A framework of integrating GIS and parallel computing for spatial control problems - a case study of wildfire control

International Journal of Geographical Information Science

Volumn 26, Issue 4, 2012, Pages 621-641

  Yin, Ling ^a,b   Shaw, Shih Lung ^a,c   Wang, Dali ^d   Carr, Eric A ^a   Berry, Michael W ^e   Gross, Louis J ^a   Comiskey, E Jane ^a  

^a UNIVERSITY OF TENNESSEE   (United States)

^b SHENZHEN INSTITUTES OF ADVANCED TECHNOLOGY   (China)

^c WUHAN UNIVERSITY   (China)

^d OAK RIDGE NATIONAL LABORATORY   (United States)

^e University of Tennessee   (United States)

Author keywords

GIS; parallel computing; spatial control; wildfire control

Indexed keywords

GIS; INTEGRATED APPROACH; PARALLEL COMPUTING; REAL TIME; SOFTWARE; SPATIAL ANALYSIS; SPATIAL DATA; WILDFIRE; WORLD WIDE WEB;

EID: 84859395506     PISSN: 13658816     EISSN: 13623087     Source Type: Journal    
DOI: 10.1080/13658816.2011.609487     Document Type: Article

References (45)

1. Almeida, C.M. 2003. Stochastic cellular automata modeling of urban land use dynamics: empirical development and estimation. Computers, Environment and Urban Systems, 27: 481-509.
2. Armstrong, M.P., Cowles, M.K. and Wang, S. 2005. Using a computational grid for geographic information analysis: a reconnaissance. The Professional Geographer, 57: 365-375.
3. Armstrong, M.P. and Densham, P.J. 1992. Domain decomposition for parallel processing of spatial problems. Computer, Environment, and Urban Systems, 16: 497-513.
4. Armstrong, M.P., Densham, P.J. and Rushton, G. Architecture for a microcomputer based spatial decision support system. Proceedings of the 2nd International Symposium on Spatial Data Handling. July5-101986, Seattle, Washington. pp.120-131. Williamsville, NY: International Geographic Union.
5. Batty, M., Xie, Y. and Sun, Z. 1999. Modeling urban dynamics through GIS-based cellular automata. Computers, Environment and Urban Systems, 23: 205-233.
6. Berjak, S.G. and Hearne, J.W. 2002. An improved cellular automation model for simulating fire in a spatially heterogeneous Savanna system. Ecological Modeling, 148: 133-151.
7. Birkin, M., Clarke, M. and Geoge, F. 1995. The use of parallel computers to solve nonlinear spatial optimization problems: an application to network planning. Environment and Planning A, 27: 1049-1068.
8. Brookes, C.J. 2001. A genetic algorithm for designing optimal patch configurations in GIS. International Journal of Geographical Information Science, 15: 539-559.
9. Cantú-Paz, E. 2000. Efficient and accurate parallel genetic algorithms, Boston, MA: Kluwer Academic Publishers.
10. Clematis, A., Mineter, M. and Marciano, R. 2003. High performance computing with geographical data. Parallel Computing, 29: 1275-1279.
11. Cooper, L. 1964. Heuristic methods for location-allocations problems. SIAM Review, 6: 37-54.
12. Densham, P.J. 1991. "Spatial decision support systems". In Geographical information systems: principles and applications, Edited by: Maguire, D.J., Goodchild, M.F. and Rhind, D.W. Vol. 1, 403-412. London: Longman.
13. Dorigo, M. 1992. "Optimization, learning and natural algorithms". In Dissertation (PhD), Italy: Politecnico di Milano.
14. Fuller, M.M. 2007. Current problems and future directions in computational science for natural resource management. IEEE Computing in Science and Engineering, 9: 40-48.
15. Garey, M. and Johnson, D. 1979. "Computers and intractability: a guide to the theory of NP-completeness". In San Francisco, CA: W. H. Freeman.
16. Glover, F. and Laguna, M. 1997. Tabu search, Boston, MA: Kluwer Academic Publishers.
17. Goodchild, M.F. 2004. The validity and usefulness of laws in geographic information science and geography. Annals of the Association of American Geographers, 94: 300-303.
18. Healey, R. 1998. Parallel processing algorithms for GIS, Bristol, PA: Taylor and Francis.
19. Hoff, J.G. and Bevers, M. 1998. Spatial optimization for managed ecosystems, New York: Columbia University Press.
20. Holland, J. 1975. Adaptations in natural and artificial systems, Ann Arbor, MI: University of Michigan Press.
21. Hosage, C.M. and Goodchild, M.F. 1986. Discrete space location-allocation solutions from genetic algorithms. Annals of Operations Research, 6: 35-46.
