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Wavelet decomposition of hyperspectral data: a novel approach to quantifying pigment concentrations in vegetation / G. Blackburn in International Journal of Remote Sensing IJRS, vol 28 n°11-12 (June 2007)
[article]
Titre : Wavelet decomposition of hyperspectral data: a novel approach to quantifying pigment concentrations in vegetation Type de document : Article/Communication Auteurs : G. Blackburn, Auteur Année de publication : 2007 Article en page(s) : pp 2831 - 2855 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] chlorophylle
[Termes IGN] coefficient de rétrodiffusion
[Termes IGN] image hyperspectrale
[Termes IGN] modèle de simulation
[Termes IGN] réflectance
[Termes IGN] réflectance végétale
[Termes IGN] transformation en ondelettesRésumé : (Auteur) This paper reports a new approach for quantifying vegetation pigment concentrations through wavelet decomposition of hyperspectral remotely sensed data. Wavelets are a group of functions that vary in complexity and mathematical properties, that are used to dissect data into different frequency components and then characterize each component with a resolution appropriate to its scale. Wavelet analysis of a reflectance spectrum is performed by scaling and shifting the wavelet function to produce wavelet coefficients that are assigned to different frequency components. By selecting appropriate wavelet coefficients, a spectral model can be established between the coefficients and biochemical concentrations. Hence, wavelet analysis has the potential to capture much more of the information contained within high-resolution spectra than previous approaches and offers the prospect of developing robust, generic methods for pigment determinations. The capabilities of the wavelet-based technique were examined using reflectance spectra and pigment data collected for a range of plant species at leaf and canopy scales. For the combined data set and all of the individual vegetation types, methods based on wavelet decomposition appreciably outperformed narrowband spectral indices and stepwise selection of narrowband reflectance. However, there was variation between vegetation types in the relative performance of the three different feature extraction techniques employed for selecting the wavelet coefficients for use in predictive models. There was also considerable variability in the performance of predictive models according to the wavelet function used for spectral decomposition and the optimum wavelet functions differed between vegetation types and between individual pigments within the same vegetation type. The research indicates that wavelet analysis holds promise for the accurate determination of chlorophyll a and b and the carotenoids, but further work is needed to refine the approach. Copyright Taylor & Francis Numéro de notice : A2007-311 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160600928625 En ligne : https://doi.org/10.1080/01431160600928625 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28674
in International Journal of Remote Sensing IJRS > vol 28 n°11-12 (June 2007) . - pp 2831 - 2855[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-07071 RAB Revue Centre de documentation En réserve L003 Disponible Mapping an invasive plant, Phragmites australis [roseau], in coastal wetlands using the EO-1 Hyperion hyperspectral sensor / B.W. Pengra in Remote sensing of environment, vol 108 n° 1 (15/05/2007)
[article]
Titre : Mapping an invasive plant, Phragmites australis [roseau], in coastal wetlands using the EO-1 Hyperion hyperspectral sensor Type de document : Article/Communication Auteurs : B.W. Pengra, Auteur ; C.A. Johnston, Auteur ; T.R. Loveland, Auteur Année de publication : 2007 Article en page(s) : pp 74 - 81 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte thématique
[Termes IGN] espèce exotique envahissante
[Termes IGN] Grands Lacs
[Termes IGN] image EO1-Hyperion
[Termes IGN] image hyperspectrale
[Termes IGN] marais
[Termes IGN] phytogéographie
[Termes IGN] plante aquatique d'eau salée
[Termes IGN] répartition géographique
