Population spatialization in China based on night-time imagery and land use data

Abstract

Population is a key indicator of socioeconomic development, urban planning and environmental protection, particularly for developing countries like China. But, census data for any given area are neither always available nor adequately reflect the internal differences of population. The authors tried to overcome this problem by spatializing the population across China through utilizing integer night-time imagery (Defense Meteorological Satellite Program/Operational Linescan System, DMSP/OLS) and land-use data. In creating the population linear regression model, night-time light intensity and lit areas, under different types of land use, were employed as predictor variables, and census data as dependent variables. To improve model performance, eight zones were created using night-time imagery clustering and shortest path algorithm. The population model is observed to have a coefficient of determination (R 2 ) ranging from 0.80 to 0.95 in the research area, which remained the same in different years. A comparison of the results of this study with those of other researchers shows that the spatialized population density map, prepared on the basis of night-time imagery, reflects the population distribution character more explicitly and in greater detail.

Monitoring Population Evolution in China Using Time-Series DMSP/OLS Nightlight Imagery

“…Although previous studies [1,30,[46][47][48] have explored various correcting methods of NLT products and have shown the feasibility of NLT products on population simulation, studies in synergistic application of systematic correction of NLT products and population spatialization are scarce. Though case studies on population spatialization with high accuracy existed, they concentrated mainly on early years before 2000 and used complicated steps [1,30,32,48]. Furthermore, detailed analysis on the evolution of spatio-temporal characteristics of the Chinese population is relatively lacking.…”

“…In this study, MOD13A3 NDVI products and VANUI were applied to eliminate or decrease light overflowing due to their high correlation with population distribution [1,25,44,48]. DN values of NLT products were normalized to the range of [0, 1.0] [44] firstly, and then the adjustment based on the vegetation distribution was accomplished based on Equation (12):…”

“…Population growth is an important indicator for evaluating socio-economic development, environmental protection, sustainable utilization of resources, and urban planning [1]. China is the largest developing and most populous country in the world, with 18.82% of the population of the world (United Nations, 2017).…”

Methodologies and applications in Digital China

“…Zeng et al [49] while addressing this issue proposed population spatialization technique utilizing integer night-time imagery and land use data. They applied their approach in China.…”

Monitoring land use change and its drivers in Delhi, India using multi-temporal satellite data

“…Therefore, the role of techniques such as remote sensing, aerial photography and image processing becomes important. Remote sensing and image processing have been used to document urban growth and dynamics in hundreds of areas throughout the world over the last decades (Miller and Small 2003;Sudhira et al 2004;Fox and Vogler 2005;Jat et al 2008;Zeng et al 2011;Lasaponara and Lanorte 2012). Timely and accurate information on existing LULC pattern, its distribution and changes over time is a prerequisite for planning, utilization and formulation of policies and programs for making any developmental plan.…”