Enhanced data and methods for improving open and free global population grids: putting 'leaving no one behind' into practice. Issue 1 (2nd January 2020)

• Record Type: Journal Article
• Authors: Freire, Sergio; Schiavina, Marcello; Florczyk, Aneta J.; MacManus, Kytt; Pesaresi, Martino; Corbane, Christina; Borkovska, Olena; Mills, Jane; Pistolesi, Linda; Squires, John; Sliuzas, Richard
• Is Part Of: International journal of digital earth. Volume 13:Issue 1(2020)
• Page Start: 61
• Page End: 77
• Publication Date: 2020-01-02
• Subjects: Population statistics -- census -- built-up areas -- GPW -- GHSL; Geographic information systems -- Periodicals; Sustainable development -- Information technology -- Periodicals; Social planning -- Information technology -- Periodicals; 910.285
• DOI: 10.1080/17538947.2018.1548656
• Languages: English
• ISSNs: 1753-8947

Abstract

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.