TY - GEN
T1 - Paddy rice field extraction using ALOS-2 PALSAR-2 full polarimetric data with agricultural parcel vector data
AU - Yonezawa, Chinatsu
N1 - Funding Information:
This research was supported by the Japan Society of Promotion of Science (JSPS) KAKENHI grant number 15K07675. Agricultural parcel data were provided by the Land Improvement Association of Miyagi Prefecture. The authors thank JAXA for providing the PALSAR-2 data as part of the ALOS user agreement (ALOS 6th RA-3054). The Landsat 8 data were downloaded from AIST's LandBrowser(https://landbrowser.airc.aist.go.jp/landbrowse r/), Landsat 8 data, courtesy of the U.S. Geological Survey.
PY - 2018/10/31
Y1 - 2018/10/31
N2 - ALOS-2 PALSAR-2 data acquired in full polarimetric mode at the rice heading and well-grown seasons were analyzed to classify agricultural areas according to their use. Eigenvalue-eigenvector and four-component decompositions were used to classify the PALSAR-2 data and discriminate different agricultural parcels. Threshold analysis was applied for the polarimetric decomposition components. Polarimetric decomposition parameters, alpha angle, double bounce scattering component ratio, and surface scattering component ratio, were applied to classify areas according to their use for paddy rice or other crops including soybean. The same threshold value used for analysis using the double bounce scattering component ratio was useful for all PALSAR-2 data analyzed in this study. However, the efficient threshold for alpha angle discrimination was different between the analyzed datasets. Differences in data observation direction, incidence angle, and the growth situation of paddy rice at observation time are conceivable reasons for this difference.
AB - ALOS-2 PALSAR-2 data acquired in full polarimetric mode at the rice heading and well-grown seasons were analyzed to classify agricultural areas according to their use. Eigenvalue-eigenvector and four-component decompositions were used to classify the PALSAR-2 data and discriminate different agricultural parcels. Threshold analysis was applied for the polarimetric decomposition components. Polarimetric decomposition parameters, alpha angle, double bounce scattering component ratio, and surface scattering component ratio, were applied to classify areas according to their use for paddy rice or other crops including soybean. The same threshold value used for analysis using the double bounce scattering component ratio was useful for all PALSAR-2 data analyzed in this study. However, the efficient threshold for alpha angle discrimination was different between the analyzed datasets. Differences in data observation direction, incidence angle, and the growth situation of paddy rice at observation time are conceivable reasons for this difference.
KW - Crop monitoring
KW - Polarimetric decomposition
KW - Synthetic aperture radar
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U2 - 10.1109/IGARSS.2018.8517291
DO - 10.1109/IGARSS.2018.8517291
M3 - Conference contribution
AN - SCOPUS:85063129344
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 5296
EP - 5299
BT - 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018
Y2 - 22 July 2018 through 27 July 2018
ER -