This paper summarizes an operational calibration result of the Advanced Land Observing Satellites-2 (ALOS-2, nicknamed "DAICHI-2"). ALOS-2, the successor to the Phased Array-type L-band Synthetic Aperture Radar (PALSAR) onboarded ALOS "DAICHI" from 2006 to 2011, was launched in 2014 and has been operating smoothly beyond its design mission life of 7 years; the PALSAR-2 onboard ALOS-2 has shown its maximum contribution in practical applications by the basic observations of global land areas with time-series high resolution, and in emergency observations during natural disasters. The observation capability of PALSAR-2 has been improved over PALSAR e.g., a finer spatial resolution of 1 x 3m by the Spotlight observing mode, a wider swath width of 490 km by the ScanSAR mode, and a right-and-left looking function. To take full advantage of these capabilities, sensor calibration is extremely important. This paper reports the latest operational calibration result of PALSAR-2 during more than 9 years of its mission operation period.

Ionospheric total electron content (TEC) can significantly affect the range geometric accuracy of spaceborne L-band synthetic aperture radar (SAR) data. This study aims to estimate the ionospheric TEC from single spaceborne L-band SAR data based on the concept of the split-spectrum method. We estimated the SAR-based TEC from the range misregistration between lower- and higher-range spectral split-band amplitude images acquired using the Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) onboard the Advanced Land Observing Satellite-2 (ALOS-2). A comparison of the SAR-based TEC with the TEC observed by the Global Navigation Satellite System showed a linear relationship with a slope of 0.76 after correcting for offsets in the estimated value. This slope seemingly represents the ionospheric TEC ratio below the ALOS-2 orbit. Correcting the ionospheric range delay in PALSAR-2 data with the SAR-based TEC estimates improved the slant range accuracy from 2.67 m to 0.77 m.

Ionospheric path delay (IPD) correction methods for creating an ortho-rectification product of L-band SAR were examined using the Phased Array type L-band Synthetic Aperture Rader-2 (PALSAR-2). Slant range correction values for the IPD were estimated using two methods. First one is coregistration between a radar geometry simulated image created using digital surface model (DSM) and a SAR amplitude image. Second one is using a total electron content (TEC) map. The geometric accuracy of the ortho products created using each correction was evaluated. The TEC map correction improved the geometric accuracy, while the coregistration one decreased. The individual slant-range shifts calculated by the co-registration showed a relationship with forest canopy height. The reason why the error increased in the co-registration correction is inferred that a false slant range shift is created due to the height difference between the scattering center point of the L-band SAR and the DSM in the forest, which results in adding an error to the slant-range correction value.

This study investigated the geometric errors in L-band synthetic aperture radar (SAR) caused by the effects of the ionosphere and troposphere based on observational evidence derived from the Phased Array type L-band SAR-2 (PALSAR-2) onboard the Advanced Land Observing Satellite-2 (ALOS-2) data, which were obtained by calibration and validation works, and external numerical data. First, the ionospheric path delay (IPD) and the tropospheric path delay (TPD) on PALSAR-2 data were estimated. The results revealed that the zenith IPD ranges from approximately 1 m to 12 m, according to the observation period, due to the solar activity cycle. In contrast, the zenith TPD ranges from 2.30 m to 2.75 m depending on the seasonal variation. Next, the slant-range error of PALSAR-2 with the slant IPD and the slant TPD were compared to investigate the relationships between them. These relationships indicated a strong correlation between the slant-range error of L-band SAR and the slant IPD, whereas the correlation with the slant TPD was not confirmed. This result suggests that the effect of the ionosphere could be the significant error factor in the L-band SAR geometric accuracy. Finally, the effective geometric accuracy of PALSAR-2 was simulated by removing the IPD and TPD. As a result, the standard deviation of the slant-range error was reduced from 2.709 m to 1.206 m, and a bias of −5.288 m remained.