[Termes IGN] Wisconsin (Etats-Unis)Résumé : (Auteur) Mapping tools are needed to document the location and extent of Phragmites australis, a tall grass that invades coastal marshes throughout North America, displacing native plant species and degrading wetland habitat. Mapping Phragmites is particularly challenging in the freshwater Great Lakes coastal wetlands due to dynamic lake levels and vegetation diversity. We tested the applicability of Hyperion hyperspectral satellite imagery for mapping Phragmites in wetlands of the west coast of Green Bay in Wisconsin, U.S.A. A reference spectrum created using Hyperion data from several pure Phragmites stands within the image was used with a Spectral Correlation Mapper (SCM) algorithm to create a raster map with values ranging from 0 to 1, where 0 represented the greatest similarity between the reference spectrum and the image spectrum and 1 the least similarity. The final two-class thematic classification predicted monodominant Phragmites covering 3.4% of the study area. Most of this was concentrated in long linear features parallel to the Green Bay shoreline, particularly in areas that had been under water only six years earlier when lake levels were 66 cm higher. An error matrix using spring 2005 field validation points (n = 129) showed good overall accuracy—81.4%. The small size and linear arrangement of Phragmites stands was less than optimal relative to the sensor resolution, and Hyperion's 30 m resolution captured few if any pure pixels. Contemporary Phragmites maps prepared with Hyperion imagery would provide wetland managers with a tool that they currently lack, which could aid attempts to stem the spread of this invasive species. Copyright Elsevier Numéro de notice : A2007-217 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2006.11.002 En ligne : https://doi.org/10.1016/j.rse.2006.11.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28580
in Remote sensing of environment > vol 108 n° 1 (15/05/2007) . - pp 74 - 81[article]Estimating spatial patterns of rainfall interception from remotely sensed vegetation indices and spectral mixture analysis / S.M. de Jong in International journal of geographical information science IJGIS, vol 21 n° 5 (may 2007)
[article]
Titre : Estimating spatial patterns of rainfall interception from remotely sensed vegetation indices and spectral mixture analysis Type de document : Article/Communication Auteurs : S.M. de Jong, Auteur ; V.G. Jetten, Auteur Année de publication : 2007 Article en page(s) : pp 529 - 545 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] érosion hydrique
[Termes IGN] évapotranspiration
[Termes IGN] image HYMAP
[Termes IGN] image hyperspectrale
[Termes IGN] indice de végétation
[Termes IGN] Leaf Area Index
[Termes IGN] pluie
[Termes IGN] ruissellementRésumé : (Auteur) Rainfall interception by vegetation is an important factor in the water balance. Consequently, rainfall interception should also be an important factor in models simulating processes such as evaporation, transpiration, surface runoff, soil erosion, and crop growth. In practice, however, it is difficult to make quantitative assessments of the spatial and temporal distribution of rainfall interception loss at the catchment level, for instance, and to make these values available as model input. In this paper, we present a novel method using earth observation images to estimate local quantitative values of rainfall interception loss. Leaf Area Index (LAI) and fractional vegetation cover per grid cell are important process variables for rainfall interception. These two variables are estimated from images using spectral vegetation indices and using spectral mixture analysis, respectively. Relations between canopy storage capacity and LAI exist for several plant species and vegetation types, but limited data are found on crops, and more research is needed in this field. The new method is explained and illustrated for a study area in southern France with a variety of land-cover types. It is found to be a valuable and practical approach to quantitatively assess spatial patterns of interception loss for given rainfall events. Copyright Taylor & Francis Numéro de notice : A2007-135 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/13658810601064884 En ligne : https://doi.org/10.1080/13658810601064884 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28498
in International journal of geographical information science IJGIS > vol 21 n° 5 (may 2007) . - pp 529 - 545[article]Exemplaires(2)
