Selection of the key earth observation sensors and platforms focusing on applications for Polar Regions in the scope of Copernicus system 2020-2030

An optimal payload selection conducted in the frame of the H2020 ONION project (id 687490) is presented based on the ability to cover the observation needs of the Copernicus system in the time period 2020–2030. Payload selection is constrained by the variables that can be measured, the power consumption, and weight of the instrument, and the required accuracy and spatial resolution (horizontal or vertical). It involved 20 measurements with observation gaps according to the user requirements that were detected in the top 10 use cases in the scope of Copernicus space infrastructure, 9 potential applied technologies, and 39 available commercial platforms. Additional Earth Observation (EO) infrastructures are proposed to reduce measurements gaps, based on a weighting system that assigned high relevance for measurements associated to Marine for Weather Forecast over Polar Regions. This study concludes with a rank and mapping of the potential technologies and the suitable commercial platforms to cover most of the requirements of the top ten use cases, analyzing the Marine for Weather Forecast, Sea Ice Monitoring, Fishing Pressure, and Agriculture and Forestry: Hydric stress as the priority use cases.Peer ReviewedPostprint (published version

Community Review of Southern Ocean Satellite Data Needs

This review represents the Southern Ocean community’s satellite data needs for the coming decade. Developed through widespread engagement, and incorporating perspectives from a range of stakeholders (both research and operational), it is designed as an important community-driven strategy paper that provides the rationale and information required for future planning and investment. The Southern Ocean is vast but globally connected, and the communities that require satellite-derived data in the region are diverse. This review includes many observable variables, including sea-ice properties, sea-surface temperature, sea-surface height, atmospheric parameters, marine biology (both micro and macro) and related activities, terrestrial cryospheric connections, sea-surface salinity, and a discussion of coincident and in situ data collection. Recommendations include commitment to data continuity, increase in particular capabilities (sensor types, spatial, temporal), improvements in dissemination of data/products/uncertainties, and innovation in calibration/validation capabilities. Full recommendations are detailed by variable as well as summarized. This review provides a starting point for scientists to understand more about Southern Ocean processes and their global roles, for funders to understand the desires of the community, for commercial operators to safely conduct their activities in the Southern Ocean, and for space agencies to gain greater impact from Southern Ocean-related acquisitions and missions.The authors acknowledge the Climate at the Cryosphere program and the Southern Ocean Observing System for initiating this community effort, WCRP, SCAR, and SCOR for endorsing the effort, and CliC, SOOS, and SCAR for supporting authors’ travel for collaboration on the review. Jamie Shutler’s time on this review was funded by the European Space Agency project OceanFlux Greenhouse Gases Evolution (Contract number 4000112091/14/I-LG)

Iceberg topography and volume classification using TanDEM-X interferometry

Icebergs in polar regions affect water salinity, alter marine habitats, and impose serious hazards on maritime operations and navigation. These impacts mainly depend on the iceberg volume, which remains an elusive parameter to measure. We investigate the capability of TanDEM-X bistatic single-pass synthetic aperture radar interferometry (InSAR) to derive iceberg subaerial morphology and infer total volume. We cross-verify InSAR results with Operation IceBridge (OIB) data acquired near Wordie Bay, Antarctica, as part of the OIB/TanDEM-X Antarctic Science Campaign (OTASC). While icebergs are typically classified according to size based on length or maximum height, we develop a new volumetric classification approach for applications where iceberg volume is relevant. For icebergs with heights exceeding 5 m, we find iceberg volumes derived from TanDEM-X and OIB data match within 7 %. We also derive a range of possible iceberg keel depths relevant to grounding and potential impacts on subsea installations. These results suggest that TanDEM-X could pave the way for future single-pass interferometric systems for scientific and operational iceberg mapping and classification based on iceberg volume and keel depth

Detection and characterization of icebergs in Kongsfjorden (Svalbard) based on ground-based radar images and additional remote sensing data

