Osamu Isoguchi

PALSAR Radiometric and Geometric Calibration

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 .

The PALSAR Polarimetric Mode for Sea Oil Slick Observation

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.

An L-Band Ocean Geophysical Model Function Derived From PALSAR

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 wind‐driven circulation in the subarctic North Pacific using TOPEX/POSEIDON altimeter data

Time-dependent wind-driven circulation in the subarctic region in the North Pacific is investigated by using TOPEX/POSEIDON (T/P) altimeter data and European Centre for Medium-Range Weather Forecasts (ECMWF) wind data for about 2 years. The first empirical orthogonal function (EOF) of the sea level anomaly (SLA) without the variation related to the steric height change (SLA*) represents a basin-sized oscillation, which is associated with the spin-up and spin-down of the subarctic gyre. Moreover, the time series of the first EOF corresponds to the Oyashio current variation measured by the moored current meter at about 1250-m depth. The first and third EOFs of the wind stress curl fields represent basin-sized south-north oscillations being associated with changes in intensity and the latitudinal position of the Aleutian low. Time series of both the dominant EOFs of the SLA* and the wind stress curl anomaly are correlated well, which suggests that dominant variation of the SLA* is mainly controlled by the wind stress curl fields represented by the first and third EOFs. The time series of the first EOF of the SLA* is in agreement with that of Sverdrup transport estimated by the wind stress curl near 40°N with a correlation of 0.70. Both standard deviations of the T/P SLA-derived transports in the interior and the western boundary regions are consistent with that of the Sverdrup transport in the same order of magnitude. These results suggest that sea surface height variation in the subarctic North Pacific is approximately explained by the time-dependent wind-driven circulation.

Assessment of ALOS PALSAR 50 m Orthorectified FBD Data for Regional Land Cover Classification by Support Vector Machines

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 Haralicks 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.

JERS-1 SAR mosaics of Southeast Asia using calibrated path images

We have produced a continent-scale, high-resolution radar mosaic of Southeast Asia using L-band Synthetic Aperture Radar (SAR) data collected by Japanese Earth Resources Satellite-1 (JERS-1). This 100 m resolution, 16-bit mosaic dataset of the backscattering coefficients has a calibration accuracy of 1.1 dB, geometric accuracy of 406 m, and an image quality similar to those of Amazon and central Africa previously produced by NASA Jet Propulsion Laboratory (JPL) and the Joint Research Center (JRC) of the European Commission (EC). This dataset may be beneficial in Earth observation research, especially for forest monitoring, because the L-band signal is sensitive to forest characteristics. This paper introduces a new mosaicking method that was developed to assemble the SAR path images into a large-scale mosaic, a way to recalibrate the radiometric imbalance across paths, and the validation.

Seasonal phytoplankton blooms associated with monsoonal influences and coastal environments in the sea areas either side of the Indochina Peninsula

The Gulf of Thailand (GoT) is a semienclosed sea on the west and southwest side of the Indochina Peninsula and connects with the near-coastal waters of the South China Sea (SCS) on the east and northeast side of the Malay Peninsula. The objective of the present study is to understand dynamic features of the phytoplankton biology in the GoT and the nearby SCS, on both sides of the Indochina Peninsula, using remote-sensing measurements of chlorophyll-a (Ch1 a), sea surface temperature (SST), and surface vector winds obtained during the period from September 1997 to March 2003. Results show that seasonal variations of the phytoplankton blooms are primarily controlled by the monsoonal winds and related coastal environments. The GoT and the near-coastal SCS have a peak in the averaged monthly Ch1 a in December and January, which is associated with the winter northeaster monsoon. The near-coastal SCS have another big peak in the averaged monthly Ch1 a in summer (July to September), which is associated with the summer southwest monsoon. The offshore bloom in the GoT occurs in its southern part and enhances the December-January peak of averaged monthly Ch1 a. By contrast, the offshore bloom in the nearby SCS is observed northeast of the Peninsula, and represents the primary source of the July-September peak Ch1 a. Here the coastal upwelling associated with the offshore Ekman transport caused by the coastal surface winds parallel to the Vietnam east coast gives physical conditions favorable to the development of offshore phytoplankton blooms. The Mekong River discharge waters flow in different directions, depending on the monsoon winds, and contributes to seasonal blooms on both sides of the Peninsula.

PALSAR CALVAL summary and update 2007

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.

Using multiscale texture information from ALOS PALSAR to map tropical forest

This research investigated the ability of the Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) to map tropical forest in central Sumatra, Indonesia. The study used PALSAR 50 m resolution orthorectified HH and HV data. As land-cover discrimination is difficult with only two bands (HH and HV), we added textures as additional information for classification. We calculated both first- and second-order texture features and studied the effects of texture window size, quantization scale and displacement length on discrimination capability. We found that rescaling to a lower number of grey levels (8 or 16) improved discrimination capability and that equal probability quantization was more effective than uniform quantization. Increasing displacement tended to reduce the discrimination capability. Low spatial resolution increased the discrimination capability because low spatial resolution features reduce the effects of noise. A larger number of features also improved discrimination capability. However, the amount of improvement depended on the window size. We used the optimum combination of backscatter amplitude and textures as input data into a supervised multi-resolution maximum likelihood classification. We found that including texture information improved the overall classification accuracy by 10%. However, there was significant confusion between natural forest and acacia plantations, as well as between oil palm and clear cuts, presumably because the backscatter and texture of these class pairs are very similar.

Palsar Calval and Generation of the Continent Scale Mosaic Products for Kyoto and Carbon Projects

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 JAXAs 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.