Enhanced data and methods for improving open and free global population grids: putting ‘leaving no one behind’ into practice

ABSTRACT

Data on global population distribution are a strategic resource currently in high demand in an age of new Development Agendas that call for universal inclusiveness of people. However, quality, detail, and age of census data varies significantly by country and suffers from shortcomings that propagate to derived population grids and their applications. In this work, the improved capabilities of recent remote sensing-derived global settlement data to detect and mitigate major discrepancies with census data is explored. Open layers mapping built-up presence were used to revise census units deemed as ‘unpopulated’ and to harmonize population distribution along coastlines. Automated procedures to detect and mitigate these anomalies, while minimizing changes to census geometry, preserving the regional distribution of population, and the overall counts were developed, tested, and applied. The two procedures employed for the detection of deficiencies in global census data obtained high rates of true positives, after verification and validation. Results also show that the targeted anomalies were significantly mitigated and are encouraging for further uses of free and open geospatial data derived from remote sensing in complementing and improving conventional sources of fundamental population statistics.

KEYWORDS:

• Population statistics
• census
• built-up areas
• GPW
• GHSL

Acknowledgements

The term country also refers, as appropriate, to territories or areas, and does not imply recognition of borders or legal status by the European Commission.

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Sergio Freire http://orcid.org/0000-0003-2282-701X

Marcello Schiavina http://orcid.org/0000-0003-3399-3400

Aneta J. Florczyk http://orcid.org/0000-0001-8912-1500

Martino Pesaresi http://orcid.org/0000-0003-0620-439X

Christina Corbane http://orcid.org/0000-0002-2670-1302

Additional information

Funding

This work has been carried out in the frame of the institutional work programme of the Joint Research Centre (JRC, European Commission) and supported by the administrative arrangement no. 33994 between the JRC and the Directorate General for Regional and Urban Policies (DG REGIO, European Commission). Work from partners on GPW4.10 and improvements described herein are funded by NASA under contract NNG08HZ11C for the continued operation of the Socioeconomic Data and Applications Center (SEDAC) at Center for International Earth Science Information Network (CIESIN) at Columbia University.