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Breiman, L.: Classification and Regression Trees. Chapman & Hall/CRC, London (1984)
Breiman, L.: Bagging predictors. Mach. Learn. 24, 123–140 (1996)
Breiman, L.: Random forests. Mach. Learn. 45, 5–32 (2001)
Cerna, L., Chytry, M.: Supervised classification of plant communities with artificial neural networks. J. Veg. Sci. 16(4), 407–414 (2005)
Chan, J.C., Paelinckx, D.: Evaluation of random forest and adaboost tree-based ensemble classification and spectral band selection for ecotope mapping using airborne hyperspectral imagery.
Remote Sens. Environ. 112, 2999–3011 (2008)
Chen, H., Ho, P.: Statistical pattern recognition in remote sensing. Pattern Recogn. 41(9), 2731–
2741 (2008)
Chow, C.K.: An optimum character recognition system using decision functions. IEEE Trans.
Electronic Comput. EC-6, 247–254 (1957)
Corbane, C., Lang, S., Pipkins, K., Alleaume, S., Deshayes, M., Millan, V.E.G., Strasser, T., Borre,
J.V., Toon, S., Michael, F.: Remote sensing for mapping natural habitats and their conservation status–new opportunities and challenges. Int. J. Appl. Earth Obs. Geoinf. 37, 7–16 (2015)
Cover, T.M., Hart, P.E.: Nearest neighbor pattern classification. IEEE Trans. Inf. Theory. 13(1),
21–27 (1967)
Crippen, R.E.: Calculating the vegetation index faster. Remote Sens. Environ. 34(1), 71–73 (1990)
Data.gov.uk, 2016.: URL: https://www.environment.data.gov.uk/ds/survey/#/survey (2016)
Datt, B.: Remote sensing of chlorophyll a, chlorophyll b, chlorophyll a+b and total carotenoid
content in Eucalyptus leaves. Remote Sens. Environ. 66(2), 111–121 (1998)
Datt, B.: Remote sensing of water content in Eucalyptus leaves. Aust. J. Bot. 47(6), 909–923
(1999)
DeFries, R., Hansen, M., Townshend, J.: Global discrimination of land cover types from metrics
derived from avhrr pathfinder data. Remote Sens. Environ. 54(3), 209–222 (1995)
Digital Globe: Digital Globe Website, URL: https://www.digitalglobe.com/about/our-constellation
(2009)
Foody, G.M.: Status of land cover classification accuracy assessment. Remote Sens. Environ.
80(1), 185–201 (2002)
Freund, Y., Schapire, R.E.: Experiments with a new boosting algorithm, Machine Learning.
Proceedings of the Thirteenth International Conference, pp. 148–156 (1996)
Friedl, M.A., Sulla-Menashe, D., Tan, B., Schneider, A., Ramankutty, N., Sibley, A., Huang, X.:
MODIS collection 5 global land cover: algorithm refinements and characterization of new
datasets. Remote Sens. Environ. 114(1), 168–182 (2010)
Fu, K.S.: Application of pattern recognition to remote sensing. In: Fu, K.S. (ed.) Applications of
Pattern Recognition. CRC Press, Boca Raton (1982)
Fukunaga, K.: Introduction to Statistical Pattern Recognition, 2nd edn. Academic, Orlando (1990)
Fuller, R., Groom, G., Jones, A.: Land cover map of Great Britain. An automated classification of
landsat thematic mapper data. Photogramm. Eng. Remote. Sens. 60(5), 553–562 (1994)
Fuller, R.M., Smith, G.M., Sanderson, J.M., Hill, R.A., Thomson, A.G.: The UK land cover map
2000: construction of a parcel-based vector map from satellite images. Cartogr. J. 39(1), 15–25
(2002)
Gabroswki, S., Jozwik, A., Chen, C.H.: Nearest neighbor decision rule for pixel classification in
remote sensing. In: Chen, C.H. (ed.) Frontiers of Remote Sensing Information Processing,
pp. 315–327. World Scientific Publishing, Singapore (2003)
Gad, S., Kusky, T.: Lithological mapping in the eastern desert of Egypt, the Barramiya area, using
Landsat Thematic Mapper (TM). J. Afr. Earth Sci. 44(2), 196–202 (2006)
Geerken, R., Zaitchik, B., Evans, J.: Classifying rangeland vegetation type and coverage from
NDVI time series using Fourier filtered cycle similarity. Int. J. Remote Sens. 26(24), 5535–
5554 (2005)
Ghimire, P.O., Benediktsson, J.A., Sveinsson, J.R.: Contextual land-cover classification: incorporating spatial dependence in land-cover classification models using random forests and the
Getis statistic. Remote Sens. Lett. 1, 45–54 (2006)
G. Jones et al.
Breiman, L.: Classification and Regression Trees. Chapman & Hall/CRC, London (1984)
Breiman, L.: Bagging predictors. Mach. Learn. 24, 123–140 (1996)
Breiman, L.: Random forests. Mach. Learn. 45, 5–32 (2001)
Cerna, L., Chytry, M.: Supervised classification of plant communities with artificial neural networks. J. Veg. Sci. 16(4), 407–414 (2005)
Chan, J.C., Paelinckx, D.: Evaluation of random forest and adaboost tree-based ensemble classification and spectral band selection for ecotope mapping using airborne hyperspectral imagery.
