396
G.M.Foody
Foody GM, Lucas RM, Curran PJ, Honzak M (1997) Non-linear mixture modelling
without end-members using an artificial neural network, International Journal of
Remote Sensing, 18,937-953
Foody GM, Cutler ME, McMorrow J, Pelz D, Tangki H, Boyd DS, Douglas I (2001)
Mapping the biomass of Bornean tropical rain forest from remotely sensed data,
Global Ecology and Biogeography, 10,379-387
Friedl MA, Woodcock C, Gopal S, Muchoney D, Strahler AH, Barker-Schaaf C (2000) A
note on procedures used for accuracy assessment in land cover maps derived from
A VHRR data, International Journal of Remote Sensing, 21, 1073-1077
Gamba P, Houshmand B (2001) An efficient neural classification chain of SAR and optical
urban images, International Journal of Remote Sensing, 22, 1535-1553
Gopal S, Woodcock CE, Strahler AH. (1999) Fuzzy neural network classification of global
land cover from al 0 A VHRR data set, Remote Sensing of Environment, 67, 230-243
Hall RJ (2000) Applications of remote sensing to forestry - current and future, Forestry
Chronicle, 76, 855-857
Ito Y, Omatu S (1997) Category classification method using a self-organising neural
network, International Journal of Remote Sensing, 18, 829-845
Ji CY (2000) Land-use classification of remotely sensed data using Kohonen selforganising feature map neural networks, Photograrnmetric Engineering and Remote
Sensing, 66, 1451-1460
Jin YQ, Liu C (1997) Biomass retrieval from high-dimensional active/passive remote
sensing data by using artificial neural networks, International Journal of Remote
Sensing, 18,971-979
Kanellopoulos I, Wilkinson GG (1997) Strategies and best practice for neural network
image classification, International Journal ofRemote Sensing, 18,711-725
Kasischke ES, Melack JM, Dobson MC (1997) The use of imaging radars for ecological
applications -a review, Remote Sensing of Environment, 59, 141-156
Kimes DS, Nelson RF, Fifer ST (2000) Predicting ecologically important vegetation
variables from remotely sensed optical/radar data using neuronal networks, In Lek, S.
and Guegan, J-F. (eds) Artificial Neuronal Networks: Applications to Ecology and
Evolution, Springer, Berlin, pp. 31-44
Lawrence RL, Ripple WJ (1998) Comparisons among vegetation indices and bandwise
regression in a highly disturbed heterogeneous landscape: Mount St. Helens,
Washington, Remote Sensing ofEnvironment, 64, 91-102
Lek S, Giraudel JL, Guegan JF (2000) Neuronal networks: algorithrns and architectures for
ecologists and evolutionary ecologists, In Lek, S. and Guegan, J-F. (eds) Artificial
Neuronal Networks: Applications to Ecology and Evolution, Springer, Berlin, pp. 327
Lillesand TM, Kiefer RW (2000) Remote Seining and Image Interpretation, fourth edition,
Wiley, New York
Loveland TR, Zhu Z, Ohlen DO, Brown JF, Reed BC, Yang L (1999) An analysis of the
IGBP global land-cover characterisation process, Photograrnmetric Engineering and
Remote Sensing, 65, 1021-1032
Lucas NS, Curran PJ (1999) Forest ecosystem simulation modelling: the role of remote
sensing, Progress in Physical Geography, 23, 391-423
Mathe, PM (1999) Computer Processing of Remotely-Sensed Images, second edition,
Wiley, Chichester
G.M.Foody
Foody GM, Lucas RM, Curran PJ, Honzak M (1997) Non-linear mixture modelling
without end-members using an artificial neural network, International Journal of
Remote Sensing, 18,937-953
Foody GM, Cutler ME, McMorrow J, Pelz D, Tangki H, Boyd DS, Douglas I (2001)
Mapping the biomass of Bornean tropical rain forest from remotely sensed data,
Global Ecology and Biogeography, 10,379-387
Friedl MA, Woodcock C, Gopal S, Muchoney D, Strahler AH, Barker-Schaaf C (2000) A
note on procedures used for accuracy assessment in land cover maps derived from
A VHRR data, International Journal of Remote Sensing, 21, 1073-1077
Gamba P, Houshmand B (2001) An efficient neural classification chain of SAR and optical
urban images, International Journal of Remote Sensing, 22, 1535-1553
Gopal S, Woodcock CE, Strahler AH. (1999) Fuzzy neural network classification of global
land cover from al 0 A VHRR data set, Remote Sensing of Environment, 67, 230-243
Hall RJ (2000) Applications of remote sensing to forestry - current and future, Forestry
Chronicle, 76, 855-857
Ito Y, Omatu S (1997) Category classification method using a self-organising neural
network, International Journal of Remote Sensing, 18, 829-845
Ji CY (2000) Land-use classification of remotely sensed data using Kohonen selforganising feature map neural networks, Photograrnmetric Engineering and Remote
Sensing, 66, 1451-1460
Jin YQ, Liu C (1997) Biomass retrieval from high-dimensional active/passive remote
sensing data by using artificial neural networks, International Journal of Remote
Sensing, 18,971-979
Kanellopoulos I, Wilkinson GG (1997) Strategies and best practice for neural network
image classification, International Journal ofRemote Sensing, 18,711-725
Kasischke ES, Melack JM, Dobson MC (1997) The use of imaging radars for ecological
applications -a review, Remote Sensing of Environment, 59, 141-156
Kimes DS, Nelson RF, Fifer ST (2000) Predicting ecologically important vegetation
variables from remotely sensed optical/radar data using neuronal networks, In Lek, S.
and Guegan, J-F. (eds) Artificial Neuronal Networks: Applications to Ecology and
Evolution, Springer, Berlin, pp. 31-44
Lawrence RL, Ripple WJ (1998) Comparisons among vegetation indices and bandwise
regression in a highly disturbed heterogeneous landscape: Mount St. Helens,
Washington, Remote Sensing ofEnvironment, 64, 91-102
Lek S, Giraudel JL, Guegan JF (2000) Neuronal networks: algorithrns and architectures for
ecologists and evolutionary ecologists, In Lek, S. and Guegan, J-F. (eds) Artificial
Neuronal Networks: Applications to Ecology and Evolution, Springer, Berlin, pp. 327
Lillesand TM, Kiefer RW (2000) Remote Seining and Image Interpretation, fourth edition,
Wiley, New York
Loveland TR, Zhu Z, Ohlen DO, Brown JF, Reed BC, Yang L (1999) An analysis of the
IGBP global land-cover characterisation process, Photograrnmetric Engineering and
Remote Sensing, 65, 1021-1032
Lucas NS, Curran PJ (1999) Forest ecosystem simulation modelling: the role of remote
sensing, Progress in Physical Geography, 23, 391-423
Mathe, PM (1999) Computer Processing of Remotely-Sensed Images, second edition,
Wiley, Chichester