ALOS-2 (Advanced Land Observing Satellite-2) / Daichi-2
ALOS-2 (Advanced Land Observing Satellite-2; SAR mission) / Daichi-2
ALOS-2 is the follow-on JAXA L-SAR satellite mission of ALOS (Daichi) approved by the Japanese government in late 2008. The overall objective is to provide data continuity to be used for cartography, regional observation, disaster monitoring, and environmental monitoring.
The post-ALOS program of JAXA has the goal to continue the ALOS (nicknamed Daichi) data utilization - consisting of ALOS-2 (SAR satellite) and ALOS-3 (optical satellite) in accordance with Japan’s new space program.
In 2010, ALOS has been operated for more than four years since January 2006 to accomplish four mission goals, including: cartography, regional observations, disaster monitoring, and resource surveys. ALOS-2 will continue the L-band SAR observations of the ALOS PALSAR (Phased Array L-band Synthetic Aperture Radar) and will expand data utilization by enhancing its performance. Table 2 shows the major observation advantages of the planned ALOS-2 mission when compared with the ALOS PALSAR. 1) 2) 3) 4) 5) 6) 7) 8) 9)
Note: The ALOS (Daichi) spacecraft was retired on May 12, 2011. The JAXA recovery team had been trying to communicate with ALOS for about three weeks after it developed a power generation anomaly.
Table 1: Overview of the ALOS-2 primary mission objectives
Figure 1: Long-Term Plan of JAXA Earth Observation (image credit: JAXA) 10)
Japan is an earthquake-prone and volcanic country where two-thirds of the land area is covered by forestry. The L-band Synthetic Aperture Radar (SAR), which was aboard the past two satellites, namely FUYO-1 (JERS-1) between 1992 and 1998 and DAICHI (ALOS) between 2006 and 2011, is a sensor using a radio wave (microwave), and it enables observations of land surface conditions even during the night and under bad weather. The special feature of the L-band radio wave (whose wave length is about 24 cm) is an ability to gather information from the land surface by penetrating vegetation such as forests (too a certain extent), thus it can acquire changes on the land more precisely compared to other band’s SAR when some diastrophism takes place due to an earthquake or a volcanic activity. 11)
DAICHI-2 (ALOS-2) is equipped with a global-leading L-band SAR (PALSAR-2) to conduct a health check mainly of the earth’s land areas in details. The observation performance has been improved to more promptly conduct accurate observations of the surface while maintaining a wide observation band. Hence, it will acquire more useful data that is directly related to our safe life as it can observe not only diastrophisms but also floods or landslides caused by a natural disaster, such as a storm or a gale, accurately in a timely manner. Its predecessor, DAICHI, responded to many requests for disaster monitoring from overseas, and, as a result, Japan was able to receive a lot of image data from foreign satellites in return in addition to those taken by the DAICHI when we were hit by the Great East Japan Earthquake. This data was very helpful to understand the situation of the unprecedented huge natural disaster in Japan. We would like to maintain this international cooperation framework with the DAICHI-2.
Besides natural disaster observations, the DAICHI-2 will regularly observe tropical rain forestry, which is difficult to observe optically due to thick clouds covering it frequently, as well as snow and ice conditions in the polar areas. By combining observation data acquired over more than 11 years, we will keep observing the time elapse to capture changes of forestry, which is a greenhouse gas sink, as well as the transformation of snow and ice due to the greenhouse gas effect. By doing so, we will contribute to environmental issues on a global scale.
With the L-band SAR, which is one of Japan’s specialties that has been inherited for a long time, the DAICHI-2 is a “national project” that contributes to safety and security in cooperation with domestic and overseas pertinent agencies. As an engineer, I am proud of participating in such an important project while I feel a heavy responsibility throughout the development of the satellite. I will do my utmost to achieve this project’s mission goal by launching and operating it smoothly in order to meet the expectations of its users and, eventually, of the people who are the ultimate beneficiaries.
The ALOS-2 system is developed by Mitsubishi Electric Corporation under contract to JAXA (Japan Aerospace and Exploration Agency).
A proper description of the spacecraft will be provided when available.
Precise positioning using GPS: ALOS-2 is equipped with spaceborne dual-frequency GPS receivers using both L1 and L2 bands, and demonstrated precise navigation on orbit. However, to achieve higher resolution observation and more accurate orbit maneuvering for next Earth observation satellites, an advanced GPS receiver was necessary. The JAXA Guidance and Control Group has been conducting a series of studies for a next-generation spaceborne GPS receiver. In this development, an enhancement of navigation accuracy is a major theme, and the new receiver will be reinforced with the ability to receive multiple frequencies and multiple channels to meet with GPS modernization. 12)
Figure 2: Artist's rendition of the ALOS-2 spacecraft in orbit (image credit: JAXA)
Recently, an algorithm of enhancing navigation accuracy especially when using the L1 band only by reducing the error due to ionospheric delay has been developed Based on the algorithm developed in this work, a software installed in the GPS receiver for ALOS-2 is developed (Ref. 4).
Real-time GPS L1 navigation:
- In monitoring disasters, real-time navigation using L1 signal is important
- Algorithm of enhancing navigation accuracy is developed (estimate of ionospheric delay and its change)
- Measurement accuracy < 10 m (95%, 3Drss).
Offline precise positioning:
- Dual (L1 and L2) off-line position determination < 1m
- ALOS-2 SAR frequency is overlapped with L2 signal
- Enhanced low-noise amplifier for GPS receiver with endurance against SAR signal is being developed
Figure 3: GPS L2 signal and SAR frequency allocation used in ALOS and ALOS-2
Table 3: Overview of major spacecraft parameters
Agile spacecraft: ALOS-2 has a body pointing function of ±30º in the roll axis. For the purpose of minimizing observation intervals, the requirement for attitude maneuvering is up to 2 minutes from the Earth pointing attitude to right- or left-looking, and the maneuvering from right- to left-looking (or from left- to right-looking) is up to 3 minutes, as shown in Figure 5.
To achieve a high agility of maximum attitude rate, 0.7º/s in roll axis, one Reaction Wheel (RW) is aligned with the roll axis, and the other four RWs are mutually skewed. This RW assembly was developed by the JAXA GCG (Guidance and Control Group), and establishes more than 0.9 Nm output torque and maximum momentum 40 Nms (at 3200 rpm). The numerical simulation results of attitude pointing are summarized in Table 4.
RF communications: The requirement calls for a payload data transmission rate of 800 Mbit/s in X-band. With a traditional modulation scheme of QPSK, the transmission speed peaks at about 400 Mbit/s since the frequency bandwidth allocation is limited to 375 MHz by the ITU (International Telecommunication Union) regulations.
To solve this problem, the project designed and developed XMOD (Multi-mode High Speed Modulator), capable of achieving a (max) data rate of 800 Mbit/s. The XMOD device has the following features, not only to achieve the 800 Mbit/s data rate, but also to target strong international competitiveness as well as high system reliability. 15) 16) 17)
1) Use of a 16QAM 16 (Quadrature Amplitude Modulation) scheme to enable the 800 Mbit/s data rate, regarded as the world’s highest RF data rate, implemented as a single X-band carrier.
2) Adoption of the QPSK (Quadrature Phase Shift Keying) technique to comply with existing ground stations and improve robustness.
3) Implementation of a “Multi-mode/Multi-rate” design capable of supporting various satellite projects.
4) Introduction of some cutting-edge techniques for space and a high reliability design to improve the tolerance to space radiation effects.
5) Reduction of XMOD in size and mass by boosting double-sided mounting techniques and applying small lightweight parts.
• Baseband module: The baseband module consists of the following devices:
- WizardLink family of multi-Gigabit Serializer/Deserializers (Ser/Des)
- SRAM-based FPGA (Virtex-4QV)
- High-speed Digital-to-Analog Converter (DAC5675A-SP)
- TCXO (Temperature Compensated Crystal Oscillator).
• RF module: The RF modules performs quadrature modulation on the I-channel and Q-channel signals generated by the baseband module, and then the modulated signals are amplified as desired.
• Load oscillator module: The local oscillator module generates the X-band local carrier frequency for the quadrature modulator
• DC/DC: The DC/DC converter, 30V-53V unregulated bus support, supplies regulated DC power to all the XMOD modules
Figure 6: Block diagram of XMOD (image credit: JAXA)
Table 5: Specification of the XMOD device
Figure 7: Photo of the XMOD EM (Engineering Model), image credit: JAXA
ALOS-2 has an improved data handling function which consists of a high-rate and huge-amount storage system, MDHS (Mission Data Handling System), and two types of high-rate transmission systems, DT (Direct Transmission) and DRC (Dual -Receive Channel), as shown in Figure 8. MDHS has a data storage volume of 130 GB. MDHS collects mission data from PALSAR-2 and health monitoring data from other components, and carries out digital processing such as adding of forward error correction code, file pointer management, and so on. It can be operated in various modes such as simultaneous record and replay, replay follow write, this scheme will contribute to flexible data handling operations.
The PALSAR-2 Electric Unit (ELU) consists of System Controller (SC), Data Processor (DP), as shown in Figure 61. SC receives command from satellite and sends telemetry to satellite. DP compresses mission data and sends it to MDHS.
Figure 9: Photo of the ALOS-2 proto flight model at JAXA's Tsukuba Test Facility in April 2012 (image credit: JAXA) 18)
Launch: ALOS-2 (Daichi-2) was launched on May 24, 2014 (03:05 UTC) on a H-IIA F24 vehicle (No 24) from the Yoshinobu Launch Complex at TNSC (Tanegashima Space Center), Japan. The launch provider was MHI (Mitsubishi Heavy Industries, Ltd.). At about 15 minutes and 47 seconds after liftoff, the separation of the DAICHI-2 was confirmed. 19) 20) 21) 22)
The secondary missions on the ALOS-2 mission by JAXA were: 23)
• Rising-2, a cooperative microsatellite (43 kg) project of Tohoku University (Sendai) and Hokkaido University, Sapporo, Japan.
• UNIFORM-1 (University International Formation Mission-1), of Wakahaya University, Wakayama, Japan.
• SOCRATES (Space Optical Communications Research Advanced Technology Satellite), a microsatellite (~ 50 kg) mission of NICT (National Institute of Information and Communications Technology), Koganei, Japan.
• SPROUT (Space Research on Unique Technology), a nanosatellite of ~7 kg of Nihon University, Tokyo, Japan.
Figure 10: Photo of the secondary payloads integrated on the adapter ring of the second stage (image credit: JAXA)
Orbit: Sun-synchronous near-circular sub-recurrent orbit, altitude = 628 km, inclination = 97.9º, period = 97.4 minutes, revisit time = 14 days, number of orbits/day = 15 3/14, LSDN (Local Sun time on Descending Node) = 12:00 hours ± 15 min.
