In the humanitarian sphere, having reliable population data is crucial for prioritizing life-saving activities. It used to be a challenge if you were looking for a publicly available population density dataset. It was even more of a challenge if you needed global data of even quality. Making population data available helps Humanitarian organizations such as the Humanitarian OpenStreetMap Team and Canadian Red Cross figure out blank spots on maps or get more info on local OSM communities when combined with other datasets. That’s how we came up with building the Kontur Population dataset and visualized into population density map.
World population density map
The world population density map shows the distribution of people across the globe, with higher population densities typically concentrated in urban areas and lower densities in rural areas.
Kontur population dataset
Kontur Population dataset is represented by H3 hexagons with population counts at 400m resolution. The reason why we use H3 grid instead of the common square grid is that unlike squares, hexagons have equal distances between a hexagon centerpoint and the centers of neighboring cells. This property greatly simplifies performing analysis and smoothing over gradients.
Population calculations are based on the Global Human Settlement Layer (GHSL) – a framework relying on a large set of sensors, including radar and optical public and commercial missions.
GHSL data is overlaid with Facebook population data (HRSL) where available.
Microsoft Building Footprint, Land Information New Zealand, and Copernicus Global Land Service data are used to improve distribution accuracy.
Improving data accuracy
Known artifacts of GHSL and HRSL datasets are constrained using OpenStreetMap data. Building presence, or otherwise built-up area, implies there’s someone on the ground, which is often missed in Facebook Africa data. Quarries and big roads are marked as unpopulated, as they are often falsely detected as populated in GHSL. Lakes, rivers, glaciers, sands, forests, and other alike land uses are marked as unpopulated.
While the population total is accurate, extremely populated cells (i.e., 500,000 people in .25 km²) are spread out to neighboring cells to satisfy constraints. Non-integer population counts are rounded to integers.
The latest version of Kontur Population is available at data.humdata.org.
The dataset was primarily designed to support visualization behind Disaster Ninja. The tool is actively used by humanitarian mappers to take action confidently based on data correlated with world population density. Read how data correlated with global population density helps support the rapid deployment of emergency mapping campaigns for Humanitarian OpenStreetMap Team.
Waste management optimization
Kontur team wanted to apply our geospatial expertise to solving local environmental challenges. We teamed up with volunteers in Batumi to help them approach the problem of litter that pollutes streets, parks, rivers, and beaches within the city. We created a bivariate choropleth map to visualize the waste bin availability along with population density within one layer.
Commercial site selection
Using geospatial data analysis significantly reduces the time it takes to find the best location when starting a new business. Reliable population data is a crucial part of such analysis. Read how we used Machine Learning algorithms to detect building footprints from satellite imagery and create a custom population dataset for a site selection project in Abu Dhabi.
Emergency service coverage
We used Kontur Population as the baseline dataset to create a Fire Service Scarcity Risk map to help cities visualize their ability to protect citizens from fire. When planning fire services, it is crucial to know the total population and its distribution within a city. In addition, data on the population of the area surrounding the city is also important since the fringe areas may become part of the city.
Population data is applicable for visualization and insight extraction in various domains. Kontur Population became one of the daily topics of #30DayMapChallenge on Twitter. Hundreds of participants use the data to create maps to visualize climate change, flood risk, water security, access to emergency services, and other topics.
Viral population density maps
If you’re interested in geodata and data visualization, you can’t help but notice worldwide population density maps going viral and getting hundreds of thousands of views on social media. Many enthusiasts use Kontur Population data to create such maps, which get noticed by media outlets like Colossal.
Building local population maps
Local population density maps are crucial for city planners and policymakers to make informed decisions about infrastructure, public services, and emergency management. Real estate professionals also rely on these maps to identify trends and make informed decisions about property values and investments.
How to use
Kontur Population is available under Creative Commons Attribution International (CC BY) license. You can use it for any purpose, even commercially.
The latest version of Kontur Population is available at United Nations Humanitarian Data Exchange (HDX). There are three resolution versions available to download:
– Global Population Density for 400m H3 Hexagons (6.6 GB)
– Global Population Density for 3km H3 Hexagons (169 MB)
– Global Population Density for 22km H3 Hexagons (6 MB)
We also publish per-country subsets of Kontur Population at 400m resolution.
If you need some custom processing or a higher-resolution version of this dataset, please get in touch with us.