In 2020, the Japanese Aerospace Exploration Agency (JAXA) and the European Space Agency (ESA) signed an agreement on the “Cooperation for the Use of Synthetic Aperture Radar Satellites in Earth Science and Applications”. The cooperation focuses on the joint analysis of L-band data acquired by JAXA’s ALOS-2/PALSAR-2 satellite together with ESA’s Sentinel-1 C-band satellite data for various applications. Research areas include polar and ocean monitoring, snow water equivalent retrieval, forest and wetland monitoring, surface soil moisture and agriculture monitoring, as well as the monitoring of geohazards and urban areas.
The key objective of the JAXA-ESA cooperation is to develop a better understanding of the benefits of combining L-band and C-band data over various areas and for the different thematic applications. A comparison with ground-based campaign data is envisaged to validate the results. The research projects will provide important insights for the development of future (L-band) SAR satellite missions, such as JAXA’s ALOS-4 satellite and the High Priority Candidate Mission (HPCM) ROSE-L currently in development at ESA, as well as synergies with existing and future spaceborne C-band SAR missions including Sentinel-1 and Sentinel-1 Next Generation.
This jointly chaired session shall give the involved scientists the opportunity to present ongoing research and results and foster the collaboration and exchange between European, Japanese and international participants.
Organizers: Julia Kubanek (ESA), Shin-ichi Sobue (JAXA), Malcolm Davidson (ESA), Takeo Tadono (JAXA), Maurice Borgeaud (ESA)
vPICO presentations: Thu, 29 Apr
Within the “Cooperation for the Use of Synthetic Aperture Radar Satellites in Earth Science and Applications”, the Japanese Aerospace Exploration Agency (JAXA) and the European Space Agency (ESA) agreed to mutually share C-band data from ESA’s Sentinel-1 mission and L-band data from JAXA’s ALOS-2 PALSAR-2 mission over selected test sites. Applications include wetland monitoring, hurricanes, sea ice, snow water equivalent and surface deformation.
The aim of the collaboration is to develop a better understanding of the benefits of combining L- and C-band data over various areas and for the different thematic applications. The findings of the different European, Japanese and international projects will help to develop future SAR satellite missions, such as JAXA’s ALOS-4, and ESA’s Copernicus mission ROSE-L and Sentinel-1 Next Generation.
This presentation will give an overview of the ongoing ESA-JAXA cooperation and will show highlights and first results of the different test sites and applications.
How to cite: Kubanek, J., Davidson, M., Borgeaud, M., Sobue, S., and Tadono, T.: Synergetic use of L- and C-band SAR data in Earth Sciences – The JAXA-ESA mutual cooperation, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7100, https://doi.org/10.5194/egusphere-egu21-7100, 2021.
Japan Aerospace Exploration Agency (JAXA) launched its first L-band SAR mission - Japanese Earth Resources Satellite (JERS-1) in 1992. Though the design life of JERS-1 was 2 years, the satellite had obtained observational data for more than 6 years and ended the mission in 1998. Following to JERS-1, Advanced Land Observing Satellite (ALOS) was launched in 2006. ALOS was equipped with three sensors: the Phased Array type L-band SAR (PALSAR), the Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM), and the Advanced Visible and Near Infrared Radiometer type 2 (AVNIR-2). ALOS's observation data has been used in various areas including disaster mitigation through observing regions damaged by earthquakes, tsunami, or typhoons, as well as carrying out forest monitoring, natural environment maintenance, agriculture, and compiling a 1/25,000 topographical map. When the Great East Japan Earthquake hit Japan in 2011, ALOS took some 400 images over disaster-stricken areas to provide information to all parties concerned.
Technologies acquired from the ALOS are succeeded to the second Advanced Land Observing Satellite “ALOS-2.”, which was successfully launched on 24th May 2014. The mission sensor of ALOS-2 is the Phased Array type L-band Synthetic Aperture Radar-2 called PALSAR-2 which is the state-of-the-art L-band SAR system. Until now after the successful completion of initial checkout after launching, ALOS-2 has been contributed to a lot of emergency observations for natural disasters, not only in Japan but also in the world. Furthermore, based on the Basic Observation Scenario (BOS) of ALOS-2, 10m global map data and other mode data are routinely collected and archived. This paper describes the results of ALOS-2 operation in nominal operation phase and outline of future ALOS series missions, especially ALOS-4 launched JFY2022.
How to cite: Sobue, S., Tadono, T., Miura, S., Noda, A., Motooka, T., and Ohki, M.: Japan's L-SAR missions, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-534, https://doi.org/10.5194/egusphere-egu21-534, 2021.
