Machine learning approaches for high-resolution urban land cover classification: [A comparative study]

ACM International Conference Proceeding Series

Volumn , Issue , 2011, Pages

  Vatsavai, Ranga Raju ^a   Varun, Chandola ^a   Cheriyadat, Anil ^a   Bright, Eddie ^a   Budhendra, Bhaduri ^a   Grasser, Jordan ^a  

^a OAK RIDGE NATIONAL LABORATORY   (United States)

Author keywords

Bayesian classification; MCS; Neural networks; Trees

Indexed keywords

BAYESIAN CLASSIFICATION; CLASSIFICATION TASKS; CLASSIFICATION TECHNIQUE; COMPARATIVE STUDIES; HIGH RESOLUTION; HIGH RESOLUTION REMOTE SENSING; LOGISTIC REGRESSIONS; MACHINE-LEARNING; MCS; MULTIPLE CLASSIFIER SYSTEMS; STATISTICAL CLASSIFICATION; TREES; URBAN LAND COVER CLASSIFICATION;

IMAGE RECONSTRUCTION; MAXIMUM LIKELIHOOD; NEURAL NETWORKS; REMOTE SENSING;

LEARNING SYSTEMS;

EID: 79960089324     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1999320.1999331     Document Type: Conference Paper

References (26)

1. L. Anselin. Spatial Econometrics: methods and models. Kluwer, Dordrecht, Netherlands, 1988.
2. R. E. Banfield, L. O. Hall, K. W. Bowyer, and W. P. Kegelmeyer. A comparison of decision tree ensemble creation techniques. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 29(1):173-180, Jan. 2007. (Pubitemid 46415955)
3. A. Benediktsson, P. Swain, and O. Ersoy. Neural network approaches versus statistical methods in classificaion of multisource remote sensing data. IEEE Transactions on Geoscience and Remote Sensing, 28(4):550, 1990.
4. L. Bruzzone, C. Consese, F. Masellit, and F. Roli. Multisource classification of complex rural areas by statistical and neural-network approaches. Photogrammetric Engineering & Remote Sensing, 63(5):523-533, May 1997.
5. L. Bruzzone and R. Cossu. A robust multiple classifier system for a partially unsupervised updating of land-cover maps. In 2nd International Workshop on Multiple Classifier Systems, pages 259-268, 69121 Heidelberg, Germany, 2001. LNCS 2096, Springer Verlag. (Pubitemid 33303233)
6. K. M. Buddhiraju and I. A. Rizvi. Comparison of CBF, ANN and SVM classifiers for object based classification of high resolution satellite images. In Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International, pages 40 -43, July 2010.
7. S. Dreiseitl and L. Ohno-Machado. Logistic regression and artificial neural network classification models: a methodology review. Journal of Biomedical Informatics, 35(5-6):352-359, 2002. (Pubitemid 36951935)
8. M. Fauvel, J. Chanussot, and J. A. Benediktsson. Decision fusion for the classification of urban remote sensing images. Geoscience and Remote Sensing, IEEE Transactions on, 44(10):2828-2838, Oct. 2006.
9. M. A. Friedl and C. E. Brodley. Decision Tree Classification of Land Cover from Remotely Sensed Data. Remote Sensing of Environment, 61:399-409, 1997. (Pubitemid 28052029)
10. J. Ham, Y. Chen, M. M. Crawford, and J. Ghosh. Investigation of the random forest framework for classification of hyperspectral data. Geoscience and Remote Sensing, IEEE Transactions on, 43(3):492-501, Mar. 2005. (Pubitemid 40320271)
11. S. Haykin. Neural Networks - A comprehensive foundation. Macmillan, 866 Third Avenue, New York, NY-10022, 1994.
12. M. Hixson, D. Scholz, and N. Funs. Evaluation of several schemes for classification of remotely sensed data. Photogrammetric Engineering & Remote Sensing, 46:1547-1553, 1980. (Pubitemid 11460603)
13. I. Kanellopoulos and G. G. Wilkinson. Strategies and best practice for neural network image classification. International Journal of Remote Sensing, 18(4):711-725, 1997.
14. B. Krishnapuram, L. Carin, M. A. Figueiredo, and A. J. Hartemink. Sparse multinomial logistic regression: fast algorithms and generalization bounds. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 27(6):957-968, June 2005. (Pubitemid 40889845)
15. L. I. Kuncheva, J. C. Bezdek, and R. P. W. Duin. Decision templates for multiple classifier fusion: an experimental comparison. Pattern Recognition, 34(2):299-314, 2001. (Pubitemid 32871876)
16. X. Liao and L. Carin. Migratory logistic regression for learning concept drift between two data sets with application to UXO sensing. Geoscience and Remote Sensing, IEEE Transactions on, 47(5):1454-1466, May 2009.
17. J. Paola and R. Schowengerdt. A detailed comparison of backpropagation neural network and maximum likelihood classifiers for urban land use classification. IEEE Transactions on Geoscience and Remote Sensing, 33(4):981-996, 1995.
18. J. Paola and R. Schowengerdt. The effect of neural-network structure on a multispectral land-use/land-cover classification. Photogrammetric Engineering & Remote Sensing, 63(5):535-544, May 1997.
19. J. D. Paola and R. A. Schowengerdt. A detailed comparison of backpropagation neural network and maximum-likelihood classifiers for urban land use classification. Geoscience and Remote Sensing, IEEE Transactions on, 33(4):981-996, July 1995.
20. G. T. Papadopoulos, K. Chandramouli, V. Mezaris, I. Kompatsiaris, E. Izquierdo, and M. G. Strintzis. A comparative study of classification techniques for Knowledge-Assisted image analysis. In Image Analysis for Multimedia Interactive Services, 2008. WIAMIS '08. Ninth International Workshop on, pages 4 -7, May 2008.
21. J. R. Quinlan. C4.5: Programs for Machine Learning. Morgan Kaufmann, San Diego, CA, 1993.
22. A. Skidmore, B. Turner, W. Brinkhof, and E. Knowles. Performance of a neural network: Mapping forest using gis and remorely sensed data. Photogrammetric Engineering & Remote Sensing, 63(5):501-514, May 1997.
23. P. C. Smits. Multiple classifier systems for supervised remote sensing image classification based on dynamic classifier selection. Geoscience and Remote Sensing, IEEE Transactions on, 40(4):801-813, Apr. 2002. (Pubitemid 34741654)
24. A. Strahler. The use of prior probabilities in maximum likelihood classification of remote sensing data. Remote Sensing of Environment, 10:135-163, 1980.
25. R. R. Vatsavai, A. Cheriyadat, and S. S. Gleason. Unsupervised semantic labeling framework for identification of complex facilities in high-resolution remote sensing images. In ICDM Workshops, pages 273-280, 2010.
26. V. Vijayaraj, A. Cheriyadat, P. Sallee, B. Colder, R. R. Vatsavai, E. A. Bright, and B. L. Bhaduri. Overhead image statistics. In AIPR, pages 1-8, 2008.