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  • Updated 18 February 2022 | Dataset date: July 05, 2021-July 05, 2021
    This dataset updates: Never
    UNOSAT code: FL20210630NPL This map illustrates satellite-detected flash floods and landslides in Melamchi village, Melamchi Municipality, Bagmati province, Nepal as observed using Sentinel-2 satellite imagery acquired on 24 June 2021. Within the analyzed area, approximately 150 structures appear to be potentially affected by the landslides. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (UNOSAT).
  • Updated 18 February 2022 | Dataset date: July 05, 2021-July 05, 2021
    This dataset updates: Never
    UNOSAT code: FL20210630NPL This map illustrates satellite-detected surface waters in Province 2, Lumbini, Gandaki,and Bagmati provinces , Nepal as observed from a Sentinel-1 image acquired on 3 July 2021 at 01:37 local time and using an automated analysis with Artificial Intelligence based methods. Within the analyzed area of about 17,000 km2 and, about 830km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters in the analyzed area, the potentially exposed population is mainly located in the district of Parsa with ~386,000 people, Rautahat with ~221,500 people, Rupandehi with~148,800, and Bara with ~148,200 people. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (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.
  • Updated 18 February 2022 | Dataset date: July 06, 2021-July 06, 2021
    This dataset updates: Never
    UNOSAT code: FL20210630NPL This map illustrates satellite-detected surface waters in Province 1, Nepal as observed from a Sentinel-1 image acquired on 4 July 2021 at 05:48 local time and using an automated analysis with Machine learning method. Within the analyzed area of 4,060 km2, about 240 km2 of lands appear to be flooded. The water extent appears to have decreased of about 200 km2 since 1 July 2021 and moved toward India. Based on Worldpop population data and the detected surface waters in the analyzed area, the potentially exposed population is mainly located in the district of Sunsari with ~186,000 people, Morang with ~83,600 people, and Jhapa with ~21,700 people. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (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.
  • Updated 18 February 2022 | Dataset date: July 02, 2021-July 02, 2021
    This dataset updates: Never
    UNOSAT code: FL20210630NPL This map illustrates satellite-detected surface waters in Province 1 and 2 as observed from a Sentinel-1 image acquired on 1 July 2021 at 05:58 local time and using an automated analysis with Artificial Intelligence based methods. Within the analyzed area of about 110,000 km2 and, about 645km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters in the analyzed area, about 700,000 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 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.
  • 4800+ Downloads
    Updated 16 February 2022 | Dataset date: January 01, 2019-December 31, 2021
    This dataset updates: As needed
    This page provides the data published in the Attacks on Health Care Monthly News Brief. For data supporting the Safeguarding Health in Conflict Coalition (SHCC), please see: https://data.humdata.org/dataset/shcchealthcare-dataset These datasets covers events where health workers were killed, kidnapped or arrested (KKA) and incidents where health facilities were damaged or destroyed by a perpetrator including state and non-state actors, criminals, individuals, students and other staff members in 2019 and in 2020 to date. All data contains incidents identified in open sources. Categorized by country and with links to relevant Monthly News Brief.
  • 6100+ Downloads
    Updated 15 February 2022 | Dataset date: January 01, 2017-December 31, 2021
    This dataset updates: As needed
    This page provides the data published in the Education in Danger Monthly News Brief. All data contains incidents identified in open sources. Categorized by country and with link to the relevant Monthly News Brief (where possible).