This thesis focuses on the exploitation of ground-based radar images to detect icebergs. Additional remote sensing data from space-borne Synthetic Aperture Radar (SAR), Unmanned Aerial Vehicle (UAV) and in-situ boat tracks has been used to compare and validate the results. The investigation site is located in Kongsfjorden (Svalbard) and the combined data acquisition took place during a two-week campaign in April 2018. Five tidewater glaciers terminate in Kongsfjorden and produce a large number of icebergs of different sizes and shapes. The ground-based radar had an elevated position in Ny-Ålesund to overview a several kilometer-wide section of the fjord. The ground-based radar used during the campaign is the GAMMA Portable Radar Interferometer (GPRI). The 5 min temporal resolution of the dataset allows one to make comparisons with the above mentioned auxiliary remote sensing data. The software Python was used to process the GPRI data. Firstly, the GPRI images were pre-processed to account for the decreasing performance in range resolution. Secondly, an area of interest located between Ny-Ålesund and Blomstrandhalvøya was chosen. Hereby, it is important to focus only on the sea region and to leave out lagoons and other coastal lines. The area of interest covers approximately 2 km long region with only water and icebergs passing by while leaving Kongsfjorden. Thirdly, a threshold was applied to the GPRI images in order to separate potential icebergs from the sea background. Analysing histograms of both iceberg and sea background is important to find the appropriate threshold. This makes sure to include as many true positive as possible. In general, we can choose between two threshold modes, namely the automated and the manual threshold methods. The automated threshold method relies on the 99.93th percentile and shows the best compromise between all GPRI images. The automated threshold method is efficient and preferably used for big amounts of data and small time slots, because one loses small icebergs or detect false alarms. Therefore, it is more effective to decide on the manual threshold method. It is time-consuming, but one can more easily distinguish between iceberg and sea background by adjusting the threshold manually. Fourthly, in order to document important parameters based on GPRI images, we extract the count, size and position of every detected iceberg. Finally, the resulting GPRI images can be georeferenced and compared with auxiliary data. The software QGIS is a useful tool to compare the GPRI image products with satellite SAR images, drone images and boat tracks. After evaluating the GPRI images with auxiliary data, it turned out that the number of detected icebergs can be increased by choosing the manual threshold method, since the positive alarms are the majority in comparison to false alarms. For the future, the automated version could be improved by applying an advanced target detection, which is already used in synthetic aperture radar imagery. The developed algorithm for iceberg detection could be further developed to track. The GPRI’s temporal resolution of 5 min is predestined for such a tracking system, because it is easier to separate different icebergs within a shorter time frame. The potential value of the results can not be overseen in terms of climate research. In the future, scientists can build upon the findings to determine the mass balance of tidewater glaciers by observing how much calved ice is leaving the fjord system. In addition, the ground-based radar is showing a high potential in detecting icebergs, even if those are rather small. This could provide new insights on the distribution, volumetry and motion of icebergs, valuable for documenting oceanic currents

Quantifying Antarctic icebergs and their melting in the ocean.

From the Antarctic Ice Sheet calves every year into the Southern Ocean, an average of 2000 km3 of icebergs. The meltwater is spread over a large area in the Southern Ocean but the large temporal variability in iceberg calving and the clustering of iceberg distribution means that meltwater injection can be locally very high. This study quantifies iceberg distribution, movement and melting using remote sensing observations and modelling. Icebergs were detected and tracked on Synthetic Aperture Radar images using a new computer-based iceberg detection method. The method allows an efficient and systematic processing of large volumes of SAR images, necessary to build a climatology of icebergs in the Southern Ocean. Tests were conducted using ground data from a field campaign and against manual image classification. The method was applied to several SAR image collections, namely the RADARS AT RAMP mosaic for the totality of coastal Antarctica, providing the first picture of iceberg distribution over such a large area. Giant icebergs (icebergs above 100 km2 in area) were shown to carry over half the total mass of the Antarctic iceberg population. Estimates of the spatial distribution of giant iceberg melting over the ocean were made using observed tracks and modelling the melting and spreading along its path. The modelling of basal melting was tested using ICESat laser altimetry to measure the reduction in the freeboard of three giant icebergs in the Ross. The distribution of meltwater for giant icebergs was combined with an existing simulation of meltwater distribution from smaller icebergs to produce the first map of total iceberg meltwater for the Southern Ocean. The iceberg contribution to the freshwater flux is shown to be relevant to both the Weddell Sea and the Southern Ocean south of the Polar Front

Arctic Sea Ice Characterization using Spaceborne Fully Polarimetric L-, C- and X-Band SAR with Validation by Airborne Measurements

