Updating land-cover maps by using texture information from very high-resolution space-borne imagery

IEEE Transactions on Geoscience and Remote Sensing

Volumn 37, Issue 3 I, 1999, Pages 1244-1254

  Smits, Paul C ^a   Annoni, Alessandro ^a  

^a JOINT RESEARCH CENTRE   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL GEOMETRY; DATA STRUCTURES; DATABASE SYSTEMS; GEOGRAPHIC INFORMATION SYSTEMS; IMAGE ANALYSIS; IMAGE QUALITY; IMAGE SEGMENTATION; KNOWLEDGE BASED SYSTEMS; MATHEMATICAL TRANSFORMATIONS;

CHANGE DETECTION; HIGH RESOLUTION SPACEBORNE IMAGERY; LAND COVER MAPS;

REMOTE SENSING;

EID: 0032654451     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/36.763282     Document Type: Article

References (41)

1. World Commission on Environment and Development, Our Common Future. Oxford, U.K.: Oxford Univ. Press, 1987.
2. EUR 12585, "CORINE land-cover project-Technical guide," Luxembourg, 1993.
3. R. M. Haralick and D. S. Simonett, Image Processing for Remote Sensing. Reading, MA: Addison-Wesley, 1986.
4. R. A. Schowengerdt, Remote Sensing-Models and Methods for Image Processing. New York: Academic, 1997.
5. J. A. Richards, Remote Sensing Digital Image Analysis: An Introduction. Berlin, Germany: Springer-Verlag, 1986.
6. B. M. Shahshahani and D. A. Landgrebe, "The effect of unlabeled samples in reducing the small sample size problem and mitigating the Hughes phenomenon," IEEE Trans. Geosci. Remote Sensing, vol. 32, pp. 1087-1095, Sept. 1994.
7. M. R. Azimi-Sadjadi, S. Ghaloum, and R. Zoughi, "Terrain classification in SAR images using principal components analysis and neural
8. networks," IEEE Trans. Geosci. Remote Sensing, vol. 31, no. 2, pp. 511-515, Mar. 1993.
9. J. Heikkonen, I. Kanellopoulos, A. Varfis, A. Steel, and K. Fullerton, "Urban land use mapping with multi-spectral and SAR satellite data using neural networks," in Proc. Int. Geoscience and Remote Sensing Symp. (1GARSS 97), pp. 1660-1662.
10. E. Console and M. C. Mouchot, "Fuzzy classification techniques in the urban area recognition," in Proc. Int. Geoscience and Remote Sensing Symp. (IGARSS 96), Lincoln, pp. 1373-1375.
11. S. W. Wharton, "A spectral knowledge-based approach for urban landcover discrimination," IEEE Trans. Geosci. Remote Sensing, vol. GE-25, no. 3, pp. 272-282, 1987.
12. F. Wang, "A knowledge-based vision system for detecting land changes at urban fringes," IEEE Trans. Geosci. Remote Sensing, vol. 31, pp. 136-145, Jan. 1993.
13. Y. Baudouin, F. Cavayas, and C. Marois, "Vers une nouvelle méthode d'inventaire et de mise àjour de 1'occupation/utilization du sol en milieu urbain," Can. J. Remote Sens., vol. 21, no. 1, pp. 2812, Mar. 1995.
14. P. C. Smits and A. Annoni, "On the use of texture information for urban analysis in space-borne remote-sensing imagery," in Proc. Europto Conf. Image and Signal Processing for Remote-Sensing IV, Barcelona, Spain, SPIE, 1998, vol. 3500, in press.
15. V. Perdigào and A. Annoni, "Technical and methodological guide for updating Corine land-cover data base," publication EUR 17288 EN of the European Commission, Luxembourg: Office for official publications of the European Communities, 1997.
16. J. S. Weszka, C. R. Dyer, and A. Rosenfeld, "A comparative study of texture measures for terrain classification," IEEE Trans. Syst., Man, Cybern., vol. SMC-6, pp. 269-285, 1976.
17. R. W. Conners and C. A. Harlow, "A theoretical comparison of texture algorithms," IEEE Trans. Pattern Anal. Machine Intel!., vol. PAMI-2, pp. 203-222, 1980.
18. A. Ohanian and A. Dubes, "Performance evaluation for four classes of textural features," Pattern Recognit., vol. 25, pp. 819-833, 1992.
19. J. M. H. Du Buf, M. Kardan, and M. Spann, "Texture feature performance for image segmentation," Pattern Recognit., vol. 23, nos. 3/4, 1990.
20. R. M. Haralick, "Statistical and structural approaches to texture," Proc. IEEE, vol. 67, no. 5, pp. 786-803, 1979.
