311 research outputs found
Advances in Large-Scale Flood Monitoring and Detection
No full textThe last decades have seen a massive advance in technologies for Earth observation
(EO) and environmental monitoring, which provided scientists and engineers with valuable spatial
information for studying hydrologic processes. At the same time, the power of computers and newly
developed algorithms have grown sharply. Such advances have extended the range of possibilities for
hydrologists, who are trying to exploit these potentials the most, updating and re-inventing the way
hydrologic and hydraulic analyses are carried out. A variety of research fields have progressed
significantly, ranging from the evaluation of water features, to the classification of land-cover,
the identification of river morphology, and the monitoring of extreme flood events. The description of
flood processes may particularly benefit from the integrated use of recent algorithms and monitoring
techniques. In fact, flood exposure and risk over large areas and in scarce data environments have
always been challenging topics due to the limited information available on river basin hydrology,
basin morphology, land cover, and the resulting model uncertainty. The ability of new tools to carry
out intensive analyses over huge datasets allows us to produce flood studies over large extents and
with a growing level of detail. The present Special Issue aims to describe the state-of-the-art on flood
assessment, monitoring, and management using new algorithms, new measurement systems and
EO data. More specifically, we collected a number of contributions dealing with: (1) the impact of
climate change on floods; (2) real time flood forecasting systems; (3) applications of EO data for
hazard, vulnerability, risk mapping, and post-disaster recovery phase; and (4) development of tools
and platforms for assessment and validation of hazard/risk models
Data Fusion Through Bayesian Methods for Flood Monitoring from Remotely Sensed Data
No full textProducing high-precision flood maps requires integrating and correctly classifying information coming from heterogeneous sources. Methods to perform such integration have to rely on different knowledge bases. A useful tool to perform this task consists in the use of Bayesian methods to assign probabilities to areas being subject to flood phenomena, fusing a priori information and modeling with data coming from radar or optical imagery. In this chapter we review the use of Bayesian networks, an elegant framework to cast probabilistic descriptions of complex systems, applied to flood monitoring from multi-sensor, multi-temporal remotely sensed and ancillary data
A Bayesian Network for Flood Detection Combining SAR Imagery and Ancillary Data
No full textAccurate flood mapping is important for both planning activity during emergencies and as a support for the successive assessment of damaged areas. A valuable information source for such a procedure can be remote sensing synthetic aperture radar (SAR) imagery. However, flood scenarios are typical examples of complex situations in which different factors have to be considered to provide accurate and robust interpretation of the situation on the ground. For this reason, a data fusion approach of remote sensing data with ancillary information can be particularly useful. In this work, a Bayesian Network (BN) is proposed to integrate remotely sensed data, such as multi-temporal SAR intensity images and InSAR coherence data, with geomorphic and other ground information. The methodology is tested on a case study regarding a flood occurred in the Basilicata region (Italy) on December 2013, monitored using a time series of COSMO-SkyMed data. It is shown that the synergetic use of different information layers can help to detect more precisely the areas affected by the flood, reducing false alarms and missed identifications which may affect algorithms based on data from a single source. The produced flood maps are compared to data obtained independently from the analysis of optical images; the comparison indicates that the proposed methodology is able to reliably follow the temporal evolution of the phenomenon, assigning high probability to areas most likely to be flooded, in spite of their heterogeneous temporal SAR/InSAR signatures, reaching accuracies of up to 89%
Effect of dietary supplementation with Lactobacillus acidophilus D2/CSL (CECT 4529) on caecum microbioma and productive performance in broiler chickens.
