Advances in mapping ice-free surfaces within the Northern Antarctic peninsula region using polarimetric RADARSAT-2 data

Ice-free areas within the Northern Antarctic Peninsula region are of interest for studying changes occurring to surface covers, including those related to glacial coverage, raised beach deposits and periglacial processes and permafrost. The objective of this work is to map the main surface covers within ice-free areas of King George Island, the largest island of the South Shetlands archipelago, using fully polarimetric RADARSAT-2 SAR data. Surface covers such as rock outcrops and glacial till, stone fields, patterned ground, and sand and gravel deposits form the most representative classes and account for 84 km2 of the ice-free areas on the island. A distribution of complex geomorphological features and landforms was obtained, being some of them considered indicators of periglacial processes and presence of permafrost.Published versio

Analysis of Permafrost Taiga by Means of X/C-Bands SAR Imagery

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Analysis of Permafrost Taiga by Means of X/C-Bands SAR Imagery

International audienc

Permafrost Taiga Analysis by Means of X/C-Band SAR Data Time Series

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Iceberg and floating sea ice characterisation in the Yung Sund fjord, Greenland,by means of optical and radar data observation

International audienceAt the Zackenberg site, sea ice starts to move between June and September resulting in icebergs flowing freely on the sea. Splitting into smaller parts, they reduce in size. Icebergs represent a risk for maritime transport and needs to be studied. In order to determine iceberg density per surface unit, size distribution, and movement of icebergs, we need to observe, detect, range and track them. The use of SAR images is particularly well adapted in regions where cloud cover is very present. We focused our study on the Yung Sund fjord in Greenland, where lots of icebergs and sea ice are generated during the summer. In the beginning of July, sea ice breaks up first, followed by icebergs created by the different glaciers based in the ocean. During our investigation, we noticed that the iceberg and sea ice were drifting very fast and thus, we needed to adapt our methodology. To achieve our goal, we collected all remote sensing data available in the region, principally Sentinel 1/2 and LandSAT 8 during one ice free season (from July 1st 2016 to September 30th, 2016). We developed an original approach in order to detect, characterize and track icebergs and sea ice independently from data. The iceberg detection was made using a watershed technique. The advantage of this technique is that it can be applied to both optical and radar images. For the latter, calibrated intensity is transformed into an image using a scaling function, in order to make ice brighter. Land data is masked using a topographic map. When data is segmented, a statistical test derived from the CFAR approach is performed to isolate an iceberg and floating sea ice from the ocean. Finally, a method, such SIFT or BRISK is used to identify and track the different segmented object. These approaches give a representation of the object and make the tracking easier and independent of the scale and rotation, which can occur because icebergs are dependent on ocean currents and wind. Finally, to fill in the gap between acquisition, mainly due to cloud cover or no image available, we use an ocean current and wind models to estimate the position of some icebergs. The used models are constrained using observation data

Iceberg and floating sea ice characterisation in the Yung Sund fjord, Greenland,by means of optical and radar data observation

International audienceAt the Zackenberg site, sea ice starts to move between June and September resulting in icebergs flowing freely on the sea. Splitting into smaller parts, they reduce in size. Icebergs represent a risk for maritime transport and needs to be studied. In order to determine iceberg density per surface unit, size distribution, and movement of icebergs, we need to observe, detect, range and track them. The use of SAR images is particularly well adapted in regions where cloud cover is very present. We focused our study on the Yung Sund fjord in Greenland, where lots of icebergs and sea ice are generated during the summer. In the beginning of July, sea ice breaks up first, followed by icebergs created by the different glaciers based in the ocean. During our investigation, we noticed that the iceberg and sea ice were drifting very fast and thus, we needed to adapt our methodology. To achieve our goal, we collected all remote sensing data available in the region, principally Sentinel 1/2 and LandSAT 8 during one ice free season (from July 1st 2016 to September 30th, 2016). We developed an original approach in order to detect, characterize and track icebergs and sea ice independently from data. The iceberg detection was made using a watershed technique. The advantage of this technique is that it can be applied to both optical and radar images. For the latter, calibrated intensity is transformed into an image using a scaling function, in order to make ice brighter. Land data is masked using a topographic map. When data is segmented, a statistical test derived from the CFAR approach is performed to isolate an iceberg and floating sea ice from the ocean. Finally, a method, such SIFT or BRISK is used to identify and track the different segmented object. These approaches give a representation of the object and make the tracking easier and independent of the scale and rotation, which can occur because icebergs are dependent on ocean currents and wind. Finally, to fill in the gap between acquisition, mainly due to cloud cover or no image available, we use an ocean current and wind models to estimate the position of some icebergs. The used models are constrained using observation data

Evaluation of a bilateral filtering approach for tomographic SAR denoising

This work proposes to evaluate the effects of a spatially adaptive filter called NDSAR-BLF (N-Dimensional SAR Bilateral Filter) on scatterer separation and height estimation from SAR tomograms. We have developed a spatial simulation procedure allowing to generate a tomographic image stack from a simple 3D building model, assuming a multi-track airborne configuration and a distributed target model incorporating multi-dimensional speckle. Inversion of such a model requires the estimation of a covariance matrix from the data. We show the importance of spatial adaptivity in covariance estimation by comparing the 3D reconstructions obtained with our filter and the boxcar filter. Our experiments show the ability of the NDSAR-BLF to improve height estimation and scatterer separation in layover areas thanks to its smoothing and edge preserving properties.Peer ReviewedPostprint (published version

Permafrost investigation in Central Siberia (Yakutia) using X-Band Dual-Pol InSAR data

International audienc

Using polarimetry in D-InSAR for ground deformation estimation over permafrost environment

International audienc

Modeling of SAR intensity for coastal survey

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