Research on characteristics in the spatial distribution of the whole county population of Sichuan province, China via ARCGIS analysis
Guiyao Zhou, Yanyou Wu, Xianjian Xie, Deke Xing, Fang Fan, Rui Yu
Available Online December 2013.
- https://doi.org/10.2991/asshm-13.2013.185How to use a DOI?
- Geostatistics; Sichuan Province; Distribution of population; Spatial interpolation model
- 2000 and 2010 year census population data of each county of Sichuan Province, China has been chosen as research objects in our research. In this study, different spatial fitting model of geostatistics modules which are based on Arcgis Software has been used to discuss the fitting effects of population density data. The best spatial distribution fitting model was obtained which has been used to make optimal Kriging interpolation. The factors affecting Sichuan Province Population change have also been analyzed. Results showed that the overall distribution of Sichuan province population has uneven spatial distribution and circular style. Counties population in space formed two macroscopic distribution patterns: One is the Western Sichuan-intensive area and the other one is basins gathering area. Time distribution of different density region has changed over time, especially the population of Chengdu economic region and the Southern Sichuan economic region which are growing rapidly. The whole population in Sichuan province shows an increasing trend from west to east. Natural conditions, policies and economic conditions are the most important factors that influence the Spatial and Temporal distribution regularity of population of Sichuan Province.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Guiyao Zhou AU - Yanyou Wu AU - Xianjian Xie AU - Deke Xing AU - Fang Fan AU - Rui Yu PY - 2013/12 DA - 2013/12 TI - Research on characteristics in the spatial distribution of the whole county population of Sichuan province, China via ARCGIS analysis BT - 2013 International Conference on Advances in Social Science, Humanities, and Management (ASSHM-13) PB - Atlantis Press SP - 999 EP - 1005 SN - 1951-6851 UR - https://doi.org/10.2991/asshm-13.2013.185 DO - https://doi.org/10.2991/asshm-13.2013.185 ID - Zhou2013/12 ER -