The relationship between hurricane sea surface wind speed and L-band$\sigma^{0}$is investigated to enable wind estimation under extreme wind condition based on four the Phased Array type L-band Synthetic Aperture Rader-2 (PALSAR-2) hurricane images and wind speed simultaneously measured by National Oceanic and Atmospheric Administration (NOAA)'s airborne Stepped Frequency Microwave Radiometer (SFMR). It was confirmed that HV$\sigma^{0}$has a little dependence on the incidence angle and tends to increase without saturation at least up to 55 m/s and an L-band HV geophysical model function (GMF) is constructed using match-ups between HV$\sigma^{0}$and SFMR wind speed. A comparison between the PALSAR-2-derived and SFMR-measured wind speeds reveals a −0.2m/s bias and 4.1m/s root mean square error (RMSE). The calculated wind speed structure shows the asymmetry wind speed radii which is almost consistent with the best track data.

We investigated L-band cross-polarized normalized radar cross section (NRCS) dependence on ocean surface wind for wind speed retrieval. Because it has been reported that the L-band HV NRCS significantly changes due to the Faraday rotation (FR), analysis was conducted on observed NRCS with less influence of FR. About 50,000 match-ups, each consisting of the L-band NRCS, incidence angles, wind speeds and wind directions, were collected from the Phased- Array L-band Synthetic Aperture Radar-2 (PALSAR-2) and scatterometer wind vectors. Based on the match-ups, the L- band HH NRCS dependence on incidence angle and wind vector is modeled for 25 to 40° incidence angles. The derived relation indicates that the wind sensitivity of the L-band HV NRCS is almost equivalent to that of the HH one. Wind speeds are then estimated from the match-ups, based on the derived model function. A comparison with the reference scatterometer winds reveals a 0.37m/s bias and 2.9m/s root mean square (RMS) error.

The relationship between ocean wind vectors and L-band normalized radar cross sections (NRCS) is examined to modify the L-band geophysical model function (GMF) using the Phased-Array L-band Synthetic Aperture Radar 2 (PALSAR-2) and scatterometer wind data. Since the PALSAR-2 has a function of dual polarized ScanSAR, the sensitivity of L-band HV on wind fields is examined. Though the HV signal shows wind speed and incidence angle dependencies, they are too noisy to be used for wind detection. In order to seek the possible cause, the L-band NRCS is compared with Faraday rotation (FR) angle, indicating a clear positive relationship between the HV NRCSs and with the FR angle. The HH/HV ratio from the PALSAR-2 observation is compared with theoretical ones calculated from FR angle. The observation and theory correspond in terms of the tendency that the HH/HV decreases with increasing the FR angle and its sensitivity decreases with incidence angle. On the other hand, the decreasing ratio of the observation exceeds the theoretical one resulting in increasing discrepancy with the FR angle. Since the HH NRCS is not significantly affected by FR, the L-band HH GMF is modified in order to cover the wider incidence angle ranges from 17° to 50°. Based on the derived GMF, wind speeds are estimated and compared with the buoy-measured winds. The comparison shows the -0.75 m/s bias and 2.07 m/s root mean square (rms) error.

This paper reports the result of over 3 years routine calibration and validation works for the Phased Array type L-band Synthetic Aperture Radar-2 (P ALSAR-2) onboard the Advanced Land Observing Satellite-2 (ALOS-2). The major observation modes and beams were evaluated, and we confirmed that the PALSAR-2 product satisfy its specification over 3 years: absolute radiometric accuracy is less than 0.5 dB, geometric accuracy is less than 10 meters (RMS), and polarimetric calibration was successfully conducted.

The PALSAR/PALSAR-2 contrast images are compared with the MODIS SST and Chl-a images. The comparison shows that the positions of line-shaped bright (ridge) patterns in the contrast images 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, suggesting a general theory that convergence areas induced by large current shear are imaged bright through the modulation of ocean surface roughness. In order to examine this imaging mechanism, time series of the PALSAR images are compared with the High-Frequency (HF) radar surface currents. The positions and strengths of the SAR front patterns generally correspond with those of strong current shears. The effect of background wind fields on the SAR front patterns are also investigated using the SAR-derived wind fields. The result suggests that relatively strong wind (>10m/s) makes the SAR ridge pattern unclear.

