Visualization Method Research And System Implementation Of Urban Spatiotemporal Data

The urban spatiotemporal data visualization is essential for understanding urban cities.Resulting from the complexity of spatiotemporal datasets,it is challenging for current data visualization approaches to discover valuable information from the large datasets and to focus on urban field.This paper contributes on effectively visualizing the spatiotemporal datasets in the context of urban planning,and reducing the visual clutter using the multi-resolution methods.The relevant urban visualization system is also implemented,which helps individuals to analyze and explore the urban spatiotemporal data visualization in valid.In this paper,a method of spatiotemporal data visualization based on Urban Planning scenario is proposed.This method summarizes the general requirements of urban planners,and describes the basic procedure of data processing and data modeling in this scenario,and finally proposes a basic visualization framework architecture for this scenario.In this paper,a method of urban spatiotemporal data visualization based on multi-resolution hierarchical structure is proposed.The method firstly samples the original data at multi-resolution levels.Secondly,a hierarchical aggregation algorithm is applied.The OD data or trajectory data are aggregated at different scales.Concurrently,particular approximate visual query strategies are proposed to pre-calculate and aggregate the spatiotemporal attributes,so as to reduce the time delay of online interactive visualization.In this paper,an urban spatiotemporal data visualization system based on multi-resolution hierarchical structure is implemented.Based on the B/S architecture,the system is designed and implemented with the principle of front-end separation and modular development mode.The system provides multi-resolution analysis and visualization for data exchange of urban space,and supports the interaction and exploration of various attributes,realizing a multi-scale,multi-perspective and multi-dimensional visualization and analysis of urban spatiotemporal data.The results of case analysis and performance test based on real urban datasets show that the visualization system can efficiently and effectively support and assist individuals to understand and analyze urban spatiotemporal datasets.