基于GIS场模型的城市餐饮服务热点探测及空间格局分析

餐饮服务是城市生活的重要组成部分,提取城市餐饮服务热点并识别其空间分布模式,对于理解城市形态结构具有重要意义。针对过去基于POI进行城市形态特征定量分析的不足,利用GIS场模型对城市特征要素的空间分布模式进行识别,并采用地学信息图谱对其模式进行可视化和分析。以济南市主城区4.71万个餐饮服务POI作为主要数据源,首先基于密度场热点探测模型提取餐饮服务热点并按照密度值进行等级划分;然后采用广义对称结构图谱和数字场层次结构图谱表达餐饮服务热点的空间分布结构特征和规模等级结构特征,并构建其分布模式图谱;最后对结果展开讨论。研究表明：① 数字场热点探测模型能够有效地从POI中识别出不同等级的热点。② 广义对称结构图谱和基于GIS场模型的层级结构图谱能够分别从纵横两个方面分析和表达餐饮热点的空间分布结构和层次等级结构特征。综上所述,本研究为基于POI的城市特征要素提取和城市形态研究提供了一种有效的定量分析思路,其方法也可以推广至其他城市特征要素的提取、分析和表达当中。

Hotspot discovery and its spatial pattern analysis for catering service in cities based on field model in GIS

Catering service is an important part of urban life. Extracting urban hotspots for catering services and identifying their spatial distribution patterns is important for our understanding urban space and urban structures. In view of the shortcomings of quantitative analysis of urban morphological features based on POI in the past, the GIS field model was used to identify the spatial distribution patterns of urban feature elements, and the Geo-information Tupu was used to visualize the patterns. Taking the 47100-catering service POIs in the main urban area of Jinan city as the main data source, the catering service hotspots were first extracted based on the density field hotspot detection model and classified according to the density value; then the catering service was expressed by Geo-information-Tupu of generalized symmetric structure and digital field based hierarchical Geo-information Tupu. The spatial distribution structure characteristics and scale structure features of the hotspots are presented, and their Geo-information Tupu of distribution pattern is constructed. Finally, the results are discussed. Research shows that: (1) The digital field hotspot detection model can effectively identify hotspots in different levels from POI. (2) The Geo-information-Tupu of generalized symmetric structure and digital field based hierarchical Geo-information Tupu can analyze and express the spatial distribution structure and hierarchical structure characteristics of the food hotspot from the aspect of vertical and horizontal of space. In summary, this study provides an effective quantitative analysis method for POI-based urban feature extraction and urban morphology research. The method can also be extended to the extraction, analysis and expression of other urban feature elements.