Art neural networks for remote sensing: vegetation classification from landsat tm and terrain Data

IEEE Transactions on Geoscience and Remote Sensing

Volumn 35, Issue 2, 1997, Pages 308-325

  Carpenter, Gail A ^a   Gjaja, Marin N ^a   Gopal, Sucharita ^a   Woodcock, Curtis E ^a  

^a BOSTON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATION; CLASSIFICATION (OF INFORMATION); FUZZY SETS; MAPPING; PATTERN RECOGNITION; PERFORMANCE; REMOTE SENSING; SATELLITES; TESTING;

AUTOMATIC MAPPING; HYBRID SYSTEMS; LANDSAT THEMATIC MAPPER; VEGETATION CLASSIFICATION;

NEURAL NETWORKS;

EID: 0031098234     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/36.563271     Document Type: Article

References (45)

1. R.M. Hoffer and Staff, Natural Resources Mapping in Mountainous Terrain by Computer Analysis of ERTS-l Satellite Data, Agricultural Experiment Station Research Bulletin 919 and LARS Contract Report 061575, Purdue University, W. Lafayette, IN, p. 124, 1975.
2. A.H. Strahler, T.L. Logan, and N.A. Bryant, " Improving forest cover classification accuracy from Landsat by incorporating topographic information," in Proc. 12th Int. Symp. Remote Sensing Environ. , Ann Arbor, MI: Environmental Research Institute of Michigan, 1978, pp. 927-942.
3. J.A. Benediktsson, P.H. Swain, and O.K. Ersoy, " Conjugate-gradient neural networks in classification of multisource and very-high-dimensional remote sensing data," Int.J. Remote Sensing, vol. 14, pp. 2883-2903, 1993.
4. A. Baraldi and F. Parmiggiani, " A neural network for unsupervised categorization of multivalued input patterns: An application of satellite image clustering," IEEE Trans. Geosci. Remote Sensing, vol. 33, pp. 305-316, 1995.
5. H. Bischoff, W. Schneider, and A.J. Pinz, " Multispectral classification of Landsat images using neural networks," IEEE Trans. Geosci. Remote Sensing, vol. 30, pp. 482-190, 1992.
6. P.D. Heermann and N. Khazenie, " Classification of multispectral remote sensing data using a back-propagation neural network," IEEE Trans. Geosci. Remote Sensing, vol. 30, pp. 81-88, 1992.
7. Y.C. Tzeng, K.S. Chen, W. -L. Kao, and A.K. Fung, " A dynamic learning neural network for remote sensing applications," IEEE Trans. Geosci. Remote Sensing, vol. 32, pp. 1096-1103, 1994. [8] S.E. Decatur, " Application of neural networks to terrain classification," in Proc. Int. Joint Conf. Neural Networks, Piscataway, NJ: IEEE, 1989, vol. I, pp. 283-288.
8. S. Grossberg, E. Mingolla, and J.R. Williamson, " Synthetic aperture radar processing by a multiple scale neural system for boundary and surface representation," Neural Networks, vol. 8, pp. 1005-1028, 1995.
9. S. Gopal, D.M. Sklarew, and E. Lambin, " Fuzzy-neural networks in multi-temporal classification of landcover change in the Sahel," in Proc. DOSES Workshop New Tools Spatial Anal. , Lisbon, Portugal, DOSES, EUROSTAT, pp. 55-68, 1994.
10. A. Abuelgasim, S. Gopal, S.J. Irons, and A. Strahler, " Classification of ASAS multi-angle and multispectral measurements using artificial neural networks," Remote Sensing Environ. , vol. 59, pp. 79-87, 1996.
11. G.F. Hepner, T. Logan, N. Ritter, and N. Bryant, " Artificial neural network classification using a minimal training set comparison of conventional supervised classification," Photogram. Eng. Remote Sensing, vol. 56, pp. 469-473, 1990.
12. R.W. Fitzgerald and B.G. Lees, " Assessing the classification accuracy of multisource remote sensing data," Remote Sensing Environ. , vol. 47, pp. 362-368, 1994.
13. R.G. Congalton, K. Green, and J. Teply, " Mapping old growth forests on national forest and park lands in the pacific northwest from remotely sensed data," Photogram. Eng. Remote Sensing, vol. 59, pp. 529-535, 1993.
14. W.G. Cibula and M.O. Nyquist, " Use of topographic and climatological models in a geographic data base to improve Landsat MSS classification for Olympic National Park," Photogrammetric Engineering and Remote Sensing, vol. 53, pp. 67-75, 1987.
15. T.D. Frank, " Mapping dominant vegetation communities in the Colorado Rocky Mountain front range with Landsat Thematic Mapper and digital terrain data," Photogram. Eng. Remote Sensing, vol. 54, pp. 1727-1734, 1988.
16. J. Franklin, T.L. Logan, C.E. Woodcock, and A.H. Strahler, " Coniferous forest classification and inventory using Landsat and digital terrain data," IEEE Trans. Geosci. Remote Sensing, vol. 24, pp. 139-149, 1986.
17. B.G. Lees and K. Ritman, " Decision-tree and rule-induction approach to integration of remotely sensed and GIS data in mapping vegetation in disturbed or hilly environments," Environ. Mgt. , vol. 15, pp. 823-831, 1991.
18. A.K. Skidmore, " An expert system classifies Eucalypt forest types using Thematic Mapper data and a digital terrain model," Photogram. Eng. Remote Sensing, vol. 55, pp. 1449-1464, 1989.
