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Environmental Earth Sciences

, Volume 74, Issue 10, pp 7133–7146 | Cite as

Visual analysis and simulation of dam-break flood spatiotemporal process in a network environment

  • Lingzhi Yin
  • Jun ZhuEmail author
  • Xiang Zhang
  • Yi Li
  • Jinhong Wang
  • Heng Zhang
  • Xiaofeng Yang
Thematic Issue

Abstract

Geographic modeling and simulation is now regarded as a fundamental approach to geographic process mining and complex geographic problems, such as dam-break floods. With the rapid development of web services and network technologies in the context of GIS, it is possible to offer a new generation of geographic analysis tools that are based on new types of Web and computer-based geographic environments that are built for understanding geographic processes and problem solving. This paper focuses on the visual analysis and simulation of dam-break flood spatiotemporal process in a network environment. The simulations were implemented with HTML5, WebGL, Ajax and Web Service and other technologies and also included the rapid computation of spatiotemporal process models, B/S network architecture construction, three-dimensional scene rendering optimization and dynamic interaction analysis. Finally, a prototype system was constructed, and an experiment was conducted to analyze dam-break flood spatiotemporal process visually in a case study region in a network simulation. The experimental results show that the scheme addressed in this paper can be used to publish spatiotemporal process information, online impact analyses and three-dimensional visualization representations in a network environment that is suitable for browsing, querying and analysis. This scheme can be used efficiently to understand dam-break flood process and support dam-break risk management.

Keywords

WebGIS Dam-break flooding Spatiotemporal process Visual analysis Network simulation 

Notes

Acknowledgments

This research is partially supported by the National Key Basic Research Program of China (Grant No. 2015CB954101), the National Natural Science Foundation of China (Grant No. 41271389 and 41001252), the Program for Changjiang Scholars and Innovative Research Team in University (Grant No. IRT13092), Special Fund by Surveying and Mapping and Geoinformation Research in the Public Interest (201412010), Open Research Fund by Sichuan Engineering Research Center for Emergency Mapping & Disaster Reduction (J2014ZC17) and the Graduate Innovation Fund of Southwest Jiaotong University under Grant (YC201414233). The authors thank two anonymous reviewers and editors whose comments have notably improved the manuscript.

Supplementary material

Supplementary material 1 (WMV 9432 kb)

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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Lingzhi Yin
    • 1
    • 2
  • Jun Zhu
    • 1
    • 2
    Email author
  • Xiang Zhang
    • 2
  • Yi Li
    • 3
  • Jinhong Wang
    • 4
  • Heng Zhang
    • 2
  • Xiaofeng Yang
    • 2
  1. 1.State-province Joint Engineering Laboratory of Spatial Information Technology for High-speed Railway SafetySouthwest Jiaotong UniversityChengduPeople’s Republic of China
  2. 2.Faculty of Geosciences and Environmental EngineeringSouthwest Jiaotong UniversityChengduPeople’s Republic of China
  3. 3.State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital EarthChinese Academy of SciencesBeijingPeople’s Republic of China
  4. 4.Shell China Exploration and Production Co LtdBeijingPeople’s Republic of China

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