One of the limitations of presently available Synthetic Aperture Radar (SAR) surface soil moisture (SSM) products is their moderated temporal resolution (e.g., 3-4 days) that is non optimal for several applications, as most user requirements point to a temporal resolution of 1-2 days or less. A possible path to tackle this issue is to coordinate multi-mission SAR acquisitions with a view to the future Copernicus Sentinel-1 (C&D and Next Generation) and L-band Radar Observation System for Europe (ROSE-L).
In this respect, the recent agreement between the Japanese (JAXA) and European (ESA) Space Agencies on the use of SAR Satellites in Earth Science and Applications provides a framework to develop and validate multi-frequency and multi-platform SAR SSM products. In 2019 and 2020, to support insights on the interoperability between C- and L-band SAR observations for SSM retrieval, Sentinel-1 and ALOS-2 systematic acquisitions over the TERENO (Terrestrial Environmental Observatories) Selhausen (Germany) and Apulian Tavoliere (Italy) cal/val sites were gathered. Both sites are well documented and equipped with hydrologic networks.
The objective of this study is to investigate the integration of multi-frequency SAR measurements for a consistent and harmonized SSM retrieval throughout the error characterization of a combined C- and L-band SSM product. To this scope, time series of Sentinel-1 IW and ALOS-2 FBD data acquired over the two sites will be analysed. The short time change detection (STCD) algorithm, developed, implemented and recently assessed on Sentinel-1 data [e.g., Balenzano et al., 2020; Mattia et al., 2020], will be tailored to the ALOS-2 data. Then, the time series of SAR SSM maps from each SAR system will be derived separately and aggregated in an interleaved SSM product. Furthermore, it will be compared against in situ SSM data systematically acquired by the ground stations deployed at both sites. The study will assess the interleaved SSM product and evaluate the homogeneous quality of C- and L-band SAR SSM maps.
Balenzano. A., et al., “Sentinel-1 soil moisture at 1km resolution: a validation study”, submitted to Remote Sensing of Environment (2020).
Mattia, F., A. Balenzano, G. Satalino, F. Lovergine, A. Loew, et al., “ESA SEOM Land project on Exploitation of Sentinel-1 for Surface Soil Moisture Retrieval at High Resolution,” final report, contract number 4000118762/16/I-NB, 2020.
How to cite: Balenzano, A., Satalino, G., Lovergine, F., Palmisano, D., Mattia, F., Rinaldi, M., and Montzka, C.: Combining Sentinel-1 and ALOS-2 observations for soil moisture retrieval, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8660, https://doi.org/10.5194/egusphere-egu21-8660, 2021.
With the upcoming L-band Synthetic Aperture Radar (SAR) satellite mission Radar Observing System for Europe at L-band (ROSE-L) and its combination with existing C-band satellite missions such as Sentinel-1, multi-frequency SAR observations with high temporal and spatial resolution will become available. To investigate the potential for estimating soil and plant parameters, the SARSense campaign was conducted between June and August 2019 at the agricultural test site Selhausen in Germany. In this regard, we introduce a new publicly available, extensive SAR dataset and present a first analysis of C- and L-band co- and cross-polarized backscattering signals regarding their sensitivity to soil and plant parameters. The analysis includes C- and L-band airborne recordings as well as Senitnel-1 and ALOS-2 acquisitions, accompanied by in-situ soil moisture measurements and plant samplings. In addition, soil moisture was measured using cosmic-ray neutron sensing as well as unmanned aerial system (UAS) based multispectral and temperature measurements were taken during the campaign period. First analysis of the dataset revealed, that due to misalignments of corner reflectors during the SAR acquisition, temporal consistency of airborne SAR data is not given. In this regard, a scene-based, spatial analysis of backscatter behaviour from airborne SAR data was conducted, while the spaceborne SAR data enabled the analysis of temporal changes in backscatter behaviour. Focusing on root crops with radial canopy structure (sugar beet and potato) and cereal crops with elongated canopy structure (wheat, barley), the lowest correlations can be observed between backscattering signal and soil moisture, with R² values ranging below 0.35 at C-band and below 0.36 at L-band. Higher correlations can be observed focusing on vegetation water content, with R² values ranging between 0.12 and 0.64 at C-band and 0.06 and 0.64 at L-band. Regarding plant height, at C-band higher correlations with R² up to 0.55 can be seen compared to R² up to 0.36 at L-band. Looking at the individual agricultural corps in more detail, in almost all cases, the backscatter signals of C- and L-band contain a different amount of information about the soil and plant parameters, indicating that a multi-frequency approach is envisaged to disentangle soil and plant contributions to the signal and to identify specific scattering mechanisms related to the crop type, especially related to the different characteristics of root crops and cereals.
