Population dataset

We build the ultimate publicly available global population dataset by obtaining and processing all available data and fixing all known issues.

It was initially developed as a fundamental part of Disaster Ninja to help Humanitarian OpenStreetMap Team take actions confidently based on data correlated with population density.

Humanitarian OSM Summit 2020: Kontur Population & Disaster.Ninja

Challenge

All maps are population maps’ is no joke if you need to correlate various sorts of social or economic data on your map. 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 Kontur Population dataset.

Solution

The dataset was primarily designed to support visualization behind disaster.ninja project actively used by HOT.

We use Global Human Settlement Layer (GHSL) overlaid with Facebook population data where available. Known artifacts of both are constrained using OpenStreetMap data as a hint. Microsoft Building Footprint data is used to improve accuracy for the USA, Canada, Uganda, and Tanzania.

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. Overly hot pixels (“half a million people in a quarter of square kilometer”) are spread to more realistic surroundings. Totals are not touched in any way; the population is shifted to neighboring cells to satisfy constraints. Non-integer population counts are fixed up by gluing people back together to complete human beings.

Latest version of Kontur Population is available at data.humdata.org.
If you need some custom processing or higher resolution version of this dataset contact us please.

Our other projects
Disaster Ninja

Disaster Ninja lets emergency cartographers prepare mapping tasks in minutes instead of hours.

When a disaster strikes, humanitarian mapping teams face such challenges as choosing the area that needs to be mapped as quickly and accurately as possible. Our interactive dashboard helps save precious time by presenting the event’s details and all available datasets in a succinct, visual form.

Dispatcher 112

Dispatcher 112 app helps dispatchers locate the closest fire stations and send the fire brigades faster to the emergency scene.

The laconic solution includes a typo-proof address search, custom routing algorithm for fire trucks, street length, and roof area measuring tools. The technology works well for the Minsk Fire Dept. and can improve disaster response worldwide.