229.

[Cover] [Contents] [Index]

Page 303

Colby, J.D. (1991) Topographic normalisation in rugged terrain’, Photogrammetric Engineering and Remote Sensing 57, 531–7.

Congalton, R.G. (1988) ‘A comparison of sampling schemes used in generating error matrices for assessing the accuracy of maps generated from remotely sensed data’, Photogrammetric Engineering and Remote Sensing 54, 593–600.

——(1991) ‘A review of assessing the accuracy of classifications of remotely sensed data’, Remote Sensing of Environment 37, 35–46.

Congalton, R.G. and Green, K. (1999) Assessing the Accuracy of Remotely Sensed Data: Principles and Practice. New York: Lewis Publishers.

Congalton R.G. and Plourde, L.C. (2000) ‘Sampling methodology, sampling placement and other important factors in assessing the accuracy of remotely sensed forest maps’, in G.B.M.Heuvelink and M.J.P.M. Lemmens (eds) Proceedings of the Accuracy 2000 Conference. Amsterdam: Delft University Press, pp. 117–24.

Congalton, R.G., Oderwald, R. and Meade, R. (1983) ‘Landsat classification accuracy using discrete multivariate analysis statistical techniques’, Photogrammetric Engineering and Remote Sensing 49, 1671–8.

Coray, C. (1981) ‘Clustering algorithms with prototype selection’, in Proceedings of Hawaii International Conference of System Science, Hawaii, USA, January, pp. 945–55.

Cortijo, F.J. and Pérez de la Blanca, N. (1999) ‘The performance of regularised discriminant analysis versus non-parametric classifiers applied to high dimensional image classification’, International Journal of Remote Sensing 20, 3345–65.

Cóté, S. and Tatnall, A.R. L. (1997) ‘The Hopfield neural network as a tool for feature tracking and recognition from satellite sensor images’, International Journal of Remote Sensing 18, 871–85.

Courant, R. and Hilbert, D. (1953) Methods of Mathematical Physics, vol 1. New York: Interscience Publishers.

Crapper, P.F. (1984) ‘An estimate of the number of boundary cells in a mapped landscape coded to grid cells’, Photogrammetric Engineering and Remote Sensing 50, 1497–503.

Crist, E. P and Cicone, R.C. (1984a) ‘A physically-based transformation of Thematic Mapper data—the TM Tasselled Cap’, IEEE Transactions on Geoscience and Remote Sensing 22, 256–63.

——(1984b) ‘Comparison of the dimensionality and features of simulated Landsat-4 MSS and TM data’, Remote Sensing of Environment 14, 235–46.

Cross, G.C. and Jain, A.K. (1983) ‘Markov random field texture models’, IEEE Transactions on Pattern Analysis and Machine Intelligence 5, 25–39.

Curlander, J.C. and McDonough, R.N. (1991) Synthetic Aperture Radar, Systems and Signal Processing. New York: John Wiley.

Curran, P.J. (1988) ‘The semi-variogram in remote sensing: an introduction’, Remote Sensing of Environment 24, 493–507.

[Cover] [Contents] [Index]


Classification Methods for Remotely Sensed Data
Classification Methods for Remotely Sensed Data, Second Edition
ISBN: 1420090720
EAN: 2147483647
Year: 2001
Pages: 354

flylib.com © 2008-2017.
If you may any questions please contact us: flylib@qtcs.net