Code-barres Cote Support Localisation Section Disponibilité 079-07031 RAB Revue Centre de documentation En réserve L003 Disponible 079-07032 RAB Revue Centre de documentation En réserve L003 Disponible Comparison between several feature extraction/classification methods for mapping complicated agricultural land use patches using airborne hyperspectral data / S. Lu in International Journal of Remote Sensing IJRS, vol 28 n°5-6 (March 2007)
[article]
Titre : Comparison between several feature extraction/classification methods for mapping complicated agricultural land use patches using airborne hyperspectral data Type de document : Article/Communication Auteurs : S. Lu, Auteur ; K. Oki, Auteur Année de publication : 2007 Article en page(s) : pp 963 - 984 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] agriculture
[Termes IGN] analyse comparative
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification dirigée
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] extraction automatique
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] image aérienne
[Termes IGN] image hyperspectrale
[Termes IGN] précision de la classification
[Termes IGN] surface cultivée
[Termes IGN] Tokyo (Japon)
[Termes IGN] utilisation du solRésumé : (Auteur) Airborne hyperspectral remote sensing was applied to agricultural land in the Miura Peninsula, near the metropolis of Tokyo in Japan. The study area is characterized by complicated land use patches, which is the general characteristic of most agricultural lands in Japan. Several feature extraction/classification methods were examined in classifying the land use and plant species. The results showed that decision boundary feature extraction (DBFE) was better than principal component analysis (PCA) as the feature extraction method. Moreover, the pre-classification process using NDVI that separates the whole study area into vegetated area and non-vegetated areas also improved the classification accuracy. After the pre-procedures, the land use and plant species were finally mapped by maximum likelihood classification (MLC) or extraction and classification of homogeneous objects (ECHO). The best kappa (overall accuracy) of classification was 0.914 (92.4%) and 0.924 (93.3%) for MLC and ECHO, respectively. The best accuracies of each category for the image were 79.5% to 100% for plant species (watermelon, pumpkin, marigold, grass and tree), 88.7% to 100% for soil types, 97.8% for concrete, and 99.4% for vinyl-mulches. Although, built-up area has low estimation accuracy, this did not affect the overall classification accuracy because it covers only a very small area. Copyright Taylor & Francis Numéro de notice : A2007-097 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160600771561 En ligne : https://doi.org/10.1080/01431160600771561 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28462
in International Journal of Remote Sensing IJRS > vol 28 n°5-6 (March 2007) . - pp 963 - 984[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-07031 RAB Revue Centre de documentation En réserve L003 Disponible Retrieval of suspended sediment from advanced hyperspectral sensor data in the Scheldt estuary at different stages in the tidal cycle / S. Sterckx in Marine geodesy, vol 30 n° 1-2 (March - June 2007)
[article]
Titre : Retrieval of suspended sediment from advanced hyperspectral sensor data in the Scheldt estuary at different stages in the tidal cycle Type de document : Article/Communication Auteurs : S. Sterckx, Auteur ; E. Knaeps, Auteur ; M. Bollen, Auteur ; K. Trouw, Auteur ; R. Houthuys, Auteur Année de publication : 2007 Article en page(s) : pp 97 - 108 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Belgique
[Termes IGN] carte pédologique
[Termes IGN] estuaire
[Termes IGN] image aérienne
[Termes IGN] image AHS
[Termes IGN] image hyperspectrale
[Termes IGN] matière organique
[Termes IGN] rayonnement proche infrarouge
[Termes IGN] réflectance
[Termes IGN] rivière
[Termes IGN] sédiment
