Potentials of TanDEM-X Interferometric Data for Global Forest/Non-Forest Classification

This paper presents a method to generate forest/nonforest maps from TanDEM-X interferometric SAR data. Among the several contributions which may affect the quality of interferometric products, the coherence loss caused by volume scattering represents the contribution which is predominantly affected by the presence of vegetation, and is therefore here exploited as main indicator for forest classification. Due to the strong dependency of the considered InSAR quantity on the geometric acquisition configuration, namely the incidence angle and the interferometric baseline, a multi-fuzzy clustering classification approach is used. Some examples are provided which show the potential of the proposed method. Further, additional features such as urban settlements, water, and critical areas affected by geometrical distortions (e.g. shadow and layover) need to be extracted, and possible approaches are presented as well. Very promising results are shown, which demonstrate the potentials of TanDEM-X bistatic data not only for forest identification, but, more in general, for the generation of a global land classification map as a next step

Editorial for the Special Issue "SAR for Forest Mapping II"

First Paragraph: As vital natural resources, forests are of extreme importance for all living beings on our planet. They play a key role in controlling climate change; represent essential sources of energy (e.g., biomass), food, jobs, and livelihoods; and serve as a natural habitat to a large variety of animal species, which is essential for biodiversity preservation. Forest ecosystems are constantly shaped and changed by physical and biological disturbances, and eventual regeneration processes. As an example, forest degradation is currently occurring at an alarming rate, and it often occurs due to illegal anthropogenic activities such as logging and fires. Sensitive environments have been irreversibly damaged, with critical environmental and economic consequences at regional as well as global scales. Precise and efficient assessment and monitoring of forest resources, treatments, and recreational opportunities are therefore of crucial importance in order to develop early warning systems. In this scenario, synthetic aperture radar (SAR) remote sensing represents a unique technique to provide high-resolution images independently of daylight and in almost any weather conditions. In the past few decades, SAR imaging has demonstrated its suitability for forest mapping applications. The combination of polarimetric, interferometric, and/or tomographic information further increases its capabilities and its products’ accuracy

The Characteristic Dimension of Four-dimensional N=2\mathcal{N} = 2 SCFTs

In this paper we introduce the characteristic dimension of a four dimensional $\mathcal{N}=2$ superconformal field theory, which is an extraordinary simple invariant determined by the scaling dimensions of its Coulomb branch operators. We prove that only nine values of the characteristic dimension are allowed, $-\infty$, 1 ,6/5, 4/3, 3/2, 2, 3, 4, and 6, thus giving a new organizing principle to the vast landscape of 4d $\mathcal N=2$ SCFTs. Whenever the characteristic dimension differs from 1 or 2, only very constrained special K\"ahler geometries (i.e. isotrivial, diagonal and rigid) are compatible with the corresponding set of Coulomb branch dimensions and extremely special, maximally strongly coupled, BPS spectra are allowed for the theories which realize them. Our discussion applies to superconformal field theories of arbitrary rank, i.e. with Coulomb branches of any complex dimension. Along the way, we predict the existence of new $\mathcal{N}=3$ theories of rank two with non-trivial one-form symmetries.Comment: 23 pages, 3 table

Aggregates of Chemically Functionalized Multiwalled Carbon Nanotubes as Viscosity Reducers

Confinement and surface effects provided by nanoparticles have been shown to produce changes in polymer molecules affecting their macroscopic viscosity. Nanoparticles may induce rearrangements in polymer conformation with an increase in free volume significantly lowering the viscosity. This phenomenon is generally attributed to the selective adsorption of the polymer high molar mass fraction onto nanoparticles surface when the polymer radius of gyration is comparable to the nanoparticles characteristic dimensions. Carbon nanotubes seem to be the ideal candidate to induce viscosity reduction of polymer due to both their high surface-to-volume ratio and their nanometric sizes, comparable to the gyration radius of polymer chains. However, the amount of nanotube in a polymer system is limited by the percolation threshold as, above this limit, the formation of a nanotubes network hinders the viscosity reduction effect. Based on these findings, we have used multiwalled carbon nanotubes MWCNT “aggregates” as viscosity reducers. Our results reveal both that the use of nanotube clusters reduce significantly the viscosity of the final system and strongly increase the nanotube limiting concentration for viscosity hindering. By using hydroxyl and carboxyl functionalized nanotubes, this effect has been rather maximized likely due to the hydrogen bridged stabilization of nanotube aggregates

