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:
smoothness
oneway
width
surface
bridge
highway
lanes
name
source
layer
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
Updated
June 29, 2020
| Dataset date: Jan 1, 2000-Dec 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.
A description of the modelling methods used for age and sex structures can be found in
Tatem et al and
Pezzulo et al.
The 'Unconstrained global per country 2000-2020' datasets represent the outputs from a project focused on construction of
consistent 100m resolution population count datasets for all countries of the World for each year 2000-2020 structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency.
These are produced using the unconstrained top-down modelling method.
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/WP00646
Updated
April 29, 2020
| Dataset date: Jan 1, 1990-Dec 31, 2017
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'.
Updated
September 28, 2018
| Dataset date: Jan 1, 1950-Dec 31, 2050
This dataset updates: Every year
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.
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.
