Identification and optimization analysis of urban building space use characteristics by integrating POI and GIS

Abstract

Aiming at the problems of single function and unbalanced use efficiency of urban architectural space, this study integrates POI data and GIS technology to construct a full chain analysis framework of "data acquisition-feature recognition-optimization simulation", aiming at revealing the use characteristics of architectural space and proposing optimization strategies. In this paper, POI data is obtained through API and business hours information is supplemented. Combined with building outline GIS data, a three-dimensional database of "Building -POI- Time" is constructed after spatial cleaning and topology correction. The spatio-temporal activity index (STAI) model is used to quantify the dynamic use characteristics of building space, and the spatial mismatch problem is diagnosed by the functional supply-demand ratio (FSR), and the multi-objective functional reorganization scheme is generated by NSGA-III multi-objective genetic algorithm.  Taking Nanshan District of Shenzhen as an empirical research area, the results show that there is a significant difference between day and night in the office activity of science and technology park, with the STAI reaching 0.85 at 9 am and dropping to 0.12 at night; There is an imbalance between functional supply and demand in different regions, such as the gap of catering service at noon on weekdays in the office area of Science and Technology Park (FSR=0.63) and the surplus of commercial leisure facilities at night in Xili Community (FSR=1.87). The comparison of optimization schemes shows that although the transformation cost of vitality priority scheme is 610 million yuan, the STAI is increased by 53% and the functional mixing entropy is 3.02, and the effect is the best. This study provides scientific methods and practical references for spatial optimization of smart cities, and enriches the theoretical system of urban spatial optimization.