关键词: 点聚合, 地理层级解析, 人机交互, 可视化管理系统, 时空数据

Abstract: To address the challenges of managing and efficiently localizing large-scale, multi-category urban spatiotemporal data, an interactive visu-alization method based on point aggregation was proposed. First, efficient aggregation algorithms based on geographic location and geo-graphic hierarchy were introduced to address the needs of government personnel for effective visualization management in different scenarios. Second, a conditional parsing algorithm was proposed based on efficient point aggregation to enable real-time parsing and conversion of spatiotemporal conditions and category visibility, improving data localization efficiency. The method used nearly 270,000 urban entities in Beijing to conduct geographic hierarchical parsing algorithms and aggregation interaction experiments. The experiments demonstrated that the average performance of our two aggregation methods exceeds improvements of 70% and 60% over the K-means in various scenarios, confirming the system's efficiency and stability in data processing and aggregation services. This aggregation application has been successfully implemented in the Yizhuang urban governance project, supporting large-scale urban data aggregation for millions of entities and highlighting the high feasibility of the system.

Key words: Point Aggregation, Geographical level analysis, Human-computer Interaction, Visualization Management System, Spatiotemporal Data