How to cite: Mengen, D. and the SARSense Campaign Team: The SARSense campaign: A dataset for comparing C- and L-band SAR backscattering behaviour to changes of soil and plant parameters in agricultural areas, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1351, https://doi.org/10.5194/egusphere-egu21-1351, 2021.
Emission and backscattering at different frequencies have varied responses to soil physical processes (e.g., moisture redistribution, freeze-thaw) and vegetation growing/senescencing. Combing the use of active and passive microwave multi-frequency signals may provide complementary information, which can be used to better retrieve soil moisture, and vegetation biomass and water content for ecological applications. To this purpose, a Community Land Active Passive Microwave Radiative Transfer Modelling Platform (CLAP) was adopted in this study to simulate both emission (TB) and backscatter (σ0), in which the CLAP is backboned by the TorVergata model for modelling vegetation scattering, and an air-to-soil transition model (ATS) (accounting for surface dielectric roughness) integrated with the Advanced Integral Equation Model (AIEM) for modelling soil surface scattering. The accuracy of CLAP was assessed by both ground-based and spaceborne measurements, and the former was from the deployed microwave radiometer/scatterometer observatory at Maqu site on an alpine meadow over the Tibetan plateau. Specifically, for the passive case, simulated TB (emissivity multiplied by effective temperature) were compared to the ground-based ELBARA-III L-band observations, as well as C-band Advanced Microwave Scanning Radiometer 2 (AMSR2) and L-band Soil Moisture Active Passive (SMAP) observations. For the active case, simulated σ0 were compared to the ground-based scatterometer C- and L-bands observations, and C-band Sentinel and L-band Phased Array type L-band Synthetic Aperture Radar 2 (PALSAR-2) observations. This study is expected to contribute to improving the soil moisture retrieval accuracy for dedicated microwave sensor configurations.
How to cite: Zhao, H., Zeng, Y., Su, B., and Hofste, J.: Modelling of Microwave Multi-Frequency Emission and Backscatter by a Community Land Active Passive Microwave Radiative Transfer Modelling Platform (CLAP), EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6659, https://doi.org/10.5194/egusphere-egu21-6659, 2021.
The Mission of GMATICS is to offer systematic monitoring services based on Earth Observation data, Artificial Intelligence techniques and Open Data Cube architectures.
After the development of two initial services, GMATICS is now focusing on forest monitoring through the ESA funded project MAFIS-Multiple Actors Forest Information System.
What is MAFIS? MAFIS performs a systematic monitoring of forests in natural environments as well as of forests and green areas in urban environments.
What is MAFIS composed of? For the natural environment we use time-series of multi-mission satellite data (Multispectral, SAR, Hyperspectral, and VHR) and in-situ surveys while for forests and green areas in urban environments we also use other geo-spatial data from aerial orthophotos, LIDAR sensing, drone surveys and specialized in situ measurements. All kind of data are organized within an Open Data Cube architecture and are processed and integrated by using various AI techniques. We also use a forest growth model, exploiting extensive meteorological data, and we make MAFIS service accessible through a Web-GIS platform, enabling customer access from desk-top and mobile devices.
What are the MAFIS outputs? A set of information layers suitable for different potential users: main tree species classification, identification of forest clear-cuts and selective cuttings, detection of disturbances due to forest fires, diseases or windstorms, estimation of Above Ground Biomass (AGB) gain and losses, detailed urban and peri-urban green area assessment for planning purpose, estimation and spatial assessment of various ecosystems services (carbon sequestration, pollutant removal, thermal comfort, pollen risks, etc.), monitoring of tree status for maintenance actions identification and prioritization.
Who are MAFIS potential users? Ministries of agriculture and environment, Local Administrations, wood-chain industry, municipalities, architects and urban planners, tree care and nursery companies, multiutility companies, International Organizations, Universities and Research Centres (forests, ecology, architecture).
How to cite: Maranesi, M., Picchiani, M., Clementini, C., Salbitano, F., Marchetti, M., Del Frate, F., Chirici, G., Hofierka, J., Bertani, R., Maroè, P., Kubanek, J., and Ferretti, S.: MAFIS-Multiple Actors Forest Information System: EO+AI+ODC for scalable forest monitoring services, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-16539, https://doi.org/10.5194/egusphere-egu21-16539, 2021.