The relationship between ocean wind vectors and L-band normalized radar cross sections (NRCS) is examined to modify the L-band geophysical model function (GMF) using the Phased-Array L-band Synthetic Aperture Radar 2 (PALSAR-2) and scatterometer wind data. The difference between the present study and previous one using the PALSAR is incidence angle range and polarimetry. Since the PALSAR-2 has a function of dual polarized ScanSAR, the sensitivity of L-band HV on wind fields is also examined. Though the HV signal shows wind speed and incidence angle dependencies, they are too noisy to be used for wind detection. Based on more than 20,000 match-ups, the L-band HH NRCS dependence on wind speed, incidence angle, and relative wind direction is modeled for the 0-20 m/s wind speed range. Wind speeds are then inversely estimated from the mutch-ups and compared with the reference winds. The accuracy shows incidence-angle-dependency. The detection at the lowest incidence angles of 25-30 degrees gets the best result, the 0.23 m/s bias and 2.33 m/s root mean square (rms) error.

We investigated the relationship between HH and HV gamma naught values by PALSAR and biomass of Japanese natural forest (44 sites) to develop an effective retrieval algorithm of forest above ground biomass by using PALSAR data. As same as previous studies, our results showed a positive logarithmic relationship between PALSAR gamma naught and in situ forest biomass. HV polarized data showed smaller RMSE and higher saturation level than HH data. The results also showed that slope corrected PALSAR data had much smaller RMSE than the non-corrected data.

The Japan Aerospace Exploration Agency (JAXA) has produced the world's first 10m resolution L-band SAR global mosaic datasets. These data sets were generated to monitor forest changes from the 1990s to present. SRTM-3 (90m resolution) DEM was used to correct the terrain-induced SAR intensity variations and the ortho-rectification. Both corrections were applied for geometric and radiometric calibration purposes. The data sets are useful to monitor the temporal forest cover and forest change, and were used to derive forest/non-forest information.

From its launch in 2006, the phased array L-band synthetic aperture radar (PALSAR) onboard the advanced land observing satellite (ALOS) has acquired many dual-polarized (FBD) images with a 70-km swath width, aiming to produce spatially consistent coverage over tropical rainforest. This paper investigates the relevancy of PALSAR orthorectified FBD product at 50-m resolution for regional land cover classification by the support vector machines (SVM). Our test site is the Riau province, Sumatra island, Indonesia, known to hold vast area of natural peatland forest with an extreme biodiversity threatened by industrial deforestation. Since it is demonstrated the radiometric information (HH and HV channels) cannot be solely used to achieve a good classification, the spatial information in these orthorectified data is investigated. A new tool using the recursive feature elimination SVM-based process and the textural Haralick's parameters is introduced. The real contribution of textures within the land cover classification can be understood. A small set of textural parameters is determined at local scale while being optimal for the land cover discrimination. The SVM-based classifier is carried out across the whole Riau province and its results are compared with a Landsat-based estimation. The agreement is over 70% with six classes and 86% for the natural forest map. These results are remarkable since only one PALSAR FBD product is used and this assessment is performed on more than 40 million pixels. The results confirm the high potential of the PALSAR sensor for forest monitoring at regional, if not global scale.

This study investigates a new technique for land cover analysis by means of the Support Vector Machines. Intrinsic spatial variability within SAR images, beyond that caused by speckle, is of high interest for land cover characterization and classification. However, its use is still an ongoing issue due to its complex multi-scale nature. On the other hand, classification algorithms based on statistical learning methods such as the supervised Support Vector Machines (SVM) approach are implemented in a wide range of data mining applications. SVM can also be used as a technique for feature selection. In this paper, a new tool using the Recursive Feature Elimination SVM-based process (SVM-RFE) and the textural Haralick's parameters is introduced. The real contribution of textures within the land cover classification can be understood. A small set of textural parameters is determined at local scale while being optimal for the land cover discrimination. In this study, orthorectified 50m resolution data acquired by the L-band PALSAR/ALOS sensor are used.

