Abstract
AbstractAirborne electromagnetic induction sensors have demonstrated their extensive capacities to measure sea-ice thickness distributions. However, biases can emerge when comparing these 1-D measurements to a broader 2-D regional scale due to the spatial anisotropy inherent to sea-ice cover. Automated processing of available sea-ice maps could significantly ease the decision on how to set up an optimised flight pattern, which would result in representative ice thickness numbers for the region. In this study, first we investigate the extent to which the sea-ice anisotropy can influence the representativeness of an airborne survey compared to the regional situation. Second, we propose a method to process sea-ice maps prior to flights to help preparing the most representative flight plan possible for the local area. The method is based on automated segmentation of radar satellite images and extensive simulation of flight transects over the image. The spatial analysis of these transects enables for the identification of the most representative survey trajectories for the area. The method was applied for seven different synthetic aperture radar satellite images over Arctic sea ice north of Svalbard. The results indicate that the proposed method improved the representativeness of the airborne survey by identifying the most suitable transect over the ice pack.
Highlights
The ongoing global climate change affects the Arctic more than the rest of the globe (Serreze and Barry, 2011)
The random flight tracks approach shows a 180° rotational symmetry in the distribution, whereas this is not apparent in the radial approach. This difference is due to design of the experiment: in the radial analysis each line only covers half of the image, from the centre to the edge, while the lines are crossing the whole image in the random analysis
Based on segmented satellite synthetic aperture radar (SAR) imagery, we investigated the effect of the floe-scale anisotropy on airborne electromagnetic instruments (AEM) surveys
Summary
The ongoing global climate change affects the Arctic more than the rest of the globe (Serreze and Barry, 2011). The current changes in Arctic sea ice (Perovich and others, 2019; Pörtner and others, 2019) are of major relevance for shipping companies, fishery, oil and gas industry, ecosystems and local residents Understanding these ongoing changes, in particular the decrease in sea-ice thickness (Ricker and others, 2017a; 2017b) and sea-ice extent (Meier and others, 2014; Perovich and others, 2019), are essential to better understand global climate processes (Budikova, 2009; Liu and others, 2012; Vihma, 2014). The flying speed and range allow a fast and extended measurement of the regional distribution of sea-ice thickness (Renner and others, 2014; King and others, 2017; Rösel and others, 2018b), which could not be obtained by any other means It avoids an underestimation of thinner ice and leads fraction which may occur, for safety reasons, on land-based surveys. The sea ice may exhibit a substantial surface anisotropy and, in particular, long linear features, such as leads and ridges, aligned on a general direction. Identifying the true size of 2-D features with 1-D transects is a well-known problem (Key, 1993; Horvat and others, 2019) as well as the potential error induced in the resulting sampling (Key and Peckham, 1991)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