The monitoring of inundation phenomena through synthetic aperture radar (SAR) data on vegetated areas can be improved through an integrated analysis of different spectral bands. The combination of data with different penetration depths beneath the vegetated canopy can help determine the response of flooded areas with distinct types of vegetation cover to the microwave signal. This is useful especially in cases, which actually constitute the majority, where ground data are scarce or not available.
The present study concerns the application of multi-temporal, multi-frequency, and multi-polarization SAR images, specifically data from the Sentinel-1 and PALSAR 2 SAR sensors, operating in C band, VV polarization, and L band, HH and HV polarizations, respectively, in synergy with globally-available land cover data, for improving flood mapping in densely vegetated areas, such as the Zambezi-Shire basin, Mozambique , characterized by wetlands, open and closed forest, cropland, grassland (herbaceous and shrubs), and a few urban areas.
We show how the combination of various data processing techniques and the simultaneous availability of data with different frequencies and polarizations can help to monitor floodwater evolution over various land cover classes. They also enable detection of different scattering mechanisms, such as double bounce interaction of vegetation stems and trunks with underlying floodwater, giving precious information about the distribution of flooded areas among the different ground cover types present on the site.
This kind of studies are expected to assume increasing importance as the availability of multi-frequency data from SAR satellite constellations will increase in the future, thanks to initiatives such as the EU Copernicus program L-band satellite mission ROSE-L , and their tight integration with Sentinel-1 as well as with other national constellations such as ALOS 2, or SAOCOM.
 Refice, A.; Zingaro, M.; D’Addabbo, A.; Chini, M. Integrating C- and L-Band SAR Imagery for Detailed Flood Monitoring of Remote Vegetated Areas. Water 2020, 12, 2745, doi:10.3390/w12102745.
 Pierdicca, N.; Davidson, M.; Chini, M.; Dierking, W.; Djavidnia, S.; Haarpaintner, J.; Hajduch, G.; Laurin, G.V.; Lavalle, M.; López-Martínez, C.; et al. The Copernicus L-band SAR mission ROSE-L (Radar Observing System for Europe). In Active and Passive Microwave Remote Sensing for Environmental Monitoring III; SPIE: Washington, DC, USA, 2019; Volume 11154, p. 13.
How to cite: Refice, A., D'Addabbo, A., Chini, M., and Zingaro, M.: Flood monitoring in remote areas: integration of multi-frequency SAR data, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4452, https://doi.org/10.5194/egusphere-egu21-4452, 2021.
Approximately 90% of the world total paddies area and annual output of the rice production are concentrated in monsoon Asia, which has no more land/water resources for further expansion of cultivation. Most rice grows under lowland conditions where currently facing to the fresh water scarcity due to sea-water intrusion accelerated by sea-level rise and land-subsidence, and decelerating freshwater supply by upstream-dam construction. Since the rice production also requires large amount of water (3,000-5,000 L kg-1 rice), water-saving irrigation practice (e.g., Alternate Wetting and Drying, a.k.a., AWD) is desirable to be implemented in this region to save the water-demand sustainably, and irrigation status need to be evaluated for the decision making on sustainable food security. In addition to the significance of AWD’s role as an adaptation to drought risks, AWD also has a potential to act as an important mitigation-measure by reducing methane emission from paddy soils. This function is very important since rice cropping is responsible for approximately 11% of global anthropogenic CH4 emissions, and rice has the highest greenhouse gas intensity among the main food crops.
In order to implement AWD in Asian rice paddies as a mitigation-measure based on a carbon pricing scheme, it is important to evaluate the spatial distribution of AWD paddy fields in the target region. For the detection of AWD-fields versus continuously-flooding fields, it is essential to develop method using EO data to detect soil inundation under rice plants at various growth stages. In this study, ALOS-2/PALSAR-2 and Sentinel-1 data were used to combine the penetration capacity of L-band SAR data with C-band data capacity to monitor rice growth status with their high temporal resolution.
The study was conducted in triple rice cropping systems in the Vietnamese Mekong delta (5 sites: Thot Not in Can Tho city; Chau Thanh, Cho Moi, Thoai Son and Tri Ton in An Giang Province, where AWD field campaign was conducted from 2012 to 2017. EO data consisted of ALOS-2/PALSAR-2 every 14 days in 2017/2018 in An Giang province at high resolution observation mode (3-6m resolution) and ScanSAR observation mode (25-100m resolution) every 42 days over the Mekong delta.
