The Contribution of ALOS PALSAR Multi-polarization and Polarimetric Data to Crop Classification.

McNairn, H., Shang, J., Jiao, X., and Champagne, C. (2009). "The Contribution of ALOS PALSAR Multi-polarization and Polarimetric Data to Crop Classification.", IEEE Transactions on Geoscience and Remote Sensing, 47(12, Article No. 5233805), pp. 3981-3992. doi : 10.1109/TGRS.2009.2026052  Access to full text


Mapping and monitoring changes in the distribution of cropland provides information that aids sustainable approaches to agriculture and supports early warning of threats to global and regional food security. This study tested the capability of PALSAR multi-polarization and polarimetric data for crop classification. L-Band results were compared with those achieved with a C-Band SAR data set (ASAR and RADARSAT-1), an integrated C- and L-Band data set, and a multi-temporal optical data set. Using all L-Band linear polarizations corn, soybeans, cereals and hay-pasture were classified to an overall accuracy of 70%. A more temporally-rich C-Band data set provided an accuracy of 80%. Larger biomass crops were well classified using the PALSAR data. C-Band data were needed to accurately classify low biomass crops. With a multi-frequency data set an overall accuracy of 88.7% was reached, and many individual crops were classified to accuracies better than 90%. These results were competitive with the overall accuracy achieved using three Landsat images (88.0%). L-Band parameters derived from three decomposition approaches (Cloude-Pottier, Freeman-Durden and Krogager) produced superior crop classification accuracies relative to those achieved using the linear polarizations. Using the Krogager decomposition parameters from all three PALSAR acquisitions, an overall accuracy of 77.2% was achieved. Results reported in this study emphasize the value of polarimetric as well as multi-frequency SAR data for crop classification. With such a diverse capability, a SAR-only approach to crop classification becomes increasingly viable.

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