Quantifying rapid permafrost thaw with computer vision and graph theory

With the Earth’s climate rapidly warming, the Arctic represents one of the most vulnerable regions to environmental change. Permafrost, as a key element of the Arctic system, stores vast amounts of organic carbon that can be microbially decomposed into the greenhouse gases CO2 and CH4 upon thaw. Extensive thawing of these permafrost soils therefore has potentially substantial consequences to greenhouse gas concentrations in the atmosphere. In addition, thaw of ice-rich permafrost lastingly alters the surface topography and thus the hydrology. Fires represent an important disturbance in boreal permafrost regions and increasingly also in tundra regions as they combust the vegetation and upper organic soil layers that usually provide protective insulation to the permafrost below. Field studies and local remote sensing studies suggest that fire disturbances may trigger rapid permafrost thaw, with consequences often already observable in the first years post-disturbance. In polygonal ice-wedge landscapes, this becomes most prevalent through melting ice wedges and degrading troughs. The further these ice wedges degrade; the more troughs will likely connect and build an extensive hydrological network with changing patterns and degrees of connectivity that influences hydrology and runoff throughout large regions. While subsiding troughs over melting ice wedges may host new ponds, an increasing connectivity may also subsequently lead to more drainage of ponds, which in turn can limit further thaw and help stabilize the landscape. Whereas fire disturbances may accelerate the initiation of this process, the general warming of permafrost observed across the Arctic will eventually result in widespread degradation of polygonal landscapes. To quantify the changes in such dynamic landscapes over large regions, remote sensing data offers a valuable resource. However, considering the vast and ever-growing volumes of Earth observation data available, highly automated methods are needed that allow extracting information on the geomorphic state and changes over time of ice-wedge trough networks. In this study, we investigate these changing landscapes and their environmental implications in fire scars in Northern and Western Alaska. We developed a computer vision algorithm to automatically extract ice-wedge polygonal networks and the microtopography of the degrading troughs from high-resolution, airborne laserscanning-based digital terrain models (1 m spatial resolution; full-waveform Riegl Q680i LiDAR sensor). To derive information on the availability of surface water, we used optical and near-infrared aerial imagery at spatial resolutions of up to 5 cm captured by the Modular Aerial Camera System (MACS) developed by DLR. We represent the networks as graphs (a concept from the computer sciences to describe complex networks) and apply methods from graph theory to describe and quantify hydrological network characteristics of the changing landscape. Due to a lack of historical very-high-resolution data, we cannot investigate a dense time series of a single representative study area on the evolution of the microtopographic and hydrologic network, but rather leverage the possibilities of a space-for-time substitution. We thus investigate terrain models and multispectral data from 2019 and 2021 of ten study areas located in ten fire scars of different ages (up to 120 years between date of disturbance and date of data acquisition). With this approach, we can infer past and future states of degradation from the currently prevailing spatial patterns and show how this type of disturbed landscape evolves over time. Representing such polygonal landscapes as graphs and reducing large amounts of data into few quantifiable metrics, supports integration of results into i.e., numerical models and thus largely facilitates the understanding of the underlying complex processes of GHG emissions from permafrost thaw. We highlight these extensive possibilities but also illustrate the limitations encountered in the study that stem from a reduced availability and accessibility to pan-Arctic very-high-resolution Earth observation datasets

A Quantitative Graph-Based Approach to Monitoring Ice-Wedge Trough Dynamics in Polygonal Permafrost Landscapes

In response to increasing Arctic temperatures, ice-rich permafrost landscapes are undergoing rapid changes. In permafrost lowlands, polygonal ice wedges are especially prone to degradation. Melting of ice wedges results in deepening troughs and the transition from low-centered to high-centered ice-wedge polygons. This process has important implications for surface hydrology, as the connectivity of such troughs determines the rate of drainage for these lowland landscapes. In this study, we present a comprehensive, modular, and highly automated workflow to extract, to represent, and to analyze remotely sensed ice-wedge polygonal trough networks as a graph (i.e., network structure). With computer vision methods, we efficiently extract the trough locations as well as their geomorphometric information on trough depth and width from high-resolution digital elevation models and link these data within the graph. Further, we present and discuss the benefits of graph analysis algorithms for characterizing the erosional development of such thaw-affected landscapes. Based on our graph analysis, we show how thaw subsidence has progressed between 2009 and 2019 following burning at the Anaktuvuk River fire scar in northern Alaska, USA. We observed a considerable increase in the number of discernible troughs within the study area, while simultaneously the number of disconnected networks decreased from 54 small networks in 2009 to only six considerably larger disconnected networks in 2019. On average, the width of the troughs has increased by 13.86%, while the average depth has slightly decreased by 10.31%. Overall, our new automated approach allows for monitoring ice-wedge dynamics in unprecedented spatial detail, while simultaneously reducing the data to quantifiable geometric measures and spatial relationships.BMBF PermaRiskNational Science FoundationPeer Reviewe

From Images to Hydrologic Networks - Understanding the Arctic Landscape with Graphs

