Abstract
The urban population (UP) measure is one of the most direct indicators that reflect the urbanization process and the impacts of human activities. The dynamics of UP is of great importance to studying urban economic, social development, and resource utilization. Currently, China lacks long time series UP data with consistent standards and comparability over time. The nighttime light images from the Defense Meteorological Satellite Program’s (DMSP) Operational Linescan System (OLS) allow the acquisition of continuous and highly comparable long time series UP information. However, existing studies mainly focus on simulating the total population or population density level based on the nighttime light data. Few studies have focused on simulating the UP in China. Based on three regression models (i.e., linear, power function, and exponential), the present study discusses the relationship between DMSP/OLS nighttime light data and the UP and establishes optimal regression models for simulating the UPs of 339 major cities in China from 1990 to 2010. In addition, the present study evaluated the accuracy of UP and non-agricultural population (NAP) simulations conducted using the same method. The simulation results show that, at the national level, the power function model is the optimal regression model between DMSP/OLS nighttime light data and UP data for 1990–2010. At the provincial scale, the optimal regression model varies among different provinces. The linear regression model is the optimal regression model for more than 60% of the provinces. In addition, the comparison results show that at the national, provincial, and city levels, the fitting results of the UP based on DMSP/OLS nighttime light data are better than those of the NAP. Therefore, DMSP/OLS nighttime light data can be used to effectively retrieve the UP of a large-scale region. In the context of frequent population flows between urban and rural areas in China and difficulty in obtaining accurate UP data, this study provides a timely and effective method for solving this problem.
Highlights
Countries worldwide, and developing countries in particular, are undergoing an unprecedented urbanization process [1]
The fitting results of the urban population (UP) based on Defense Meteorological Satellite Program (DMSP)/Operational Linescan System (OLS) nighttime light data were better than those of the non-agricultural population (NAP) (Figure 3)
The accuracy of the evaluation results showed that the fitting results of the UP based on DMSP/OLS nighttime light data were better than those of the NAP
Summary
Countries worldwide, and developing countries in particular, are undergoing an unprecedented urbanization process [1]. Since the founding of the People’s Republic of China, China has conducted six successive national censuses (in 1953, 1964, 1982, 1990, 2000, and 2010), whereby the population was studied and measured on a general, door-to-door and person-by-person basis These censuses have facilitated the acquisition of relatively accurate statistical data on the UP [5,6,7,8]. The second common method involves acquiring information on the UP by substituting the non-agricultural population (NAP) for the UP. Due to their relatively high levels of continuity, data on the NAP have been extensively used in statistical publications and in urban studies in China. WuesreedufsoerdNfoArPNdAatPa d[4a3t]a. [T4h3e].thTihredtthyiprde otyf pdeatoafids aGtIaSiasuGxIiSliaaruyxdilaiatary, wdhaitcah, warheic1h:4,a0r0e01,0:40,000d0a,t0a0o0fdthatea oaf dthmeinadismtraintiivsetrabtoivuenbdoaruinesdaorfieps roofvpinrocevsinacnesdanpdrepfercetfuercet‐ulerev-ellevceitliecsitieins iCnhCinhainapupbulbislhisehdedonontthhee NNataitoinonalalGGeoemomaatitciscsCCenenteterroof fCChhininaawweebbssiittee[[4444]]
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