PALSAR orthorectified HH and HV produced at 50m resolution is used for analysis. Since only two bands (HH and HV) have been limited in land cover discrimination, textures have been used as additional information for classification. This research derives second-order textures at different spatial resolutions and compares second-order textures at multiple scales to demonstrate their contributions in land cover classification. The discriminating capability of texture features is derived by the transformed divergence on several selected regions of interest. Optimum combination of backscattering and textures are used as input data into a supervised multi-resolution maximum likelihood classification. It is found that by including the texture information, the overall classification accuracy is improved by 10%.

An L-band normalized radar cross section (NRCS) characteristic derived from the Phased Array L-band Synthetic Aperture Radar (PALSAR) 50-m resolution dual-polarization mosaic and the land cover database in Riau province, Sumatra Island, represent that HV signals of natural forests are 2-3 dB larger than those of cleared and many plantations, indicating the usefulness of HV measurements for the detection of new deforestation. The 2007 and 2008 mosaic series, in fact, elucidates 3dB decreases in the HV channel for major deforested areas. On the other hand, HH shows no significant changes. 46-day repeat ScanSAR observations clarify common HH signal changes for the deforestation: they once increase departing from the annual cycle of natural forests and reach a peak in a rainy season. The result suggests the availability of the ScanSAR-derived HH time series for near-real-time deforestation monitoring. A HH signal variation on an acacia plantation cycle represents a similar characteristic to that for the deforestation: HH anomalously increases during the subsequent rainy season after the plantation. The increase level depends on an incidence angle, suggesting the dominance of surface scattering component over young acacia areas. With analogy with deforestations, it is suggested that the incidence angle dependency seems to be considered for the deforestation monitoring by ScanSAR.

In this study an electromagnetic approach is proposed for exploiting polarimetric information for sea oil slick observation in L-band ALOS PALSAR full polarimetric SAR data. The problem is tackled form an electromagnetic viewpoint by describing the sea surface scattering mechanism with and without oil slicks. Following this rationale, a filtering technique, based on the Mueller scattering matrix, is applied to detect oil slicks in full polarimetric SAR data. Successively, the filtering results are verified by the analysis of the slick-free and slick-covered pedestal height and polarimetric entropy (H). Experiments, accomplished on a meaningful set of Level 1.1 L-Band ALOS PALSAR full polarimetric data, demonstrate the effectiveness of the proposed approach.

This paper describes the updated results of the PALSAR CALVAL activity conducted for last three years using the PALSAR calibration archives and the connected ground truth data. The results show that PALSAR has pretty good stabilities on the geometric and radiometric accuracies. Using PALSAR data, change detection on the forest in Indonesia and the polar regions (North Pole region, Antarctica region, and Greenland region) are in progress tracking the change of the sigma-naught and/or the phases.

This paper examines L-band normalized radar cross section (NRCS) dependence on ocean surface wind. More than 90 000 match-ups, each consisting of the L-band HH NRCS, incidence angles, wind speeds, and wind directions, were collected from the Phased-Array L-Band Synthetic Aperture Radar (PALSAR) and scatterometer wind vectors. Based on the match-ups, the L-band HH NRCS dependence on incidence angle and wind vector is modeled for 0-20-m/s wind speeds and 17deg-43deg incidence angles. The derived relation indicates that the wind sensitivity of the L-band NRCS is less than that of the C-band at moderate winds and large incidence angles, whereas comparable at stronger winds ((>10 m/s) and small incidence angles. The upwind-crosswind difference is amplified in the 10-15-m/s range followed by an almost zero amplitude from 4 to 8 m/s, which represents a clear phase shift with the C-band VV and Ku-band HH models. Wind speeds are then estimated from the match-ups, based on the derived model function. A comparison with the reference scatterometer winds reveals a 0.05-m/s bias and a 1.85-m/s root mean square error, where crosswind data give rise to large errors due to low wind sensitivity at wind speeds of around 10 m/s, particularly at large incidence angles. The L-band NRCS behavior in strong winds (>20 m/s), at which the C-band is saturated, was not determined in the current model due to the limited number of the match-ups.

