In repeat-pass interferometric synthetic aperture radar (In-SAR), the coherence loss derived from temporal decorrelation can be modeled using an exponential decay function. Many researches have investigated the relationships between decay parameters over various land-cover types for C-band SAR satellites. Although ALOS PALSAR provides many L-band SAR images, its revisit time was insufficient for understanding the rapid exponential drop in temporal decorrelation. Due to the lack of an appropriate archived dataset, analyzing the decay parameters for L-band SAR was a challenging task. In this study, we processed four-year interferometric pairs derived from ALOS-2 PALSAR-2 full-aperture ScanSAR images. This dataset has a 14 day minimum temporal interval. We selected Nairobi, Kenya, in the middle of the East African rift, as the study area and investigated how decay functions differ over multiple land-cover types. In addition, we compared decay models for Sentinel-1 interferograms. This study demonstrates that the decay parameters of L-band coherence completely differs across forest types, whereas C-band coherence is low coherence regardless of forest type.

Interferometric SAR time series analysis using multilooked interferograms has measured ground deformation with high accuracy over large areas, but is known to be contaminated by a systematic bias when using only short-term interferograms. This bias, also referred to as a "fading signal", has been investigated using the abundant time series data from Sentinel-1 C-band SAR, and soil moisture and biomass changes have been suggested as two possible causes for the observed bias. Several correction methods have been proposed to mitigate the phase bias, assuming a periodic observation strategy. The phase bias is supposed to increase with the wavelength, but the bias in ALOS-2 L-band SAR has not been investigated in detail because the data distribution policy restricts its users. In addition, these correction methods are not suitable for the infrequently observed data such as ALOS-2. In this paper, we investigated the systematic bias in ALOS-2 multilooked interferograms with respect to various interferometric pairs. We also corrected the phase bias using the noise-filtering technique. The bias in ALOS-2 multilooked interferograms showed >3 mm/year with an average temporal baseline of 144 days, which is equivalent to that of Sentinel-1 with the temporal baseline of 78 days. That is, the bias effect toward the temporal baseline was larger in ALOS-2 than in Sentinel-1. The noise-filtering technique could mitigate the bias with less pairs regardless of land-use.

Operational deforestation detection and forest early warning is one hot topic in synthetic aperture radar (SAR) Earth observation (EO) today. Especially in tropical regions where persistent cloud coverage is incapacitating optical sensors during large parts of the year, active microwave is regarded as the most promising technology to combat illegal and unsustainable deforestation activities. The key aspect for a true EWS is the timely detections of fresh and ongoing deforestation activities in a matter of days. allowing authorities to act on a given warning in meaningful fashion, e.g., inspecting detected sites, detain deforesters and pretend the remaining forest from further destruction. The development of JAXA’s next-generation algorithm (NGA) for deforestation detection builds upon the important breakthroughs in long-term pantropical forest monitoring made by the ALOS-2 mission. A field survey conducted in the Brazilian Amazon verified the unparalleled performance of the NGA to reliably detect ongoing deforestation.

Forest monitoring is a prime objective for orbital synthetic aperture radar (SAR) missions. Especially in tropical regions where persistent cloud coverage incapacitates optical satellite observations for large parts of the year, radar remote sensing provides a unique tool for consistent all-year round data acquisition. In contrast to high-frequencies SARs at C- and X-band, L-band radar constitutes a powerful tool to obtain direct information from the full forest strata ranging from the top canopy all the way down to the forest ground. However, despite important advantages, SAR faces various challenges when it comes to potential error sources. As radar backscattering from distributed natural forest targets is profoundly complicated in nature, ill-defined signal fluctuations often limited the reliability of models and applications. To overcome these challenges by improved understanding of the spatial-temporal fluctuations in forest backscatter, coherent, multitemporal and polarimetric observations covering all kinds of environment conditions are required. Nearing 9 years in orbit since its launch in 2014, ALOS-2 has acquired the world’s first long-term pantropical L-band SAR archive fulfilling exactly these requirements.

In this paper, we propose a novel disaster damage detection method using Synthetic Aperture Radar (SAR) interferometric analysis. SAR interferometric coherence analysis is an effective method for disaster monitoring especially in the urban area, where the amplitude of SAR image changes only slightly unless the damage level is high. One drawback of the interferometric coherence-based analysis is the existence of the Cramér-Rao lower bound. That is, a small spatial window for its ensemble averaging leads significant bias while a large window makes its spatial resolution worse. To solve this problem, we propose to extend the ensemble average window towards temporal domain by increasing the number of interferometric pairs. Conventional methods which use multiple interferometric pairs firstly calculate coherence values independently. Instead, the proposed method unifies the interferograms first. We report some preliminary experimental results showing the effectiveness of the proposed method.

In this study, the dominant and medium scattering phases generated by the Touzi decomposition are investigated for discontinuous permafrost mapping in peatland regions. Polarimetric ALOS2, LIDAR and field data were collected in the middle of August 2014, at the maximum permafrost thaw conditions, over discontinuous permafrost distributed within wooded palsa bogs and peat plateaus near the Namur Lake (Northern Alberta). The ALOS2 image, which was miscellaneously calibrated with antenna cross-talk (-33dB), much higher than the actual ones, is recalibrated. This leads to a reduction of the residual calibration error (down to -43 dB), and permit a significant improvement of the dominant and medium scattering type phase (20°-to-30°) over peatlands underlain by discontinuous permafrost. The Touzi decomposition, Cloude-Pottier α-H incoherent target scattering decomposition, and the HH-VV phase difference are investigated, in addition to the conventional multi-polarization (HH, HV, and VV) channels, for discontinuous permafrost mapping using the recalibrated ALOS2 image. A LiDAR-based permafrost classification developed by Alberta Geological Survey (AGS) is used, in conjunction with the field data collected during the ALOS2 image acquisition, for the validation of the results. It is shown that the dominant and scattering type phases are the only polarimetric parameters which can detect peatland subsurface discontinuous permafrost. The medium scattering type phase, ϕs2, performs better than the dominant scattering type phase, ϕs1, and permits a better detection of subsurface discontinuous permafrost in peatland regions. ϕs2also allows for better discrimination of areas underlain by permafrost from the non-permafrost areas. The medium Huynen maximum polarisation return (m2) and the minimum degree of polarisation (DoP), pmin, can be used to remove the scattering type phase ambiguities that might occur in areas with deep permafrost (more than 50cm depth). The excellent performances of polarimetric PALSAR2 in term of NESZ (-37 dB) permit the demonstration of the very promising L-band long penetration SAR capabilities for enhanced detection and mapping of relatively deep (up to 50 cm) discontinuous permafrost in peatlands regions [1].

Nearing 8 years in orbit, ALOS-2/PALSAR-2 has acquired the world's first long-term pantropical L-band SAR forest monitoring data archive. The unprecedented dual-polarimetric time-series data allow to revolutionize our knowledge of the complex spatial-temporal processes governing the backscattering behaviors in tropical forests from local to global scale. The paper discusses ALOS-2's tremendous contributions to fundamental SAR forest research, forest cover mapping, biomass estimation, and deforestation monitoring, from better forest/non-forest maps and improved forest type classifications to all-new detailed flooded forest maps and groundbreaking insights on the rainfall impacts on L-band SAR imaging shedding light on the often overlooked relation between precipitation and forest backscatter. Based on these pioneering achievements a novel AI-supported false alarm suppression method was developed for the JICA-JAXA forest early warning system in the tropics (JJ-FAST) enabling the first operational fully automatic near real-time deforestation detection service with overall accuracies above 80% in the Amazon basin.

Forest observation is one prime objective for current and future L-band SAR missions. Despite the tremendous achievements made in the last 3 decades, the reliability of derived products, e.g., forest cover and biomass maps, is still largely hampered by ill-defined backscatter fluctuations. To better understand the rain-induced noise-like variations in tropical forest backscatter timeseries, we demonstrate big data deep learning applications exploiting the unprecedented long-term data sets provided by ALOS-2/PALSAR-2 from 2016–2021. Robust fully automatic deforestation detection is achieved in an operational forest monitoring system by using a CNN-based false alarm suppression method. Using 400 TB of ScanSAR images together with 50 billion auxiliary rainfall data an automatic rainfall prediction and correction procedure for L-band SAR is proposed based on LSTM artificial neural network. First results show the approach's potential to reliably reduce rain related disturbances in L-band forest timeseries in an unsupervised fashion.

JICA-JAXA Forest Early Warning System in the Tropics (JJ-FAST) monitors tropical forest in 77 countries by using PALSAR-2/ScanSAR time-series data. The deforestation detection algorithm used in JJ-FAST shows overall user's accuracies of 71.1%, but the user's accuracies was 53.3 % for Latin America. Four convolutional neural network models (CNN) have been developed and tested to improve deforestation detection accuracies in Peru and Brazil. By applying the suggested CNN models, averaged user's accuracies are improved from 45 % to 77 - 85 % in dry season, and from 34 % to 48 - 57 % in rainy season. Averaged relative F1 are improved from 0.6 to 0.67 - 0.75 in dry season, and from 0.49 to 0.52 - 0.63 for rainy season. It is shown that adding CNN operation improves the deforestation detection accuracies. Intermediate CNN outputs were visualized to gain insights about what features of the image does each layer learn for improving the accuracies.

In this study, we applied the modified PS INSAR for detecting the land slide area under the forest cover region, and decomposed the UD and EW components of the movement from the time series data A and D InSAR pairs. The target area showed L-band SAR (PALSAR-2/ALOS-2) could detect the slow movement of the land surface which is covered by the deciduous trees.

One of the prime objectives for orbital civilian SARs is forest observation. Though tremendous effort has been devoted to improving applications like biomass estimation and deforestation detection, the reliability has been impeded by insufficient knowledge about spatial-temporal variabilities of forest backscatter. In the tropics, these backscatter fluctuations are largely controlled by the rainfall regime. This paper investigates the impact of rainfall on L-band forest observation using 300 TB pan-tropical ALOS-2 ScanSAR timeseries with 1.5 billion TRMM based GSMaP precipitation datasets. The results show that the correlation between forest gamma naught and antecedent rainfall can exceed R=0.9 in many areas outside the rainforest. In the rainforest strong negative correlation below R=-0.8 can occur in the severely flooded forest. We assess the impact of rainfall on deforestation detection accuracies and discuss a new classification scheme for tropical forests using statistics of seasonal backscattering behaviors together with response to precipitation.

JICA and JAXA have operated a tropical forest early warning system (JJ-FAST) since 2016 and ALOS-2 L-band SAR system (PALSAR-2/ScanSAR) is used for forest monitoring and deforestation detection. There are many factors to cause commission errors in SAR image and ground moisture is one of them. To reduce such commission errors, seasonal change analysis is effective. In this study, a time-series analysis method using Savitzky-Golay (SG) filtering was developed. The method of speckle noise filtering by frost and 2-step thresholding and time-series analysis using SG was good method. The accuracy of forest change detection was improved from 19% of the threshold method to 80%.

JJ-FAST is the SAR-satellite based early deforestation monitoring system, and deforestation information obtained by using PALSAR-2/ScanSAR data are released on the JJ-FAST web site, 3 to 4 days after the observation. ScanSAR/50m spatial resolution data is currently used for the deforestation detection, and the minimum detection size is 3ha. In this paper, ScanSAR/25m spatial resolution data is used for the deforestation detection, and the detection accuracies are compared with the one obtained with the 50m spatial resolution data for four test sites. The minimum deforestation detection size is set to be 1ha in this time. The results show that the 25m spatial resolution data always shows higher detection accuracies. The results obtained in Cambodia test site show that user's accuracies are 21.4 % higher than the case of 50m resolution, and number of correctly detected polygon is 2.3 times more than the one for the 50m resolution case. It is indicated that the 25m spatial resolution ScanSAR data improves the detection accuracies with minimum detection size of 1 ha.

This study investigated a method of flood detection in built-up areas by L-band synthetic aperture radar (SAR) images, using interferometric phase statistics instead of the widely used coherence. Simulation and actual SAR data analysis showed that phase statistics are more accurate than coherence is, especially when there are many point-like scatterers. Accuracy was further improved by using an interferometric phase filter. The flood detection accuracies obtained by the phase statistics were κ = 0.535 (0.304 by coherence) in the 2015 flood in Joso and κ = 0.679 (0.609 by coherence) in the 2018 flood in Mabi. These results showed that coherence should be used with great care with point targets and that the phase-only statistics can be more robust in such cases. The proposed method is expected to apply to other types of disasters where coherence has been used previously.

Compact-hybrid SAR (CP) is a dual-polarization (dual-pol) SAR mode that transmits a circular polarization (CirP) and measures the received signal at the horizontal and vertical antenna polarization. It is now admitted that the actual SAR technology does not permit the generation of a perfectly CirP and this may significantly affect CP radiometric and phase information. Since all the existing CP calibration models assume a perfectly transmitted CirP, there is an immediate need for the development of a new model that permits efficient assessment and calibration of CP non-circularity. In this article, a new general polarimetric hybrid SAR model (PolHyb) is introduced for both dual- (CP) and quad-polarization hybrid SAR modes. PolHyb explicitly includes the transmitted polarization non-circularity, in addition to conventional radar transmit and receive distortion matrices, channel imbalances and Faraday rotation contamination. The non-circularity of transmitted polarization is expressed in terms of the axial ratio (AR), which used to be popular in the 1960s for characterization of circularly polarized (transmit and receive) dual- and quad-polarization radar. The new CP model derived from PolHyb is adapted to PALSAR2-CP and used as the basis of an efficient method for an assessment of CP non-circularity using Amazonian rainforests. PALSAR2-CP data collected at four different beams (H2-6 to H2-9), with incidence angle varying between 30° and 45°, allows for the first ever demonstration of non-circularity of PALSAR2 CP transmitted polarization. Although it is lower than 0.5 dB for H2-6 and H2-7, the AR of PALSAR2-CP transmitted polarization increases significantly with incidence angle to reach up to 1 dB at Beam H2-8, and 2.3 dB at the highest incidence angles of Beam H2-9.