  • 15000+ Downloads
    Updated 11 February 2022 | Dataset date: April 01, 2021-August 15, 2022
    This dataset updates: As needed
    The Relative Wealth Index predicts the relative standard of living within countries using de-identified connectivity data, satellite imagery and other nontraditional data sources. The data is provided for 93 low and middle-income countries at 2.4km resolution. Please cite / attribute any use of this dataset using the following: Microestimates of wealth for all low- and middle-income countries Guanghua Chi, Han Fang, Sourav Chatterjee, Joshua E. Blumenstock Proceedings of the National Academy of Sciences Jan 2022, 119 (3) e2113658119; DOI: 10.1073/pnas.2113658119 More details are available here: https://dataforgood.fb.com/tools/relative-wealth-index/ Research publication for the Relative Wealth Index is available here: https://www.pnas.org/content/119/3/e2113658119 Press coverage of the release of the Relative Wealth Index here: https://www.fastcompany.com/90625436/these-new-poverty-maps-could-reshape-how-we-deliver-humanitarian-aid An interactive map of the Relative Wealth Index is available here: http://beta.povertymaps.net/
  • 3200+ Downloads
    Updated 14 January 2022 | Dataset date: September 21, 2020-September 21, 2020
    This dataset updates: Every year
    This data contains aggregated weighted statistics at the regional level by gender for the 2020 Survey on Gender Equality At Home as well as the country and regional level for the 2021 wave. The Survey on Gender Equality at Home generates a global snapshot of women and men’s access to resources, their time spent on unpaid care work, and their attitudes about equality. Researchers and nonprofits interested in access to survey microdata can apply at: https://dataforgood.facebook.com/dfg/tools/survey-on-gender-equality-at-home
  • 80+ Downloads
    Updated Live | Dataset date: January 01, 2019-December 31, 2020
    This dataset updates: Live
    This dataset contains the following administrative boundaries: ADM0, ADM1, ADM2, ADM3. Produced and maintained since 2017, the geoBoundaries Global Database of Political Administrative Boundaries Database www.geoboundaries.org is an open license, standardized resource of boundaries (i.e., state, county) for every country in the world.
  • 19000+ Downloads
    Updated 15 December 2021 | Dataset date: October 13, 2021-October 13, 2021
    This dataset updates: As needed
    We use an anonymized snapshot of all active Facebook users and their friendship networks to measure the intensity of connectedness between locations. The Social Connectedness Index (SCI) is a measure of the social connectedness between different geographies. Specifically, it measures the relative probability that two individuals across two locations are friends with each other on Facebook. Details on the underlying data and the construction of the index are provided in the “Facebook Social Connectedness Index - Data Notes.pdf” file. Please also see https://dataforgood.fb.com/ as well as the associated research paper “Social Connectedness: Measurement, Determinants and Effects,” published in the Journal of Economic Perspectives (https://www.aeaweb.org/articles?id=10.1257/jep.32.3.259). Region identifiers are taken from GADM v2.8 https://gadm.org/download_country_v2.html. Future versions will update IDs to be compatible with the newest GADM version.
  • 100+ Downloads
    Updated 14 December 2021 | Dataset date: October 07, 2021-October 15, 2022
    This dataset updates: Every year
    This table contains subnational multidimensional poverty data from the data tables published by the Oxford Poverty and Human Development Initiative (OPHI), University of Oxford. The global Multidimensional Poverty Index (MPI) measures multidimensional poverty in over 100 developing countries, using internationally comparable datasets and is updated annually. The measure captures the severe deprivations that each person faces at the same time using information from 10 indicators, which are grouped into three equally weighted dimensions: health, education, and living standards. The global MPI 2021 methodology is detailed in Alkire, Kanagaratnam & Suppa (2021).
  • Updated 10 October 2021 | Dataset date: November 24, 2020-February 09, 2021
    This dataset updates: Never
    The UNHCR Standardized Expanded Nutrition Surveys (SENS) provide regular nutrition data that play a key role in delivering effective and timely interventions to ensure good nutritional outcomes among populations affected by forced displacement. This survey was conducted in October 2018 in Beldangi and Sanischare Refugee Camps Nepal to measure the nutrition status of Bhutanese refugees, located in Province 1, Jhapa and Morang Districts. At the time of the survey, there were 6,656 refugees living in both camps, following a large resettlement programme in previous years. UNHCR and partners work in consultation with the local government to increase refugees’ access to nearby government health facilities to achieve sustainable and adequate health services for both refugees and local communities. The nutrition programme was discontinued from the camps in 2016 considering the camp stability, population reduction and improved nutrition status. The main objective of the nutrition survey was to assess the prevalence of malnutrition and anaemia in children aged 6-59 months and anaemia prevalence in non-pregnant women 15-49 years old and formulate workable recommendations for appropriate nutritional and public health interventions. Additional data was collected on coverage of vitamin A supplementation, deworming, supplementary feeding programme, antenatal care program and Infant and young child feeding (IYCF) practicesin the camps.
