#Us map of population density update#
#Us map of population density full#
#Us map of population density download#

Existing population distribution data for urban areas in low and middle-income regions is often limited by (i) a lack of spatially detailed data to capture within-urban heterogeneities, (ii) a lack of multi-temporal data to support improved understanding and forecasting of urban growth. The population of Africa is predicted to double over the next 40 years, driving exceptionally high urban expansion rates. The figure below shows an example for Nigeria.

#Us map of population density full#

WorldPop have therefore developed methods for the production of high resolution age-structure mapping from geolocated household survey data, together with full quantification of model uncertainty. Just as is the case for population counts, in some countries, contemporary and reliable census data are unavailable for supporting detailed mapping of population pyramids.

#Us map of population density download#

Further details are provided here , the datasets are available to download here , and an example output for women of childbearing age is shown below. The construction of spatially detailed databases of boundary-matched census data (outlined above) enables construction of such mapped outputs. In addition to the high resolution mapping of total population counts and densities, WorldPop works to produce similar outputs broken down by age and sex to provide detailed spatial mapping of population pyramids.

The age-group composition of populations varies considerably across the world, and obtaining accurate, spatially detailed estimates about key groups, such as numbers of children under 5 years is important in designing vaccination strategies, educational planning or maternal healthcare delivery, for example. The figure below shows an example for northern Vietnam. WorldPop have developed peer-reviewed spatial statistical methods, exploiting the power of machine learning, to transform and disaggregate population counts at administrative unit levels to 100x100m grid square level, exploiting relationships with spatial covariate layers from satellites and other sources. The figure below shows examples of such datasets for three countries.Īdministrative units within a country typically vary substantially in their shapes and sizes, making the consistent mapping of population distributions and densities across a country, and their integration with other datasets produced on differing spatial frameworks challenging. WorldPop works with statistics agencies, ministries of health and other organizations to construct databases of the most spatially detailed and recent population census data available, and match these to corresponding administrative boundaries. The accuracy of gridded population mapping is strongly related to the availability of contemporary and spatially detailed population census data.

Gridded population maps, whereby population numbers per 100x100m grid square are estimated, represent a more consistent representation of population distributions across a landscape than administrative unit counts, as well as enabling smooth integration with multiple other gridded datasets. Census, survey, satellite, social media, cellphone and other spatial datasets are all integrated in flexible and peer-reviewed statistical methods to produce open, fully-documented and consistent gridded maps of population distributions. WorldPop develops methods to exploit and integrate the growing range of geospatial data on human populations, their demographics and factors relating to population distributions. The scarcity of mapping resources, lack of reliable validation data and difficulty in obtaining high resolution contemporary census statistics remain major obstacles to settlement and population mapping across the low income regions of the World. High-income countries often have extensive mapping resources and expertise at their disposal to create such databases, but across the low income regions of the world, relevant data are either lacking or are of poor quality. Maps of human population distributions have found use in disease burden estimation, epidemic modelling, resource allocation, disaster management, accessibility modelling, transport and city planning, poverty mapping and environmental impact assessment amongst other applications.

#Us map of population density update#

The methods outlined below are becoming outdated and have been superseded in some places – we are working to update these based on newly published papers. Therefore, to keep up with the latest methods, we recommend visiting our publications page. A primary focus of WorldPop is ensuring that the methods developed and resulting output datasets undergo academic peer review.