Zambia population data

This dataset presents a fine-grained population map of Zambiawith a resolution of 100 meters for 2020, generated using the POMELO super-resolution technique that is based on deep learning. Please refer to our Nature Scientific Reports publication for more details. Background: Traditionally, many countries, including those in sub-Saharan Africa, rely on aggregated census data over expansive spatial units, which are not always timely or accurate. The need for detailed population maps is paramount in several sectors, including urban development, environmental supervision, public health, and humanitarian initiatives. Addressing this gap, the POMELO methodology leverages coarse census data in conjunction with open geodata to produce high precision population maps. Key Features: Resolution: The map offers a granular view with a 100m ground sampling distance, providing intricate details about population distributions in Zambia. Data Sources: Utilizing a combination of projected admisistrative census data (UN), and supplementing it with open geodata. Reliability: In comparative experiments conducted in sub-Saharan Africa, POMELO's ability to disaggregate coarse census counts achieved R2 values of 85-89%. Furthermore, its potential to predict population numbers without any census data reached accuracy levels of 48-69%.

These data were produced by the WorldPop Research Group at the University of Southampton. This work is part of the GRID3 (Geo-Referenced Infrastructure and Demographic Data for Development) project funded by the Bill and Melinda Gates Foundation (BMGF) and the United Kingdom’s Department for International Development (OPP1182408). Project partners include WorldPop at the University of Southampton, the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation. The Zambia Statistics Agency supported and facilitated this work, and provided the household survey datasets. The modelling work was led by Claire A. Dooley with support from Douglas R. Leasure. Geospatial data processing was carried out by Heather R. Chamberlain, Claire A. Dooley and Oliver Pannell. Coordination and stakeholder engagement was led by Heather R. Chamberlain and Claire A. Dooley with support from Polly Marshall. Oversight was provided by Andrew J. Tatem and Attila N. Lazar. Note, these data are operational population estimates and are not official government statistics For further details, please, read ZMB_population_v1_0_README.pdf __Recommended citation__ _WorldPop (School of Geography and Environmental Science, University of Southampton). 2020. Bottom-up gridded population estimates for Zambia, version 1.0. https://dx.doi.org/10.5258/SOTON/WP00662_

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

Spatial distribution of the population of Zambia, 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.

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.

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.

No description yet.

No description yet.

No description yet.

No description yet.

A gridded raster of population distribution for Zambia, with cell values representing population counts. The data cover the year 2030 and are published by WorldPop (University of Southampton).

Gridded population data for Zambia, published by WorldPop (University of Southampton). Each raster cell measures the spatial distribution of population, with a reference date of 2030.