Geostatistical and statistical classification of sea-ice properties and provinces from SAR data

Recent drastic reductions in the Arctic sea-ice cover have raised an interest in understanding the role of sea ice in the global system as well as pointed out a need to understand the physical processes that lead to such changes. Satellite remote-sensing data provide important information about remote ice areas, and Synthetic Aperture Radar (SAR) data have the advantages of penetration of the omnipresent cloud cover and of high spatial resolution. A challenge addressed in this paper is how to extract information on sea-ice types and sea-ice processes from SAR data. We introduce, validate and apply geostatistical and statistical approaches to automated classification of sea ice from SAR data, to be used as individual tools for mapping sea-ice properties and provinces or in combination. A key concept of the geostatistical classification method is the analysis of spatial surface structures and their anisotropies, more generally, of spatial surface roughness, at variable, intermediate-sized scales. The geostatistical approach utilizes vario parameters extracted from directional vario functions, the parameters can be mapped or combined into feature vectors for classification. The method is flexible with respect to window sizes and parameter types and detects anisotropies. In two applications to RADARSAT and ERS-2 SAR data from the area near Point Barrow, Alaska, it is demonstrated that vario-parameter maps may be utilized to distinguish regions of different sea-ice characteristics in the Beaufort Sea, the Chukchi Sea and in Elson Lagoon. In a third and a fourth case study the analysis is taken further by utilizing multi-parameter feature vectors as inputs for unsupervised and supervised statistical classification. Field measurements and high-resolution aerial observations serve as basis for validation of the geostatistical-statistical classification methods. A combination of supervised classification and vario-parameter mapping yields best results, correctly identifying several sea-ice provinces in the shore-fast ice and the pack ice. Notably, sea ice does not have to be static to be classifiable with respect to spatial structures. In consequence, the geostatistical-statistical classification may be applied to detect changes in ice dynamics, kinematics or environmental changes, such as increased melt ponding, increased snowfall or changes in the equilibrium line

St. Lawrence Island polynya: Ice circulation and dense water production

Thesis (Ph.D.) University of Alaska Fairbanks, 1999The St. Lawrence Island polynya (SLIP) opens every winter off the coast of St. Lawrence Island as winds move ice away from the shore. The SLIP is an important site for production of the dense water that flows northward through the Bering Strait to help maintain the Arctic Ocean halocline. Winter 1991/1992 ERS-1 SAR, thermal infrared, and passive microwave imagery are analyzed in combination with regional climate system and analytical simulations to investigate SLIP ice circulation, heat fluxes, and dense water production. Emphasis is on the February 1992 southern SLIP event. Satellite-based measurements show this polynya extended ~165km offshore and ~100km along shore at maximum extent. ERS-1 SAR GPS-derived ice motion indicated maximum ice speeds of ~30km day -1 during polynya expansion. Ice along the polynya boundary drifted parallel to the wind at 3--4% of the wind speed during north/northeasterly winds >7m s-1 Heat fluxes associated with the SLIP varied depending on method of calculation, but indicated increasing trends during polynya development. Associated ice production rates of 4.218.9cm day-1 were computed via different models. Dense water production, derived from ice production rates and polynya size, ranged from 0.011--0.017Sv, suggesting that the SLIP could account for 19--27% of the Bering Sea's contribution and 1--2% of the total Arctic contribution to Arctic Ocean halocline maintenance. Although the regional climate system model generated the SLIP on the same time scales as observed, a larger polynya resulted. The simulated polynya's heat and moisture impact was observed to at least 800mb, reaching 50km downstream. During periods of sustained winds, ice circulation was similar to that observed. Incorporation of a "barotropic" ocean component suggested that ocean circulation may be an important ice circulation forcing mechanism at the SLIP, especially during periods of weak winds, as inclusion greatly improved the simulated ice circulation. The "barotropic" ocean also improved polynya shape and extent. If regional climate changes alter the existence of polynyas like the SLIP, changes in the Arctic Ocean halocline might occur. Additional in situ observations and better fully-coupled atmosphere-ice-ocean models are needed to further ascertain the impact of polynyas on the overall Arctic climate system

