Chapter 20 . Classification of Remotely Sensed Images
395
Bishop CM (1995) Neural Networks for Pattern Recognition Oxford University Press,
Oxford
Bruzzone L, Prieto DF (1999) A technique for the selection of kernel-function parameters
in RBF neural networks for classification of remote sensing images, IEEE
Transactions on Geoscience and Remote Sensing, 37: 1179-1184
Campbell JB (1996) Introduction to Remote Sensing, second edition, Taylor and Francis,
London
Carpenter GA, Gopal S, Macomber S, Martens S, Woodcock CE (1999a) A neural network
method for mixture estimation for vegetation mapping, Remote Sensing of
Environment, 70, 138-152
Carpenter GA, Gopal S, Macomber S, Martens S, Woodcock CE, Franklin J (1999b) A
neural network method for efficient vegetation mapping, Remote Sensing of
Environment, 70, 326-338
Cote S, Tatnall ARL (1997) The Hopfield neural network as a tool for feature tracking and
recognition from satellite sensor images, International Journal of Remote Sensing, 18,
871-885
Curran PJ, Dungan JL, Peterson DL (2001) Estimating the foliar biochemical concentration
of leaves with reflectance spectrometry. Testing the Kokaly and Clark methodologies,
Remote Sensing of Environment, 76, 349-359
Davalo E, Naim P (1991) Neural Networks, Macmillan, Basingstoke
Day C (1997) Remote sensing applications which may be addressed by neural networks
using parallel processing technology, In Kanellopoulos, I, Wilkinson, G. G., Roli, F.,
Austin, 1. (eds) Neuro-computation in Remote Sensing Data Analysis, Springer,
Berlin, pp. 262-279
Estes J, Belward A, Loveland T, Scepan J, Strahler A, Townshend J, Justice C (1999), The
way forward, Photograrnmetric Engineering and Remote Sensing, 65, 1089-1093
Fardanesh MT, Ersoy OK (1998) Classification accuracy improvement of neural network
classifiers by using unlabeled data, IEEE Transactions on Geoscience and Remote
Sensing, 36, 1020-1025
Fischer MM (1998) Computational neural networks a new paradigm for spatial analysis,
Environment and Planning A, 30, 1873-1891
Fischer MM, Gopal S, Staufer P, Steinnocher K. (1997) Evaluation of neural pattern
classifiers for a remote sensing application, Geographical Systems, 4, 195-225
Foody GM (1996) Approaches for the production and evaluation of fuzzy land cover
classifications from remotely-sensed data, International Journal of Remote Sensing,
17,1317-1340
Foody GM (1999a) Image classification with a neural network: from completely-crisp to
fully-fuzzy situations, In Atkinson, P. M. and Tate, N. J. (eds) Advances in Remote
Sensing and GIS, Wiley, Chichester, pp. 17-37
Foody GM (1999b) The continuum of classification fuzziness in thematic mapping,
Photograrnmetric Engineering and Remote Sensing, 65, 443-451
Foody GM (2001) Thematic mapping from remotely sensed data with neural networks:
MLP, RBF and PNN based approaches, Journal of Geographical Systems, 3, in press
Foody GM, Arora MK (1997) An evaluation of some factors affecting the accuracy of
classification by an artificial neural network, International Journal of Remote Sensing,
18,799-810
395
Bishop CM (1995) Neural Networks for Pattern Recognition Oxford University Press,
Oxford
Bruzzone L, Prieto DF (1999) A technique for the selection of kernel-function parameters
in RBF neural networks for classification of remote sensing images, IEEE
Transactions on Geoscience and Remote Sensing, 37: 1179-1184
Campbell JB (1996) Introduction to Remote Sensing, second edition, Taylor and Francis,
London
Carpenter GA, Gopal S, Macomber S, Martens S, Woodcock CE (1999a) A neural network
method for mixture estimation for vegetation mapping, Remote Sensing of
Environment, 70, 138-152
Carpenter GA, Gopal S, Macomber S, Martens S, Woodcock CE, Franklin J (1999b) A
neural network method for efficient vegetation mapping, Remote Sensing of
Environment, 70, 326-338
Cote S, Tatnall ARL (1997) The Hopfield neural network as a tool for feature tracking and
recognition from satellite sensor images, International Journal of Remote Sensing, 18,
871-885
Curran PJ, Dungan JL, Peterson DL (2001) Estimating the foliar biochemical concentration
of leaves with reflectance spectrometry. Testing the Kokaly and Clark methodologies,
Remote Sensing of Environment, 76, 349-359
Davalo E, Naim P (1991) Neural Networks, Macmillan, Basingstoke
Day C (1997) Remote sensing applications which may be addressed by neural networks
using parallel processing technology, In Kanellopoulos, I, Wilkinson, G. G., Roli, F.,
Austin, 1. (eds) Neuro-computation in Remote Sensing Data Analysis, Springer,
Berlin, pp. 262-279
Estes J, Belward A, Loveland T, Scepan J, Strahler A, Townshend J, Justice C (1999), The
way forward, Photograrnmetric Engineering and Remote Sensing, 65, 1089-1093
Fardanesh MT, Ersoy OK (1998) Classification accuracy improvement of neural network
classifiers by using unlabeled data, IEEE Transactions on Geoscience and Remote
Sensing, 36, 1020-1025
Fischer MM (1998) Computational neural networks a new paradigm for spatial analysis,
Environment and Planning A, 30, 1873-1891
Fischer MM, Gopal S, Staufer P, Steinnocher K. (1997) Evaluation of neural pattern
classifiers for a remote sensing application, Geographical Systems, 4, 195-225
Foody GM (1996) Approaches for the production and evaluation of fuzzy land cover
classifications from remotely-sensed data, International Journal of Remote Sensing,
17,1317-1340
Foody GM (1999a) Image classification with a neural network: from completely-crisp to
fully-fuzzy situations, In Atkinson, P. M. and Tate, N. J. (eds) Advances in Remote
Sensing and GIS, Wiley, Chichester, pp. 17-37
Foody GM (1999b) The continuum of classification fuzziness in thematic mapping,
Photograrnmetric Engineering and Remote Sensing, 65, 443-451
Foody GM (2001) Thematic mapping from remotely sensed data with neural networks:
MLP, RBF and PNN based approaches, Journal of Geographical Systems, 3, in press
Foody GM, Arora MK (1997) An evaluation of some factors affecting the accuracy of
classification by an artificial neural network, International Journal of Remote Sensing,
18,799-810