No full textThis study examines the effects of the dietary supplementation with Lactobacillus acidophilus D2/CSL (CECT 4529) (LA) on productive performances, incidence of foot pad dermatitis and caecum microbioma in broiler chickens. A total of 1,100 one-day old male Ross 308 chicks were divided into 2 groups of 16 replicates with 25 birds each and reared from 1-41 d. One group was fed a basal diet (CON) and the other group the same diet supplemented with LA. Caecum contents were collected from 4 selected birds at day one and 5 selected birds at the end of the rearing period. Then, they were submitted to DNA extraction and whole DNA shotgun metagenomic sequencing. Overall, the LA supplementation produced a significant beneficial effect on body weight gain between 15-28 d and improved feed conversion rate in the overall period. On the contrary, litter moisture, pH and incidence of the foot pad lesions were not affected by LA. Birds treated with LA showed a lower occurrence of pasty vent at both 14 and 28 d. At the end of the rearing period, Lachanospiraceae were significantly higher in LA birds in comparison to CON (17.07 vs 14.39%; P = 0.036). Moreover, Ruminococcus obeum, Clostridium clostridioforme, Roseburia intestinalis, Lachnospiraceae bacterium 14-2T and Coprococcus eutactus were significantly higher in LA birds in comparison to CON. The relative abundance of Lactobacillus acidophilus was comparable between LA and CON groups. However, a positive effect was observed in relation to the metabolic functions in the treated group, with particular reference to the higher abundance of β-glucosidase. In conclusion, the LA supplementation improved broiler productive performances and metabolic functions promoting animal health
A Bayesian Network for Flood Detection Combining SAR Imagery and Ancillary Data
No full textAccurate flood mapping is important for both planning activities during emergencies and as a support for the successive assessment of damaged areas. A valuable information source for such a procedure can be remote sensing synthetic aperture radar (SAR) imagery. However, flood scenarios are typical examples of complex situations in which different factors have to be considered to provide accurate and robust interpretation of the situation on the ground. For this reason, a data fusion approach of remote sensing data with ancillary information can be particularly useful. In this paper, a Bayesian network is proposed to integrate remotely sensed data, such as multitemporal SAR intensity images and interferometric-SAR coherence data, with geomorphic and other ground information. The methodology is tested on a case study regarding a flood that occurred in the Basilicata region (Italy) on December 2013, monitored using a time series of COSMO-SkyMed data. It is shown that the synergetic use of different information layers can help to detect more precisely the areas affected by the flood, reducing false alarms and missed identifications which may affect algorithms based on data from a single source. The produced flood maps are compared to data obtained independently from the analysis of optical images; the comparison indicates that the proposed methodology is able to reliably follow the temporal evolution of the phenomenon, assigning high probability to areas most likely to be flooded, in spite of their heterogeneous temporal SAR/InSAR signatures, reaching accuracies of up to 89%
AGU hydrology days 2013
No full text2013 annual AGU hydrology days was held at Colorado State University on March 25 - March 27, 2013.Includes bibliographical references.In the present work, we present an application of a new formulation for the estimation of the soil moisture in the root zone based on the measured value of soil moisture at the surface. The method has been recently proposed by Manfreda et al. (2012) with the aim to provide a mathematical relationship between surface and root zone soil moisture. It derives from a simplified form of the soil water balance equation and provides a closed form of the relationship between the root zone and the surface soil moisture with a limited number of physically consistent parameters. The approach was used to interpret soil moisture dynamics at the point scale using soil moisture measurements taken from the African Monsoon Multidisciplinary Analysis (AMMA) database. These measurements form an excellent database with a significant number of measurements in time and space. Moreover, the measurements provide a detailed description of the soil moisture along the root-zone profile. According to this, we have used the surface soil moisture measurements at 5 cm depth to predict the soil moisture in the lower layer of the soil where the relative saturation is measured at various depths. The method provided good prediction of the averaged soil moisture in the root zone soil layer with the advantage that all parameters are physically consistent
Cosmic-ray electrons and positrons with the Fermi Large Area Telescope
No full textIn this work it is described a measurement of the cosmic ray inclusive electron and positron spectrum performed with 7 years of data collected by the Fermi Large Area Telescope, covering the energy range from 7 Gev to 2 TeV. The analysis reduces the statistical and systematics uncertainties compared to previous Fermi measurements and eliminates also some unaccounted bias which affected them in the low energy region. The spectrum found is well described by a broken power-law, with a break at 53±8 GeV and spectral index of -3.21 ± 0.02 below the break and -3.07 ± 0.02(stat+syst) ± 0.04 (energy scale) above. The predicted deviation from power-law behavior above 1 TeV is not confirmed by the data
Pass 8: development and science prospects for the new Fermi LAT event-level analysis
No full textThe Large Area Telescope (LAT) onboard the Fermi Gamma-ray Space Telescope (Fermi) is a pair-conversion telescope for high-energy gamma rays operating on orbit since June 2008.