To achieve higher coherence of interferometry, autonomous accurate orbit maneuvering (within 500 m orbital tube) and enhanced GPS receiver with endurance against L-band SAR signal were developed. The orbit control requirement to satisfy the geometric restriction which arises from the repeat-pass SAR interferometry, is illustrated in Figure 11. The reference Earth-fixed flight path is defined for a repeat cycle of its orbit. ALOS-2 satellite must fly within a tube-shaped corridor, the center of which is the reference flight path. The radius of the tube-shaped corridor, 500 m, is the tolerance of an orbit error. The orbit prediction, based on a detailed perturbation model, is introduced to generate the reference flight path. Using it as a reference of orbit maintenance, unnecessary orbital maneuvers can be avoided.
As a result of numerical simulations, throughout the mission life, orbit maintenance within the 500 m tube was verified to be accomplished 99.7% of the time, which exceeds the requirement of 95%. An average period between orbit maneuvers was 4.9 days for in-plane maneuver and 176 days for out-of-plane maneuver. The minimum interval of in-plane maneuvers during active solar period was estimated 1.5 days. This means the autonomous orbit maintenance is essential for this mission in terms of operational aspects.
The on-board software of ALOS-2 can handle operations of orbit determination, maneuver prediction and planning, and maneuver executions for both drag-makeup maneuvers and inclination maneuvers. This feature of autonomy is expected to be great help for efficient ground operations of ALOS-2. 24) 25)
Figure 12: Flow chart of autonomous orbit control algorithm (image credit: JAXA)
• July 14. 2020: According to one estimate, there are more than 3.6 million lakes in the Arctic. They are remote and hard to reach and sample in the field, especially when they are covered with ice during the Arctic’s long winters. 26)
- Yet they are critically important to understanding climate change. As tiny organisms in Arctic lake sediments called archaea break down organic matter, they release methane, a potent greenhouse gas. Methane (CH4) has a heat-trapping power about 30 times stronger than carbon dioxide.
Figure 13: Detail image of Figure 14. Using the SAR-based technique, Engram and colleagues calculated the methane flux—the rate of methane exchanged between the lake and the atmosphere—of 5,143 of the estimated 134,000 lakes in Alaska. To validate their satellite observations, they also made ground-based measurements at dozens of lakes near Barrow Peninsula, Atqasuk, Toolik, Northern Seward Peninsula, and Fairbanks, where they placed submerged “bubble traps” to measure methane emissions (image credit: NASA Earth Observatory images by Lauren Dauphin, using data from Engram, Melanie, et al. (2020) and Landsat data from the U.S. Geological Survey. The researchers used data collected by the PALSAR (Phased Array type L-band Synthetic Aperture Radar) sensor on the Japanese ALOS-2 (Advanced Land Observing Satellite). The data is processed and stored by the Alaska Satellite Facility at the University of Alaska Fairbanks. Story by Adam Voiland)
- Finding the sources of methane around the world and measuring how much they are emitting has become an important scientific pursuit. Most attempts to measure methane emissions from lakes have focused on summer conditions when lakes are ice free, but the processes that produce the gas continue through the winter when many lakes are frozen.
- “But the sheer number of Arctic lakes makes getting to them all impossible in any season,” explained Melanie Engram, a University of Alaska scientist. To get around this problem, Engram and colleagues have developed a new satellite-based technique to measure methane from lakes. The new technique makes use of L-Band synthetic aperture radar (SAR), a technology that involves bouncing microwaves off Earth’s surfaces and looking for changes in the reflection patterns observed by the satellite. The technique works even in cloudy conditions, if a layer of snow covers lake ice, or in darkness.
- “When methane rises from the lake bottom, the columns of bubbles serve as insulators, slowing ice growth near the bubble column,” explained Engram. “Ice grows more quickly around the column, and you end up with these big divots beneath bubble columns that fill with water. Since water is especially reflective to microwave pulses, we are able to make measurements of how the waves bounce back after hitting the water divots to infer how much methane has bubbled up.” The photograph above shows an example of how methane bubbles in a frozen lake in Fairbanks, Alaska, can alter ice.
Figure 14: Synthetic Aperture Radar of ALOS-2 is offering scientists a new way to measure how much of the potent greenhouse gas is bubbling up from frozen Arctic lakes. The team found that the smallest lakes tended to have the highest fluxes, but the larger lakes emitted more gas by volume. The map at the top of the page shows methane fluxes for the lakes surrounding Fairbanks—an area that stood out for the range of fluxes in its lakes. Several of the smaller lakes had fluxes that exceeded 90 grams per square meter per year; most of the larger lakes were between 0 and 15 (image credit: NASA Earth Observatory)
- Measuring methane flux from Arctic lakes is part of a broader effort to better understand the methane budget—an accounting of how much of the gas is moving between various parts or the environment. Concentrations of methane in the atmosphere have risen significantly in recent decades, prompting scientists to try to understand why. Yet because there are several ways that methane enters the atmosphere, pinpointing the sources of the increase is difficult. Fossil fuel production, agriculture, fires, wetlands, thawing permafrost, and several other sources all emit methane and could be contributing to the buildup of the gas.
- While Arctic lakes, wetlands, and permafrost are thought to be a modest source of methane, they are of particular concern because global warming could be increasing their share of emissions. Previous attempts to quantify methane flux from Arctic lakes have produced starkly different estimates. “Top-down” estimates, based on measurements from airplanes, satellites, and modeling, imply a flux rate that is two or three times lower than “bottom up” approaches, which are based on ground-based measurements at a limited number of lakes and then extrapolating across larger areas.
- “This SAR work is really exciting because it is helping us resolve the big discrepancy between top-down and bottom-up estimate that we have had for years,” said Katey Walter Anthony, also of the University of Alaska. “These SAR results are showing us that some of the bottom-up estimates we did in the past were too high.”
- Still, Engram and Walter Anthony caution that their SAR work has just begun, as they have analyzed less than 0.14 percent of the lakes in the Arctic. “We would love to extend our analysis to all Arctic lakes eventually,” she said. “There is plenty of SAR data available for Alaska, Canada, and Greenland. The biggest challenges will be Russia, the largest region of the Arctic, but where SAR coverage is very sparse.”
Figure 15: A key reason the small lakes around Fairbanks had such high fluxes is that they are located within yedoma—a type of Pleistocene-aged permafrost rich with organic material that releases significant amounts of methane when thawed. There are also some gravel-filled mining lakes around Fairbanks that have very low methane flux. In more northerly parts of Alaska, such as Barrow Peninsula, lakes tended to be larger, more numerous, and had a lower flux (image credit: NASA Earth Observatory)
• January 23, 2020: JAXA (Japan Aerospace Exploration Agency) has agreed to collaborate with Food and Agriculture Organization of the United Nations (FAO) on data utilization of Earth observation satellites, and Imai Ryoichi, JAXA Vice President and Daniel Gustafson, FAO’s Deputy Director-General for Programs have signed the Memorandum of Understanding at JAXA Tsukuba Space Center on January 23, 2020. 27)
- Leveraging this cooperation, JAXA and FAO will be monitoring forests and mangroves around the world by JAXA's satellites with L-band Synthetic Aperture Radar (SAR).
- Only JAXA has observed forest using L-band radar (SAR) technology from 1992. Observation data of global forests that JAXA has been accumulating for over 25 years will be provided to SEPAL ( System for Earth Observation Data Access, Processing and Analysis for Land Monitoring) that is FAO's toolkit for monitoring forest and land-use. Additionally, this cooperation supports JAXA to improve the accuracy of its satellite data.
Figure 16: Imai Ryoichi, JAXA Vice President (left) and Daniel Gustafson, FAO’s Deputy Director-General (right) have signed the Memorandum of Understanding on January 23, 2020. The partnership adds powerful L-band radar data to FAO’s geospatial toolkit to monitor forests around the world (image credit: JAXA)
- SEPAL offers anyone easy-to use access to satellite data and supercomputing power, allowing them to create critical forest and land cover information in their efforts to mitigate and adapt to climate change, and now is used in 160 countries.
- Thanks to this cooperation, available data on SEPAL will be expanded, and users will be able to access JAXA’s forest observation information and satellite data. Since satellite radar have the capability to provide information on forest and mangroves in the areas where optical satellites are impeded by weather (rain and clouds) or lack of sunlight, the improvement of capability for forest and land-use management in these areas is expected.
- JAXA will continue the forest observations using our satellites in cooperation with various users around the world, and will provide satellite data widely as a scientific evidence to support decision-making on forest management which is a sink for greenhouse gases. With these efforts, JAXA hopes to contribute to the achievement of the Paris Agreement and Sustainable Development Goals (SDGs).
• January 23, 2020: FAO will bolster the scale and scope of its geospatial monitoring toolkit thanks to collaboration with the Japan Aerospace Exploration Agency (JAXA) that will expand the capacity of FAO's accessible platforms for forestry and land-use assessments. 28)
- A three-year agreement signed today will enhance the access of FAO member states and other users to JAXA data sets and more "ground-truthing" evidence through FAO's forest monitoring platforms.
Figure 17: A part of Sudan, seen from above (image credit: FAO, JAXA)
- "As deforestation and land-use changes are one of the leading sources of global carbon emissions, satellite-based information has a critical role to play in supporting countries to achieve their commitments on climate change," said Daniel Gustafson, FAO's Deputy Director-General for Programs, who signed the agreement in Tsukuba today.
- Technically, the new collaboration will expand the scope and usability of FAO platforms such as SEPAL and the Global Forest Resources Assessment Remote Sensing Survey, while also boosting the granular accuracy of JAXA-led initiatives that cover the world's mangroves as well as forestry and land-use themes in general. JAXA uses L-band Synthetic Aperture Radar (SAR) technology which has a unique feature of being able to observe the Earth's land surface regardless of time (day and night) and weather (rains and clouds) with waves with especially long wavelengths, allowing to accumulate both vegetation and ground information.
- "Over 20 years, JAXA has accumulated global L-band SAR data, which is essential to understand changes in forests and predict their future. JAXA expects our satellite data to be used to support sound decision-making," said JAXA Vice President Imai Ryoichi, noting that the application of L-band SAR data would be further required in a variety of areas to tackle global agenda and that JAXA stands ready to contribute in remote sensing areas.
- Along with offering reciprocal access to select data, FAO and JAXA will conduct training workshops for FAO member states and integrate the data FAO's Open Foris platform.
- FAO's geospatial toolkit, including SEPAL - the System for Earth Observation Data Access, Processing and Analysis for Land Monitoring now has more than 4,300 active users from 160 countries- offers anyone easy-to-use access to satellite data and supercomputing power, allowing them to create critical forest and land cover information in their efforts to mitigate and adapt to climate change. The SEPAL platform is built on collaboration and partnerships, and JAXA joins Google, NASA, ESA, Planet, and the World Bank as contributors to the platform. The SEPAL project is funded by NICFI (Norway's International Climate and Forest Initiative).
- FAO expects the collaboration will benefit its ongoing work on forest, peatland and mangrove monitoring and assessment, areas in which JAXA initiatives including the Global Mangrove Watch and JJ-Fast - a forest early warning system in the tropics set up by JAXA and JICA (Japan International Cooperation Agency) are highly valued contributions.
- "This is the kind of partnership that smartly leverages skills and resources to boost our knowledge base and potential impact," said Hiroto Mitsugi, FAO Assistant-Director-General of the Forestry Department.