We extracted the surface deformation of Mt. Shinnmoe-dake using the INSAR analysis of the time series PALSAR-2 data. Since the eruption in Oct. 2017, Mt. Shinmoedake volcano has been continuing the eruption activities, and showing the fluctuations in the crater from February 2017 to February 2018. In order to perform more accurate fluctuation measurement, we conducted the two calibrations to the original Interferometric SAR (InSAR) data: the external calibration using the GNSS points of Geospatial Survey Institute of Japan (GSI) and the atmospheric correction which was newly developed in this research. As a result, it was confirmed that the crater has been slightly moving, that the radar-line-of-sight distance between the crater and the satellite in ascending is decreased by 0.2 cm, and that descending distance is increased by 0.7 cm.

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.

In this paper, we performed the interferometric analysis of ALOS-2/PALSAR-2 for detecting the landslide area in Ishizaka Forest in Hatoyama Town and decomposed the slide movement in the east-west and in the vertical directions by using the 2.5-dimensional analysis method. We also analyzed the trend using time series analysis. As a result, a minute fluctuation of 0.4 cm/year in the east direction and 0.2 cm/year in the settling direction was obtained. In future, we will improve the estimation accuracy and will carry out comparative verification with GPS with future progress.

Insufficient knowledge about spatial-temporal forest heterogeneities in the tropics is a major impediment to better estimation of carbon storage and prevention of deforestation by remote sensing. While the differences between the dense evergreen rainforest and the open (semi-) deciduous dry forest is obviously large, variations caused by seasonal changes can easily introduce fluctuations in the same order of magnitude within the same forest class. In this study, we present a comprehensive analysis of the variability of tropical forests based on homogeneous big data analysis on multitemporal ALOS-2 dual-polarized ScanSAR data. The first, easy to understand global forest variability maps provide unseen insights into forest structures for the entire tropical belt. Based on these results, we discuss the development of a new global classification scheme for tropical forests. Preliminary results demonstrate how the use of various statistical parameters obtained from the long-term systematic L-band SAR forest monitoring data, including the average γ0, its temporal standard deviation and the γ0range, can improve the classical global-scale forest classifications. In addition to the basic separation into the three main forest types i) rainforest, ii) moist forest and iii) dry forest, the results provide a detailed mapping of the seasonally flooded forest areas.

In order to reduce speckle noise effects in forest cover change analysis, two types of SAR processing approach have been proposed so far. One is a type of object-based segmentation approaches and another is pixel-based processing approaches using speckle noise filtering such as Lee and Frost filter. This paper proposes a methodology of the pixel-based algorithm for forest change detection using PALSAR-2 ScanSAR data. Frost filter is applied to reduce speckle noise and normalization filter is implemented to reduce ground moisture effects. In case of Peru and Paraguay, the user's accuracy of developed algorithm was almost same as those of JJ-FAST version-2 while the producer's accuracy was 3 times better than JJ-FAST latest version (version-2).

Rapid and all-weather detection of flood areas is needed for monitoring and mitigating flood disasters. In this paper, we investigated flood area detection in built-up area using PALSAR-2 data acquired during the 2015 heavy rainfall disaster in the Kanto and Tohoku areas, Japan. We performed an interferometric processing using pre- and co-event PALSAR-2 data and compared proposed phase-only statistics with traditional coherence-based flood detection. The result indicated that the flood detection accuracy by thresholding of phase standard deviation (PSD) image is more accurate than that of coherence and the accuracy was a 0.443 kappa coefficient in flood/non-flood discrimination. This result demonstrated the feasibility of using PALSAR-2 data for rapid flood monitoring in built-up area without being affected by strong backscattering from the buildings.

In Earth Observation, Analysis Ready Data (ARD) are commonly referred to as satellite data that have been processed to a minimum set of requirements and organised into a form that allows immediate analysis with a minimum of additional user effort and that facilitates interoperability through both time and space with other datasets. The Committee on Earth Observation Satellites (CEOS) is currently developing a set of ARD specifications for both optical and Synthetic Aperture Radar (SAR) satellite data under the so called CARD4L (CEOS Analysis Ready Data for Land) framework [1], [2].The Japan Aerospace Exploration Agency (JAXA) generates global SAR mosaic on an annual basis from data acquired by the JERS-1 SAR, ALOS PALSAR and ALOS-2 PALSAR-2 missions. The mosaic products have been subject to full geometric and radiometric corrections and organised into a format that can be considered ARD. In order for the mosaic products to obtain CARD4L certification, JAXA has undertaken a product alignment assessment of what additional processing steps or ancillary information that would be required for the mosaic products also to be compliant with the CARD4L specifications for Normalised Radar Backscatter. The data products, alignment process and outcome of the assessment are described below.

300 MHz X band FMCW single pass INSAR instrument and processing algorithm were developed for generating the accurate DEM of the Earth. Japan has more than hundred active volcanoes and often to vary the topography. This light weighted InSAR instrument can quickly monitor and measure the change of the earth surface flying on the low altitude of the small manned airplane. The imaging and interferometric SAR algorithms were developed for fast and accurate provision of the topography preparation. The algorithm can bear the long strip processing without limitations on the fast memory storage composed of two steps: browsing and high precision mode. Height and geolocation accuracies are evaluated and measured as better than several meter.

ALOS2-PALSAR2, which was launched on the 24th of May 2014, is equipped with an experimental Compact mode (CP) ([1], [2]), that can collect CP images at various incidence angles (H2-1 to H2-9, from 18° to 44°). PALSAR2-CP transmits a circular polarization and measures the received signal at the horizontal and vertical antenna polarization. Recently, it was brought out that the actual technology does not permit the generation of a perfectly circular polarization [3]. The transmitted polarization is non circular, and the non circularity varies with incidence angle. Since all the calibration methods developed for CP assume that the transmitted polarization is perfectly circular, there is immediate requirement for the development of a new CP calibration model that includes the transmitted polarization non circularity. In this study, a new CP calibration model, which explicitly includes the transmitted polarization non circularity, in addition to conventional radar transmit and receive distortion matrices, channel imbalances and Faraday rotation contamination, is introduced. The new CP model is adapted to ALOS2-PALSAR2 and used as the basis of a new method for assessment of CP non circularity using Amazonian rainforests, at low Faraday rotation. ALOS2-CP data collected at four different beams (H26 to H29), with incidence angle varying between 30° and 44°, permit the first ever demonstration of non circularity of ALOS2 CP transmitted polarization. It is shown that the transmitted polarization axis ratio of ALOS2-CP increases with incidence angle, and can reach up to 2.5 dB at the most raising incidence angle (44°) of the beam H29.

JJ-FAST is the first SAR-based global and early deforestation monitoring system, and started the operation from November 2016. In this paper, improved deforestation detection algorithm were suggested for using JJ-FAST system. One of the improvement is to increase maximum number of data used from 15 to 20 to suppress error detection occurred in mountain area and swamp forest. The other improvement is to adopt 0.5 dB lower threshold level to increase number of deforestation detection. Suggested algorithm were evaluated by using optical satellite data (GLAD), obtained in one of the active deforestation spots in Peru, Brazil, Cambodia, and Mozambique. User's accuracies increases by 6.7%, and number of correctly detected deforestation polygon make it 1.3 times as large.

Monitored storage data derived from detection and estimation of oil tank can be gathered to report statistics of demand and supply trend and these are tremendously important for economics and commodity trading. Several previous studies focusing on the tanks have been reported with SAR imagery but application with L-band requires completely different discussion. In this paper, we introduce an algorithm estimating floating roof height by use of ALOS-2 imagery and the proposed technique is discussed not only in StripMap mode but also in ScanSAR mode. Since an evaluation by use of ground measurement data is difficult, qualitative results are shown and discussed in this report.

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.

In the dry tropical forest and semi-arid savanna information about the soil moisture dynamics and distribution are vital to better understand and mitigate damages caused by drought. To estimate the soil moisture over large areas from 50-m resolution ALOS-2 ScanSAR data, we adopt dual-polarization L-band algorithms originally developed for high resolution ALOS data. Based on the partial-polarimetric eigenvector decomposition, the scattering entropy and alpha angles are employed to correct for the above ground vegetation effects. The large incidence angle variation along the 350-km ScanSAR swath requires the use of an incidence angle correction factor. However, due to the relative poor data quality of the ScanSAR products suffering from scalloping and near-range/far-range striping along the subswathes, we observe lower accuracies than Stripmap mode. While in the dry season soil moisture retrieval in the open forest is well possible, in the rainy season the entropy exceeds the validity range due to the larger amounts of canopy biomass resulting in unreliable soil moisture estimates. Savanna vegetation allows a biomass-corrected soil moisture estimation throughout the whole year. Due to the lack of distributed in-situ data, we use coarse scale SMOS and SMAP soil moisture data to validate the accuracy of dual-polarization ScanSAR soil moisture estimates. Comparisons between the kilometer-scale radiometer derived soil moisture estimates and 50-m ALOS-2 results show a good agreement in the dry season with RMSEs smaller 5 Vol.-%, while in the rainy season the RMSEs can be as high as 15 Vol.-%.

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.

JJ-FAST is an operational forest early warning system using PALSAR-2/ScanSAR mode data. Its deforestation detection algorithm has been updated since 2016 and the current is version 1 (as of January, 2018) and the algorithm version 2 is preparing to implement in March 2018. Overall user's accuracy of version-1 products was estimated from several field experiments, and achieved as 83.3%. There are omission errors in the version 1 products because of its simple HV change detection approach.

The Advanced Land Observing Satellite-2 (ALOS-2) was successfully launched on 24th May, 2014, carrying the state-of-the-art L-band synthetic aperture radar, PALSAR-2. The satellite was developed and is stably operated by Japan Aerospace Exploration Agency (JAXA). As of January 2018, the satellite bus system and PALSAR-2 system are working very well. The PALSAR-2 data were acquired based on a systematic observation strategy to achieve consistent data acquisitions in time and space. JAXA also respond to the emergency observation requests for disasters. The observation data are distributed to both scientific and commercial users and utilized for disaster monitoring, environmental monitoring, and many other fields of applications.

Rapid and all-weather detection of flood areas is needed for monitoring and mitigating flood disasters. In this paper, we investigated flood area detection using ALOS-2 PALSAR-2 data acquired during the 2015 heavy rainfall disaster in the Kanto and Tohoku areas, Japan. We detected flood areas by thresho ldlng amplitude images from PALSAR-2 and then evaluated their accuracies against inundation maps based on aerial photographs. The highest accuracy was a 0.583 kappa coefficient in flood/non-flood discrimination. Our comparative study results indicate that lower off-nadir angles (around 30 degrees or less) are effective in the detection of flood areas. We also found polarimetric analysis and speckle filtering to be effective in improving accuracy. The results of this study demonstrate the feasibility of using PALSAR-2 data for rapid flood monitoring and as a reference for future flood disasters.

ALOS-2-PALSAR is equipped with an experimental Compact mode (CP), which can collect CP images at various incidence angles. PALSAR2-CP transmits a circular polarization and measures the received signal at the horizontal and vertical antenna polarization. Recently, it was brought out that the actual SAR technology does not permit the generation of a perfectly circular polarization and this may significantly affect CP information [1]. Since all the calibration methods assume that the transmitted polarization is perfectly circular, there is an immediate need for a new CP calibration model that is more suitable to actual CP SARs. In this study, a new CP calibration model that takes into account the non circularity of transmitted polarization, in addition to conventional SAR transmitter and receiver distortion matrices, is introduced. The CP calibration model is used as the basis for the development of an efficient method that permits the measurement of transmitted polarization axis ratio, and its variations with incidence angle. The method is validated using PALSAR2-CP data collected at various incidence angles on the Amazonian forests. It is shown that the transmitted polarization axis ratio varies with PALSAR2-CP beam, and can reach up to 1.1 dB for the CP mode (H2-8) (at about 37° incidence angle).

A preliminary version of the semi-automatic deforestation detection algorithm was developed for the JJ-FAST system, which monitors deforestation and forest changes in tropical regions for approximately every 1.5 months and covers 77 countries. PALSAR-2/ScanSAR HH, HV, HH and HV ratio were used to detect various deforestation stages. Multitemporal data were used to suppress the effect of seasonality and rainfall. Moreover, the deforestation accuracies for the active deforestation spots in Brazil and Peru were estimated. The user's accuracies achieved as 80.5% in the dry season, but these decreased to 11.1% in the rainy season.

In this paper, we demonstrated the possibility of performing land use and land cover (LULC) classification over a wide area by an L-band polarimetric synthetic aperture radar (SAR). In previous studies, there has been scant LULC classification by polarimetric SAR data over a wide area. We used satellite-based SAR data with an area of ca. 320 000 km2obtained by the Phased Array type L-band SAR (PALSAR)-2 phase array. We performed the LULC classification using full polarimetry (FP), compact polarimetry (CP), and dual polarimetry (DP) data by PALSAR-2 and compared their classification accuracy. Our results show FP to be the most accurate. The CP and the DP have the advantages of large-scale coverage and compact data volume but is slightly less accurate than the FP. To further improve accuracy of the classification process, texture analysis, observation date information, and feature elimination are effective. We determined the classification accuracy for seven classes to be 73.4% (the kappa coefficient is 0.668). We found the rice paddy, forest, grass, and urban areas to be sufficiently accurate (84.5%) for practical application. We compared the obtained classification map with an existing LULC map to grasp the LULC changes induced by a recent disaster and successfully detected the damage areas of the disaster. These results indicate the possibility of large-scale LULC monitoring by an L-band polarimetric SAR, which can acquire images rapidly without being affected by weather.

Recently many studies for application of multi-temporal interferometric SAR technique in monitoring ground motion have been reported. When we focus on number of scenes in high resolution mode of ALOS/PALSAR and ALOS-2/PALSAR-2, available number of scenes for interferometry are limited because of their global observation scenario. ALOS/PALSAR and ALOS-2/PALSAR-2 observation has been conducted with less number of scenes but globally and equally in comparison to other sensors which have been widely used, such as TerraSAR-X and COSMO-SkyMed. Therefore, overcoming this problem of scene number will promote application field of them. Since the scenes cannot be merged for interferometry analysis between these sensors as they are on different orbit and with different frequency, in this study, inter-sensor time-series analysis of persistent scatterer interferometry is discussed to increase availability of the data set. These scenes from different sensors in different orbit are merged to be used for estimation process in time-series analysis and an output parameter set is calculated although traditional approach estimates parameter set after time-series analysis in different data set has been conducted.

