DRONE-BASED UWB RADAR TO MEASURE SNOW LAYERING IN AVALANCHE STARTING ZONES Rolf Ole Rydeng Jenssen *1,2 , Markus Eckerstorfer 1 , Hannah Vickers 1 , Kjell-Arild Høgda 1 , Eirik Malnes 1 , Svein Ketil Jacobsen 2,1 1 Norut, Northern Research Institute, Tromsø, Norway 2 UiT The Arctic University of Norway, Department of Physics and Technology, Tromsø, Norway ABSTRACT: Slab avalanches release due to failure in a weak snow layer. Determining the spatial distribution and depth of weak layers in avalanche starting zones are high-risk tasks. Moreover, by manually digging snow pits, the occurrence of a weak layer can only be identified on a pit scale (meters). We therefore propose a technical solution to this problem by mounting an Ultra Wide Band (UWB) radar system onto a drone to obtain information about the occurrence, depth, and spatial distribution of weak layers over a larger area in order to improve safety for avalanche professionals. Here, we present the testing of an UWB radar system and show its capabilities of detecting snow stratigraphy. To simulate airborne operations, we have during the spring 2016 operated the radar system via a stationary rig 1 m above the snow, along 4.2 m long transects. For verification, we dug a full snow profile pit, identifying snow stratigraphy, liquid water content and snow density using traditional methodology as well as the Avatech SP2 and the Toikka SnowFork. Preliminary results were promising and showed the potential of an airborne UWB radar in detecting distinct snow layers. In the coming winter, the radar will be mounted on a drone to perform further airborne measurements. Future work will also include more comprehensive data analysis methods to improve snow layer identification and classification. KEYWORDS: UWB radar, UAV, Snow stratigraphy, Avalanche risk assessment, Avatech. 1. INTRODUCTION The release of a dry snow slab avalanche requires the formation of failure within a so-called weak layer buried below a cohesive, denser slab layer (Gaume et al., 2016). To determine the occurrence and spatial distribution of weak and slab layers, pit scale observations are upscaled using process thinking. This traditional field methodology is both time consuming, risky, and prone to observer bias. We therefore propose a noninvasive method of obtaining spatially upscaled information about snow stratigraphy in avalanche starting zones, by using an UWB radar mounted underneath an unmanned aerial vehicle (UAV) or drone. This method has to some extent been explored with semi-stationary, ground based rigs before (Gogineni et al., 2013; Kanagaratnam et al., 2007; Marshall et al., 2007). A similar approach has also been tested from airplanes over arctic sea ice (Kwok et al., 2011). Here we present the first results obtained using a stationary rig where the radar was mounted in order to simulate airborne data acquisition. 2. METHODS 2.1 Ultra Wideband Snow Sensor (UWiBaSS) The Ultra Wide Band Snow Sounder (UWiBaSS) is a UIT developed radar system (Fig. 1) specifically designed to detect snow stratigraphy. It consist of an Ilmsens m:explore 1 sensor connected to two Archimedean spiral antennas (one transmit (TX), one receive (RX)) and a single board computer running the Ilmsens developed software to acquire and log the impulse responses. The constructed antennas have opposite polarization for RX and TX; where RX is Right Hand Circularly Polarized (RHCP) and TX is Left Hand Circularly Polarized (LHCP) (Fig 2). These antennas have a measured frequency range of approximately 950 MHz - 11 GHz (ca. 10 GHz bandwidth) (Tbl 1). However, the full range of the antennas is not used since the radar sensor operates at 0.1 - 6 GHz (5.9 GHz bandwidth) (Tbl 1). The antennas were placed in a housing with absorbing material in the backing cavity to remove the rear lobe of the antenna (Fig. 1). This causes a 1 http://ilmsens.com/index.php/en/m-explore * Corresponding author address: Rolf Ole Rydeng, Norut, Pb 6434, Tromsø Science Park, 9294 Tromsø; tel: +47 77 62 94 00; email: rolfolejenssen@gmail.com Proceedings, International Snow Science Workshop, Breckenridge, Colorado, 2016 573