Urban mapping using coarse SAR and optical data: Outcome of the 2007 GRSS data fusion contest

IEEE Geoscience and Remote Sensing Letters

Volumn 5, Issue 3, 2008, Pages 331-335

  Pacifici, Fabio ^a,b   Del Frate, Fabio ^a,b   Emery, William J ^a,c   Gamba, Paolo ^a,d   Chanussot, Jocelyn ^a,e  

^a IEEE

^b UNIVERSITY OF ROME TOR VERGATA   (Italy)

^c UCB 450   (United States)

^d UNIVERSITY OF PAVIA   (Italy)

^e GIPSA LAB   (France)

Author keywords

Data fusion; European remote sensing satellite (ERS); Image classification; Landsat; Neural networks (NNs); Urban remote sensing

Indexed keywords

CONFORMAL MAPPING; DETECTORS; FUSION REACTIONS; IMAGING SYSTEMS; IMAGING TECHNIQUES; INFORMATION FUSION; MAPS; NUCLEAR PHYSICS; OPTICAL SENSORS; RADAR; REGIONAL PLANNING; REMOTE SENSING; SPACE OPTICS; SYNTHETIC APERTURE RADAR; SYNTHETIC APERTURES; TARGET DRONES;

DATA SETS; GEOSCIENCE; LAND USE/LAND COVER (LULC); MAPPING ACCURACY; MULTI TEMPORAL; MULTI-SOURCE; NEURAL CLASSIFICATION; OPTICAL DATA; REMOTE SENSING DATA FUSION; SATELLITE SENSORS; TECHNICAL COMMITTEES; URBAN AREAS; URBAN MAPPING;

SENSOR DATA FUSION;

EID: 47849094269     PISSN: 1545598X     EISSN: None     Source Type: Journal    
DOI: 10.1109/LGRS.2008.915939     Document Type: Article

References (28)

