530 research outputs found
Assessment of the P- and L-band SAR tomography for the characterization of tropical forests
No full textInferring the diameter of a biopolymer from its stretching response
No full textWe investigate the stretching response of a thick polymer model by means of extensive stochastic simulations. The computational results are synthesized in an analytic expression that characterizes how the force versus elongation curve depends on the polymer structural parameters: its thickness and granularity (spacing of the monomers). The expression is used to analyze experimental data for the stretching of various different types of biopolymers: polypeptides, polysaccharides, and nucleic acids. Besides recovering elastic parameters (such as the persistence length) that are consistent with those obtained from standard entropic models, the approach allows us to extract viable estimates for the polymers diameter and granularity. This shows that the basic structural polymer features have such a profound impact on the elastic behavior that they can be recovered with the sole input of stretching measurements
Temporal decorrelation in tropical forest: results from TropiScat and implications for BIOMASS tomography
No full textPOLARIMETRIC SAR TOMOGRAPHY FOR THE CHARACTERIZATION OF FORESTED AREAS
No full textPolarimetric Synthetic Aperture Radar Tomography (TomoSAR) is a technology to image the three-dimensional (3D) structure of the illuminated media. TomoSAR exploits the key feature of microwaves to penetrate into vegetation, snow, and ice, hence providing the possibility to see features that are hidden to optical and hyper-spectral systems. Several experimental studies by different research groups demonstrate that the use of the 3D information results in an accurate characterization of forested areas, providing access to a number of biophysical variables such as terrain topography below the vegetation, forest height, forest Above Ground Biomass (AGB), and forest classification. This paper is intended to provide the reader with an introduction to the use of TomoSAR for the characterization of forest areas, addressing basic imaging principles and methods, retrieval of biophysical parameters, and perspective for spaceborne missions
COVID-19 and Tail-event Driven Network Risk in the Eurozone
No full textThis paper analyses tail risk spillover, considering interaction of the 46 largest capitalization firms in the Eurozone over the period 9 January 2006 to 28 December 2020 (including part of the COVID-19 era). Employing the Tail-Event driven NETwork (TENET) model, our findings identify insights about the risk sender and receiver in interrelationships of systemic risk beyond contemporaneous total spillover effects. First, total connectedness surged and peaked in the early months of 2020, relative to previous crises. Second, industrial manufacturing and consumer products have a high degree of risk transmission. Third, we determine the predictive indicators of spillover risk. Finally, our results hold several policy implications
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