Thomas Hollands

Performance of a multiscale correlation algorithm for the estimation of sea ice drift from SAR images: initial results

Abstract Sea-ice drift fields were obtained from sequences of synthetic aperture radar (SAR) images using a method based on pattern recognition. the accuracy of the method was estimated for two image products of the Envisat Advanced SAR (ASAR) with 25 m and 150 m pixel size. For data from the winter season it was found that 99% of the south–north and west–east components of the determined displacement vector are within ±3–5 pixels of a manually derived reference dataset, independent of the image resolution. For an image pair with 25 m resolution acquired during summer, the corresponding value is 12 pixels. Using the same resolution cell dimensions for the displacement fields in both image types, the estimated displacement components differed by 150–300 m. the use of different texture parameters for predicting the performance of the algorithm dependent on ice conditions and image characteristics was studied. It was found that high entropy values indicate a good performance.

Comparison of Automatic DSM Generation Modules by Processing IKONOS Stereo Data of an Urban Area

This study deals with the evaluation of four different image-processing software modules for the generation of digital surface models from very high-resolution stereo satellite data. The analysis was done in an urban area due to the growing interest in 3-D information over built-up areas. Depending on the different geometric model approaches used by the different software packages, shifts between 3.06-3.27 m between the digital surface models (DSMs) and the reference DSM were measured. The vertical RMSE of the four tested software packages range between 2.96-14.01 m. However, the visual evaluation resulted in a different ranking and does not confirm the quantitative results entirely. The results show that, depending on the building type to be extracted, the choice of software package may vary. The challenges of automatic DSM extraction in urban areas and the performance of current software package modules to address them are discussed. Potential improvements for automatic DSM extraction in urban areas are identified.

Reliability Measures for Sea Ice Motion Retrieval From Synthetic Aperture Radar Images

Sea ice motion is triggered by wind and ocean currents. Its magnitude and direction can be automatically retrieved using pairs of satellite images acquired over the same area. However, external reference data for validation of drift retrievals, such as tracks from buoys, are sparse. Information about the reliability of the retrieved ice drift field is crucial for applications such as operational sea ice mapping or validation of computer models for simulations of sea ice dynamics. In this paper, we introduce an intrinsic measure based on the properties of radar image pairs to assess the reliability of the retrieved ice drift vectors. The proposed method combines different parameters, e.g., correlation coefficient and two textural quantities, to provide information about the suitability of subimage regions for pattern matching. In this way, we generate a quality parameter [called confidence factor (CFA)] for the calculated ice drift velocities. The CFA is compared to results obtained by “backmatching.” The latter requires that the drift field is computed twice using the image pair, first in sequential and then in reversed order. For stable ice conditions, the results show that areas regarded as unreliable by the CFA compare well with the areas revealing larger differences from backmatching.

An assessment of the reliability of sea-ice motion and deformation retrieval using SAR images

Abstract The local mass balance of sea ice is dependent on the advection of ice into and out of an area and on the deformation processes in that area. Sea-ice motion can be observed from space by synthetic aperture radar (SAR) and quantified by drift-detection algorithms. Due to the scarcity of field observations, it remains a challenging task to validate the resulting motion fields. We analyse the quality of sea-ice motion fields derived from SAR data, using an example dataset from the Weddell Sea region. We apply a quality indicator for sea-ice motion fields which is independent of field data and evaluate it with reference data obtained from visual analysis of the SAR images. Together with the motion field, sea-ice deformation can also be retrieved from SAR data. Similarly to ice motion, it is very difficult to obtain field data to evaluate the quality of the results. Based on a manually derived reference dataset, we introduce a method to validate the retrieved deformation rates. This procedure requires no additional field data. Our analysis shows that deformation rates derived from SAR data are consistent with results obtained from buoy analysis by previous studies.