Spatiotemporal patterns of population in mainland China, 1990 to 2010

Abstract

According to UN forecasts, global population will increase to over 8 billion by 2025, with much of this anticipated population growth expected in urban areas. In China, the scale of urbanization has, and continues to be, unprecedented in terms of magnitude and rate of change. Since the late 1970s, the percentage of Chinese living in urban areas increased from ~18% to over 50%. To quantify these patterns spatially we use time-invariant or temporally-explicit data, including census data for 1990, 2000, and 2010 in an ensemble prediction model. Resulting multi-temporal, gridded population datasets are unique in terms of granularity and extent, providing fine-scale (~100 m) patterns of population distribution for mainland China. For consistency purposes, the Tibet Autonomous Region, Taiwan, and the islands in the South China Sea were excluded. The statistical model and considerations for temporally comparable maps are described, along with the resulting datasets. Final, mainland China population maps for 1990, 2000, and 2010 are freely available as products from the WorldPop Project website and the WorldPop Dataverse Repository.

Effects of law enforcement and community outreach on mammal diversity in a biodiversity hotspot

“…Human density within 3 km of each camera was calculated based on the Chinese population map of 2010 (Gaughan et al. ). We included a random intercept to account for spatial autocorrelation within parks not driven by the environmental factors in our models.…”

“…We used human population density and the distance from each camera to the border of the protected area (a metric of site accessibility) as indices of potential human disturbance. Human density within 3 km of each camera was calculated based on the Chinese population map of 2010 (Gaughan et al 2016). We included a random intercept ε park to account for spatial autocorrelation within parks not driven by the environmental factors in our models.…”

Evaluating nighttime lights and population distribution as proxies for mapping anthropogenic CO2emission in Vietnam, Cambodia and Laos

“…The WorldPop model is parameterized for each year of interest using an aggregated set of administrative units (Laos n=10035, Cambodia n=1621, Vietnam n=688) and by maintaining the same consistent boundary definitions over time (Gaughan et al 2016). By relying on census data to inform the modeling process, the gridded population outputs effectively represent residential population counts which is in contrast to data such as Landscan which models ambient population counts (Dobson et al 2000).…”

“…columbia.edu/downloads/docs/gpw-v4/gpw-v4-country-level-summary-rev10.xlsx) across all three countries of interest. We followed the approach outlined in Gaughan et al (2016) and used both temporallyinvariant and temporally-explicit covariates (table 1) while excluding NTL data. Temporally-invariant data include topography and slope, average annual precipitation and temperature (representative of the current conditions), presence of main roads and their intersections, waterways, water bodies, and coastlines.…”

Mapping internal connectivity through human migration in malaria endemic countries

“…Regarding the second assumption, it is important to highlight that the use of census data from many years ago for some countries may have generated inaccurate estimates for the period considered in this study (i.e., 2005–2010), for example because of major changes in the countries’ socio-economic conditions from the time period covered by the census (e.g., the rapid economic development and urbanization that has occurred in China during the last two decades 91,92 ). Similarly, in some other countries, either the presence of conflicts 93 or the occurrence of natural disasters 88,89 during the specific time period covered by the census may have produced fluctuations in the number of internal migrants and consequently biased results for the period considered in this study.…”