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Original Articles

Image segmentation scale parameter optimization and land cover classification using the Random Forest algorithm

Pages 69-79 | Published online: 09 Jul 2010

References

  • Archer , K. and Kimes , R. 2007 . Empirical characterization of random forest variable importance measures . Computational Statistics & Data Analysis , 52 : 2249 – 2260 .
  • Benz , U. C. , Hofmann , P. , Willhauck , G. , Lingenfelder , I. and Heynen , M. 2004 . Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information . ISPRS Journal of Photogrammetry and Remote Sensing , 58 ( 3–4 ) : 239 – 258 .
  • Bhandarkar , S. M and Zhang , H. 1999 . Image segmentation using evolutionary computation . IEEE Transactions on Evolutionary Computation , 3 ( 1 ) : 1 – 21 .
  • Bhanu , B. , Lee , S. and Ming , J. 1995 . Adaptive image segmentation using a genetic algorithm . IEEE Transactions on Systems, Man, and Cybernetics , 25 ( 12 ) : 1543 – 1567 .
  • Breiman , L. 2001 . Random forests . Journal of Machine Learning ResearchI , 45 : 5 – 32 .
  • Breiman , L. , Friedman , J. H. , Olshen , R. A. and Stone , C. J. 1984 . Classification and Regression Trees , Boca Raton : Chapman and Hall/CRC .
  • Castilla , G. and Hay , G. J. 2008 . “ Image objects and geographic objects ” . In Object-Based Image Analysis Spatial Concepts for Knowledge-Driven Remote Sensing Applications , 91 – 109 . Berlin : Springer .
  • Chen , X. and Liu , M. 2005 . Prediction of protein–protein interactions using random decision forest framework . Bioinformatics , 21 : 4394 – 4400 .
  • Congalton , R. G. and Green , K. 1993 . A practical look at the sources of confusion in error matrix generation . Photogrammetric Engineering and Remote Sensing , 59 ( 5 ) : 641 – 644 .
  • Gislason , P. O. , Benediktsson , J. A. and Sveinsson , J. R. 2006 . Random forests for land cover classification . Pattern Recognition Letters Research , 27 : 294 – 300 .
  • Gitelson , A. A. , Kaufman , Y. J. and Merzlyak , M. N. 1996 . Use of a green channel in remote sensing of global vegetation from EOS-MODIS . Remote Sensing of Environment , 58 : 289 – 298 .
  • Guo , X. , Price , K. and Stiles , J. 2003 . Grasslands discriminant analysis using landsat TM single and multitemporal data . Photogrammetric Engineering and Remote Sensing , 69 ( 11 ) : 1255 – 1262 .
  • Hinterműller , M. and Ring , W. 2003 . A second order shape optimization approach for image segmentation . SIAM Journal on Applied Mathematics , 64 ( 2 ) : 442 – 467 .
  • Jelinski , D. E. and Wu , J. 1996 . The modifiable areal unit problem and implications for landscape ecology . Landscape Ecology , 11 ( no. 3 ) : 129 – 140 .
  • Kim , M. , Madden , M. and Warner , T. 2008 . “ Estimation of optimal image object size for the segmentation of forest stands with multispectral IKONOS imagery ” . In Object-Based Image Analysis Spatial Concepts for Knowledge-Driven Remote Sensing Applications , 291 – 308 . Berlin : Springer .
  • Kriegler , F. J. , Malila , W. A. , Nalepka , R. F. and Richardson , W. Preprocessing transformations and their effects on multispectral recognition . Proceedings of the Sixth International Symposium on Remote Sensing of Environment . pp. 97 – 131 .
  • Laliberte , A. S. , Rango , A. , Havstad , K. M. , Paris , J. F. , Beck , R. F. , McNeely , R. and Gonzalez , A. L. 2004 . Object-oriented image analysis for mapping shrub encroachment from 1937 to 2003 in southern New Mexico . Remote Sensing of Environment , 93 ( 1–2 ) : 198 – 210 .