[Termes IGN] turbidité des eauxRésumé : (Auteur) Hyperspectral airborne remote sensing images and in-situ data are combined to assess the spatial and temporal sediment dynamics in the tidal Scheldt river. A log-linear empirical relationship has been developed between a near-infrared reflectance difference and total suspended matter. The relationship was shown to be relatively insensitive to the varying cirrus cloud cover occurring during data acquisition. The produced sediment maps show good agreement with known variations of turbidity over the tidal cycle: maximum turbidity around high water, gradual settling of the sediment in the succeeding slack water and resuspension at the onset of the ebb flow stage. Copyright Taylor & Francis Numéro de notice : A2007-437 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/01490410701296341 En ligne : https://doi.org/10.1080/01490410701296341 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28800
in Marine geodesy > vol 30 n° 1-2 (March - June 2007) . - pp 97 - 108[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 230-07011 RAB Revue Centre de documentation En réserve L003 Disponible Spectral analysis of coastal vegetation and land cover using AISA+ hyperspectral data / R. Jensen in Geocarto international, vol 22 n° 1 (March - May 2007)PermalinkExtraction of spectral channels from hyperspectral images for classification purposes / S.B. Serpico in IEEE Transactions on geoscience and remote sensing, vol 45 n° 2 (February 2007)PermalinkMonitoring spatio-temporal dynamics of photosynthesis with a portable hyperspectral imaging system / U. Rascher in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 1 (January 2007)PermalinkMapping salt-marsh vegetation by multispectral and hyperspectral remote sensing / E. Belluco in Remote sensing of environment, vol 105 n° 1 (15/11/2006)PermalinkExploiting class hierarchies for knowledge transfer in hyperspectral data / S. Rajan in IEEE Transactions on geoscience and remote sensing, vol 44 n° 11 Tome 2 (November 2006)PermalinkEvaluation of hyperspectral data for geological mapping / Muneendra Kumar in Geoinformatics, vol 9 n° 6 (01/09/2006)PermalinkMapping carbon and water vapor fluxes in a chaparral ecosystem using vegetation indices derived from AVIRIS / D.A. Fuentes in Remote sensing of environment, vol 103 n° 3 (15 August 2006)PermalinkA patch-based image classification by integrating hyperspectral data with GIS / B. Zhang in International Journal of Remote Sensing IJRS, vol 27 n°15-16 (August 2006)PermalinkA support vector method for anomaly detection in hyperspectral imagery / Amit Banerjee in IEEE Transactions on geoscience and remote sensing, vol 44 n° 8 (August 2006)PermalinkSome issues in the classification of DAIS hyperspectral data / M. Pal in International Journal of Remote Sensing IJRS, vol 27 n°12-13-14 (July 2006)PermalinkConsideration of smoothing techniques for hyperspectral remote sensing / C. Vaiphasa in ISPRS Journal of photogrammetry and remote sensing, vol 60 n° 2 (April 2006)PermalinkRelevance of hyperspectral data for natural resources management / T.V. Ramachandra in GIS development, vol 10 n° 4 (April 2006)PermalinkNoise reduction of hyperspectral imagery using hybrid spatial-spectral derivative-domain wavelet shrinkage / H. Othman in IEEE Transactions on geoscience and remote sensing, vol 44 n° 2 (February 2006)PermalinkAn empirical investigation of cross-sensor relationships of NDVI and red/near-infrared reflectance using EO-1 Hyperion data / T. Miura in Remote sensing of environment, vol 100 n° 2 (30 January 2006)PermalinkCompression des images hyperspectrales et son impact sur la qualité des données / E. Christophe (2006)PermalinkResource management information systems / K.R. Mccloy (2006)PermalinkSampling scheme optimization from hyperspectral data / Pravesh Debba (2006)PermalinkMapping impervious surface type and sub-pixel abundance using Hyperion hyperspectral imagery / J. Falcone in Geocarto international, vol 20 n° 4 (December 2005 - February 2006)PermalinkA method for the surface reflectance retrieval from PROBA/CHRIS data over land: application to ESA SPARC campaigns / L. Guanter in IEEE Transactions on geoscience and remote sensing, vol 43 n° 12 (December 2005)PermalinkFusion of hyperspectral data using segmented PCT for color representation and classification / V. Tsagaris in IEEE Transactions on geoscience and remote sensing, vol 43 n° 10 (October 2005)PermalinkQuality criteria benchmark for hyperspectral imagery / E. Christophe in IEEE Transactions on geoscience and remote sensing, vol 43 n° 9 (September 2005)PermalinkDe-shadowing of