Improved Sea Ice Concentration Estimation Through Fusing Classified SAR Imagery and AMSR-E Data

2016 ◽  
Vol 42 (1) ◽  
pp. 41-52 ◽  
Author(s):  
Lei Wang ◽  
K. Andrea Scott ◽  
David A. Clausi
2021 ◽  
Author(s):  
Grant J. Macdonald ◽  
Stephen F. Ackley ◽  
Alberto M. Mestas-Nuñez

Abstract. Polynyas are key sites of ice production during the winter and are important sites of biological activity and carbon sequestration during the summer. The Amundsen Sea Polynya (ASP) is the fourth largest Antarctic polynya, has recorded the highest primary productivity and lies in an embayment of key oceanographic significance. However, knowledge of its dynamics, and of sub-annual variations in its area and ice production, is limited. In this study we primarily utilize Sentinel-1 SAR imagery, sea ice concentration products and climate reanalysis data, along with bathymetric data, to analyze the ASP over the period November 2016–March 2021. Specifically, we analyze (i) qualitative changes in the ASP's characteristics and dynamics, and quantitative changes in (ii) summer polynya area, (iii) winter polynya area and ice production. From our analysis of SAR imagery we find that ice produced by the ASP becomes stuck in the vicinity of the polynya and sometimes flows back into the polynya, contributing to its closure and limiting further ice production. The polynya forms westward off a persistent chain of grounded icebergs that are located at the site of a bathymetric high. Grounded icebergs also influence the outflow of ice and facilitate the formation of a 'secondary polynya' at times. Additionally, unlike some polynyas, ice produced by the polynya flows westward after formation, along the coast and into the neighboring sea sector. During the summer and early winter, broader regional sea ice conditions can play an important role in the polynya. The polynya opens in all summers, but record-low sea ice conditions in 2016/17 cause it to become part of the open ocean. During the winter, an average of 78 % of ice production occurs in April–May and September–October, but large polynya events often associated with high winds can cause ice production throughout the winter. While passive microwave data or daily sea ice concentration products remain key for analyzing variations in polynya area and ice production, we find that the ability to directly observe and qualitatively analyze the polynya at a high temporal and spatial resolution with Sentinel-1 imagery provides important insights about the behavior of the polynya that are not possible with those datasets.


2021 ◽  
Author(s):  
Juha Karvonen

<p>This research is related to the JAXA 6th Research Announcement for the Advanced Land<br>Observing Satellite-2 (ALOS-2) project "Improved Sea Ice Parameter Estimation with L-Band SAR (ISIPELS)".<br>In the study ALOS-2/PALSAR-2 dual-polarized Horizontal-transmit-Horizontal-receive/<br>Horizontal-transmit-Vertical-receive (HH/HV) ScanSAR mode L-band  Synthetic Aperture Radar (SAR) imagery<br>over an Arctic study area were evaluated for their suitability for operational sea ice monitoring.<br>The SAR data consisting of about 140 HH/HV ScanSAR ALOS-2/PALSAR-2 images were acquired during the winter 2017.<br>These L-band SAR data were studied for estimation of different sea ice parameters:<br>sea ice concentration, sea ice thickness, sea ice type, sea ice drift. Also some comparisons with nearly<br>coincident C-band data over the same study area have been made. The results indicate that L-band<br>SAR data from ALOS-2/PALSAR-2 are very useful for estimating the studied sea ice parameters and equally good<br>or better than using the conventional operational dual-polarized C-band SAR satellite data.</p><p> </p>


2014 ◽  
Vol 8 (5) ◽  
pp. 1639-1650 ◽  
Author(s):  
J. Karvonen

Abstract. We have studied the possibility of combining the high-resolution synthetic aperture radar (SAR) segmentation and ice concentration estimated by radiometer brightness temperatures. Here we present an algorithm for mapping a radiometer-based concentration value for each SAR segment. The concentrations are estimated by a multi-layer perceptron (MLP) neural network which has the AMSR-2 (Advanced Microwave Scanning Radiometer 2) polarization ratios and gradient ratios of four radiometer channels as its inputs. The results have been compared numerically to the gridded Finnish Meteorological Institute (FMI) ice chart concentrations and high-resolution AMSR-2 ASI (ARTIST Sea Ice) algorithm concentrations provided by the University of Hamburg and also visually to the AMSR-2 bootstrap algorithm concentrations, which are given in much coarser resolution. The differences when compared to FMI daily ice charts were on average small. When compared to ASI ice concentrations, the differences were a bit larger, but still small on average. According to our comparisons, the largest differences typically occur near the ice edge and sea–land boundary. The main advantage of combining radiometer-based ice concentration estimation and SAR segmentation seems to be a more precise estimation of the boundaries of different ice concentration zones.


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