Estimating coniferous forest structure using SAR texture and tone

Canadian Journal of Remote Sensing

Volumn 22, Issue 4, 1996, Pages 382-389

  Wilson, Bradley A ^a  

^a UNIVERSITY OF REGINA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

FORESTRY; OPTICAL DATA PROCESSING; POLARIZATION; RADAR IMAGING; REGRESSION ANALYSIS; SYNTHETIC APERTURE RADAR;

CONIFEROUS FOREST STRUCTURE; STEPWISE REGRESSION METHOD;

REMOTE SENSING;

EID: 0030417734     PISSN: 07038992     EISSN: 17127971     Source Type: Journal    
DOI: 10.1080/07038992.1996.10874662     Document Type: Article

References (35)

1. Ahem, F.J., Leckie, D.J., and Drieman, J.A., 1993, Seasonal Changes in Relative C-band Backscatter of Northern Forest Cover Types, IEEE Transactions on Geoscience and Remote Sensing, vol. 31, no. 3, pp. 668-680.
2. Ahem, F.J., Skelly, W.C., McDonald, K., and Pearce, C.M., 1991, Studies of Microwave Sensitivity to Black Spruce Forest Biomass with the MIMICS Model, Proceedings, 14th Canadian Symposium on Remote Sensing, Calgary, Alberta, pp. 234-239.
3. Barber, D.G., and LeDrew, E.F., 1991, SAR Sea Ice Discrimination Using Texture Statistics: A Multivariate Approach, Photogrammetric Engineering and Remote Sensing, vol. 57, no. 4, pp. 385-395.
4. Brown, R.J., 1987, Preparing for Satellite Microwave Systems for Renewable Resource Management, Geocarto International, vol. 3, pp. 31-37.
5. Brown, R.J., Guindon, B., Teillet, P.M., and Goodenough, D.G., 1986, Crop Type Determination from Multitemporal SAR Imagery, Proceedings, 9th Canadian Symposium on Remote Sensing, pp. 683-691.
6. Bryan, M.L., 1981, Urban Land Use Classification Using Synthetic Aperture Radar, Proceedings, PECORA VII Symposium, Sioux Falls, South Dakota, Oct. 18-21, pp. 124-143.
7. Chauhan, N.S., Lang, R.H., and Ranson, K.J., 1991, Radar Modeling of a Boreal Forest, IEEE Transactions on Geoscience and Remote Sensing, vol. 29, no. 4, pp. 627-637.
8. Cohen, W.B., Spies, T.A., and Fiorella, M., 1995, Estimating the Age and Structure of Forests in a Multi-ownership Landscape of Western Oregon, USA, International Journal of Remote Sensing, vol. 16, no. 4, pp. 721-746.
9. Dobson, M.C., Ulaby, F.T., LeToan, T., Beaudoin, A., Kasischke, E.S., and Christensen, N., 1992, Dependence of Radar Backscatter on Coniferous Forest Biomass, IEEE Transactions on Geoscience and Remote Sensing, vol. 30, no. 2, pp. 412-415.
10. Evans, D.L., and Smith, M.O., 1991, Separation of Vegetation and Rock Signatures in Thematic Mapper and Polarimetric SAR Images, Remote Sensing of Environment, vol. 37, pp. 63-75.
11. Fiumara, A., and Pierdicca, N., 1989, Evaluation of Classification Results Obtained with Combined Multitemporal Optical and Microwave Data, Proceedings, 12th Canadian Symposium on Remote Sensing, IGARRS ‘89, July 10-14, 1989, Vancouver, British Columbia, vol. 2, pp. 787-790.
12. Franklin, S.E., M.B. Lavigne, B.A. Wilson, and E.R. Hunt, 1994, Empirical relations between balsam Fir Forest Stands Conditions and ERS-1 SAR Data in Western Newfoundland, Canadian Journal of Remote Sensing, vol. 20, no. 2, pp. 124-130.
13. Hall, R.J., Kruger, A.R., Scheffer, J., Titus, S.J., and Moore, W.C., 1989, A Statistical Evaluation of Landsat TM and MSS Data for Mapping Forest Cutovers, The Forestry Chronicle, December, pp. 441-449.
14. Haralick, R.M., Shanmugam, K., and Dinstein, I., 1973, Textural Features for Image Classification, IEEE Transactions on Systems, Man, and Cybernetics, vol. SMC-3, no. 6, pp. 610-621.
15. Imhoff, M.L., 1995, A Theoretical Analysis of the Effect of Forest Structure on Synthetic Aperture Radar Backscatter and the Remote Sensing of Biomass, IEEE Transactions on Geoscience and Remote Sensing, vol. 33, no. 2, pp. 341-352.