ALOS-2 ScanSAR data was used for examining the effect of precipitation and soil moisture variations on L-band forest backscatter in tropical regions. Multitemporal data spanning from observation cycle 39 to 62 acquired over tropical forests in South America and Africa has been used. Precipitation data provided through JAXA's global rainfall watch was used to examine the temporal change of L-band σ0for forests as well as deforestation areas. The best choice for temporal integration of rainfall prior to the image acquisitions was investigated. The results show that σ0HHvalues show an average increase smaller 1 dB, whereas σ0HVvalues can increase by more than 2 dB in dense forests after heavy rain. Our findings also indicate that dense forest and open/moderately dense forests can show quite different rainfall effects. The latter may even exhibit a decrease in both σ0HHand σ0HVafter heavy rain due to standing water. Implementations for the ongoing development of an advanced tropical forest monitoring system are discussed.

This paper introduces the operational status of the Advanced Land Observing Satellite-2 (ALOS-2) and its follow-on L-band SAR mission in Japan. ALOS-2 observes the earth surface with the Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) that is effectively used for many applications such as land deformation mapping and forest change mapping. To keep and enhance the applications using PALSAR-2 data, JAXA plans to launch a successor satellite to the ALOS-2 in Japanese Fiscal Year 2020. The concepts of the ALOS-2 follow-on are expanding swath width and increasing observation frequency while keeping high spatial resolution of the PALSAR-2 for improving the response of disaster monitoring, early detection of anomalies on the earth surface, and enabling time-series interferometric SAR (INSAR) analysis.

In 2016, the Advanced Land Observing Satellite-2 (ALOS-2, “DAICHI-2”) observed various disaster affected areas. Japan Aerospace Exploration Agency (JAXA) operated the emergency observation more than hundred times in the year. The Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) aboard ALOS-2 contributed for detecting the disaster affected area, ground deformation and flood affected area. Especially for the ground deformation and damaged area detection caused by the devastating earthquakes in 2016, e.g., Kumamoto earthquakes in Japan and Kaikoura earthquake in New Zealand, researchers provided variable analytical results from ALOS-2 observation data. In this paper, some examples of the emergency observation results are presented.

Land cover is an important earth observation parameter for understanding the Earth's ecosystem. Compared with optical sensors, Synthetic Aperture Radar (SAR) enables more rapid land cover monitoring with its all-weather, day-and-night imaging capability. We mosaicked 390 scenes of PALSAR-2 fully polarimetric data acquired in Japan and computed several polarimetric decompositions. Then, we applied supervised land-cover classification. The accuracy of seven categories classification in the Kanto region, Japan, was 75.0%.

ALOS-2/PALSAR-2 25-m spaced global mosaic has been produced as the L-band SAR forest monitoring dataset selected from the best acquisitions over the global land and year 2014 and 2015, as the resume of the dataset after pausing the ALOS/PALSAR on 2011 April 22, in the end of 2015. Detailed evaluation results showed some image degradations compared to ALOS/PALSAR: visible stripes across the neighboring strips. The possible causes are 1) less overlapping area between two neighboring strips and needs careful area selection for the radiometric balancing, and 2) antenna elevation pattern needed some more calibration. These two points were well recovered as the recalibration processing in 2016. We are creating the new version of the mosaic as of now. In this paper, we will describe the details of recalibrated and regenerated PALSAR-2 mosaic products for 2014/2015 and 2016 using the improved radiometric calibration algorithm.

Time series PALSAR-2/ScanSAR data and Landsat data were used for examining the differences in detection timing of deforestation. Optical sensor-based (Landsat) deforestation information taken about every 16 days and SAR data taken about every 1.5 months were used, and the temporal change of L-band γ0was examined for the deforestation areas. The γ0HHvalue increased by 1.2 dB on average for areas undergoing the early stages of deforestation, where fallen trees were left on the ground. The detection timing was almost same as that using the optical sensor. On the other hand, the γ0HVvalue decreased by 1.2 dB on average for areas undergoing the late stages of deforestation, where fallen trees were removed. The detection timing using γ0HVwas about a few month after the detection using γ0HH, or optical sensor. It is concluded that γ0HHis useful for early-stage deforestation detection, and γ0HVis useful for late-stage deforestation detection.

The polarimetric characteristics of early- and late-stage deforestation areas were examined using PALSAR-2. An early-stage deforestation site, where the fallen trees had been left on the ground, showed an increase in σsurface0of 2.9 dB, and decrease in σvolume0of 1.4 dB. This induced the 0.9 dB increase in σHH0. A late-stage deforestation site, where the fallen tree had been removed, showed an increase in σsurface0of 2.3 dB, and a decrease in σvolume0of 6.4 dB. This induced the 6.1 dB decrease in σHV0. Polarimetric analysis clarified the scattering mechanism for the early- and late-stage deforestation areas.

This letter closes a special stream consisting of selected papers from the fifth Asia-Pacific Conference on Synthetic Aperture Radar in 2015 (APSAR 2015). The latest research results and outcomes from APSAR 2015, particularly on the synthetic aperture radar (SAR) systems/subsystems design, data processing techniques, and various SAR applications in remote sensing, are summarized and presented. All these results represent the recent advances in SAR remote sensing. Hopefully, this letter can provide some references for SAR researchers/engineers and stimulate the future development of SAR technology for remote sensing.

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.

The Advanced Land Observing Satellite-2 (ALOS-2) was successfully launched on 24th May, 2014. The mission sensor of ALOS-2 is the Phased Array type L-band Synthetic Aperture Radar-2 called PALSAR-2 which is the state of the art L-band SAR system. At After launch, the initial checkout and the calibration and validation phase had been completed, and the PALSAR-2 standard products were released via web site at the end of November 2015. Until now, ALOS-2 has had contributed to a lot of emergency observations for disasters such as earthquakes flood, land slide which were impacted by typhoons, and volcano eruptions, not only in Japan but also in the world. Furthermore, based on the Basic Observation Scenario (BOS) of ALOS-2, base map data are collected and archived for the interferometry SAR processing in Japan area as well as global world. This document describes the results of ALOS-2 operation in routine operation phase.

One of the main missions of the Advanced Land Observing Satellite-2 (ALOS-2, “DAICHI-2” ) is the disaster monitoring. Japan Aerospace Exploration Agency (JAXA) has operated the emergency observation more than hundred times in 2015. Not only the most important event in 2015, the Mw 7.8 Gorkha earthquake on April 25, the Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) aboard ALOS-2 observed various floods, volcano eruptions and earthquakes. In this paper, we present some emergency observation results which were impossible to be performed by the previous ALOS. That is, automatically burst aligned ScanSAR to ScanSAR interferometry and, left / right looking for increasing acquisition opportunity.

Decreasing the carbon emission from the deforestation and forest degradation is one of the issues that the humans need to tag for sustaining the Earth. Monitoring the forest from the space is the recent achievements that the space agencies contribute. Measuring the forest cover change is being conducted by using the high resolution optical and/or SAR images. ALOS-2 has been on-orbit carrying the L-band SAR since May 24, 2014. After more than one year data acquisition and related processing, the first version of the 25-m resolution global PALSAR-2 mosaic dataset from the 2014-2015 acquisitions, forest-non-forest map, and the forest cover change from 2007 to 2015 were generated.

The Jakarta province proposed the Jakarta Giant Sea Wall as the waterfront city for the new urban settlement zone and the deep seaport for the new economic zone along the coastal areas at northern Jakarta. This letter investigated land deformation at 11 watersheds of the West Java Mega Urban Region using the persistent scatterer interferometry technique of the Advanced Land Observing Satellite phased-array-type L-band synthetic aperture radar data. The result shows that land deformation at the study area, particularly the Bandung city area gives a significant impact to sedimentation velocity along the eastern Jakarta strait, particularly the deep seaport for 43 years later. This letter recommends to evaluate land conservation at upland watersheds and the well management of artificial canals to reduce the impact of sedimentation at the Jakarta strait, particularly the new depth seaport.

The Advanced Land Observing Satellite-2 (ALOS-2) was launched from Tanegashima Space Center by H-IIA rocket successfully on 24th May 2014. The Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) is the state-of-the-art L-band SAR system which succeeds to PALSAR onboard ALOS. PALSAR-2 uses almost whole bandwidth allocated for L-band active sensor of Earth Exploration Satellites Service specified by the Radio Regulation in order to realize the high resolution observation, and also, PALSAR-2 transmits more than 6 kW power using 180 TRMs driven by Gallium Nitride (GaN) amplifier which is the first use for satellite in order to realize the lower Noise Equivalent Sigma Zero. Furthermore, because ALOS-2 carries PALSAR-2 only, PALSAR-2 antenna can be mounted under the satellite body. It enables to observe right-/left-looking observation by satellite maneuvering. And the high accuracy orbit control which maintains within 500 m radius tube for the reference orbit enables high coherence for the InSAR processing. Using these new technologies, ALOS-2 has been operating to fulfill the mission requirements such as disaster monitoring and so on. At this moment, one year has passed since the launch. This document introduces the first year operation result of ALOS-2.

ALOS-Next/Tandem-L is a proposal for a highly innovative L-band SAR satellite mission for the global observation of dynamic processes on the Earth's surface with hitherto unparalleled quality and resolution. It is based on a collaboration between DLR and JAXA which started with a pre-phase A study in 2013 and is currently undergoing a phase A study. Thanks to the novel imaging techniques and the vast recording capacity with up to 8 Tbytes/day, it will provide vital information for solving pressing scientific questions in the biosphere, geosphere, cryosphere, and hydrosphere. By this, the new L-band SAR mission will make an essential contribution for a better understanding of the Earth system and its dynamics. ALOS-Next/Tandem-L will, moreover, open new opportunities for risk analysis, disaster management and environmental monitoring by employing especially designed acquisition modes and techniques in combination with a reconfigurable tandem satellite configuration and an L-band SAR instrument with advanced digital beamforming techniques.

In the field of Synthetic Aperture Radar (SAR) interferometry, we generally expect that there is only unique dominant scatterer in one pixel. To make a SAR interferogram, we have to observe a place twice. The dominant scatterer in every pixel must be identical in those observations. However, in an actual situation, there are multiple scatterers in one pixel physically, and the dominant one may be changed in the two observations. Slight difference of incident angle may cause the change of the dominant scatterer and the propagation path. The change can generate singular points (SPs) in the inter-ferogram which prevent us from accurate phase unwrapping. Here, we present experimental results in an anechoic chamber which show the mechanism of the singular point generation.

In this paper we introduce recent results of studies performed under the cooperated activities between Japan Aerospace Exploration Agency (JAXA) and the Agenzia Spaziale Italiana (ASI) for disaster monitoring. Under this cooperation, we performed simulation study of coordinated observation by ALOS-2, COSMO-SkyMed and other SAR satellites in case of huge Nankai Trough Earthquake in Japan. The result proved that coordinated observation could improve observation frequency and reduce time to acquire seamless dataset over vast disaster areas. The COSMO-SkyMed PSInSAR study over Sakurajima in Japan revealed possible deformation caused by volcanic activities. We challenged flood detection case study by using both L band and X-band SAR images for developing semi-automatic discrimination of inundated areas in urban areas in northern Kyushu where were suffered by an unprecedented heavy rain in 2011. The comparative study to investigate the sensitivity of polarimetric parameters of L-band SAR and X band SARs shows the single image L band polarimetry provides effective information on landslides in mountainous area covered by vegetation.

PALSAR2 distortion matrix is measured using corner reflectors (CR) deployed in the Amazonian forest. The Amazonian forest near the geomagnetic equator provides ideal sites for the assessment of PALSAR antenna parameters, at free Faraday rotation. The extended Freeman-Van Zyl calibration method [1] introduced and validated for ALOS-PALSAR calibration is used for the assessment of PALSAR-2 calibration parameters. Six data sets collected over the Amazonian forest (with CRs) are used to assess PALSAR-2 distortion matrix for five beams (FP3 to FP7) with incidence angle varying from 25° to 40°. It is shown that PALSAR2 antenna is highly isolated with very low cross-talk (lower than -40 dB).

Correlations between L-band SAR polarimetric parameters obtained with airborne SAR (Pi-SAR-L2) and metrics obtained with airborne LiDAR were examined to identify the relationship between the full polarimetric parameters and forest parameters obtained for a natural forest in Indonesia. Values of a0HVand a0VVshow good correlations with canopy height and 90thpercentile metrics of LiDAR, with R2values of 0.85-0.89. These correlations show higher R2values than the value of 0.33 for a0HVvs. above-ground biomass. The results indicate that a0shows a robust correlation with tree height weighted to taller trees. Polarimetric parameters estimated from a single tree also support the results. Entropy and anisotropy obtained from a single tree shows almost the same value, and a is about 45°, while the tree height ranges 2 m to 6 m. This indicates that these parameters are preferable for land cover classification.

Advanced Land Observing Satellite-2 (ALOS-2) is a spaceborne Synthetic Aperture Radar (SAR) system, developed by Mitsubishi Electric Corporation under contract to Japan Aerospace Exploration Agency (JAXA). The SAR system named Phased Array type L-band Synthetic Aperture Radar-2(PALSAR-2) is installed to ALOS-2. Its unique frequency of L-band is expected continuous investigation such as forest, volcanoes, and earthquake activities. Compact polarimetry mode and Along track interferometry (ATI) mode are available in PALSAR-2 as experimental mode. The evaluation of each experimental mode has been completed and reported in this paper. Compact polarimetry mode is that H and V polarization are transmitted at the same time, therefore the swath can be maintained. Each polarization status of compact polarimetry is calculated from the covariance matrix using some assumption. The full polarimetry-like image can be obtained as first evaluation. Along track interferometry is the technique to detect the moving target. ALOS-2 has two receiver channels. The moving target and its velocity are obtained from the interferometric image of each channel. The velocity can be calculated from the phase difference between two images. This result compared with another method using Doppler shift to validate it.

