U.S. Law of the Sea Cruise to Map the Foot of the Slope and 2500-m Isobath of the U.S. Arctic Ocean Margin

U.S. Law of the Sea cruise to map the foot of the slope and 2500-m isobath of the US Arctic Ocean margin CRUISE HEALY 1102 August 15 to September 28, 2011 Barrow, AK to Dutch Harbor, A

Operational Use of Civil Space-Based Synthetic Aperture Radar (SAR)

Synthetic Aperture Radar (SAR) is a remote-sensing technology which uses the motion of the aircraft or spacecraft carrying the radar to synthesize an antenna aperture larger than the physical antenna to yield a high-spatial resolution imaging capability. SAR systems can thus obtain high-spatial resolution geophysical measurements of the Earth over wide surface areas, under all-weather, day/night conditions. This report was prepared to document the results of a six-month study by an Ad Hoc Interagency Working Group on the Operational Use of Civil (i.e., non-military) Space-based Synthetic Aperture Radar (SAR). The Assistant Administrator of NOAA for Satellite and Information Services convened this working group and chaired three meetings of the group over a six-month period. This action was taken in response to a request by the Associate Administrator of NASA for Mission to Planet Earth for an assessment of operational applications of SAR to be accomplished in parallel with a separate study requested of the Committee on Earth Studies of the Space Studies Board of the National Research Council on the scientific results of SAR research missions. The representatives of participating agencies are listed following the Preface. There was no formal charter for the working group or long term plans for future meetings. However, the working group may be reconstituted in the future as a coordination body for multiagency use of operational SAR systems

Science plan for the Alaska SAR facility program. Phase 1: Data from the first European sensing satellite, ERS-1

Science objectives, opportunities and requirements are discussed for the utilization of data from the Synthetic Aperture Radar (SAR) on the European First Remote Sensing Satellite, to be flown by the European Space Agency in the early 1990s. The principal applications of the imaging data are in studies of geophysical processes taking place within the direct-reception area of the Alaska SAR Facility in Fairbanks, Alaska, essentially the area within 2000 km of the receiver. The primary research that will be supported by these data include studies of the oceanography and sea ice phenomena of Alaskan and adjacent polar waters and the geology, glaciology, hydrology, and ecology of the region. These studies focus on the area within the reception mask of ASF, and numerous connections are made to global processes and thus to the observation and understanding of global change. Processes within the station reception area both affect and are affected by global phenomena, in some cases quite critically. Requirements for data processing and archiving systems, prelaunch research, and image processing for geophysical product generation are discussed

Detection and classification of sea ice from spaceborne multi-frequency synthetic aperture radar imagery and radar altimetry

The sea ice cover in the Arctic is undergoing drastic changes. Since the start of satellite observations by microwave remote sensing in the late 1970\u27s, the maximum summer sea ice extent has been decreasing and thereby causing a generally thinner and younger sea ice cover. Spaceborne radar remote sensing facilitates the determination of sea ice properties in a changing climate with the high spatio-temporal resolution necessary for a better understanding of the ongoing processes as well as safe navigation and operation in ice infested waters.The work presented in this thesis focuses on the one hand on synergies of multi-frequency spaceborne synthetic aperture radar (SAR) imagery for sea ice classification. On the other hand, the fusion of radar altimetry observations with near-coincidental SAR imagery is investigated for its potential to improve 3-dimensional sea ice information retrieval.Investigations of ice/water classification of C- and L-band SAR imagery with a feed-forward neural network demonstrated the capabilities of both frequencies to outline the sea ice edge with good accuracy. Classification results also indicate that a combination of both frequencies can improve the identification of thin ice areas within the ice pack compared to C-band alone. Incidence angle normalisation has proven to increase class separability of different ice types. Analysis of incidence angle dependence between 19-47\ub0 at co- and cross-polarisation from Sentinel-1 C-band images closed a gap in existing slope estimates at cross-polarisation for multiyear sea ice and confirms values obtained in other regions of the Arctic or with different sensors. Furthermore, it demonstrated that insufficient noise correction of the first subswath at cross-polarisation increased the slope estimates by 0.01 dB/1\ub0 for multiyear ice. The incidence angle dependence of the Sentinel-1 noise floor affected smoother first-year sea ice and made the first subswath unusable for reliable incidence angle estimates in those cases.Radar altimetry can complete the 2-dimensional sea ice picture with thickness information. By comparison of SAR imagery with altimeter waveforms from CryoSat-2, it is demonstrated that waveforms respond well to changes of the sea ice surface in the order of a few hundred metres to a few kilometres. Freeboard estimates do however not always correspond to these changes especially when mixtures of different ice types are found within the footprint. Homogeneous ice floes of about 10 km are necessary for robust averaged freeboard estimates. The results demonstrate that multi-frequency and multi-sensor approaches open up for future improvements of sea ice retrievals from radar remote sensing techniques, but access to in-situ data for training and validation will be critical

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

Polarimetric SAR as a Tool for Remote Sensing Salt Diapirs, Axel Heiberg Island, Nunavut

The costs and hazards associated with traditional geological mapping have driven rapid advancement of remote predictive mapping techniques using satellite data. However, few studies have implemented synthetic aperture radar for geology. This study uses quad-polarimetric RADARSAT-2 and PALSAR-1 data to produce circular polarization ratio images over Axel Heiberg Island, Nunavut, Canada. These images are used to characterize the radar properties of gypsum and anhydrite diapirs and secondary salt deposits that have been mapped using visible and near infrared, short wave infrared, and thermal infrared spectroscopy. Diapiric salt outcrops appear rough in radar at the C-Band and L-Band (cm-dm) scales, whereas the secondary salts appear smooth. Ground truthing in the field confirms that salt diapirs are rough from millimeter to meter scale, whereas secondary salt minerals are precipitating on smoother surfaces, like floodplains and hillslopes. These results show that radar can be used to differentiate between diapiric and secondary salt exposures

Report of the panel on international programs

The panel recommends that NASA participate and take an active role in the continuous monitoring of existing regional networks, the realization of high resolution geopotential and topographic missions, the establishment of interconnection of the reference frames as defined by different space techniques, the development and implementation of automation for all ground-to-space observing systems, calibration and validation experiments for measuring techniques and data, the establishment of international space-based networks for real-time transmission of high density space data in standardized formats, tracking and support for non-NASA missions, and the extension of state-of-the art observing and analysis techniques to developing nations

Cryosphere Applications

Synthetic aperture radar (SAR) provides large coverage and high resolution, and it has been proven to be sensitive to both surface and near-surface features related to accumulation, ablation, and metamorphism of snow and firn. Exploiting this sensitivity, SAR polarimetry and polarimetric interferometry found application to land ice for instance for the estimation of wave extinction (which relates to sub surface ice volume structure) and for the estimation of snow water equivalent (which relates to snow density and depth). After presenting these applications, the Chapter proceeds by reviewing applications of SAR polarimetry to sea ice for the classification of different ice types, the estimation of thickness, and the characterisation of its surface. Finally, an application to the characterisation of permafrost regions is considered. For each application, the used (model-based) decomposition and polarimetric parameters are critically described, and real data results from relevant airborne campaigns and space borne acquisitions are reported

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