Regional high-resolution fast ice maps - Satellite synthetic aperture radar (SAR) data

Progress Code: completed Purpose The purpose of this dataset was to develop an algorithm to derive high spatial- and -temporal resolution maps of fast ice from time series of satellite SAR data in specific regions. Provision of the data in support of the Japanese Cape Darnley Polynya project (involv...

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Bibliographic Details
Format: Dataset
Language:unknown
Published: Australian Ocean Data Network
Subjects:
AMD
Online Access:https://researchdata.edu.au/regional-high-resolution-sar-data/2819271
Description
Summary:Progress Code: completed Purpose The purpose of this dataset was to develop an algorithm to derive high spatial- and -temporal resolution maps of fast ice from time series of satellite SAR data in specific regions. Provision of the data in support of the Japanese Cape Darnley Polynya project (involving Australian collaboration). This dataset comprises high spatial- and temporal-resolution maps of coastal landfast sea ice (fast ice) distribution in the vicinity of the Cape Darnley Polynya in East Antarctica, in the June-November (winter-spring) periods of 2008 and 2009. The maps were derived from cross-correlation of pairs of spatially-overlapping Envisat Advanced Synthetic Aperture Radar (ASAR) images, using a modified version of the IMCORR algorithm to determine vectors of sea-ice motion (as described in Giles et al., 2011). Fast ice is then distinguished from moving pack ice by the fact that it is stationary. The raw ASAR WSM data (swath width 500 km) were processed using ENVI image processing software to produce geo-referenced images with a 75m pixel size. Use of SAR data ensures coverage uninterrupted by cloud cover or polar darkness. Image pairs were chosen with a time separation between 2 and 21 days. IMCORR processing of the image pairs for mapping fast ice follows Giles et al (2011) – using a reference tile size of 32x32 pixels and a search tile size of 64 x 64 pixels. A land mask was applied to avoid contamination from matches on stationary features over the continental ice sheet. The grid spacing was set to 16 x 16 pixels, so the images were over-sampled by a factor of 2 to provide a more dense set of results. Stationary fast ice vectors were chosen from the IMCORR results using a combination of the cluster search technique and a variation of the z-axis threshold technique as detailed in Giles et al (2011). The cluster search technique was applied to the IMCORR results from each image pair to derive the initial set of valid vectors – this set could contain both stationary fast ice vectors and ...