• November 6, 2019: On September 28, 2018, a powerful, shallow earthquake ruptured the land surface and seafloor near Indonesia’s Sulawesi island and sent a devastating tsunami into the city of Palu. While the nearby strike-slip fault was a known tsunami hazard, the magnitude 7.5 earthquake surprised scientists because it triggered large and deadly landslides in an area with a gently sloping landscape. 29)
- One year later, a team of scientists from six countries has unraveled the mystery of the landslides and discovered a new earthquake hazard in the process. Examining various types of radar and visible satellite data, the team found that mud and soil flowed most readily near irrigated rice paddies.
Figure 18: An earthquake in Indonesia made the land flow like mud in a place where science previously said it shouldn't. This image of PALSAR-2 on ALOS-2 is a damage proxy map created by Yun and colleagues at NASA/JPL. They examined satellite radar data collected before and after the quake, mapping changes in the land surface and built structures. Yun’s data has been overlaid on a digital elevation map to show the slope of the landscape (image credit: NASA Earth Observatory, image by Joshua Stevens, using data courtesy of Bradley, K. et al. (2019) and topographic data from the Shuttle Radar Topography Mission (SRTM). Story by Michael Carlowicz, with reporting from Esprit Smith and Carol Rasmussen, NASA Jet Propulsion Laboratory, and Shireen Federico, Nanyang Technological University)
- The practice of keeping farmland soaked for rice cultivation slowly draws the water table—the layer below ground where the soil becomes saturated—closer to the land surface. This makes the soil wetter and more prone to liquefaction—the process by which sandy soils behave like a liquid in response to strong ground shaking. As shaking overpowers the friction that normally holds particles together, soil loses its structural integrity and begins to flow like a liquid. It can act like a lubricated surface, allowing relatively solid ground to slide freely downslope under the force of gravity.
- Soil liquefaction usually occurs in flat landscapes with sandy or silty ground, such as coastal plains where the water table is close to the surface. While Palu has sandy soil, the gently sloping valley around the city appeared to pose little risk as high water tables are rare on hillsides. But when researchers began to examine damage after the Palu quake, they noticed that all the landslides originated along a distinct line and near an aqueduct. “We started studying why the aqueduct so clearly defined the boundary between land sliding and not sliding,” said Sang-Ho Yun, a natural disasters researcher at NASA’s Jet Propulsion Laboratory.
- The Gumbasa Aqueduct was built in the early 20th century on the east side of Palu to reduce the risk of famine by providing a consistent water supply to local farmers. Only the land downhill from the aqueduct is irrigated. Farmers just below the aqueduct practice wet rice cultivation, in which fields are flooded at one point in the growing cycle. Farther downhill, near Palu, farmers grow tree crops like coconut palms, which require less irrigation and do not raise the water table as much.
- Despite slopes of no more than 1.5 to 2 degrees, the earthquake caused land to slide as much as 1 kilometer. The cause was widespread liquefaction in the irrigated rice paddies below the aqueduct. (No liquefaction was identified upslope of the aqueduct, where the water table was closer to its natural level.) Because the aqueduct did not have an impermeable lining, it is likely that leakage also played a role. The slides were slowed or halted by the coconut palm plantations.
- “If there hadn't been intensive irrigation, the landslides and the resulting damage and loss of life probably would not have happened,” said Bradley, the lead author on the paper. “This was a human-caused hazard, and it can have a human solution. We cannot directly reduce the hazard of ground shaking on Palu, but the agricultural practices can be updated to reduce the human exposure to this hazard.” For instance, farmers could plant more trees near their rice fields in order to better anchor the soil and draw down the water table.
- The findings from Palu have Bradley and colleagues considering whether agricultural practices have played a role in other landslides or could be creating new seismic hazards elsewhere. Indonesia is not the only place in the world where people grow heavily irrigated crops on wet, sandy slopes. “There are a few historical cases where earthquake-triggered liquefaction seems to have been strongly correlated with irrigation, and cases where major slope failures and landslides were related in some way to irrigation,” Bradley added. “This is likely to be a problem where irrigation practices are inefficient and excess groundwater exists. However, any tectonically active location with sandy soils, a surface slope, and a raised water table are of concern.”
Figure 19: These maps made from data provided by Kyle Bradley of Nanyang Technological University. Provoked by damage maps, Bradley and colleagues gathered land-cover maps plus visible satellite imagery taken by the commercial satellite company Planet just before and after the Palu earthquake in order to determine where and why the land deformed and slid. They used software to calculate horizontal land displacement, particularly in areas around the aqueduct (image credit: Planet and NASA Earth Observatory using data courtesy of Bradley, K. et al. (2019). Story by Michael Carlowicz, with reporting from Esprit Smith and Carol Rasmussen, NASA/JPL and Shireen Federico, Nanyang Technological University)
• July 25, 2019: The ground beneath Southern California moved furiously in early July 2019 due to two large earthquakes, one of which was the strongest in the region in at least two decades. Remote sensing scientists are getting better at measuring such events and showing how they disrupt and move the land surface. 30)
- At 10:33 a.m. Pacific Daylight Time (PDT) on July 4, 2019, an earthquake struck northeast of Ridgecrest, California, which is north of Los Angeles and northeast of Bakersfield. The magnitude 6.4 temblor turned out to be a foreshock of a stronger quake—magnitude 7.1—that occurred at 8:19 p.m. PDT on July 5 about 6 miles (11 km) to the northwest. In the days and weeks that followed, thousands of aftershocks rumbled beneath Southern California, the vast majority of them too small to be felt by humans. Though news outlets described some damage to business and residential property, no major casualties or infrastructure breaks were reported.
Figure 20: Remote sensing scientists are getting better at measuring such events and showing how they disrupt and move the land surface. The maps are based on data from the ARIA (Advanced Rapid Imaging and Analysis) team at NASA/JPL (Jet Propulsion Laboratory) and the California Institute of Technology’s Seismological Laboratory, as well as a digital elevation model to show the contours of the land surface. This map depicts the amount of ground displacement—land shifting vertically, horizontally, or both—in meters. Blue areas moved roughly northwest (horizontally) and up (vertically), while red and orange areas moved southeast and down (image credit: NASA Earth Observatory, image by Joshua Stevens, using ALOS-2 (Advanced Land Observing Satellite-2) data courtesy of Eric Fielding/NASA JPL and JAXA (Japan Aerospace Exploration Agency). Story by Michael Carlowicz)
- According to the USGS (U.S. Geological Survey), the Ridgecrest earthquakes released energy along at least two shallow strike-slip faults about 100 miles (150 km) northeast of the San Andreas Fault. The quakes fell within the Eastern California shear zone (sometimes called Walker Lane), in an area where the faults and their connections are less understood than the San Andreas.
- The first earthquake (M6.4) involved motion on a fault aligned from northeast to southwest; this is visible on the map of Figure 20) as a difference in the colors between Ridgecrest and the area to the southeast. That quake probably triggered the larger earthquake (M7.1) with motion on a nearly perpendicular fault running northwest to southeast (the much stronger color discontinuity).
Figure 21: This ARIA Team map, observed with ALOS-2 on 16 April 2018 and 8 July 2019, shows this displacement visualized in three dimensions (image credit: NASA Earth Observatory, image by Joshua Stevens, using ALOS-2 (Advanced Land Observing Satellite-2) data courtesy of Eric Fielding/NASA JPL and JAXA (Japan Aerospace Exploration Agency). Story by Michael Carlowicz)
- ARIA researchers compiled and processed SAR (Synthetic Aperture Radar) data from the Japan Aerospace Exploration Agency’s ALOS-2 satellite. SAR instruments bounce radio signals off of the ground and measure the reflections to determine the distance between the ground and the satellite. By comparing SAR images from different days, scientists can determine how much the land surface and human-built structures have shifted. (The ARIA team also used the data to create a map depicting areas that were likely damaged as a result of the earthquakes.)
- “These radar movement maps tell scientists where the faults moved and how much each part of the faults moved during the two earthquakes,” said Eric Fielding, a geophysicist and part of the ARIA group. “Geophysicists can then use computer models to estimate how stress has increased or decreased on other faults in the surrounding area.”
- According to the ARIA team, the land on the west side of the fault (blue) moved by as much as 0.8 m. Red/orange areas moved by as much as 0.6 m. According to USGS, the Pacific plate generally moves to the northwest (relative to the North American plate) at approximately 48 mm/year.
- NASA provides such maps to the California Geological Survey, the Federal Emergency Management Agency, and USGS as they assess damages and map the faults. The analysis can be used to estimate where the fault moved deep and which areas have increased stress and higher likelihood of future earthquakes.
- “The SAR data were very useful for field mapping teams to help guide them where faults are located,” said Chris Milliner, a geophysicist at JPL. “One interesting result is that the SAR revealed many more faults surrounding the main rupture than was anticipated, which might have been missed in the field without this remote guidance.”
• July 9, 2019: Damage from two strong earthquakes that rattled Southern California on July 4 and July 5 — a magnitude 6.4 and a magnitude 7.1, respectively — can be seen from space. The epicenter of the quakes was near the city of Ridgecrest, about 150 miles (241 km) northeast of Los Angeles. According to the U.S. Geological Survey, the 7.1 quake was one of the largest to hit the region in some 40 years. 31)
- The Advanced Rapid Imaging and Analysis (ARIA) team at NASA's Jet Propulsion Laboratory in Pasadena, California, used synthetic aperture radar (SAR) data from the ALOS-2 satellite to produce a map showing surface displacement from the earthquakes. The post-quake imagery was acquired on July 8, 2019, and compared with April 8, 2018, data from the same region.
Figure 22: NASA's Advanced Rapid Imaging and Analysis (ARIA) team created this co-seismic Interferometric Synthetic Aperture Radar (InSAR) map, which shows surface displacement caused by the recent major earthquakes in Southern California, including the magnitude 6.4 and the magnitude 7.1 events on July 4 and July 5, 2019, respectively. The interferogram is derived from synthetic aperture radar (SAR) images from the ALOS-2 satellite, operated by JAXA (Japan Aerospace Exploration Agency). The images were taken before (April 16, 2018) and after (July 8, 2019) the sequence of earthquakes. - The image covers an area of 50 x 125 km, and each pixel measures about 90 m across. No filter was applied during the processing. The linear features across which the color fringes break indicate likely locations of surface rupture caused by the earthquakes, and the "noisy" areas may indicate locations where ground surface was disturbed by the earthquakes (image credit: NASA/JPL-Caltech)
- Each color cycle represents 12 cm of ground displacement in the radar line-of-sight. The linear features that cut the color fringes in the southeast indicate likely locations of surface rupture caused by the earthquakes, and the "noisy" areas in the northwest may indicate locations where the ground surface was disturbed by them.
- The USGS reported over 1,000 aftershocks in the region following the July 5 earthquake. State and federal scientists, including those from the California Geological Survey and USGS, are using this surface deformation map in the field for assessing the damages and mapping the faults that broke during the two major earthquakes as well as the thousands of aftershocks.