The experience and the great amount of data accumulated in this first years of mission,
have led to a deeper understanding and improved description of the LAT performance in the orbital environment. On that basis, a radical revision of the entire event-level analysis, which includes virtually every aspect of the data reduction process, is in course of development by
the Fermi collaboration. This new event analysis framework, going under the name of Pass 8,
is expected to give a significant improvement to the quality and quantity of the data collected
by the LAT.
The new event reconstruction being essentially frozen, the present work fits into the subsequent stage of the event-level analysis, namely the characterization of the topological information available on an event-by-event basis and its use for the background rejection. The connections with some relevant science topics and the corresponding prospectives will be described in details in the thesis.
First, I present the results of a multivariate analysis, made using the variables produced
by the various reconstruction algorithms, aimed at characterizing the quality of the energy
reconstruction. This is achieved by an algorithm that, based on the topology of the event in the detector, tries to estimate the probability that its energy measurement will be in the core of the energy dispersion distribution. The algorithm is created by training several Classification Trees on the simulated data. Various possible approaches to the task are examined, as well as a series of different design choices, and their results are compared to determine the one with the best performances.
The resultant estimator (PE) will become part of the standard selection algorithms developed by the Fermi collaboration as a variable onto which operate quality cuts finalized to remove the tails of the energy dispersion. Furthermore, it can be used to select event sample with a narrower energy dispersion, which can potentially enhance the sensitivity in several different science analyses. A natural application of this first stage of the work is the search of possible monochromatic lines in the gamma rays spectrum. Through a series of Monte Carlo simulations I show that, taking into account the information given by P(E), the sensitivity to a line can improve up to 15% in interesting regions of the phase space.
Furthermore I present my work on various stages of an ongoing analysis of the high-energy cosmic ray electrons measured by the LAT with the new Pass 8 event level analysis. My main contribution was the development of a custom event selection, made of both hand-made cuts and specifically trained Classification Trees, aimed at discriminating electrons from the other charged species. In the thesis this event selection will be characterized in terms of the acceptance of the detector and of the residual background after all the cuts. A preliminary electron spectrum is included, as final conclusion of this work
COMPARING SECONDARY SCHOOL ARTS CURRICULUM BETWEEN SLOVENIA AND ONTARIO CANADA
No full textTema diplomske naloge je primerjava slovenskega učnega načrta z ontarijskim učnim načrtom. V diplomski nalogi poskušamo poiskati razlike in podobnosti med izbranima učnima načrtoma. Vsebino raziskovalnega vprašanja predstavljamo v petih poglavjih diplomske naloge. S kratkim pregledom srednješolskega izobraževanja v Sloveniji ter podrobnejšim opisom vzgojno izobraževalnega sistema v Kanadi opravimo interpretacijo obeh učnih načrtov. V nadaljevanju povzamemo in analiziramo ontarijski učni načrt in kot dopolnilo k diplomskemu delu podamo primer iz prakse ene izmed ontarijskih srednjih šol. V zaključku potrdimo oziroma zavrnemo tri hipoteze. Naloga prinaša ugotovitve, da se kanadski vzgojno izobraževalni sistem precej razlikuje od slovenskega, da v provinci Ontario v Kanadi posegajo po drugačnih strategijah učenja umetnosti kot v Sloveniji in da je posamezne segmente ontarijskega učnega načrta nemogoče prenesti v naš učni sistem.The purpose of this thesis is a comparison between the Slovenian Art Curriculum and the Art Curriculum of the Province Ontario. In this final thesis the author tries to find the differences and similarities between chosen curriculums. The research questions are presented in five chapters of the thesis. With the short overview of the secondary education in Slovenia and a closer look of the educational system in Canada the author makes an interpretation of both curriculums. Later on there is a summary and analysis of the Ontario Art Curriculum and as a fulfillment to the final thesis the author adds a practical example of one of the High Schools in Ontario. In conclusion the author confirms or rejects the three hypotheses, which stated that the Canadian educational system differs significantly from the Slovenian one, that in the province of Ontario, Canada teachers use different teaching strategies than in Slovenia and that it is impossible to transfer individual segments of the Ontario curriculum into our educational system
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