JAXA has conducted earth observations using the AMSR series of satellite-borne microwave radiometers (MWRs) for 20 years. Although design of the AMSR series poses problems in terms of lifetime, spatial resolution, and artificial radio frequency interference (RFI), the same design has been carried over to the AMSR2 successor (AMSR3) currently under development. In response to the need for technological development to solve these problems, we began studying a satellite-borne MWR based on a new concept. We recently developed a new-type MWR, DS$\mu $RAD. This is the world’s first hyperspectral MWR that can receive microwave power from L- to Ka-band with an ultrawideband antenna and measure the spectrum of brightness temperature in high-frequency resolution by ultrahigh-speed A/D converters. Based on the development of DS$\mu $RAD, we believe that a hyperspectral microwave interferometer (MWI) with a phased array antenna (PAA) composed of ultrawideband antennas is the most ideal MWR that can solve all the problems at once. This MWI controls pointing by true time delay (TTD) taking advantage of ultrahigh-speed sampling. As the first step to demonstrate this idea, we developed and tested the most basic two-element ultrawideband hyperspectral MWI based on DS$\mu $RAD. As a result, the sharp main lobe of the MWI was simultaneously formed over the 4–16 GHz range at the same position, and its pointing and width could be controlled as intended. In particular, the azimuthal shift of the main lobe caused by the time delay given to the signal of either element did not depend on the frequency.

The Advanced Microwave Scanning Radiometer-3 (AMSR3), the successor to AMSR2, is currently under development for launch in 2023. One of the goals of the AMSR3 mission is to make the retrieval limit of sea surface temperature (SST) to the coast at least 30 km (ultimately 20 km) while mitigating the effects of weather. Since AMSR3 needs to maintain the same design as AMSR2 as much as possible in order to shorten the development period, this goal must be mainly achieved by a data processing approach. Therefore, we first developed a spatial resolution enhancement algorithm for the brightness temperature ($T_{B}$) based on the Backus–Gilbert method. We aim to achieve the goal by retrieving SST using this resolution enhanced$T_{B}$. At present, the standard SST product of AMSR2 retrieves SST in waters more than 80 km from the coast using the C-band$T_{B}$. Therefore, we applied our spatial resolution enhancement algorithm to the C-band$T_{B}$of AMSR2 to retrieve hi-resolution SST (HST), evaluated how close the retrieval limit is to the coast, and compared the retrieval accuracy with the standard SST product. As a result, it was confirmed that the retrieval limit of HST is less than 30 km to the coast, with retrieval accuracy as approximating that of the standard SST product.

A microwave radiometer (MWR) is an instrument used to measure the microwave power emitted from the natural origin as a brightness temperature ( TB). A more active use of microwaves below the Ka-band is being planned for wireless communication in the near future, thereby increasing the risk of artificial radio frequency interference (RFI) with natural origin TBmeasurement. Although measuring TBvalues in high-frequency resolution is an effective way to detect and remove the effect of RFI from measured TB, it is difficult to fundamentally increase the number of simultaneously measurable TBin the conventional MWR due to space issues. Therefore, we developed a new MWR - direct RF sampling hyperspectral microwave radiometer (DS μRAD) that adopts multiple A/D converters of 10-GSPS order [samples per second (SPS)] to digitize microwave power received by an ultrawideband antenna. DS μRAD can measure the microwave power of the vertical and horizontal polarizations to decompose each into a TBspectrum from 512 MHz to 40.96 GHz at 16-MHz intervals. We expect that DS μRAD will open up new possibilities for microwave remote sensing, including a drastic response to increased RFI risk, i.e., effective detection and removal (or extraction) of RFI. This letter presents the DS μRAD design in detail and the initial evaluation results of the instrument's performance.

The Advanced Microwave Scanning Radiometer-2 (AMSR2) follow-on mission is currently being considered, and end users are demanding the acquisition of sea-surface temperature (SST) with higher spatial resolution. However, it is assumed that the AMSR2 baseline design will be followed as much as possible to shorten the development period. The SST image retrieved from the 6- or 10-GHz brightness temperatures includes random “snow” noise due to the thermal noise originating from the receiver components. In AMSR2, simple spatial averaging was performed to reduce such random noise to obtain clear SST images, but this method is not suitable for acquiring SST images with the high spatial resolution because it degrades the spatial resolution. In the AMSR2 follow-on mission, the algorithm for the AMSR2 L1R product (Backus-Gilbert method) will be applied to reduce random noise without degrading the spatial resolution. In addition, we propose equipping not only a 10-GHz channel with the conventional frequency band but also that with an extended frequency band. This letter presents the results of the study that led to these proposals required to obtain clear SST images with higher spatial resolution in the AMSR2 follow-on mission.