19. C.E. Woodcock, J. Collins, S. Gopal, V. Jakabhazy, X. Li, S. Macomber, S. Ryherd, Y. Wu, V.J. Harward, J. Levitan, and R. Warbington, " Mapping forest vegetation using Landsat TM imagery and a canopy reflectance model," Remote Sensing Environ. , vol. 50, pp. 240-254, 1994.
20. D.E. Rumelhart, G. Hinton, and R. Williams, " Learning internal representations by error propagation," Parallel Distributed Processing, D.E. Rumelhart and J.L. McClelland, Eds. Cambridge, MA: MIT Press, 1986, pp. 318-362.
21. P. Werbos, " Beyond Regression: New Tools for Prediction and Analysis in the Behavioral Sciences," Ph. D Thesis, Cambridge, MA: Harvard University, 1974.
22. F. Rosenblatt, " The perceptron: A probabilistic model for information storage and organization in the brain," Psychol. Rev. , vol. 65, pp. 386-408, 1958. Reprinted in J.A. Anderson and E. Rosenfeld, Eds. , Neurocomputing: Foundations of Research. Cambridge, MA: MIT Press, 1988, pp. 18-27.
23. Y. Salu and J. Tilton, " Classification of multispectral image data by the binary diamond neural network and by nonparametric, pixel-by-pixel methods," IEEE Trans. Geosci. Remote Sens. , vol. 30, pp. 606-618, 1993.
24. D.M. Foody, M.B. McCulloch, and W.B. Yates, " Classification of remotely sensed data by an artificial neural network: Issues related to training data characteristics," Photogramm. Eng. Remote Sens. , vol. 61, pp. 391-401, 1995.
25. P. Gong, " Frequency-based contextual classification and grey-level vector reduction for land-use identification," Photogramm. Eng. Remote Sens. , vol. 58, pp. 439-448, 1992.
26. A.K. Skidmore and B.J. Turner, " Forest mapping accuracies are improved using a supervised nonparametric classifier with SPOT data," Photogramm. Eng. Remote Sens. , vol. 54, pp. 1415-1421, 1988.
27. P.C. Van Deusen, " Modified highest confidence first classification," Photogramm. Eng. Remote Sens. , vol. 61, pp. 419-425, 1995.
28. S. Grossberg, " Adaptive pattern classification and universal recoding, II: Feedback, expectation, olfaction, and illusions," Biolog. Cybernet. , vol. 23, pp. 187-202, 1976.
29. G.A. Carpenter and S. Grossberg, " A massively parallel architecture for a self-organizing neural pattern recognition machine," Comput. Vision Graphics Image Process. , vol. 37, pp. 54-115, 1987.
30. Pattern Recognition by Self-Organizing Neural Networks, G.A. Carpenter and S. Grossberg, Eds. Cambridge, MA: MIT Press, 1991.
31. G.A. Carpenter and S. Grossberg, " ART 2: Stable self-organization of pattern recognition codes for analog input patterns," Appl. Optic. , vol. 26, pp. 4919-4930, 1987.
32. G.A. Carpenter, S. Grossberg, and D.B. Rosen, " Fuzzy ART: Fast stable learning and categorization of analog patterns by an Adaptive Resonance system," Neural Networks, vol. 4(6), pp. 759-771, 1991.
33. G.A. Carpenter, S. Grossberg, and J.H. Reynolds, " ARTMAP: Supervised real-time learning and classification of nonstationary data by a self-organizing neural network," Neural Networks, vol. 4, pp. 565-588, 1991.
34. G.A. Carpenter, S. Grossberg, N. Markuzon, J.H. Reynolds, and D.B. Rosen, " Fuzzy ARTMAP: A neural network architecture for incremental supervised learning of analog multidimensional maps," IEEE Trans. Neural Networks, vol. 3, pp. 698-713, 1992.
35. G.A. Carpenter and S. Grossberg, " ART 3: Hierarchical search using chemical transmitters in self-organizing pattern recognition architectures," Neural Networks, vol. 3, pp. 129-152, 1990.
36. B. Moore, " ART 1 and pattern clustering," in P roc. 1988 Connectionist Models Summer School, D. Touretzky, G. Hinton, and T. Sejnowski, Eds. San Mateo, CA: Morgan Kaufmann, 1989, pp. 174-185.
37. L. Zadeh, " Fuzzy sets," Information and Control, vol. 8, pp. 338-353, 1965.
38. G.A. Carpenter and N. Markuzon, " ARTMAP-IC and medical diagnosis: Instance counting and inconsistent cases," Neural Networks, Tech. Rep. CAS/CNS TR-96-017, Boston, MA: Boston University, 1996.
39. W.J. Matyas and I. Parker, " CALVEG mosaic of existing vegetation of California," San Francisco, CA: Regional Ecology Group, U.S. Forest Service, Region 5, 630 Sansome Street, p. 27, 1980.
40. T.M. Lillesand and R.W. Kiefer, Remote Sensing and Image Interpretation, 3rd ed. New York: Wiley, 1994, pp. 594-596.
41. J. Richards, Remote Sensing Digital Image Analysis: An Introduction. Berlin, Germany: Springer-Verlag: 1993, pp. 182-189.
42. R.O. Duda and P.E. Hart, Pattern Classification and Scene Analysis. New York: Wiley, 1973.
43. E.P. Christ, " A TM tasseled cap equivalent transformation for re-flectance factor data," Remote Sensing Environ. , vol. 17, pp. 301-306, 1985.
44. S.E. Franklin, D.R. Peddle, and J.E. Moulton, " Spectral/geomorphometric discrimination and mapping of terrain: A study of Gros Morne National Park," Canadian J. Remote Sensing, vol. 15, pp. 28-42, 1989.
45. J.A. Benediktsson, P.H. Swain, and O.K. Ersoy, " Neural network approaches versus statistical methods in classification of multisource remote sensing data," IEEE Trans. Geosci. Remote Sensing, vol. 28, pp. 540-552, 1990.