As the result of the classification using the dual-polarization ALOS-2/PALSAR-2 data, soil inundation status could be detected during various rice growth stages. To evaluate rice productivity and GHG emissions from rice fields, we developed a simulation system based on the DeNitrification-Decomposition (DNDC) model which can assimilate PALSAR-2 inundation map and ground observed GHG -flux and rice growth status data on a pixel basis. For spatial extension, rice map, together with rice calendar (sowing date, rice growth status), required as inputs by DNDC are provided by the GeoRice project, based on the use of Sentinel-1 6-day time series. This paper presents the performance of multi-sensor data fusion to realize sustainable agricultural management by mitigating the GHGs emission while maintaining or improving regional fresh water use efficiency for stable food production under climate change pressure.
How to cite: Arai, H., Le Toan, T., Takeuchi, W., Oyoshi, K., Phan, H., Nguyen, L. D., Fumoto, T., and Inubushi, K.: Detecting rice inundation status for water saving and methane emission mitigation measures using Sentinel-1 & ALOS-2/PALSAR-2 Data, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7831, https://doi.org/10.5194/egusphere-egu21-7831, 2021.
The split-spectrum method (SSM) can largely isolate and correct for the ionospheric contribution in the L-band interferometric synthetic aperture radar (InSAR). The standard SSM is performed on the assumption of only the first-order ionospheric dispersive effect, which is proportional to the total electron content (TEC). It is also known that during extreme atmospheric events, either originated from the ionosphere or in the troposphere, other dispersive effects do exist and potentially provide new insights into the dynamics of the atmosphere, but there have been few detection reports of such signals by InSAR. We apply L-band InSAR into heavy rain cases and examine the applicability and limitation of the standard SSM. Since no events such as earthquakes to cause surface deformation took place, the non-dispersive component is apparently attributable to the large amount of water vapor associated with heavy rain, whereas there are spotty anomalies in the dispersive component that are closely correlated with the heavy rain area. The ionosonde and Global Navigation Satellite System (GNSS) rate of total electron content index (ROTI) map both show little anomalies during the heavy rain, which suggests few ionospheric disturbances. Therefore, we interpret that the spotty anomalies in the dispersive component of the standard SSM during heavy rain are originated not in the ionosphere but the troposphere. While we can consider two physical mechanisms, one is runaway electron avalanche and the other is the scattering due to rain, comparison with the observations from the ground-based lightning detection network and rain gauge data, we conclude that the rain scattering interpretation is spatiotemporally favorable. We further propose a formulation to examine if another dispersive phase than the first-order TEC effect is present and apply it to the heavy rain cases as well as two extreme ionospheric sporadic-E events. Our formulation successfully isolates the presence of another dispersive phase during heavy rain that is in positive correlation with the local rain rate. Furthermore, our formulation is also able to detect the occurrence of higher-order ionospheric effects during Sporadic-E cases.
How to cite: Setiawan, N. and Furuya, M.: Tropospheric Dispersive Phase Anomalies during Heavy Rain Detected by L-band InSAR and Their Interpretation, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13944, https://doi.org/10.5194/egusphere-egu21-13944, 2021.
This research is related to the JAXA 6th Research Announcement for the Advanced Land
Observing Satellite-2 (ALOS-2) project "Improved Sea Ice Parameter Estimation with L-Band SAR (ISIPELS)".
In the study ALOS-2/PALSAR-2 dual-polarized Horizontal-transmit-Horizontal-receive/
Horizontal-transmit-Vertical-receive (HH/HV) ScanSAR mode L-band Synthetic Aperture Radar (SAR) imagery
over an Arctic study area were evaluated for their suitability for operational sea ice monitoring.
The SAR data consisting of about 140 HH/HV ScanSAR ALOS-2/PALSAR-2 images were acquired during the winter 2017.
These L-band SAR data were studied for estimation of different sea ice parameters:
sea ice concentration, sea ice thickness, sea ice type, sea ice drift. Also some comparisons with nearly
coincident C-band data over the same study area have been made. The results indicate that L-band
SAR data from ALOS-2/PALSAR-2 are very useful for estimating the studied sea ice parameters and equally good
or better than using the conventional operational dual-polarized C-band SAR satellite data.
How to cite: Karvonen, J.: ALOS-2/PALSAR-2 dual-polarized L-band data for sea ice parameter estimation and sea ice classification , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3920, https://doi.org/10.5194/egusphere-egu21-3920, 2021.