  • Liaw , A. and Wiener , M. 2002 . Classification and Regression by random Forest . R. News , 2 : 18 – 22 .
  • McFeeters , S. K. 1996 . The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features . International Journal of Remote Sensing , 17 ( 7 ) : 1425 – 1432 .
  • Pal , M. 2005 . Random forest classifier for remote sensing classification . International Journal of Remote Sensing , 26 ( 1 ) : 217 – 222 .
  • Rondeaux , G. , Steven , M. and Baret , F. 1996 . Optimization of soil-adjusted vegetation indices . Remote Sensing of Environment , 55 : 95 – 107 .
  • Rouse , J. W. , Haas , R. H. , Schell , J. A. and Deering , D. W. Monitoring vegetation systems in the Great Plains with ETRS . Proceedings of Third ETRS Symposium, NASA SP353 . pp. 309 – 317 .
  • Segal , M. 2004 . Machine Learning Benchmarks and Random Forest Regression Technical report, Center for Bioinformatics & Molecular Biostatistics, University of California, San Francisco, CA
  • Sesnie , S. , Gessler , P. , Finegan , B. and Thessler , S. 2008 . Integrating Landsat TM and SRTM-DEM derived variables with decision trees for habitat classification and change detection in complex neotropical environments . Remote Sensing of Environment , 112 ( 5 ) : 2145 – 2159 .
  • Shi , T. , Seligson , D. , Belldegrun , A. S. , Palotie , A. and Horvath , S. 2005 . Tumor classification by tissue microarray profiling: random forest clustering applied to renal cell carcinoma . Modern Pathology: An Official Journal of the United States and Canadian Academy of Pathology Inc , 18 : 547 – 557 .
  • Singh , M. , Singh , S. and Partridge , D. 2005 . “ Parameter optimization for image segmentation algorithms: a systematic approach ” . In Lecture Notes in Computer Science, 3687 , 11 – 19 . Berlin : Springer .
  • Song , W. and Bien , Z. 1997 . “ Optimization of parameters of color image segmentation using evolutionary programming ” . In Lecture Notes in Computer Science, 1285 , 97 – 105 . Berlin : Springer .
  • Stephens , S. E. , Walker , J. A. , Blunck , D. R. , Jayaraman , A. , Naugle , D. E. , Ringelman , J. K. and Smith , A. J. 2008 . Predicting the risk of habitat conversion in native temperate grasslands . Conservation Biology , 22 ( 5 ) : 1320 – 1330 .
  • Svetnik , V. , Liaw , A. , Tong , C. , Culberson , J. , Sheridan , R. and Feuston , B. 2003 . Random forest: a classification and regression tool for compound classification and QSAR modeling . Journal of Chemical Information and Computer Sciences , 43 : 1947 – 1958 .
  • van der Sande , C. J. , de Jong , S. M. and de Roo , A. P.J. 2003 . A segmentation and classification approach of IKONOS-2 imagery for land cover mapping to assist flood risk and flood damage assessment . International Journal of Applied Earth Observation and Geoinformation , 4 ( 3 ) : 217 – 229 .
  • Wang , J. and Cohen , M. F. 2005 . An iterative optimization approach for unified image segmentation and matting . Tenth IEEE International Conference on Computer Vision , 2 : 936 – 943 .
  • Yan , G. , Mas , J. F. , Maathuis , B. H.P. , Xiangmin , Z. and Van Dijk , P. M. 2006 . Comparison of pixel-based and object-oriented image classification approaches—a case study in a coal fire area, Wuda, Inner Mongolia, China . International Journal of Remote Sensing , 27 ( 18 ) : 4039 – 4055 .
  • Zhang , Y. , Brady , M. and Smith , S. 2001 . Segmentation of brain MRI images through a hidden Markov random field model and the expectation-maximization algorithm . IEEE Transactions on Medical Imaging , 20 ( 1 ) : 45 – 57 .

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