We tested the performance of the stereo observations of the Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) onboard the Advanced Land Observing Satellite (ALOS) in the mapping of forest aboveground biomass (AGB) in Japan. Digital canopy height models (DCHMs), which are differences between PRISM digital surface models and surveying-based digital terrain models (DTMs), were compared to in situ AGB measurements of several forest types (number of stands: 28; average stand size: 0.54 ha; stand size range: 0.25-3.00 ha). DCHM values exhibited a significant correlation with AGB (r = 0.66-0.87; five different DCHMs), and the root-mean-square error and bias of the regression model evaluated by the leave-one-out cross-validation were 37.2-57.8t/ha(22.1%-32.6%) and-0.11-1.89 t/ha, respectively. There was no saturation in the relationship between DCHM and AGB (AGB range: 19-332 t/ha). The correlations between DCHM and mean canopy height (r = 0.17-0.52) and between DCHM and Lorey's height (r = 0.26-0.66) were weaker than the correlation between DCHM and AGB. The PRISM AGB distribution estimated by the regression model was consistent with a tree density map produced from aerial photos. Comparison to Phased Array-type L-band Synthetic Aperture Radar (PALSAR) data showed that the PRISM DCHMs can estimate high AGB over the saturation level of PALSAR backscattering coefficient, i.e., 100-200 t/ha. The results described here demonstrate that the PRISM DCHMs are capable of wall-to-wall AGB estimation at 50-m resolution. This approach will be useful for improving the performance of satellite-based AGB estimation when an accurate DTM is available.

The temporal variations (diurnal and annual) in arboreal (εTree) and bare soil (εSoil) dielectric constants and their correlation with precipitation were examined for several trees in Japan. A significant (1 σ (standard deviation) and 2 σ) εTreeincrease is observed after rainfall at 89.8% and 90.5% probability. However, rainfall does not always induce significant εTreeincreases. Rainfall of more than 5 mm/day can induce 1 σ εTreeTree increase at a 59.6% probability. In order to examine whether the increase in εTree affects the L-band σ0variation in a forest, the four-year temporal variation of the L-band backscattering coefficient (σ0) was estimated from observations by the Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar. Observed maximum absolute deviations from the mean over the forest area were 1.0 and 1.2 dB for σHH0and σHV0, respectively, and 4.0 and 3.0 dB over open land. σ0and rainfall correlations show that εTreeand σForest0are proportional to precipitation integrated over seven or eight days; εSoiland σOpen land0are proportional to precipitation integrated over three days. This finding indicates that εTreevariations influence σForest areas0. A stronger correlation between σHV0and precipitation is observed in several sites with low σHV0, where less biomass is expected, and several sites with high σHV0, where more biomass is expected. A weaker correlation between σHV0and precipitation is observed for several sites with high σHV0. These differences may be explained by the different contributions of double bounce scattering and potential transpiration, which is a measure of the ability of the atmosphere to remove water from the surface through the processes of transpiration. The two other results were as follows: 1) The functional relation between aboveground biomass and σ0showed dependence on precipitation data, this being an effect connected with seasonal changes of the εTree. This experiment reinforces the fact that the dry season is preferable for retrieval of woody biomass from inversion of the functional dependence of SAR backscatter and for avoiding the influence of rainfall. 2) The complex dielectric constant for a tree trunk, which is measured between 0.2 and 6 GHz, indicates that free water is dominant in the measured tree.

PALSAR full polarimetry data were used to detect thaw/freeze conditions on the ground to try to determine the cause of a spring flood on a northern river in Russia. Full polarimetric data was used to identify the forest area, and the radar backscattering coefficient, σ0HV, was examined. The σ0HV over a frozen forest area was -19.9 dB, while that of a thawing forest area was -11.9 dB, and freeze/thaw events over the forest area were well represented by this parameter. Using this characteristic, together with optical sensor (AVNIR-2) data and microwave radiometer (AMSR-E) data, freeze/thaw conditions were examined for an area including Markha, where a large ice jam flood occurred in 2007, and compared it to 2009, when no flooding occurred. The results indicate that the thawing event proceeded more rapidly between March 29 and April 10, 2007 for the forest, and this rapid thawing may be one of the possible causes for the large ice jam flood in Markha in 2007.

PALSAR-2 (Phased Array type L-band Synthetic Aperture Radar-2) is a spaceborne L-band SAR (Synthetic Aperture Radar) system installed on Japanese Advanced Land Observing Satellite-2 (ALOS-2). PALSAR-2 is expected to provide valuable data for global monitoring and disaster monitoring. To meet the variety of demands, PALSAR-2 provides various operational modes. This paper describes the overview of the calibration plan of PALSAR-2. Since PALSAR-2 have more than 1,000 operational modes, effective and efficient procedure is crucial. The process is divided in three different phases; pre-launch calibration, check-out phase (C/O phase) after the launch, and image calibration phase. The overview of each phase is described.

Tandem-L is a proposal for an innovative interferometric radar mission to monitor the Earth system and its intricate dynamics. Important mission objectives are global inventories of forest height and above-ground biomass, largescale measurements of Earth surface deformations due to plate tectonics, erosion and anthropogenic activities, observations of glacier movements and 3-D structure changes in land and sea ice, and the monitoring of ocean surface currents. A detailed description of the mission goals can be found in [1]. The mission concept is based on co-flying two fully-polarimetric L-band SAR satellites in a close formation. Tandem-L employs new techniques and advanced technologies to achieve its ambitious mission goals. The feasibility of a joint DLR/JAXA mission is currently being investigated in the scope of a pre-phase A study. This paper provides an overview of the Tandem-L instrument design concept and its performance predictions. Innovative aspects like the employment of advanced digital beamforming techniques and operation in a variety of imaging modes are detailed.

In this study, we examine the applicability of digital surface model (DSM) generated from ALOS PRISM data for mapping forest above ground biomass (AGB). We obtained the digital canopy height model (DCHM) by calculating the differences between the PRISM DSM and surveying-based digital elevation model (DEM), and investigated the relationship between the DCHM values and field measured mean tree height and AGB in Northern Hokkaido, Japan. The results show a strong linear relationship between the field measured AGB and PRISM-DCHM (R = 0.872, n = 25). The RMSE and bias of the regression model, which were evaluated by the leave-one-out cross validation, are 38.1 t/ha (22 %) and -0.2 t/ha, respectively. Saturation at high AGB is not shown. We also demonstrate the wall-to-wall AGB mapping by using the regression model and the PRISM DCHM image. A pan-sharpen image generated from PRISM and AVNIR-2 images is utilized for forest cover mapping. The PRISM-based AGB values are generally reasonable except for high mountain areas. The relationship between the PRISM AGB and backscattering coefficient measured by L-band synthetic aperture radar (PALSAR) is consistent with the regression models discovered by the previous researches.

This paper describes SAR system design of the Advanced Land Observing Satellite-2 (ALOS-2), which is a next-generation Japanese L-band SAR satellite. Since one of an important mission of ALOS-2 is a global monitoring using its unique frequency of L-band, a capability of wider coverage is required. On the contrary, in the point of disaster monitoring especially for urban area, relatively higher spatial resolution is essential. To comply with such a contradictive requirement of wide swath and high resolution, ALOS-2 utilizes a dual-receive channel (DRC) technique, and achieved a coverage area of up to 50km with a spatial resolution of down to 3m. In the paper, the H/W design of ALOS-2 DRC mode is explained. For a wider coverage of polarimetric observation, ALOS-2 installs the fully redundant and “quad-receive channel” system to full-polarimetric mode, achieving a maximum coverage of 50km at 6m resolution. As an experimental mode, new polarimetric mode called “compact polarimetry” is installed for a wide coverage of polarimetric observation.

The Advanced Land Observation Satellite-2 (ALOS-2) will be launched in 2013 and will carry an L-band synthetic aperture radar (PALSAR-2) to a polar orbit with an altitude of 628 km and 14-day revisit time. Four mission objectives are disaster mitigation, environmental monitoring as represented by forest and cryospheric monitoring, land monitoring, and technology development. PALSAR-2 onboard ALOS-2 will provide 1-3-m high-resolution Spotlight and Strip with multiple polarizations with an imaging swath of 25/50/70 km, ScanSAR with dual polarizations with a 350/490 km swath, a shorter temporal baseline of 14 days and spatial baseline of within 1 km, emergency observation service within a 12-h delay for any global target and especially within a 72-h (74 h in the worst case) delay as synchronized observation with the archives, i.e., same off-nadir and observation mode, and ScanSAR interferometry with more than 90% global beam synchronization. The ALOS-2 science program initiates the calibration, validation, and application research of PALSAR-2/ALOS-2 and Pi-SAR-L2. As application research, disaster mitigation and the urban-area monitoring using the high-resolution data should contribute significantly to safety since disasters have occurred frequently and globally in the recent past. High-resolution and multi-polarimetric SAR with a shorter revisit time ensures quicker detection of land changes. In this paper, we summarize the contents of the ALOS-2 science program and its expected outcomes. Some application examples of disaster mitigation using recent high-resolution SARs, i.e., Pi-SAR-L2 and PALSAR, are also introduced.

The spatiotemporal distribution of subsidence at Palangkaraya, Central Kalimantan, Indonesia, was studied by a time-series analysis of PALSAR data obtained over 26 passes of ALOS over the study area. This area consists mainly of peatland and tends to subside because of climate change, i.e., global warming. Applying a moving weighted window to the stacking of a DinSAR dataset, each of which was calibrated using stable points in the image, we quantitatively captured subsidence phenomena and found that the area has subsided at an average rate of 2.02 cm/yr .

This paper describes the performance, calibration method, and observation scenarios for the ALOS-2/PALSAR-2 polarimetry mode. It also describes simulation studies conducted using data from Pi-SAR-L2, JAXA's L-band airborne SAR, for calibration and application studies.

The Advanced Land Observing Satellite-2 (ALOS-2) carries the state-of-the-art L-band Synthetic Aperture Radar (SAR) called PALSAR-2 which succeed to the ALOS / PALSAR. Since more acquisition modes of PALSAR-2 than those of PALSAR may trigger more conflicts among user requests, systematic acquisition strategy is very important to achieve the mission requirements. For example, trade-off studies have been made for INSAR basemap data acquisition through discussion with user groups, and an optimum scenario was proposed to fulfill both requirements for quick response and time-series data acquisition under a same condition (incidence angle, descending/ascending, left/right look). As the ALOS data resulted in a comprehensive and homogeneous global archive, consistent data archives will be requested for ALOS-2 as well. This paper describes a draft acquisition strategy for PALSAR-2.

Aboveground (AG)-biomass was estimated from a field biomass collection and LiDAR observations for a natural forest in Indonesia. The derived AG-biomass data were plotted against full polarimetric parameters calculated from Polarimetric and Interferometric Airborne Synthetic Aperture Radar L2 (Pi-SAR-L2) and PALSAR data. The α°-AG-biomass curve shows saturation by around 100 tons/ha, while for entropy, correlation is observed up to 200 tons/ha. The largest coefficient of determination (R2= 0.2348) was observed for the range with AG-biomass of more than 100 tons/ha for the relation between AG-biomass and entropy. The α°HV-biomass plot derived from PALSAR data shows smaller variance in the dry season than in other seasons, indicating that dry season data is preferable for a more accurate estimate of AG-biomass.

Deorientation processing has been incorporated into model-based decomposition to cure the overestimation of volume scattering contribution, by rotating the coherency matrix to minimize the cross-polarization term. First, the derivation of the rotation angle is clarified for avoiding the ambiguity. Moreover, even with the implementation of deorientation processing, oriented built-up areas with large orientation angles are still misjudged as volume scattering dominant. Further to the investigation of the deorientation effect, we focus on oriented built-up patches. A parameter, named dominant polarization orientation angle (DPOA), is introduced to label each patch. The behavior of the deorientation on coherency matrix and model-based decomposition over purely oriented built-up areas with respect toDPOAis disclosed. Experimental studies from the Advanced Land Observing Satellite/Phased Array type L-band Synthetic Aperture Radar (ALOS/PALSAR) polarimetric SAR data set demonstrate that model-based decompositions with deorientation work well for oriented built-up areas when |DPOA| ≤ 22.5°. However, for large |DPOA| (e.g., |DPOA| >; 22.5°), even with the deorientation processing, for the conventional decompositions which assume that only the volume scattering contributes to the cross-polarization term, the decomposed volume scattering power may also be dominant even for purely oriented built-up areas. Thereby, misinterpretation still occurs, motivating further advancements.

In the present paper, we propose the application of a differential synthetic aperture radar interferometry (DInSAR) technique to retrieve the volume changes of the damaged area and the volcanic sediment on the sloped surface of Merapi volcano, Indonesia, which erupted on October 26 and November 4, 2010. This technique was used to investigate the thickness of volcanic ash and the volume change of post-ejected wet lava (sand and rock) surrounding Merapi volcano by assessing L-band ALOS PALSAR data. The results reveal the volume of the damaged area, or deformation, and the volume of sedimentation in the study area are 1.4 million and 2.2 million m3, respectively, and indicate that the radius of the dangerous area is 15.6 km.

The Advanced Land Observing Satellite (ALOS, nicknamed `Daichi') was launched on January 2006, and has operated very well. However, its operation moved to the low load mode (LLM) since April 22, 2011, and was subsequently followed by an official termination on May 12, 2011. Notwithstanding, approx. 6,500,000 scenes of archived data covering the entire globe are available to users. Therefore the calibration result is still important information for users. This paper describes calibration results of two optical instruments called PRISM and AVNIR-2 onboard ALOS are summarized during whole mission period. The previous result has been published in 2009, which was explained an overview of calibration and validation plan, and their results at that time. As the updated calibration results, we confirmed 6.1 m (root mean square error, RMSE) for PRISM nadir-looking radiometer and 21.9 m (RMSE) for AVNIR-2 0 deg. pointing of absolute geometric accuracies, and no significant degradation on radiometric accuracy.

Japan is one of the main forest countries in the developed countries. For management and administration of the forest, amount of cost and work is needed to be observed vast woodland with regularity. Since the earth observation satellites can repeatedly observe wider area at one time is significant, they are suitable for observing the boundless natural environment. It is important for forest management and forest industry to measure forest area and height of trees. In this study, tree height was calculated using digital surface model (DSM) generated by the image taken by the Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) onboard the Advanced Land Observing Satellite (ALOS), which was launched by the Japan Aerospace Exploration Agency (JAXA) on January 24, 2006. This paper reports procedure of calculating trees height using the DSM generated by the PRISM and its validation.

