The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
The abundance mapping of rangeland plant communities using hyperspectral remote sensing data is investigated. The cover fraction of five rangeland components (green grass, yellow grass, litter, shrubs and soil) was estimated using constrained Spectral Mixture Analysis (SMA). Three sets of endmembers were assessed. The first set labeled the laboratory endmember refers to the laboratory reflectance...
Identification of materials in a planetological scene observed by an imaging spectrometer is a common problem in remote sensing. Usually the pixel size is larger than the typical size of material change over planets, leading to a linear spatial mixing. We propose here an unsupervised approach based on source separation methods to estimate the pure spectra of the components present in the observed...
In this study we combine the spectral domain with the directional domain of hyperspectral CHRIS (Compact High Resolution Imaging Spectrometer) data to map 3D heterogeneity of an Alpine coniferous forest during wintertime. CHRIS mounted onboard the PROBA (Project for On-board Autonomy) spacecraft is capable of sampling terrestrial reflectance anisotropy over the visible/near-infrared region of the...
In mountainous areas, slope and altitude variations modulate the airborne sensed hyperspectral radiance image. A new algorithm, SIERRA, has been developed for atmospheric, relief and BRDF corrections in order to extract the surface reflectance in the form of bi-hemispherical albedo that does not depend on solar incidence and observation angles. The forward modeling efforts focus on the estimation...
We attempt to test the refined concept of combining multi-angle and hyperspectral remote sensing proposed by using airborne data. The concept proposes a system that acquires hyperspectral signals only in the nadir direction and measures in two additional directions in two spectral bands, red and NIR. It has been successfully demonstrated that the off-nadir hyperspectral simulations could be closely...
The use of polarized lasers for Raman spectroscopy provides a powerful tool in chemical physics as it allows a precise differentiation of the vibration modes of the crystals according to their crystallographic symmetry and local spatial orientation. In this paper we analyze the possibility of efficiently using the polarization information in Raman spectroscopy by taking into account the relationships...
This paper presents a new semi-supervised segmentation algorithm, suited to high dimensional data, of which hyperspectral images are an example. The algorithm implements two main steps: (a) semi-supervised learning, used to infer the class distributions, followed by (b) segmentation, by inferring the labels from a posterior density built on the learned class distributions and on a Markov random field...
In vegetation spectroscopy, compositional information of leaves contained at band level or across the electromagnetic spectrum (EMS) and parts thereof, plays a huge rule in the analysis of spectra and their relations to the reflectance patterns across the spectrum. Spectral matching is often achieved by means of matching algorithms such as the Spectral Angle Mapper (SAM), Spectral information divergence...
Spectra of powdered mineral samples are used for calibration of air-borne data and for quantitative estimation of mineral content. However, in natural environments, minerals can be orientated in a specific manner and their lattices are usually unbroken. Using powders, we minimize orientation effects, but thereby creating a level of uncertainty that should be evaluated. In this study, we attempt primarily...
Achieving reliable ground cover maps and high classification accuracies using limited ground truth is a key challenge for hyperspectral data analysts. In this paper, we explore the benefits of combining spectral derivative information along with reflectance information for hyperspectral classification. In addition to providing useful class-specific slope information, spectral derivatives are likely...
This study assessed the utility of hyperspectral imagery in discriminating remnant tree species and stand regeneration stages in Southeast Queensland, Australia. Reflectance data of three species of woody vegetation (i.e. Eucalyptus populnea, Acacia pendula and Eucalyptus orgadophila), acquired using a HyMaptrade airborne system, were analysed using partial least squares (PLS) regression. Three groups...
Recent advances in electronics and sensor design have enabled the development of a hyperspectral video camera, which can capture hyperspectral datacubes at near video rates. In this work, we show how high-speed hyperspectral imaging can be used to address several challenging problems in video surveillance. In particular, we combine traditional methods for hyperspectral image analysis and computer...
Endmember extraction for spectral mixture analysis is a necessary step when endmember information is unknown. If endmembers are assumed to be pure pixels present in an image scene, endmember extraction is to search the most distinctive pixels. Popular algorithms using the criteria of simplex volume maximization (e.g., N-FINDR) and spectral signature similarity (e.g., Vertex Component Analysis) belong...
Acknowledged and justified is the recognition of remote sensing as a powerful tool in land cover/land use monitoring for a large number of purposes ranging from agricultural practices to global ecology and environment protection. Data collected and information created from Earth observations constitute critical inputs to the sustainable management of the Earth - providing evidence for informed decision-making...
One of the most challenging issues in unsupervised linear spectral mixture analysis (LSMA) is how to obtain unknown knowledge of target signatures referred to as virtual endmembers (VEs) directly from the data to be processed. This issue has never arisen in supervised LSMA where the VEs are either assumed to be known a priori or can be provided by visual inspection. With the recent advent of hyperspectral...
This paper deals with an original method suitable for estimating the noise introduced by optical imaging systems, such as CCD cameras, multispectral scanners and imaging spectrometers. The power of the signal-dependent photonic noise is decoupled from that of the signal-independent noise generated by the electronic circuitry. The method relies on the multivariate regression of local sample mean and...
We present a detailed study on the classification of urban hyperspectral data with morphological profiles (MP). Although such a spectral-spatial classification approach may significantly increase achieved accuracy, the computational complexity as well as the increased dimensionality and redundancy of such data sets are potential drawbacks. This can be overcome by feature selection. Moreover it is...
We analyze the spectra measured by the Gamma Ray Spectrometer (GRS) on board the SELENE satellite orbiting the Moon. The spectra consist in 8192 energy channels ranging from 0 to 12 MeV and exhibiting lines of interest (O, Mg, Al, Si, Ti, Ca, Fe, K, Th, and U) superposed on a continuum. We have also analysed the data with various multivariate techniques, one of them being the Independent Component...
In previous work, kernel methods were introduced as a way to generalize the linear mixing model. This work led to a new set of algorithms that performed the unmixing of hyperspectral imagery in a reproducing kernel Hilbert space. By processing the imagery in this space different types of unmixing could be introduced - including an approximation of intimate mixtures. Whereas previous research focused...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.