WorldPop Global Project Population Data: Estimated Residential Population per 100x100m Grid Square  |  Earth Engine Data Catalog  |  Google for Developers
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WorldPop Global Project Population Data: Estimated Residential Population per 100x100m Grid Square
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Page Summary
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The WorldPop project provides high-resolution, open access population distribution datasets using transparent and peer-reviewed methods.
Population counts from recent censuses are disaggregated to approximately 100x100m grid cells using machine learning techniques.
This dataset provides estimated population residing in each grid cell for the years 2010, 2015, and other years, available from 2000 to 2021.
The dataset is licensed under the Creative Commons Attribution 4.0 International License, requiring clear attribution to WorldPop.
Dataset Availability
2000-01-01T00:00:00Z–2021-01-01T00:00:00Z
Dataset Producer
WorldPop
Earth Engine Snippet
ee.ImageCollection("WorldPop/GP/100m/pop")
open_in_new
Tags
demography
population
worldpop
Description
Global high-resolution, contemporary data on human population distributions are
a prerequisite for the accurate measurement of the impacts of population
growth, for monitoring changes, and for planning interventions. The WorldPop
project aims to meet these needs through the provision of detailed and open
access population distribution datasets built using transparent and
peer-reviewed approaches.
Full details on the methods and datasets used in constructing the
data, along with open access publications, are provided on the
WorldPop website. In brief, recent census-based
population counts matched to their associated administrative units are
disaggregated to ~100x100m grid cells through machine learning approaches
that exploit the relationships between population densities and a range of
geospatial covariate layers. The mapping approach
is Random Forest-based dasymetric redistribution.
This dataset depict estimated number of people
residing in each grid cell in 2010, 2015, and other years.
For 2020, the breakdown of population by age and sex is available in
the WorldPop/GP/100m/pop_age_sex
and WorldPop/GP/100m/pop_age_sex_cons_unadj
collections.
Further WorldPop gridded datasets on population age structures,
poverty, urban growth, and population dynamics are freely available on
the WorldPop website. WorldPop represents a collaboration between
researchers at the University of Southampton, Universite Libre de
Bruxelles, and University of Louisville. The project is principally funded by
the Bill and Melinda Gates Foundation.
Bands
Bands
Pixel size: 92.77 meters (all bands)
Name
Min
Max
Pixel Size
Description
population
0*
21171*
92.77 meters
Estimated number of people residing in each grid cell
* estimated min or max value
Image Properties
Image Properties
Name
Type
Description
country
STRING
Country
year
DOUBLE
Year
Terms of Use
Terms of Use
WorldPop datasets are licensed under the Creative Commons Attribution 4.0
International License. Users are free to use, copy, distribute, transmit,
and adapt the work for commercial and non-commercial purposes, without
restriction, as long as clear attribution of the source is provided.
Citations
Citations:
Please cite the WorldPop website as the source: www.worldpop.org.
Americas population data: Alessandro Sorichetta, Graeme M. Hornby,
Forrest R. Stevens, Andrea E. Gaughan, Catherine Linard, Andrew J. Tatem,
2015, High-resolution gridded population datasets for Latin America and the
Caribbean in 2010, 2015, and 2020, Scientific Data,
doi:10.1038/sdata.2015.45
Africa population count data: Linard, C., Gilbert, M., Snow, R.W., Noor,
A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns
and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743.
Asia population count data: Gaughan AE, Stevens FR, Linard C, Jia P and
Tatem AJ, 2013, High resolution population distribution maps for Southeast
Asia in 2010 and 2015, PLoS ONE, 8(2): e55882.
DOIs
https://doi.org/10.1038/sdata.2015.45
Explore with Earth Engine
Important:
Earth Engine is a platform for petabyte-scale scientific analysis and visualization of
geospatial datasets, both for public benefit and for business and government users.
Earth Engine is free to use for research, education, and nonprofit use. To get started, please
register for Earth Engine access.
Code Editor (JavaScript)
var dataset = ee.ImageCollection('WorldPop/GP/100m/pop');
var visualization = {
bands: ['population'],
min: 0.0,
max: 50.0,
palette: ['24126c', '1fff4f', 'd4ff50']
};
Map.setCenter(113.643, 34.769, 7);
Map.addLayer(dataset, visualization, 'Population');
Python setup
See the
Python Environment page for information on the Python API and using
geemap for interactive development.
import ee
import geemap.core as geemap
Colab (Python)
dataset = ee.ImageCollection('WorldPop/GP/100m/pop')
visualization = {
'bands': ['population'],
'min': 0.0,
'max': 50.0,
'palette': ['24126c', '1fff4f', 'd4ff50'],
}
m = geemap.Map()
m.set_center(113.643, 34.769, 7)
m.add_layer(dataset, visualization, 'Population')
m
Open in Code Editor
WorldPop Global Project Population Data: Estimated Residential Population per 100x100m Grid Square
Global high-resolution, contemporary data on human population distributions are a prerequisite for the accurate measurement of the impacts of population growth, for monitoring changes, and for planning interventions. The WorldPop project aims to meet these needs through the provision of detailed and open access population distribution datasets built using transparent …
WorldPop/GP/100m/pop,
demography,population,worldpop
2000-01-01T00:00:00Z/2021-01-01T00:00:00Z
-90 -180 90 180
Google Earth Engine
https://developers.google.com/earth-engine/datasets
https://doi.org/10.1038/sdata.2015.45
https://doi.org/10.1038/sdata.2015.45
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