The greatest advantage of a satellite-borne microwave radiometer (MWR) is that it can obtain information on the Earth's surface with less influence by rain and clouds compared to an infrared radiometer; however, it has the disadvantage that the observing area is large so the spatial resolution is low. One example is the Advanced Microwave Scanning Radiometer-2 (AMSR2) loaded on the GCOM-W satellite. Hardware technologies to overcome this disadvantage are in progress, but software processings to improve spatial resolution are also needed, especially to process previously obtained data. The author was inspired by the experience of developing the L1R product for the AMSR2 and has investigated optimizing the Backus-Gilbert (BG) method to enhance spatial resolution. First, the BG method was used to calculate weighting coefficients to synthesize the brightness temperature equivalently obtained in a small observation area from those obtained in multiple larger areas. Next, a viable algorithm was developed and implemented in order to solve the problem appearing in this simple application of the BG method. The algorithm was verified and shown to reduce the observation area by about 17%, enhancing the spatial resolution.

The Global Change Observation Mission-Water (GCOM-W) satellite was launched by the Japan Aerospace Exploration Agency (JAXA) in May 2012. It carries the Advanced Microwave Scanning Radiometer 2 (AMSR2), which is a 6-band multi-frequency, dual-polarization microwave radiometer with a 2-m aperture antenna. The GCOM-W/AMSR2 completed its 5-year designed mission life in May 2017, and has transferred to extended-mission phase. Besides the 10-month gaps between AMSR-E and AMSR2, the AMSR series provide long-term global observation data for studies of the global water cycle, airsea interactions and polar environments. An overview of these studies is given in this paper.

The Advanced Microwave Scanning Radiometer 2 (AMSR2) on board the Global Change Observation Mission - Water (GCOM-W or “SHIZUKU”) satellite was launched in May 2012 and will achieve its 5-year designed mission life in May 2017. Major goal of the satellite is to provide continuous observations of global water cycle succeeding role of JAXA's Advanced Microwave Scanning Radiometer for EOS (AMSR-E) on the NASA's Aqua satellite. The GCOM-W satellite is also flying in the A-train orbit to provide synergies among the other A-train satellites, such as Aqua and Cloudsat. During the 5-year mission, we provide eight standard products and two research products to both science and operational communities. Since the satellite and instrument are in healthy conditions, we expect to continue the mission as long as possible to bridge follow-on mission that is currently discussed.

The Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) had been operated in special slow rotation mode to obtain continuous brightness temperatures for the inter-comparison with those of AMSR2 on the Global Change Observation Mission-Water (GCOM-W) for three years. Although its observation coverage is sparse and some calibration uncertainties exist, the data are still very useful for straightforward inter-comparison.

The Global Change Observation Mission 1st-Water (GCOM-W1) satellite, which was launched by the Japan Aerospace Exploration Agency in May 2012, contains an Advanced Microwave Scanning Radiometer-2 (AMSR2). The AMSR2 provides multifrequency measurements of microwave energy (brightness temperature) emitted by the Earth's surface and atmosphere. However, each frequency field of view (FOV) differs in size because of its hardware design. For the retrieval of more accurate geophysical parameters from multifrequency brightness temperatures, the brightness temperatures should be modified to be the same as measured in the same FOV. The Backus-Gilbert (BG) method is one of the antenna pattern matching techniques used for this modification. We applied the BG method to the AMSR2 data to define a new data set of modified brightness temperatures, a level 1R (L1R) product that is freely and widely available. We optimized the implementation of the BG method to obtain the L1R product, with smoothing factors dynamically determined for all modified brightness temperatures. This paper describes the implementation method, including the criterion used to determine the smoothing factors and presents a quality assessment of the L1R product.

The Advanced Microwave Scanning Radiometer 2 (AMSR2) on board the Global Change Observation Mission — Water (GCOM-W or “SHIZUKU”) was launched on May 18, 2012 (JST), and continuous its observation from the A-Train orbit more than one year successfully. Validation results of AMSR2 standard products satisfied required release accuracy, and JAXA has released AMSR2 geophysical parameters to public though the GCOM-W1 Data Providing Service System (https://gcom-w1.jaxa.jp) since May 17, 2013. In addition to AMSR2 standard products, research products are defined to extend possible utilization of AMSR2 data. We are also planning to integrate the water-related parameters derived from AMSR2 with those from AMSR-E to produce long-term continuous datasets for climate change studies.

The Advanced Microwave Scanning Radiometer 2 (AMSR2) on board the Global Change Observation Mission - Water (GCOM-W or “SHIZUKU”) was launched on May 18, 2012 (JST), and continuous its observation from the ATrain orbit more than one year successfully. Validation results of AMSR2 standard products satisfied required release accuracy, and JAXA has released AMSR2 geophysical parameters to public though the GCOM-W1 Data Providing Service System (https://gcom-w1.jaxa.jp) since May 17, 2013. Definition of AMSR2 research products are currently discussed under the AMSR2 Science Team and some candidate algorithms are being processed and tested for operation utilization in some user agencies.