16. Kasischke, E.S., Christensen, N.L., Jr. and Bourgeau-Chavez, L.L., 1995, Correlating Radar Backscatter with Components of Biomass in Loblolly Pine Forests, IEEE Transactions on Geoscience and Remote Sensing, vol. 33, no. 3, pp. 643-659.
17. Lavigne, M.B., 1988, Stem Growth and Respiration of Young Balsam Fir Trees in Thinned and Unthinned Stands, Canadian Journal of Forest Research, vol. 18, pp. 483-489.
18. LeToan, T., Beaudoin, A., Riom, J., and Guyon, D., 1992, Relating Forest Biomass to SAR Data, IEEE Transactions on Geoscience and Remote Sensing, vol. 30, no. 2, pp. 403-411.
19. Mascarenhas, N.D.A., Ono, S.E., Fernandes, D„ and Kux, H.J.H., 1991, A Comparative Study of Speckle Reduction Filters in SAR Images and their Application for Classification Performance Improvement, 24th International Symposium on Remote Sensing of Environment, Rio de Janeiro, Brazil, May 27-31, Vol. II, pp. 911-923.
20. McDonald, K.C., Dobson, M.C., and Ulaby, F.T., 1991, Modeling Multifrequency Diurnal Backscatter from a Walnut Orchard, IEEE Transactions on Geoscience and Remote Sensing, vol. 29, no. 6, pp. 852-863.
21. Moghaddam, M., Durden, S., and Zebker, H., 1994, Radar Measurement of Forested Areas during OTTER, Remote Sensing of Environment, vol. 47, pp. 154-166.
22. Paris, J.F., and Kwong, H.H., 1988, Characterization of Vegetation with Combined Thematic Mapper and Shuttle Imaging (SIR-B) Image Data, Photogrammetric Engineering and Remote Sensing, vol. 54, no. 8, pp. 1187-1193.
23. Rast, M., Jaskolla, F., and Amason, K., 1991, Comparative Digital Analysis of SEASAT-SAR and Landsat-TM Data for Iceland, International Journal of Remote Sensing, vol. 12, no. 3, pp. 527-544.
24. Richards, J.A., Sun, G.Q., and Simonett, D.S., 1987, L-band Radar Backscatter Modeling of Forest Stands, IEEE Transactions on Geoscience and Remote Sensing, Vol. GE-25, no. 4, pp. 487-498.
25. Rochon, G., Gosselin, C., Rheault, M., Vincent, P., Thomson, K.P.B., Goze Bertin, B., Poirier, S., and Cavayas, F., 1986, Study on the use of SAR data for Agriculture and Forestry, Proceedings, ESA Workshop on SAR Applications, Frascati, Italy, Sept. 16-18, 1986, pp. 81-93.
26. Rubin, T., 1989, Analysis of Radar Texture with Variograms and Other Simplified Descriptors, Proceedings, Image Processing’89, May 23, 1989, Sparks, NV, pp. 185-195.
27. Sheen, D.R., and Johnston, L.P., 1992, Statistical and Spatial Properties of Forest Clutter Measured with Polarimetric SAR, IEEE Transactions on Geoscience and Remote Sensing, vol. 30, no. 3, pp. 578-588.
28. Spurr, S.H., 1964, Forest Ecology, Ronald Press Company, New York, 352p.
29. Strong, W.L., and Leggat, K.R., 1992, Ecoregions of Alberta, Alberta Forestry, Lands and Wildlife, publication # T/245, 56p.
30. Thomas, I.L. and Allcock, G.M., 1984, Determining the Confidence Level for a Classification, Photogrammetric Engineering and Remote Sensing, vol. 50, no. 10, pp. 1491-1496.
31. Ulaby, F.T., Kouyate, F., Brisco, B., and Williams, T.H.L., 1986, Textural Information in SAR Images, IEEE Transactions on Geoscience and Remote Sensing, Vol. GE-24, no. 2, pp. 235-245.
32. Ustin, S.L., Martens, S.N., and Vanderbilt, V.C., 1991, Canopy Architecture of a Walnut Orchard, IEEE Transactions on Geoscience and Remote Sensing, vol. 29, no. 6, pp. 843-851.
33. Vistnes, R., 1987, Computer Texture Analysis and Segmentation, Proceedings, IEEE Computer Society Workshop on Computer Vision, Miami Beach, Florida, Nov. 30-Dec. 2, 1987, pp. 231-233.
34. Weishampel, J.F., Sun, G., Ranson, K.J., LeJeune, K.D., and Shugart, H.H., 1994, Forest Textural Properties from Simulated Microwave Backscatter: The Influence of Spatial Resolution, Remote Sensing of Environment, vol. 47, pp. 120-131.
35. Young, T.Y., and Fu, K., (editors), 1986, Handbook of Pattern Recognition and Image Processing, Academic Press, Orlando, Florida, pp. 247-265.