DocumentCode :
143082
Title :
Integration of optical and polarimetric SAR imagery for locally accurate crop classification
Author :
Cheng Qiao ; Daneshfar, Bahram ; Davidson, Andrew ; Jarvis, Ian ; Tianyu Liu ; Fisette, Thierry
Author_Institution :
Geomatics & Earth Obs. Div., Agric. & Agri-Food Canada, Ottawa, ON, Canada
fYear :
2014
fDate :
13-18 July 2014
Firstpage :
1485
Lastpage :
1488
Abstract :
This research aims to find the best selection of imagery (optical and polarimetric radar) and methodology for very accurate and operational crop classification that could be used as a replacement for direct field observations and annual monitoring. We use RapidEye imagery as the optical source and RADARSAT-2 imagery as the Synthetic Aperture Radar (SAR) source. Both Dual polarization (Dual-pol) and Quad polarization (Quad-pol) imagery are used in this research. Optical, polarimetric SAR and the integration of both optical and polarimetric SAR images are tested for crop classification. Results show that the integration works better than single source of imagery, and Quad-pol outweigh Dual-pol in the integration with RE, especially for cereals, pasture and soybeans.
Keywords :
crops; geophysical image processing; optical images; radar imaging; radar polarimetry; remote sensing by radar; synthetic aperture radar; vegetation mapping; RADARSAT-2 imagery; RapidEye imagery; cereals; direct field observations; dual polarization imagery; locally accurate crop classification; operational crop classification; optical imagery; optical source; pasture; polarimetric SAR imagery; quadpolarization imagery; soybeans; synthetic aperture radar source; Accuracy; Adaptive optics; Agriculture; Integrated optics; Optical imaging; Optical sensors; Synthetic aperture radar; Crop classification; RADARSAT-2; RapidEye; decomposition; polarimetric SAR;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
Conference_Location :
Quebec City, QC
Type :
conf
DOI :
10.1109/IGARSS.2014.6946718
Filename :
6946718
Link To Document :
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