Performance-Optimized Quantization for SAR and InSAR Applications

For the design of present and next-generation spaceborne SAR missions, constantly increasing data rates are being demanded, which impose stringent requirements in terms of onboard memory and downlink capacity. In this scenario, the efficient quantization of SAR raw data is of primary importance since the utilized compression rate is directly related to the volume of data to be stored and transmitted to the ground, and at the same time, it affects the resulting SAR imaging performance. In this article, we introduce the performance-optimized block-adaptive quantization (PO-BAQ), a novel approach for SAR raw data compression that aims at optimizing the resource allocation and, at the same time, the quality of the resulting SAR and InSAR products. This goal is achieved by exploiting the a priori knowledge of the local SAR backscatter statistics, which allows for the generation of high-resolution bitrate maps that can be employed to fulfill a predefined performance requirement. Analyses of experimental TanDEM-X interferometric data are presented, which demonstrates the potential of the proposed method as a helpful tool for performance budget definition and data rate optimization of present and future SAR missions

Automating Data Layout Conversion in a Large Cosmological Simulation Code

International audienc

Generation of Global Backscatter Maps for Future SAR Missions Design

The generation of global backscatter maps allows for the exploitation of a priori knowledge of local synthetic aperture radar (SAR) backscatter statistics. SAR backscatter maps can be used for accurate performance prediction and for the optimization of instrument settings for present and future SAR systems. Also, many further SAR applications can benefit from the availability of backscatter maps in order to monitor the backscatter evolution in time and to investigate the radar reflectivity behaviour depending on sensor parameters and target properties. In this work, X-band backscatter maps are generated by mosaicking images acquired by the TerraSAR-X (TSM) and the TanDEM-X (TDM) missions at global scale. The correction models used for the characterization of backscatter behaviour are based on the database provided by Ulaby and are here presented for HH polarization and for any required reference incidence angle. As an example of application for future SAR missions design, a novel performance-optimized block-adaptive quantization (PO-BAQ), coming from the need of optimizing the resource allocation of the state-of-the-art quantization algorithms for SAR systems, is then considered. The methodology relies on global backscatter statistics for the generation of bitrate maps, which can provide a helpful information for performance budget definition and for optimizing resource allocation. strategie

Lavoro agile e smart working nella società post-pandemica. Profili giuslavoristici e di relazioni industriali

Il volume analizza, da una prospettiva giuslavoristica e di relazioni industriali, la tematica del lavoro agile e dello smart working con riferimento ai diversi profili di interesse di tale modalità di lavoro che è, al contempo, progetto organizzativo-manageriale del datore di lavoro, progetto di vita individuale della lavoratrice e del lavoratore e progetto politico di organizzazione della società. Attraverso l’analisi del quadro normativo e della prassi contrattual-collettiva, i contributi raccolti nel volume offrono nuove prospettive e nuove soluzioni per interpretare i processi di trasformazione del lavoro da remoto e conformarne gli effetti sul fronte individuale, collettivo e sociale, verso un adeguato bilanciamento degli interessi in gioco

Monitoring of self-healing composites: a nonlinear ultrasound approach

Self-healing composites using a thermally mendable polymer, based on Diels–Alder reaction were fabricated and subjected to various multiple damage loads. Unlike traditional destructive methods, this work presents a nonlinear ultrasound technique to evaluate the structural recovery of the proposed self-healing laminate structures. The results were compared to computer tomography and linear ultrasound methods. The laminates were subjected to multiple loading and healing cycles and the induced damage and recovery at each stage was evaluated. The results highlight the benefit and added advantage of using a nonlinear based methodology to monitor the structural recovery of reversibly cross-linked epoxy with efficient recycling and multiple self-healing capability