- In the aftermath of the earthquakes, NASA's Earth Science Disasters Program is in communication with the California Earthquake Clearinghouse, which is coordinating response efforts with the California Air National Guard, the USGS and the Federal Emergency Management Agency. NASA analysts are using data from satellites to produce visualizations of land deformation and potential landslides, among other earthquake impacts, and are making them available to response agencies. NASA's Disasters Program promotes the use of satellite observations in predicting, preparing for, responding to and recovering from disasters around the world.
- JAXA provided the ALOS-2 data for the production of the map. The ARIA team's analysis was funded by NASA's Disasters Program.
• February 2019: The ALOS-2 mission is in its 5th year on-orbit operating nominally.
• December 26, 2018: Observation Result for Eruption of Anak Krakatau Volcano in Indonesia by ALOS-2. 32)
Overview: On 22 December 22 2018, Anak Krakatau erupted and the probably-related tsunami caused serious damages on coastal cities. JAXA performed an emergency observation with the PALSAR-2 (Phased Array type L-band Synthetic Aperture Radar-2) instrument aboard the ALOS-2/DAICHI-2 satellite on 24 December 2018. Table 6 summarizes the observation data by ALOS-2. Figure 1 shows the observation area by ALOS-2.
- On December 22, 2018, Tsunami probably related to the eruption of Anak Krakatau caused serious damages on coastal cities close to the island.
- JAXA performed an emergency observation by ALOS-2 (“DAICHI-2”) on December 24, 2018 (UTC), and ALOS-2 captured significant topographic changes in the southern island.
Figure 23: Region of observation of ALOS-2 (image credit: JAXA/EORC)
Figure 24: Comparison of the two HH amplitude images acquired before (August 20, 2018) and after (December 24, 2018) the eruption. The white-dotted circle shows Anak Krakatau Island (image credit: JAXA/EORC)
Figure 25: This image is a polarimetric color-composite (red: August 20 HV polarization, green: December 24 HV pol., blue: December 24 HH pol.), where the topographic change is easier to identify than Figure 24 (image credit: JAXA/EORC)
• July 2018: JAXA has been regularly checking the performance of the ALOS-2 bus system which is operating nominally. The orbit is automatically controlled within a 500 m radius tube around the reference orbit. As shown in Figure 26, the success rate of the autonomous orbit control was almost 100%. The signal plots (Figure 26) of the 16QAM constellation were distributed around the ideal positions, and the obtained frequency spectrums were good, indicating successful data transmission to the ground stations. 33)
- The performance of PALSAR-2 system is checked every three months. The main items are the thermal condition of components, phase-shifter performance, and onboard RF characteristics. As a result, PALSAR-2 also works very well. The PALSAR-2 data were acquired based on a systematic observation strategy known as BOS (Basic Observation Scenario) to achieve consistent data acquisitions in time and space. Among the various observation modes of PALSAR-2 such as Spotlight, 3/6/10-m resolution stripmap, and ScanSAR, the coverage of Japan area by 3 m stripmap mode is shown in Figure 27, and the coverage of the global world by 10 m stripmap is shown in Figure 28.
- Scientific activities: PALSAR-2 data are distributed to both scientific and commercial users. Commercial distribution is granted to the ALOS-2 Data Distribution Consortium. On the other hand, the Earth Observation Research Center (EORC) of JAXA is responsible for the research announcement (RA) for distributing PALSAR-2 data to every researcher, called principal investigator (PI), selected in a peer-review process. JAXA made contracts with more than 700 PIs from all over the world in total for the first and second ALOS-2 RAs (RA4 and RA6 in 2013 and 2016) and the first joint RA of Earth observation in 2017.
Figure 27: Coverage of the acquired data for Japan area by 3 m stripmap mode (U2, right-looking) in (left) ascending and (right) descending orbit (August 2014 to July 2017). The colors represent the number of data acquisitions (image credit: JAXA)
Figure 28: Coverage of the acquired data for the global world by 10 m stripmap mode (F2, right-looking) in (left) ascending and (right) descending orbit (August 2014 to July 2017). The colors represent the number of data acquisition (image credit: JAXA)
- Observation highlights: PALSAR-2 is utilized for disaster monitoring, environmental monitoring, and many other fields of applications with the advantages of SAR such as all-weather and day-and-night observation capability. The L-band SAR data has particular advantage of high penetration and interferometric coherence.
- Figure 29 shows the flood area estimation of the west coast of Florida on September 12, 2017, struck by Hurricane “Irma.” Responding to the emergency requests from the International Charter of Space and Major Disasters, JAXA performed this observation and data analysis.
• On May 25, 2018, JAXA (Japan Aerospace Exploration Agency) and FRMO (Forest Research and Management Organization)/ FFPRI (Forestry and Forest Products Research Institute), signed a basic agreement concerning the application of Earth observation satellite data to collaboratively solve issues surrounding the global forests. FRMO and FFPRI are both of Tsukuba, Japan. 34)
- In order to sustain and activate various functions of forests such as conservation of national landscapes, fostering of water resources and prevention of global warming, it is necessary to monitor the forest resources and to promote forest development systematically. Since a vast proportion of the world’s tropical rainforests lies in developing countries,where funds and human resources are limited the protective mechanism is not fully in place.
- JAXA's ALOS-2/Daichi-2 mission as well as other earth observation satellites promptly monitor wide swaths from space. The observation data enables us to track changes in the forests including disaster-hit and inaccessible areas.
- Based on this agreement, JAXA will provide with local governments the satellite data for forest stewardship and the latest status through JICA-JAXA (Forest Early Warning System in the Tropics), JJ-FAST. Data verification will ensue in developing countries to improve the accuracy of JJ-FAST by comparing JJ-FAST data with the ground-based counterpart including statistics of deforestation presented by FFPRI. — FFPRI will use the satellite data from JAXA to examine forest management methods that local governments can employ and explore possibilities to utilize the data for forest monitoring in developing countries.
- JJ-FAST is a project, jointly developed by JICA (Japan International Cooperation Agency) and JAXA. JJ-FAST monitors the removal and other changes of tropical forests usingALOS-2/Daichi-2 satellite data. Daichi-2 has the observation capabilities that penetrate the clouds which are present throughout the year above some portions across the tropics due to their long wet season. Currently, 77 countries are using JJ-FAST. In Brazil, the system helped identify and monitor the groups that illegally cleared the forest.
Note: In November 2016, JICA (Japan International Cooperation Agency) and JAXA launched the “JICA-JAXA Forest Early Warning System in the Tropics” (JJ-FAST) service, easily accessible from PCs and smartphones to obtain information based on deforestation and forest change data for tropical regions using JAXA’s ALOS-2 (Advanced Land Observing Satellite-2). 35) 36)
• January 24, 2018: The ALOS-2 spacecraft and its payload are operating nominally in 2018. The PALSAR-2 calibration and validation are conducted regularly. ALOS-2 keeps good performance over 3 years, a lot of L-band data have been accumulated. 37)
1) Internal calibration
- Using the on-board calibration mode every 3 months
- Keeping good condition after launch
2) External calibration: Product quality of major observation modes has been evaluated regularly using SAR data over the calibration sites.
- Point target characteristics (resolution, etc.)
- Radiometric accuracy
- Geometric accuracy
- Polarimetric calibration.
Figure 30: ALOS series development/operation (image credit: JAXA)
• December 6, 2017: On November 21, 2017 Mount Agung in Bali Island, Indonesia, began eruption for the first time in 54 years. JAXA performed an emergency observation with the PALSAR-2 (Phased Array Type L-band Synthetic Aperture Radar 2) onboard ALOS-2/ DAICHI-2 (Advanced Land Observing Satellite-2) on around 16:38 on November 30, 2017 (UT). 38)
- Figure 31 illustrates the observation area and the overall image. The observation mode was the high-resolution 10 m mode (dual polarization). The color composite in the image represents HH polarization in red, HV polarization in green, and HH/HV in blue. In this image, black or dark blue roughly show water or bare land, green shows the vegetation covered areas, and bright green or purple show the urban areas.
• July 25, 2017 (with updates on Oct. 12, 2017): Larsen is one of the huge ice shelves in Antarctica. Larsen-A and -B experienced their destruction in 1995 and 2002, respectively. The Larsen Ice Shelf affects the ice loss in west Antarctica and its contribution to global sea level rise. Therefore, many glaciologists have paid much attention to their dynamics. On 12th July, 2017, a large iceberg separated from Larsen-C Ice Shelf, whose mass is estimated to be one trillion tons, its surface area is about 5,800 km2. Due to its size, the ALOS-2 ScanSAR mode (Observation width: 350 km) is suitable for capturing the entire portion of the iceberg (Figure 32). 39)
Overview of updated events:
1) A huge iceberg detached from Larsen-C Ice Shelf in Antarctic Peninsula on 12th July, 2017.
2) ALOS-2 ScanSAR observation on 21st July, 2017 revealed the entire portion of the detached iceberg.
3) The observation image on 4th August, 2017 shows that the iceberg was pushed back toward the ice shelf by sea ice.
4) The observation image on 1st September, 2017 shows that the iceberg again started to be away from the ice shelf.
5) The observation image on 29th September, 2017 shows that the distance between the ice shelf and iceberg was larger than 20 km.
Figure 33: Animation composed of four ALOS-2 observation images on 19th August, 2016, 21st July, 2017, 4st August, 2017, and 1st September, 2017 (image credit: JAXA)
Figure 34: This image shows a comparison of the color-composite images (red: HV, green: HV and blue: HH polarization) observed on 29th September, 2017 (left) and 1st September, 2017 (right). The image on 29th September shows that the width of the crack between the huge iceberg and the ice shelf became 20 km larger than that in 1st September (blue arrows). We have considered that the sea ice around the iceberg has been thinning with the progress of season (yellow arrow) and that the force of sea ice pushing toward the ice shelf has been weakening. Moreover, a small iceberg calved from the huge iceberg (red arrow). The huge iceberg is estimated to flow offshore, and we are going to continue the observation by ALOS-2 (image credit: JAXA)
• August 30, 2017: The ARIA (Advanced Rapid Imaging and Analysis) team at NASA/JPL in Pasadena, California, created this Flood Proxy Map depicting areas of Southeastern Texas that are likely flooded as a result of Hurricane Harvey, shown by light blue pixels. The map is derived from synthetic aperture radar amplitude images from the Japan Aerospace Exploration Agency's (JAXA) ALOS-2 PALSAR-2 satellite, taken before (July 30, 2017) and after (August 27, 2017) Hurricane Harvey made landfall. The map covers an area of 350 km2. Each pixel measures about 50 m2. Local ground observations provided anecdotal preliminary validation. This flood proxy map should be used as guidance to identify areas that are likely flooded, and may be less reliable over urban areas. ALOS-2 data were accessed through the International Charter. 40) 41)
Figure 35: JPL ARIA team created this Flood Proxy Map showing areas of Southeast Texas likely flooded from Hurricane Harvey (light blue). The map is derived from radar images from the JAXA (Japan Aerospace Exploration Agency) ALOS-2 PALSAR-2 satellite before and after landfall (image credit: NASA/JPL-Caltech/JAXA/METI/Google Earth)
• March 23, 2017: Last November's magnitude 7.8 Kaikoura earthquake in New Zealand was so complex and unusual, it is likely to change how scientists think about earthquake hazards in plate boundary zones around the world, finds a new international study. 42) 43)
- The study, led by GNS Science, Avalon, New Zealand, with NASA participation, is published this week in the journal Science. The team found that the Nov. 14, 2016, earthquake was the most complex earthquake in modern history. The quake ruptured at least 12 major crustal faults, and there was also evidence of slip along the southern end of the Hikurangi subduction zone plate boundary, which lies about 20 km below the North Canterbury and Marlborough coastlines. 44)
- Lead author and geodesy specialist Ian Hamling of GNS Science says the quake has underlined the importance of re-evaluating how rupture scenarios are defined for seismic hazard models in plate boundary zones worldwide. "This complex earthquake defies many conventional assumptions about the degree to which earthquake ruptures are controlled by individual faults, and provides additional motivation to re-think these issues in seismic hazard models," Hamling says.
