The Phased-Array L-band Synthetic Aperture Radar-2 (PALSAR-2) high-pass-filtered image is compared with the Moderate Resolution Imaging Spectroradiometer (MODIS) sea surface temperature (SST) and Chlrolophyll-a (Chl-a) images. The comparison shows that the positions of line-shaped bright (ridge) patterns in the image correspond with large SST gradients, i.e., SST fronts. Moreover, the comparison with the Chl-a image represents some local Chl-a maxima along the SAR ridge patterns in the PALSAR-2 contrast image. In order to examine the relationship between the SAR line-shaped bright patterns and surface currents comprehensively, the time series of the PALSAR images are compared with the High-Frequency (HF) radar surface currents. The positions and strengths of the SAR line-shaped bright patterns generally correspond with those of current shear, suggesting a general theory that convergence areas induced by large current shear are imaged bright through the modulation of ocean surface roughness. The SAR-derived line-shaped bright pattern thus indicates current-rips (Shiome) characterized physically as the convergence of surface currents. The effect of background wind fields on the SAR line-shaped bright patterns is also investigated using the SAR-derived wind fields. It is found that the SAR line-shaped patterns are not identified under strong winds stronger than 10m/s even if the current shear is large.
We investigated the difference in cloud characteristics (fraction and thermodynamic phase) between the Barents Sea (70-80°N, 0-40°E) and East Siberian Sea (70-80°N, 120-180°E) using remote sensing data from a Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite in summer (JJA) and winter (DJF). In the Arctic region, the total cloud fraction is larger in summer than winter as a whole. The fraction of ice cloud layers between －25°and 0°C was clearly larger in the East Siberian Sea than in the Barents Sea in winter. The difference in the ice cloud fraction between the East Siberian Sea and Barents Sea was remarkable between －25°and －10°C, being about 20% greater in the East Siberian Sea in winter. The ice cloud layer fraction in the lower troposphere (under 2km) was larger in the East Siberian Sea than in the Barents Sea in winter. These results indicate that the ice formation process was promoted more in the lower troposphere in the East Siberian Sea than in the Barents Sea in winter. These are the first results obtained from observations of the cloud internal structure as viewed by the active sensor on board CALIPSO.
In mountainous areas, radiance decreases locally owing to the shade created by the topographic slope. This reduction causes paddy fields to be misclassified using satellite images. The characteristics of the radiance of paddy fields are close to those of shaded forest and grassland because paddy fields are covered with paddy and water that absorb radiance. In this study, we propose a novel method to correct the classification results using the terrain characteristics of terraced paddy fields in mountainous areas. We then applied this method to the Honghe Hani Rice Terraces in Yunnan, China. The results show that this correction method significantly improves the accuracy of paddy field classification. The kappa coefficient of the proposed method is equal to or greater than that of existing model.
A terrestrial laser scanner-based method for estimating leaf area density (LAD) distribution is examined under considering of the degree of penetration of the laser beams into the tree and the influence of wind, which can lead to errors in outdoor measurements. Two Japanese zelkova (Zelkova serrata) trees, 6m in height, were each scanned from four positions at a distance of 4.5m. To evaluate the influence of wind on the estimation accuracy of the LAD distribution, beam-transparent sheets were installed around one tree to block the wind. LAD distributions with a voxel size of 0.3m×0.3m×0.3m were estimated based on a previously developed method to calculate the contact frequency between laser beams and leaves. Two different methods for analyzing data acquired from multiple scanning positions were examined: calculating LAD from integrated data (integration method), and calculating LAD for each scanning position while adopting maximum LAD for each voxel (selection method). The estimated leaf area was compared with the area measured by stratified clipping. When the wind was blocked, the difference in estimation accuracy between the integration and selection methods was small, even though the number of incident laser beams on each voxel in the selection method was smaller than that in the integration method. The estimation errors in determining the leaf area for the upper, middle, and lower layers of the tree were within 10-15% for both methods. When the wind was not blocked and the wind speed reached 0.5m/s, LAD was overestimated by both methods, but the difference between the LAD estimated with and without shielding was within 10% in the selection method. Conversely, the LAD estimated by the integration method was 20% greater than that estimated by the selection method. These results indicate that the selection method is suitable for estimating LAD distribution in outdoor spaces.