Search results for "Meteor"
showing 10 items of 4734 documents
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…
Anticipating the impact of pitfalls in kinetic biodegradation parameter estimation from substrate depletion curves of organic pollutants
2019
[EN] Accurate and reliable estimation of kinetic parameters of pollutant biodegradation processes is essential for environmental and health risk assessment. Common biodegradation models proposed in the literature, such as the nonlinear Monod equation and its simplified versions (e.g. Michaelis-Menten-like and first-order equations), are problematic in terms of accuracy of kinetic parameters due to the parameter correlation. However, a comparison between these models in terms of accuracy and reliability, related to data imprecision, has not been performed in the literature. This task is necessary, mainly because the model selection cannot be straightforward, as shown in this work. To facilit…
Controlled time integration for the numerical simulation of meteor radar reflections
2016
We model meteoroids entering the Earth[U+05F3]s atmosphere as objects surrounded by non-magnetized plasma, and consider efficient numerical simulation of radar reflections from meteors in the time domain. Instead of the widely used finite difference time domain method (FDTD), we use more generalized finite differences by applying the discrete exterior calculus (DEC) and non-uniform leapfrog-style time discretization. The computational domain is presented by convex polyhedral elements. The convergence of the time integration is accelerated by the exact controllability method. The numerical experiments show that our code is efficiently parallelized. The DEC approach is compared to the volume …
A Lightweight Prototype of a Magnetometric System for Unmanned Aerial Vehicles
2021
Detection of the Earth’s magnetic field anomalies is the basis of many types of studies in the field of earth sciences and archaeology. These surveys require different ways to carry out the measures but they have in common that they can be very tiring or expensive. There are now several lightweight commercially available magnetic sensors that allow light-UAVs to be equipped to perform airborne measurements for a wide range of scenarios. In this work, the realization and functioning of an airborne magnetometer prototype were presented and discussed. Tests and measures for the validation of the experimental setup for some applications were reported. The flight sessions, appropriately programm…
Modelling and Analysis of Flow Rate and Pressure Head in Pipelines
2019
Currently, various approaches with several utilities are proposed to identify damage in the pipeline. The pipeline system is modeled in the form of a distributed parameter system, such that the state space related to the distributed parameter system contains infinite dimension. In this paper, a novel technique is proposed to analyze and model the flow in the pipeline. Important theorems are proposed for testing the observability as well as controllability of the proposed model.
Cloud detection on the Google Earth engine platform
2017
The vast amount of data acquired by current high resolution Earth observation satellites implies some technical challenges to be faced. Google Earth Engine (GEE) platform provides a framework for the development of algorithms and products built over this data in an easy and scalable manner. In this paper, we take advantage of the GEE platform capabilities to exploit the wealth of information in the temporal dimension by processing a long time series of satellite images. A cloud detection algorithm for Landsat-8, which uses previous images of the same location to detect clouds, is implemented and tested on the GEE platform.
Processing and Assessment of Spectrometric, Stereoscopic Imagery Collected Using a Lightweight UAV Spectral Camera for Precision Agriculture
2013
Imaging using lightweight, unmanned airborne vehicles (UAVs) is one of the most rapidly developing fields in remote sensing technology. The new, tunable, Fabry-Perot interferometer-based (FPI) spectral camera, which weighs less than 700 g, makes it possible to collect spectrometric image blocks with stereoscopic overlaps using light-weight UAV platforms. This new technology is highly relevant, because it opens up new possibilities for measuring and monitoring the environment, which is becoming increasingly important for many environmental challenges. Our objectives were to investigate the processing and use of this new type of image data in precision agriculture. We developed the entire pro…
Multi-phase classification by a least-squares support vector machine approach in tomography images of geological samples
2016
Abstract. Image processing of X-ray-computed polychromatic cone-beam micro-tomography (μXCT) data of geological samples mainly involves artefact reduction and phase segmentation. For the former, the main beam-hardening (BH) artefact is removed by applying a best-fit quadratic surface algorithm to a given image data set (reconstructed slice), which minimizes the BH offsets of the attenuation data points from that surface. A Matlab code for this approach is provided in the Appendix. The final BH-corrected image is extracted from the residual data or from the difference between the surface elevation values and the original grey-scale values. For the segmentation, we propose a novel least-squar…