1. D. Hall, Mathematical Techniques in Multisensor Data Fusion. Boston, MA: Artech House, 1992.
2. A. H. Schistad Solberg, A. K. Jain, and T. Taxt, "Multisource classification of remotely sensed data: Fusion of Landsat TM and SAR images," IEEE Trans. Geosci. Remote Sens., vol. 32, no. 4, pp. 768-778, Jul. 1994.
3. M. Fauvel, J. Chanussot, and J. A. Benediktsson, "Decision fusion for the classification of urban remote sensing images," IEEE Trans. Geosci. Remote Sens., vol. 44, no. 10, pp. 2828-2838, Oct. 2006.
4. 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 Sens., vol. 28, no. 4, pp. 540-552, Jul. 1990.
5. J. Chanussot, G. Mauris, and P. Lambert, "Fuzzy fusion techniques for linear features detection in multi-temporal SAR images," IEEE Trans. Geosci. Remote Sens., vol. 37, no. 3, pp. 1292-1305, May 1999.
6. A. H. Schistad Solberg, T. Taxt, and A. K. Jain, "A Markov random field model for classification of multisource satellite imagery," IEEE Trans. Geosci. Remote Sens., vol. 34, no. 1, pp. 100-113, Jan. 1996.
7. A. H. Schistad Solberg, "Contextual data fusion applied to forest map revision," IEEE Trans. Geosci. Remote Sens., vol. 37, no. 3, pp. 1234-1243, May 1999.
8. A. V. Bogdanov, S. Sandven, O. M. Johannessen, V. Y. Alexandrov, and L. P. Bobylev, "Multisensor approach to automated classification of sea ice image data," IEEE Trans. Geosci. Remote Sens., vol. 43, no. 7, pp. 1648-1664, Jul. 2005.
9. M. Q. Nguyen, P. M. Atkinson, and H. G. Lewis, "Superresolution mapping using a Hopfield neural network with fused images," IEEE Trans. Geosci. Remote Sens., vol. 44, no. 3, pp. 736-749, Mar. 2006.
10. S. Zhao, "Remote sensing data fusion using support vector machine," in Proc. IGARSS, Sep. 20-24, 2004, vol. 4, pp. 2575-2578.
11. J. A. Benediktsson, J. R. Sveinsson, and P. H. Swain, "Hybrid consensus theoretic classification," IEEE Trans. Geosci. Remote Sens., vol. 35, no. 4, pp. 833-843, Jul. 1997.
12. L. Alparone, L. Wald, J. Chanussot, C. Thomas, P. Gamba, and L. M. Bruce, "Comparison of pansharpening algorithms: Outcome of the 2006 GRS-S data fusion contest," IEEE Trans. Geosci. Remote Sens., vol. 45, no. 10, pp. 3012-3021, Oct. 2007.
13. P. Gamba, "A collection of data for urban area characterization, " in Proc. IGARSS, Sep. 20-24, 2004, vol. 1, pp. 69-72.
14. F. Dell'Acqua, P. Gamba, and G. Lisini, "Improvements to urban area characterization using multitemporal and multiangle SAR images," IEEE Trans. Geosci. Remote Sens., vol. 4.1, no. 9, pp. 1996-2004, Sep. 2003.
15. J. A. Richards and X. Jia, Remote Sensing Digital Image Analysis. Berlin, Germany: Springer-Verlag, 2006.
16. C. Bishop, Neural Networks for Pattern Recognition. New York: Oxford Univ. Press, 1995.
17. N. K. Kasabov, Foundations of Neural Networks, Fuzzy Systems and Knowledge Engineering. Cambridge, MA: MIT Press, 1996.
18. V. Kecman, Learning and Soft Computing: Support Vector Machines, Neural Networks and Fuzzy Logic Models. Cambridge, MA: MIT Press, 2001.
19. S. K. Pal and S. Mitra, "Multilayer perceptron, fuzzy sets, and classification," IEEE Trans. Neural Netw., vol. 3, no. 5, pp. 683-697, Sep. 1992.
20. F. Del Frate, A. Petrocchi, J. Lichtenegger, and G. Calabresi, "Neural networks for oil spill detection using ERS-SAR data," IEEE Trans. Geosci. Remote Sens., vol. 38, no. 5, pp. 2282-2287, Sep. 2000.
21. F. Del Frate, F. Pacifici, G. Schiavon, and C. Solimini, "Use of neural networks for automatic classification from high-resolution images," IEEE Trans. Geosci. Remote Sens., vol. 45, no. 4, pp. 800-809, Apr. 2007.
22. M. F. Møller, "A scaled conjugate gradient algorithm for fast supervised learning," Neural Netw., vol. 6, no. 4, pp. 525-533, 1993.
23. B. Hassibi, D. G. Stork, and G. Wolf, "Optimal brain surgeon and general network, pruning," in Proc. IEEE Int. Conf. Neural Netw., San Francisco, CA, Apr. 1993, pp. 293-300.
24. T. Kavzoglu and P. M. Mather, "Pruning artificial neural networks: An example using land cover classification of multi-sensor images," Int. J. Remote Sens., vol. 20, no. 14, pp. 2787-2803, Sep. 1999.
25. A. Zell et al, SNNS, Stuttgart Neural Network Simulator, User's Manual v.4.2. Stuttgart, Germany: Univ. Stuttgart.
26. T. Ragg, H. Braun, and H. Landsberg, "A comparative study of neural network optimization techniques," in Proc. ICNNGA, Norwich, U.K., 1997, pp. 343-347.
27. H. Huang, J. J. Legarsky, S. Gudimetla, and C. H. Davis, "Post-classification smoothing of digital classification map of St. Louis, Missouri," in Proc. IGARSS, Sep. 2004, vol. 5, pp. 3039-3041.
28. R. A. Schowengerdt, Techniques for Image Processing and Classification in Remote Sensing. New York: Academic, 1983.