Prediction of 2 x 2 tables of change from repeat cluster sampling of marginal counts

Canadian Journal of Forest Research

Volumn 34, Issue 8, 2004, Pages 1703-1713

  Magnussen, Steen ^a  

^a LAURENTIAN FORESTRY CENTRE   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL GEOMETRY; CORRELATION METHODS; ERROR DETECTION; PARAMETER ESTIMATION; SAMPLING;

CLUSTER SAMPLING; HYPERGEOMETRIC DISTRIBUTION; ROOT MEAN SQUARE ERRORS;

FORESTRY;

CLUSTER ANALYSIS; SAMPLING; STATISTICAL ANALYSIS;

CORRELATION; FORESTRY; GEOMETRY; PARAMETERS; SAMPLING;

EID: 8644237535     PISSN: 00455067     EISSN: None     Source Type: Journal    
DOI: 10.1139/X04-041     Document Type: Article

References (53)

1. Agresti, A. 1992. A survey of exact inference for contingency tables. Stat. Sci. 7: 131-177.
2. Ahn, C., and Odom-Maryon, T. 1995. Estimation of a common odds ratio under binary cluster sampling. Stat. Med. 14: 1567-1576.
3. Anderson, A.B. 2002. Detecting changes in natural resources using Land Condition Trend Analysis data. Environ. Manage. 29: 428-436.
4. Antelman, G.R. 1972. Interrelated Bernoulli processes. J. Am. Stat. Assoc. 67: 831-841.
5. Brown, S. 2002. Measuring, monitoring, and verification of carbon benefits for forest-based projects. Philos. Trans. R. Soc. Lond. A Math. Phys. Sci. 360: 1669-1683.
6. Cihlar, J., Latifovic, R., Beaubien, J., Guindon, B., and Palmer, M. 2003. Thematic mapper (TM) based accuracy assessment of a land cover product for Canada derived from SPOT VEGETATION (VGT) data. Can. J. Rem. Sens. 29: 154-170.
7. Collett, D. 1991. Modelling binary data. Chapman & Hall Ltd., London.
8. Congalton, R.G. 1991. A review of assessing the accuracy of classification of remotely sensed data. Remote Sens. Environ. 37: 35-45.
9. Congalton, R.G. 2001. Accuracy assessment and validation of remotely sensed and other spatial information. Int. J. Wildland Fire, 10: 321-328.
10. Coomes, D.A., Allen, R.B., Scott, N.A., Goulding, C., and Beets, P. 2002. Designing systems to monitor carbon stocks in forests and shrublands. For. Ecol. Manage. 164: 89-108.
11. Corona, P., Chirici, G., and Marchetti, M. 2002. Forest ecosystem inventory and monitoring as a framework for terrestrial natural renewable resource survey programmes. Plant Biosyst. 136: 69-82.
12. Cox, D.R. 2003. Conditional and marginal association for binary random variables. Biometrika, 90: 982-984.
13. Diggle, P.J. 1988. An approach to the analysis of repeated measurements. Biometrics, 44: 959-971.
14. Duerr, H.P., and Dietz, K. 2000. Stochastic models for aggregation processes. Math. Biosci. 165: 135-145.
15. Fleiss, J.L. 1981. Statistical methods for rates and proportions. John Wiley & Sons Inc., New York.
16. Foody, G.M. 2000. Accuracy of thematic maps derived from remote sensing. In Accuracy 2000: Proceedings of the 4th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, Amsterdam, 12-14 July 2000. Edited by G.B.M. Heuvelink and M.J.P.M. Lemmens. Delft University Press, Amsterdam. pp. 217-224.
17. Foody, G.M. 2002. Status of land cover classification accuracy assessment. Remote Sens. Environ. 80: 185-201.
18. Franklin, S.E. 2001. Remote sensing for sustainable forest management. Lewis Publishers, Inc., Boca Raton, Fla.
19. Gallant, A.R. 1987. Nonlinear statistical methods. John Wiley & Sons Inc., New York.
20. Genest, C., and Boies, J.-C. 2003. Detecting dependence with Kendall plots. Am. Stat. 57: 275-284.
21. Goodenough, D.G., Bhogal, A.S., Dyk, A., Apps, M.J., Hall, R.J., Tickle, P., Chen, H., Butler, K., and Gim, A. 2000. Determination of above-ground carbon in Canada's forests. In International Geoscience and Remote Sensing Symposium, Honolulu, Hawaii, 24-28 July 2000. Institute of Electrical and Electronics Engineers, Inc., Piscataway, N.J.
22. Irony, T.Z., Pereira, C.A.d.B., and Tiwari, R.C. 2000. Analysis of opinion swing: comparison of two correlated proportions. Am. Stat. 54: 57-62.
23. Kaiser, M.S., and Cressie, N. 2000. The construction of multivariate distributions from Markov random fields. Journal of Multivariate Analysis, 73: 199-220.
24. Kennedy, R.E., and Cohen, W.B. 2003. Automated designation of tie-points for image-to-image coregistration. Int. J. Remote Sens. 24: 3467-3490.
25. Lichstein, J.W., Simons, T.R., Shriner, S.A., and Franzreb, K.E. 2002. Spatial autocorrelation and autoregressive models in ecology. Ecol. Monogr. 72: 445-463.
26. Lloyd, C.J. 1999. Analysis of categorical variables. John Wiley & Sons Inc., New York.