The 2011 off the Pacific coast of Tohoku earthquake was observed using phased array type L-band synthetic aperture radar (PALSAR) and polarimetric and interferometric airborne synthetic aperture radar (PiSAR) full-polarimetric data. Representative polarimetric parameters were calculated from full-polarimetric data for urban areas, where most of the buildings were destroyed by the subsequent tsunami, in order to identify the radar scattering mechanism in these areas. These parameters were compared with the ones observed before the disaster. The full-polarimetric data analysis shows that the affected areas were represented by surface scattering with high entropy, indicating that a complex scattering mechanism with nonreflection symmetry is involved. The coherence between HH and VV and that between RR and LL are the most important factors in distinguishing the disaster areas from the data. Alpha angle and anisotropy are also important factors in this respect; however, anisotropy derived from PiSAR data does not show the difference between areas with collapsed and still-standing buildings. This may be because the azimuth slope angle for the target urban area is different before and after the disaster for both PALSAR and PiSAR data. Owing to the double-bounce scattering from azimuthally rotated targets in the urban areas, the power estimated from the four-component decomposition model is distributed within a wide range not only for double-bounce scattering but also for volume and surface scatterings. Additionally, the model does not show a systematic change between before and after the disaster, and σ0for four polarizations with 30-m resolution does not show a systematic difference.

In this paper, the long-term consecutive differential interferometric synthetic aperture radar (SAR) technique is used to measure the volume change during land deformation. This technique was used to investigate the subsidence of Bandung city, Indonesia, by assessing the data from two Japanese L-band spaceborne SARs (Japanese Earth Resources Satellite 1 SAR and Advanced Land Observation Satellite Phased Array type L-band Synthetic Aperture Radar) during the periods of 1993–1997 and 2007–2010. The results are confirmed using GPS observation data, ground survey data, local statistics, ground water level trend data, and the geological formation of the study area. The obtained results reveal a close correlation between the subsidence measurements and changes in the ground water level due to water pumping, population growth, industry growth, and urbanization of the study area.

The first bistatic SAR experiment between Japanese spaceborne PALSAR and airborne Pi-SAR-L was successfully performed and gave an excellent image in 2010. This paper mainly reports the result of this bistatic SAR experiment and its data analysis. As the result of the analysis, two conclusions are confirmed. One is the success of the bistatic SAR observation without special functions for them and the other is the advantage of this bistatic SAR observation.

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.

This paper proposes a new polarimetric Synthetic Aperture Radar (PolSAR) calibration method that applies an incoherent decomposition model to the uncalibrated covariance data measured for the forest and surface, and determines the polarimetric distortion matrix (PDM). The Freeman-Durden model [1] is used to express the polarization dependent signal reflection from and penetration through the forest. Non-linear equations built for uncalibrated PolSAR data are solved iteratively. This method is applicable to the lower frequency SAR that associates with the polarization dependent signal penetration through forest canopies. Using the time series Phased Array Type L-band SAR (PALSAR) data acquired for the Amazon rainforest for around 3 years, we confirm that the proposed method succeeds the PDM estimation and that the calibrated data preserve the polarimetric performance on HH-VV orthogonality, low cross-talks, and ideal polarimetric signature for the corner reflector.

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.

The objective of this study is to develop new glacial lake inventory to understand existing condition using the optical imageries of the Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) and the Advanced Visible and Near Infrared Radiometer type 2 (AVNIR-2) onboard the Advanced Land Observing Satellite (ALOS, nicknamed "Daichi"). Glacial lakes can be caused outburst flood when natural dams terminated by moraines are broken, and it represents serious hazard damage in downstream regions. Problems of glacial lake outburst floods (GLOFs) are that anyone does not know when it will occur and how much damage causes by it. To contribute these problems, new glacial lake inventory is currently developing in the Bhutan Himalayan using ALOS imageries. This paper describes procedure of the inventory development including image processing that introduces pan-sharpened and ortho-rectified images by PRISM and AVNIR-2, glacial lakes extraction, and its validation.

The goal of the paper is to demonstrate radiometric stability of PALSAR instrument on 4 years time interval using new type of calibration targets strong passive scatterers of both artificial and natural origin. Artificial targets used in our study were parabolic antennas located at Special Design Bureau of Moscow Power Engineering Institute (SDB MPEI) calibration site. Natural calibration targets we selected for calibration were bright scattering objects identified in urban and industrial areas near SDB MPEI calibration site in Moscow region, Russia.

The Japan Space Exploration Agency Kyoto and Carbon (K&C) Initiative seeks to demonstrate the potential of the Advanced Land Observing Satellite (ALOS) Phased Arrayed L-band Synthetic Aperture Radar (PALSAR) data for addressing regional applications relating to climate change, carbon cycle science, and environmental conservation. This paper outlines the generation of a regional dual-polarization (HH and HV) mosaic for the entire African continent at spatial resolution on the order of 100 m. The main computational and radar science issues undertaken to generate a seamless mosaic with good radiometric and geometric accuracy are summarized. Preliminary investigations into the thematic information provided by the K&C Africa mosaic and comparisons with the JERS-1 SAR mosaic generated as part of the Global Rain Forest Mapping Project are reported, with emphasis placed on characterizing and detecting change in forests and savannas.

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 paper proposes a new polarimetric synthetic aperture radar (SAR) (PolSAR) calibration method that applies an incoherent decomposition model to the uncalibrated covariance data measured for the forest and surface and determines the polarimetric distortion matrix (PDM). The Freeman-Durden model is used to express the polarization-dependent signal reflection from and penetration through the forest. Nonlinear equations built for uncalibrated PolSAR data are solved iteratively. This method is applicable to the lower frequency SAR that associates with the polarization-dependent signal penetration through forest canopies. Using the time series Phased-Array-Type L-band SAR (PALSAR) data acquired from the Amazon rainforest for around three years, we confirm that the proposed method succeeds in the PDM estimation and that the calibrated data preserve the polarimetric performance on HH-VV orthogonality, low crosstalks, and ideal polarimetric signature for the corner reflector. This paper also investigates the signal-penetration properties of the forest associated with the L-band SAR.

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%.

The Advanced Land Observing Satellite (ALOS) was developed for detailed observation of the Earth's surface and frequent monitoring of global environmental changes, using high-resolution optical (visible and near infrared push-broom) and active microwave sensors (L-band synthetic aperture radar). ALOS has four mission objectives: cartography, regional observations, disaster observations, and resource exploration. It has been operational since its launch in January 24, 2006, and is acquiring a large amount of land-surface data supported by the Ka-band intersatellite communication system that downlinks to ground receiving stations. A global systematic acquisition strategy is implemented for all three sensors to enable consistent data collection over all land areas on a repetitive basis. Through its three sensors, acquisition strategy, and communication infrastructure, the ALOS mission is aimed to contribute to monitoring water, carbon, and global climate change. In this paper, we describe ALOS and its contribution to global environmental monitoring.

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.

We investigate an effective algorithm to identify flood-inundated area with ALOS/PALSAR observations. Radar cross section from water surface is generally smaller than that from ground surface without water, which derives larger differences of radar cross section in flood-inundated area because there is no water in this area before disaster. Variances of differences in 3×3 pixels are also enough to identify flood-inundated area, and more effective algorithm to identify flood-inundated area will be obtained by taking radar cross section differences and variances of differences into account.

Frozen ground is a sensitive indicator of how our home planet is changing. In the meantime, new spaceborne SAR systems have been launched, such as the polarimetric PALSAR sensor onboard ALOS in January 2006. In this paper, the relevance of L-band polarimetric SAR data for extracting information on frozen ground is presented. Dealing with ground assessments, the necessity for a validated Electromagnetic (EM) model is of importance. The adequation between Oh's po-larimetric EM model and PALSAR data is first studied over agricultural bare fields in Hokkaido, Japan. The assessment of residual liquid water can be realized by means of bare soil EM backscattering model. Over natural wildland area, an approach is proposed in order to tackle the effect of the vegetation or other irrelevant effects. The monitoring of permafrost active layer is performed over the ANWR, Alaska.

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.

Because of the higher interferometric coherence, ALOS/PALSAR data are often used for monitoring the deformation caused by the disaster events (i.e., earthquakes, volcanoes, land subsidence by water and oil pumping, land slide, etc) using the interferometric data analysis. JAXA has been a member of the international charter, and responds to the charter calls for the emergency call. In this paper we will introduce the responses to the charter call events and the data examples generated and distributed to the disaster event as the interferometric SAR products.

The Advanced Land Observing Satellite (ALOS, nicknamed ¿Daichi¿) was successfully launched on January 24, 2006, and continues to work very well. In this paper, we introduce the updating calibration results and their time trends of the standard products for two optical instruments onboard ALOS, the Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) and the Advanced Visible and Near Infrared Radiometer type-2 (AVNIR-2). Geometric calibration is important in generating a precise digital surface model (DSM) by a stereo pair image of PRISM. Relative geometric calibration of both PRISM and AVNIR-2 are conducted by evaluating accuracies within one scene and evaluating sensor alignments as absolute calibration. For absolute geometric accuracies, we achieved 7.8 m for nadir-, 8.0 m for forward-, 18.7 m for backward-looking images of PRISM, and 114.2 m for AVNIR-2, respectively.

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.

The Advanced Visible and Near Infrared Radiometer type 2 (AVNIR-2) on-orbit radiometric performance has been improved through the comparison of cross-calibration and onboard lamp calibration. We proposed a new cross-calibration scheme which uses top-of-atmosphere reflectance functions of satellite zenith angle at temporally and spatially stable ground sites. Each function is made from Moderate Resolution Imaging Spectroradiometer (MODIS) 500-m resolution data over 16 days, which includes AVNIR-2 observation dates. The results showed that the radiances of AVNIR-2 bands 1 (463 nm), 2 (560 nm), and 3 (652 nm) agreed with the radiances of Aqua and Terra MODIS within 3% accuracy (standard deviation of 2%). AVNIR-2 band 4 (821 nm) had a difference of about 7% (AVNIR-2< MODIS) due to water-vapor absorption which could explain more than half of the 7%. Using many samples from this scheme, we found dependences of radiometric calibration errors within the field of view (FOV) and for different gain modes. The lamp calibration system onboard AVNIR-2 unveiled these dependences over the FOV and time. Furthermore, for the gain mode, consistent results could be retrieved using the cross-calibration scheme. The retrieved radiometric correction factors (over the FOV and gain modes) have been applied to the Japan Aerospace Exploration Agency AVNIR-2 processing scheme. The subsequent validation of the correction showed, for polar snow areas, an improved radiometric performance over the entire FOV.

The Scanning Synthetic Aperture Radar (ScanSAR) is very useful for Earth observation because of its wider imaging swath and shorter revisit time. However, ScanSAR is sometimes affected by the following three artifacts: (1) scalloping, which often appears as repeating weak azimuth stripes at both edges of the focused burst image; (2) azimuth ambiguity (i.e., a form of ghosting that appears over the adjacent uniform area when the pulse repetition frequency is below the Doppler bandwidth); and (3) radiometric discontinuity (i.e., banding) between two adjacent scans. This paper proposes three methods to correct these artifacts, which are, specifically, the proposal for scalloping correction using Amazon Rainforest data, band limitation, and the correction for the inter SCAN banding using the dynamic gain correction algorithm. Several corrected sample data sets of the Phased-Array L-band SAR onboard the Advanced Land-Observing Satellite are presented to demonstrate the validity of the proposed methods.

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 17 papers in this special issue focus on the calibration and validation of ALOS sensors and their use for bio- and geophysical parameter retrievals.

The Advanced Land Observing Satellite [(ALOS); nicknamed ldquoDaichirdquo] was successfully launched on January 24, 2006, and it continues to work very well. This paper describes the calibrations of two optical instruments onboard ALOS, which are the Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) and Advanced Visible and Near-Infrared Radiometer type 2 (AVNIR-2). PRISM consists of three panchromatic radiometers and is used to derive a digital surface model (DSM) with high spatial resolution, which is an objective of the ALOS mission. AVNIR-2 has four radiometric bands from blue to near infrared, which are used for investigating regional environment issues such as land-use and land-cover classifications, and disaster monitoring. In this paper, we introduce the calibration and validation plan, methodologies, accuracy assessments of the standard products, image quality evaluations for PRISM and AVNIR-2, and their results. Geometric calibration is important in generating a precise DSM by a stereo pair image of PRISM. The relative geometric calibrations of both PRISM and AVNIR-2 are conducted by evaluating accuracies within one scene and evaluating sensor alignments as absolute calibration. For absolute geometric accuracies, we achieved 8.1 m for nadir-looking images and 9.3 m for forward- and backward-looking images of PRISM; we also achieved 114.2 m for AVNIR-2. PRISM is also radiometrically calibrated both relatively and absolutely. PRISM relative radiometric calibration is accomplished by using acquired images over homogeneous targets, such as oceans, deserts, ice, and snow areas, as well as nighttime observation. Simultaneously observed images with calibrated AVNIR-2 are used for absolute radiometric calibration by cross-calibration. The absolute radiometric accuracy of the PRISM nadir-looking radiometer is similar to that of AVNIR-2.

Polarimetric Phased-Array-type L-band Synthetic Aperture Radar (PALSAR) system parameters are assessed using data sets collected over several calibration sites. The data collected over the Amazonian rain forest help validate the hypothesis that Faraday rotation is zero near the equator. The analysis of the Amazonian forest data and the response of the corner reflectors deployed there during the PALSAR acquisitions lead to the conclusion that the antenna is highly isolated (better than -35 dB). These results are confirmed using the data collected over calibration sites located in Sweden and Canada. The 5-m-height corner reflector deployed at the Remningstorp (Sweden) calibration site by Chalmers University of Technology provides accurate measurement of antenna parameters and detection of a (2deg -3deg) Faraday rotation during day-time acquisitions, whereas no Faraday rotation was noted during night-time acquisitions. Small Faraday rotation angles (2deg-3deg) have been measured using acquisitions over the DLR Oberpfaffenhofen and the Ottawa calibration sites. The presence of small but still significant Faraday rotation (2deg-3deg) induces a corner reflector return at the cross-polarization HV and VH that should not be interpreted as the actual antenna crosstalk. These results show that the PALSAR antenna is highly isolated (better than -35 dB), and diagonal antenna distortion matrices (with zero crosstalk terms) can be used for accurate calibration of PALSAR polarimetric data.