Open access data in polar and cryospheric remote sensing

This paper aims to introduce the main types and sources of remotely sensed data that are freely available and have cryospheric applications. We describe aerial and satellite photography, satellite-borne visible, near-infrared and thermal infrared sensors, synthetic aperture radar, passive microwave imagers and active microwave scatterometers. We consider the availability and practical utility of archival data, dating back in some cases to the 1920s for aerial photography and the 1960s for satellite imagery, the data that are being collected today and the prospects for future data collection; in all cases, with a focus on data that are openly accessible. Derived data products are increasingly available, and we give examples of such products of particular value in polar and cryospheric research. We also discuss the availability and applicability of free and, where possible, open-source software tools for reading and processing remotely sensed data. The paper concludes with a discussion of open data access within polar and cryospheric sciences, considering trends in data discoverability, access, sharing and use.A. Pope would like to acknowledge support from the Earth Observation Technology Cluster, a knowledge exchange project, funded by the Natural Environment Research Council (NERC) under its Technology Clusters Programme, the U.S. National Science Foundation Graduate Research Fellowship Program, Trinity College (Cambridge) and the Dartmouth Visiting Young Scientist program sponsored by the NASA New Hampshire Space Grant.This is the final published version. It's also available from MDPI at http://www.mdpi.com/2072-4292/6/7/6183

Earth resources: A continuing bibliography with indexes, issue 50

This bibliography lists 523 reports, articles and other documents introduced into the NASA scientific and technical information system between April 1 and June 30, 1986. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economic analysis

Arctic–CHAMP: A program to study Arctic hydrology and its role in global change

The Arctic constitutes a unique and important environment that is central to the dynamics and evolution of the Earth system. The Arctic water cycle, which controls countless physical, chemical, and biotic processes, is also unique and important. These processes, in turn, regulate the climate, habitat, and natural resources that are of great importance to both native and industrial societies. Comprehensive understanding of water cycling across the Arctic and its linkage to global biogeophysical dynamics is a scientific as well as strategic policy imperative

The Polar Oceans Program of the Alaska SAR Facility

The science plan for the Alaska SAR Facility (ASF) focuses on earth surface characteristics that are of interest within the overall concept of global change and that show significant regional, seasonal and interannual variations resulting in changes in the strength of their radar returns. The polar oceans, with the continuous motion and deformation of the pack ice and the changes in the surface state of the surrounding open seas, offer excellent opportunities for such research. Because such studies require both frequent and detailed analysis of Synthetic Aperture Radar (SAR) data, a Geophysical Processor System (GPS) has been developed to speed the extraction of useful geophysical information from SAR data sets. The system will initially produce three main types of products: (a) sets of ice motion vectors obtained by automated computer tracking of identifiable ice floes on sequential images, (b) the areal extent and location of several different ice types and open water and (c) a characterization of the wave state in ice-free regions as well as within the ice in the marginal ice zone at locations where significant wave penetration occurs. Details of these analysis procedures are described. Initially the GPS is planned to process 10 image pairs/day for ice motion, 20 images/day for ice type variations and 1 image/day for wave information, with a total estimated processing time of 13 hours. A variety of projects plan to utilize the SAR data stream in studies of ice, lead and polynya dynamics and thermodynamics. A common feature of these research programs will be attempts to provide, via the coupling of the SAR data with ice property and ice dynamics models, improved estimates of the heat and mass fluxes into both the atmosphere and the ocean as affected by the characteristics of the ice cover.Key words: SAR, radar, sea ice, image analysis, remote sensingMots clés: RAAS, radar, glace de mer, analyse d’images, télédétectio

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

Earth resources: A continuing bibliography with indexes

This bibliography lists 579 reports, articles, and other documents introduced into the NASA scientific and technical information system. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economical analysis

Earth Resources, A Continuing Bibliography with Indexes

This bibliography lists 460 reports, articles and other documents introduced into the NASA scientific and technical information system between July 1 and September 30, 1984. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economical analysis

Earth resources: A continuing bibliography with indexes (issue 51)

This bibliography lists 382 reports, articles and other documents introduced into the NASA scientific and technical information system between July 1 and September 30, 1986. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economic analysis