Monitoring soil erosion in the Souss basin, Morocco, with a multiscale object-based remote sensing approach using UAV and satellite data

This article presents a multiscale approach for detecting and monitoring soil erosion phenomena (i.e. gully erosion) in the agro-industrial area around the city of Taroudannt, Souss basin, Morocco. The study area is characterized as semi-arid with an annual average precipitation of 200 mm. Water scarcity, high population dynamics and changing land use towards huge areas of irrigation farming present numerous threats to sustainability. The agro-industry produces citrus fruits and vegetables in monocropping, mainly for the European market. Badland areas strongly affected by gully erosion border the agricultural areas as well as residential areas. To counteract the significant loss of land, land-leveling measures are attempted to create space for plantations and greenhouses. In order to develop sustainable approaches to limit gully growth the detection and monitoring of gully systems is fundamental. Specific gully sites are monitored with unmanned aerial vehicle (UAV) taking small-format aerial photographs (SFAP). This enables extremely high-resolution analysis (SFAP resolution: 2-10 cm) of the actual size of the gully channels as well as a detailed continued surveillance of their growth. Transferring the methodology on a larger scale using Quickbird satellite data (resolution: 60 cm) leads to the possibility of a large-scale analysis of the whole area around the city of Taroudannt (Area extent: ca. 350 km²). The results will then reveal possible relationships of gully growth and agro-industrial management and may even illustrate further interdependencies. The main objective is the identification of areas with high gully-erosion risk due to non-sustainable land use and the development of mitigation strategies for the study area

Correlated disorder in myelinated axons orientational geometry and structure

While the ultrastructure of the myelin has been considered to be a quasi-crystalline stable system, nowadays its multiscale complex dynamics appears to play a key role for its functionality, degeneration and repair processes following neurological diseases and trauma. In this work, we have investigated the axons interactions associated to the nerve functionality, measuring the spatial distribution of the orientational fluctuations of axons in a Xenopus Laevis sciatic nerve. At this aim, we have used Scanning micro X-ray Diffraction (SmXRD), a non-invasive already applied to other heterogeneous systems presenting complex geometries from microscale to nanoscale. We have found that the orientational spatial fluctuations of fresh axons show a correlated disorder described by Levy flight distribution. Thus, we have studied how this correlated disorder evolves during the degeneration of the nerve. Our results show that the spatial distribution of axons orientational fluctuations in unfresh, aged nerve loose the correlated disorder assuming a randomly disordered behaviour. This work allows a deeper understanding of nerve states and paves the way to study other materials and biomaterials with the same technique to detect and to characterize their states and supramolecular structure, associated with dynamic structural changes at the nanoscale and mesoscale.Comment: 9 pages, 4 figure

Expanding Hardware-in-the-Loop Formation Navigation and Control with Radio Frequency Crosslink Ranging

The Formation Flying Testbed (FFTB) at the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) provides a hardware-in-the-loop test environment for formation navigation and control. The facility continues to evolve as a modular, hybrid, dynamic simulation facility for end-to-end guidance, navigation, and control (GN&C) design and analysis of formation flying spacecraft. The core capabilities of the FFTB, as a platform for testing critical hardware and software algorithms in-the-loop, are reviewed with a focus on recent improvements. With the most recent improvement, in support of Technology Readiness Level (TRL) 6 testing of the Inter-spacecraft Ranging and Alarm System (IRAS) for the Magnetospheric Multiscale (MMS) mission, the FFTB has significantly expanded its ability to perform realistic simulations that require Radio Frequency (RF) ranging sensors for relative navigation with the Path Emulator for RF Signals (PERFS). The PERFS, currently under development at NASA GSFC, modulates RF signals exchanged between spacecraft. The RF signals are modified to accurately reflect the dynamic environment through which they travel, including the effects of medium, moving platforms, and radiated power

Recurrent Scene Parsing with Perspective Understanding in the Loop

Objects may appear at arbitrary scales in perspective images of a scene, posing a challenge for recognition systems that process images at a fixed resolution. We propose a depth-aware gating module that adaptively selects the pooling field size in a convolutional network architecture according to the object scale (inversely proportional to the depth) so that small details are preserved for distant objects while larger receptive fields are used for those nearby. The depth gating signal is provided by stereo disparity or estimated directly from monocular input. We integrate this depth-aware gating into a recurrent convolutional neural network to perform semantic segmentation. Our recurrent module iteratively refines the segmentation results, leveraging the depth and semantic predictions from the previous iterations. Through extensive experiments on four popular large-scale RGB-D datasets, we demonstrate this approach achieves competitive semantic segmentation performance with a model which is substantially more compact. We carry out extensive analysis of this architecture including variants that operate on monocular RGB but use depth as side-information during training, unsupervised gating as a generic attentional mechanism, and multi-resolution gating. We find that gated pooling for joint semantic segmentation and depth yields state-of-the-art results for quantitative monocular depth estimation

Research and Education in Computational Science and Engineering

Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment alone is equipped to answer. CSE provides scientists and engineers of all persuasions with algorithmic inventions and software systems that transcend disciplines and scales. Carried on a wave of digital technology, CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society; and the CSE community is at the core of this transformation. However, a combination of disruptive developments---including the architectural complexity of extreme-scale computing, the data revolution that engulfs the planet, and the specialization required to follow the applications to new frontiers---is redefining the scope and reach of the CSE endeavor. This report describes the rapid expansion of CSE and the challenges to sustaining its bold advances. The report also presents strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie

Integrating nuclide specific and dose rate based methods for airborne and ground based gamma spectrometry

Results of joint airborne survey work conducted by SUERC and JAEA are presented, for areas to the north and south of Fukushima Daiichi using four different airborne survey systems, cross calibrated at reference sites in Scotland and near Namie. Airborne measurements were made at a series of different survey heights using three high volume NaI based spectrometers, and for the first time using a high resolution system based on the Ortec IDM HPGe spectrometer. The JAEA data sets were analysed using the same methods applied to national scale mapping in Japan since the accident. The SUERC data sets were analysed using nuclide specific approaches validated in the European ECCOMAGS project. The data presented on a digital terrain model show marked correspondence with landscape features, which both suggest the initial deposition processes, and indicate trajectories for future re-deposition by natural processes. All data sets are traceable to each other, and to the ground based calibration sites. Nuclide specific inventories have been defined, which can serve as a future reference to evaluate environmental change