Remote sensing-based Earth Observation plays an important role in assessing environmental changes throughout our planet. As an image-heavy domain, the evaluation of the data strongly focuses on statistical and pixel-based spatial analysis methods. However, considering the complexity of our Earth system, there are some environmental structures and dependencies that are not possible to accurately describe with these traditional image analysis approaches. One example for such a limitation is the representation of (spatial) networks and their characteristics. In this study, we thus propose a computer vision approach that enables the representation of semantic information gained from images as graphs. As an example, we investigate digital terrain models of Arctic permafrost landscapes with its very characteristic polygonal patterned ground. These regular patterns, which are clearly visible in high-resolution image and elevation data, are formed by subsurface ice bodies that are very vulnerable to rising temperatures in a warming Arctic. Observing these networks’ topologies and metrics in space and time with graph analysis thus allows insights into the landscape’s complex geomorphology, hydrology, and ecology and therefore helps to quantify how they interact with climate change. We show that results extracted with this analytical and highly automated approach are in line with those gathered from other manual studies or from manual validation. Thus, with this approach, we introduce a method that, for the first time, enables upscaling of such terrain and network analysis to potentially pan-Arctic scales where collecting in-situ field data is strongly limited

Research of the Power Plant Operational Modes

In this article the algorithm of the power plant operational modes research is offered. According to this algorithm the program for the modes analysis and connection power transformers choice is developed. The program can be used as educational means for studying of the power plant electric part, at the same time basic data are provided. Also the program can be used for the analysis of the working power plants modes. Checks of the entered data completeness and a choice correctness of the operational modes are provided in the program; in all cases of a deviation from the correct decisions to the user the relevant information is given

Magnetohydrodynamic Enhanced Entry System for Space Transportation (MEESST) as a Key Building Block for Future Exploration Missions

Aside from the launch environment, atmospheric re-entry imposes one of the most demanding environments which a spacecraft can experience. The combination of high spacecraft velocity and the presence of atmospheric particles leads to partially ionised gas forming around the vehicle, which significantly inhibits radio communications, and leads to the generation of high thermal loads on the spacecraft surface. Currently, the latter is solved using expensive, heavy, and often expendable thermal protection systems (TPS). The use of electromagnetic fields to exploit Magnetohydrodynamic (MHD) principles has long been considered as an attractive solution for this problem. By displacing the ionised gas away from the spacecraft, the thermal loads can be reduced, while also opening a magnetic window for radio waves, mitigating the blackout phenomenon. The application of this concept has to date not been possible due to the large magnetic fields required, which would necessitate the use of exceptionally massive and power-hungry copper coils. High Temperature Superconductors (HTS) have now reached industrial maturity. HTS coils can now offer the necessary low weight and compactness required for space applications. The MEESST consortium the has been awarded a grant from the EU Horizon 2020 programme for the development and demonstration of a novel HTS-based re-entry system based with its foundation on MHD principles. The project will first harmonize existing numerical codes, and then design, manufacture, and test a HTS magnet. The study shows that the use of MEESST technology can have a positive impact on the cost-effectiveness and available payload of interplanetary missions

Electrochemical study of gold recovery from ammoniacal thiosulfate, simulating the PCBs leaching of mobile phones

[EN] The high volume of sales and the high degree of obsolescence of mobile phones, together with the reduction of the natural reserves of the metals used in the composition of their printed circuit boards (PCBs), makes the recycling of these devices economically and environmentally attractive. Moreover, the search for the reduction of toxicity levels inherent to the gold leaching processes with alternatives to cyanide, such as thiosulfate is a priority. Thus, it is necessary to search for efficient alternatives for the recovery of gold from solutions containing thiosulfate, in the presence of copper, used in the leaching of PCBs of mobile phones. One of these alternatives could be the electrochemical recovery of the metals present in solution. Thus, this study aimed to verify some variables involved in the process of recovery of gold and copper and to determine the electrochemical yield obtained for these solutions. Initially, cyclic scanning voltammetry with a rotating disk electrode (RDE) was performed to verify the electrochemical behavior of gold and copper in solution. Then, electrowinning tests were used to determine the recovery rates of these metals and to calculate the yield obtained in the process. The results showed that this electrochemical reaction is mass transport controlled, which allowed the calculation of the diffusion coefficients of the metal in solution. In real solutions, the gold fraction recovered reached a 94%, and the copper fraction recovered was 95%, applying electrode potential values of -500 mV(Ag/AgCl) and -700 mV(Ag/AgCl), respectively. The current efficiency for the gold electrowinning achieved in the experiments was lower than 3%. (c) 2017 Elsevier Ltd. All rights reserved.The authors would like to thank the Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES) and Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq) from Brazil for financial support.Kasper, AC.; Veit, HM.; García Gabaldón, M.; Pérez-Herranz, V. (2018). Electrochemical study of gold recovery from ammoniacal thiosulfate, simulating the PCBs leaching of mobile phones. Electrochimica Acta. 259:500-509. https://doi.org/10.1016/j.electacta.2017.10.161S50050925

