Examining the correlates and drivers of human population distributions across low- and middle-income countries

• Published in: Journal of the Royal Society interface Vol. 14; no. 137; p. 20170401
• Main Authors: Nieves, Jeremiah J., Stevens, Forrest R., Gaughan, Andrea E., Linard, Catherine, Sorichetta, Alessandro, Hornby, Graeme, Patel, Nirav N., Tatem, Andrew J.
• Format: Journal Article
• Language: English
• Published: England The Royal Society 01.12.2017; The Royal Society Publishing
• Subjects: Census; Continents; Dasymetric; Decision Trees; Demography; Developing Countries; Disaggregation; Economic models; Geography; Human populations; Humans; Income; Learning algorithms; Life Sciences–Earth Science interface; Low income groups; Machine Learning; Mapping; Population; Population Density; Population distribution; Population Dynamics; Population growth; Poverty; Random Forests; Regression Analysis; Spatial discrimination; Spatial distribution; Topography; random forests; disaggregation; mapping; dasymetric; census; population

Geographical factors have influenced the distributions and densities of global human population distributions for centuries. Climatic regimes have made some regions more habitable than others, harsh topography has discouraged human settlement, and transport links have encouraged population growth. A...