Modeling and estimation of heterogeneous spatiotemporal attributes under conditions of uncertainty

IEEE Transactions on Geoscience and Remote Sensing

Volumn 49, Issue 1 PART 2, 2011, Pages 366-376

  Yu, Hwa Lung ^a   Christakos, George ^b  

^a NATIONAL TAIWAN UNIVERSITY   (Taiwan)

^b SAN DIEGO STATE UNIVERSITY   (United States)

Author keywords

Bayesian maximum entropy (BME); generalized random field; knowledge synthesis; spatiotemporal analysis; uncertainty

Indexed keywords

BAYESIAN MAXIMUM ENTROPIES; GENERALIZED RANDOM FIELDS; KNOWLEDGE SYNTHESIS; SPATIOTEMPORAL ANALYSIS; UNCERTAINTY;

BAYESIAN NETWORKS; DATA HANDLING; ENTROPY; ESTIMATION; NUMERICAL METHODS;

UNCERTAINTY ANALYSIS;

BAYESIAN ANALYSIS; DATA PROCESSING; LINEARITY; NUMERICAL MODEL; SPATIOTEMPORAL ANALYSIS; STOCHASTICITY; UNCERTAINTY ANALYSIS;

EID: 78650911592     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2010.2052624     Document Type: Article

References (56)