21. D.-C. He and L. Wang, "Texture unit, texture spectrum, and texture analysis," IEEE Trans. Geosci. Remote Sensing, vol. 28, pp. 509-512, July 1990.
22. L. Van Gool, P. Dewaele, and A. Oosterlinck, "Texture analysis anno 1983," Comput. Vision, Graphics, Image Process., vol. 29, pp. 336-357, 1985.
23. Tuceryan and Jain, "Texture analysis," in Handbook of Pattern Recognition and Computer Vision, C. H. Chen, L. F. Pau, and P. S. P. Wang, Eds. Singapore: World Scientific, pp. 235-276, 1993.
24. T. R. Reed and J. M. H. Du Buf, "A review of recent texture segmentation and feature extraction techniques," CVGIP: Image Understanding, vol. 57, no. 3, pp. 359-372, 1993.
25. R. W. Conners, M. A. Trivedi, and C. A. Harlow, "Segmentation of a high resolution urban scene using texture operators," Comput. Vision, Graphics, Image Processing, vol. 25, pp. 273-310, 1984.
26. R. Haralick and L. Shapiro, Computer and Robot Vision. Reading, MA: Addison-Wesley, 1992.
27. M. F. Augusteijn, L. E. Clemens, and K. A. Shaw, "Performance evaluation of texture measures for ground cover identification in satellite images by means of a neural network classifier," IEEE Trans. Geosci. Remote Sensing, vol. 33, pp. 616-626, May 1995.
28. R. D'Astous and M. Jernigan, "Texture discrimination based on detailed measures of the power spectrum," in IEEE Int. Conf. Pattern Recognition, Montreal, P.Q., Canada, 1984, pp. 83-86.
29. K. Steinnocker, "Integration of spectral and spatial classification methods for building a land-use model of Austria," Int. Arch. Photogramm. Remote Sensing, vol. XXXI, pt. B4, pp. 841-846, 1996.
30. J. L. Chen and A. Kundu, "Rotation and gray scale transform invariant texture identification using wavelet decomposition and hidden Markov model," IEEE Trans. Pattern Anal. Machine Intell, vol. 16, pp. 208-214, 1994.
31. H. Greenspan, S. Belongie, R. Goodman, and P. Perona, "Rotation invariant texture recognition using a steerable pyramid," in Proc. I2th Int. Conf. Pattern Recognition, 1994, pp. 162-167.
32. R. L. Kashyap and A. Khotanzad, "A model based method for rotation invariant classification," IEEE Trans. Pattern Anal. Machine Intell., vol. PAMI-8, pp. 472-481, 1986.
33. T. N. Tan, "Noise robust and rotation invariant texture classification," in Proc. EUSIPC094, pp. 717-728.
34. J. You and H. A. Cohen, "Classification and segmentation of rotated and scaled textured images using tuned masks," Pattern Recognit., vol. 26, pp. 245-258, 1993.
35. P. C. Smits and S. G. Dellepiane, "Synthetic aperture radar image segmentation by a detail preserving Markov random field approach," IEEE Trans. Geosci. Remote Sensing, vol. 35, pp. 844-857, July 1997.
36. S. Z. Li, Markov Random Field Modeling in Computer Vision. Tokyo, Japan: Springer-Verlag, 1995.
37. K. Fukunaga and R. R. Hayes, "Effects of sample size in classifier design," IEEE Trans. Pattern Anal. Machine Intell., vol. 11, Aug. 1989.
38. V. Bessettes, J. Desachy, and E. Cubero-Castan, "Applying co-operative operators for urban area detection using SPOT imagery," in Proc. Europto Conf. Image and Signal Processing for Remote Sensing III, Taormina, Italy, Sept. 23-25, 1996; Proc. SPIE, vol. 2955, pp. 106-117, 1996.
39. A. Baraldi and F. Parmiggiani, "Urban area classification by multispectral SPOT images," IEEE Trans. Geosci. Remote Sensing, vol. 28, pp. 674-680, 1990.
40. J. D. Paola and R. A. Schowengerdt, "A detailed comparison of backpropagation neural network and maximum-likelihood classifiers for urban land use classification," IEEE Trans. Geosci. Remote Sensing, vol. 33, pp. 981-996, July 1995.
41. S. Khorram, J. A. Brockhaus, and H. M. Cheshire, "Comparison of Landsat MSS and TM data for urban land-use classification," IEEE Trans. Geosci. Remote Sensing, vol. 25, pp. 238-243, Mar. 1987.