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Spectranomics: Emerging science and conservation opportunities at the interface of biodiversity and remote sensing / Gregory P. Asner in Global ecology and conservation, vol 8 (October 2016)
[article]
Titre : Spectranomics: Emerging science and conservation opportunities at the interface of biodiversity and remote sensing Type de document : Article/Communication Auteurs : Gregory P. Asner, Auteur ; Roberta E. Martin, Auteur Année de publication : 2016 Article en page(s) : pp 212 -219 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] biogéographie
[Termes IGN] canopée
[Termes IGN] couvert forestier
[Termes IGN] couvert végétal
[Termes IGN] politique de conservation (biodiversité)
[Termes IGN] réflectance végétale
[Termes IGN] spectroscopieRésumé : (auteur) With the goal of advancing remote sensing in biodiversity science, Spectranomics represents an emerging approach, and a suite of quantitative methods, intended to link plant canopy phylogeny and functional traits to their spectral-optical properties. The current Spectranomics database contains about one half of known tropical forest canopy tree species worldwide, and has become a forecasting asset for predicting aspects of plant functional and biological diversity to be remotely mapped and monitored with current and future spectral remote sensing technology. To mark ten years of Spectranomics, we review recent scientific outcomes to further stimulate engagement in the use of spectral remote sensing for biodiversity and functional ecology research. In doing so, we highlight three major emerging opportunities for the science and conservation communities based on Spectranomics. Numéro de notice : A2016-715 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET/IMAGERIE Nature : Article DOI : 10.1016/j.gecco.2016.09.010 En ligne : http://dx.doi.org/10.1016/j.gecco.2016.09.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82108
in Global ecology and conservation > vol 8 (October 2016) . - pp 212 -219[article]Two heads are better than one / Brian Curtiss in GEO: Geoconnexion international, vol 15 n° 8 (September 2016)
[article]
Titre : Two heads are better than one Type de document : Article/Communication Auteurs : Brian Curtiss, Auteur Année de publication : 2016 Article en page(s) : pp 33 - 37 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] appariement automatique
[Termes IGN] appariement d'images
[Termes IGN] image hyperspectrale
[Termes IGN] image multibande
[Termes IGN] spectroradiométrieRésumé : (éditeur) Using linked spectroradiometers enables far better collection of field reflectance spectra, to improve the matching of remote sensed imagery.Brian Curtiss shows how it can be done Numéro de notice : A2016-662 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81893
in GEO: Geoconnexion international > vol 15 n° 8 (September 2016) . - pp 33 - 37[article]An interactive tool for semi-automatic feature extraction of hyperspectral data / Zoltan Kovacs in Open geosciences, vol 8 n° 1 (January - July 2016)
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Titre : An interactive tool for semi-automatic feature extraction of hyperspectral data Type de document : Article/Communication Auteurs : Zoltan Kovacs, Auteur ; Szilárd Szabó, Auteur Année de publication : 2016 Article en page(s) : pp 493 - 502 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] extraction semi-automatique
[Termes IGN] image hyperspectrale
[Termes IGN] régression
[Termes IGN] spectrométrie
[Termes IGN] VBARésumé : (auteur) The spectral reflectance of the surface provides valuable information about the environment, which can be used to identify objects (e.g. land cover classification) or to estimate quantities of substances (e.g. biomass). We aimed to develop an MS Excel add-in – Hyperspectral Data Analyst (HypDA) – for a multipurpose quantitative analysis of spectral data in VBA programming language. HypDA was designed to calculate spectral indices from spectral data with user defined formulas (in all possible combinations involving a maximum of 4 bands) and to find the best correlations between the quantitative attribute data of the same object. Different types of regression models reveal the relationships, and the best results are saved in a worksheet. Qualitative variables can also be involved in the analysis carried out with separability and hypothesis testing; i.e. to find the wavelengths responsible for separating data into predefined groups. HypDA can be used both with hyperspectral imagery and spectrometer measurements. This bivariate approach requires significantly fewer observations than popular multivariate methods; it can therefore be applied to a wide range of research areas. Numéro de notice : A2016--071 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1515/geo-2016-0040 En ligne : https://doi.org/10.1515/geo-2016-0040 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84417
in Open geosciences > vol 8 n° 1 (January - July 2016) . - pp 493 - 502[article]A novel method to correct for wood MOE ultrasonics and NIRS measurements on increment cores in Liquidambar styraciflua L / Herizo Rakotovololonalimanana in Annals of Forest Science, vol 72 n° 6 (September 2015)
[article]
Titre : A novel method to correct for wood MOE ultrasonics and NIRS measurements on increment cores in Liquidambar styraciflua L Type de document : Article/Communication Auteurs : Herizo Rakotovololonalimanana, Auteur ; Gilles Chaix, Auteur ; Loïc Brancheriau, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 753 - 761 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse comparative
[Termes IGN] élasticité
[Termes IGN] image proche infrarouge
[Termes IGN] Liquidambar styraciflua
[Termes IGN] spectrométrie
[Termes IGN] télédétection acoustique
[Termes IGN] ultrasonRésumé : (auteur) Key message : Ultrasounds overestimate the MOE value. This paper analyses the causes of this difference and opens the perspective for a novel method allowing the calculation of the correct MOE from ultrasounds or NIRS measurements on cores.
