Abstract：With the acceleration of urbanization in China and the growing proportion of urban population， the theoretical research， which was set in and directed at mutual influence and interaction between cities and human beings， had drawn increasing attention and concern from relevant scholars and urban planning administrations. This study was carried out by using Google Maps as a platform， showing the areas surrounding Wuchang District， Wuhan. From the collected and pre-processed Volunteered Geographic Information (VGI) photos that was uploaded by the public， urban hotspot spatial distribution would be drawn in a kernel density estimation manner to explore the public preferences for urban space. Based on the VGI as the source of the sample data with a multi-time scale characteristics， the spatial hotspot pattern and the evolutionary trend in the inter-annual and inter-monthly variation were explored. The result shows that the distribution pattern of hotspots in Wuchang District is relatively stable. Among the inter-annual changes， the Wuhan Yangtze River Bridge， Yellow Crane Tower， and Luojia Mountain in Wuhan University have attracted high attention as the core hotspots； the urban space centered on the Wuhan Railway Station and the Hubei Province Museum has a rather high degree of heat and tends to be stable with year-by-year increase. In the monthly changes， the urban hotspot pattern in Wuchang District shows a strong consistency on the whole， but the public's attention to the hotspots is fluctuating within the year， which sharply increased and reached the peak of the year in September and October.
林木森,王道飘,刘博源,黎 华. 基于自发式地理信息的武汉市城市热点空间分析[J]. 华中师范大学学报(自然科学版), 2019, 53(1): 147-153.
LIN Musen,WANG Daopiao,LIU Boyuan,LI Hua. Analysis of urban hot space in Wuhan based on VGI. journal1, 2019, 53(1): 147-153.
2019, Vol. 53 