  • Updated 10 October 2021 | Dataset date: July 13, 2021-September 09, 2021
    This dataset updates: Never
    The COVID-19 Socioeconomic-/Cash-Based Intervention Post-Distribution Monitoring (CBI PDM) was conducted in September 2021 to assess the needs of the refugees in Eastern Nepal and Kathmandu. The survey consists of two parts. The first part of the survey measures the impact of COVID-19 on refugees' knowledge, behavior and health as well as refugees' economic livelihoods and the second part monitors the latest cash assistance programme. As a response to COVID-19, UNHCR has since the start of the pandemic launched multiple new cash grants and expanded existing programs. UNHCR's cash assistance complements governments' efforts by contributing with an additional safety net for vulnerable refugees and others left behind. Also during the course of 2021, UNHCR has continued to support the COVID-19 emergency response with cash assistance. UNHCR uses PDM as a mechanism to collect refugees' feedback on the quality, sufficiency, utilization and effectiveness of the assistance items they receive. In order to ensure that the cash assistance provided meets the intended programme objectives and that desired outcomes are achieved, UNHCR conducts regular post-distribution and outcome monitoring with a sample or all of the recipients.
  • 13000+ Downloads
    Updated 22 August 2021 | Dataset date: January 01, 1990-August 15, 2021
    This dataset updates: Never
    This no longer updated dataset contains Global Food Prices data from the World Food Programme covering foods such as maize, rice, beans, fish, and sugar for 76 countries and some 1,500 markets. It is updated weekly but contains to a large extent monthly data. The data goes back as far as 1992 for a few countries, although many countries started reporting from 2003 or thereafter.
  • 1900+ Downloads
    Updated 4 August 2021 | Dataset date: January 01, 1970-December 31, 2019
    This dataset updates: Every three months
    Education indicators for Nepal. Contains data from the UNESCO Institute for Statistics bulk data service covering the following categories: National Monitoring (made 2021 March), SDG 4 Global and Thematic (made 2021 March), Demographic and Socio-economic (made 2021 March)
  • 300+ Downloads
    Updated 4 August 2021 | Dataset date: August 01, 2020-August 15, 2022
    This dataset updates: As needed
    The COVID-19 preventative health survey is designed to help policymakers and health researchers better monitor and understand people’s knowledge, attitudes and practices about COVID-19 to improve communications and their response to the pandemic.
  • Updated 28 July 2021 | Dataset date: November 01, 2017-November 01, 2017
    This data is by request only
    This data is the collection of perception of people affected by earthquake in Nepal. The data is collected in 14 district of Nepal which has more than sixty percent of damage level by earthquake in 2015. The total of 2100 people are surveyed in various VDC of the district.
  • 500+ Downloads
    Updated 18 July 2021 | Dataset date: January 01, 2000-December 31, 2020
    This dataset updates: Every year
    Food Security Indicators for Nepal. Contains data from the FAOSTAT bulk data service.
  • Updated 4 July 2021 | Dataset date: November 24, 2020-February 09, 2021
    This dataset updates: Never
    THE CBI Covid PDM Household Survey was conducted in Nepal from November, 2020 to February, 2021. In Nepal, UNHCR has supported the Covid-19 response in multiple sectors in 2020, such as Cash-Based Interventions. One of the main findings of the survey was that almost a third of the households answered that they were currently not able to meet basic needs of the households, even though alll of them had benefitted from interventions earlier. UNHCR uses Post-Distribution Monitoring (PDM) as a mechanism to collect refugees' feedback on the quality, sufficiency, utilization and effectiveness of the assistance items they receive. The underlying principle behind the process is linked to accountability, as well as a commitment to improve the quality and relevance of support provided, and related services. UNHCR increasingly uses Cash-Based Interventions (CBIs) as a preferred modality for delivering assistance, offering greater dignity and choice to forcibly displaced and stateless persons in line with UNHCR's core protection mandate. In order to ensure that the cash assistance provided meets the intended programme objectives and that desired outcomes are achieved, UNHCR conducts regular post-distribution and outcome monitoring with a sample or all of refugee recipients.
