Spatial Distribution Estimates of the Urban Population Using DSM and DEM Data in China

Spatial distribution and population density are important parameters in studies on urban development, resource allocation, emergency management, and risk analysis. High-resolution height data can be used to estimate the total or spatial pattern of the urban population for small study areas, e.g., the downtown area of a city or a community. However, there has been no case of population estimation for large areas. This paper tries to estimate the urban population of prefectural cities in China using building height data. Building height in urban population settlement (Mdiffs) was first extracted using the digital surface model (DSM), digital elevation model (DEM), and land use data. Then, the relationships between the census-based urban population density (CPD) and the Mdiffs density (MDD) for different regions were regressed. Using these results, the urban population for prefectural cities of China was finally estimated. The results showed that a good linear correlation was found between Mdiffs and the census data in each type of region, as all the adjusted R2 values were above 0.9 and all the models passed the significance test (95% confidence level). The ratio of the estimated population to the census population (PER) was between 0.7 and 1.3 for 76% of the cities in China. This is the first attempt to estimate the urban population using building height data for prefectural cities in China. This method produced reasonable results and can be effectively used for spatial distribution estimates of the urban population in large scale areas.

[1]  A. Tatem,et al.  Dynamic population mapping using mobile phone data , 2014, Proceedings of the National Academy of Sciences.

[2]  Peter M. Atkinson,et al.  A Comparison of Small-Area Population Estimation Techniques Using Built-Area and Height Data, Riyadh, Saudi Arabia , 2016, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[3]  Constantine E. Kontokosta,et al.  Urban phenology: Toward a real-time census of the city using Wi-Fi data , 2017, Comput. Environ. Urban Syst..

[4]  Qihao Weng,et al.  Population Estimation of Urban Residential Communities Using Remotely Sensed Morphologic Data , 2015, IEEE Geoscience and Remote Sensing Letters.

[5]  P. Dong,et al.  Evaluation of small-area population estimation using LiDAR, Landsat TM and parcel data , 2010 .

[6]  Xiang Li,et al.  Discovering and Predicting Temporal Patterns of WiFi-interactive Social Populations , 2014, ArXiv.

[7]  Forrest R. Stevens,et al.  Improving Large Area Population Mapping Using Geotweet Densities , 2016, Trans. GIS.

[8]  Dongjin Song,et al.  High resolution population estimates from telecommunications data , 2015, EPJ Data Science.

[9]  A. Ye,et al.  Using Land Use Data to Estimate the Population Distribution of China in 2000 , 2012 .

[10]  Yu Liu,et al.  Towards Estimating Urban Population Distributions from Mobile Call Data , 2012 .

[11]  Peter M. Atkinson,et al.  Estimating the spatial distribution of the population of Riyadh, Saudi Arabia using remotely sensed built land cover and height data , 2013, Comput. Environ. Urban Syst..

[12]  Catherine Linard,et al.  Spatiotemporal patterns of population in mainland China, 1990 to 2010 , 2016, Scientific Data.

[13]  Ashleigh J. Rich,et al.  Estimating the Size of the MSM Population in Metro Vancouver, Canada, Using Multiple Methods and Diverse Data Sources , 2018, Journal of Urban Health.

[14]  R. Engstrom,et al.  Spatial refinement of census population distribution using remotely sensed estimates of impervious surfaces in Haiti , 2010 .

[15]  Jonathan Mellon,et al.  Twitter and Facebook are not representative of the general population: Political attitudes and demographics of British social media users , 2017 .

[16]  Jungho Im,et al.  Population estimation based on multi-sensor data fusion , 2010 .

[17]  Martin Herold,et al.  Population Estimation and Interpolation Using Remote Sensing , 2006 .

[18]  Xiaomin Qiu,et al.  Population Estimation Methods in GIS and Remote Sensing: A Review , 2005 .

[19]  N. Lam Spatial Interpolation Methods: A Review , 1983 .

[20]  Olivier Ferrando,et al.  Manipulating the Census: Ethnic Minorities in the Nationalizing States of Central Asia1 , 2008, Nationalities Papers.

[21]  David Coleman,et al.  The Twilight of the Census , 2013 .

[22]  Michael Leitner,et al.  Population at risk: using areal interpolation and Twitter messages to create population models for burglaries and robberies , 2017, Cartography and geographic information science.