Contribution of multi-frequency, multi-sensor, and multi-temporal radar data to operational annual crop mapping.

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 Geoscience and Remote Sensing Letters, 3(1), pp. III378-III381. doi : 10.1109/IGARSS.2008.4779362  Access to full text

Abstract

Information on agricultural land use (crop inventory) is needed by various organizations on an annual basis. To meet this operational requirement, Agriculture and Agri-Food Canada (AAFC) has carried out a multi-year (2004 - 2007), multi-sensor (Landsat ™, SPOT, RADARSAT-1, ASAR), and multi-site (five provinces: Ontario, Saskatchewan, Alberta, Manitoba, P.E.I.) research activity to develop a robust methodology to inventory crops across Canada's large and diverse agricultural landscapes. Results clearly demonstrated that multi-temporal satellite data can successfully classify crops for a variety of cropping systems across Canada. Overall accuracies of at least 85% were achieved. When available, multi-temporal (2 to 3 scenes acquired at different growth stages) optical data are ideal for crop classification. However due to cloud and haze interference, good optical data are not always obtainable. A SAR-optical combination offers a good alternative. This research has found that when only one optical image is available, the addition of two ASAR images acquired in VV/VH polarization will provide acceptable accuracies. Of particular interest is the observation that with the incorporation of radar, crop inventories can be delivered earlier in the growing season.

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