  • 200+ Downloads
    Updated 4 May 2021 | Dataset date: January 01, 1990-December 31, 2030
    This dataset updates: Every year
    The aim of the Human Development Report is to stimulate global, regional and national policy-relevant discussions on issues pertinent to human development. Accordingly, the data in the Report require the highest standards of data quality, consistency, international comparability and transparency. The Human Development Report Office (HDRO) fully subscribes to the Principles governing international statistical activities. The HDI was created to emphasize that people and their capabilities should be the ultimate criteria for assessing the development of a country, not economic growth alone. The HDI can also be used to question national policy choices, asking how two countries with the same level of GNI per capita can end up with different human development outcomes. These contrasts can stimulate debate about government policy priorities. The Human Development Index (HDI) is a summary measure of average achievement in key dimensions of human development: a long and healthy life, being knowledgeable and have a decent standard of living. The HDI is the geometric mean of normalized indices for each of the three dimensions. The 2019 Global Multidimensional Poverty Index (MPI) data shed light on the number of people experiencing poverty at regional, national and subnational levels, and reveal inequalities across countries and among the poor themselves.Jointly developed by the United Nations Development Programme (UNDP) and the Oxford Poverty and Human Development Initiative (OPHI) at the University of Oxford, the 2019 global MPI offers data for 101 countries, covering 76 percent of the global population. The MPI provides a comprehensive and in-depth picture of global poverty – in all its dimensions – and monitors progress towards Sustainable Development Goal (SDG) 1 – to end poverty in all its forms. It also provides policymakers with the data to respond to the call of Target 1.2, which is to ‘reduce at least by half the proportion of men, women, and children of all ages living in poverty in all its dimensions according to national definition'.
  • 200+ Downloads
    Updated 15 April 2021 | Dataset date: March 01, 2020-December 31, 2020
    This dataset updates: Every three months
    Under the leadership of UNDP and DCO, an inter-agency task team developed the UN framework for the immediate socio-economic response to COVID-19 (adopted in April 2020) to govern its response over 12 to 18 months. To measure the UN’s support to the socio-economic response and recovery, UN entities developed a simple monitoring framework with 18 programmatic indicators (endorsed by the UNSDG in July 2020). Lead entities – based on their mandate and comparative advantage – were nominated to lead the development of methodological notes for each indicator and lead the collection of data at the country level. These lead entities reported through the Office of the Resident Coordinators the collective UN results on a quarterly basis through UN Info. All 2020 data was reported by March 2021. This is the UN development system’s first comprehensive attempt at measuring its collective programming contribution and results. These programmatic indicators enabled the UN system to monitor the progress and achievements of UNCT’s collective actions in socio-economic response. In support of the Secretary-General’s call for a "… single, consolidated dashboard to provide up-to-date visibility on [COVID-19] activities and progress across all pillars” all data was published in real time on the COVID-19 data portal, hosted by DCO. The data is disaggregated by geography (rural/urban), sex, age group and at-risk populations -- to measure system-wide results on the socio-economic response to the pandemic, in order to ensure UNDS accountability and transparency for results.