A study on sea oil slick observation by means of L-band polarimetric synthetic aperture radar (SAR) data is accomplished. It is based on different sea surface scattering mechanism expected with and without surface slicks. Polarimetric measurements are processed by means of a simple and very effective filtering technique which is electromagnetically based on the Mueller scattering matrix. Moreover, some polarimetric features, evaluated on both slick-free and slick-covered sea surfaces, are analyzed for confirming the filter output. Experiments are accomplished on the polarimetric SAR data acquired by the Phased Array-type L-band Synthetic Aperture Radar (PALSAR) sensor, mounted on board of the Advanced Land Observing Satellite (ALOS), and are relevant to oil slick, due to a tank accident, and look-alikes. Results demonstrate for the first time that L-band polarimetric SAR measurements are useful for oil slick observation purposes and witness the capability of the ALOS PALSAR data for such application.

This paper summarizes the results obtained from geometric and radiometric calibrations of the Phased-Array L-Band Synthetic Aperture Radar (PALSAR) on the Advanced Land Observing Satellite, which has been in space for three years. All of the imaging modes of the PALSAR, i.e., single, dual, and full polarimetric strip modes and scanning synthetic aperture radar (SCANSAR), were calibrated and validated using a total of 572 calibration points collected worldwide and distributed targets selected primarily from the Amazon forest. Through raw-data characterization, antenna-pattern estimation using the distributed target data, and polarimetric calibration using the Faraday rotation-free area in the Amazon, we performed the PALSAR radiometric and geometric calibrations and confirmed that the geometric accuracy of the strip mode is 9.7-m root mean square (rms), the geometric accuracy of SCANSAR is 70 m, and the radiometric accuracy is 0.76 dB from a corner-reflector analysis and 0.22 dB from the Amazon data analysis (standard deviation). Polarimetric calibration was successful, resulting in a VV/HH amplitude balance of 1.013 (0.0561 dB) with a standard deviation of 0.062 and a phase balance of 0.612deg with a standard deviation of 2.66deg .

Polarization dependence of L-band measurements over the ocean on surface wind is investigated for the incidence angle ranging from 23 to 25 degrees, by using the Phased-Array L-band Synthetic Aperture Radar (PALSAR) onboard the Advanced Land Observing Satellite (ALOS) and MetOp/ASCAT wind vectors. Polarization ratio (VV/HH) shows clear incidence angle and wind speed dependencies. It increases with increasing incidence angle and decreases with wind speed, ranging from 1.8 dB at 2 m/s wind to 0.5 dB at strong wind >12 m/s. These dependences are in good quantitative agreement with the Resonant Curvature Approximation (RCA) model proposed by Mouche et al. (2007). Although relative wind direction dependency of the polarization ratio is not so significant, downwind values are larger than cross- and upwind values at strong winds >12 m/s.

ALOS/PALSAR has been on the orbit since January 24 2006. After the initial calibration phase, the PALSAR has been being used as the calibrated instrument for the land monitoring. Using the calibration target data of the corner reflectors and the distributed target, it has been confirmed that the PALSAR is well stabilized and calibrated. One of the two major themes that the PALSAR can contribute to, the forest monitoring, is being progressed. The creation of the 50-meter orthorectified multi polarization mosaic, the major part of the providing products, is being generated at Kyoto and Carbon project. Here, the JAXA's contribution, the generation of the Asia SAR mosaic data, is in progress. This paper introduces the PALSAR CALVAL updated information and the quality of the PALSAR ortho-mosaic.

The relationship between ocean wind vectors and L-band normalized radar cross sections (NRCS) is examined using the Phased-Array L-band Synthetic Aperture Radar (PALSAR). We used PALSAR ScanSAR images with a wide range of incidence angles from 17deg to 43deg. More than 6,000 match-ups, each consisting of the NRCS, incidence angles, wind speeds and wind directions, were collected. The NRCS exhibits a power-law relationship with respect to the wind speed. The coefficients of the power law can be derived as a function of the incidence angles. Based on this relation, the wind speeds are then inversely estimated from the NRCS and the incidence angles. A comparison with the truth winds reveals -0.23 m/s bias and 2.63 m/s rms error, demonstrating the feasibility of L-band scatterometry. Collecting more match-ups and further considering wind- direction dependence, which was not included in this study, would lead to the derivation of a robust L-band model function.