- The research team included 29 coauthors from 11 national and international institutes. To conduct the study, they combined multiple datasets, including satellite radar interferometry and GPS data that measure the amount of ground movement associated with the earthquake, along with field observations and coastal uplift data. The team found that parts of New Zealand's South Island moved more than 5 m closer to New Zealand's North Island and were uplifted by as much as 8 m.
- The Kaikoura earthquake rupture began in North Canterbury and propagated northward for more than 170 km along both well-known and previously unknown faults. It straddled two distinct active fault domains, rupturing faults in both the North Canterbury Fault zone and the Marlborough Fault system.
- The largest movement during the earthquake occurred on the Kekerengu fault, where pieces of Earth's crust were displaced relative to each other by up to 25 m, at a depth of about15 km. Maximum rupture at the surface was measured at 12 m of horizontal displacement.
- Hamling says there is growing evidence internationally that conventional seismic hazard models are too simple and restrictive. "Even in the New Zealand modeling context, the Kaikoura event would not have been included because so many faults linked up unexpectedly," he said. "The message from Kaikoura is that earthquake science should be more open to a wider range of possibilities when rupture propagation models are being developed."
- The scientists analyzed interferometric synthetic aperture radar (InSAR) data from the Copernicus Sentinel-1A and -1B satellites, which are operated by the European Space Agency, along with InSAR data from the Japan Aerospace Exploration Agency's ALOS-2 satellite. They compared pre- and post-earthquake images of Earth's surface to measure land movement across large areas and infer movement on faults at depth. The Sentinel and ALOS-2 satellites orbit Earth in near-polar orbits at altitudes of 600 and 700 km, respectively, and image the same point on Earth at repeat intervals ranging from six to 30 days. The Sentinel and ALOS-2 satellites use different wavelengths, which means they pick up different aspects of surface deformation, adding to the precision and completeness of the investigation.
- In the spirit of international cooperation, both space agencies had re-prioritized their satellites immediately after the quake to collect more images of New Zealand to help with research and support the emergency response activities.
- Before the earthquake, coauthors Cunren Liang and Eric Fielding of NASA/JPL ( Jet Propulsion Laboratory), Pasadena, California, developed new InSAR data processing techniques to measure the ground deformation in the satellite flight direction using wide-swath images acquired by the ALOS-2 satellite. This is the first time this new approach has been successfully used in earthquake research. "We were surprised by the amazing complexity of the faults that ruptured in the Kaikoura earthquake when we processed the satellite radar images," said Fielding. "Understanding how all these faults moved in one event will improve seismic hazard models."
- The authors say the Kaikoura earthquake was one of the most recorded large earthquakes anywhere in the world, enabling scientists to undertake analysis in an unprecedented level of detail. This paper (Ref. 44) is the first in a series of studies to be published on the rich array of data collected from this earthquake.
Figure 36: Two ALOS-2 satellite images show ground displacements from the Nov. 2016 Kaikoura earthquake as colors proportional to the surface motion in two directions. The purple areas in the left image moved up and east 4 m; purple areas in the right image moved north up to9 m (image credit: NASA/JPL-Caltech/JAXA)
• March 6, 2017: JAXA released the global DSM (Digital Surface Model) dataset with a horizontal resolution of approx. 30 m mesh (1 arcsec) free of charge. The dataset has been compiled with images acquired by ALOS/ Daichi (Advanced Land Observing Satellite). The dataset is published based on the DSM dataset (5 m mesh version) of the "World 3D Topographic Data", which is the most precise global-scale elevation data at this time, and its elevation precision is also at a world-leading level as a 30 m mesh version. This dataset is expected to be useful for scientific research, education, as well as the private service sector that uses geospatial information. 45)
1) Release history:
- May and October 2015: Japan and a part of individual continent released as Beta Version (Total 7,279 tiles).
- April 2016: Version 1 covering Japan and a part of individual continent released (Total 7,278 tiles).
- May 2016: Global terrestrial region (within approx. 82 deg. of N/S latitudes) of Version 1 released (approx. 22,100 tiles).
- March 2017: Update with void-filled DSM within 60 deg. of N/S latitudes as Version 1.1 [Updated]. Void pixels due to clouds and snow pixels within 60 deg. of north and south latitudes in Version 1 were complemented by existing DEMs. Out of the areas are same with Version 1 product.
2) Descriptions of the AW3D30 DSM dataset
- Resolution: 1 arcsec (approx. 30m mesh) containing 1 deg. lat/long tile.
- Height accuracy: 5 meters as standard deviation (1 sigma)
DSM (Height above sea level, signed 16bit GeoTIFF) The calculated elevation value by average (AVE) and median (MED) when resampling from 5-meter mesh version. The nearest neighbor (NN) is considered in next version)
Mask information file (8bit GeoTIFF)
Stacked number file (8bit GeoTIFF, DN=number of stacking)
Quality assurance Information (ASCII text, add information for 1 arcsec product to original 5-m mesh DSM information)
Header file (ASCII text)
New mask values have been defined to release Version 1.1 product. Please refer to "Product Format Description Ver.1.1" for the details of dataset (PDF format, 309KB).
Please confirm processing status and
qualities i.e. clouds by "Thumbnail of publishing AW3D30" on the top
for your area of interests. The published area will be expanding to all
over the world near future.
This is temporally registration and will send e-mail you to accept your registration request. After the confirmation of your request, the download information will send by e-mail. The dataset download site is: http://www.eorc.jaxa.jp/ALOS/en/aw3d30/data/index.htm
This dataset is available to use with no charge under the following conditions.
- When the user provides or publishes the products and services to a third party using this dataset, it is necessary to display that the original data is provided by JAXA.
- You are kindly requested to show the copyright (© JAXA) and the source of data When you publish the fruits using this dataset.
- JAXA does not guarantee the quality and reliability of this dataset and JAXA assume no responsibility whatsoever for any direct or indirect damage and loss caused by use of this dataset. Also, JAXA will not be responsible for any damages of users due to changing, deleting or terminating the provision of this dataset.
Figure 37: ALOS Global Digital Surface Model "ALOS World 3D - 30m" (AW3D30), image credit: JAXA/EORC)
• On November 15, 2016 at 23:00 UTC, an emergency observation with the PALSAR-2 aboard ALOS-2 (Daichi-2) was performed in response to the magnitude 7.8 earthquake in New Zealand on November 13, 2016 at 1:36 (UTC). Figure 38 shows the observation area. JAXA (Japan Aerospace Exploration Agency) has provided the acquired data to corresponding authorities. 46)
- Figure 39 shows a differential interferometry (DInSAR) result derived from the PALSAR-2 data acquired before (October 18, 2015; UTC) and after (November 15, 2016; UTC) the earthquake. Two major deformation regions were found, approx. 100 km length deformation in north west of Clarence and approx. 70 km length deformation in south west of Kaikoura. Over 3m deformation close to the satellite (eastward and / or upward movement) was detected in the west region of Clarence. The deformation should be larger in the area between the Kekerengu Fault and the Clarence Fault.
• On November 13, 2016, JICA (Japan International Cooperation Agency) and and the JAXA (Japan Aerospace Exploration Agency) launched the “JICA-JAXA Forest Early Warning System in the Tropics” (JJ-FAST) service, easily accessible from PCs and smartphones to obtain information based on deforestation and forest change data for tropical regions using JAXA’s Advanced Land Observing Satellite-2 (ALOS-2). 47)
- Between 2009 and 2012, JICA and JAXA supported the monitoring of illegal logging in the Amazon Basin of Brazil in near-real time using observation data from ALOS, the predecessor to ALOS-2. The ability of ALOS to penetrate clouds made it possible to constantly monitor tropical forests during the rainy season. More than 2,000 incidents of illegal logging were detected by ALOS in Brazil, which greatly contributed to a 40 percent reduction in illegal logging areas.
- Building on the knowledge obtained through these efforts, JICA and JAXA then agreed to monitor deforestation and forest changes in tropical regions around the world using data from ALOS-2, and announced the “Initiative for Improvement of Forest Governance” at the Japan pavilion of the twenty-first session of the Conference of the Parties (COP21) to the United Nations Framework Convention on Climate Change (UNFCCC) in Paris in 2015.
- JJ-FAST was established as part of this initiative, and will provide the latest information on deforestation and forest changes in tropical regions globally, on an average of once every 45 days. JJ-FAST can be accessed by anyone anywhere under an environment capable of connecting to the Internet.
- When the service begins, the data for five countries in Latin America will be released. The target area will expand gradually to African and Asian regions. The final goal for JJ-FAST is to release monitoring data of approximately 60 countries that have tropical forests. The detection accuracy of deforestation in JJ-FAST will be improved according to user feedback.
- Because of its ability to monitor vast forest areas from space, JJ-FAST can be an effective means to monitor forests for developing countries that have problems doing so due to inadequate infrastructure, public security issues, a shortage of qualified personnel or budgetary issues. JICA and JAXA support sustainable forest management for developing countries through the spread of JJ-FAST, and are dedicated to reducing deforestation with the long-term aim of mitigating climate change.
• January 28, 2016: JAXA developed a whole-globe forest map of 25-meter resolution, “Global Forest/Non-forest map”, using the DAICHI-2 (ALOS-2) launched on May 24, 2014, and released it from today free of charge. For achieving a long-term objective of controlling global warming that was set by the UN COP21 (United Nations Conference of Parties 21) held in Paris in December 2015, it is imperative to globally understand and maintain forests which are an important source of absorbing CO2. To tackle such a global-scale issue, JAXA, in cooperation with JICA ( Japan International Cooperation Agency), will establish a “Forest Monitoring System” in the next Japan fiscal year starting in April 2016. Data from the Global Forest/Non-forest map will also be used for the above system as its basic information. 48)
- In recent years, deforestation has been expanding in tropical and sub-tropical areas and is one of the causes of global warming. Therefore, the United Nations and many governments in the world place priority on understanding forest areas and maintaining them as important measures against global warming for political decisions. The L-band Synthetic Aperture Radar-2 (PALSAR-2) aboard the DAICHI-2 with its high sensitivity and resolution uses a radio wave of long wave length (about 24 cm) that is suitable for observing the existence of forests (natural forests) and the current status of forest use. It can also perform observations regardless of weather conditions or time (day or night) hence it is especially advantageous to measure forests in tropical areas which are covered by clouds almost all around the year.
