Kontur population

Kontur is a geospatial data and real-time risk kontur population solutions provider for business, government and humanitarian organizations. You logged out of HDX. Thank you for using HDX! Not you?

In the humanitarian sphere, having reliable population data is crucial for prioritizing life-saving activities. Yet, detailed and free population data on a global scale is challenging to find. While it may be known to humanitarians, we were curious to see how a wider community of mappers less familiar with our data would experience using Kontur Population. This blog post is about what we have learned through their maps and from their feedback. Every November, the Kontur team and hundreds of other mapping enthusiasts worldwide participate in the social mapping project 30DayMapChallenge by creating maps for 30 consecutive days. Each day of November has an official theme to be reflected in the map submitted on that day, and this year the Kontur Population dataset has become one of the daily themes. More than individuals and organizations have created maps using our population dataset and posted them on Twitter.

Kontur population

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. 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 is represented by H3 hexagons with population counts at m 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. 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.

Tonga: Population Density for m H3 Hexagons. Lakes, rivers, kontur population, glaciers, sands, forests, and other similar areas are also marked as unpopulated. Hundreds of participants use the data to create maps to visualize climate change, flood kontur population, water security, access to emergency servicesand other topics.

Values represent number of people in cell. Release Known artifacts of both datasets are constrained using OpenStreetMap data as a hint. Quarries and big roads are marked unpopulated, as they are often falsely detected as populated in GHSL. Lakes, rivers, glaciers, sands, forests, and other similar areas are also marked as unpopulated. We use scale coefficient taking into account the nesting of levels of administrative division in cases when the total population of the administrative area significantly differs from the United Nations population estimates and projections.

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. 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 is represented by H3 hexagons with population counts at m resolution.

Kontur population

The map contains hexagons of approximately 1, feet meters in size. The same map can be created by you for any country or state, using this tutorial. As of the census, the total population of India is 1,,, But at last count, more than 1.

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Non-integer populations are fixed up by 'gluing people back together' to keep realistic human beings. Your message was sent. Per-country subsets of Kontur Population can be found here: data. Population data is applicable for visualization and insight extraction in various domains. Hungary population density for m H3 hexagons. Israel population density for m H3 hexagons. Remember me. Australia Population Density. 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. Along with wildfires, floods are the most widespread type of natural disaster on our planet, and there are few places where people are not vulnerable to them. Page URL. While it may be known to humanitarians, we were curious to see how a wider community of mappers less familiar with our data would experience using Kontur Population. By using this site you consent to the use of cookies. Greenland: Population Density for m H3 Hexagons.

In the humanitarian sphere, having reliable population data is crucial for prioritizing life-saving activities.

Kontur Population dataset is represented by H3 hexagons with population counts at m resolution. Non-integer population counts are rounded to integers. We are also grateful to the mappers who have taken the time to comment on the dataset so we can use this input for future improvement. Czechia: Population Density for m H3 Hexagons. This dataset updates: As needed. Global Population dataset. Rwanda population density for m H3 hexagons. Dataviz Gallery. The population is shifted to neighboring cells to satisfy constraints. Services Solutions Datasets Blog Contact us. At Kontur, one of our areas of expertise is creating global maps of critical service availability in populated areas, such as our Fire Service Scarcity Risk map. Israel population density for m H3 hexagons. Barbados: Population Density for m H3 Hexagons. Kontur team wanted to apply our geospatial expertise to solving local environmental challenges.