Search results for "Names"
showing 10 items of 6843 documents
Structural characterization and chemical composition of aragonite and vaterite in freshwater cultured pearls
2008
AbstractVaterite and aragonite polymorphs in freshwater cultured pearls from mussels of the genus Hyriopsis (Unionidae) were structurally and compositionally characterized by Raman spectroscopy, Micro computer tomography, high resolution field emission scanning electron microscopy, electron microprobe analysis and laser ablation inductively coupled plasma mass spectrometry. The appearance of vaterite in pearls is related to the initial stages of biomineralization, although we demonstrate that vaterite can not be a precursor to aragonite. It is not related to a particular crystal habit and therefore does not have a structural functionality in the pearls. Larger contents of elements typically…
Joint Gaussian processes for inverse modeling
2017
Solving inverse problems is central in geosciences and remote sensing. Very often a mechanistic physical model of the system exists that solves the forward problem. Inverting the implied radiative transfer model (RTM) equations numerically implies, however, challenging and computationally demanding problems. Statistical models tackle the inverse problem and predict the biophysical parameter of interest from radiance data, exploiting either in situ data or simulated data from an RTM. We introduce a novel nonlinear and nonparametric statistical inversion model which incorporates both real observations and RTM-simulated data. The proposed Joint Gaussian Process (JGP) provides a solid framework…
Automatic emulator and optimized look-up table generation for radiative transfer models
2017
This paper introduces an automatic methodology to construct emulators for costly radiative transfer models (RTMs). The proposed method is sequential and adaptive, and it is based on the notion of the acquisition function by which instead of optimizing the unknown RTM underlying function we propose to achieve accurate approximations. The Automatic Gaussian Process Emulator (AGAPE) methodology combines the interpolation capabilities of Gaussian processes (GPs) with the accurate design of an acquisition function that favors sampling in low density regions and flatness of the interpolation function. We illustrate the good capabilities of the method in toy examples and for the construction of an…
Multioutput Automatic Emulator for Radiative Transfer Models
2018
This paper introduces a methodology to construct emulators of costly radiative transfer models (RTMs). The proposed methodology is sequential and adaptive, and it is based on the notion of acquisition functions in Bayesian optimization. Here, instead of optimizing the unknown underlying RTM function, one aims to achieve accurate approximations. The Automatic Multi-Output Gaussian Process Emulator (AMO-GAPE) methodology combines the interpolation capabilities of Gaussian processes (GPs) with the accurate design of an acquisition function that favors sampling in low density regions and flatness of the interpolation function. We illustrate the promising capabilities of the method for the const…
Optimal modalities for radiative transfer-neural network estimation of canopy biophysical characteristics: Evaluation over an agricultural area with …
2011
International audience; Neural networks trained over radiative transfer simulations constitute the basis of several operational algorithms to estimate canopy biophysical variables from satellite reflectance measurements. However, only little attention was paid to the training process which has a major impact on retrieval performances. This study focused on the several modalities of the training process within neural network estimation of LAI, FCOVER and FAPAR biophysical variables. Performances were evaluated over both actual experimental observations and model simulations. The SAIL and PROSPECT radiative transfer models were used here to simulate the training and the synthetic test dataset…
Efficient remote sensing image classification with Gaussian processes and Fourier features
2017
This paper presents an efficient methodology for approximating kernel functions in Gaussian process classification (GPC). Two models are introduced. We first include the standard random Fourier features (RFF) approximation into GPC, which largely improves the computational efficiency and permits large scale remote sensing data classification. In addition, we develop a novel approach which avoids randomly sampling a number of Fourier frequencies, and alternatively learns the optimal ones using a variational Bayes approach. The performance of the proposed methods is illustrated in complex problems of cloud detection from multispectral imagery.
On numerical broadening of particle size spectra: a condensational growth study using PyMPDATA 1.0
2021
Abstract. The work discusses the diffusional growth in particulate systems such as atmospheric clouds. It focuses on the Eulerian modeling approach in which the evolution of the probability density function describing the particle size spectrum is carried out using a fixed-bin discretization. The numerical diffusion problem inherent to the employment of the fixed-bin discretization is scrutinized. The work focuses on the applications of MPDATA family of numerical schemes. Several MPDATA variants are explored including: infinite-gauge, non-oscillatory, third-order-terms and recursive antidiffusive correction (double pass donor cell, DPDC) options. Methodology for handling coordinate transfor…
Blast waves from violent explosive activity at Yasur Volcano, Vanuatu
2013
[1] Infrasonic and seismic waveforms were collected during violent strombolian activity at Yasur Volcano (Vanuatu). Averaging ~3000 seismic events showed stable waveforms, evidencing a low-frequency (0.1–0.3 Hz) signal preceding ~5–6 s the explosion. Infrasonic waveforms were mostly asymmetric with a sharp compressive (5–106 Pa) onset, followed by a small long-lasting rarefaction phase. Regardless of the pressure amplitude, the ratio between the positive and negative phases was constant. These waveform characteristics closely resembled blast waves. Infrared imagery showed an apparent cold spherical front ~20 m thick, which moved between 342 and 405 m/s before the explosive hot gas/fragments…
Comment on “Rill erosion processes on steep colluvial deposit slope under heavy rainfall in flume experiments with artificial rain by F. Jiang et al.”
2020
Abstract Since rill flows are characterized by small water depths and steeply sloping channels, the corresponding hydraulic conditions are very different to those which are typically found in channels of streams and rivers. Furthermore, limited information is currently available on the effect of rainfall on flow resistance. The objective of this comment was to investigate the applicability of a recently theoretically deduced rill flow resistance equation, based on a power-velocity profile, using measurements carried out by Jiang et al. for both different slope steepness conditions and rainfall intensity. The relationship between the velocity profile parameter Γ, the channel slope and the fl…
Testing a theoretical resistance law for overland flow on a stony hillslope
2020
Overland flow, sediments, and nutrients transported in runoff are important processes involved in soil erosion and water pollution. Modelling transport of sediments and chemicals requires accurate estimates of hydraulic resistance, which is one of the key variables characterizing runoff water depth and velocity. In this paper, a new theoretical power–velocity profile, originally deduced neglecting the impact effect of rainfall, was initially modified for taking into account the effect of rainfall intensity. Then a theoretical flow resistance law was obtained by integration of the new flow velocity distribution. This flow resistance law was tested using field measurements by Nearing for the …