Search results for "Gaussian process"
showing 10 items of 128 documents
Mapping landscape canopy nitrogen content from space using PRISMA data
2021
Abstract Satellite imaging spectroscopy for terrestrial applications is reaching maturity with recently launched and upcoming science-driven missions, e.g. PRecursore IperSpettrale della Missione Applicativa (PRISMA) and Environmental Mapping and Analysis Program (EnMAP), respectively. Moreover, the high-priority mission candidate Copernicus Hyperspectral Imaging Mission for the Environment (CHIME) is expected to globally provide routine hyperspectral observations to support new and enhanced services for, among others, sustainable agricultural and biodiversity management. Thanks to the provision of contiguous visible-to-shortwave infrared spectral data, hyperspectral missions open enhanced …
Color degradation mapping of rock art paintings using microfading spectrometry
2021
[EN] Rock art documentation is a complex task that should be carried out in a complete, rigorous and exhaustive way, in order to take particular actions that allow stakeholders to preserve the archaeological sites under constant deterioration. The pigments used in prehistoric paintings present high light sensitivity and rigorous scientific color degradation mapping is not usually undertaken in overall archaeological sites. Microfading spectrometry is a suitable technique for determining the light-stability of pigments found in rock art paintings in a non-destructive way. Spectral data can be transformed into colorimetric information following the recommendations published by the Commission …
Gaussian Process Sensitivity Analysis for Oceanic Chlorophyll Estimation
2017
Source at https://doi.org/10.1109/JSTARS.2016.2641583. Gaussian process regression (GPR) has experienced tremendous success in biophysical parameter retrieval in the past years. The GPR provides a full posterior predictive distribution so one can derive mean and variance predictive estimates, i.e., point-wise predictions and associated confidence intervals. GPR typically uses translation invariant covariances that make the prediction function very flexible and nonlinear. This, however, makes the relative relevance of the input features hardly accessible, unlike in linear prediction models. In this paper, we introduce the sensitivity analysis of the GPR predictive mean and variance functions…
Multi-fidelity Gaussian Process Emulation for Atmospheric Radiative Transfer Models
2023
This repository contains several datasets of spectral atmospheric transfer functions (i.e. path radiance, transmittances, spherical albedo) simulated with MODTRAN6 atmospheric radiative transfer model. The simulations are stored in hdf5 files using the Atmospheric Look-up table Generator (ALG) toolbox (https://doi.org/10.5194/gmd-13-1945-2020). Each dataset has an associated .xml file that includes the configuration of ALG/MODTRAN6 executions. All datasets include the input atmospheric/geometric variables that are summarized in the following table. Each dataset file has a random distribution (based on latin hypercube sampling) these input variables with varying number of points (e.g. train5…
Design of measurement-based correlation models for shadow fading
2010
This paper deals with the design of measurement-based correlation models for shadow fading. Based on the correlation model, we design a simulation model using the sumof-sinusoids (SOS) method to enable the simulation of spatial lognormal processes characterizing real-world shadow fading scenarios. The model parameters of the simulation model are computed by applying the L p -norm method (LPNM). This method facilitates an excellent fitting of the simulation model's autocorrelation function (ACF) to that of measured channels. Our study includes an evaluation of all important statistical quantities of the proposed measurement-based simulation model, such as the probability density function (PD…
Stochastic differential calculus for wind-exposed structures with autoregressive continuous (ARC) filters
2008
In this paper, an alternative method to represent Gaussian stationary processes describing wind velocity fluctuations is introduced. The technique may be considered the extension to a time continuous description of the well-known discrete-time autoregressive model to generate Gaussian processes. Digital simulation of Gaussian random processes with assigned auto-correlation function is provided by means of a stochastic differential equation with time delayed terms forced by Gaussian white noise. Solution of the differential equation is a specific sample of the target Gaussian wind process, and in this paper it describes a digitally obtained record of the wind turbolence. The representation o…
Exact Closed-Form Expressions for the Distribution, the Level-Crossing Rate, and the Average Duration of Fades of the Capacity of OSTBC-MIMO Channels
2009
Article from the journal: IEEE Transactions on Vehicular Technology Official site: http://dx.doi.org/10.1109/TVT.2008.927038 This paper deals with some important statistical properties of the channel capacity of multiple-input-multiple-output (MIMO) systems with orthogonal space-time block code (OSTBC) transmission. We assume that all the subchannels are uncorrelated. For OSTBC-MIMO systems, exact closed-form expressions are derived for the probability density function (PDF), the cumulative distribution function (CDF), the level-crossing rate (LCR), and the average duration of fades (ADF) of the channel capacity. Furthermore, it will be shown that these exact closed-form expressions can be …
Optimal Sampling Period and Required Number of Samples for OSTBC-MIMO Rayleigh Fading Channel Capacity Simulators
2014
The purpose of this paper is to contribute to the performance assessment of channel capacity simulators. Here, we consider the instantaneous capacity (also referred to as the mutual information) in orthogonal space-time block code (OSTBC) transceiver systems over multiple-input multiple-output (MIMO) Rayleigh fading channels. To ensure that the level-crossing rate (LCR) of the instantaneous capacity can efficiently and accurately be simulated, we derive closed-form approximate solutions to the optimal sampling period and the required number of samples to be generated. Several numerical examples will be presented to illustrate the usefulness of our procedure. It will also be shown that the d…
A global Canopy Water Content product from AVHRR/Metop
2020
Abstract Spatially and temporally explicit canopy water content (CWC) data are important for monitoring vegetation status, and constitute essential information for studying ecosystem-climate interactions. Despite many efforts there is currently no operational CWC product available to users. In the context of the Satellite Application Facility for Land Surface Analysis (LSA-SAF), we have developed an algorithm to produce a global dataset of CWC based on data from the Advanced Very High Resolution Radiometer (AVHRR) sensor on board Meteorological–Operational (MetOp) satellites forming the EUMETSAT Polar System (EPS). CWC reflects the water conditions at the leaf level and information related …
A new Framework for the Spectral Information Decomposition of Multivariate Gaussian Processes
2021
: Different information-theoretic measures are available in the literature for the study of pairwise and higher-order interactions in multivariate dynamical systems. While these measures operate in the time domain, several physiological and non-physiological systems exhibit a rich oscillatory content that is typically analyzed in the frequency domain through spectral and cross-spectral approaches. For Gaussian systems, the relation between information and spectral measures has been established considering coupling and causality measures, but not for higher-order interactions. To fill this gap, in this work we introduce an information-theoretic framework in the frequency domain to quantify t…