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.

Snow classification using full-polarimetric PALSAR data is investigated in this paper. It is first demonstrated that dry snowpack over frozen ground slightly affects polarimetric signature at L-band. Given the fact that PALSAR data do not permit the use of a simplistic threshold-based method, a refined method for Snow Covered Area mapping is outlined. A supervised Support Vector Machine approach is used showing fairly good results within the framework of a three-classes classification (dry snow over frozen ground, wet snow and no snow).

A cross-calibration scheme which uses top-of-atmosphere (TOA) reflectance functions of satellite zenith angle at temporally and spatially stable ground sites is proposed. Each function is made from MODIS 500m-channel observations over 16 days which includes AVNIR-2 observation dates. The results showed that radiances of AVNIR-2 channels 1 (463 nm), 2 (560 nm), and 3 (652 nm) agreed to the radiances of Aqua and Terra MODIS channels 3 (466 nm), 4 (554 nm) and 1 (646 nm) respectively within 5% accuracy. AVNIR-2 channel-4 (821 nm) decreased more than 5% by water-vapor absorption in some cases. Using many samples from this scheme, we found possible gain dependencies on Field Of View (FOV) and gain-modes. Lamp calibration system onboard AVNIR-2 showed dependencies on FOV, time change of the FOV error, and gain-mode consistent with the cross-calibration results. After correction of the identified errors, inter-channel consistency of FOV in the polar-snow scenes was improved.

We have examined the capability of the PALSAR SCANSAR SCANSAR interferometry by observing the African forest and Sahara desert, both of which are separated 46 days in March and April of 2008. These two paths are well tuned for the orbital tube of 200 m and the beam synchronization of the transmission positions in 200 m to 500 m, we have succeeded the PALSAR SCANSAR SCANSAR interferometry and achieved the detection of the height information. We will report the results in this paper.

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.

We discovered anomalous stripes over the large area of Amazon when the region was scanned by the radar (PALSAR) onboard ALOS satellite. The stripes appeared on the local midnight along the geomagnetic field line with a typical characteristic width of 600 m.

The Advanced Land Observing Satellite (ALOS, nicknamed "Daichi") was successfully launched on January 24, 2006 and it continuously working very well. This paper introduces the updated results of calibration for two optical sensors of ALOS i.e. the Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) and the Advanced Visible and Near Infrared Radiometer type-2 (AVNIR-2). PRISM consists of three panchromatic radiometers, and is using to derive a digital surface model (DSM) that is topography and terrain height information with high spatial resolution. Therefore, geometric calibration is important in generating a highly accurate DSM by stereo pair image of PRISM. The radiometric calibration is also important for PRISM as well as AVNIR-2. This paper describes the updated results of geometric and radiometric calibrations and image quality evaluation of PRISM and AVNIR-2 in the operational phase, which are including stability or time trend of accuracies during 2.5 years since launch the ALOS.

The algorithm for generating digital surface model (DSM) from PRISM was developed for Earth Observation Research Center in Japan Aerospace Exploration Agency (EORC/JAXA). The geometric model stability and accuracy of PRISM have been calibrated for the DSM generation. The interior parameters of PRISM geometry are CCD alignment models and calibrated by the self-calibrations with dense ground control points (GCPs). The exterior parameters of PRISM geometry consist of the orbit data measured by the onboard GPSR, the satellite attitude data measured by the onboard star tracker and sensor alignment models. Those exterior parameters have been calibrated with GCPs as well. The accuracies of DSM generated from those PRISM geometric models are presented with the results of the comparison with high accuracy and high resolution reference DSM data sets derived from LiDAR and aerial photo at the various terrain features.

Polarimetric PALSAR system parameters are assessed using data sets collected over various calibration sites. The data collected over the Amazonian forest permits validating the zero Faraday rotation hypotheses near the equator. The analysis of the Amazonian forest data and the response of the corner reflectors deployed during the PALSAR acquisitions lead to the conclusion that the antenna is highly isolated (better than -35 dB). Theses results are confirmed using data collected over the Sweden and Ottawa calibration sites. The 5-m height trihedrals deployed in the Sweden calibration site by the Chalmers University of technology permits accurate measurement of antenna parameters, and detection of 2-3 degree Faraday rotation during day acquisition, whereas no Faraday rotation was noted during night acquisition. Small Faraday rotation angles (2-3 degree) have been measured using acquisitions over the DLR Oberpfaffenhofen and the Ottawa calibration sites. The presence of small but still significant Faraday rotation (2-3 degree) induces a CR return at the cross-polarization HV and VH that should not be interpreted as the actual antenna cross-talk. PALSAR antenna is highly isolated (better than -35 dB), and diagonal antenna distortion matrices (with zero cross-talk terms) can be used for accurate calibration of PALSAR polarimetric data.

We assess the spatial resolution and phase noise of interferograms made from L-band Advanced Land Observing Satellite (ALOS) synthetic-aperture-radar (SAR) data and compare these results with corresponding C-band measurements from European Space Agency Remote Sensing Satellite (ERS). Based on cross-spectral analysis of phase gradients, we find that the spatial resolution of ALOS interferograms is 1.3times better than ERS interferograms. The phase noise of ALOS (i.e., line-of-sight precision in the 100-5000-m wavelength band) is 1.6times worse than ERS (3.3 mm versus 2.1 mm). In both cases, the largest source of error is tropospheric phase delay. Vector deformation maps associated with the June 17, 2007 (Father's day) intrusion along the east rift zone of the Kilauea Volcano were recovered using just four ALOS SAR images from two look directions. Comparisons with deformation vectors from 19 continuous GPS sites show rms line-of-site precision of 14 mm and rms azimuth precision (flight direction) of 71 mm. This azimuth precision is at least 4times better than the corresponding measurements made at C-band. Phase coherence is high even in heavily vegetated areas in agreement with previous results. This improved coherence combined with similar or better accuracy and resolution suggests that L-band ALOS will outperform C-band ERS in the recovery of slow crustal deformation.

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 describes the system and experiment of Pi- SAR(L) repeat pass interferometric SAR To obtain a high- quality interferometric image, it is necessary to make two flights on the same pass and observe in the same direction. We built a flight control system utilizing the preinstalled autopilot. This system measures position and altitude precisely with using a differential GPS, and controls the flight pass to be within virtual tube of 10 m diameter. The antenna rotation mechanism was also installed to control the observation direction. The repeat-pass flight has been conducted many times. The flights were stable and the deviation was within a few meters for both horizontal and vertical even in the gusty condition. The SAR data were processed in time domain based on range Doppler algorism to make the complete motion compensation. The interferometric image processed after precise phase compensation is shown.

The ALOS Kyoto & Carbon Initiative is an international collaborative project led by the JAXA Earth Observation Research Center (EORC). It forms the continuation of JAXA's on-going JERS-1 SAR Global Rain Forest and Global Boreal Forest Mapping project(GRFM/GBFM) into the era of the Advanced Land Observation Satellite (ALOS). The ALOS K & C Initiative has been set up to support the data and information needs required by international environmental Conventions; Carbon Cycle scientists and Environmental Conservation programs (referred below to as the CCCs). Led and coordinated by EORC JAXA, the Initiative is being undertaken by an international Science Team and focuses primarily on defining and optimizing the provision of data products and validated thematic information derived from in-situ and satellite sensors focusing on data acquired from the Phased Array L-band Synthetic Aperture Radar (PALSAR) on-board the Advanced Land Observing Satellite (ALOS). The objective of the ALOS K & C Initiative is to define, develop and validate thematic products derived from ALOS PALSAR data that can be used to meet specific information requirements relating to the CCCs. A key component of this work has been the development of a systematic data acquisition strategy for ALOS which comprises fixed, systematic global observation plans for PALSAR. The strategy is implemented as a top-level foreground mission and with a priority level second only to that of emergency observations. With emphasis on acquiring repetitive and consistent data over continental scales, it ensures that adequate data will be collected to allow the required thematic output products to be developed on a timely basis. The K & C Initiative is based on the three coordinated themes relating to global biomes; Forests, Wetlands, Deserts and Semi-Arid Regions, and a fourth theme dealing with the generation of regional ALOS PALSAR Mosaics. A key word for the Initiative is regional- scale applications and product development, with data requirements in the order of hundreds or thousands of PALSAR scenes for each prototype area. Each theme has identified key products that can be generated from the PALSAR data including land cover, forest change mapping and forest biomass and structure analysis; global wetland inventory compilation and landscape change determination; and freshwater resources and desertification. Each of the products developed will be generated using a combination of PALSAR imagery, in situ measurements and ancillary datasets.An international Scientific Advisory Panel has been established to maintain the scientific relevance of project design and to ensure alignment with other relevant international efforts (e.g. GOFC/GOLD, IGOL, GTOS/TCO). The panel consists of scientists active in the fields of carbon modeling and biophysical parameter retrieval; SAR and image processing, as well as and representatives from GOFC, TCO, FAO, space agencies, universities and public research institutions.

PALSAR PolInSAR capability was evaluated. One of the important capabilities that the PolInSAR offers is to estimate the forest height. For one-year and more months after the launch of the ALOS on Jan. 24 2006, PLASAR observed several test areas using the polarimetry modes repeatedly. We applied the PolInSAR method to retrieve the forest heights of the four test sites in Japan and Amazon. In this paper, we introduce an applied method and results. The results show that the forest tree height can be estimated with good accuracy.

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.

The Advanced Land Observing Satellite (ALOS, the nickname is “Daichi”) was successfully launched on January 24th, 2006, and it continuously working very well. This paper introduces the updated results of calibration for two optical sensors of ALOS i.e., the Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) and the Advanced Visible and Near Infrared Radiometer type-2 (AVNIR-2). PRISM consists of three panchromatic radiometers, and is used to derive a Digital Surface Model (DSM) with high spatial resolution, which is also an objective of the ALOS mission. The geometric calibration is important in generating a highly accurate DSM by stereo pair image of PRISM. The radiometric calibration is also important for PRISM as well as AVNIR-2. This paper describes the results of geometric and radiometric calibrations for PRISM and AVNIR-2 in the operational phase after initial calibration phase, which are including methodology of analysis and experiment, update parameters related to the absolute accuracy, stability evaluations during one and half years after the launch, and accuracy assessment plan during mission life of the ALOS.

PRISM carried at ALOS satellite is expected to generate worldwide topographic data in respects of its high resolution and stereoscopic observation. The algorithms for generating Digital Surface Model (DSM) and Ortho-Rectified Image (ORI) have been developed for those objectives in Earth Observation Research Center / Japan Aerospace Exploration Agency (EORC / JAXA). During first one year following the successful ALOS launch, the capabilities of the algorithm have been widely tested. In this paper, the performance analysis intermediate results of DSM and corresponding ORI processing are described. First, the geometric model analysis of PRISM sensor is presented with the experimental results of the orientation processing. Then, the performance analysis of DSM and ORI generated with the PRISM geometric model is presented. The accuracy assessment results of generated DSM are presented from the comparison with high accuracy and high resolution reference DSM data sets of LiDAR DSM and Aerial Photo DSM. The accuracy assessment results of generated ORI are presented from the comparison with GCP.

JERS-1/SAR images taken in 1990’s and ALOS/PALSAR images taken in 2000’s are used and examined the deforestation status during ∼14 years. Many trees had been fallen by a typhoon hit in 2004 in a test site, Tomakomai. There is also a plantation area and the site show active change during the term. The forest stands could be roughly classified for four types, forest stands, vacant, where almost all trees were carried out, and two types of transitional stands from a forest to a vacant. Many deforested areas are easily detected by using the difference of backscattering coefficients between two images, if fallen trees have been carried out from the stands. The change from the normal forest to the vacant stands causes 3.1dB decrease in the σ0HH. On the other hands, transitional stands show almost same backscattering as the normal forest stands, although. Threecomponent scattering model shows surface scattering component accounts for 50% over the vacant stands, while volume scattering component accounts for ∼60% over the forest stands. But the model doesn’t show the clear difference between transitional forest site and normal forest. The temporal changes of the forest during 14 years are also examined for the plantation area. One stand show gradual increase of σ0and the values seem to be saturated around 17.4 tons/ha (∼5m in average height).

The Advanced Land Observing Satellite (ALOS) is Japan's new-generation Earth Observation satellite, launched in January 2006 by the Japan Aerospace Exploration Agency. ALOS carries two optical instruments (Panchromatic Remote-sensing Instrument for Stereo Mapping and Advanced Visible and Near-Infrared Radiometer type 2) and, to maintain Japan's commitment to spaceborne L-band Synthetic Aperture Radar (SAR), the Phased Array L-band SAR (PALSAR). The successor to the SAR onboard the Japanese Earth Resources Satellite (1992-1998), the PALSAR instrument provides enhanced sensor characteristics, including full polarimetry, variable off-nadir viewing, and ScanSAR operations, as well as significantly improved radiometric and geometric performance. As important as the technical improvements and the reason PALSAR here is referred to as a pathfinder mission for global environmental monitoring is the systematic data-acquisition strategy which has been implemented for ALOS. With a priority second only to emergency observations, the PALSAR observation strategy has been designed to provide consistent, wall-to-wall observations at fine resolution of all land areas on the Earth on a repetitive basis, in a manner which has earlier been conceived only for coarse- and medium-resolution instruments.

This paper discusses an ambiguity resolution of polarimetric calibration parameter. Since ALOS was successfully launched on January 24, 2006, the utilization of polarimetric data observed by PALSAR is expected for various remote sensing applications. Thus, polarimetric calibration becomes important issue. However, there is a possibility that calibration algorithm has a 180deg sign ambiguity with respect to cross-polarized components of a calibrated scattering matrix. The reason is that two polarimetric calibration parameter sets are derived. On the other hand, we found that a 180deg phase shift of cross-polarized component occurred due to the change of an angle between a direction parallel to a building wall and a radar line of sight in azimuth plane. Thus, we examined that this scattering property was applied for selecting a correct polarimetric calibration parameter set. The experimental result shows that urban structures can be used for polarimetric calibration.

