ALOS has been on orbit for two years and a half after its launch on January 24 2006. After its initial calibration for the
first six months, ALOS was thrown into the operational phase after Oct. 23 2006. In operation phase, PALSAR has
been activated based on the basic mission operation plan that summarizes the requests for imaging from JAXA
calibration team, the power users, Principal Investigator (PIs) of the ALOS Research announcement, and the Kyoto and
Carbon initiatives for monitoring the forest deforestation and degradation. By now, ALOS collected the PALSAR data
more than 700,000 scenes, which correspond to 8 times global, land coverage. The calibration results using the one year
data set shows that PALSAR has an excellent performance of the radiometric accuracy of 0.6 dB using all the corner
reflectors associated with the calibration experiments and 0.17 dB using the Swedish 5m sized corner reflectors, the
geometric accuracy with 9.3 m (RSS). The polarimetric performance is that the amplitude variation of the VV/HH
channels is 0.3 dB and phase is 0.3 degrees. In this paper, we will introduce the stability of the PALSAR calibration
results for after operation phase. This covers the stability of the sensor its self and the update of the antenna pattern
measurements, SCANSAR processing update, and the suppression of the ground radar interference. We also introduce
the generation of the 50 meter spaced ortho-rectified PALSAR mosaic datasets for the Kyoto and Carbon Initiatives.
Using the corner reflectors, we have monitored the temporal variation of the accuracies. We have also conducted the
antenna pattern variation and the stabilities using the Amazon rain forest data.
This paper presents an overview of the Advanced Land Observing Satellite (ALOS) and its research activities, which are carried out at the Earth Observation Research and Application Center (EORC) of the Japan Aerospace Exploration Agency (JAXA). The mission objectives of ALOS include cartography, regional observation, and disaster monitoring etc. ALOS has three mission instruments, the PRISM, AVNIR-2, and PALSAR, to achieve these objectives.
Our research activities can be categorized into two main parts of the ALOS mission: calibration and validation, and application and science. We are presently developing calibration and validation tools for each sensor, evaluating the pre-flight test data acquired on the ground, establishing test sites and reference facilities, and considering mission operation plans to observe the test sites effectively. The application and scientific results will demonstrate the ALOS data utilization capability. We define the digital elevation model (DEM), ortho-rectified images for each sensor, and the surface deformation map as high-level and research products. We describe here our research and scientific activities, particularly calibration and validation, to improve the absolute accuracy and image quality of the products and we provide some examples of data utilization.
The ADEOS-II satellite was successfully launched with an H-IIA rocket from Tanegashima Space Center in southern Japan on December 14, 2002. Amongst the six remote sensing instruments on-board, the payload includes the Global Imager (GLI) - a 36-channel multi-spectral scanner developed by the National Space Development Agency of Japan (NASDA) for ocean, terrestrial, atmosphere and cryosphere applications. 30 bands operate with a 1 km spatial resolution, while the remaining six bands, primarily dedicated for terrestrial use, acquire data with 250 metres ground resolution at nadir. The cancellation of one of the two planned Data Relay Test Satellites (DRTS) required for data down-link however resulted in reduced acquisition capacity at 250 metre resolution and thus prompted the establishment of a dedicated 250-metre data observation strategy, which aims to optimise 250 m observations over land, and to provide spatially and temporally consistent, multi-seasonal global land coverage, on a repetitive basis during the life-time of the ADEOS-II satellite. Plans for 250 m data product generation are furthermore outlined briefly in this paper.
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