Adaptive Multi-Scale Population Spatialization Model Constrained by Multiple Factors: A Case Study of Russia

Abstract

Population spatialization is the foundation for the visualization and analysis of population integrated with other information, such as environmental resources, economy, and public health. The existing population spatialization models have solved many problems for population distribution, but most of these studies have focused on a specific, single-scale approach and ignored the scale transformation for population spatialization. However, multi-scale visualization and the analysis of spatial information need multi-scale information. Meanwhile, the population distribution map as one kind of thematic map is always overlaid with the digital vector map or remote sensing map and visualized in the Web Geographic Information Systems (Web GIS), so it should adapt to the map scale showed in browser, when the user zoom in and zoom out. Hence adaptive multi-scale is necessary for population spatialization. Therefore, in this study, an adaptive multi-scale population spatialization model (APSM) is proposed with comprehensive factors constrained. These factors are residential area, land cover, public transport, hydrology, terrain, and climate. All of them are closely associated with population distribution. The overall methodology of APSM and the process for APSM are expounded in this paper. Meanwhile, with a case study of Russia, the processes of APSM for Russia are stated, and a population spatialization tool is implemented for expanding the application of APSM. The experimental analysis showed that APSM satisfied the requirement of geospatial analysis well and obtained a reliable accuracy.