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Ujaval Gandhi

ujaval@spatialthoughts.com

Introduction to QGIS

Introduction to Gridded Population Datasets

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Population Datasets

  • Population data is typically collected and aggregated by census blocks.
  • Vector population datasets include census polygons with population counts.
  • Limitations of Vector Population Datasets
    • It is not possible to know the distribution of population within each polygon.
    • It is not possible to get population of arbitrary regions.

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Gridded Population Data

  • Many applications require knowledge of distribution of population at finer scales than census blocks.
  • One can disaggregate the population counts from census blocks to a uniform grid.
    • Common techniques include modeling the population distribution based on landuse/landcover, building counts, satellite imagery etc.
  • The output is a uniform grid with population counts. This is stored and distributed as a raster dataset.
    • Raster data model allows for aggregating counts for any region.

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Gridded Population Datasets

  • GPW (Gridded Population of the World) - NASA SEDAC
    • 1 km grid cells
    • Available for 2000, 2005, 2010, 2015, and 2020
  • GHSL (Global Human Settlements Layer)
    • 250m grid cells
    • Available from 1975, 1990, 2000, 2015, 2020, (2025, 2030)
  • WorldPop
    • 100m grid cells
    • Available for each year from 2000 - 2020
  • Facebook’s High Resolution Population Data [download link]
    • 30m grid cells
    • Available for 2019/2020
  • Landscan Global
    • 1km grid cells
    • Available yearly from 2000-2022

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Calculating Total Population

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Aggregating Population in Regions

  • Each pixel in a gridded population dataset represents the population count.
  • To count the total population within a polygon, we can calculate the ‘sum’ of pixel values within that polygon.
  • This analysis is known as ‘Zonal Statistics’.
    • Zonal Statistics allows us to compute raster statistics in vector ‘zones’.

Processing Toolbox → Raster Analysis → Zonal statistics