Context : Standardized methods for determining wood modulus of elasticity (MOE) are destructive and require many replicates. Other methods such as NIRS and ultrasound have been developed to characterize wood properties and overcome these constraints.
Aim : The aim of this study was to compare the two MOE measurement methods (NIRS and ultrasound) applied to cores of wood taken from standing trees (Liquidambar styraciflua).
Methods : MOE, measured by an acoustic method in standard samples (360 × 20 × 20 mm), was used as a reference. Then MOE was predicted by an NIRS model and determined using ultrasound in standard samples (360 × 20 × 20 mm), small samples (10 × 20 × 20 mm), and cores (15 mm in diameter).
Result : MOE values determined by acoustic method on standard samples and by ultrasonic method on small samples were correlated (R 2 = 0.72) and were not statistically different. The NIRS PLS regression yielded a model with R 2 cv = 0.80. The link between NIRS and ultrasound on cores was statistically significant (R 2 = 0.68).
Conclusion : The ultrasonic technique determines an apparent modulus enables comparative data analysis. This apparent modulus can be used for quantitative analysis if a corrective model is used. A correction formula to ultrasonic MOE was proposed in the case of a prismatic geometry.Numéro de notice : A2015-409 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1007/s13595-015-0469-6 Date de publication en ligne : 12/03/2015 En ligne : https://doi.org/10.1007/s13595-015-0469-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76896
in Annals of Forest Science > vol 72 n° 6 (September 2015) . - pp 753 - 761[article]A fast classification scheme in Raman spectroscopy for the identification of mineral mixtures using a large database with correlated predictors / Corey J. Cochrane in IEEE Transactions on geoscience and remote sensing, vol 53 n° 8 (August 2015)
[article]
Titre : A fast classification scheme in Raman spectroscopy for the identification of mineral mixtures using a large database with correlated predictors Type de document : Article/Communication Auteurs : Corey J. Cochrane, Auteur ; Jordana Blacksberg, Auteur Année de publication : 2015 Article en page(s) : pp 4259 - 4274 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Rayonnement électromagnétique
[Termes IGN] classification automatique
[Termes IGN] diffusion de Raman
[Termes IGN] régression
[Termes IGN] spectroscopieRésumé : (Auteur) Robust classification methods are vital to the successful implementation of many material characterization techniques, particularly where large databases exist. In this paper, we demonstrate an extremely fast classification method for the identification of mineral mixtures in Raman spectroscopy using the large RRUFF database. However, this method is equally applicable to other techniques meeting the large database criteria, these including laser-induced breakdown, X-ray diffraction, and mass spectroscopy methods. Classification of these multivariate datasets can be challenging due in part to the various obscuring features inherently present within the underlying dataset and in part to the volume and variety of information known a priori. Some of the more specific challenges include the observation of mixtures with overlapping spectral features, the use of large databases (i.e., the number of predictors far outweighs the number of observations), the use of databases that contain groups of correlated spectra, and the ever present, clouding contaminants of noise, undesired background, and spectrometer artifacts. Although many existing classification algorithms attempt to address these problems individually, not many address them as a whole. Here, we apply a multistage approach, which leverages well-established constrained regression techniques, to overcome these challenges. Our modifications to conventional algorithm implementations are shown to increase speed and performance of the classification process. Unlike many other techniques, our method is able to rapidly classify mixtures while simultaneously preserving sparsity. It is easily implemented, has very few tuning parameters, does not require extensive parameter training, and does not require data dimensionality reduction prior to classification. Numéro de notice : A2015-386 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2394377 En ligne : https://doi.org/10.1109/TGRS.2015.2394377 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76864
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 8 (August 2015) . - pp 4259 - 4274[article]Réservation
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