Advanced regression and detection methods for remote sensing data analysis

Nowadays the analysis of remote sensing data for environmental monitoring is fundamental to understand the local and global Earth dynamics. In this context, the main goal of this thesis is to present novel signal processing methods for the estimation of biophysical parameters and for the analysis icy terrain with active sensors. The thesis presents three main contributions. In the context of biophysical parameters estimation we focus on regression methods. According to the analysis of the literature, most of the regression techniques require a relevant number of reference samples to model a robust regression function. However, in real-word applications the ground truth observations are limited as their collection leads to high operational cost. Moreover, the availability of biased samples may result in low estimation accuracy. To address these issues, in this thesis we propose two novel contributions. The first contribution is a method for the estimation of biophysical parameters that integrates theoretical models with empirical observations associated to a small number of in-situ reference samples. The proposed method computes and correct deviations between estimates obtained through the inversion of theoretical models and empirical observations. The second contribution is a semisupervised learning (SSL) method for regression defined in the context of the ε-insensitive SVR. The proposed SSL method aims to mitigate the problems of small-sized biased training sets by injecting priors information in the initial learning of the SVR function, and jointly exploiting labeled and unlabeled samples in the learning phase of the SVR. The third contribution of this dissertation addresses the clutter detection problem in radar sounder (RS) data. The capability to detect clutter is fundamental for the interpretation of subsurface features in the radargram. In the state of the art, techniques that require accurate information on the surface topography or approaches that exploit complex multi-channel radar sounder systems have been presented. In this thesis, we propose a novel method for clutter detection that is independent from ancillary information and limits the hardware complexity of the radar system. The method relies on the interferometric analysis of two-channel RS data and discriminates the clutter and subsurface echoes by modeling the theoretical phase difference between the cross-track antennas of the RS. This allows the comparison of the phase difference distributions of real and simulated data. Qualitative and quantitative experimental results obtained on real airborne SAR and RS data confirm the effectiveness of the proposed methods

Results from an anthracological investigation of the Mousterian layer A9 at Grotta di Fumane, Italy.

A large charcoal sample taken from the Mousterian layer A9 at the Fumane cave, Italy, have been analyzed with the aim to identify the wood used for the several hearths discovered, achieve information on the criteria of collecting the wood and broadly draw the ecological context at the cave surroundings. Charcoal analysis is thus aimed to understand the state and the size at which the wood was collected. Once these data have been achieved and the heat producing energy of the predominant species, larch, was determined, a hypothesis was advanced on whether the Neanderthals applied particular criteria in the collection of firewood, taking advantage of a particular species. Compared to the other levels of the Fumane cave, layer A9 records the coldest climate based on anthracological analyses, showing that the tree-line was positioned at an elevation not far from the cave, with denser forests of spruce in the valley bottom

How to Efficiently Produce Ultrapure Acids

Subboiling distillation has been used since two decades for the purification of analytical grade acids from inorganic contaminants and demonstrated an efficient method to obtain pure acids starting from reagent grade chemicals. Nevertheless, the effect of the subboiling parameters on the purity of the distilled acids has never been methodically investigated. Aim of the present research is a systematic evaluation of the subboiling distillation protocol for the production of pure hydrochloric and nitric acid. In particular, the effect of the subboiling temperature and the number of subsequent distillations was investigated as these parameters were recognised as the most important factors controlling acid purity, acid concentration, and distillation yield. The concentration of twenty elements in the purified acids was determined by Inductively Coupled Plasma-Mass Spectrometry. As a result, the subboiling temperature (up to 82°C) and the number of subsequent distillations (up to four) were demonstrated not to affect the purity of the distilled nitric and hydrochloric acids. Under normal laboratory conditions, the residual elemental concentrations were in most cases below 10 ng/L in both nitric (2.75% w/w) and hydrochloric (0.1 M) blanks. Ultrapure nitric and hydrochloric acids could accordingly be produced under the most favorable conditions, i.e., the highest temperature and one distillation process only

Contrasting non-dynamic and dynamic models of the water-energy nexus in small, off-grid Mediterranean islands

ISSN:1029-7006ISSN:1607-796