India is 9.9k pp/km 2 and China is 8.9k pp/km 2. This is a more representative measure than standard population density, which is affected by low density suburban/peri-urban and rural land, even where the population in these areas is relatively low.Ĭhina and India have very high density cities, but their large rural populations translate into moderate Population Weighted Density statistics overall. The PWD is calculated by weighting each 1km 2 cell according to the population, summing all the cells for the city/region, and then dividing the sum by the total population of the country/city (i.e. Population Weighted Density is a measure of the typical density experienced by residents in the country/city, in this case using the 1km 2 scale GHSL data. To complement the graph of the population in each density category, this updated version of the World Population Density Map includes Population Weighted Density statistics for each country and city. The statistical analysis on the World Population Density Map website has also been updated using the 2023 GHSL data, so you can view the density profiles for all countries around the globe. Example images for Shanghai and New York City are shown below.Ĭountry Density Profiles – the Diversity of Human Settlement The dataset can now be used for more accurate comparisons of population and density for cities across the globe. Previous releases of the GHSL were underestimating urban densities for cities where census data was weaker, but this appears to no longer be the case. The added level of detail also improves the representation of cities, with more accurate density analysis, and improved techniques to differentiate residential from industrial and commercial urban land uses. This is also the case for other key regions such as Sub-Saharan Africa, and China. The tens of thousands of small villages are identified and used to more accurately distribute India’s huge population. The results are much improved, particularly for complex rural and peri-urban landscapes in the Global South, such as for India shown below. The new GHSL 2023 data has produced a much more detailed 10 metre dataset of built-up area (using recent European Space Agency Sentinel data), and this is the basis for creating the updated population layer. Improved Level of Detail for Cities and Rural Landscapes I have updated the World Population Density Map website to include this new 2023 data, with both the cartography and statistical analysis now based on the new data. The level of detail for cities and rural areas is impressive, and it overcomes the limitations of previous releases of the GHSL. This update has greatly improved the GHSL data, with a 10 metre scale built-up area dataset of the entire globe which has been used to create a 100 metre scale global population density layer. This approach involves a little work, but avoids the vagaries of looking for a prepared dataset or map, which may be out-of-date or based on data other than census 2010 or the 2014 July 1st estimates.The European Commission JRC recently released a new 2023 update of the Global Human Settlement Layer (GHSL) data. In rendering the map you can normalize total population by area to produce an up-to-date map. Retrieve the result table and working in ArcMap or ArcGIS Pro, join it to your shapefile (I would recommend file-based geodatabase as a more robust option for storing the counties or block groups). A guided search will have you find county-level population estimates in a first step and in a second step, allocation to "All counties. Both are available from the census bureau's web site. (2) I would recommend the American Communities Survey (ACS) data if you want recent data you can cite (at this date probably the July 1st estimates for 2014, I have not checked to see if the 2015 estimates are available as yet)-unless there is a requirement that you use PL data from the 2010 census. You can retrieve shapefiles or geodatabase layers from that resource. (1) You can get the geography data from the census bureau's pages, visit and look for block groups, and counties for New York.
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