In preparation for a research project focused on the risk of the sea level rise (SLR), and on the basis of previous studies, we started to investigate the ice loss by some marine-terminating ice tongues in Antarctica in the last 10 years. The first test site selected for this study was the Erebus Ice Tongue (EIT) which stretches from Ross Island into the Ross Sea. The analysis was carried out using Cosmo-SkyMed (CSK) images from the catalogue of the Italian Space Agency (ASI) and from a recent acquisition. The scene under analysis includes various elements such as sea-ice, open-sea and sections of the Ross Island coast. Over the years, the area of the EIT underwent various changes. Thus, to avoid misinterpretations caused by the temporal variations of the scene elements, it was decided to restrict the analysis to the tongue itself. The first step of the analysis defined a methodology for automatically detecting the EIT in a delimited window. This was accomplished using a Template Matching technique which samples the input image with a manual training pattern of the EIT structure. The result shows the matches of the EIT patch. In the second step, a relaxation method for pixel labelling was developed in order to compare the area of the ice tongue as it was 10 years ago and today. In the case of the Erebus Ice Tongue, the analysis shows a modest decline of the area in the last 10 years, hence a modest ice loss.
This paper presents a processing scheme for the fast computation of pancake ice size distribution from aerial photographs. The test image used in this study was collected by the Twin Otter of the Naval Research Laboratory which assisted the cruise of the research ship “Sikuliaq” while carrying out an extensive study of the autumn sea ice in the southern Beaufort Sea in 2015. The processing scheme is composed of the following steps: i) image enhancement, ii) nonlinear support vector machine (SVM) analysis, and iii) ice size distribution computation. The result confirms the advantage of having immediate information on pancake ice size distribution during a field campaign in the Arctic.
This study presents an analysis of the sea-ice area time series for the East Greenland Sea for the period January 2003 – December 2013. The data used are a subset of the Arctic Sea Ice Concentration data set derived from the observations of the passive microwave sensors AMSR-E and AMSR-2 and produced, on a daily basis, by the Inst. of Environ. Physics of the University of Bremen. The area of interest goes, approximately, from 57◦N to 84◦N and from 53◦W to 15◦E. On the basis of previous studies, the parameter Sea Ice Area as the sum of all pixels whose sea ice concentration is above 70%, was introduced for measuring sea-ice extent. A first survey of the Greenland Sea data set showed a large anomaly in year 2012; this anomaly, clearly linked with the transition period from AMSR-E to AMSR-2 when re-sampled SSM/I data were used, was partially corrected with a linear regression procedure. The correlation between monthly mean Sea Ice Area and other geophysical parameters, like air temperature, surface wind and cloud cover, was further investigated. High anti-correlation coefficients between air temperature, at sea level and in five different tropospheric layers, and observed ice cover is confirmed. Our analysis shows that the strong decline of Arctic sea-ice area in the last 10 years is not observed in the East Greenland Sea; this implies that large reductions have occurred in the Canadian and Russian Arctic. This result confirms a hypothesis recently postulated to explain the different sea-ice decline in the Arctic and Antarctic regions.
The Spinning Enhanced Visible and Infra Red Imager (SEVIRI) radiometer, on board on Meteosat Second Generation
(MSG) geostationary satellite, collects, each 15 minutes, images of the underneath part of the globe in 12 spectral bands
with a spatial resolution of 3 km. In this work the Aerosol Optical Thickness (AOT) retrieval over land using SEVIRI
data is presented. AOT at 0.55 μm is estimated minimizing the difference between measured and computed radiances in
the visible channel centered at 0.6 μm by means Look-Up Tables (LUT) obtained using 6S radiative ransfer code. The
0.6 μm surface reflectance has been computed using different procedures based on SEVIRI channels 3 and 4 centered
respectively around 1.6 and 3.9 µm. For the 0.6 μm surface reflectance retrieval using the 1.6 μm procedure, the
measurements of five automatic sun-photometers of the Aerosols Robotic Network (AERONET) located in the
Mediterranean area (Avignon, Laegeren, Modena, Rome and Lecce) has been used. The procedures show encouraging
results in case of 1.6 μm procedure retrieval and the inadequacy of 3.9 μm procedure. An AOT map of the Po Valley
(Italy), obtained from an MSG image taken during a typical winter polluted day, is shown in the paper and compared
with MODIS retrieval.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.