1. R. G. Aykroyd, "Bayesian estimation for homogeneous and inhomogeneous Gaussian random fields," IEEE Trans. Pattern Anal. Mach. Intell., vol. 20, no. 5, pp. 533-539, May 1998.
2. K. J. Friston, Statistical Parametric Mapping: The Analysis of Functional Brain Images, 1st ed. Boston, MA: Elsevier/Academic, 2007.
3. L. S. Gandin, Objective Analysis of Meteorological Fields (Objektivnyi Analiz Meteorologicheskikh Polei). Jerusalem, Israel: Israel Program for Scientific Translations, 1963.
4. R. P. Haining, Spatial Data Analysis in the Social and Environmental Sciences. New York: Cambridge Univ. Press, 1990.
5. P. E. Kinahan, J. A. Fessler, and J. S. Karp, "Statistical image reconstruction in PET with compensation for missing data," IEEE Trans. Nucl. Sci., vol. 44, no. 4, pp. 1552-1557, Aug. 1997.
6. A. M. Yaglom, "Some classes of random fields in n-dimensional space related to stationary random processes," Theory Prob. Appl., vol. 2, no. 3, pp. 273-320, 1957.
7. A. M. Yaglom, Correlation Theory of Stationary and Related Random Functions. New York: Springer-Verlag, 1987.
8. R. Adler, "Some new random field tools for spatial analysis," Stochastic Environ. Res. Risk Assessment, vol. 22, no. 6, pp. 809-822, Oct. 2008.
9. G. Christakos, "Modern statistical analysis and optimal estimation of geotechnical data," Eng. Geol., vol. 22, no. 2, pp. 175-200, Oct. 1985.
10. G. Christakos, "Random field modeling and its applications in stochastic data processing," Ph.D. dissertation, Appl. Sci. Division, Harvard Univ., Cambridge, MA, 1990.
11. G. Christakos, "On certain classes of spatiotemporal random fields with applications to space-time data processing," IEEE Trans. Syst., Man, Cybern., vol. 21, no. 4, pp. 861-875, Jul./Aug. 1991.
12. G. Christakos, "Some applications of the BME concept in geostatistics," Fundam. Theor. Phys., no. 43, pp. 215-229, 1991.
13. G. Christakos, Random Field Models in Earth Sciences. San Diego, CA: Academic, 1992.
14. C. Goodall and K. V. Mardia, "Challenges in multivariate spatio-temporal modeling," in Proc. XVIIth Int. Biometrics Conf., Hamilton, ON, Canada, 1994, pp. 1-17.
15. T. C. Haas, "Local prediction of a spatio-temporal process with an application to wet sulfate deposition," J. Amer. Stat. Assoc., vol. 90, no. 432, pp. 1189-1199, Dec. 1995.
16. P. Bogaert, "Comparison of Kriging techniques in a space-time context," Math. Geol., vol. 28, no. 1, pp. 73-86, Jan. 1996. (Pubitemid 26467295)
17. J. Zidek, L. Sun, N. Le, and H. Ozkaynak, "Contending with spacetime interaction in the spatial prediction of pollution: Vancouver's hourly ambient PM10 field," Environmetrics, vol. 13, no. 5/6, pp. 595-613, Aug./Sep. 2002.
18. M. L. Serre, A. Kolovos, G. Christakos, and K. Modis, "An application of the holistochastic human exposure methodology to naturally occurring arsenic in Bangladesh drinking water," Risk Anal., vol. 23, no. 3, pp. 515- 528, Jun. 2003.
19. C. S. Ma, "Spatio-temporal stationary covariance models," J. Multivariate Anal., vol. 86, no. 1, pp. 97-107, Jul. 2003.
20. A. Douaik, M. van Meirvenne, T. Toth, and M. Serre, "Space-time mapping of soil salinity using probabilistic Bayesian maximum entropy," Stochastic Environ. Res. Risk Assessment, vol. 18, no. 4, pp. 219-227, Aug. 2004.
21. A. Kolovos, G. Christakos, D. T. Hristopulos, and M. L. Serre, "Methods for generating non-separable spatiotemporal covariance models with potential environmental applications," Adv. Water Resources, vol. 27, no. 8, pp. 815-830, Aug. 2004.
22. A. Kolovos, G. Christakos, M. L. Serre, and C. T. Miller, "Computational Bayesian maximum entropy solution of a stochastic advection-reaction equation in the light of site-specific information," Water Resour. Res., vol. 38, no. 12, pp. 54.1-54.17, Dec. 28, 2002.
23. E. Porcu, P. Gregori, and J. Mateu, "Nonseparable stationary anisotropic space-time covariance functions," Stochastic Environ. Res. Risk Assessment, vol. 21, no. 2, pp. 113-122, Dec. 2006.
24. L. F. Li, J. F. Wang, Z. D. Cao, and E. Zhong, "An information-fusion method to identify pattern of spatial heterogeneity for improving the accuracy of estimation," Stochastic Environ. Res. Risk Assessment, vol. 22, no. 6, pp. 689-704, Oct. 2008.
25. H.-L. Yu, "Development and implementation of knowledge synthesis methods for stochastic natural systems," Ph.D. dissertation, Dept. Environ. Sci. Eng., Univ. North Carolina, Chapel Hill, NC, 2005.
26. H.-L. Yu, G. Christakos, K. Modis, and G. Papantonopoulos, "A composite solution method for physical equations and its application in the Nea Kessani geothermal field (Greece)," J. Geophys. Res.-Solid Earth, vol. 112, no. B6, p. B06 104, 2007, DOI: 10.1029/2006JB004900. (Pubitemid 47354832)
27. H.-L. Yu, A. Kolovos, G. Christakos, J. C. Chen, S. Warmerdam, and B. Dev, "Interactive spatiotemporal modelling of health systems: The SEKS-GUI framework," Stochastic Environ. Res. Risk Assessment, vol. 21, no. 5, pp. 555-572, Aug. 2007.
