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A Web-Based Decision Support System For Wildfire Management

Ouyang, Weichen
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1406901679

Abstract Details

2014, MS, University of Cincinnati, Engineering and Applied Science: Computer Science.
Wild?re is one of the most signi?cant disturbances responsible for reshaping the terrain and changing the ecosystem as well as causing massive loss of human lives and properties. The growing trend in terms of frequency and intensity over the last decade have necessitated the development of more portable and ef?cient Wildfire Management Systems. In this thesis, different from the traditional desktop application of similar systems, we proposed and implemented a web-based Wildfire Management System----“ForestFireCloud”. Taking full advantage of the powerful functionality of Data Visualization and GIS data processing of the new Google Maps API v3, along with other modern web developing framework, we construct a portable wildfire monitoring, modeling and management platform, including several subsystems: a near real-time wildfire monitoring system based on WMS and RSS; a new fire danger assessment model targeting both meteorological and anthropogenic factors; a fire propagation simulation system based on cellular automata(CA). To monitor current wildfire status in real-time, we mainly use Google Map API to visualize fire observation data in KML and JSON format gathered from data feeds provided by several national wildfire management agencies. In our fire danger assessment system, a modified Keetch-Byram Drought Index (KBDI) is introduced as a diagnostic and forecasting measure to assess the potential of wildfire; a web-based KBDI calculator and visualization system is also implemented. Besides, we introduce a new mechanism to visualize fire record data and intense traffic spot; based on that we conduct an experiment to observe the correlation between traffic hotspot and wildfire occurrence, which yields a strong evidence shows a causality relation between the two objects. At last, to target the difficulty of precise prediction of wild?re propagation behavior caused by uncertainties in weather conditions as well as imperfect knowledge about exact vegetation and topographical conditions, we present a prototype of wildfire propagation model based on cellular automata and discrete terrain representations.
Chia Han, Ph.D. (Committee Chair)
Susanna Tong, Ph.D. (Committee Member)
Anca Ralescu, Ph.D. (Committee Member)
112 p.
Computer Science
Wildfire; Google Maps API; KML; JSON; Cellular Automata; KBDI

Recommended Citations

Citations

  • Ouyang, W. (2014). A Web-Based Decision Support System For Wildfire Management [Master's thesis, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1406901679

    APA Style (7th edition)

  • Ouyang, Weichen. A Web-Based Decision Support System For Wildfire Management. 2014. University of Cincinnati, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1406901679.

    MLA Style (8th edition)

  • Ouyang, Weichen. "A Web-Based Decision Support System For Wildfire Management." Master's thesis, University of Cincinnati, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1406901679

    Chicago Manual of Style (17th edition)

ucin1406901679
724
© 2014, all rights reserved.
This open access ETD is published by University of Cincinnati and OhioLINK.