MIT Joint Program on the Science and Policy of Global Change
Doi
Abstract
http://globalchange.mit.edu/research/publications/2254In this study, we introduce a new method of downscaling global population distribution, for which
purpose conventional approaches have serious limitations in application. Our approach is “eclectic,” as
it explores the intersection between an optimization framework and the empirical regularities involved in
rank-size distributions. The novelty of our downscaling model is that it allows city-size distributions to
interact with socioeconomic variables. Our contribution to the urban studies literature is twofold. One
is our challenge to the conventional view that the proportionate growth dynamics underlies empirical
rank-size regularities. We first show that the city-size distribution of a region can deviate substantially
from a log-normal distribution with cross-regional and time variations, and then demonstrate that such
variations can be explained by certain socioeconomic conditions that each region confronts at a
particular time point. In addition to expanding academic debates on city-size distributions, our study can
pave the way for various academic and professional research projects, which need spatial distribution of
global population at fine grid cell levels as key input. Our model is applicable to the entire globe,
including regions for which reliable sub-regional population data sets are limitedly available, and can be
extended easily to function as a forecasting model.The Joint Program on the Science and Policy of Global Change is funded by the U.S.
Department of Energy, Office of Science under grants DE-FG02-94ER61937, DE-FG02-
93ER61677, DE-FG02-08ER64597, and DE-SC0003906; the U.S. Department of Energy,
National Renewable Energy Laboratory under grant XEU-0-9920-01; the U.S. Environmental
Protection Agency under grants XA-83344601-0, XA-83240101, PI-83412601-0, and RD-
83427901-0; the U.S. National Science Foundation under grants SES-0825915, EFRI-0835414,
BCS-0410344, ATM-0329759, DMS-0426845, and AGS-0944121; the U.S. National
Aeronautics and Space Administration under grants NNX07AI49G, NNX08AY59A,
NNX06AC30A, NNX09AK26G, NNX08AL73G, NNX09AI26G, NNG04GJ80G,
NNG04GP30G, and NNA06CN09A; the U.S. National Oceanic and Atmospheric
Administration under grant NA070AR4310050; the U.S. Federal Aviation Administration under
grants 06-C-NE-MIT and 09-C-NE-MIT; the U.S. Department of Transportation under grant
DTRT57-10-C-10015; the U.S. Department of Agriculture under grant 58-0111-9-001; the
Electric Power Research Institute under grant EP-P32616/C15124; and a consortium of 40
industrial and foundation sponsor