Extrapolation of population grids for risk analysis. Issue 3 (September 2018)

• Record Type: Journal Article
• Authors: Bellucci, A.; Tholey, N.; Studer, Mathias; Goester, J.F.; Fuentes, N.
• Is Part Of: Journal of space safety engineering. Volume 5:Issue 3/4(2018)
• Page Start: 192
• Page End: 196
• Publication Date: 2018-09
• Subjects: Astronautics -- Periodicals; Space flight -- Periodicals; Space flight -- Safety measures -- Periodicals; Space flight -- Safety regulations -- Periodicals; Astronautics -- Safety measures -- Periodicals; Astronautics -- Safety regulations -- Periodicals; 629.4
• DOI: 10.1016/j.jsse.2018.01.006
• Languages: English
• ISSNs: 2468-8967

Abstract

Abstract: To fulfill its mission of control within the framework of the FSOA (French Space Operation Act), including in particular the monitoring of safety requirements for people and property, CNES has developed and has been using since eight years the model and tool ELECTRA, especially designed to estimate human risk during launch and controlled or uncontrolled re-entry. The major contributor in probabilistic assessment of human risk is the population density on areas where some re-entry fragments may fall. In this framework, information about population spatial distribution at a global scale is a key parameter. In particular, CNES needs to have an estimation of the evolution of population for future decades to estimate risk during launch phase and re-entry for future space missions presently in preparation. The objectives of the CNES POPSCAN study, started in 2011 with SERTIT, include census of available databases about worldwide population, qualitative and quantitative analyses of these data and proposals to improve population models used in risk analysis. In this paper, we present a method to extrapolate until 2050, at different time steps, the world population grid provided by CIESIN (Columbia University), i.e. the GPW-V4-UN-adjusted geo-referenced raster dataset. Reasons having led to the choice of this particular database are presented as well as some of the main existing extrapolation methods. The method exploits existing geo-spatial population information at a grid cell level provided by past population distribution grids and computes the successive future population layers: it is based on an exponential approach with an adjustment to UN projections (United Nations World Population Prospects, the 2015 Revision). This approach combines two advantages: keeping the gridded representation of population distribution from geo-data bases such as GPW and benefiting from the tabular data computed by UN and their sophisticated methods for world population projections.