Title :
Contribution of Multi-Frequency, Multi-Sensor, and Multi-Temporal Radar Data to Operational Annual Crop Mapping
Author :
Shang, Jiali ; McNairn, Heather ; Champagne, Catherine ; Jiao, Xianfeng
Author_Institution :
Agric. & Agri-Food Canada, Ottawa, ON
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 TM, 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.
Keywords :
agriculture; crops; data acquisition; image classification; remote sensing by radar; synthetic aperture radar; vegetation mapping; AD 2004 to 2007; ASAR image acquisition; Agriculture and Agri-Food Canada; Canada; SAR-optical image; VV/VH polarization; agricultural land use; agricultural landscapes; cloud-haze interference; crop mapping; cropping systems; crops classification; inventory crops; multi-frequency radar; multi-sensor radar research; multi-temporal optical data; multi-temporal radar data; Agriculture; Clouds; Crops; Interference; Layout; Optical polarization; Remote sensing; Robustness; Satellites; Spaceborne radar; crop inventory; image classification; multi-frequency; multi-temporal; optical; radar;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International
Conference_Location :
Boston, MA
Print_ISBN :
978-1-4244-2807-6
Electronic_ISBN :
978-1-4244-2808-3
DOI :
10.1109/IGARSS.2008.4779362