TY - JOUR
T1 - Analysis of the applicability of multi-temporal full polarimetric airborne L-band SAR scattering to paddy rice field mapping
AU - Yonezawa, Chinatsu
AU - Watanabe, Manabu
N1 - Funding Information:
This research was supported by Japan Society for the Promotion of Science (JSPS) KAKENHI grant number 15K07675. Agricultural parcel data were provided by the Ministry of Agriculture, Forestry, and Fisheries, Japan. The authors thank JAXA for providing the Pi-SAR-L2 data as part of the ALOS user agreement (ALOS 5th-RA-2048). ASTER-VA images were courtesy of NASA/METI/AIST/Japan Spacesystems, and the U.S./Japan ASTER Science Team. Landsat 7 and 8 data were courtesy of the U.S. Geological Survey.
Funding Information:
This research was supported by Japan Society for the Promotion of Science (JSPS) KAKENHI grant number 15K07675. Agricultural parcel data were provided by the Ministry of Agriculture, Forestry, and Fisheries, Japan. The authors thank JAXA for providing the Pi-SAR-L2 data as part of the ALOS user agreement (ALOS 5th-RA-2048). ASTER-VA images were courtesy of NASA/METI/AIST/Japan Spacesystems, and the U.S./Japan ASTER Science Team. Landsat 7 and 8 data were courtesy of the U.S. Geological Survey.
Publisher Copyright:
© 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2020/4/2
Y1 - 2020/4/2
N2 - A Synthetic Aperture Radar (SAR) is an all-weather imaging system that is often used for mapping paddy rice fields and estimating the area. Fully polarimetric SAR is used to detect the microwave scattering property. In this study, a simple threshold analysis of fully polarimetric L-band SAR data was conducted to distinguish paddy rice fields from soybean and other fields. We analysed a set of ten airborne SAR L-band 2 (Pi-SAR-L2) images obtained during the paddy rice growing season (in June, August, and September) from 2012 to 2014 using polarimetric decomposition. Vector data for agricultural land use areas were overlaid on the analysed images and the mean value for each agricultural parcel computed. By quantitatively comparing our data with a reference dataset generated from optical sensor images, effective polarimetric parameters and the ideal observation season were revealed. Double bounce scattering and surface scattering component ratios, derived using a four-component decomposition algorithm, were key to extracting paddy rice fields when the plant stems are vertical with respect to the ground. The alpha angle was also an effective factor for extracting rice fields from an agricultural area. The data obtained during August show maximum agreement with the reference dataset of estimated paddy rice field areas.
AB - A Synthetic Aperture Radar (SAR) is an all-weather imaging system that is often used for mapping paddy rice fields and estimating the area. Fully polarimetric SAR is used to detect the microwave scattering property. In this study, a simple threshold analysis of fully polarimetric L-band SAR data was conducted to distinguish paddy rice fields from soybean and other fields. We analysed a set of ten airborne SAR L-band 2 (Pi-SAR-L2) images obtained during the paddy rice growing season (in June, August, and September) from 2012 to 2014 using polarimetric decomposition. Vector data for agricultural land use areas were overlaid on the analysed images and the mean value for each agricultural parcel computed. By quantitatively comparing our data with a reference dataset generated from optical sensor images, effective polarimetric parameters and the ideal observation season were revealed. Double bounce scattering and surface scattering component ratios, derived using a four-component decomposition algorithm, were key to extracting paddy rice fields when the plant stems are vertical with respect to the ground. The alpha angle was also an effective factor for extracting rice fields from an agricultural area. The data obtained during August show maximum agreement with the reference dataset of estimated paddy rice field areas.
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U2 - 10.1080/01431161.2019.1693074
DO - 10.1080/01431161.2019.1693074
M3 - Article
AN - SCOPUS:85075396688
SN - 0143-1161
VL - 41
SP - 2500
EP - 2516
JO - International Journal of Remote Sensing
JF - International Journal of Remote Sensing
IS - 7
ER -