Remote Sens. Environ. 112, 2999–3011 (2008)
Chen, H., Ho, P.: Statistical pattern recognition in remote sensing. Pattern Recogn. 41(9), 2731–
2741 (2008)
Chow, C.K.: An optimum character recognition system using decision functions. IEEE Trans.
Electronic Comput. EC-6, 247–254 (1957)
Corbane, C., Lang, S., Pipkins, K., Alleaume, S., Deshayes, M., Millan, V.E.G., Strasser, T., Borre,
J.V., Toon, S., Michael, F.: Remote sensing for mapping natural habitats and their conservation status–new opportunities and challenges. Int. J. Appl. Earth Obs. Geoinf. 37, 7–16 (2015)
Cover, T.M., Hart, P.E.: Nearest neighbor pattern classification. IEEE Trans. Inf. Theory. 13(1),
21–27 (1967)
Crippen, R.E.: Calculating the vegetation index faster. Remote Sens. Environ. 34(1), 71–73 (1990)
Data.gov.uk, 2016.: URL: https://www.environment.data.gov.uk/ds/survey/#/survey (2016)
Datt, B.: Remote sensing of chlorophyll a, chlorophyll b, chlorophyll a+b and total carotenoid
content in Eucalyptus leaves. Remote Sens. Environ. 66(2), 111–121 (1998)
Datt, B.: Remote sensing of water content in Eucalyptus leaves. Aust. J. Bot. 47(6), 909–923
(1999)
DeFries, R., Hansen, M., Townshend, J.: Global discrimination of land cover types from metrics
derived from avhrr pathfinder data. Remote Sens. Environ. 54(3), 209–222 (1995)
Digital Globe: Digital Globe Website, URL: https://www.digitalglobe.com/about/our-constellation
(2009)
Foody, G.M.: Status of land cover classification accuracy assessment. Remote Sens. Environ.
80(1), 185–201 (2002)
Freund, Y., Schapire, R.E.: Experiments with a new boosting algorithm, Machine Learning.
Proceedings of the Thirteenth International Conference, pp. 148–156 (1996)
Friedl, M.A., Sulla-Menashe, D., Tan, B., Schneider, A., Ramankutty, N., Sibley, A., Huang, X.:
MODIS collection 5 global land cover: algorithm refinements and characterization of new
datasets. Remote Sens. Environ. 114(1), 168–182 (2010)
Fu, K.S.: Application of pattern recognition to remote sensing. In: Fu, K.S. (ed.) Applications of
Pattern Recognition. CRC Press, Boca Raton (1982)
Fukunaga, K.: Introduction to Statistical Pattern Recognition, 2nd edn. Academic, Orlando (1990)
Fuller, R., Groom, G., Jones, A.: Land cover map of Great Britain. An automated classification of
landsat thematic mapper data. Photogramm. Eng. Remote. Sens. 60(5), 553–562 (1994)
Fuller, R.M., Smith, G.M., Sanderson, J.M., Hill, R.A., Thomson, A.G.: The UK land cover map
2000: construction of a parcel-based vector map from satellite images. Cartogr. J. 39(1), 15–25
(2002)
Gabroswki, S., Jozwik, A., Chen, C.H.: Nearest neighbor decision rule for pixel classification in
remote sensing. In: Chen, C.H. (ed.) Frontiers of Remote Sensing Information Processing,
pp. 315–327. World Scientific Publishing, Singapore (2003)
Gad, S., Kusky, T.: Lithological mapping in the eastern desert of Egypt, the Barramiya area, using
Landsat Thematic Mapper (TM). J. Afr. Earth Sci. 44(2), 196–202 (2006)
Geerken, R., Zaitchik, B., Evans, J.: Classifying rangeland vegetation type and coverage from
NDVI time series using Fourier filtered cycle similarity. Int. J. Remote Sens. 26(24), 5535–
5554 (2005)
Ghimire, P.O., Benediktsson, J.A., Sveinsson, J.R.: Contextual land-cover classification: incorporating spatial dependence in land-cover classification models using random forests and the
Getis statistic. Remote Sens. Lett. 1, 45–54 (2006)
G. Jones et al.