Crop-type identification potential of Radarsat-2 and MODIS images for the Canadian prairies

Canadian Journal of Remote Sensing

Volumn 37, Issue 1, 2011, Pages 45-54

  Hong, Gang ^a   Zhang, Aining ^a   Zhou, Fuqun ^a   Townley Smith, Lawrence ^b   Brisco, Brian ^a   Olthof, Ian ^a  

^a CANADA CENTRE FOR REMOTE SENSING   (Canada)

^b AGRICULTURE AND AGRI FOOD CANADA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); CROPS; DATA FUSION; IMAGE FUSION; IMAGE RECONSTRUCTION; IMAGE RESOLUTION; IMAGE SEGMENTATION; RADAR IMAGING; RADIOMETERS; SATELLITE IMAGERY; SYNTHETIC APERTURE RADAR;

CLASSIFICATION ACCURACY; FUSION CLASSIFICATION; MODERATE RESOLUTION; MULTIRESOLUTION SEGMENTATION; PRINCIPAL COMPONENTS; SPATIAL RESOLUTION; SPECTRAL INFORMATION; SPECTRO-RADIOMETERS;

IMAGE PROCESSING;

EID: 84869997388     PISSN: 07038992     EISSN: 17127971     Source Type: Journal    
DOI: 10.5589/m11-026     Document Type: Article

References (21)

1. Ban, Y. 2003. Synergy of multitemporal ERS-1 SAR and LANDSAT TM data for classification of agricultural crops. Canadian Journal of Remote Sensing, Vol. 29, No. 4, pp. 518-526. doi: 10.5589/m03-014.
2. Blaes, X., Vanhalle, L., and Defourny, P. 2005. Efficiency of crop identification based on optical and SAR image time series. Remote Sensing of Environment, Vol. 96, Nos. 3-4, pp. 352-365. doi: 10.1016/j.rse.2005.03.010.
3. Brisco, B., and Brown, R.J. 1995. Multi-date SAR/TM synergism for crop classification in western Canada. Photogrammetric Engineering and Remote Sensing, Vol. 61, No. 8, pp. 1009-1014.
4. Brisco, B., and Brown, R.J. 1998. Agricultural applications with Radar. In Manual of Remote Sensing. 3rd ed. Principles and Applications of Imaging Radar. Edited by R.A. Ryerson. Wiley, New York. pp. 381-406.
5. Brisco, B., Brown, R.J., and Manore, M.J. 1989. Early season crop discrimination with combined SAR and TM data. Canadian Journal of Remote Sensing, Vol. 15, No. 1, pp. 44-54.
6. Cihlar, J., Latifovic, R., Beaubien, J., Guindon, B., and Palmer, M. 2003. Thematic mapper (TM) based accuracy assessment of a land cover product for Canada derived from SPOT VEGETATION (VGT) data. Canadian Journal of Remote Sensing, Vol. 29, No. 2, pp. 154-170. doi: 10.5589/m02-091.
7. Cihlar, J., Xiao, Q., Beaubien, J., Fung, K., and Latifovic, R. 1998. Classification by progressive generalization: a new automated methodology for remote sensing multichannel data. International Journal ofRemote Sensing, Vol. 19, No. 14, pp. 2685-2704. doi: 10.1080/014311698214451.
8. Congalton, R.G. 1991. A review of assessing the accuracy of classifications of remotely sensed data. Remote Sensing of Environment, Vol. 37, No. 1, pp. 35-46.
9. Congalton, R., and Green, K. 1999. Assessing the accuracy of remotely sensed data: principles and practices. CRC/Lewis Press, Boca Raton, Florida.
10. Hong, G., Zhang, Y., Zhang, A., Zhou, F, and Li, J. 2007. Fusion of MODIS and Radarsat data for crop type classification -an initial study. ISPRS Workshop on Updating Geo-spatial Databases with Imagery and the 5th ISPRS Workshop on DMGISs, Editors, Jie Jiang, Renliang Zhao. ISPRS Working Groups, WG IV/1 Spatial Data Infrastructure, Istanbul, Turkey. pp. 153-156.
11. Hong, G., Zhang, Y., and Mercer, B. 2009. A wavelet and IHS integration method to fuse high resolution SAR with moderate resolution multispectral images. Photogrammetric Engineering and Remote Sensing, Vol. 75, No. 10, pp. 1213-1225.
12. Le Hegarat-Mascle, S., Quesney, A., and Vidal-Madjar, D. 2000. Land cover discrimination from multitemporal ERS images and multispectral Landsat images: a study case in an agricultural area in France. International Journal of Remote Sensing, Vol. 21, No. 3, pp. 435-456. doi: 10.1080/014311600210678.
13. Lewis, J.A., Henderson, F.M., and Holcomb, D.W 1998. Radar fundamentals: the geoscience perspective. In Manual ofRemote Sensing. 3rd ed., Principles and Applications of Imaging Radar. Edited by R.A. Ryerson, Wiley, New York, pp. 131-183.
14. McNairn, H., Ellis, J., van der Sanden, J.J., Hirose, T., and Brown, R.J. 2002. Providing crop information using RADARSAT-1 and satellite optical imagery International Journal of Remote Sensing, Vol. 23, No. 5, pp. 851-870. doi: 10.1080/01431160110070753.
15. McNairn, H., Champagne, C., Shang, J., Holmstrom, D., and Reichert, G. 2009. Integration of optical and synthetic aperture radar (SAR) imagery for delivering operational annual crop inventories. ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 64, No. 5, pp. 434-449. doi: 10.1016/j.isprsjprs.2008.07.006.
16. Richards, J.A., and Jia, X. 2006. Remote sensing digital image analysis: an introduction. 4th ed. Springer-Verlag, Berlin.
17. Schistad-Solberg, A., Jain, A., and Taxt, T. 1994. Multisource classification of remotely sensed data: fusion of Landsat TM and SAR Images. IEEE Transactions on Geoscience and Remote Sensing, Vol. 32, No. 4, pp.768-776. doi: 10.1109/36.298006.
18. Shang, J., McNairn, H., Champagne, C., and Jiao, X. 2009. Contribution of multi-frequency, multi-sensor, and multi-temporal radar data to operational annual crop mapping. IEEE Transactions on Geoscience and Remote Sensing, Vol. 3, No. 1, pp. III378-III381. doi: 10.1109/IGARSS.2008.4779362
19. Tou, J.T., and Gonzalez, R.C. 1974. Pattern Recognition Principles. Addison-Wesley Publishing Co., Reading, Massachusetts.
20. Trishchenko, A.P, Luo, Y, and Khlopenkov, K.V 2006. A method for downscaling MODIS land channels to 250 m spatial resolution using adaptive regression and normalization. Proceedings of SPIE -The International Society for Optical Engineering 6366. Art. No. 636607.
21. Van der Sanden, J.J., and Thomas, S.J, (Eds.). 2004. Applications potential of Radarsat-2. Supplement One. Canada Centre of Remote Sensing, Ottawa, Ontario.