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  • OCHA FTS
    Updated February 19, 2018 | Dataset date: Feb 19, 2018
    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
    • 1200+ 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.
  • 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.
  • 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.
  • 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 data set contains the location of CiC office in the Rohingya Refugee camps of Kutupalong area under the Palongkhali union of Ukhia Upazila, Cox's Bazar.
  • HDX
    Updated February 14, 2018 | Dataset date: Dec 21, 2017
    Topline figures for the Rohingya Displacement event page
    • CSV
    • 100+ Downloads
    • This dataset updates: Every week
  • The Satellite image (Pléiades ©CNES 2017, Distribution Airbus DS) as of 26 October 2017 converted to .kmz for using through Google Earth on a computer, Earth for Android for easy viewing in the field, OSMNavigator for offline, Google Maps-style real-time GPS position overlay on top of the image, Garmin handheld GPS units etc.
    • zipped kml
    • 100+ Downloads
    • This dataset updates: Every month
  • This dataset is the baseline survey prior to monthly Needs and Population Monitoring assessment Round 8. The baseline survey covers all locations hosting Rohingya population in Cox’s Bazar District in Bangladesh and records the number of Rohingya population by location.
  • This geodatabase contains the outline of the camps, settlements, and sites where Rohingya refugees are staying in Cox's Bazar, Bangladesh.
  • Armed Conflict Location & Event Data Project (ACLED)
    Updated February 6, 2018 | Dataset date: Jan 1, 2015-Dec 31, 2017
    The ACLED project codes reported information on the type, agents, exact location, date, and other characteristics of political violence events, demonstrations and select politically relevant non-violent events. ACLED focuses on tracking a range of violent and non-violent actions by political agents, including governments, rebels, militias, communal groups, political parties, external actors, rioters, protesters and civilians. Data contain specific information on the date, location, group names, interaction type, event type, reported fatalities and contextual notes.
    • CSV
    • This dataset updates: Live
  • This shapefile contains the roads of Kutupalong-Balukhali Rohingya refugee sites including vehicle road, main path, footpath, military constructed Road and Planned roads. Also included existing and planned bridge.
  • UNESCO
    Updated February 1, 2018 | Dataset date: Jan 1, 1970-Dec 31, 2016
    Contains data from UNESCO's data portal covering various indicators.
    • CSV
    • 10+ Downloads
    • This dataset updates: Every year
  • WFP - World Food Programme
    Updated February 1, 2018 | Dataset date: Feb 1, 2018
    This dataset is an extraction of roads from OpenStreetMap data made by WFP following UNSDI-T standards. The data is updated in near-real time from OSM servers and include all latest updates. NOTE: this dataset doesn't include streets and pathways that have been published on a separate dataset (streets and pathways). More documentation on the whole process for extracting OpenStreetMap roads can be found here: http://geonode.wfp.org/documents/6823/download https://geonode.wfp.org/layers/ogcserver.gis.wfp.org%3Ageonode%3Abgd_trs_roads_osm
    • SHP
    • 10+ Downloads
    • This dataset updates: Every day
  • Inter Sector Coordination Group
    Updated January 29, 2018 | Dataset date: Jan 29, 2018
    The dataset contains the location (lat/lon), type, and estimated population of the Rohingya Refugees 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
    • 4400+ Downloads
    • This dataset updates: Every week
  • The flood layer prepared by IOM and UNHCR, combined a mix method: High quality drone imagery from December 2017, was analysed to verify non-usable[1] locations and to determine the extent of their boundaries. A buffer of approximately 2-3 m was added to the outlines of these areas to accommodate the differing conditions during the rainy season. These outlines were then validated onsite and where needed, adjusted to reflect a more realistic flooding scenario, taking inputs from local residents as needed. The onsite verification revealed that in most instances, the assumptions were either accurate or slightly underestimated thus requiring only minor expansion of the boundaries in some cases, but no reductions were made. The main river flood levels, with an enormous and complicated catchment area, was calculated empirically, based upon field measurements taken of high water levels as indicated from people who have lived in the area for over 20 years. The river was surveyed, both in section and longitudinally, and the volume of water was back calculated based on the river arrangement where the high water level was known. For small tributaries, with well-defined and small catchment areas, rainfall intensity data (from International Journal of Scientific & Engineering Research, Volume 6, Issue 5, May 2015) for Chittagong, with a 10 year return period was used to calculate the volume of water. The height of the flood waters for the smaller tributaries was based on the channel sections, the slope and volume of water calculated from the rainfall intensity. Landslide Layer prepared ADPC, UNHCR and IOM: The impact area is calculated based on the fact that slopes of more than 35 degrees have a risk of failure. The slope was calculated based on the DEM dataset at 0.5 meter spatial resolution, gathered by IOM drone imagery. The DEM was adjusted match a geographical point of reference, and trees and buildings removed. The additional area of susceptibility of landslide was extended by manually drawing polygons by UNHCR and ADPC, with the support of DEM topography and contour lines. These polygons are extensions of 40 degrees and above until reaching the base of the respective slope. Spatial analysis was carried out in order to provide the statistical results of the population at risk. Risk Management Criteria and assumptions made: • The crucial landslide trigger factor is pore pressure • The land slide failure would be sudden • When it does fail, it will have an aspect ratio of 1 to 1 • 35 degrees slope and above, a risk of failure • 40 degree slope and above has a 50% chance of failure • 45 degree slope and above 85% chance of failure
    • ZIP
    • 70+ Downloads
    • This dataset updates: Every six months
  • HDX
    Updated January 27, 2018 | Dataset date: Jan 1, 1950-Dec 31, 2050
    Contains data from World Health Organization's data portal covering various indicators (one per resource).
    • CSV
    • 300+ Downloads
    • This dataset updates: Every year
  • HDX
    Updated January 25, 2018 | Dataset date: Jan 1, 2011-Dec 31, 2017
    Data used to update country toplines in HDX. Contains data from World Bank's data portal.
    • CSV
    • 700+ Downloads
    • This dataset updates: Every year
  • HDX
    Updated January 25, 2018 | Dataset date: Jan 1, 1960-Dec 31, 2017
    Contains data from World Bank's data portal covering various economic and social indicators (one per resource).
    • JSON
    • 30+ Downloads
    • This dataset updates: Every year
  • Zipped shapefile containing 1m contour lines for Kutupalong mega camp area including Thangkhali, Hakimpara, Jamtoli and Bagghona/Potibonia. These are created by NPM team of IOM using a UAV of December 2017.
  • Internal Displacement Monitoring Centre (IDMC)
    Updated January 24, 2018 | 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
    • 30+ Downloads
    • This dataset updates: Every year