27,287
Views
2,126
CrossRef citations to date
0
Altmetric
Letters To The Editor

Random forest classifier for remote sensing classification

Pages 217-222 | Received 01 Oct 2003, Accepted 01 May 2004, Published online: 22 Feb 2007

References

References

  • Boser B Guyon I Vapnik VN A training algorithm for optimal margin classifiers. 1992 Proceedings of the 5th Annual Workshop on Computer Learning Theory San Mateo CA Morgan Kaufman pp. 144–152
  • Breiman , L . 1996 . Bagging predictors. . Machine Learning , 26 : pp. 123–140
  • Breiman L Random forests—random features. 1999 Technical Report 567, Statistics Department, University of California, Berkeley, ftp://ftp.stat.berkeley.edu/pub/users/breiman
  • Breiman L Friedman JH Olshen RA Stone CJ 1984 Classification and Regression Trees Monterey CA Wadsworth
  • Briem , GJ , Benediktsson , JA and Sveinsson , JR . 2002 . Multiple classifiers applied to multisource remote sensing data. . IEEE Transactions on Geoscience and Remote Sensing , 40 : pp. 2291–2299
  • Chang C Lin C LIBSVM: A Library for Support Vector Machines. 2001 Department of Computer Science and Information Engineering, National Taiwan University, Taiwan, http://www.csie.ntu.edu.tw/∼cjlin/libsvm
  • Cortes , C and Vapnik , VN . 1995 . Support vector networks. . Machine Learning , 20 : pp. 273–297
  • Cristianini N Shawe‐Taylor J 2000 An Introduction to Support Vector Machines Cambridge Cambridge University Press
  • Dietterich TG 2002 Ensemble Learning. The handbook of brain theory and neural networks Arbib M. A, (Ed.) Cambridge MA The MIT Press
  • Feller W 1968 An Introduction to Probability Theory and its Application vol. 1, 3rd edn New York Wiley
  • Freund Y Schapire R Experiments with a new boosting algorithm. 1996 Proceedings of the Thirteenth International Conference on Machine Learning pp. 148–156
  • Friedl , MA , Brodley , CE and Strahler , AH . 1999 . Maximizing land cover classification accuracies produced by decision tree at continental to global scales. . IEEE Transactions on Geoscience and Remote Sensing , 37 : pp. 969–977
  • Giacinto G Roli F Ensembles of neural networks for soft classification of remote sensing images. 1997 Proceedings of the European Symposium on Intelligent Techniques, European Network for Fuzzy Logic and Uncertainty Modelling in Information Technology Bari Italy pp. 166–170
  • Mingers , J . 1989 . An empirical comparison of pruning methods for decision tree induction. . Machine Learning , 4 : pp. 227–243
  • Muchoney , D , Borak , J , Chi , H , Friedl , M , Gopal , S , Hodges , J , Morrow , N and Strahler , A . 2000 . Application of MODIS global supervised classification model to vegetation and land cover mapping of Central America. . International Journal of Remote Sensing , 21 : pp. 1115–1138
  • Pal , M and Mather , PM . 2003a . An assessment of the effectiveness of decision tree methods for land cover classification. . Remote Sensing of Environment , 86 : pp. 554–565
  • Pal M Mather PM Support vector classifiers for land cover classification. 2003b Map India 2003, New Delhi, 28–31 January, www.gisdevelopment.net/technology/rs/pdf/23.pdf
  • Quinlan JR 1993 C4.5: Programs for Machine Learning San Mateo CA Morgan Kaufmann
  • Vapnik VN 1995 The Nature of Statistical Learning Theory New York Springer‐Verlag

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.