Discriminating Between Different Streamflow Regimes by Using the Fisher-Shan Method: An Application to the Colombia Rivers

The Fisher-Shannon (FS) information plane, defined by the Fisher information measure (FIM) and the Shannon entropy power (N_X), was robustly used to investigate the complex dynamics of eight monthly streamflow time series in Colombia. In the FS plane the streamflow series seem to aggregate into two different clusters corresponding to two different climatological regimes in Colombia. Our findings suggest the use of the statistical quantity defined by the FS information plane as a tool to discriminate among different hydrological regimes.     

Comparing seismicity declustering techniques by means of the joint use of Allan Factor and Morisita index

In this paper, we propose to compare different declustering methods on the basis of the time-correlation and the space-clustering of the residual earthquake catalog after the declustering techniques have been applied. To this aim, we applied two point process clustering measures, the Allan Factor and the Morisita Index, for the identification and quantification of temporal correlation and spatial clustering in point processes, respectively. We used our joint space–time approach to study the earthquake space–time point processes of southern California and Switzerland with surrounding area, declustered by using the method of Gardner and Knopoff (with Grünthal and Uhmhammer window) and that of Reasenberg (with different setting parameters). Our results show that the residual declustered catalog is still characterized by time-correlated structures at long timescales; however, the cutoff timescale that is the lowest timescale above which the time-correlation is visible is higher with the Reasenberg method while is smaller with the Gardner and Knopoff method with Grünthal window. The space-clustering analysis performed by means of the Morisita Index suggests that the declustering technique effectively reduces the spatial clustering of the seismicity of Switzerland, but does not change the spatial properties of the residual seismic catalogue of the southern California.     

Examining deforestation and agropasture dynamics along the Brazilian TransAmazon Highway using multitemporal Landsat imagery

This research aims to understand the difference of major land-cover change results caused in various time periods and to examine the impacts of human-induced factors on land-cover changes along the TransAmazon Highway region. The Landsat Thematic Mapper and Operational Land Imager data from 2011, 2014, and 2017 and our previous land-cover classification results in 1991, 2000, and 2008 were used to examine land-cover dynamics. A classification system consisting of five land-cover classes – primary forest (PF), secondary forest (SF), agropasture (AP), urban area, and water – were chosen. The hierarchical-based classification method was used to generate land-cover classification results, and the post-classification comparison approach was used to produce detailed “from-to” conversions for each detection period. The emphasis was on deforestation of PF, dynamic change of SF and AP, and urbanization over time. The impacts of human-induced factors such as population and economic conditions on urban expansion, AP expansion, and deforestation were examined. This research indicated that selection of a suitable time period was critical for effectively detecting land-cover changes; that is, too long time period (i.e., 9 years) cannot accurately capture some land-cover changes such as the AP and SF in this research. Although deforestation – the conversion from PF to SF and AP – accounted for a large proportion of land-cover changes, the changes between SF and AP became more important than PF conversion, and required a short time period (i.e., 3 years here) for effectively reflecting their dynamics. Human-induced factors play important roles in deforestation, dynamic changes between AP and SF, and urbanization.     

Region-based classification of PolSAR data using radial basis kernel functions with stochastic distances

Region-based classification of PolSAR data can be effectively performed by seeking for the assignment that minimizes a distance between prototypes and segments. Silva et al. [“Classification of segments in PolSAR imagery by minimum stochastic distances between wishart distributions.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 6 (3): 1263–1273] used stochastic distances between complex multivariate Wishart models which, differently from other measures, are computationally tractable. In this work we assess the robustness of such approach with respect to errors in the training stage, and propose an extension that alleviates such problems. We introduce robustness in the process by incorporating a combination of radial basis kernel functions and stochastic distances with Support Vector Machines (SVM). We consider several stochastic distances between Wishart: Bhatacharyya, Kullback-Leibler, Chi-Square, Rényi, and Hellinger. We perform two case studies with PolSAR images, both simulated and from actual sensors, and different classification scenarios to compare the performance of Minimum Distance and SVM classification frameworks. With this, we model the situation of imperfect training samples. We show that SVM with the proposed kernel functions achieves better performance with respect to Minimum Distance, at the expense of more computational resources and the need of parameter tuning. Code and data are provided for reproducibility.     

