Microwave satellite remote sensing for a sustainable sea

The oceans cover roughly 2/3 of the Earth’s surface and are a fundamental ecosystem regulating climate, weather and representing a huge reservoir of biodiversity and natural resources. The preservation of the oceans is therefore not only relevant on an environmental perspective but also on an economical one. A sustainable approach is requested that cannot be simply achieved by improving technologies but calls for a shared new vision of common goods.Within such a complex and holistic problem, the role of satellite microwave remote sensing to observe marine ecosystem and to assist a sustainable development of human activities must be considered. In such a view the paper is meant. Accordingly, the key microwave sensor technologies are reviewed paying particular emphasis on those applications that can provide effective support to pursue some of the UN Sustainable Development Goals. Three meaningful sectors are showcased:oil and gas, where microwave sensors can provide continuous fine-resolution monitoring of critical infrastructures; renewable energy, where microwave satellite remote sensing allows supporting the management of offshore wind farms during both feasibility and operational stages; plastic pollution, where microwave technologies that exploit signals of opportunity offer large-scale monitoring capability to provide marine litter maps of the oceans

Workshop on Science Opportunities for a Multidisciplinary Long-Range Aircraft for Antarctic Research: Program and Abstract Volume

Organizing Committee: Bea Csatho, David H. Bromwich, Michael Studinger, Thomas R. Parish, Robin Muench, and Jeff StithOffice of Polar Programs, National Science Foundatio

GNSS transpolar earth reflectometry exploriNg system (G-TERN): mission concept

The global navigation satellite system (GNSS) Transpolar Earth Reflectometry exploriNg system (G-TERN) was proposed in response to ESA's Earth Explorer 9 revised call by a team of 33 multi-disciplinary scientists. The primary objective of the mission is to quantify at high spatio-temporal resolution crucial characteristics, processes and interactions between sea ice, and other Earth system components in order to advance the understanding and prediction of climate change and its impacts on the environment and society. The objective is articulated through three key questions. 1) In a rapidly changing Arctic regime and under the resilient Antarctic sea ice trend, how will highly dynamic forcings and couplings between the various components of the ocean, atmosphere, and cryosphere modify or influence the processes governing the characteristics of the sea ice cover (ice production, growth, deformation, and melt)? 2) What are the impacts of extreme events and feedback mechanisms on sea ice evolution? 3) What are the effects of the cryosphere behaviors, either rapidly changing or resiliently stable, on the global oceanic and atmospheric circulation and mid-latitude extreme events? To contribute answering these questions, G-TERN will measure key parameters of the sea ice, the oceans, and the atmosphere with frequent and dense coverage over polar areas, becoming a “dynamic mapper”of the ice conditions, the ice production, and the loss in multiple time and space scales, and surrounding environment. Over polar areas, the G-TERN will measure sea ice surface elevation (<;10 cm precision), roughness, and polarimetry aspects at 30-km resolution and 3-days full coverage. G-TERN will implement the interferometric GNSS reflectometry concept, from a single satellite in near-polar orbit with capability for 12 simultaneous observations. Unlike currently orbiting GNSS reflectometry missions, the G-TERN uses the full GNSS available bandwidth to improve its ranging measurements. The lifetime would be 2025-2030 or optimally 2025-2035, covering key stages of the transition toward a nearly ice-free Arctic Ocean in summer. This paper describes the mission objectives, it reviews its measurement techniques, summarizes the suggested implementation, and finally, it estimates the expected performance.Peer ReviewedPostprint (published version

Polar research from satellites

In the polar regions and climate change section, the topics of ocean/atmosphere heat transfer, trace gases, surface albedo, and response to climate warming are discussed. The satellite instruments section is divided into three parts. Part one is about basic principles and covers, choice of frequencies, algorithms, orbits, and remote sensing techniques. Part two is about passive sensors and covers microwave radiometers, medium-resolution visible and infrared sensors, advanced very high resolution radiometers, optical line scanners, earth radiation budget experiment, coastal zone color scanner, high-resolution imagers, and atmospheric sounding. Part three is about active sensors and covers synthetic aperture radar, radar altimeters, scatterometers, and lidar. There is also a next decade section that is followed by a summary and recommendations section

Sea Ice Extraction via Remote Sensed Imagery: Algorithms, Datasets, Applications and Challenges

The deep learning, which is a dominating technique in artificial intelligence, has completely changed the image understanding over the past decade. As a consequence, the sea ice extraction (SIE) problem has reached a new era. We present a comprehensive review of four important aspects of SIE, including algorithms, datasets, applications, and the future trends. Our review focuses on researches published from 2016 to the present, with a specific focus on deep learning-based approaches in the last five years. We divided all relegated algorithms into 3 categories, including classical image segmentation approach, machine learning-based approach and deep learning-based methods. We reviewed the accessible ice datasets including SAR-based datasets, the optical-based datasets and others. The applications are presented in 4 aspects including climate research, navigation, geographic information systems (GIS) production and others. It also provides insightful observations and inspiring future research directions.Comment: 24 pages, 6 figure

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

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)

