Ethiopia population data

This data set has been collected from official databases and contains: 1- Youth Population (15-35) for 2018 and 2063 2- Proportion of Youth Members of Parliaments (Lower and Upper house) 3- Ratification of African Youth Charter 4- Existence of Youth Policy

Open and free data for assessing the human presence on the planet. The Global Human Settlement Layer (GHSL) project produces global spatial information, evidence-based analytics, and knowledge describing the human presence on the planet. The GHSL relies on the design and implementation of spatial data processing technologies that allow automatic data analytics and information extraction from large amounts of heterogeneous geospatial data including global, fine-scale satellite image data streams, census data, and crowd sourced or volunteered geographic information sources. The JRC, together with the Directorate-General for Regional and Urban Policy (DG REGIO) and Directorate-General for Defence Industry and Space (DG DEFIS) are working towards a regular and operational monitoring of global built-up and population based on the processing of Sentinel Earth Observation data produced by European Copernicus space program. In addition, the EU Agency for the Space Programme (EUSPA) undertakes activities related to user uptake of data, information and services.

Settlements and residential areas: named cities, towns, villages, suburbs, and residential land (`place=*` and `landuse=residential`). Useful for demographic context, settlement-level targeting, and population analysis. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: place, landuse - Part of the country exports on HDX by HOT

The household income index of the different cluster numbers in Ethiopia from the Demographic Health Survey , 2016 -    from Low income per household to High household income per cluster - at a resolution of about 5000 metres

The computed dataset represents the credit services , in the different clusters and households which was computed  as a result of the mode per cluster at a resolution of about 5000 metres , from the DHS , 2016

Ethiopia household members per cluster entails the average household members per cluster (645 Clusters According to the 2016 DHS data - with a Spatial  Resolution of 0.05 pixels about 5000 metres

Sex of the Household Head in Ethiopia - Computed from the different clusters in Ethiopia - from the Demographic Health Survey (DHS) standard datasets of 2016 - This is the average Household head per cluster which has the (Male and Female )  with a resolution of 0.05pixels approximately 5000 metres  referenced (2016)

This dataset represents the estimated population density of Ethiopia in the year 2020 , expressed as the number of people per square kilometer. It is intended to support spatial analysis and decision-making in areas such as disaster risk reduction, resource allocation, development planning, and vulnerability assessment Source - WORLDPOP Relationship to Exposure- (Positive)-   The higher the population, the higher the exposure

Spatial distribution of the population of Ethiopia, showing where people live and in what densities across the country. Use this layer for understanding settlement patterns, sizing infrastructure, planning service delivery, and conducting demographic analysis.

[Initial analysis] The database contains information about buildings identified by Google outside of settlements recognized by GRID3. It serves as a proxy for identifying potential new settlements or areas of urban growth. The analysis incorporates two levels of clustering: one at a distance of 500 meters and another at 100 meters. The 500-meter clustering helps identify broader areas where multiple buildings are concentrated, potentially indicating the presence of a new settlement or an expansion of an existing one. This distance threshold allows for the initial identification of potential new settlement areas. The 100-meter clustering provides a more granular view, highlighting tighter clusters of buildings within the broader 500-meter areas. This finer level of clustering aids in distinguishing individual settlement units or neighborhoods within the larger potential settlement areas. By combining these two levels of clustering, the database facilitates a comprehensive analysis of potential new settlements or urban growth areas. It enables researchers, urban planners, and policymakers to identify and prioritize areas for further investigation, resource allocation, or development planning.

The GRID3 ETH - Settlement Extents v3.0 consists of a geographic representation of settlements in Ethiopia. Data inputs and methodology are described in data release notes available at GRID3 ETH - Settlement Extents v3.0 3iS has enhanced the settlement dataset by integrating administrative attributes from a shapefile at the Admin 3 level. This process involved associating settlements with the corresponding administrative divisions, including the following attributes: - Admin 1 (Region) Names and P-codes: Identifying the broader regions where settlements are located. - Admin 2 (Zone) Names and P-codes: Associating zones within regions to each settlement. - Admin 3 (Woreda) Names and P-codes: Providing detailed locality-level information.

This dataset contains administrative polygons grouped by country (admin-0) with the following subdivisions according to Who's On First placetypes: - macroregion (admin-1 including region) - region (admin-2 including state, province, department, governorate) - macrocounty (admin-3 including arrondissement) - county (admin-4 including prefecture, sub-prefecture, regency, canton, commune) - localadmin (admin-5 including municipality, local government area, unitary authority, commune, suburb) The dataset also contains human settlement points and polygons for: - localities (city, town, and village) - neighbourhoods (borough, macrohood, neighbourhood, microhood) The dataset covers activities carried out by Who's On First (WOF) since 2015. Global administrative boundaries and human settlements are aggregated and standardized from hundreds of sources and available with an open CC-BY license. Who's On First data is updated on an as-need basis for individual places with annual sprints focused on improving specific countries or placetypes. Please refer to the README.md file for complete data source metadata. Refer to our blog post for explanation of field names. Data corrections can be proposed using Write Field, an web app for making quick data edits. You’ll need a Github.com account to login and propose edits, which are then reviewed by the Who's On First community using the Github pull request process. Approved changes are available for download within 24-hours. Please contact WOF admin about bulk edits.

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From the Demographic Health Survey ( DHS) this is the dataset for mobile ownership per cluster in the mode using the different Households - at the resolution of 5000 metres referenced ( 2016)

A gridded raster of population distribution for Ethiopia, with cell values representing population counts. It covers the year 2030 and is published by WorldPop (University of Southampton).

Gridded raster of population distribution for Ethiopia, with cell values measuring population. Published by WorldPop (University of Southampton). The data cover Ethiopia for the year 2030.