpop.org.uk/data/summary/?doi=10.5258/SOTON/WP00020 >> The estimated likelihood of living below $2.50/day). Second, we used a Deprivation Index which is estimated in the report Lagging District Reports 2015 (Source: http://www.plancomm.gov.bd/wp-content/uploads/2015/02/15_Lagging-Regions-Study.pdf > Appendices > Table 20), which combines many socio-economic variables into one Deprivation Index through PCA analysis. Detailed methodology Vulnerability The above-mentioned poverty source file is on a raster level. This raster level poverty was transformed to admin-4 level geographic areas (source: https://data.humdata.org/dataset/bangladesh-admin-level-4-boundaries), by taking a population-weighted average. (Source population also Worldpop). The district-level PCA components from abovementioned reports were matched to the geodata based on district names, and thus joined to the admin-4 level areas, which now contain a poverty value as well as Deprivation Index value. Note that all admin-4 areas within one district (admin-2) obviously all have the same value. The poverty rates do differ between all admin-4 areas. Lastly, both variables were transformed to a 0-10 score (linearly), and a geomean was taken to calculate the final index of the two. A geomean (as opposed to an arithmetic mean) is often used in calculating composite risk indices, for example in the widely used INFORM-framework (www.inform-index.org).
  • WFP - World Food Programme
    Updated July 26, 2017 | Dataset date: Jul 24, 2017
    The Global Food Prices Database has data on food prices (e.g., beans, rice, fish, and sugar) for 76 countries and some 1,500 markets. The dataset includes around 500,000 records and is updated monthly. The data goes back as far as 1992 for a few countries, although most of the price trends start in 2000-2002.
    • CSV
    • 800+ Downloads
    • This dataset updates: Every month
  • This map illustrates satellite-detected possible damaged shelter structures in Kutupalong Refugee Camp, Palong Khali Union and Cox Bazar District, Chittagong Division, Bangladesh. The UNITAR-UNOSAT analysis used Pleiades satellite imagery acquired the 6th and the 7th June 2017 as post-images. The UNITAR-UNOSAT analysis identified 1,105 possible damaged shelter structures within the extent of the camp. Kindly note that the number of possible shelter damaged structures could have been under or overestimated in some areas due to the cloud cover and the delimitation of the camp extent. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR – UNOSAT.
  • This map illustrates satellite-detected potentially affected shelters in Nayapara refugee camp in Teknaf Union, Cox s Bazar District, and Chittagong Division of Bangladesh. About 12,500 people are registred in this camp. The UNITAR-UNOSAT analysis used a Pleiades satellite image acquired the 05th of June 2017 and could identify 560 possible damaged shelter structures within the extent of the camp. Kindly note that the number of damaged shelters could have been underestimated as some groups of shelter structures might be identified as one structure.This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.
  • This map illustrates satellite-detected potentially affected shelters in Leda refugee camp in Nhilla Union, Cox s Bazar District, and Chittagong Division of Bangladesh. About 18,350 people are registered in this camp. The UNITAR-UNOSAT analysis used a Pleiades satellite image acquired 05 June 2017 and could identify 215 possible damaged shelter structures within the extent of the camp. Kindly note that the number of damaged shelters could have been underestimated as some groups of shelter structures might be identified as one structure. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.
  • This map illustrates the satellite-detected water extent in the District of Chittagong, Chittagong Division, in the southeastern part of Bangladesh after the tropical cyclone Mora-17. The UNITAR-UNOSAT analysis used a Sentinel-1 satellite image acquired on the 30 May 2017 and detected several areas with standing waters. In the district of Chittagong ~4,790 ha are likely flooded and almost 12 km of the local roads seem to be affected. The population exposure analysis using WorldPop data shows that ~70,000 people are potentially affected by floods within map extent. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.
  • This map illustrates satellite-detected surface water extent in the District of Cox's Bazar, Chittagong Division, located in the southeastern part of Bangladesh after the tropical cyclone Mora-17 using a Sentinel-1 satellite image acquired on the 30 May 2017. A total of 23,058 ha surface waters were observed. In many zones, the affected lands are mainly agricultural. The analysis of this image reveals also that about 234 km of roads mainly tertiary roads seem to be potentially affected. The population exposure analysis using WorldPop data shows that ~267,000 people are potentially affected by floods within map extent. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.