Chemical Solution Deposition of Insulating Yttria Nanolayers as Current Flow Diverter in Superconducting GdBa2Cu3O7-δ Coated Conductors

The primary benefit of a metallic stabilization/shunt in high temperature superconductor (HTS) coated conductors (CCs) is to prevent joule heating damage by providing an alternative path for the current flow during the HTS normal state transition (i.e., quench). However, the shunt presence in combination with unavoidable fluctuations in the critical current (I c) of the HTS film can develop a localized quench along the CC's length if the operational current is kept close to I c. This scenario, also known as the hot-spot regime, can lead to the rupture of the CC if the local quench does not propagate fast enough. The current flow diverter (CFD) is the CC architecture concept that has proven to increase the conductor's robustness against a hot-spot regime by simply boosting the quench velocity in the CC, which avoids the shunt compromise in some applications. This work investigates a practical manufacturing route for incorporating the CFD architecture in a reel-to-reel system via the preparation of yttrium oxide (Y2O3) as an insulating thin nanolayer (∼100 nm) on top of a GdBa2Cu3O7 (GdBCO) superconductor. Chemical solution deposition (CSD) using ink jet printing (IJP) is shown to be a suitable manufacturing approach. Two sequences of the experimental steps have been investigated, where oxygenation of the GdBCO layer is performed after or before the solution deposition and the Y2O3 nanolayer thermal treatment formation step. A correlated analysis of the microstructure, in situ oxygenation kinetics, and superconducting properties of the Ag/Y2O3/GdBCO trilayer processed under different conditions shows that a new customized functional CC can be prepared. The successful achievement of the CFD effect in the case of the preoxygenated customized CC was confirmed by measuring the current transfer length, thus demonstrating the effectiveness of the CSD-IJP as a processing method.We acknowledge the funding of this research by FASTGRID Project (EU-H2020, 721019); the Projects COACHSUPENERGY (MAT2014-51778-C2-1-R) and SUMATE (RTI2018-095853-BC21 and RTI2018-095853-B-C22) from the Spanish Ministry of Economy and Competitiveness, which were cofunded by the European Regional Development Fund; and the Project 2017-SGR 753 from Generalitat de Catalunya and the COST Action NANOCOHYBRI (CA16218). ICMAB authors also acknowledge the Center of Excellence awards Severo Ochoa SEV-2015-0496 and CEX2019-000917-SWith funding from the Spanish government through the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000917-S).Peer reviewe

Airborne LiDAR and stereo-photogrammetric characterization of permafrost landscapes and thaw subsidence

Rapid climate change in the northern high latitudes has a strong impact on permafrost stability, apparent as coastal erosion, subsidence, or lake dynamics with potentially severe consequences for local communities and ecology. In a rapidly warming Arctic, the monitoring of these processes is essential to understand and predict permafrost dynamics over the upcoming decades. These landscape dynamics are highly diverse, localized, but widely distributed and require datasets with very high spatial resolution, which are barely achieved by satellite data alone. Repeat observations over several years allow for unprecedented insights into highly critical landscape dynamics and the potential integration with and validation of more coarse resolution satellite data. AWI’s research aircraft (Polar-5 and Polar-6) were equipped with airborne LiDAR (full-waveform, multi-echo) as well with experimental modular sensors such as the DLR-developed multi-spectral optical Modular Airborne Camera System (MACS) with a spatial resolution of few cm, stereo capabilities and a very broad radiometric range. The incoming data stream of acquired laser return point cloud data as well as hundreds of thousands of high-resolution images for individual campaigns poses new challenges of handling and processing large data volumes. Here we present an overview about past and upcoming flight campaigns in Alaska and northwestern Canada. Furthermore, we will show applications of the acquired datasets, such as assessments of subsidence, coastal erosion or infrastructure development

Expression of the Phosphatase Ppef2 Controls Survival and Function of CD8+ Dendritic Cells

Apoptotic cell death of Dendritic cells (DCs) is critical for immune homeostasis. Although intrinsic mechanisms controlling DC death have not been fully characterized up to now, experimentally enforced inhibition of DC-death causes various autoimmune diseases in model systems. We have generated mice deficient for Protein Phosphatase with EF-Hands 2 (Ppef2), which is selectively expressed in CD8+ DCs, but not in other related DC subtypes such as tissue CD103+ DCs. Ppef2 is down-regulated rapidly upon maturation of DCs by toll-like receptor stimuli, but not upon triggering of CD40. Ppef2-deficient CD8+ DCs accumulate the pro-apoptotic Bcl-2-like protein 11 (Bim) and show increased apoptosis and reduced competitve repopulation capacities. Furthermore, Ppef2−/− CD8+ DCs have strongly diminished antigen presentation capacities in vivo, as CD8+ T cells primed by Ppef2−/− CD8+ DCs undergo reduced expansion. In conclusion, our data suggests that Ppef2 is crucial to support survival of immature CD8+ DCs, while Ppef2 down-regulation during DC-maturation limits T cell responses