PALSAR-2全偏波観測データによる十分に生育した水稲作付圃場の抽出可能性

抄録

The estimation of paddy rice field areas is an important application of satellite remote sensing in agricultural research. Polarimetric data are useful in this regard and can be obtained from the PALSAR-2 L-band synthetic aperture radar (SAR) system aboard the ALOS-2 satellite. In this study, PALSAR-2 data acquired in the full polarimetric mode during the maturation season of rice were analyzed in order to classify agricultural areas according to their use for paddy rice and other crops, such as soybeans. Eigenvalue-eigenvector and four-component decompositions were used to classify the PALSAR-2 data and discriminate between different agricultural parcels. Vector data for agricultural land-use areas were overlaid on the analyzed images, and the mean value for each agricultural parcel was computed. Landsat 8 OLI images obtained during flooding and heading times of paddy rice fields were also analyzed in order to extract paddy rice agricultural parcels. A quantitative comparison of the classification results made it possible to determine the most efficient decomposition components for discriminating paddy rice fields from fields of other crops: alpha angle, double bounce scattering component ratio, and surface scattering component ratio. Mature paddy rice plants cause linear dipole scattering, which allows differentiation between paddy rice and other crops. The spatial distribution maps of these parameters’ threshold values corresponded well with the Landsat 8 OLI analysis results. For example, a comparison of the alpha angle classification with the Landsat data resulted in differences of 1.8 % and 1.6 % in field number and area, respectively. One advantage of full polarimetric data analysis is the usefulness of one-time observation data for paddy field extraction. This study’s results prove the usefulness of PALSAR-2 full polarimetric data in discriminating full-grown paddy rice fields from fields of soybeans and other crops.