Assessing the ground data requirements for regional scale remote sensing of tropical forest biophysical properties

International Journal of Remote Sensing

Volumn 21, Issue 13-14, 2000, Pages 2571-2587

  Atkinson, P M ^a   Foody, G M ^a   Curran, P J ^a   Boyd, D S ^b  

^a UNIVERSITY OF SOUTHAMPTON   (United Kingdom)

^b KINGSTON UNIVERSITY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

AVHRR; NOAA SATELLITE; REGRESSION ANALYSIS; REMOTE SENSING; SAMPLING; TROPICAL FOREST;

EID: 0033904637     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/01431160050110188     Document Type: Article

References (43)

1. ATKINSON, A. C., and DONEV, A. N., 1992, Optimum Experimental Designs (Oxford: Oxford University Press).
2. ATKINSON, P. M., 1991, Optimal ground-based sampling for remote sensing investigations: estimating the regional mean. International Journal of Remote Sensing, 12, 559-567.
3. ATKINSON, P. M., 1997, Scale and spatial dependence, In Scaling-up, edited by P. R. van Gardingen, G. M. Foody and P. J. Curran (Cambridge: Cambridge University Press), pp. 35-60.
4. ATKINSON, P. M., 2000, Mapping the forests of Cameroon: scales and scaling-up. In Vegetation Mapping: From Patch to Planet, edited by R. Alexander (Chichester: Wiley) (in press).
5. ATKINSON, P. M., and CURRAN, P. J., 1995, Defining an optimal size of support for remote sensing investigations. IEEE Transactions on Geoscience and Remote Sensing, 33, 1-9.
6. ATKINSON, P. M., and CURRAN, P. J., 1997, Choosing an appropriate spatial resolution for remote sensing investigations. Photogrammetric Engineering and Remote Sensing, 63, 1345-1351.
7. BIAN, L., and WALSH, S. J., 1993, Scale dependencies of vegetation and topography in a Mountainous environment in Montana. The Professional Geographer, 45, 1-11.
8. BURGESS, T. M., and WEBSTER, R., 1980, Optimal interpolation and isarithmic mapping of soil properties II. Block kriging. Journal of Soil Science, 31, 333-341.
9. BURGESS, T. M., WEBSTER, R., and MOBRATNEY, A. B., 1981, Optimal interpolation and isarithmic mapping of soil properties IV. Sampling strategy. Journal of Soil Science, 32, 643-659.
10. CARR, J. R., 1996, Spectral and textural classification of single and multiple band digital images. Computers and Geosciences, 22, 849-865.
11. COHEN, W. B., SPIES, T. A., and BRADSHAW, G. A., 1990, Semivariograms of digital imagery for analysis of conifer canopy structure. Remote Sensing of Environment, 34, 167-178.
12. CRESSIE, N. A. C., 1991, Statistics for Spatial Data (New York: Wiley).
13. CURRAN, P. J., and ATKINSON, P. M., 1998, Geostatistics and remote sensing. Progress in Physical Geography, 22, 61-78.
14. CURRAN, P. J., and HAY, A. M., 1986, The importance of measurement error for certain procedures in remote sensing at optical wavelengths. Photogrammetric Engineering and Remote Sensing, 52, 229-241.
15. CURRAN, P. J., and WILLIAMSON, H. D., 1985, The accuracy of ground data used in remote sensing investigations. International Journal of Remote Sensing, 6, 1637-1651.
16. CURRAN, P. J., and WILLIAMSON, H. D., 1986, Sample size for ground and remotely sensed data. Remote Sensing of Environment, 20, 31-41.
17. DEUTSCH, C. V., and JOURNEL, A. G., 1992, GSLIB Geostatistical Software Library Users Guide (Oxford: Oxford Univeristy Press).
18. DOZIER, J., and STRAHLER, A. H., 1983, Ground investigations in support of remote sensing. In Manual of Remote Sensing, 2nd edition, edited by R. N. Colwell (Falls Church, VA: American Society of Photogrammetry), pp. 959-986.
19. DUNGAN, J. L., PETERSON, D. L., and CURRAN, P. J., 1994, Alternative approaches for mapping vegetation quantities using ground and image data. In Environmental Information Management and Analysis: Ecosystem to Global Scales, edited by W. Michener, J. Brunt and S. Stafford (London: Taylor and Francis), pp. 237-261.