28. K. M. Choi, H. L. Yu, and M. L. Wilson, "Spatiotemporal statistical analysis of influenza mortality risk in the State of California during the period 1997-2001," Stochastic Environ. Res. Risk Assessment, vol. 22, pp. S15-S25, Mar. 2008.
29. E. Renshaw, C. Comas, and J. Mateu, "Analysis of forest thinning strategies through the development of space-time growth-interaction simulation models," Stochastic Environ. Res. Risk Assessment, vol. 23, no. 3, pp. 275-288, Mar. 2009.
30. M. D. Ruiz-Medina, J. M. Angulo, and V. V. Anh, "Multifractality in space-time statistical models," Stochastic Environ. Res. Risk Assessment, vol. 22, pp. S81-S86, Mar. 2008.
31. G. Christakos and V. M. Vyas, "A novel method for studying population health impacts of spatiotemporal ozone distribution," Social Sci. Med., vol. 47, no. 8, pp. 1051-1066, Oct. 1998.
32. D. C. Law, K. Bernstein, M. L. Serre, C. M. Schumacher, P. A. Leone, J. M. Zenilman, W. C. Miller, and A. M. Rompalo, "Modeling an early Syphilis outbreak through space and time using the Bayesian maximum entropy approach," Ann. Epidemiol., vol. 16, no. 11, pp. 797-804, Nov. 2006.
33. G. Christakos and D. T. Hristopulos, Spatiotemporal Environmental Health Modelling. Boston, MA: Kluwer, 1998.
34. H.-L. Yu and G. Christakos, Spatiotemporal modelling and mapping of the bubonic plague epidemic in India, Int. J. Health Geographics, vol. 5, no. 12, 2006. [Online]. Avalable: http://www.ij-healthgeographics. com/content/5/1/12
35. G. Christakos and G. A. Thesing, "The intrinsic random-field model in the study of sulfate deposition processes," Atmos. Environ. A-General Topics, vol. 27, no. 10, pp. 1521-1540, Jul. 1993.
36. V. M. Vyas and G. Christakos, "Spatiotemporal analysis and mapping of sulfate deposition data over eastern USA," Atmos. Environ., vol. 31, no. 21, pp. 3623-3633, Nov. 1997.
37. G. Christakos and P. Bogaert, "Spatiotemporal analysis of spring water ion processes derived from measurements at the Dyle Basin in Belgium," IEEE Trans. Geosci. Remote Sens., vol. 34, no. 3, pp. 626-642, May 1996.
38. G. Christakos, "Recursive estimation of nonlinear-state nonlinearobservation systems," Kansas Geol. Surv., Lawerence, KS, Res. Rep. 86- 29, 1986.
39. G. Christakos, "Optimal estimation of nonlinear state nonlinear observation systems," J. Optim. Theory Appl., vol. 62, no. 1, pp. 29-48, Jul. 1989.
40. A. Bardossy, "Copula-based geostatistical models for groundwater quality parameters," Water Resour. Res., vol. 42, no. 11, p. W11 416, Nov. 21, 2006.
41. A. Bardossy and J. Li, "Geostatistical interpolation using copulas," Water Resour. Res., vol. 44, no. 7, p. W07 412, Jul. 24, 2008.
42. H. Kazianka and J. Pilz, "Copula-based geostatistical modeling of continuous and discrete data including covariates," Stochastic Environ. Res. Risk Assessment, vol. 24, no. 5, pp. 661-673, Jul. 2010.
43. G. Christakos, Modern Spatiotemporal Geostatistics. New York: Oxford Univ. Press, 2000.
44. G. Christakos, P. Bogaert, and M. L. Serre, Temporal GIS. NewYork: Springer-Verlag, 2002.
45. I. M. Gelfand and G. E. Shilov, Generalized Functions. New York: Academic, 1964.
46. M. Loève, Probability Theory. Princeton, NJ: Van Nostrand, 1963.
47. A. Stein, "Analysis of space-time variability in agriculture and the environment with geostatistics," Statistica Nederlandica, vol. 52, no. 1, pp. 18-41, Mar. 1998.
48. P. K. Kitanidis, "Statistical estimation of polynomial generalized covariance functions and hydrologic applications," Water Resour. Res., vol. 19, no. 4, pp. 909-921, 1983.
49. E. Pardo-Iguzquiza, "GCINFE: A computer program for inference of polynomial generalized covariance functions," Comput. Geosci., vol. 23, no. 2, pp. 163-174, Mar. 1997.
50. G. Christakos, "On the assimilation of uncertain physical knowledge bases: Bayesian and non-Bayesian techniques," Adv. Water Resour., vol. 25, no. 8-12, pp. 1257-1274, Aug.-Dec. 2002.
51. G. Christakos, Integrative Problem-Solving in a Time of Decadence. New York: Springer-Verlag, 2010.
52. A. Kolovos, H.-L. Yu, and G. Christakos, SEKS-GUI v.0.6. User's Manual-06 Ed. San Diego, CA: Dept. of Geography, San Diego State Univ., 2006.
53. S.-J. Lee, E. A. Wentz, and P. Gober, "Space-time forecasting using soft geostatistics: A case study in forecasting municipal water demand for Phoenix, Arizona," Stochastic Environ. Res. Risk Assessment, vol. 24, no. 2, pp. 283-295, Feb. 2009.
54. T. C. Yang and P. S. Yu, "Application of fuzzy multi-objective function on reducing groundwater demand for aquaculture in land-subsidence areas," Water Resour. Manage., vol. 20, no. 3, pp. 377-390, Jun. 2006.
55. T. Mikosch, "Copulas: Tales and facts," Extremes, vol. 9, no. 1, pp. 3-20, Mar. 2006.
56. C. Scholzel and P. Friederichs, "Multivariate non-normally distributed random variables in climate research-Introduction to the copula approach," Nonlinear Process. Geophys., vol. 15, no. 5, pp. 761-772, 2008.