This paper describes the initial results of the PALSAR characterization using the data acquired in the commissioning phase for the five modes of FBS, FBD, DSN, SCANSAR and POL, and using the active radar calibrator deployed at the calibration site in Japan. This paper also describes the radiometric and geometric performances of the PALSAR images shortly. This paper will end up with the parameters which should be evaluated and determined within the calibration phase.

The advanced land observing satellite (ALOS, the nickname is "Daichi") was successfully launched on January 24th, 2006. This paper introduces the initial results of calibration and validation for two optical sensors of ALOS i.e., the panchromatic remote-sensing instrument for stereo mapping (PRISM) and the advanced visible and near infrared radiometer type-2 (AVNIR-2). PRISM consists of three panchromatic radiometers, and is used to derive a digital surface model (DSM) with high spatial resolution, which is also an objective of the ALOS mission. The geometric calibration is important in generating a highly accurate DSM by stereo pair image of PRISM. The radiometric calibration is also important for PRISM as well as AVNIR-2. The relative radiometric calibration will be done using acquired images over homogeneous targets such as ocean, deserts, ice and snow areas and the nighttime observation. The absolute radiometric calibration will be carried out by the cross calibration using with calibrated satellite images i.e., MODIS, ASTER etc. In this paper, results of the first images acquisition and initial analysis for calibration and validation are described.

PALSAR L-band SAR will be affected by Faraday rotation. In this study, PALSAR system is briefly described, and the Freeman calibration method is considered for PALSAR calibration. However, this method requires the deployment of a minimum of one corner reflector (CR) for the calibration of each scene, and this is not convenient in practice. In this paper, the use of human-made and natural symmetric targets is investigated for the calibration of SAR subject to Faraday rotation. The target scattering vector model (TSVM), which permits a unified decomposition of point and distributed target scattering, is used to derive a new calibration method that does not require the deployment of CRs. It is shown that the orientation (i.e. target tilt angle) and roll invariant maximum polarization parameters of symmetric target scattering can be used to measure and remove Faraday rotation and channel imbalance errors from PALSAR data. Antenna gain and cross-talk incidence angle variations are measured using data acquisitions over the Amazonian forests, under low Faraday rotation conditions.

Relation between coherence, forest biomass, and L-band sigma0were examined by using the L-band data taken by Japanese Polarimetric and Interferometric Airborne SAR (PiSAR). Several PiSAR observations were performed over a well-managed national forest, in which four kinds of conifers were dominantly planted. A coherence map over the forest area was made from two flight data, whose observation interval was about 30 minutes. The coherence in this site are ranging from 0.5 to 0.8. High coherence values of 0.7 ~ 0.8 were appeared at the young stands. On the other hands, some stands with high biomass also show high coherence value. Since the coherence values are weakly correlated with sigma0HHand sigma0HVat the stands with high biomass, the high coherence value and the high sigma0value are considered to be the same origin. The regression curve between the coherence and a stem volume derived in this analysis shows higher coherence value than the other two JERS-1 (L-band) 44-day pair data and one ERS 1/2 C-band 1-day pair data. This may be due to the shorter repeat-cycle of the PiSAR pair data and difference of the scattering elements.

The purpose of this letter is to present the results on the study of searching effective parameters that describe the relation between high-resolution synthetic aperture radar (SAR) images and forest parameters. The study is based on the non-Gaussian texture analysis of the polarimetric airborne Pi-SAR data over coniferous forests in Hokkaido, Japan. The radar cross section (RCS) in terms of a forest biomass is first analyzed. It is found that the$hboxL$-band RCS increases steadily with the biomass and saturates at approximately 40 tons/ha. These results are similar to the previous studies. The probability density function of the image amplitude is then investigated, and among Rayleigh, log-normal, Weibull, and$K$-distributions, the$K$-distribution is found to fit best to the$hboxL$-band data of all polarizations, although the Weibull distribution fits equally well. Further, the correlation between the tree biomass and the order parameter of the$K$-distribution in the cross-polarization images is found to be very high, and the order parameter increases consistently with the biomass to approximately 100 tons/ha, which is well beyond the saturation limit of the$hboxL$-band RCS. Thus, the order parameter of the$K$-distribution can be a promising new parameter to estimate the forest biomass from high-resolution polarimetric SAR data in a much wider range than the conventional RCS method.

Biophysical parameters and L-band polarimetry synthetic aperture radar observation data were taken for 59 test sites in Tomakomai national forest, which is located in the northern part of Japan. Correlations between the derived sigmaHH0, sigmaHV0, and sigmaVV0and the biophysical parameters are investigated and yield the following results. 1) The above-ground biomass-sigma0curves saturate above 50 tons/ha for sigmaVV0, 100 tons/ha for sigmaHH0, and over 100 tons/ha for sigmaHV0when all forest species are included in the curves. 2) The sigmaHH0-above-ground biomass curve for one forest species indicates a higher saturation level than that for the other forest species. Dependence on the forest species was absent for VV polarization and low for HV polarization. 3) A simple three-component scattering model indicates that volume scattering accounts for 80%-90% when the above-ground biomass exceeds 50 tons/ha. The surface-scattering components are up to ~20% for young stands, and the volume-scattering components are down to 70%. The origin of the dependency among the forest species was examined for the sigmaHH0-above-ground biomass. It is concluded that a possible cause of the dependency is the different characteristics of the stands rather than forest species

This paper describes the updated status of the PALSAR CAL/VAL and scientific activity of 2005, which is being conducted as a part of the JAXA's ALOS science program. The updated information includes 1) Detailed schedule of the initial calibration phase, 2) Distribution of the calibration targets, 3) Calibration strategy (antenna pattern, polarimetric calibration, absolute calibration, image quality evaluation, noise equivalent sigma-naught), 4) PALSAR data format update, and 5) Yaw steering mode and observation scenario for polarimetry.

This paper introduces the updated plans of calibration and validation for two optical sensors i.e., the Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) and the Advanced Visible and Near Infrared Radiometer type-2 (AVNIR-2), which are to fly on the Advanced Land Observing Satellite (ALOS). PRISM consists of three panchromatic radio- meters, and is used to derive a Digital Elevation Model (DEM) or a Digital Surface Model (DSM) with very high spatial resolution, which is also an objective of the ALOS mission. The geometric calibration is important in generating a highly accurate DEM by stereo pair images of PRISM. The radiometric calibration is also important for PRISM as well as AVNIR-2. The relative radiometric calibration will be done using acquired images over homogeneous targets such as the nighttime observation, ocean, deserts, and ice lands. The absolute radiometric calibration will be carried out by vicarious calibration and the cross calibration using with calibrated satellite images i.e., ASTER, IKONOS etc. In this paper, test simulations of calibration tools are described using current satellite images. Keywords-ALOS; PRISM; AVNIR-2; Calibration; Validation.

The Advanced Land Observing Satellite (ALOS) has been developed to contribute to the fields of mapping, precise land coverage observation, disaster monitoring, and resource surveying and will be launched in 2005. The Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) carried at ALOS satellite is expected to generate worldwide Digital Maps in respects of its high resolution and stereoscopic observation. The development and evaluation of the software for generating digital surface model (DSM), based on this aim of ALOS operation, is now undertaking for the purpose of equipping the system which producing DSM semi-routinely in the Earth Observation Research and Application Center (EORC). In this paper, the statuses of pre-launch simulations and DSM assessment plans are described. PRISM consists of three panchromatic radiometers for forward, nadir, and backward views and acquires each image in the same orbit at almost the same time. It enables to generate more precision DSM frequently than usual stereoscopic observations. For this specific stereo image configuration, the triplet images matching algorithm is applied for the DSM generation. To evaluate the algorithm, three line scanner (TLS) data is used as the PRISM simulation data. The DSM generation using the JERS-1 OPS stereo images is being performed as the operational simulation. The basic functions of the software such as bundle adjustment, DSM mosaic, mask operation, etc. are evaluated in those simulations. The accuracy assessment of generated DSM is planned to be performed using the LIDAR DSM data, SRTM data, GCP etc.

In the context of the Global Boreal Forest Mapping project (GBFM), an initiative of the Japan Aerospace Exploration Agency (JAXA), a continental scale radar mosaic of the Eurasian Taiga was compiled. The mosaic is composed of some 520 strip-images (typically covering 80 km by 2500 km each) acquired in 1997-98 by the L-band SAR aboard the JERS-1 spacecraft. The mosaic was assembled in two phases. Coverage in the first stage included the area between the Ural Mountains in the west, Bering Strait in the east, Arctic Ocean in the north and the Korean Peninsula in the south. In the second phase an extended version was produced that comprises the European part of the Boreal ecosystems west of the Ural Mountain and up to the European Union region. Pixel spacing of the high resolution final products is 100 m and map projection is Albers equal-area conical. In this paper selected topics are presented related to a revision of the mosaic geometry. This step was called for to improve the internal consistency and assure proper absolute geolocation of the mosaics with respect to reference data sets. It consists of: i) a data representation (virtual frames) for handling the strip-images in smaller units that are more effective for dealing with local distortions; and ii) inclusion of control points derived from the Landsat GeoCover data sets. Results characterizing the mosaic geometric accuracy in terms of root mean square residuals are reported. Finally, we present, as a first thematic result, a vegetation map at coarse resolution (900 m) derived by a combination of the Global Land Cover 2000 map and the GBFM radar mosaic.

Boreal ecosystems play an essential role in global climate regulation. Forests constitute pools of terrestrial carbon and are generally considered as global sinks of atmospheric CO/sub 2/, contributing to attenuating the greenhouse effect. Large amounts of carbon are also stored in boreal lakes, bogs and wetlands, partially released as CH/sub 4/ and other trace gases to the atmosphere during the spring and summer months. Human activities in the forest zone are however reducing the size of the carbon pool and climate change is triggering shorter winters and earlier thaw onset, changing the natural equilibrium. Given its global importance, there is a need to map and monitor the boreal zone, and as the changes occur on all from local, regional to global scales, fine resolution information over vast areas is required. The Global Boreal Forest Mapping (GBFM) project is an international collaborative undertaking initiated by NASDA in 1996, as a follow-on to the tropical-focused Global Rain Forest Mapping (GRFM) project [A. Rosenqvist et al., (2000)]. Utilising the L-band Synthetic Aperture Radar (SAR) on the Japanese Earth Resources Satellite (JERS-1). one of the main objectives of the GBFM project is the generation of extensive, pan-boreaL SAR image mosaics, to provide snap-shots of the forest wetland and open water status in the mid-1990's. Mosaics over Canada, Alaska. Siberia and Europe have been generated, available on the Internet and on DVD free of charge for research and educational purposes. The GBFM project also entails research activities in North America, Siberia and northern Europe, aimed at advancing scientific applications of L-band SAR data in the boreal zone.

The Advanced Land Observing Satellite (ALOS) is scheduled for launch by the Japan Aerospace Exploration Agency (JAXA) in 2005, and it carries three remote sensing instruments: an L-band polarimetric Synthetic Aperture Radar (PALSAR), an along-track 2.5 metre panchromatic resolution stereo mapper (PRISM) and a 10-metre multi-spectral scanner (AVNIR-2). The successor of the JERS-1 satellite (1992-1998), ALOS not only provides enhanced sensor performance, but also feature an entirely new acquisition concept. Abandoning traditional, local-focused instrument operations, JAXA is implementing a comprehensive acquisition strategy, in which geographical region, sensor mode, acquisition timing and repetition frequency, are fixed in advance, to achieve spatially and temporally consistent, global coverage on a repetitive basis, at the same time as reducing programming and user conflicts.

This paper describes generation of the digital elevation model (DEM) using the L band repeat pass airborne polarimetric Interferometric SAR (Pi-SAR) system, which is jointly developed by Japan Aerospace Exploration Agency (JAXA) and National Institute for Communication Technology (NICT). An image pair acquired over the Tottori calibration site in 2000 had a baseline of less than hundred meters and was used for this interferometric data analysis. Although the quantitative evaluation has not been conducted, the result shows that the detailed feature of the topography in the target area was well obtained.

Proposes a new method to calibrate L band polarimetric SAR using the forest data. Model based covariance matrix containing the distortion matrices and the scattering components from the forest were solved using the Pi-SAR data over the Japan uniform forest of Tomakomai, Hokkaido. The result showed that the distortion matrices depend on the function of the incidence angle and the operation timings.

