Search results for "Earth"
showing 10 items of 12204 documents
Estimating Missing Information by Cluster Analysis and Normalized Convolution
2018
International audience; Smart city deals with the improvement of their citizens' quality of life. Numerous ad-hoc sensors need to be deployed to know humans' activities as well as the conditions in which these actions take place. Even if these sensors are cheaper and cheaper, their installation and maintenance cost increases rapidly with their number. We propose a methodology to limit the number of sensors to deploy by using a standard clustering technique and the normalized convolution to estimate environmental information whereas sensors are actually missing. In spite of its simplicity, our methodology lets us provide accurate assesses.
Supporting group decision makers to locate temporary relief distribution centres after sudden-onset disasters
2020
International audience; In the humanitarian response, multiple decision-makers (DMs) need to collaborate in various problems, such as locating temporary relief distribution centres (RDCs). Several studies have argued that maximising demand coverage, reducing logistics costs and minimising response time are among the critical objectives when locating RDCs after a sudden-onset disaster. However, these objectives are often conflicting and the trade-offs can considerably complicate the situation for finding a consensus.To address the challenge and support the DMs, we suggest investigating the stability of non-dominated alternatives derived from a multi-objective model based on Monte Carlo Simul…
Stochastic Galerkin method for cloud simulation
2018
AbstractWe develop a stochastic Galerkin method for a coupled Navier-Stokes-cloud system that models dynamics of warm clouds. Our goal is to explicitly describe the evolution of uncertainties that arise due to unknown input data, such as model parameters and initial or boundary conditions. The developed stochastic Galerkin method combines the space-time approximation obtained by a suitable finite volume method with a spectral-type approximation based on the generalized polynomial chaos expansion in the stochastic space. The resulting numerical scheme yields a second-order accurate approximation in both space and time and exponential convergence in the stochastic space. Our numerical results…
Effects of natural radiation damage on back-scattered electron images of single crystals of minerals
2006
Generally, it has been assumed that signal intensity variations in back-scattered electron (BSE) images of minerals are mainly controlled by chemical heterogeneity. This is especially true for images of single crystals, where effects of different crystal orientations with respect to the incident beam on the observed BSE are excluded. In contrast, we show that local variations of the structural state within single-crystals (i.e., degree of lattice order or lattice imperfectness) may also have dramatic effects on the back-scattering of electrons. As an example, we present BSE images of single-crystals of natural zircon, ZrSiO 4 , whose intensity patterns are predominantly controlled by struct…
Soil organic carbon stock on the Majorca Island: temporal change in agricultural soil over the last 10 years
2019
8 Pags.- 5 Tabls.- 3 Figs.
Changements environnementaux survenant à la limite Oligocène/Miocène du bassin des Limagnes (Massif central, France).
2018
16 pages; International audience; Continental environments are very sensitive to climatic variations. A unique opportunity to study the climate changes around the Oligocene/Miocene boundary is offered by the Limagne graben Basin (France) where this stage boundary is well constrained by fossils. Indeed, some localities of the Limagne Graben Basin are so rich in mammal remains that they have become a European reference for mammal biostratigraphy. The dominant sedimentary facies of the lacustrine deposits in the northern part of the Limagne Graben Basin are composed of poorly cemented marls and calcarenites containing various plants and animals remains (e.g. algae, fish bones and teeth, gastro…
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.
SVM-based classification of High resolution Urban Satellites Images using Dense SURF and Spectral Information
2018
Remote-sensing focusing on image classification knows a large progress and receives the attention of the remote-sensing community day by day. Combining many kinds of extracted features has been successfully applied to High resolution urban satellite images using support vector machine (SVM). In this paper, we present a methodology that is promoting a performed classification by using pixel-wise SURF description features combined with spectral information in Cielab space for the first time on common scenes of urban imagery. The proposed method gives a promising classification accuracy when compared with the two types of features used separately.
SAR Image Classification Combining Structural and Statistical Methods
2011
The main objective of this paper is to develop a new technique of SAR image classification. This technique combines structural parameters, including the Sill, the slope, the fractal dimension and the range, with statistical methods in a supervised image classification. Thanks to the range parameter, we define the suitable size of the image window used in the proposed approach of supervised image classification. This approach is based on a new way of characterising different classes identified on the image. The first step consists in determining relevant area of interest. The second step consists in characterising each area identified, by a matrix. The last step consists in automating the pr…
The effect of rheological approximations in 3-D numerical simulations of subduction and collision
2018
Abstract Subduction and collision zones evolve differently from one another due to different rheological properties, different amounts of regional isostatic compensation, and the different mechanisms by which forces are applied to the convergent plates. The rheology of mantle and lithosphere is known to have the largest influence on the dynamics of subduction and continental collision. However, previous 3-D geodynamic models of subduction/collision processes have used various rheological approximations, making their results difficult to compare, since there is no clear understanding on the extent of these approximations on the dynamics. Here, we test the effect of rheological approximations…