  • 50+ Downloads
    Updated 5 April 2021 | Dataset date: May 05, 2020-May 05, 2020
    This dataset updates: Never
    This data was developed as part of the Modelling Exposure Through Earth Observation Routines (METEOR) project and is a Level 1, or a global-quality exposure data set. Minimal country-specific data was collected. The data is intended for CAT modeling and loss estimation. Repurposing this data for any reason other than assessing risk is not recommended. The data presents the estimated number of buildings, building area, and rebuilding value at a 15-arcsecond grid resolution (approximately 500 meters at the equator). This data set is in point shapefile format where the points represent the centroids of the 15-arcsecond grid. The results were created through a process of spreading the number of buildings to the 15-arcsecond level by a statistical assessment of moderate resolution EO data, which is described in more detail in the dasymetric mapping lineage processing step. The estimated building count at any given area is a result of statistical processes and should not be mistaken as a building count. The structural classes of buildings used for risk assessment are estimated given the building wall, floor, and roof material classes surveyed through 2002 Population and Housing Census - Volume 1. Analytical report. Additionally, the data is provided in Open Exposure Data (OED) import format, as a pair of CSV files. One CSV file contains the location details, and the other is an "account" file that is filled with default information to satisfy OED format requirements. The OED input files are set to use "All perils" (i.e. "AA1"). All required OED account-related fields are populated with "1" by default (such as PortNumber, AccNumber, PolNumber). If you find this data useful please provide feedback via our questionnaire; it should take only a few minutes: https://forms.gle/DQjhE89CRegNKB3X8 Please see the METEOR project page for information about the METEOR Project: http://meteor-project.org/ Please see the METEOR map portal for interactive maps: https://maps.meteor-project.org/ For more information about the Open Exposure Data (OED) standard, please see https://github.com/OasisLMF/OpenDataStandards
  • 100+ Downloads
    Updated 24 November 2020 | Dataset date: January 01, 2000-December 31, 2020
    This dataset updates: Every year
    WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km at the equator) -Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area. These are produced using the unconstrained top-down modelling method. -Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population UN adjusted count datasets by dividing the number of people in each pixel, adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area. These are produced using the unconstrained top-down modelling method. Data for earlier dates is available directly from WorldPop. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00674
  • 300+ Downloads
    Updated 24 November 2020 | Dataset date: January 01, 2000-December 31, 2020
    This dataset updates: Every year
    WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. Bespoke methods used to produce datasets for specific individual countries are available through the WorldPop Open Population Repository (WOPR) link below. These are 100m resolution gridded population estimates using customized methods ("bottom-up" and/or "top-down") developed for the latest data available from each country. They can also be visualised and explored through the woprVision App. The remaining datasets in the links below are produced using the "top-down" method, with either the unconstrained or constrained top-down disaggregation method used. Please make sure you read the Top-down estimation modelling overview page to decide on which datasets best meet your needs. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 3 and 30 arc-seconds (approximately 100m and 1km at the equator, respectively): - Unconstrained individual countries 2000-2020 ( 1km resolution ): Consistent 1km resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020. - Unconstrained individual countries 2000-2020 ( 100m resolution ): Consistent 100m resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020. - Unconstrained individual countries 2000-2020 UN adjusted ( 100m resolution ): Consistent 100m resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020 and adjusted to match United Nations national population estimates (UN 2019) -Unconstrained individual countries 2000-2020 UN adjusted ( 1km resolution ): Consistent 1km resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020 and adjusted to match United Nations national population estimates (UN 2019). -Unconstrained global mosaics 2000-2020 ( 1km resolution ): Mosaiced 1km resolution versions of the "Unconstrained individual countries 2000-2020" datasets. -Constrained individual countries 2020 ( 100m resolution ): Consistent 100m resolution population count datasets created using constrained top-down methods for all countries of the World for 2020. -Constrained individual countries 2020 UN adjusted ( 100m resolution ): Consistent 100m resolution population count datasets created using constrained top-down methods for all countries of the World for 2020 and adjusted to match United Nations national population estimates (UN 2019). Older datasets produced for specific individual countries and continents, using a set of tailored geospatial inputs and differing "top-down" methods and time periods are still available for download here: Individual countries and Whole Continent. Data for earlier dates is available directly from WorldPop. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00645
  • 15000+ Downloads
    Updated 17 November 2020 | Dataset date: November 17, 2020-August 15, 2022
    This dataset updates: Every year
    Nepal administrative level 0-2 and district (un-numbered) boundaries Vetting and live service provision by Information Technology Outreach Services (ITOS) with funding from USAID. See caveats