Pumpellyite in low-grade metamorphic rocks from Ligurian and Lucanian Apennines,Maritime Alps and Calabria (Italy)

In the Ligurian Apennines and the Brianzonese area of the Maritime Alps (Northern Italy), and in the Lucanian Apennines and Calabria (Southern Italy), pumpellyite formed during the Alpine metamorphism is widespread in terranes of Late Paleozoic to Miocene age, particularly in mafic ophiolites (Tethyan ophiolites of Jurassic-Early Cretaceous age).Pumpellyite developed under variable metamorphic conditions, which include zeolite, prehnite-pumpellyite, pumpellyite-actinolite, lawsonite-albite and blueschist facies. Pumpellyite from rocks belonging to all these facies was studied in 30 specimens of different chemistry, derived mostly from ophiolitic basalt and gabbro, but also from gneiss, amphibolite, and greywacke protoliths.Microprobe data give evidence of strong compositional variations of pumpellyite. The ranges are extreme for Al and Fe^tot (Al₂O₃=18.74–30.91; FeO_tot=0.46–12.71), to a lesser extent for Mg (MgO=0.58–4.00), with a reciprocal variation of Al and Fe^tot which suggests that most Fe is Fe³⁺.Pumpellyite compositions can be related with the metamorphic conditions, particularly an increase of the Al/Fe^tot ratio with increasing pressure, but larger compositional variation for each facies in the Al-Fe^tot-Mg diagram than those previously described was recognized. Particularly the compositions of pumpellyite from the pumpellyite-actinolite and blueschist fades assemblages extend towards higher Fe^tot contents. Moreover, pumpellyites of the lawsonite-albite facies rocks result to be more aluminous than in blueschist facies; such relations appear to be inconsistent with that expected by the effects of pressure on the Al content.As the rocks are generally incompletely re-equilibrated, their bulk chemistry is not an important factor of pumpellyite composition; in fact the correlations of Al, Fe^tot and Mg are low. The local environment of crystallization, more evidently the composition of the precursor minerals, seems to be a major controlling factor. The observed topologic relations indicate that either the nature of the precursor mineral, or the presence of relict phases have a great influence on the pumpellyite composition. The observed variations within individual specimens, as well as the interspecimen ones, can be explained by small-scale inhomogeneities and in some cases by differences in the activity of O₂.It can be therefore concluded that the composition of pumpellyite often reflects disequilibrium crystallization and cannot be generally used as an indicator of metamorphic conditions.     

Seismological constraints on the 2018 Mt. Etna (Italy) flank eruption and implications for the flank dynamics of the volcano

3D earthquake locations, focal mechanisms and stress tensor distribution in a 16‐month interval covering the 2018 Mt. Etna flank eruption, enabled us to investigate the relationship between magma intrusion and structural response of the volcano and shed light on the dynamic processes affecting the instability of Mt. Etna. The magma intrusion likely caused tension in the flanks of the volcano, leading to significant ground deformation and redistribution of stress on the neighbouring faults at the edge of Mt. Etna's unstable sector, encouraging the ESE sliding of the eastern flank of the volcano. Accordingly, FPSs of the post‐eruptive events show strike slip faulting mechanisms, under a stress regime characterized by a maximum compressive σ₁, NE‐SW oriented. In this perspective, any flank eruption could temporarily enhance the sliding process of both the southern and eastern flanks of the volcano.     

“Galileo Galilei” (GG) a small satellite to test the equivalence principle of Galileo, Newton and Einstein

“Galileo Galilei” (GG) is a small satellite designed to fly in low Earth orbit with the goal of testing the Equivalence Principle—which is at the basis of the General Theory of Relativity—to 1 part in 10¹⁷. If successful, it would improve current laboratory results by 4 orders of magnitude. A confirmation would strongly constrain theories; proof of violation is believed to lead to a scientific revolution. The experiment design allows it to be carried out at ambient temperature inside a small 1-axis stabilized satellite (250 kg total mass). GG is under investigation at Phase A-2 level by ASI (Agenzia Spaziale Italiana) at Thales Alenia Space in Torino, while a laboratory prototype (known as GGG) is operational at INFN laboratories in Pisa, supported by INFN (Istituto Nazionale di fisica Nucleare) and ASI. A final study report will be published in 2009.     

Community structure and dynamics in climate networks

We consider climate networks constructed from observed and model simulated fields of three climate variables and investigate their community structure. We find that for all fields the number of effective communities is rather small (four to five). We are able to trace the origin of these communities to certain dynamical properties of climate. Our results suggest that the complete complexity of the climate system condenses beyond the ??weather?? time scales into a small number of low-dimensional interacting components and provide clues as to the nature of the climate subsystems underlying these components.