Ocean Eddy Identification and Tracking using Neural Networks

Global climate change plays an essential role in our daily life. Mesoscale ocean eddies have a significant impact on global warming, since they affect the ocean dynamics, the energy as well as the mass transports of ocean circulation. From satellite altimetry we can derive high-resolution, global maps containing ocean signals with dominating coherent eddy structures. The aim of this study is the development and evaluation of a deep-learning based approach for the analysis of eddies. In detail, we develop an eddy identification and tracking framework with two different approaches that are mainly based on feature learning with convolutional neural networks. Furthermore, state-of-the-art image processing tools and object tracking methods are used to support the eddy tracking. In contrast to previous methods, our framework is able to learn a representation of the data in which eddies can be detected and tracked in more objective and robust way. We show the detection and tracking results on sea level anomalies (SLA) data from the area of Australia and the East Australia current, and compare our two eddy detection and tracking approaches to identify the most robust and objective method.Comment: accepted for International Geoscience and Remote Sensing Symposium 201

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Quasi‐freestanding graphene on SiC(0001) by Ar‐mediated intercalation of antimony: a route toward intercalation of high‐vapor‐pressure elements

A novel strategy for the intercalation of antimony (Sb) under the (6√3×6√3)\u1d44530° reconstruction, also known as buffer layer, on SiC(0001) is reported. Using X‐ray photoelectron spectroscopy, low‐energy electron diffraction, and angle‐resolved photoelectron spectroscopy, it is demonstrated that, while the intercalation of the volatile Sb is not possible by annealing the Sb‐coated buffer layer in ultrahigh vacuum, it can be achieved by annealing the sample in an atmosphere of Ar, which suppresses Sb desorption. The intercalation leads to a decoupling of the buffer layer from the SiC(0001) surface and the formation of quasi‐freestanding graphene. The intercalation process paves the way for future studies of the formation of quasi‐freestanding graphene by intercalation of high‐vapor‐pressure elements, which are not accessible by previously known intercalation techniques, and thus provides new avenues for the manipulation of epitaxial graphene on SiC