R. De Abreu

Airborne SAR observations of ocean surface waves penetrating floating ice

The results are presented for a new and improved procedure for estimating the synthetic-aperture radar (SAR) image spectrum of ocean waves. This procedure, the spectral-sum method, involves summing individual image spectra derived from each of the looks of a multilook set. An automatic registration of the per-look spectral information is achieved, accounting for subimage look misregistration due to the wave propagation between looks. Spectral-sum processing is compared with traditional look-sum processing as a function of the radar slant-range. Spectral-sum processing is applied to SAR imagery of waves penetrating the marginal ice zone. >

On the utility of SeaWinds/QuikSCAT data for the estimation of the thermodynamic state of first-year sea ice

The thermodynamic state of sea ice is important to accurately and remotely monitor in order to provide improved geophysical variable parameterizations in sea ice thermodynamic models. Operationally, monitoring the thermodynamic state of sea ice can facilitate eased ship navigation routing. SeaWinds/QuikSCAT (QuikSCAT) dual-polarization [i.e., horizontal (HH) and vertical (VV)] active microwave data are available at a sufficiently large spatial scale and high temporal resolution to provide estimates of sea ice thermodynamics. This analysis evaluated the temporal evolution of the backscatter coefficient (/spl sigma//spl deg/) and VV/HH copolarization ratio from QuikSCAT for estimating sea ice thermodynamics. QuikSCAT estimates were compared against RADARSAT-1 synthetic aperture radar (SAR) imagery and the Canadian Ice Service (CIS) prototype operational ice strength algorithm. In situ data from the Collaborative Interdisciplinary Cryospheric Experiment (C-ICE) for 2000, 2001, and 2002 were used as validation. Results indicate that the temporal evolution of /spl sigma//spl deg/ from QuikSCAT is analogous to RADARSAT-1. The QuikSCAT /spl sigma//spl deg/ temporal evolution has the ability to identify winter, snow melt, and ponding thermodynamic states. Moreover, the copolarization VV/HH ratio of QuikSCAT could provide a second estimate of the ponding state in addition to identifying the drainage state that is difficult to detect by single-polarization SAR. QuikSCAT detected thermodynamic states that were found to be in reasonable agreement to that of in situ observations at the C-ICE camp for all years. Operational implications of this analysis suggest QuikSCAT is a more effective and efficient medium for monitoring ice decay compared to RADARSAT-1 and can be utilized to provide more robust modeled ice strength thresholds.

Operational sea ice monitoring with RADARSAT-2 - a glimpse into the future

In order to assess the potential of RADARSAT-2, a field-validated airborne and satellite SAR sea ice dataset was collected over young and first year sea ice at multiple polarizations. Some preliminary observations are presented.

Evaluating the use of QuikSCAT data for operational sea ice monitoring

Near-real time QuikSCAT image products are evaluated for ice mapping from the perspective of the Canadian Ice Services Operational Environment.

Radarsat-1 for sea ice monitoring in Canada-an operational success story

Monitoring of sea ice in Canadas Arctic was one of the prime motivations for the development of an all-weather, active remote sensing satellite by the Canadian government. The Canadian Ice Service (CIS) has been an active participant in the Radarsat-1 program since its inception, and throughout the research, development, and operational phases. The CIS now critically relies on Radarsat-1 to provide operational ice reconnaissance over a seasonal ice cover of approximately 2 million km/sup 2/.

Multi-polarization SAR data for operational ice monitoring

The launch of Envisat-ASAR, RADARSAT-2 and ALOS-PALSAR will offer operational polarization-diverse SAR data for the first time. A series of example data sets from aircraft and SIR-C are examined to evaluate the operational potential of these future systems. The primary operational advantage of multi-polarization data will be improved ice-water discrimination at low incidence angles, although the expected noise-floor of the satellite systems may limit their utility for discrimination of new ice types.

Initial Evaluation of Radarsat-2 for Operational Sea Ice Monitoring

Environment Canadas Canadian Ice Service (CIS) is responsible for the daily monitoring of Canadian coastal waters for ice and icebergs, and the presence of oil-based pollution. The routine provision of information on floating ice conditions promotes safe and efficient maritime operations and protects Canadas environment by providing reliable and timely information to marine users in Canadian waters. The CIS relies on a suite of both airborne and satellite sensors to operationally monitor ice in Canadian coastal and inland waterways. Satellite SAR, primarily from RADARSAT-1 and Envisat ASAR, are the primary satellite datasets used by the CIS for monitoring. On December 14, 2007, RADARSAT-1s successor, RADARSAT-2 was successfully launched. In the winter and spring of 2008, the CIS will be performing an evaluation of the performance of RADARSAT-2 in support of its ice operations. In this work, we will provide a preliminary assessment of the use of this new SAR sensor for monitoring sea ice conditions. Its performance will be compared against RADARSAT-1 and the utility of the new advanced SAR modes (e.g. ScanSAR dual-polarization) for operational ice monitoring will be reviewed based on images collected to date. Preliminary recommendations on mode selection will also be made to assist those interested in using this new platform for ice monitoring.

Sea Ice Type and Open Water Discrimination for Operational Ice Monitoring with RADARSAT-2

Envisat ASAR alternating polarization (AP) modes are evaluated to determine the potential utility of multi-polarization data for operational sea ice monitoring in preparation for RADARSAT-2.

An evaluation of SeaWinds/QuikSCAT data for the estimation of the decay status of first-year sea ice

This analysis evaluates the temporal evolution of the microwave backscatter coefficient (sigmadeg) and VV/HH sigmadeg co-polarization ratio from Qscat for estimating sea ice thermodynamics. Qscat sigmadeg were compared against RADARSAT-1 SAR sigmadeg and in situ data from the Collaborative Interdisciplinary Cryospheric Experiment (C-ICE) for 2000, 2001, and 2002 were used as validation. Results indicate that the temporal evolution of sigmadeg from Qscat is analogous to RADARSAT-1. The Qscat sigmadeg temporal evolution has the ability to identify Winter, Snow Melt, and Ponding thermodynamic states. Moreover, the co-polarization VV/HH ratio of Qscat provides a more robust estimate of the Ponding state and identifies the Drainage state that is difficult to detect by single polarization SAR

Combining AMSR-E and QuikSCAT image data to improve sea ice classification

The benefits of augmenting AMSR-E image data with QuikSCAT image data for supervised sea ice classification in the Western Arctic region are investigated. Experiments compared the performance of a maximum likelihood classifier when used with the AMSR-E only data set against the combined data and examined the preferred number of features to use as well as the reliability of training data over time. Adding QuikSCAT often improves classifier accuracy in a statistically significant manner and never decreased it significantly when enough features are used. Combining these data sets is beneficial for sea ice mapping. Using all available features is recommended and training data from a specific date remains reliable within 30 days.