Performing two independent surveys in 2016 and 2017 over a flat sample plot (6700 m 2 ), we compare snow-depth measurements from Unmanned-Aerial-System (UAS) photogrammetry and from a new high-resolution laser-scanning device (MultiStation) with manual probing, the standard technique used by operational services around the world. While previous comparisons already used laser scanners, we tested for the first time a MultiStation, which has a different measurement principle and is thus capable of millimetric accuracy. Both remote-sensing techniques measured point clouds with centimetric resolution, while we manually collected a relatively dense amount of manual data (135 pt in 2016 and 115 pt in 2017). UAS photogrammetry and the MultiStation showed repeatable, centimetric agreement in measuring the spatial distribution of seasonal, dense snowpack under optimal illumination and topographic conditions (maximum RMSE of 0.036 m between point clouds on snow). A large fraction of this difference could be due to simultaneous snowmelt, as the RMSE between UAS photogrammetry and the MultiStation on bare soil is equal to 0.02 m. The RMSE between UAS data and manual probing is in the order of 0.20-0.30 m, but decreases to 0.06-0.17 m when areas of potential outliers like vegetation or river beds are excluded. Compact and portable remote-sensing devices like UASs or a MultiStation can thus be successfully deployed during operational manual snow courses to capture spatial snapshots of snow-depth distribution with a repeatable, vertical centimetric accuracy.

One of the most challenging aspects of the new-generation Low-Frequency Aperture Array (LFAA) radio telescopes is instrument calibration. The operational LOw-Frequency ARray (LOFAR) instrument and the future LFAA element of the Square Kilometre Array (SKA) require advanced calibration techniques to reach the expected outstanding performance. In this framework, a small array, called Medicina Array Demonstrator (MAD), has been designed and installed in Italy to provide a test bench for antenna characterization and calibration techniques based on a flying artificial test source. A radio-frequency tone is transmitted through a dipole antenna mounted on a micro Unmanned Aerial Vehicle (UAV) (hexacopter) and received by each element of the array. A modern digital FPGA-based back-end is responsible for both data-acquisition and data-reduction. A simple amplitude and phase equalization algorithm is exploited for array calibration owing to the high stability and accuracy of the developed artificial test source. Both the measured embedded element patterns and Exp Astron (2015) 39:405-421 calibrated array patterns are found to be in good agreement with the simulated data. The successful measurement campaign has demonstrated that a UAV-mounted test source provides a means to accurately validate and calibrate the full-polarized response of an antenna/array in operating conditions, including consequently effects like mutual coupling between the array elements and contribution of the environment to the antenna patterns. A similar system can therefore find a future application in the SKA-LFAA context.

ABSTRACT:The purpose of this paper is to discuss how much the phases of flight planning and the setting of the camera orientation can affect a UAVs photogrammetric survey. The test site chosen for these evaluations was the Rocca of San Silvestro, a medieval monumental castle near Livorno, Tuscany (Italy). During the fieldwork, different sets of data have been acquired using different parameters for the camera orientation and for the set up of flight plans. Acquisition with both nadiral and oblique orientation of the camera have been performed, as well as flights with different direction of the flight lines (related with the shape of the object of the survey). The different datasets were then processed in several blocks using Pix4D software and the results of the processing were analysed and compared. Our aim was to evaluate how much the parameters described above can affect the generation of the final products of the survey, in particular the product chosen for this evaluation was the point cloud.

Abstract.Photogrammetric surveys using Unmanned Aerial Systems (UAS) may represent an alternative to existing methods for measuring the distribution of snow, but additional efforts are still needed to establish this technique as a low-cost, yet precise tool. Importantly, existing works have mainly used sparse evaluation datasets that limit the insight into UAS performance at high spatial resolutions. Here, we compare a UAS-based photogrammetric map of snow depth with data acquired with a 5MultiStation and with manual probing over a sample plot. The relatively high density of manual data (135 pt over 6700 m 2 , i.e., 2 pt/100 m 2 ) enables to assess the performance of UAS in capturing the marked spatial variability of snow. The use of a MultiStation, which exploits a scanning principle, also enables to compare UAS data on snow with a frequently used instrument in high-resolution applications. Results show that the Root Mean Square Error (RMSE) between UAS and MultiStation data on snow is equal to 0.036 m when comparing the two point clouds. A large fraction of this difference may be, however, due 10 to spurious differences between datasets due to simultaneous snowmelt, as the RMSE on bare soil is equal to 0.02 m. When comparing UAS data with manual probing, the RMSE is equal to 0.31 m, whereas the median difference is equal to 0.12 m. The statistics significantly decrease up to RMSE = 0.17 m when excluding areas of likely water accumulation in snow and ice layers. These results suggest that UAS represent a competitive choice among existing techniques for high-precision, high-resolution remote sensing of snow.

In this paper we present the electromagnetic modeling and beam pattern measurements of a 16-elements ultra wideband sparse random test array for the low frequency instrument of the Square Kilometer Array telescope. We discuss the importance of a small array test platform for the development of technologies and techniques towards the final telescope, highlighting the most relevant aspects of its design. We also describe the electromagnetic simulations and modeling work as well as the embeddedelement and array pattern measurements using an Unmanned Aerial Vehicle system. The latter are helpful both for the validation of the models and the design as well as for the future instrumental calibration of the telescope thanks to the stable, accurate and strong radio frequency signal transmitted by the UAV. At this stage of the design, these measurements have shown a general agreement between experimental results and numerical data and have revealed the localized effect of un-calibrated cable lengths in the inner side-lobes of the array pattern.