22. Jankowski, P. 1997. Spatial group choice: a SDSS tool for collaborative spatial decision-making. International Journal of Geographical Information Systems, 11: 577-602.
23. Karafyllidis, I. and Thanailakis, A. 1997. A model for predicting forest fire spreading using cellular automata. Ecological Modeling, 99: 87-97.
24. Kirkpatrick, S., Gelatt, C.D. and Vecchi, M.P. Jr. 1983. Optimization by simulated annealing. Science, 220: 671-680.
25. Li, X. and Liu, X. 2008. Embedding sustainable development strategies in agent-based models for use as a planning tool. International Journal of Geographical Information Science, 22: 21-45.
26. Li, X. and Yeh, A.G.O. 2000. Modelling sustainable urban development by the integration of constrained cellular automata and GIS. International Journal of Geographical Information Science, 14: 131-152.
27. Li, X. and Yeh, A.G.O. 2005. Integration of genetic algorithms and GIS for optimal location search. International Journal of Geographical Information Science, 19: 581-601.
28. Malczewski, J. 1999. GIS and multicriteria decision analysis, New York: Wiley.
29. Miller, H. 2004. Tobler's first law and spatial analysis. Annals of the Association of American Geographers, 94: 284-289.
30. Miller, H. and Shaw, S.-L. 2001. Geographic information systems for transportation: principles and applications, New York: Oxford University Press.
31. Ntaimo, L. 2004. Forest fire spread and suppression in DEVS. Simulation, 80: 479-500.
32. Ohgai, A. 2005. "Development of a webGIS supporting community-based planning for disaster mitigation integrated with a fire spread simulation model using CA". In Resource paper in 9th international conference on computer in urban planning and urban management, 29 June-1 July 2005 London
33. Openshaw, S. and Openshaw, C. 1997. Artificial intelligence in geography, Chichester, UK: Wiley.
34. O'sullivan, D. and Unwin, D.J. 2003. Geographic information analysis, Hoboken, NJ: Wiley.
35. Perry, G.L.W. 1998. Current approaches to modelling the spread of wildland fire: a review. Progress in Physical Geography, 22: 222-245.
36. Rückemann, C.-P. Using parallel multicore and HPC systems for dynamical visualisation. Proceeding of the international conference on advanced geographic information systems & web services 2009. February1-72009, Cancun, Mexico. Edited by: Dragicevic, S., Roman, D. and Tanasescu, V. pp.13-18. Los Alamitos, CA: IEEE Computer Societ Press.
37. Simão, A., Densham, P.J. and Haklay, M. 2009. Web-based GIS for collaborative planning and public participation: an application to the strategic planning of wind farm sites. Journal of Environmental Management, 90: 2027-2040.
38. Tan, Y., Gu, X. and Wang, H. Adaptive system anomaly prediction for large-scale hosting infrastructures. Proceeding of the 29th annual ACM symposium on principles of distributed computing. July25-282010, Zurich, Switzerland. Edited by: Richa, Andréa W. and Guerraoui, Rachid. pp.173-182. New York: ACM Press.
39. Tobler, W.R. 1970. A computer movie simulating urban growth in the Detroit region. Economic Geography, 46: 234-240.
40. Vouk, M. 2008. Cloud computing-issues, research and implementations. Journal of Computing and Information Technology, 4: 235-246.
41. Wang, D. August 2006, San Diego 2006. "A GIS-enabled distributed simulation framework for high performance ecosystem modeling". In Proceedings of ESRI International User Conference August 2006, San Diego, 7-11.
42. Wang, S. 2010. A CyberGIS framework for the synthesis of cyberinfrastructure, GIS, and spatial analysis. Annals of the Association of American Geographers, 100: 535-557.
43. Wang, S. and Armstrong, M.P. 2003. A quadtree approach to domain decomposition for spatial interpolation in grid computing environments. Parallel Computing, 29: 1481-1504.
44. Wu, F. and Webster, C.J. 2000. Simulating artificial cities in a GIS environment: urban growth under alternative regulation regimes. International Journal of Geographical Information Science, 14: 625-648.
45. Xiao, N. 2008. A unified conceptual framework for geographical optimization using evolutionary algorithms. Annals of the Association of American Geographers, 98: 795-817.