High-Resolution Sea Ice Topography Mapping using UAS-based Sensors and Structure-from-Motion Techniques

Abstract:

Digital Elevation Models (DEMs) of sea-ice are key descriptors of the surface boundary between ice and atmosphere. High resolution (meter-scale) and accurate (cm-scale) DEM data are required to correctly understand surface-atmosphere interactions in arctic environments. Beyond that, high-quality DEM data is also needed to understand sea ice stability and quantify the suitability of sea ice as a means of navigation both on and through the ice.

Due to the stringent accuracy requirements of sea ice topography mapping, Lidar data are often used to generate sea ice DEMs. Despite their proven performance, Lidar sensors are expensive and difficult to operate especially in harsh and remote Arctic environments. Hence, alternative more efficient solutions need to be found.

To address this issue, this study is investigating the applicability of two recent technical innovations to sea ice DEM production: (1) We analyze the performance of Structure from Motion (SfM) techniques for sea ice topography mapping. SfM is an image processing technique that has recently gained momentum in the geosciences and enables high-quality DEM production from images of uncalibrated off-the-shelf cameras; (2) we investigate the applicability of Unmanned Aerial Systems (UAS) as platform for our camera systems. UAS have significant advantages for Arctic applications due to their high flexibility, low-cost, and ability to fly in environments deemed risky for manned operations. Combined, SfM and UAS may result in an intriguing alternative to traditional sensors.

Using data from a 2015 field campaign near Barrow, Alaska, we showcase the DEM measurement performance that can be achieved with UAS-based sensors and SfM processing. In addition to showing examples of DEM products, we will provide results of an extensive performance analysis where DEM measurements were compared to ground observations and DEMs from alternative sources. To analyze the impact of flight-track information on DEM quality, we first process our data with high-quality flight track information and investigate the degradation of DEM accuracy as flight-track accuracy is reduced. We also investigate the impact of lighting conditions—an important issue in the Arctic—on SfM performance.