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Department of Urban and Environmental Engineering (Environmental Science and Engineering)Sea ice closely interacts with the atmosphere and ocean systems. Land fast sea ice (fast ice) is a kind of sea ice attached to the shore, ice shelves, or grounded icebergs. It is widely distributed along the Antarctic coast and acts as an interface between the atmosphere and the ocean, affecting heat balance feedback, thermal insulation effects, and deep water formation depending on the temporal and spatial effects of the environmental conditions. It also plays an important role in the biological aspects of Antarctica. Attached to the Antarctic glacier is strongly associated with calving events of ice shelf as it is physically coupled with glaciers at the terminus. The existing Antarctic fast ice has been mainly focused on the East Antarctic, especially for the research on long-term fast ice. Several case studies for West Antarctic fast ice with satellite images were performed in local areas. Various types of satellite data and detection techniques were utilized to successfully detect fast ice. In addition, long-term fast ice maps specifically focused on the Amundsen sea of West Antarctica were generated to investigate the distribution and variability of fast ice. This thesis reports the results of fast ice detection algorithms that have been developed using various satellite images that can be used for fast ice detection. Along with the use of multiple satellite data, the proposed fast ice detection algorithms can more effectively detect fast ice, which then allows to obtain more accurate fast ice detection and produce long-term fast ice with high accuracy. Especially, the distribution and variability of time-series fast ice in West Antarctica, which is more concentrated in the Amundsen Sea, were analyzed together with bathymetry data and the distribution of glacier icebergs. In order to detect fast ice, machine learning techniques were basically used in this thesis. Two classes (i.e. fast ice and non-fast ice) were classified. Using MODIS images, there was a problem that fast ice was not produced in cloud cover areas and the polar night season, which is winter season in Antarctica. MODIS and AMSR-E satellite data were selectively used to solve the cloud contamination problem. Correlation-related variables were finally added based on the fact that fast ice is motionless for a certain period of time, and fast ice detection was performed at 15-day intervals using the improved input variables. Active microwave sensor data, ALOS PALSAR, was also used to detect fast ice and to validate fast ice detection results. Its high-spatial resolution allows to extract fast ice boundary more accurately. Fast ice detections showed good agreement with available ALOS PALSAR SAR images and MODIS reflectance images. Nearly decade-long fast ice extents were produced in the Amundsen Sea of West Antarctica and analyzed in terms of spatiotemporal variations with bathymetry and icebergs calved from ice shelves in study area. In addition, anomalous fast ice breakup events were examined, which suggests the importance of fast ice on the stability of ice shelves.clos

Earth Observing System. Volume 1, Part 2: Science and Mission Requirements. Working Group Report Appendix

Areas of global hydrologic cycles, global biogeochemical cycles geophysical processes are addressed including biological oceanography, inland aquatic resources, land biology, tropospheric chemistry, oceanic transport, polar glaciology, sea ice and atmospheric chemistry

Ionospheric correction of interferometric SAR data with application to the cryospheric sciences

Thesis (Ph.D.) University of Alaska Fairbanks, 2018The ionosphere has been identified as an important error source for spaceborne Synthetic Aperture Radar (SAR) data and SAR Interferometry (InSAR), especially for low frequency SAR missions, operating, e.g., at L-band or P-band. Developing effective algorithms for the correction of ionospheric effects is still a developing and active topic of remote sensing research. The focus of this thesis is to develop robust and accurate techniques for ionospheric correction of SAR and InSAR data and evaluate the benefit of these techniques for cryospheric research fields such as glacier ice velocity tracking and permafrost deformation monitoring. As both topics are mostly concerned with high latitude areas where the ionosphere is often active and characterized by turbulence, ionospheric correction is particularly relevant for these applications. After an introduction to the research topic in Chapter 1, Chapter 2 will discuss open issues in ionospheric correction including processing issues related to baseline-induced spectrum shifts. The effect of large baseline on split spectrum InSAR technique has been thoroughly evaluated and effective solutions for compensating this effect are proposed. In addition, a multiple sub-band approach is proposed for increasing the algorithm robustness and accuracy. Selected case studies are shown with the purpose of demonstrating the performance of the developed algorithm. In Chapter 3, the developed ionospheric correction technology is applied to optimize InSAR-based ice velocity measurements over the big ice sheets in Greenland and the Antarctic. Selected case studies are presented to demonstrate and validate the effectiveness of the proposed correction algorithms for ice velocity applications. It is shown that the ionosphere signal can be larger than the actual glacier motion signal in the interior of Greenland and Antarctic, emphasizing the necessity for operational ionospheric correction. The case studies also show that the accuracy of ice velocity estimates was significantly improved once the developed ionospheric correction techniques were integrated into the data processing flow. We demonstrate that the proposed ionosphere correction outperforms the traditionally-used approaches such as the averaging of multi-temporal data and the removal of obviously affected data sets. For instance, it is shown that about one hundred multi-temporal ice velocity estimates would need to be averaged to achieve the estimation accuracy of a single ionosphere-corrected measurement. In Chapter 4, we evaluate the necessity and benefit of ionospheric-correction for L-band InSAR-based permafrost research. In permafrost zones, InSAR-based surface deformation measurements are used together with geophysical models to estimate permafrost parameters such as active layer thickness, soil ice content, and permafrost degradation. Accurate error correction is needed to avoid biases in the estimated parameters and their co-variance properties. Through statistical analyses of a large number of L-band InSAR data sets over Alaska, we show that ionospheric signal distortions, at different levels of magnitude, are present in almost every InSAR dataset acquired in permafrost-affected regions. We analyze the ionospheric correction performance that can be achieved in permafrost zones by statistically analyzing correction results for large number of InSAR data. We also investigate the impact of ionospheric correction on the performance of the two main InSAR approaches that are used in permafrost zones: (1) we show the importance of ionospheric correction for permafrost deformation estimation from discrete InSAR observations; (2) we demonstrate that ionospheric correction leads to significant improvements in the accuracy of time-series InSAR-based permafrost products. Chapter 5 summarizes the work conducted in this dissertation and proposes next steps in this field of research