20. FOODY, G. M., and CURRAN, P. J., 1994, Scale and environmental remote sensing. In Environmental Remote Sensing from Regional to Global Scales, edited by G. M. Foody and P. J. Curran (Chichester: Wiley), pp. 223-232.
21. GOHIN, F., and LANGLOIS, G., 1993, Using geostatistics to merge in situ measurements and remotely sensed observations of sea surface temperature. International Journal of Remote Sensing, 14, 9-19.
22. GOOVAERTS, P., 1997, Geostatistics for Natural Resources Evaluation (New York: Oxford University Press).
23. ISAAKS, E. H., and SRIVASTAVA, R. M., 1989, Applied Geostatistics (Oxford: Oxford University Press).
24. JOURNEL, A. G., and HUUBREGTS, C. J., 1978, Mining Geostatistics (London: Academic).
25. JUPP, D. L. B., STRAHLER, A. H., and WOODCOCK, C. E., 1988, Autocorrelation and regularization in digital images I. Basic theory. IEEE Transactions on Geoscience and Remote Sensing, 26, 463-473.
26. JUPP, D. L. B., STRAHLER, A. H., and WOODCOCK, C. E., 1989, Autocorrelation and regularization in digital images II. Simple image models. IEEE Transactions on Geoscience and Remote Sensing, 27, 247-258.
27. LAPORTE, N., JUSTICE, C., and KENDALL, J., 1995, Mapping the dense humid forest of Cameroon and Zaire using AVHRR satellite data. International Journal of Remote Sensing, 16, 1127-1145.
28. LUCAS, R. M., HONZAK, M., CURRAN, P. J., FOODY, G. M., and NGUELE, D. T., 2000, Characterising tropical forest regeneration in Cameroon using NOAA AVHRR data. International Journal of Remote Sensing (in press).
29. MOBRATNEY, A. B., and WEBSTER, R., 1981, The design of optimal sampling schemes for local estimation and mapping ofregionalized variables II. Program and examples. Computers and Geosciences, 7, 335-365.
30. MCGWIRE, K., FRIEDL, m., and ESTES, J. E., 1993, Spatial structure, sampling design and scale in remotely sensed imagery of a California savanna woodland. International Journal of Remote Sensing, 14, 2137-2164.
31. MARCEAU, D. J., GRATTON, D. J., FOURNIER, R. A., and FORTIN, J.-P., 1994, Remote sensing and the measurement of geographical entities in a forested environment. 2. The optimal spatial resolution. Remote Sensing of Environment, 49, 105-117.
32. MATÈRN, B., 1960, Spatial variation, Meddelanden Från Statens Skogsforskningsinstitut, 49, 1-144.
33. MATHERON, G., 1965, Les Variables Régionalisées et Leur Estimation (Paris: Masson).
34. MATHERON, G., 1971, The Theory of Regionalized Variables and its Applications (Fontainebleau: Centre de Morphologie Mathematique de Fontainebleau).
35. RAMSTEIN, G., and RAEFY, M., 1989, Analysis of the structure of radiometric remotely sensed images. International Journal of Remote Sensing, 10, 1049-1074.
36. ROSSI, R. E., MULLA, D. J., JOURNEL, A. G., and FRANZ, E. H., 1992, Geostatistical tools for modeling and interpreting ecological spatial dependence, Ecological Monographs, 62, 277-314.
37. STEVEN, M. D., 1987, Ground truth an underview. International Journal of Remote Sensing, 8, 1033-1038.
38. TOWNSHEND, J. R. G., and JUSTICE, C. O., 1988, Selecting the spatial resolution of satellite sensors required for global monitoring of land transformations. International Journal of Remote Sensing, 9, 187-236.
39. WEBSTER, R., 1985, Quantitative spatial analysis of soil in the field, Advances in Soil Science, 3, 1-70.
40. WEBSTER, R., CURRAN, P. J., and MUNDEN, J. W., 1989, Spatial correlation in reflected radiation from the ground and its implications for sampling and mapping by ground-based radiometry. Remote Sensing of Environment, 29, 67-78.
41. WEBSTER, R., and OLIVER, M. A., 1990, Statistical Methods for Soil and Land Resources Survey (Oxford: Oxford University Press).
42. WOODCOCK, C. E., and STRAHLER, A. H., 1987, The factor of scale in remote sensing. Remote Sensing of Environment, 21, 311-322.
43. YATES, F., 1948, Systematic sampling. Philosophical Transactions of the Royal Society, A241, 345-377.