satellite/airborne imagery / R. Richter in International Journal of Remote Sensing IJRS, vol 26 n° 15 (August 2005)PermalinkPermalinkA statistical self-organizing learning system for remote sensing classification / H.M. Chi in IEEE Transactions on geoscience and remote sensing, vol 43 n° 8 (August 2005)PermalinkA whole image approach using field measurements for transforming EO1 Hyperion hyperspectral data into canopy reflectance spectra / E.W. Ramsey in International Journal of Remote Sensing IJRS, vol 26 n° 8 (April 2005)PermalinkIntegration of spatial and spectral information by means of unsupervised extraction and classification for homogenous objects applied to multispectral and hyperspectral data / L.O. Jimenez in IEEE Transactions on geoscience and remote sensing, vol 43 n° 4 (April 2005)PermalinkAn automatic nonlinear correlation approach for processing of hyperspectral images / R.N. Ingram in International Journal of Remote Sensing IJRS, vol 25 n° 22 (November 2004)PermalinkThe development of superspectral approaches for the improvement of land cover classification / M. Gianinetto in IEEE Transactions on geoscience and remote sensing, vol 42 n° 11 (November 2004)PermalinkEvaluation of hyperspectral remote sensing as a means of environmental monitoring in the St Austell China clay (kaolin) region, Cornwall, UK / R.J. Ellis in Remote sensing of environment, vol 93 n° 1 (30/10/2004)PermalinkEvaluating airborne hyperspectral imagery for rangeland assessment in south Texas / James H. Everitt in Geocarto international, vol 19 n° 3 (September - November 2004)PermalinkUse of hyperspectral derivative ratios in the red-edge region to identify plant stress responses to gas leaks / K.L. Smith in Remote sensing of environment, vol 92 n° 2 (15/08/2004)PermalinkClassification of hyperspectral remote sensing images with support vector machines / F. Melgani in IEEE Transactions on geoscience and remote sensing, vol 42 n° 8 (August 2004)PermalinkIntegrating imaging spectroscopy (445-2543nm) and geographic information systems for post-disaster management: a case of hailstorm damage in Sydney / S. Bhaskaran in International Journal of Remote Sensing IJRS, vol 25 n° 13 (July 2004)PermalinkMapping coastal vegetation using an expert system and hyperspectral imagery / K.S. Schmidt in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 6 (June 2004)PermalinkWavelet transform applied to EO-1 hyperspectral data for forest LAI and crown closure mapping / R. Pu in Remote sensing of environment, vol 91 n° 2 (30/05/2004)PermalinkClassification of contamination in salt marsh plant using hyperspectral reflectance / M.D. Wilson in IEEE Transactions on geoscience and remote sensing, vol 42 n° 5 (May 2004)PermalinkRefinement of wavelength calibrations of hyperspectral imaging data using a spectrum-machine technique / B.C. Gao in Remote sensing of environment, vol 90 n° 4 (30/04/2004)PermalinkClassification of remotely sensed imagery stochastic gradient boosting as a refinement of classification tree analysis / R. Lawrence in Remote sensing of environment, vol 90 n° 3 (15/04/2004)PermalinkHyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: modelling and validation in the context of precision agriculture / D. Haboudane in Remote sensing of environment, vol 90 n° 3 (15/04/2004)PermalinkLinear mixture analysis-based compression for hyperspectral image analysis / Q. Du in IEEE Transactions on geoscience and remote sensing, vol 42 n° 4 (April 2004)PermalinkIntegrating imaging spectroscopy and neural networks to map grass quality in the Kruger National Park, South Africa / Onisimo Mutanga in Remote sensing of environment, vol 90 n° 1 (15/03/2004)PermalinkLa télédétection avec ENVI / Françoise de Blomac in SIG la lettre, n° 55 (mars 2004)PermalinkPredicting in situ pasture quality in the Kruger National Park, South Africa, using continuum-removed absorption features / Onisimo Mutanga in Remote sensing of environment, vol 89 n° 3 (15/02/2004)PermalinkMapping coal fires based on OMIS1 thermal infrared band image / Y. Wan in International Journal of Remote Sensing IJRS, vol 25 n° 3 (February 2004)PermalinkUnsupervised classification of hyperspectral data: an ICA mixture model based approach / Chintan A. Shah in International Journal of Remote Sensing IJRS, vol 25 n° 2 (January 2004)Permalink