ALBERT

Description: Soil organic carbon (SOC) is one of the key indicators for soil quality and plays an important role in the global C cycle. Remote sensing techniques are rapidly evolving for mapping and monitoring SOC. Platforms range from unmanned aerial systems (UAS) to airborne and satellite systems. Multivariate analysis and machine learning techniques are used to calibrate SOC prediction models from the reflectance of bare soil surfaces in the visible, near infrared and shortwave infrared wavelengths (400–2500 nm). The principles of imaging spectroscopy, its application from UAS, airborne and satellite platforms and the challenges for the future of this rapidly evolving technique are discussed.

Description: Analysis and identifying the displacement characteristics play a key role in timely monitoring and detecting the physical responses of the bridge to ensure the safety of the human and structure. Many previous kinds of research used GNSS data to identify displacement and oscillation modelling of the bridge with different algorithms. This study uses GNSS time-series data to determine linear displacement and model oscillation of the bridge using a procedure including filtering outliers, linear regression, and sin function to identify amplitude in three directions, the plane displacement velocity, spatial displacement velocity, and vibration model of the bridge. The data in the research in the GNSS time-series data from three P5 GNSS receivers of the CHC brand on the Dachongyong bridge in Nanning, China with 1646 observations, at one-hour sample intervals in 68 consecutive days. The plane and spatial velocity of the three points DCQ01, DCQ02, and DCQ03 is 0.0181 mm/h, 0.0185 mm/h; 0.0114 mm/h, 0.0173 mm/h; and 0.0071 mm/h, 0.0082 mm/h respectively. The study results are significant in analyzing and identifying the bridge's displacement characteristics.

Description: Volcanic flanks subject to hydrothermal alteration become mechanically weak and gravitationally unstable, which may collapse and develop far-reaching landslides. The dynamics and trajectories of volcanic landslides are hardly preserved and challenging to determine, which is due to the steep slopes and the inherent instability. Here we analyze the proximal deposits of the 21 July 2014, landslide at Askja (Iceland), by combining high-resolution imagery from satellites and Unoccupied Aircraft Systems. We performed a Principal Component Analysis in combination with supervised classification to identify different material classes and altered rocks. We trained a maximum-likelihood classifier and were able to distinguish 7 different material classes and compare these to ground-based hyperspectral measurements that we conducted on different rock types found in the field. Results underline that the Northern part of the landslide source region is a hydrothermally altered material class, which bifurcates halfway downslope and then extends to the lake. We find that a large portion of this material is originating from a lava body at the landslide headwall, which is the persistent site of intense hydrothermal activity. By comparing the classification result to in-situ hyperspectral measurements, we were able to further identify the involved types of rocks and the degree of hydrothermal alteration. We further discuss associated effects of mechanical weakening and the relevance of the heterogeneous materials for the dynamics and processes of the landslide. As the study demonstrates the success of our approach for identification of altered and less altered materials, important implications for hazard assessment in the Askja caldera and elsewhere can be drawn.

Description: This dataset contains the processed and raw data collected with the Backscatter Cloud Probe with Polarization Detection during the HALO-AC³ campaign in March and April 2022 with the Polar 6 Aircraft out of Longyearbyen, Svalbard. The dataset contains two kinds of data. Data to which no inversion procedure has been applied and data to which the inversion procedure has been applied. The inversion procedure is applied to account for an uneven intensity of the laser beam across the sample area and resulting undersizing effects. The inversion procedure has been discussed in Lucke et al. (2023) (doi.org/10.4271/2023-01-1485) and Beswick et al. (2014) (doi.org/10.5194/amt-7-1443-2014). All quantities which carry the suffix inv are based on the inverted data, all other properties are not. It should be noted, that the necessity of the inversion procedure remains unclear (see the previously mentioned publications). The inversion procedure could only be applied when more than 2000 particles were present over a 5 second interval. When this was not the case, the inverted data are 9999.999. The inverted data are therefore also computed from a 5s rolling average. The measurements of the BCPD are likely severely influenced by inertial separation effects, due to the proximity of the BCPD sample area to the fuselage (approx. 3cm). When ice particles are present, shattering occurs on the fuselage and artificially increases the ice number concentration. The number of ice and liquid particles listed in this data set can be useful for assessing the presence of ice and liquid particles. To estimate the number of liquid and ice particles more than 100 particles are required over a 5s interval. When this is not the case, the data are 9999.999. The number of ice and liquid particles were computed as rolling averages over 5s intervals. The sample area in case no inversion procedure is applied is 0.273 square millimeters.

Description: During the HALO-(AC)³ campaign performed in March/April 2022, broadband solar and thermal-infrared irradiances in the vicinity of Svalbard were measured by pairs of CMP22 (0.2-3.6 µm) and CGR4 (4.5-42 µm) radiometers (Kipp&Zonen), respectively, onboard Polar 5 and Polar 6. The data set contains time series of both upward and downward solar and thermal-infrared irradiances obtained during in total 26 research flights (13 with each aircraft). All irradiances were corrected for instrument inertia (Ehrlich and Wendisch, 2015), the solar downward irradiance additionally for the aircraft attitude (Bannehr and Schwiesow, 1993). Since the latter correction is only valid for cloud-free conditions dominated by direct illumination, both a corrected and an uncorrected version are given. A rough cloud flag is included in the data set to distinguish between situations dominated by direct and diffuse illumination. To avoid too large uncertainties, the attitude flag can be used to filter situations with aircraft attitude angles (roll, pitch) exceeding 5°. Additionally, obvious icing and large temperature gradients, which disturb the thermal equilibrium between sensor and instrument body, are flagged. The data set further contains the solar downward irradiance simulated for cloud-free conditions and the upward brightness temperature measured by the KT-19 infrared thermometer (HEITRONICS, 9.6-11.5 µm).