- JAXA provided observation data of forest areas by the PALSAR aboard the DAICHI (ALOS) between 2007 and 2010, and it was utilized for monitoring illegal deforestation of the tropical rain forest in the Amazon region by the Brazilian government. As the Daichi's operations were completed in 2011, monitoring by the DAICHI had been halted since then.
- JAXA plans to provide the Global Forest/Non-forest map by the DAICHI-2 once a year to contribute to measures against global warming through the understanding of forest distribution. With this data, we can grasp the reduction and increase of forests in each area in the world based on spatial and temporal changes. Therefore, it is expected to be useful for government organizations around the world for their forest maintenance plans such as which area should be prioritized for monitoring and maintenance.
Figure 40: The COP21 set a long-term objective of controlling the average temperature increase in the world within the 1.5º Celsius range compared to that of the pre-industrial revolution, and that was well below the previously mentioned 2º Celsius range (image credit: JAXA).
- In the next Japan fiscal year starting from April 2016, JAXA plans to release more frequent change information on tropical forests to the world through the “Forest Monitoring System”, which will be implemented in cooperation with JICA ( Japan International Cooperation Agency). 49)
Figure 41: Deforestation on Borneo Island observed between 2010 and 2015 based on observations by synthetic aperture radars on the DAICHI and DAICHI-2 (image credit: JAXA)
• Jan. 21, 2016: Corresponding to emergency requests from NASA and the International Charter of Space and Major Disasters for flooding of the Mississippi River, JAXA performed an emergency observation over the area by means of PALSAR-2 (Phased Array type L-band Synthetic Aperture Radar-2 ) aboard ALOS-2/Daichi-2 in the period January 6-16, 2016. 50)
Figure 42: On Jan. 16, 2016, JAXA acquired this estimated inundation map of the Mississippi in the New Orleans region (image credit: JAXA/EORC)
Figure 43: ALOS-2 played an important role for supporting restoration in disaster-stricken areas by sending data following the East Japan Earthquake, but it completed its operations in May 2011. The DAICHI-2 is currently under development to capture the Earth's images more quickly covering much broader areas with more details. This video explains the DAICHI-2 mission in light of "preparing for a disaster" and its "application in our lives." (video credit: JAXA, published on 26 November 2013)
• August 19, 2015: JAXA has been observing the volcanic activity of Sakurajima, Japan, using the ALOS-2/Daichi-2 spacecraft, following a request from the Coordinating Committee for Prediction of Volcanic Eruptions of JMA (Japan Meteorological Agency). JAXA was asked to perform an emergency observation as there had been a warning of an eruption since August 16, 2015. 51)
- The acquired data are being immediately provided to the Geospatial Information Authority of Japan (GSI) and other related disaster preparation organizations, and being analyzed for crustal deformation.
Legend to Figure 44: The image shows the comparison result of the data acquired on January 4 and August 16, 2015. The deformation of up to about 16 cm closer toward the satellite was observed at the area on the east side of the Minamidake Summit of Sakurajima (indicated by the white square).
• August 2015: The performance of the ALOS-2/PALSAR-2 instrument was confirmed during the initial calibration and validation phase of Aug. 4 – Nov. 20, 2014. Within this phase, all the PALSAR-2 modes were evaluated for raw data characteristics and quality of the SAR images, and the SAR images were calibrated geometrically and radiometrically using the natural forest in the amazon and the corner reflectors deployed globally. In total, 58 antenna beams from the six modes [i.e., spotlight (84 MHz), ultrafine (84 MHz), high sensitive-full polarimetry (42 MHz), high resolution, ScanSAR narrow (350 km), and ScanSAR wide (490 km)], were calibrated using the Amazon forest. The geometric accuracy of the standard product is 5.34 m RMSE (Root Mean Square Error), and radiometric stability is 0.4 dB using the Amazon data. The other parameters of the SAR image qualities, i.e., resolution, NESZ (Noise-Equivalent Sigma Zero), PSLR (Peak-to-Sidelobe-Ratio), etc., meet the requirement to the SAR image quality. In this evaluation phase, the other SAR quality was evaluated as well. i.e., INSAR, Polarimetry, forest observation and so on. 52)
The calibration instruments are the corner reflectors, active radar calibrator, receiver, and the distributed targets in the Amazon Forest. First, the raw data were evaluated especially on the saturation rate and the signal to noise ratio. Second, the antenna elevation patterns were determined using the distributed targets in the Amazon region. Since the PALSAR-2 has 116 beams prepared for operating in the basic observation scenario, all the calibration activities required an extremely large number of the operational time in the initial calibration of the PALSAR-2 instrument — a total of 3.5 months were needed, and 58 beams have been calibrated. Then, the radiometric calibration and validations were performed using the globally distributed CR and the Amazon data, which shows the constant gamma-zero performance wrt the incidence angle. The geometric calibration of the PALSAR-2 was conducted using the location of the CRs. Then, the PALSAR-2 data were evaluated for their image quality. The results of the PALSAR-2 image quality were summarized in Table 7 and the sample image of Figure 45. As a result of the initial calibration, the PALSAR-2 has shown an extremely good performance with a high quality of the SAR imagery.
• July 3, 2015: Corresponding to an emergency request from Sentinel Asia related to a GLOF (Glacial Lake Outburst Flood) reported in Bhutan on June 28, 2015, JAXA performed an emergency observation at 5:59 (GMT) on July 2, 2015 by means of PALSAR-2 (Phased Array type L-band Synthetic Aperture Radar-2) aboard the Advanced Land Observing Satellite-2 (ALOS-2, "DAICHI-2"). 53)
- According to an ALOS dataset, "the Glacial Lake Inventory of Bhutan using ALOS ("DAICHI") data", two glacier lakes with GLOF potential as Lake A and B are located in [89°34'50.0"E; 28°4'7.7"N] and [89°36'7.7"E; 28°6'54.1"N] in a headwater of the Mo Chu river basin, in western Bhutan.
Figure 46: Location of the glacier lakes in the Bhutan Himalaya region (image credit: JAXA/EORC)
1) GLOF (Glacial Lake Outburst Flood) was reported in western Bhutan on June 28, 2015 (local time).
2) Emergency observation of PALSAR-2 onboard ALOS-2 was performed on July 2, 2015 by JAXA, corresponding to a request from Sentinel Asia.
3) Remarkable change in lake area is recognized in Lake A (ICIMOD id: mo_gl_200). The area increased between March 8 and April 23 (+48.0%) and then decreased between April 23 and July 2 (-52.9%) in 2015.
4) Collapse of a moraine edge is recognized near Lake A after the GLOF event.
Figure 47: Temporal area changes of Lake A and B (image credit: JAXA/EORC)
- From this result, Lake A has a higher potential as the source of the GLOF. It is located at a glacier terminus surrounded by a moraine. These obtained results have been contributed to a governmental organization of Bhutan. JAXA would carry out rapid observations against such a mountain hazard in remote regions in cooperation with concerned authorities. Related results would be distributed to relevant organizations and this website (Ref. 53).
• May 14, 2015: JAXA concluded an agreement with the Kyushu Regional Development Bureau of the MLIT (Ministry of Land, Infrastructure, Transport and Tourism) on April 30, 2015, to provide observation data by theALOS-2/Daichi-2 mission. The purpose of the agreement is to survey (1) secular changes of landscape and ash fall and (2) isolated islands for their up keep. The two parties will work together to conduct surveys more efficiently with broader covering areas by mutually sharing and studying observation data possessed by the Kyushu Regional Development Bureau and JAXA's satellite data. 54)
• May 7, 2015: JAXA has performed observations of the 2015 Nepal earthquake, which struck on April 25, 2015 (local time), with the PALSAR-2 (Phased Array type L-band Synthetic Aperture Radar-2) instrument aboard ALOS-2/Daichi-2. The emergency observations were requested from Sentinel Asia and the International Charter. 55)
Table 8: Summary of the Nepal earthquake investigation
- The project applied an interferometric analysis to the PALSAR-2 data acquired before (Feb. 21, 2015) and after (May 2, 2015) the quake to map the crustal deformation. Figure 48 illustrates the whole interferogram obtained by the analysis. Colored fringes denote the change of LOS (Line-of-Sight) distance (distance between the satellite and the ground) between the two observation dates. The dense fringes distributed throughout the image show that the deformation extended at least 100 km from north to south. A large elliptical fringe at just south of the image center means that LOS distance became shortened, and the land at the center of the fringe moved at least 1.5 meter. The center of Kathmandu moved toward the satellite approximately 1 meter. A different ellipsoidal fringes at the north side means that the LOS distance was extended. Note that the noise, distributed over the north side,is due to the change of surface conditions between the observations, such as snow cover.
Legend to Figure 48: Observation mode: Stripmap Fine (10 m resolution), swath width: 70 km. The red star and black line circles indicate the epicenters of the main shock (Mw 7.8) and the aftershock (more than Mw 5), respectively.
- Figure 49 shows an enlarged image over central Kathmandu. Several local-scale displacements are found in the boxes (1) and (2). The land at the box (1) moved by up to 30 cm in the satellite-ground direction compared to the outside of the box. The local displacements possibly caused different damages of structures depending on the area. According to the quick report from the in situ investigation by Japan Society of Civil Engineers, Japanese Geotechnical Society, and Japan Association of Earthquake Engineering, ground subsidence and damage of roads and buildings were found at the box (2) (Figure 50). JAXA and its partners continue to look for similar changes in the interferogram and to share the information with the in situ investigators.
Figure 49: PALSAR-2 interferogram around Kathmandu; local displacements are found in the box (1) and (2), image credit: JAXA
Figure 50: In situ photo taken on May 1 at the grey-color point in the box (2), image credit: Japan Society of Civil Engineers, Japanese Geotechnical Society, and Japan Association of Earthquake Engineering
- Figure 51 shows the prospective damaged building and road areas obtained by difference of coherence analysis for the box (2) area in Figure 49. The analysis evaluates the difference of coherence obtained before the disaster (Oct. 4, 2014 - Feb. 21, 2015) and between the disaster (Feb. 21, 2015 - May 2, 2015). The large difference indicates a large radar image difference between the three observations. The large radar image difference includes the collapse of buildings, the damage of roads, changes of agricultural fields, and snow cover. A significant decrease of coherence is observed for the areas, where buildings and roads are damaged.
Figure 51: Prospective damaged buildings and road areas obtained by the difference of coherence analysis for the box (2) area in Figure 49 (image credit: JAXA)
JAXA will collaborate with the relevant organization, and continue the observation of this stricken region. The data and analysis results were provided to the International Charter, "Space and Major Disasters".