Cold eddy streets formed in the lee of isolated islands were investigated in relation to the Kuroshio current. Multi- temporal SAR images acquired over a one-month period revealed island wake patterns, such as meandering disturbances and eddy streets. These patterns corresponded to the Kuroshio path, indicating a Kuroshio-island interaction. We constructed high-spatial-resolution sea-surface temperature (SST) images for the time when the Kuroshio impinged on the islands by regressing the LANDSAT infrared images on the AVHRR-derived SST. The images revealed low-SST island wakes, some of which included cold eddy streets. A numerical simulation was performed to investigate their formation mechanism. The simulation qualitatively reproduced the cold eddy pattern, with eddy-driven mixing developing a mixed layer down to 100 m, causing the low- SST island wakes. The shedding frequency and distance of the model-produced eddies were close to those of the Karman vortex theory, suggesting that Karman-like cold eddy streets developed behind the islands when the Kuroshio passed.

This paper summarizes the geometric and radiometric calibration results of the PALSAR achieved during the ALOS initial calibration phase, which covers five months between May 16 2006 and October 23, 2006, and the half-year of the operational phase. All the PALSAR modes, FBS (fine beam single), FBD (Fine beam dual), SCANSAR, DSN (band limited SAR), and POL (Full polarimetry) were calibrated and validated using in-total 500 calibration points collected world widely and distributed target data from the Amazon. Through the characterization of the PALSAR, antenna pattern determination, and polarimetric calibration, we performed the adjustments of the PALSAR radiometric and geometric model installed on the SAR processor (SIGMA-SAR). Using the reference points, we finally confirmed that the geometric accuracy of the FBS, FBD, DSN, and POL modes is 9.3 m, that of SCANSAR is 70 m, and radiometric accuracy is 0.64 dB. Polarimetric calibration was successful that amplitude balance of VV/HH is 0.025 dB and the phase balance is 0.32 degrees.

Suttu, which is located in the western Hokkaido, is known to be the 4thstrongest windy place in Japan, where topographical gaps efficiently develop strong winds. These gap winds over the ocean and their effects on sea surface temperature (SST) fields are investigated by scatterometer- and synthetic aperture radar (SAR)-observed wind fields and the Advanced Very High Resolution Radiometer (AVHRR)-derived SST data. The SAR wind field observed by a wide-swath ScanSAR mode reveals a series of wind jet/wake patterns, which correspond to upstream land topography. The strong jets extend offshore over 100 km. It is found by several SAR-derived wind fields that these gap winds develop under the condition of upstream easterly winds. The easterly winds are common in spring and summer, which are known as the Yamase phenomena in northern Japan. Low/high SST patterns, which correspond to the jet/wake, are frequently observed off the western Hokkaido coasts in summertime. We create a composite image of the SST spatial anomalies for windy days, based oninsituwind measurements in Suttu. The composite image shows well-defined local SST cooling/warming stripes along general wind jet/wake regions. These are probably induced by the difference of the diurnal warming amplitude.

Wind fields are modified drastically in the coastal zone and have a large impact on human activities such as sea traffic and leisure, so that understanding of coastal wind fields is required. Synthetic Aperture Radar (SAR) is a unique tool, which can detect a wind speed map in near-coastal areas. Recently our group has established the L-band model function by comparing huge SAR-measured NRCS derived from JERS- 1/SAR with buoy and scatterometer-estimated winds. It, however, does not take account of incidence angle dependency due to constrain of the JERS-1 operation. Authors plan to develop the L-band model function with the incidence angle dependency by acquiring ALOS/PALSAR data by design. The improved model function will be useful for radiometric calibration of future L-band SAR as well as PALSAR.