This paper introduces the updated plans for sensor calibration and product validation of the two optical sensors i.e., the Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) and the Advanced Visible and Near Infrared Radiometer type-2 (AVNIR-2), which are to fly on the Advanced Land Observing Satellite (ALOS). PRISM consists of three panchromatic radiometers, and is used to derive Digital Elevation Models (DEMs) with very high spatial resolution, which is also one of the objectives of the ALOS mission. The geometric calibration is important in generating a highly accurate DEM by using PRISM's triplet images. Highly accurate ground control points (GCPs) are necessary to calibrate the geometric accuracy and validate the generated DEM. The geometric calibration of AVNIR-2 can be done using the calibrated PRISM product. In this paper, we describe the current plans for calibrating and validating PRISM and AVNIR-2. In particular, preparation status of GCPs with evaluation items for geometric calibration, including expected problem effects regarding geometric accuracy, orbit and observation simulations to determine pointing accuracy, and preliminary investigation of nighttime GCP using current available satellite images

The Advanced Land Observing Satellite (ALOS) has been developed to contribute to the fields of mapping, precise land coverage observation, disaster monitoring, and resource surveying. The Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM), carried on ALOS satellite is expected to generate worldwide Digital Maps in respects of its high resolution and stereoscopic observation. The development and evaluation of the software for generating Digital Elevation Model (DEM), based on this aim of ALOS operation, is now undertaking for the purpose of equipping the system which producing DEM semi-routinely in the Earth Observation Research and application Center (EORC). In this paper, the software's outline of functions, the algorithm and the current status of its development and evaluation are described. PRISM consists of three panchromatic radiometers for forward, nadir, and backward views and acquires each image in the same orbit at almost the same time. It enables to generate more precision DEM frequently than usual stereoscopic observations. For this specific stereo image configuration, the triplet images matching algorithm is applied for the DEM generation. To evaluate the algorithm, Three Line Scanner (TLS) data is used as the PRISM simulation data and the Lider DEM is used as the reference data. The absolute accuracy of generated DEM is estimated in this simulation

PALSAR L-band SAR is affected by Faraday rotation. In this study, PALSAR system is briefly described, and Freeman's method is considered for the calibration of PALSAR. Unless channel imbalances are measured abroad, a reference point target has to be deployed for each scene to be calibrated. For practical reasons, the use of symmetric targets is investigated for calibration and validation of polarimetric PALSAR data

We examined relationship between forest parameters and /spl sigma//sup 0/ derived by airborne multi-polarization SAR (PiSAR). PiSAR observations and field measurements were simultaneously performed on November 2002 and August 2003. One data set was taken from stands with pure pine (Picea glehnii Masters) forest. More than 70% of the trees in biomass are Picea glehnii Masters in the data set with same stand age. The other data set was taken from the stands where mixture of species is proceeding in some degree. The former data set shows more tight correlations compared to the other and correlation coefficient reaches 0.98. We conclude that (1) the mixture of the species and stand age are two of the major reasons of data scattering between forest parameters and /spl sigma//sup 0/, and (2) the above ground biomass saturation level is about /spl sim/150 tons/ha for L-band /spl sigma//sub HH//sup 0/ and /spl sigma//sub HV//sup 0/ and /spl sim/70 tons/ha for /spl sigma//sub VV//sup 0/ in this akaezomatsu site, using a biomass expansion factor of 1.36 to convert from the trunk biomass to the above-ground biomass.

Wind retrieval from Japanese Earth Resources Satellite-1 (JERS-1) synthetic aperture radar (SAR) using an L-band model function in coastal regions is evaluated. It is known that JERS-1 SAR has excessive ambiguities. This paper also gives a quantitative evaluation of excessive ambiguities in coastal scenes of JERS-1 SAR. First, focusing on the cases where wind blows from the shore in Sagami Bay, we investigate phenomena of wind speed increase with offshore distance using European Remote sensing Satellite-1 (ERS-1) SAR-derived wind speeds. The relation between wind speed and offshore distance is well formulated, which indicates the transition of the atmospheric boundary layer from land to sea surface. Wind speeds derived from JERS-1 SAR should be overestimated due to the excessive ambiguity. Then, for observation time of each JERS-1 SAR capturing the cases that wind blows from the shore in Sagami Bay, the expected wind speed growth profile is derived from the wind speed growth formula and an in situ wind observation of Hiratsuka Experiment Station. We convert the wind-speed profile into the sigma-0 profile by an L-band model function. Finally, the profiles of JERS-1 SAR-observed and the estimated sigma-0 are compared, and the excessive ambiguity is estimated as the difference between them. As a result, the dynamic range of first azimuth ambiguity is as large as that of the wind-relating signal from the ocean surface. Moreover, higher order azimuth ambiguities and range ambiguity also may have a significant impact on near-shore wind retrieval.

We used multi-sensor, multi-frequency and multi-polarization SAR data for biophysical parameter retrieval in plantation forests of Northern Japan. The statistical relationships with different biophysical parameters are quite robust for certain frequencies-polarization combination. A combination of different frequencies and polarizations facilitate the retrieval of these parameters with R 2 of 0.95 and rms error of 15.19 tons ha -1 .

The Kyoto & Carbon Initiative is an international collaboration initialised by NASDA in 2000 [1], set out to support dataand information needs raised by certain multinational environmental conventions and by global carbon cycle science, through provision of data products and high level information derived from ALOS, JERS-1 and ADEOS-II data. The conventions primarily in focus are the UNFCCC Kyoto Protocol and the Ramsar Convention on Wetlands, to which fineresolution, multi-scale information about the status and changes in forests and wetlands will be derived. There is apparent synergy with terrestrial carbon cycle science information needs, where improved spatial information about carbon pools, sources and sinks at local, regional to global scales are of high priority. Support to the UN Millennium Development goal on water access, as well as to the UN Convention to Combat Desertification, are

An L-band geophysical model function is developed using Japanese Earth Resources Satellite-1 (JERS-1) synthetic aperture radar (SAR) data. First, we estimate the SAR system noise, which has been a serious problem peculiar to the JERS-1 SAR. It is found that the system noise has a feature common in all the SAR images and that the azimuth-averaged profile of noise can be expressed as a parabolic function of range. By subtracting the estimated noise from the SAR images, we can extract the relatively calibrated ocean signals. Second, using the noise-removed SAR data and wind vector data from the NASA Scatterometer and buoys operated by the Japan Meteorological Agency, we generate a match-up dataset, which consists of the SAR sigma-0, the incidence angle, the surface wind speed, and wind direction. Third, we investigate the sigma-0 dependence on incidence angle, wind speed, and wind direction. While the incidence angle dependence is negligible in the present results, we can derive distinct sigma-0 dependence on wind speed and direction. For wind speeds below 8 m/s, the wind direction dependence is not significant. However, for higher wind speeds, the upwind-downwind asymmetry becomes very large. Finally, taking into account these characteristics, a new L-band-HH geophysical model function is produced for the SAR wind retrieval using a third-order harmonics formula. Resultant estimates of SAR-derived wind speed have an rms error of 2.09 m/s with a negligible bias against the truth wind speed. This result enables us to convert JERS-1 SAR images into the reliable wind-speed maps.

The Panchromatic Remote sensing Instrument for Stereo Mapping (PRISM) sensor that will be carried on the Advanced Land Observing Satellite (ALOS) includes creation of digital elevation maps as one of its purposes. PRISM is capable of high spatial resolution and along-track stereoscopic observation. In order to provide software to create a Digital Elevation Model (DEM) semi-routinely at the Earth Observation Research Center (EORC), development of a DEM generation algorithm and software was carried out. The authors considered the basic function of DEM generation software, various processing algorithms for DEM generation were examined, and a trial production and evaluation which used test data was performed This paper reports the resulting processing method, and evaluation of results, of DEM generated from test data consisting of the nadir and forward images from JERS-1/OPS.

An L-band geophysical model function (GMF) is developed using Japanese Earth Resources Satellite-1 (JERS-1) SAR data. This GMF describes the relationship among L-band NRCS and ocean surface wind speed and direction. It enables us to convert JERS-1 SAR image into a wind-speed map. Using retrieved SAR wind, a high-resolution wave prediction model, SWAN (Simulating WAves Nearshore) was derived to demonstrate SAR high-resolutions winds.

This paper presents the current calibration plan of the Advanced Visible and Near Infrared Radiometer type 2 (AVNIR-2). Radiometric calibration methods based on internal calibration lamps and Earth-observed data are outlined. Several areas for surface radiometric reference are selected on the Asian and North American continents and in the Pacific Ocean. Vicarious calibration is planned in these areas. For geometric calibration, concerns about the pointing function of AVNIR-2 and the complementary method by the simultaneous use of Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) am outlined.

Several research products using the Advanced Visible and Near Infrared Radiometer type 2 (AVNIR-2) onboard Advanced Land Observing Satellite (ALOS) are planned to be produced in the Earth Observation Research Center, National Space Development Agency of Japan (NASDA EORC). The products are snow cover maps albedo maps, land cover maps, land cover classification maps, vegetation classification maps, and so on. These products are to be produced in combination with the Digital Elevation Model (DEM) derived from the Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM), and to be mainly used for local to regional scale land applications. The outline and the methods to produce each product are introduced in this paper.

Peat swamp forests are very important sources of carbon among the terrestrial forest ecosystems. Large areas of peat swamp forests have been deforested in the recent past. A time series of L-band SAR data has been employed to detect the deforestation that has occurred in the central Kalimantan region, Indonesia, between 1994 and 1998. Large areas that have been deforested have been converted into cultivated lands but agricultural crops have miserably failed to grow on these soils because of the adverse water and soil chemistry. Furthermore, the L-band SAR has been able to detect the flooded conditions in these forests, particularly in short pole and riverside vegetation types where the transmissivity of the L-band SAR signals are quite significant. In case of very dense forests, the inundation could not be detected because of very high attenuation and thus low penetration of L-band radar. The information about these two phenomena viz., deforestation and inundation would be used for estimation of the carbon and trace gases exchange in these forests.

This paper introduces preliminary CAL/VAL of the Phased Array type of L-band Synthetic Aperture Radar (PALSAR) onboard the Advanced Land Observing Satellite (ALOS) in terms of the antenna pattern error distribution and the image correlation using the PALSAR parameters. More CAL VAL will be conducted to ensure the applicable potential of PALSAR to the Earth environmental monitoring, e.g., the disaster, forest (biomass), land surface classification, DEM generation capability, and so on.

Forest biomass is one of the key parameters that indicate temporal change of the global continental carbon volumes, and its global estimation is required as described in the Kyoto protocol. NASDA's ALOS science project strongly intends its estimation either solely by SAR or in conjunction with the other optical sensors and the ground truth data. There have been (or are being) developed SAR based methods to estimate the forest biomass, which utilize the relationship between sigma-zero and biomass quantity, those based on coherence of one day separated C band data and L band radar intensity, and those based on forest tree heights and biomass quantities, etc. For the third category, it is expected that Pol-In-SAR might relate the interferometric phase difference at different polarizations to the tree structures and heights, and two-frequency interferometry relates to the phase center difference to the tree height.

Introduces the current plans for calibrating and validating the Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) aboard the Advanced Land Observing Satellite (ALOS), which will be launched in 2004. PRISM will be used to derive a Digital Elevation Model (DEM) with very high spatial resolution. That also is one of the objectives of the ALOS mission. In order to do so, PRISM consists of three panchromatic radiometers for forward, nadir and backward views and acquires images in the same orbit and at almost the same time. More calibration and validation will be conducted to ensure high accuracy of the DEM.

X-and L-band airborne SAR developed by CRL and NASDA has the capability of high resolution, polarimetry and cross-track interferometry. The radar has been operated since 1995 in the domestic area of Japan aiming at technical capability and validating for various applications. In this paper, we pick up the examples of the volcanic events to show the ability of the Pi-SAR.

This paper evaluates a method to obtain the slope-corrected normalized radar cross section (/spl sigma//sup 0/) using SAR interferometry. An error model on a slope correction factor has been derived as a function of a scene coherence and a baseline distance. The model has been verified using JERS-1 SAR data and a ground terrain model. Analyses have shown that the proposed method can correct the radiometric slope effect within an accuracy of 0.3 dB if the interference condition is satisfied.

An imaging (or correlation) process for saturated synthetic aperture radar (SAR) data that is caused by the limited dynamic range of the analog-to-digital converter (ADC) was investigated using the stochastic process approach. The theoretical models for the correlation power and its normalized standard deviation were derived. Based on these, a radiometric correction method for the saturated SAR data was proposed. Error analysis was conducted for the data acquired in the manual and automatic gain modes. It was shown that the proposed method can correct the saturated SAR data of both modes, although the data in automatic gain are more accurately corrected than that in manual gain; the proposed method was verified by using the JERS-1 SAR data.

Calibration results of the ocean color and temperature scanner (OCTS) on board the Advanced Earth Observing Satellite (ADEOS) are presented. The authors have evaluated the OCTS responses to internal calibration sources (i.e., lamps, electric voltages, and sunlight), natural targets (i.e., night data and uniform targets in the daytime), external calibration source (i.e., underflight of a calibrated airborne sensor), and a theoretical calibration source modeled for the atmospheric radiation. The authors then compared the acceptability of these calibration sources.

In this paper, the impulse response function (IRF) of a synthetic aperture radar (SAR) image of frequency-tunable reference point targets [e.g., active radar calibrator (ARC)] is analyzed. The frequency-tunable ARC is an effective SAR calibration device that can yield a larger radar cross section (RCS or /spl sigma/) than a corner reflector, and it displaces the response to a desirable background area for isolation from brighter man-made targets (e.g., buildings). SAR calibration accuracy is degraded by frequency shift, however, because of less correlation gain and broader IRF. We compared the theoretically derived IRF with the measurement data and drew the following conclusions: first, the location shift and the peak gain loss can be theoretically estimated within 4.2 m and 1.6 dB (one standard deviation); second, the peak calibration method is degraded by the defocused IRF; third, the integral method, which is not sensitive to defocusing, is recommended for SAR calibration; and fourth, the frequency shift should be less than 40 Hz for the satellite-based L-band SAR calibration.

Calibration results of the advanced visible and near infrared radiometer (AVNIR) on board ADEOS are presented. First, the AVNIR responses to the internal and external calibration sources are evaluated, and their short- and long-term stabilities are summarized. Second, absolute radiometric calibration of AVNIR is conducted by using the NASA JPL's calibrated airborne optical sensor, and the results from several different calibration methods (preflight calibration, and in-flight calibrations using the on-board data, the AVIRIS, and the vicarious method) are compared. Third, the geometric accuracy and the image quality are summarized.

A method to measure the antenna elevation pattern of synthetic aperture radar (SAR) using distributed targets is introduced. The features of the method are (1) the antenna pattern model parameters are estimated as the solutions of maximum likelihood estimation; (2) To guarantee the uniformity, a screening process based on a chi-square similarity test is applied to the image data; and (3) Noise generated in the SAR receiver and data processor tends to broaden the estimated antenna pattern. To improve it, the estimated noise level is subtracted from the image data. The authors assume that the scattering coefficient over the evaluated images is unknown yet constant (although this could easily be extended to the case where the variation of /spl gamma/ or /spl sigma//spl deg/ with incidence angle is known), Three types of antenna pattern models are tested, Among them, the best result is given by a fourth order power model. This technique is applied to selected image data sets from the SIR-B mission, including several scenes analyzed previously by Moore from the Amazon rain forest and Illinois farmland. For the Amazon data (which give the best results), the authors found that the technique adopted in the paper gives residual errors on the antenna pattern fit of less than 0.08 dB for a given scene. Applying the antenna pattern estimated from one scene to others, residual errors of less than 0.3 dB are achieved.>