In the yearlong MOSAIC expedition (2019-2020) R/V Polarstern drifted with sea ice through the Arctic Ocean, with the goal to continually monitor changes in the coupled ocean-ice-atmosphere system throughout the seasons. A substantial amount of synthetic aperture radar (SAR) satellite images overlapping the campaign was collected. Here, we investigate the change in polarimetric features over sea ice from the freeze up to the advanced melt season using fully polarimetric L-band images from the ALOS-2 PALSAR-2 and fully polarimetric C-band images from the RADARSAT-2 satellite SAR sensors.
Three different sea ice types are investigated, young ice, level first year ice and deformed first and second-year ice. Areas of deformed and level sea ice were observed in the vicinity of R/V Polarstern and these areas are included whenever possible in the yearlong time series.
Comparing the different sea ice types, we observe that during the freezing season there is a larger difference in the co-polarization channels between smooth and deformed ice in L-band compared to C-band. Similar to earlier findings we observe larger differences between young ice and deformed ice backscatter values in the L-band data compared to the C-band data. Moreover, throughout the year the HV-backscatter values show larger differences between level and deformed sea ice in L-band than C-band. The L-band data variability is significantly smaller for the level sea ice compared to the deformed sea ice, and this variability was also smaller than that observed for the overlapping C-band data. Thus L-band data could be more suitable to reliable separate deformed from level sea ice areas.
Within the L-band images a noticeable shift towards higher backscatter values in early melt season compared to the freezing season for all polarimetric channels is observed, though no such strong trend is found in the C-band data. The change in backscatter values is first noticeable in the C-band images and later followed by a change in the L-band images, probably caused by their different penetration depth and volume scattering sensitivities. This change also results in a smaller backscatter variability.
The polarization difference (PD; VV-HH on a linear scale) show a seasonal dependency for the smooth and deformed sea ice within the L-band data, whereas for the C-band data no such trend is observed. For the L-band data were the PD variability for all ice classes reasonably small for the freezing season, with a significant shift towards larger variability during the early melt season, though during this time period the mean PD values remained similar. However, once the temperatures reached above 0°C both the variability and the mean values increased significantly.
Overall, our results demonstrate that the C- and L-band data are complementary to one another and that through their slightly different dependencies on season and sea ice types, a combination of the two frequencies can aid improved sea ice classification. The availability of a high spatial and temporal resolution dataset combined with in-situ information ensures that seasonal changes can be fully explored.
How to cite: Johansson, M., Singha, S., Spreen, G., Howell, S., Sobue, S., and Davidson, M.: High spatial and temporal resolution L- and C-band Synthetic Aperture Radar data analysis from the yearlong MOSAiC expedition, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2892, https://doi.org/10.5194/egusphere-egu21-2892, 2021.
Synthetic aperture radar (SAR) has become an essential component in ocean remote sensing due it’s high sensitivity to sea surface dynamics and its high spatial resolution. The ALOS-2 SAR data are underutilized for ocean surface wind and current retrieval. Although the primary goals of the ALOS-2 mission are focused on land applications, the extension of the satellite scenes over the coastal areas offers an opportunity for ocean applications. The underutilization of ALOS-2 data is mainly due to the fact that at low radar frequencies, e.g. L-band, the sensitivity of the radar scattering coefficient to wind speed and the sensitivity of the Doppler frequency shift to sea surface velocity is lower than at higher frequencies, e.g. C- and X-band. This is also due to the fact that most of ALOS-2 images are acquired in HH or HV polarization while the VV polarization is often preferred in ocean applications due the higher signal to noise ratio.
The wind speed is retrieved from Sentinel-1 and ALOS-2 using the existing empirical C- and L-band geophysical model functions. For Sentinel-1, the Doppler frequency shift provided in the OCN product is used. For ALOS-2, the Doppler frequency shift is estimated from the single look complex data using the pulse-pair processing method. The estimated Doppler shift converted to the surface radial velocity and the velocity is calibrated using land as a reference. The estimated L-band Doppler shift and surface velocity is compared to the C-band Doppler shift provided in the Sentinel-1 OCN product. Due the difference in the local time of ascending node (about 6 hours at the equator) of the two satellites, a direct pixel-by-pixel comparison is not possible, i.e. the wind and surface current can not be assumed to be constant during such a large time difference. Thus, the retrieved wind from each sensor is compared separately to model data and in-situ observations.
