Modeling the population of China using DMSP operational linescan system nighttime data

Radiance-calibrated DMSP-OLS nighttime lights data of China acquired between March 1996 and January-February 1997 were evaluated for their potential as a source of population data at the provincial, county, and city levels. The light clusters were classified into six categories of light intensity, and their areal extents were extracted from the image. Mean pixel values of light clusters corresponding to the settlements were also extracted. A light volume measure was developed to gauge the three-dimensional capacity of a settlement. A density of light cluster measure known as percent light area was also calculated for each spatial unit. Allometric growth models and linear regression models were developed to estimate the Chinese population and population densities at the three spatial levels using light area, light volume, pixel mean, and percent light area as independent variables. It was found that the DMSP-OLS nighttime data produced reasonably accurate estimates of non-agricultural (urban) population at both the county and city levels using the allometric growth model and the light area or light volume as input. Non-agricultural population density was best estimated using percent light area in a linear regression model at the county level. The total sums of the estimates for non-agricultural population and even population overall closely approximated the true values given by the Chinese statistics at all three spatial levels. It is concluded that the 1-km resolution radiance-calibrated DMSP-OLS nighttime lights image has the potential to provide population estimates of a country and shed light on its urban population from space.