A 3D Geosciences Modeling System for Large-Scale Water-Diversion Projects

Liu, Siyuan; Wen, Gaojin; Jianping, Fan

doi:10.1109/mcse.2010.1

Cited by 3 publications

(4 citation statements)

References 15 publications

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“…To visualize the distribution information, for example, the hot spots in the city, we utilize a heat map to represent the statistic data. To speed up visualization efficiency, we utilize the level of details [35] to investigate the large-scale trajectory data in digital map. In this paper, we will introduce our fingerprinting technique.…”

Section: Main Techniquesmentioning

confidence: 99%

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VAIT: A Visual Analytics System for Metropolitan Transportation

Liu

Luo

et al. 2013

IEEE Trans. Intell. Transport. Syst.

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With the increasing availability of metropolitan transportation data, such as those from vehicle Global Positioning Systems (GPSs) and road-side sensors, it has become viable for authorities, operators, and individuals to analyze the data for better understanding of the transportation system and, possibly, improved utilization and planning of the system. We report our experience in building the Visual Analytics for Intelligent Transportation (VAIT) system, which is the first system on real-life large-scale data sets for intelligent transportation. Our key observation is that metropolitan transportation data are inherently visual as they are spatio-temporal around road networks. Therefore, we visualize and manage traffic data, together with digital maps, and support analytical queries through this interactive visual interface. As a case study, we demonstrate VAIT on real-world taxi GPS and meter data sets from 15 000 taxis running for two months in a Chinese city of over 10 million people. We discuss the technical challenges in data calibration, storage, visualization, and query processing and offer first-hand lessons learned from developing the system. Based on our extensive empirical experiment results, VAIT beats state-of-the-art methods and systems in terms of scalability, efficiency, and effectiveness and offers us an easy-to-use, efficient, and scalable platform to shed more light on intelligent transportation research.

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Section: Main Techniquesmentioning

confidence: 99%

“…The server is equipped with eight AMD Athlon(tm) II X2 B24 processors running at 3.01 GHz each and 24-GB RAM. We employed JDBC to connect to the database server and Java swing to develop visualization modules [35], [40].…”

Section: A Experiments Setupmentioning

confidence: 99%

VAIT: A Visual Analytics System for Metropolitan Transportation

Liu

Luo

et al. 2013

IEEE Trans. Intell. Transport. Syst.

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“…To visualize the distribution information, for example, the hot spots in the city, we utilize a heat map to represent the statistic data. To speed up visualization efficiency, we utilize the LOD (Level of Details [14]) to investigate the large scale trajectory data in digital map. In VAST, we provide a history scheme for users to track their operations so that users can always go back to any step in their operations.…”

Section: Visualizationmentioning

confidence: 99%

“…The digital map is a .shp file (including bit maps and vectors to describe the objects in the digital map). We divided the map into different layers in VAST with each layer storing one kind of geographic objects, such as buildings, road networks and mountain areas [14].…”

Section: Experiments Setupmentioning

confidence: 99%

A visual analytics system for metropolitan transportation

Liu¹,

Liu

Luo³

et al. 2011

Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

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With the increasing availability of metropolitan transportation data, such as those from vehicle GPSs (Global Positioning Systems) and road-side sensors, it becomes viable for authorities, operators, as well as individuals to analyze the data for a better understanding of the transportation system and possibly improved utilization and planning of the system. We report our experience in building the VAST (Visual Analytics for Smart Transportation) system. Our key observation is that metropolitan transportation data are inherently visual as they are spatio-temporal around road networks. Therefore, we visualize traffic data together with digital maps and support analytical queries through this interactive visual interface. As a case study, we demonstrate VAST on real-world taxi GPS and meter data sets from 15, 000 taxis running two months in a Chinese city of over 10 million population. We discuss the technical challenges in data cleaning, storage, visualization, and query processing, and offer our first-hand lessons learned from developing the system.

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Three-dimensional visual analysis for construction layout of reservoir project

Zhong

Wang

et al. 2012

Trans. Tianjin Univ.

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A 3D Geosciences Modeling System for Large-Scale Water-Diversion Projects

Cited by 3 publications

References 15 publications

VAIT: A Visual Analytics System for Metropolitan Transportation

VAIT: A Visual Analytics System for Metropolitan Transportation

A visual analytics system for metropolitan transportation

Three-dimensional visual analysis for construction layout of reservoir project

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