In this paper, the quality of the wind speed retrieved from the L-band SAR (ALOS-2) in coastal areas is assessed and compared to the C-band SAR (Sentinel-1). In addition, the feasibility of the surface current retrieval from the L-band Doppler frequency shift is investigated and also compared to Sentinel-1. Examples will be shown and discussed. This opens an opportunity for synergy between L-band and C-band SAR missions to increase the spatial and temporal coverage, which is one of the main limitations of SAR application in ocean remote sensing.
How to cite: Elyouncha, A. and Eriksson, L. E. B.: Assessment of the sea surface wind and current retrieval from ALOS-2 and Sentinel-1 SAR data over coastal areas, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7490, https://doi.org/10.5194/egusphere-egu21-7490, 2021.
In support of ESA's Mission Advisory Group for ROSE-L (Radar Observing System for Europe at L-band), a project team consisting of members of operational ice services and the International Ice Charting Working Group, the International Ice Patrol, and groups from universities and research institutes is investigating the benefits of using data from L-band SAR in addition to C-band SAR imagery for separating different sea ice classes and detecting icebergs. The tasks are: (1) a critical assessment of the current state-of-the-art in sea ice monitoring and iceberg detection, (2) matching C- and L-band SAR images acquired with temporal gaps of several hours, (3) tests and assessments of the practical use of L-band images in the operational mapping services, and (4) comparison of classification accuracies that can be achieved at C-band, L-band, and a combination of both, based on the results of automated segmentation and classification algorithms. Based on the suggestions of operational ice centers, data have been collected since April 2019 over six test sites for the Northern Hemisphere: Fram Strait, Belgica Bank, northern and southern parts of Greenland, Baffin Bay and Labrador Sea. The SAR images are acquired by Sentinel-1 at Extra Wide and Interferomeric Wide Swath modes, by RADARSAT-2 at ScanSAR mode, and by ALOS-2 PALSAR-2 at Wide Beam and Fine Beam modes. The PALSAR-2 data are provided through the 2019 to 2022 mutual cooperation project between ESA and JAXA on using SAR data in earth sciences and applications. The presentation - with contributions from project partners - will focus on the conclusions from the literature review, assessments of operational ice services regarding the gain they find in using L-band SAR images supplementary to routinely analyzed C-band imagery, and preliminary results of automated classification.
How to cite: Dierking, W. and Davidson, M.: Use of L- and C-Band SAR Satellites for Sea Ice and Iceberg Monitoring (LC-ICE), EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3916, https://doi.org/10.5194/egusphere-egu21-3916, 2021.
Interferometric Synthetic Aperture Radar (InSAR) imagery is a promising technique for retrieving Snow Water Equivalent (SWE). It exploits the relation of the interferometric phase to the amount and density of the snow in the radar signal path, leading to a quasi-linear relation with SWE (Guneriussen et al., 2001; Leinss et al., 2015). Here, we analyze timeseries of Sentinel-1 and ALOS-2 interferometric image pairs, collected over a test site in Sodankylä, Northern Finland, during the winter of 2019-2020. The satellite imagery is complemented by tower-based SAR observations using SodSAR (Sodankylä SAR) a 1-10GHz fully polarimetric SAR instrument. Typical satellite visit times (7 and 14 days) are compared with the 12-hour temporal resolution provided by SodSAR. Interferometric pairs from the three sensors are generated, and the interferograms are used to estimate the increase in SWE between the image acquisitions. Retrieved SWE is compared with measurements of an in-situ SWE scale, as well as manual ground observations made in the area. Coherence conservation and its relation with various meteorological events are also analyzed.
How to cite: Jorge Ruiz, J., Lemmetyinen, J., Kontu, A., and Pulliainen, J.: Snow Water Equivalent retrieval using L- & C-band InSAR., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11066, https://doi.org/10.5194/egusphere-egu21-11066, 2021.
Millions of lakes and ponds occupy large areas of the Arctic discontinuous and continuous permafrost zones. During most of the year, the surfaces of these lakes remain covered by a thick layer of ice. Synthetic Aperture Radar (SAR) data have shown to be useful for studying the ice on Arctic lakes, especially for monitoring lake ice phenology and the grounding state of the ice (ice frozen to the lakebed versus floating lake ice). Significant backscatter is often observed from the floating ice regime in C-band due to scattering on a rough ice-water interface.
Recent research has revealed features of anomalously low backscatter in Sentinel-1 C-band SAR imagery on some of the West Siberian lakes that likely belong to the floating ice regime. These anomalies are characterized by prominent shapes and sizes and seem to expand throughout late winter and/or spring. It is currently assumed that some of these features are related to strong emissions of natural gas (methane from hydrocarbon reservoirs), making it important to assess their origin in detail and understand the associated mechanisms. However, in-situ data are still missing.
