Monitoring of Natura 2000 sites using hyperspectral remote sensing : quality assessment of field and airborne data for Ginkelse & Ederheide and Wekeromse Zand

In 2007, an airborne imaging spectroscopy campaign was organized in the frame of the HABISTAT project. Airborne data with the AHS sensor were acquired in the Netherlands and Belgium. One test site in Belgium was recorded, the Kalmthoutse Heide and one in the Netherlands: the Edese and Ginkelse Heide and the Wekeromse Zand. This report describes the quality assessment of the field and airborne data for the Edese and Ginkelse Heide and the Wekeromse Zand site. The results for the Kalmthoutse Heide will be presented in a separate report (INBO, 2008)

AHS2005: The 2005 airborne imaging spectroscopy campaign in the Millingerwaard, the Netherlands

The Millingerwaard was one of the first nature rehabilitation projects for river floodplains in the Netherlands. It therefore serves as an example project for other floodplain rehabilitation projects. As a consequence a lot of effort has been put in monitoring the vegetation succession in the floodplain. To stimulate the development of a heterogeneous landscape, a low grazing density of 1 animal (e.g., Galloway, Koniks) per 2-4 ha has been chosen. This density allows grazing whole year round and also development of forest is possible. The surface area of water changes over the year. During high floods, the whole floodplain except for the higher parts of the river dunes is flooded. This report describes the field and airborne data acquired during the AHS2005 imaging spectroscopy campaign in the Millingerwaard floodplain during the summer of 2005. The campaign is part of a research line that explores the use of hyperspectral sensors to retrieve biochemical and biophysical variables as input for ecological models using an integrated approac

Opposite-side flavour tagging of B mesons at the LHCb experiment

The calibration and performance of the oppositeside flavour tagging algorithms used for the measurements of time-dependent asymmetries at the LHCb experiment are described. The algorithms have been developed using simulated events and optimized and calibrated with B + →J/ψK +, B0 →J/ψK ∗0 and B0 →D ∗− μ + νμ decay modes with 0.37 fb−1 of data collected in pp collisions at √ s = 7 TeV during the 2011 physics run. The oppositeside tagging power is determined in the B + → J/ψK + channel to be (2.10 ± 0.08 ± 0.24) %, where the first uncertainty is statistical and the second is systematic

AoA-aware Probabilistic Indoor Location Fingerprinting using Channel State Information

With expeditious development of wireless communications, location fingerprinting (LF) has nurtured considerable indoor location based services (ILBSs) in the field of Internet of Things (IoT). For most pattern-matching based LF solutions, previous works either appeal to the simple received signal strength (RSS), which suffers from dramatic performance degradation due to sophisticated environmental dynamics, or rely on the fine-grained physical layer channel state information (CSI), whose intricate structure leads to an increased computational complexity. Meanwhile, the harsh indoor environment can also breed similar radio signatures among certain predefined reference points (RPs), which may be randomly distributed in the area of interest, thus mightily tampering the location mapping accuracy. To work out these dilemmas, during the offline site survey, we first adopt autoregressive (AR) modeling entropy of CSI amplitude as location fingerprint, which shares the structural simplicity of RSS while reserving the most location-specific statistical channel information. Moreover, an additional angle of arrival (AoA) fingerprint can be accurately retrieved from CSI phase through an enhanced subspace based algorithm, which serves to further eliminate the error-prone RP candidates. In the online phase, by exploiting both CSI amplitude and phase information, a novel bivariate kernel regression scheme is proposed to precisely infer the target's location. Results from extensive indoor experiments validate the superior localization performance of our proposed system over previous approaches

A Robotic CAD System using a Bayesian Framework

We present in this paper a Bayesian CAD system for robotic applications. We address the problem of the propagation of geometric uncertainties and how esian CAD system for robotic applications. We address the problem of the propagation of geometric uncertainties and how to take this propagation into account when solving inverse problems. We describe the methodology we use to represent and handle uncertainties using probability distributions on the system's parameters and sensor measurements. It may be seen as a generalization of constraint-based approaches where we express a constraint as a probability distribution instead of a simple equality or inequality. Appropriate numerical algorithms used to apply this methodology are also described. Using an example, we show how to apply our approach by providing simulation results using our CAD system

The SWAP EUV Imaging Telescope Part I: Instrument Overview and Pre-Flight Testing

The Sun Watcher with Active Pixels and Image Processing (SWAP) is an EUV solar telescope on board ESA's Project for Onboard Autonomy 2 (PROBA2) mission launched on 2 November 2009. SWAP has a spectral bandpass centered on 17.4 nm and provides images of the low solar corona over a 54x54 arcmin field-of-view with 3.2 arcsec pixels and an imaging cadence of about two minutes. SWAP is designed to monitor all space-weather-relevant events and features in the low solar corona. Given the limited resources of the PROBA2 microsatellite, the SWAP telescope is designed with various innovative technologies, including an off-axis optical design and a CMOS-APS detector. This article provides reference documentation for users of the SWAP image data.Comment: 26 pages, 9 figures, 1 movi

Monte Carlo Simulations of the Transition Radiation Detector of the AMS-02 Experiment

The Transition Radiation Detector of the AMS-02 experiment on the International Space Station is used for the separation of cosmic-ray positrons and electrons from protons and anti-protons, and for the identification of nuclei up to carbon (Z<=6). We present the Geant4 simulation that is used to describe the ionization and transition radiation processes and compare its results to flight data from AMS-02. After applying empirical corrections to the simulated data, the particle energy deposition and likelihood distributions in the TRD are described with high accuracy.Comment: 7 pages, 9 figures. Accepted for publication in Nuclear Inst. and Methods in Physics Research, A. CC-BY-NC-ND 4.0 licens