• May 5, 2015: JAXA has been performing the emergency observations with the PALSAR-2 (Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) aboard ALOS-2/Daichi-2 for monitoring the effects of an earthquake struck Nepal on April 25, 2015. JAXA analyzed the PALSAR-2 data acquired on April 26, 2015, 7:02 (GMT) over Kathmandu. Figure 52 shows the coverage area of the data. 56)
- Figure 53 shows the overall image obtained with the high-resolution 3 m mode (dual polarization). The color composite in the image represents HH polarization in red, HV polarization in green, and HH/HV in blue. The different colors in the image indicate different backscattering signals from the ground. The bright purple and green colors generally indicate buildings. The color difference depends on the difference of urban structures or building shapes and do not directly show the damage.
- An enlarged image of a part of Kathmandu is shown in Figure 54. The project compared it with an image acquired before the earthquake (March 3, 2015) with 10 m resolution mode. Although the observation resolutions and angles of two images were different, the dark color areas after the earthquake probably indicate the damages of buildings. The yellow circles (1) and (2) are the locations of the Durbar square and the Dharahara (Bhimsen) tower.
• Jan. 23, 2015: After the calibration and validation of ALOS-2/CIRC (Compact Infrared Camera), JAXA confirmed the data quality of ALOS-2/CIRC is adequate. All ALOS-2/CIRC data is available from CIRC observation data search, if user follows the CIRC data policy. The ultimate goal of the CIRC project is to minimize the damage and impact caused by forest fires, as well as contributing to urban planning and our understanding of volcanic disasters. 57)
Table 9: Summary of the PALSAR-2 instrument performance parameters as of the end of January 2015 58)
• JAXA declared the ALOS-2/Daichi-2 mission “operational“ as of Nov. 25, 2014. Regular provision of observation data started today after the completion of the commissioning phase (i.e., completion of functional confirmation and of calibration operations). 59)
• Sept. 30, 2014: JAXA captured images of depressions and deposition of falling ash following of Japan's Mt. Ontake's volcanic eruption on Sept. 27,2014 through emergency observations by the ALOS-2 (Advanced Land Observing Satellite-2 /Daichi-2). The observations were conducted according to a request from the Coordinating Committee for Prediction of Volcanic Eruptions (Secretariat: Japan Meteorological Agency) and the Cabinet Office (Disaster Management) under the agreement with ministries related to disaster management. The acquired data was provided for confirming geographical changes and the accumulation of falling ash. JAXA continues to observe Mt. Ontake in cooperation with the disaster management agencies. 60)
- Figure 55 shows a comparison between the images near the peak of Mt. Ontake taken on Aug. 18, prior to the volcanic eruption (right), and on Sept. 29 (left) after the eruption. The images were shot by the PALSAR-2 (Phased Array L-band Synthetic Aperture Radar-2) instrument aboard Daichi-2. The PALSAR-2 can capture the status of the volcanic crater without being hampered by fumes by seeing through them thanks to its long radio wave length of L-band (1.2 GHz bandwidth). In the left image (after the eruption), a new depression measuring 210 m in length and 70 m in width was newly created due to the eruption. This seems to be an exhaust vent hole (volcanic orifice) freshly formed this time.
Figure 56 is an extraction of changes observed from the observation images near Mt. Ontake peak taken from the same orbit on Aug. 18 and Sept. 29. Changes are colored in purple. It is estimated that falling ash has been accumulated near the peak crater through the satellite images. The observation were performed facing the right side (west to east) from the ascending node orbit (moving over Japan from south to north) .
• July 2014: The CIRC (Compact Infrared Camera) instrument, a demonstration imager intended for observing forest fires, volcanoes, and heat island phenomena, captured its first images after the initial functional verification phase (July 4-14, 2014). Figure 57 demonstrates the advantage of infrared sensors, which can obtain images even at night. The image color represents surface temperature, with black representing the lowest temperature while yellow represents the highest. 61)
• June 27, 2014: JAXA acquired PALSAR-2 (Phased Array Type L-band Aperture Radar-2) imagery aboard ALOS-2 (Daichi-2) as shown on Figure 58. The left image of Figure 58 is of Izuoshima Island on Japan's coast. The right image is a bird’s-eye view image compiled by using altitude data acquired by the PRISM aboard the Daichi. One can still see the scars of the large-scale landslide caused by Typhoon No. 26 in October 2013, even though almost eight months have passed (the dark area circled in red.) The vegetation has not recovered there yet. Image 58 was colored spuriously using polarization data acquired through observations in order to understand the land cover classification more precisely. Roughly speaking, green indicates vegetation, light purple and yellow-green are urban areas, and dark purple is barren areas. 62)
• May 27, 2014: JAXA confirmed via telemetry that the attitude control system of the Advanced Land Observing Satellite (ALOS-2/Daichi-2) shifted to the regular operation mode. With this confirmation, scheduled important operations of the critical phase including the deployment of antennas for direct communications and mission instruments were all achieved, thus the critical operations phase 1 of the DAICHI-2 was completed. 63)
- The satellite is now in a stable condition - and will move to the initial functional verification operation phase2 to verify the function of the satellite onboard instruments for about two and half months.
• May 26, 2014: JAXA confirmed that the L-band synthetic aperture radar (PALSAR-2) antenna of the Advanced Land Observing Satellite (ALOS-2 /Daichi-2) was deployed successfully (the second wing deployment). With this confirmation, the PALSAR-2 antenna deployment operation was completed. The satellite is now in a stable condition. 64) 65) 66)
Figure 59: Schematic view of the PALSAR-2 deployment sequence diagrams (image credit: JAXA)
Figure 60: PALSAR-2 depolyment (image credit: JAXA)
Sensor complement: (PALSAR-2, CIRC, SPAISE2)
PALSAR-2 (Phased Array L-band Synthetic Aperture Radar-2):
PALSAR-2 is an L-band SAR instrument based on APAA (Active Phased Array Antenna) technology. The APAA of ALOS-2 allows not only conventional stripmap and ScanSAR, but also Spotlight mode observations with electronic beam steering in the range and azimuth directions. To cover wide area observations, PALSAR-2 offers the capability of wide incidence angle (8º - 70º) electronic beam steering as well as a means for left-side or right-side looking observations from the satellite ground track; the required spacecraft maneuver for this observation change can be accomplished in about 2 minutes from the nominal nadir look direction. 67) 68) 69) 70) 71) 72) 73) 74)
System design: The PALSAR-2 system is composed of two subsystems: the Antenna subsystem (ANT) and the Electric Unit (ELU).
ELU: The key components of the ELU are Exciter (EX), Transmitter (TX), Receiver (RX), Digital Processor (DP), and System controller (SC).
As for the RF signal, EX generates the pulse, selects two chirp signals (up / down and phase modulation) with selected center frequencies of either 1257.5, 1236.5 or 1278.5 MHz in order to avoid the interference into RNSS (Radio Navigation Satellite Service) using the L-band, and stretches the signal to the selected bandwidth at either 84 MHz, 42 MHz, 28 MHz or 14 MHz. The received radar echo signal is compressed by the BAQ (Block Adaptive Quantization) or the improved BAQ algorithm. The compression mode is selected from 4 bit, 2 bit, and no compression with or without the improved compression mode. Figure 61 shows the system diagram of PALSAR-2.
Figure 62: Schematic diagram of PALSAR-2 elements (image credit: MELCO)
Legend to Table 11: Performance values @ incidence angle of 37º; CP: Compact Polarimetry (Linear+circular), FP: Full Polarimetry (HH+HV+VV+VH).
The specification of Table 11 is defined for an incidence angle of 37º above the equator. The polarization acronyms are as follows:
- SP: Single Polarization
- DP: Dual Polarization
- FP: Full Polarization (quad)
- CP: Compact Polarization (experimental mode).
Figure 63: Illustration of conventional PALSAR-2 polarization modes (same as implemented on PALSAR), image credit: JAXA
Figure 64: Schematic view of new polarization mode CP of PALSAR-2 (image credit: JAXA)
The enhanced instrument performance of ALOS-2, enabled through the right-and-left looking observation capability, will greatly expand the FOR (Field of Regard) of the satellite, up to about 3 times (from 870 km on Daichi to 2,320 km), for event monitoring services.
Figure 65: SAR antenna orientation shown in nadir (left) and in right-side looking direction (right), image credit: JAXA
Figure 66: Schematic view of the spotlight mode configuration (image credit: JAXA)
Figure 67: Observation modes of PALSAR-2 on ALOS-2 (image credit: JAXA)
L-band SAR antenna (ANT): ANT is an active phased array antenna which steers the beam in both elevation and azimuth direction (±30º in elevation and ±3.5º in azimuth). It has a size of 9.9 m (azimuth) x 2.9 m (elevation) and is composed of 5 electrical panels. The antenna consists of 1,080 radiation elements which are driven by 180 TRMs (Transmit and Receive Modules). The design enables to steer and form the beam in elevation and azimuth direction for several imaging modes: Stripmap, Spotlight and ScanSAR. The antenna nominal pointing is in the nadir direction and it is pointing 30º sideways when observing (either to the left side or to the right side of the ground track). 75)
Figure 68: PALSAR-2 antenna configuration (image credit: JAXA, MELCO)
The SAR antenna is a DRC (Dual Receive Channel) system (Figure 69):
- The full aperture (5 panels) or partial aperture ( 3 of 5 panels, No 2, 3 and 4) of the antenna aperture may be used for signal transmission (Tx). The peak radiation power is 3,300 W with three panels for Spotlight mode and Ultra-Fine mode, or 5,100 W with full aperture for High sensitive mode, Fine mode and ScanSAR mode.
- In receive, the antenna is divided into two separate partitions in along-track. The signals of both receiving antenna partitions are being detected and recorded separately; this concept permits wide-swath acquisitions.
Wide swath coverage for polarimetric observation: ALOS-2 SAR utilizes a type of polarimetry as single, dual and quad (full-pol.) as a standard mode, and compact (or hybrid) as an experimental mode. Full-pol. mode on ALOS-2 is a system which realizes transmitted polarization by replacing horizontal / vertical by turns with an interval of PRI (Pulse Repetition Interval). Therefore, when selecting full-pol. mode, the PRF of full-pol. is doubled as that of single/dual-pol., which means that the available swath in full-pol. is drastically restricted. In the case of conventional mode (“fine mode”: resolution of 10 m), the range coverage of full-pol. becomes 30 km, which is less than a half of single/dual-pol. (70 km).
The wider coverage of full-pol. is also achieved by using the DRC method. Since the full-pol. mode requires two receive channels for H and V polarization synchronously, utilization of the DRC mode for full-pol. requires double channels compared with the conventional full-pol. Mode, namely quad- receive channel. For the purpose of wide coverage and observation capability in higher incidence angles for full-pol. mode, ALOS-2 can execute the DRC and full-pol. observation simultaneously, in “high sensitive mode” (HS mode). The swath of the full-pol. mode in HS mode is 40-50 km with a resolution of down to 6 m in an off-nadir angle of 18-35º.
