Search results for "Spectral"
showing 10 items of 3116 documents
The Visible and the Invisible in photographic works by Patrick Hogan, Ailbhe Ni Bhriain and David Creedon
2014
International audience
Spectral function for overoccupied gluodynamics from classical lattice simulations
2019
We study the spectral properties of an overoccupied gluonic system far from equilibrium. Using classical Yang-Mills simulations and linear response theory, we determine the statistical and spectral functions. We measure dispersion relations and damping rates of transversally and longitudinally polarized excitations in the gluonic plasma, and also study further structures in the spectral function.
UAS BASED TREE SPECIES IDENTIFICATION USING THE NOVEL FPI BASED HYPERSPECTRAL CAMERAS IN VISIBLE, NIR AND SWIR SPECTRAL RANGES
2016
Abstract. Unmanned airborne systems (UAS) based remote sensing offers flexible tool for environmental monitoring. Novel lightweight Fabry-Perot interferometer (FPI) based, frame format, hyperspectral imaging in the spectral range from 400 to 1600 nm was used for identifying different species of trees in a forest area. To the best of the authors’ knowledge, this was the first research where stereoscopic, hyperspectral VIS, NIR, SWIR data is collected for tree species identification using UAS. The first results of the analysis based on fusion of two FPI-based hyperspectral imagers and RGB camera showed that the novel FPI hyperspectral technology provided accurate geometric, radiometric and sp…
HYPERSPECTRAL REFLECTANCE SIGNATURES AND POINT CLOUDS FOR PRECISION AGRICULTURE BY LIGHT WEIGHT UAV IMAGING SYSTEM
2018
Abstract. The objective of this investigation was to study the use of a new type of a low-weight unmanned aerial vehicle (UAV) imaging system in the precision agriculture. The system consists of a novel Fabry-Perot interferometer based hyperspectral camera and a high-resolution small-format consumer camera. The sensors provide stereoscopic imagery in a 2D frame-format and they both weigh less than 500 g. A processing chain was developed for the production of high density point clouds and hyperspectral reflectance image mosaics (reflectance signatures), which are used as inputs in the agricultural application. We demonstrate the use of this new technology in the biomass estimation process, w…
VARIABILITY OF REMOTE SENSING SPECTRAL INDICES IN BOREAL LAKE BASINS
2018
Remotely sensed hyperspectral data has widely been used to determine water quality parameters in oceanic waters. However in freshwater basins the dependence between the hyperspectral data and the parameters is more complicated. In this work some ideas are presented concerning the study of this dependence. The data used in this study were collected from the lake Hiidenvesi in southern Finland. The hyperspectral data consists of reflectances in 36 bands in the wavelength area 508…878 nm and the separately measured water quality parameters are turbidity, blue-green algae, chlorophyll, pH and dissolved oxygen. Hyperspectral data was used as bare band reflectances, but also in the …
CHOOSING OF OPTIMAL REFERENCE SAMPLES FOR BOREAL LAKE CHLOROPHYLL A CONCENTRATION MODELING USING AERIAL HYPERSPECTRAL DATA
2018
Abstract. Optical remote sensing has potential to overcome the limitations of point estimations of lake water quality by providing spatial and temporal information. In open ocean waters the optical properties are dominated by phytoplankton density, while the relationship between color and the constituents is more complicated in inland waters varying regionally and seasonally. Concerning the difficulties relating to comprehensive modeling of complex inland and coastal waters, the alternative approach is considered in this paper: the raw digital numbers (DN) recorded using aerial remote hyperspectral sensing are used without corrections and derived by means of regression modeling to predict C…
Minimal learning machine in anomaly detection from hyperspectral images
2020
Abstract. Anomaly detection from hyperspectral data needs computationally efficient methods to process the data when the data gathering platform is a drone or a cube satellite. In this study, we introduce a minimal learning machine for hyperspectral anomaly detection. Minimal learning machine is a novel distance-based classification algorithm, which is now modified to detect anomalies. Besides being computationally efficient, minimal learning machine is also easy to implement. Based on the results, we show that minimal learning machine is efficient in detecting global anomalies from the hyperspectral data with low false alarm rate.
CLUSTERING INCOMPLETE SPECTRAL DATA WITH ROBUST METHODS
2018
Abstract. Missing value imputation is a common approach for preprocessing incomplete data sets. In case of data clustering, imputation methods may cause unexpected bias because they may change the underlying structure of the data. In order to avoid prior imputation of missing values the computational operations must be projected on the available data values. In this paper, we apply a robust nan-K-spatmed algorithm to the clustering problem on hyperspectral image data. Robust statistics, such as multivariate medians, are more insensitive to outliers than classical statistics relying on the Gaussian assumptions. They are, however, computationally more intractable due to the lack of closed-for…
Effects of Temperature and Axial Strain on Four-Wave Mixing Parametric Frequencies in Microstructured Optical Fibers Pumped in the Normal Dispersion …
2014
A study of the effect of temperature and axial strain on the parametric wavelengths produced by four-wave mixing in microstructured optical fibers is presented. Degenerate four-wave mixing was generated in the fibers by pumping at normal dispersion, near the zero-dispersion wavelength, causing the appearance of two widely-spaced four-wave mixing spectral bands. Temperature changes, and/or axial strain applied to the fiber, affects the dispersion characteristics of the fiber, which can result in the shift of the parametric wavelengths. We show that the increase of temperature causes the signal and idler wavelengths to shift linearly towards shorter and longer wavelengths, respectively. For t…
Enabling Searches on Wavelengths in a Hyperspectral Indices Database
2018
Abstract. Spectral indices derived from hyperspectral reflectance measurements are powerful tools to estimate physical parameters in a non-destructive and precise way for several fields of applications, among others vegetation health analysis, coastal and deep water constituents, geology, and atmosphere composition. In the last years, several micro-hyperspectral sensors have appeared, with both full-frame and push-broom acquisition technologies, while in the near future several hyperspectral spaceborne missions are planned to be launched. This is fostering the use of hyperspectral data in basic and applied research causing a large number of spectral indices to be defined and used in various…