The Multi-level Visualization Task Model for Multi-modal Spatio-temporal Data

doi:10.11947/j.AGCS.2018.20180104

Acta Geodaetica et Cartographica Sinica ›› 2018, Vol. 47 ›› Issue (8): 1098-1104.doi: 10.11947/j.AGCS.2018.20180104

The Multi-level Visualization Task Model for Multi-modal Spatio-temporal Data

LIU Mingwei¹, ZHU Qing¹, ZHU Jun¹, FENG Bin¹, LI Yun¹, ZHANG Junxiao¹, FU Xiao¹, ZHANG Pengcheng², YANG Weijun², NING Xinwen^1,3, XU Wanyan⁴

1. Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China;
2. Guangzhou Urban Planning and Design Survey Research Institute, Guangzhou 510060, China;
3. China Railway Design Corporation, Tianjin 300251, China;
4. The Bureau of Land and Resources of Lipu, Guilin 546600, China

Received:2018-01-12 Revised:2018-04-04 Online:2018-08-20 Published:2018-08-22
Supported by:
The National Natural Science Foundation of China (No. 41471320);The Smart Guangzhou Spatio-temporal Information Cloud Platform Construction (No. GZIT2016-A5-147)

Abstract

Abstract: The existing spatio-temporal data visualization methods are mainly targeted at low-level view-only visualization tasks,which is difficult to meet the high concurrency and multi-level visualization tasks of multi-modal spatio-temporal data.To address this challenge,it is presented that the multi-level visualization task model for multi-modal spatiotemporal data,which categorized the visualization task as view-only visualization task,analytical visualization task and explorative visualization task.The main features of this model are:①it described the main driving forces and spatio-temporal information needed in different level of tasks;②it described the requirements of task and its relationship between storage,computing and rendering.Based on the model,task-aware and adaptive spatiotemporal data visualization engine is designed.Finally taking the refinement management and decision-making applications in smart city as an example,the model is proved to be effectively meet the needs of multi-level visualization and analysis applications and could lay a solid foundation for the complex applications in smart city.

Key words: multi-modal spatio-temporal data, visualization task, task model, task-aware, adaptive visualization

CLC Number:

P208

LIU Mingwei, ZHU Qing, ZHU Jun, FENG Bin, LI Yun, ZHANG Junxiao, FU Xiao, ZHANG Pengcheng, YANG Weijun, NING Xinwen, XU Wanyan. The Multi-level Visualization Task Model for Multi-modal Spatio-temporal Data[J]. Acta Geodaetica et Cartographica Sinica, 2018, 47(8): 1098-1104.

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The Multi-level Visualization Task Model for Multi-modal Spatio-temporal Data

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