Another approach for wider coverage of polarimetric observation is a new technique of “compact (or hybrid) polarimetry”. Since one T/R module of ALOS-2 has two identical amplifiers for H and V polarimetry, RF signals of H/V polarization with an optimum phase offset is generated from each antenna element, and resultantly circular or oriented at 45º is transmitted. Although polarimetric information of compact pol. is not enough compared to that of full-pol., the swath of compact polarimetry is wider than that of full-pol., and is the same as that of single/dual polarimetry mode.
TRMs (Transmit Receive Modules):
The TRMs enable to select the polarization of single (HH/VV/HV), dual (HH + HV=VV + VH), quad (HH + HV + VV + VH), and compact polarimetry (Tx: oriented 45º or circular, Rx: H or V) by transmitting H and V polarization simultaneously. In L-band, the propagation disturbances and especially the ionospheric effects like Faraday rotation and phase delay have to be considered and if possible to be corrected. The quad polarimetry mode uses the alternative pulses of H and V which increase the PRF and result in a narrow swath.
The SAR instrument features a CP (Compact Polarimetry) mode as an experimental mode which can transmit the H and V polarization simultaneously resulting in a linear polarization oriented at 45º or circular (LHCP or RHCP), selectable by command.
Compared to the TRMs used in PALSAR, establishing higher power amplification in the TRMs of PALSAR-2 through a wider operational frequency range is necessary, as summarized in Table 12. An output power of 34 W is generated at the PALSAR-2 TRM output port with a low-loss and high-power solid state power amplifier using a GaN (Gallium Nitride) HEMT (High Electron Mobility Transistor). - The performance of a HPA (High-Power Amplifier) using GaN HEMT is tested by a breadboard model and confirmed to meet the requirement. Figure 70 shows the outside view of the HPA and the inside view of the BBM (Breadboard Model).
Figure 71: TRM architecture of the L-band SAR instrument (image credit: JAXA)
The image quality with chirp modulation: To distinguish each pulse, PALSAR-2 implements the chirp modulation.
- Up/down and phase modulation in each pulse
- PALSAR is only Down chirp.
Figure 72: Schematic view of up/down chirp modulation in PALSAR-2 (image credit: JAXA)
Chirp signal management: In order to reduce range ambiguities, the ALOS-2 PALSAR-2 system has an ability to send up/down chirp signals alternatively.
Data compression algorithm: The maximum data rate (800 Mbit/s) of PALSAR-2 is much higher than that of PALSAR (240 Mbit/s max) due to the improved performances of the SAR instrument providing higher resolution data and a wide swath. To realize the frequent observations and data acquisitions, it is necessary to develop a new data compression technique on board with a highly efficient and a low error rate.
The data compression technique for PALSAR-2 is BAQ (Block Adaptive Quantization) or an improved BAQ version, namely DS-BAQ (Down-Sampling BAQ selectable. The BAQ technique, used for other SAR satellite like TerraSAR-X and COSMO-SkyMed, is the conventional technique. DS-BAQ is the new data compression technique. At conventional radar system, the A/D sampling frequency is wider than the transmitting bandwidth to decrease the ambiguity level. In DS-BAQ, the differential bandwidth between transmitting bandwidth and A/D sampling frequency is cut before BAQ processing (Ref. 67).
Figures 73 and 74 show the simulation results amplitude and phase error analysis, respectively. According to these Figures, DS-BAQ is able to decrease the error more than the BAQ technique in same compression ratio.
The error analysis result based on a simulation comparing the two compression algorithms under several polarization modes shows that, in the same data compression ratio, down-sampling BAQ satisfies the lower errors of both amplitude and phase better than BAQ. The compression ratio was evaluated on the BBM (Breadboard Model) of the data compression module, confirming also its processing speed.
The implementation of the data compression algorithm is such that a compression mode is onboard selectable between the DS-BAQ, the original BAQ, and direct output without data compression.
Figure 75: Schematic view of the down-sampling BAC algorithm (image credit: JAXA)
Figure 76: Overview of ALOS-2 implementation phases (image credit: JAXA, Ref. 4)
CIRC (Compact Infrared Camera):
CIRC is an infrared demonstration instrument of JAXA with state-of-the-art COTS (Commercial-off-the-Shelf) technology developed at MELCO (Mitsubishi Electric Corporation). The camera is equipped with an uncooled infrared array detector (microbolometer). The main objective of CIRC is to provide infrared imagery for wildfire detection. CIRC is mounted onto the spacecraft pointing to the right of the flight path at an off-nadir angle of 30º (Figure 77). CIRC is a small size instrument with a mass of ~ 3 kg. 76) 77) 78) 79)
Wildfires are one of the major and chronic disasters affecting many countries in the Asia-Pacific region, and indications are that this will get worse with global warming and climate change. Wildfire detection is one of the main goals in the Sentinel Asia project and to share this information in near real-time across the Asia-Pacific region.
The goal is to realize frequent observations by loading CIRC devices in as many satellites as possible by taking advantage of there small size, low weight, and low power consumption. Other mission targets of the CIRC are volcanoes or heat island phenomena in a city.
JAXA developed two CIRC instruments, one will be launched aboard the ALOS-2 spacecraft; the second one will be launched in 2015 onboard CALET (CALorimetric Electron Telescope), which was installed in the JEM -EF (Japanese Experiment Module) on the ISS (International Space Station) in April 2015.
The baseline specifications of the CIRC instrument are listed in Table 13. The detector has a large format (640 x 480 pixels) to capture a wide field of view. Spatial resolution is an important factor for wildfire detection; it is 200 m from an altitude of 600 km (ALOS-2) and 130 m from an altitude of 400 km (CALET). Eliminating the cooling system reduces the size (110 mm x 180 mm x 230 mm) and the consumption power (<20 W) for CIRC.
Microbolometer: The project adopted microbolometers as an infrared FPA (Focal Plane Array) of the CIRC device. Microbolometers are based on the principle of detecting infrared energy as minute changes of the IR absorber temperature when infrared radiation id detected. Their advantage is that they do not require a cooling system, such as a mechanical cooler. Sensors without a detector cooling system can be made to have a small size, low mass and low power consumption.
CIRC features a SOI (Silicon-on-Insulator) diode uncooled IR FPA developed by MELCO. Its pixel size is 25 µm square. The SOI diode uncooled IR FPA uses a single-crystal silicon pn-junction diode as a temperature sensor. The single-crystal sensor based on silicon LSI (Large-Scale Integration) technology gives it a low-noise characteristic. The NEDT (Noise Equivalent Differential Temperature) is 40 mK with f/1 optics. The drive and readout circuits are almost the same as those of the commercial IR camera. For the space application, the project performed a radiation damage test, and a screening of commercial devices.
Athermal optics: CIRC employs f/1.2 refractive optics with a focal length of 78 mm. The orbital temperature change of the optics will cause a defocus because the refractive indices of the lens materials are highly dependent on temperature. To compensate for this defocus, the project may employ a focus mechanism or a heater to keep the optics’ temperature constant. However, such mechanisms increase the instrument resources. An athermal optics can compensate for the defocus due to the temperature change without such mechanisms. CIRC can operate in a temperature range from -15º to 50ºC while maintaining its performance. Figure shows the optical design of CIRC. The athermal optics of the CIRC compensates for the defocus by a combination of different lens materials and diffractive lenses. The CIRC optics uses a germanium and a chalcogenide glass (GASIR). The MTF and athermal characteristics of the CIRC device have been verified in laboratory tests.
Figure 78: Block diagram of the CIRC instrument (image credit: JAXA)
Shutterless system: The project eliminated the mechanical shutter from the CIRC for downsizing reasons. A mechanical shutter is more commonly used as a calibration source. Therefore, a way was devised to achieve temperature calibration and straylight correction from the inside the CIRC device. The project obtained images of various temperature blackbody with different CIRC temperatures in order to perform stray-light correction by temperature of the CIRC device.
Figure 80: Photo of the CIRC PFM (Proto Flight Model) for the ALOS-2 mission (image credit: JAXA)
Airborne observations with the CIRC GTM (Ground Test Model): The project carried out airborne observations with the GTM) of CIRC. The model was constructed for establishing a way to perform ground calibration and carry out field observations before fabrication of the PFM.
Observational flight were carried out on March, 22 and 28, 2012. The aircraft was a “Cessna172 Sky hawk”. The observation area was Tsukuba City, Tsuchiura City in the south of Ibaraki Prefecture, and Narita City in Chiba Prefecture, all in Japan. The flight altitude ranged from 300 m to 750 m. The GSD (Ground Sample Distance) at these altitudes ranged from 10 cm to 25 cm. The flights confirmed that the performance of the CIRC is as expected and sufficient for launch on ALOS-2.
SPAISE2 (SPace based Automatic Identification SystemExperiment 2)
SPAISE2 is a second generation AIS instrument of JAXA featuring: 80)
• A 4 channel AIS signal reception capability (simultaneously 2 channels)
• Digital sampling and ground signal processing archtecture.
Table 14: Parameters of the SPAISE2 instrument
Figure 81: Schematic view of the AIS system (image credit: JAXA)
An overview of the CIRC ground system is shown in Figure 82. The ACGS (ALOS-2/CIRC Ground System) consists of three components: a CIRC observation planning system, a data processing system, and a data archive system.
Figure 82: Overview of ACGS (ALOS-2/CIRC Ground System), image credit: JAXA (Ref. 78)
Generally, observation plans are constructed in response to requests from users by the CIRC observation planning system, utilizing satellite operation information. After observation, the data processing system obtains Level-0 data from the ALOS-2 ground system and performs geometric and radiometric correction to produce Level-1 data. Then, the detection of wildfires, for example, is conducted to produce Level-2 data. Subsequently, the Level-1 and Level-2 data are released online through the data archive system, making them available to the users.
The ALOS-2 ground system is composed of the Satellite Control and Mission Operation System and the Information System, located at the JAXA Tsukuba Space Center. The Information System will have the functions of data processing, archiving, cataloging and user service functions for ALOS and ALOS-2.
For the global observation, the ALOS-2 ground system will utilize data relay communication and very fast X-band direct downlink (Figure 83). The observation data of PALSAR-2 will be once recorded on the solid state recorder onboard ALOS-2 and reproduced at 278 Mbit/s for Ka-band and at 800/400/200 Mbit/s via X-band.
Figure 83: The ALOS-2 ground system and tracking network (image credit: JAXA, Ref. 74)
When a disaster occurs, command will be ready within 60 minutes for emergency observation. After the Ground station receives the observation data, the emergency product will be ready within 60 minutes. Figure 84 shows the example of quick tasking and processing in natural disaster occurrence.
ALOS-2 science capabilities include global environmental monitoring using the time-series PALSAR-2. The research target also covers biospheric, cryospheric, and coastal ocean research as well as disaster mitigation. Table 15 summarizes these research products. 81)
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The information compiled and edited in this article was provided by Herbert J. Kramer from his documentation of: ”Observation of the Earth and Its Environment: Survey of Missions and Sensors” (Springer Verlag) as well as many other sources after the publication of the 4th edition in 2002. - Comments and corrections to this article are always welcome for further updates (firstname.lastname@example.org).