Accepted manuscript version. Published version available at https://doi.org/10.1109/TGRS.2018.2809504.In recent years, spaceborne synthetic aperture radar (SAR) polarimetry has become a valuable tool for sea ice analysis. Here, we employ an automatic sea ice classification algorithm on two sets of spatially and temporally near coincident fully polarimetric acquisitions from the ALOS-2, Radarsat-2, and TerraSAR-X/TanDEM-X satellites. Overlapping coincident sea ice freeboard measurements from airborne laser scanner data are used to validate the classification results. The automated sea ice classification algorithm consists of two steps. In the first step, we perform a polarimetric feature extraction procedure. Next, the resulting feature vectors are ingested into a trained neural network classifier to arrive at a pixelwise supervised classification. Coherency matrix-based features that require an eigendecomposition are found to be either of low relevance or redundant to other covariance matrix-based features, which makes coherency matrix-based features dispensable for the purpose of sea ice classification. Among the most useful features for classification are matrix invariant-based features (geometric intensity, scattering diversity, and surface scattering fraction). Classification results show that 100% of the open water is separated from the surrounding sea ice and that the sea ice classes have at least 96.9% accuracy. This analysis reveals analogous results for both X-band and C-band frequencies and slightly different for the L-band. The subsequent classification produces similarly promising results for all four acquisitions. In particular, the overlapping image portions exhibit a reasonable congruence of detected sea ice when compared with high-resolution airborne measurements

Ocean remote sensing techniques and applications: a review (Part II)

As discussed in the first part of this review paper, Remote Sensing (RS) systems are great tools to study various oceanographic parameters. Part I of this study described different passive and active RS systems and six applications of RS in ocean studies, including Ocean Surface Wind (OSW), Ocean Surface Current (OSC), Ocean Wave Height (OWH), Sea Level (SL), Ocean Tide (OT), and Ship Detection (SD). In Part II, the remaining nine important applications of RS systems for ocean environments, including Iceberg, Sea Ice (SI), Sea Surface temperature (SST), Ocean Surface Salinity (OSS), Ocean Color (OC), Ocean Chlorophyll (OCh), Ocean Oil Spill (OOS), Underwater Ocean, and Fishery are comprehensively reviewed and discussed. For each application, the applicable RS systems, their advantages and disadvantages, various RS and Machine Learning (ML) techniques, and several case studies are discussed.Peer ReviewedPostprint (published version

Applications of Satellite Earth Observations section - NEODAAS: Providing satellite data for efficient research

The NERC Earth Observation Data Acquisition and Analysis Service (NEODAAS) provides a central point of Earth Observation (EO) satellite data access and expertise for UK researchers. The service is tailored to individual users’ requirements to ensure that researchers can focus effort on their science, rather than struggling with correct use of unfamiliar satellite data

Earth Observations for Addressing Global Challenges

"Earth Observations for Addressing Global Challenges" presents the results of cutting-edge research related to innovative techniques and approaches based on satellite remote sensing data, the acquisition of earth observations, and their applications in the contemporary practice of sustainable development. Addressing the urgent tasks of adaptation to climate change is one of the biggest global challenges for humanity. As His Excellency António Guterres, Secretary-General of the United Nations, said, "Climate change is the defining issue of our time—and we are at a defining moment. We face a direct existential threat." For many years, scientists from around the world have been conducting research on earth observations collecting vital data about the state of the earth environment. Evidence of the rapidly changing climate is alarming: according to the World Meteorological Organization, the past two decades included 18 of the warmest years since 1850, when records began. Thus, Group on Earth Observations (GEO) has launched initiatives across multiple societal benefit areas (agriculture, biodiversity, climate, disasters, ecosystems, energy, health, water, and weather), such as the Global Forest Observations Initiative, the GEO Carbon and GHG Initiative, the GEO Biodiversity Observation Network, and the GEO Blue Planet, among others. The results of research that addressed strategic priorities of these important initiatives are presented in the monograph

Satellite monitoring of harmful algal blooms (HABs) to protect the aquaculture industry

Harmful algal blooms (HABs) can cause sudden and considerable losses to fish farms, for example 500,000 salmon during one bloom in Shetland, and also present a threat to human health. Early warning allows the industry to take protective measures. PML's satellite monitoring of HABs is now funded by the Scottish aquaculture industry. The service involves processing EO ocean colour data from NASA and ESA in near-real time, and applying novel techniques for discriminating certain harmful blooms from harmless algae. Within the AQUA-USERS project we are extending this capability to further HAB species within several European countries