Paper
19 October 2005 Crop discrimination on ENVISAT ASAR images acquired in alternating polarization mode
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Abstract
The objective of this study is to find an efficient method of crop classification based solely on satellite microwave data. Microwave data can sometimes be the only non-contaminated satellite data available for a selected area, where frequent cloudiness makes optical data useless. Hence, this approach has to be studied at least as an alternative method for application when other data are missing. Although ASAR is not a fully polarimetric instrument, a selection of dual polarization modes and a selection of incidence angles are available when using ASAR alternating polarization product (APP). Larger incidence angle and cross-polarized data are better for crop discrimination, while lower incidence angle and co-polarized data contain more information on soil moisture. In the years 2003 and 2004 a sequence of ASAR IS2, IS4 and IS6 images acquired during a growth season was analyzed. Supervised classification of ASAR APP was performed with ground truth data collected for 700 plots covered by homogeneous crops. For growth seasons of 2003 and 2004 various combination of images were tested in order to find the best set of data providing the highest accuracy of crop classification.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Krystyna A. Stankiewicz "Crop discrimination on ENVISAT ASAR images acquired in alternating polarization mode", Proc. SPIE 5976, Remote Sensing for Agriculture, Ecosystems, and Hydrology VII, 597615 (19 October 2005); https://doi.org/10.1117/12.634715
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Cited by 1 scholarly publication.
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KEYWORDS
Polarization

Image classification

Microwave radiation

Satellites

Satellite imaging

Image segmentation

Neural networks

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