Measuring the contribution of built-settlement data to global population mapping

• Published in: Social sciences & humanities open Vol. 3; no. 1; p. 100102
• Main Authors: Nieves, Jeremiah J., Bondarenko, Maksym, Kerr, David, Ves, Nikolas, Yetman, Greg, Sinha, Parmanand, Clarke, Donna J., Sorichetta, Alessandro, Stevens, Forrest R., Gaughan, Andrea E., Tatem, Andrew J.
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 2021; Elsevier
• Subjects: Built; Growth model; Machine learning; Meta-analysis; Population; Settlement; Urban; Urban; Settlement; Growth model; Built; Machine learning; Population; Meta-analysis

Top-down population modelling has gained applied prominence in public health, planning, and sustainability applications at the global scale. These top-down population modelling methods often rely on remote-sensing (RS) derived representation of the built-environment and settlements as key predictive...