Title Generation of high-resolution East Antarctic sea ice maps from cloud-free MODIS satellite composite imagery
Author Fraser, A.D.; Massom, R.A.; Michael, K.J.
Author Affil Fraser, A.D., University of Tasmania, Antarctic Climate and Ecosystems Cooperative Research Centre, Hobart, Tasmania, Australia
Source Remote Sensing of Environment, 114(12), p.2888-2896, . Publisher: Elsevier, New York, NY, United States. ISSN: 0034- 4257
Publication Date Dec. 15, 2010
Notes In English. 43 refs. Ant. Acc. No: 91478. GeoRef Acc. No: 310015
Index Terms glacial geology; ice; icebergs; mapping; remote sensing; Antarctica--East Antarctica; Southern Ocean; Antarctica; Cape Adare; East Antarctica; errors; high- resolution methods; imagery; MODIS; monitoring; satellite methods; sea ice; seasonal variations
Abstract A method to generate high spatio-temporal resolution maps of landfast sea ice from cloud-free MODIS composite imagery is presented. Visible (summertime) and thermal infrared (wintertime) cloud-free 20-day MODIS composite images are used as the basis for these maps, augmented by AMSR-E ASI sea-ice concentration composite images (when MODIS composite image quality is insufficient). The success of this technique is dependent upon efficient cloud removal during the compositing process. Example wintertime maximum (~ 374,000 km2) and summertime minimum (~ 112,000 km2) fast-ice maps for the entire East Antarctic coast are presented. The summertime minimum map provides the first high-resolution indication of multi-year fast- ice extent, which may be used to help assess changes in Antarctic sea-ice volume. The 2sigma errors in fast-ice extent are estimated to be 2.98% when >= 90% of the fast-ice pixels in a 20-day period are classified using the MODIS composite, or 8.76 otherwise (when augmenting AMSR-E or the previous/next MODIS composite image is used to classify 10% of the fast ice). Imperfect composite image quality, caused by persistent cloud, inaccurate cloud masking or a highly dynamic fast-ice edge, was the biggest impediment to automating the fast-ice detection procedure.
URL http://hdl.handle.net/10.1016/j.rse.2010.07.006
Publication Type journal article
Record ID 65006837