Journal of Geographical Sciences - Urban land intensive use is an important indicator in harmonizing the relationship between land supply and demand. The system dynamics (SD) can be used to... 相似文献
Urban agglomeration is caused by the continuous acceleration of the urbanization process in China. Studying the expansion of construction land can not only know the changes and development of urban agglomeration in time, but also obtain the great significance of the future management. In this study, taking Changsha-Zhuzhou-Xiangtan (Chang-Zhu-Tan) urban agglomeration in Hunan province as a study area, Landsat images from 1995 to 2014 and Autologistic-CLUE-S model simulation data were used. Moreover, several factors including gravity center, direction, distance and landscape index were considered in the analysis of the expansion. The results revealed that the construction area increased by 132.18%, from 372.28 km2 in 1995 to 864.37 km2 in 2014. And it might even reach 1327.23 km2 in 2023. Before 2014, three cities had their own respective and discrete development directions. However, because of the integration policy implementation in 2008, the Chang-Zhu-Tan began to gather, the gravity center moved southward after 2014, and the distance between cities decreased, which was in line with the development plan of urban expansion. The research methods and results were relatively reliable, and these results could provide some reference for the future land use planning and spatial allocation in the urbanization process of Chang-Zhu-Tan urban agglomeration.
Understanding scale effects is important and indispensable for geography studies. However, spatial and spatiotemporal statistical tools for measuring the operational scales of different processes are rather limited. This article extends the popular geographically and temporally weighted regression (GTWR) model to consider operational scale effects by proposing multiscale GTWR (MGTWR), which offers a flexible and scalable framework for identifying and analysing multiscale processes by specifying flexible bandwidths for various covariates. Then, MGTWR is employed to explore spatiotemporal variations and how influential factors are associated with housing prices in Shenzhen. This article attempts to extend GTWR to MGTWR in consideration of scale effects, thereby highlighting the importance of different levels of spatiotemporal heterogeneity. Furthermore, the empirical results of this study can provide valuable policy implications for real estate development in areas where urban planning should address multiscale effects in both temporal and spatial dimensions. 相似文献