It has already been confirmed that microwave signals are emitted by rock failures in our laboratory experiments. From the results of rock failure experiments, it has been concluded that the microwave signals generated by rock failures near the ground are strong enough to be detected by a satellite borne radiometer like the Advanced Microwave Scanning Radiometer for Earth-Observation System (AMSR-E) [1]. Synthetic Aperture Rader (SAR) can detect an area where the land surface was deformed by seismic activity. But it can not determine by what the land surface was deformed, preslips, a main shock or aftershocks due to its poor time resolution. On the other hand, rock failures are likely to occur extremely near the land surface around ruptures in such an area. From our simulation results, microwave signals generated by these rock failures should be detected by AMSR-E. Accordingly, we have developed an algorithm to detect rock failure microwave signals emitted from the ground in association with seismic activity from the data of AMSR-E [2, 3].

Volcanic surveillance is one of the practical fields for remotesensing technology. Monitoring of thermal anomalies on volcanoes by infrared radiometer and detection of slight landsurface deformations around volcanoes by interferometry of synthetic aperture radar (SAR) are good examples. However, an infrared radiometer is a little nervous for clouds which cover volcanoes, and interferometry of SAR also has a weakness that the time resolution becomes low in exchange for high spatial resolution. Meanwhile, focusing on microwave radiometer, we know it is less affected by clouds than infrared radiometer. Its time resolution is also higher than interferometry of SAR. Therefore, microwave radiometer can become a promising tool for volcanic surveillance. But, a new methodology to compensate its coase spatial resolution is essential. It was a serious problem.

It was experimentally confirmed that microwave energy is emitted during the compression of rocks. Land-surface deformations are likely to be accompanied by rock failures. From the experimental results, we could conclude that the microwave signals generated by rock failures near the land surface are detectable by a satellite-borne radiometer. Therefore, we developed an algorithm to evaluate the microwave energy generated by rock failures on the land surface and applied the algorithm to the data of the Advanced Microwave Scanning Radiometer for the Earth Observing System for the earthquake that struck Al Hoceima, Morocco, on February 24, 2004. As a result, we detected definitive microwave signals around the epicenter two days before the earthquake only in the entire observation period of six years. This paper presents the details of the algorithm and the analysis results.

It was experimentally confirmed that microwave is emitted during the compression of rocks. Land-surface deformations are likely to be accompanied by rock failures. From the experimental results, we could conclude the microwave signals generated by rock failures near the land surface are detectable by a satelliteborne radiometer. Therefore, we developed an algorithm to evaluate microwave energy generated by rock failures on the land surface, and applied the algorithm to the data of the Advanced Microwave Scanning Radiometer for Earth-Observation System for the earthquake that struck Sichuan, China, on May 12, 2008. As a result, we detected definitive microwave signals around the epicenter one day after the main shock only in the entire observation period of six years. This paper presents the details of the algorithm and the analysis results.

We propose a novel interface called Tearable that allows users to continuously experience the real sense of tearing paper. To provide such a real sense, we measured the actual vibration data of tearing a piece of real paper and analyzed them. Based on this data, we utilized hook-and-loop fasteners and a DC motor for representing the sense of tearing. We compared the force given by Tearable with that by a piece of real paper and recommended its reproducibility and usability. In addition, we evaluated Tearable with questionnaires after user experiences.

This letter presents the possibility of detecting earthquakes (EQs) from microwaves emitted when rock fractures. The method is based on an experiment in which microwave emission was detected from rock fracturing in a laboratory for the first time in the world. First, the method of calibrating emitted microwave power from experimental data is presented. A model of microwave emission and propagation to a satellite is then proposed. An advantage of microwaves is that they penetrate the Earth's ionosphere, unlike radiowaves of frequencies lower than several tens of megahertz. The power received by a satelliteborne receiver is estimated by assuming parameters of a radiometer currently operating in orbit. The result indicates that a satelliteborne receiver can detect microwave signals generated by an EQ. Based on this result, we attempted to detect some features associated with an actual EQ from the data of the Advanced Microwave Scanning Radiometer for Earth Observation System aboard the remote sensing satellite Aqua.

In order to extract a local and faint variation generated by a specific source from a physical value obtained by a remote-sensing satellite, we should focus on the difference between physical values at two points. We have developed a new data-restructuring algorithm based on this concept. This algorithm enables us to obtain a distribution of physical values at any interval and to calculate the difference between any two points regardless of the sensor-sampling interval. This paper presents this algorithm and how to implement it on a computer. Based on this data-restructuring algorithm, we have established a new data-processing method and analyzed the brightness-temperature data obtained by a microwave radiometer. As a result, we have successfully extracted the feature associated with a volcanic eruption. This feature cannot be extracted from brightness temperatures directly. This paper demonstrates this data-processing method by analyzing a volcanic eruption.

e-Learning is able to realize effective education by low cost, it also has problem it is difficult to know for teacher situation of learners. As a related idea, the concept map has been presented in pedagogical literature, and it can more easily and rapidly represent a part of learner's understanding without written and oral examination. In the authors' research, they have studied supporting individual learning based on modeling "keyword-map" that is a kind of "concept map", and especially focuses on transitive relation among keywords. They call such modeling KMSM (keyword map structural modeling). In this paper, they propose and consider applying KMSM to group learning.