27. Long, D., and Krzysztofowicz, R. 1995. A family of bivariate densities constructed from marginals. J. Am. Stat. Assoc. 90: 739-746.
28. Lunetta, R.S., and Elvidge, C.D. 1999. Remote sensing change detection. Environmental monitoring methods and applications. Taylor & Francis Ltd., London.
29. Lunetta, R.S., Congalton, R.G., Fenstermaker, L.K., Jensen, J.R., McGwire, K.C., and Tinney, L.R. 1991. Remote sensing and geographic information system data integration: error sources and research issues. Photogramm. Eng. Remote Sens. 57: 677-687.
30. Magnussen, S. 1997. A method for enhancing tree species proportions from aerial photos. For. Chron. 73: 479-487.
31. Magnussen, S., and de Bruin, S. 2003. Updating cover type maps using sequential indicator simulation. Remote Sens. Environ. 87: 161-170.
32. Martin, L.R.G., and Howarth, P.J. 1989. Change-detection accuracy assessment using SPOT multispectral imagery of the rural-urban fringe. Remote Sens. Environ. 30: 55-66.
33. Mizoue, N., and Dobbertin, M. 2003. Detecting differences in crown transparency assessments between countries using the image analysis system CROCO. Environ. Monit. Assess. 89: 179-195.
34. Nakajima, N.Y., Yoshida, S., and Imanaga, M. 1996. Comparison of change estimation between four ground-survey methods for use in a continuous forest inventory system. J. For. Plann. 2: 145-150.
35. Nelder, J.A., and Mead, R. 1965. A simplex method for function minimization. Comput. J. 7: 308-313.
36. O'Laughlin, J., and Cook, P.S. 2003. Inventory-based forest health indicators - implications for national forest management. J. For. 101: 11-17.
37. Parr, T.W., Ferretti, M., Simpson, I.C., Forsius, M., and Kovacs-Lang, E. 2002. Towards a long-term integrated monitoring programme in Europe: network design in theory and practice. Environ. Monit. Assess. 78: 253-290.
38. Patil, G.P., and Taillie, C. 2003. Modeling and interpreting the accuracy assessment error matrix for a doubly classified map. Environ. Ecol. Stat. 10: 357-373.
39. Patterson, P.L., and Williams, M.S. 2003. Effects of registration erors between remotely sensed and ground data on estimators of forest area. For. Sci. 49: 110-118.
40. Pendergast, J.F., Gange, S.J., Newton, M.A., Lindstrom, M.J., Palta, M., and Fisher, M.R. 1996. A survey of methods for analyzing clustered binary response data. Int. Stat. Rev. 64: 89-118.
41. Pratt, W.K. 1991. Digital image processing. John Wiley & Sons Inc., New York.
42. Prentice, R.L. 1986. Binary regression using an extended beta-binomial distribution, with discussion of correlations induced by covariate measurement errors. J. Am. Stat. Assoc. 81: 321-327.
43. Raffy, M. 1994. Change of scale theory: a capital challenge for space observation of earth. Int. J. Remote Sens. 15: 2353-2357.
44. Ridout, M.S., Demetrio, C.G.B., and Firth, D. 1999. Estimating intra-class correlation for binary data. Biometrics, 55: 137-148.
45. Rosner, B., and Milton, R.C. 1988. Significance testing for correlated binary outcome data. Biometrics, 44: 505-512.
46. Särndal, C.-E., Swensson, B., and Wretman, J. 1992. Model assisted survey sampling. Springer-Verlag New York Inc., New York.
47. Snedecor, G.W., and Cochran, W.G. 1971. Statistical methods. Sixth ed. Iowa State University Press, Ames, Iowa.
48. Steele, B.M., Patterson, D.A., and Redmond, R.L. 2003. Toward estimation of map accuracy without a probability test sample. Environ. Ecol. Stat. 10: 333-356.
49. Suratman, M.N. 2003. Applicability of Landsat TM data for inventorying and monitoring of rubber (Hevea brasiliensis) plantations in Selangor, Malaysia: linkages to policies. Ph.D. thesis, The University of British Columbia, Vancouver, B.C.
50. Upton, G.J.G., and Fingleton, B. 1985. Spatial data analysis by example. Point patterns and quantitative data. John Wiley & Sons Ltd., Chichester, UK.
51. Wang, Z.G., and Louis, T.A. 2003. Matching conditional and marginal shapes in binary random intercept models using a bridge distribution function. Biometrika, 90: 765-775.
52. Woodcock, C.E., Macomber, S.A., Pax-Lenney, M., and Cohen, W.B. 2001. Monitoring large areas for forest change using Landsat: generalization across space, time and Landsat sensors. Remote Sens. Environ. 78: 194-203.
53. Wulder, M., Cranny, M., and Dechka, J. 2002. An illustrated methodology for land cover mapping of forests with Landsat-7 ETM+ data: methods in support of EOSD land cover. Version 2. Canadian Forest Service, Internal Report, Victoria, BC.