Here, we assess the potential of the combined use of C-band Sentinel-1 (freely available) and L-band ALOS PALSAR-2 data (available through JAXA PI agreement #3068002) to study the backscatter anomalies. We highlight the differences between observed backscatter from the two sensors with respect to different surface types (ground-fast lake ice, floating lake ice and anomalies) and investigate backscatter differences between frozen and melting conditions. Further, polarimetric classification is performed on L-band PALSAR-2 imagery, which reveals differences in scattering mechanisms between anomalies and floating lake ice.
How to cite: Pointner, G. and Bartsch, A.: The potential of using Sentinel-1 and ALOS PALSAR-2 data for characterizing West Siberian lake ice backscatter anomalies, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11931, https://doi.org/10.5194/egusphere-egu21-11931, 2021.
The interferometric utilization of Synthetic Aperture Radar data from L-band and C-band has an important role for the monitoring of land surface deformations like former evaluations have proven . Meanwhile several multi-sensor ground-stations are available, equipped with bi-directional artificial corner-reflectors (CR) and permanent GNSS stations, attached to fine leveling baselines. The long wavelength of L-band SAR missions like ALOS-2 (λ = 22.9 cm) provides highly coherent interferograms, but here large-sized CR are required e.g. for absolute motion calibration. SAR missions with shorter wavelengths, like the C-band onboard the Sentinel-1 mission (λ = 5.6 cm) provide, in general, less coherent interferograms, but a smaller CR size is sufficient. In order to assess the capabilities of L- and C-band SAR data the impulse response function will be calculated at corner-reflector sites and the coherence will be estimated in rural areas of the Saar test site.
The test site is located in the Saar-Lorraine coal basin at the French-German border, a nowadays post-mining district with highly urbanized settlements as well as large stretches of forested and rural areas. The area is characterized by century long active deep mining – mainly for hard coal – including extensive groundwater management measures. Here, the active coal mining started in the 18th century and ended in 2006 (Lorraine) and 2012 (Saar) . Meanwhile some of the underground mines got progressively flooded. As a consequence surface uplift occurred and is expected to be ongoing in the near future . For a 12 by 14 km area in the Saar district dense and highly accurate leveling campaigns have been performed bi-annually since 2013. Thus, besides good knowledge of subsurface geology and mining activities also precise in-situ measurements of the ground motion are available. The recent and ongoing surface deformations will be monitored using multiple methods including a network of CR at multi-sensor ground stations  and publicly accessible Persistent Scatterer Interferometry datasets from the Sentinel-1 based Ground Motion Service Germany .
In late 2020 first ALOS-2 acquisitions of the Saar area from the ESA-JAXA cooperation were made available to the authors. The ALOS-2 data are evaluated and placed in relation to Sentinel-1 acquisitions. Finally, an outlook on the possible complementary use of geodetic and C- and L-band data in the Saar district as well as for other mining areas in Germany is given.
 Wegmueller et al. 2005: Monitoring of mining induced surface deformation using L-band SAR interferometry. IGARSS 2005; DOI: 10.1109/IGARSS.2005.1526447
 Corbel et al. 2017: Coal mine flooding in the Lorraine-Saar basin: experience from the French mines. IMWA 2017. https://www.imwa.info/docs/imwa_2017/IMWA2017_Corbel_161.pdf
 Heitfeld-Schetelig 2016: Gutachten zu den Bodenbewegungen im Rahmen des stufenweisen Grubenwasseranstiegs in den Wasserprovinzen Reden und Duhamel. http://www.bid.rag.de/bid/PDFs/SA//GWA_Reden_Duhamel/3_IHS_Bodenbewegungen/IHS_Saar_Gelaendehebungen_WH_Reden_Duhamel_2016_04_20.pdf
 Spreckels et al. 2020: GNSS, Nivellement und Radar – einheitliche Multisensor-Standorte als Referenzpunkte zur Überwachung von Bodenbewegungen. Geomonitoring 2020. DOI: 10.15488/9351
 BGR, 2021: https://bodenbewegungsdienst.bgr.de
How to cite: Kalia, A. C., Spreckels, V., and Lege, T.: Comparison of L- and C-Band SAR data in the Saar Mining District, Germany, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12736, https://doi.org/10.5194/egusphere-egu21-12736, 2021.
We are sorry, but presentations are only available for users who registered for the conference. Thank you.
We are sorry, but presentations are only available for users who registered for the conference. Thank you.