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Systematic corrections of AVHRR image composites for temporal studies / J. Cihlar in Remote sensing of environment, vol 89 n° 2 (30/01/2004)
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Titre : Systematic corrections of AVHRR image composites for temporal studies Type de document : Article/Communication Auteurs : J. Cihlar, Auteur ; R. Latifovic, Auteur ; et al., Auteur Année de publication : 2004 Article en page(s) : pp 217 - 233 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] correction d'image
[Termes IGN] distribution du coefficient de réflexion bidirectionnelle BRDF
[Termes IGN] image en couleur composée
[Termes IGN] image Landsat-TM
[Termes IGN] image NOAA-AVHRR
[Termes IGN] réflectance végétaleRésumé : (Auteur) For quantitative studies of vegetation dynamics, satellite data need to be corrected for spurious effects. In this study, we have applied several changes to an earlier advanced very high resolution radiometer (AVHRR) processing methodology (ABC3; [Remote Sens. Environ. 60 (1997) 35; J. Geophys. Res.Atmos, 102 (1997) 29625; Can. J. Remote Sens. 23 (1997) 163]), to better represent the various physical processes causing contamination of the AVHRR measurements. These included published recent estimates of the NOAA-11 and NOAA-14 AVHRR calibration trajectories for channels 1 and 2; the best available estimates for the water vapour, aerosol and ozone amounts at the time of AVHRR data acquisition; an improved bidirectional reflectance algorithm that also takes into consideration surface topography; and an improved image screening algorithm for contaminated pixels. Unlike the previous study that compared the composite images to a single-date AVHRR image, we employed coincident TM images to approximate the AVHRR pixel field of view during the data acquisition. Compared to ABC3, the modified procedure ABOV2 was found to improve the accuracy of AVHRR pixel reflectance estimates, both in the sensitivity (slope) of the regression and in r2. The improvements were especially significant in AVHRR channel 1. In comparison with reference values derived from two full TM scenes, the corrected AVHRR surface reflectance estimates had average standard errors values of + 0.009 for AVHRR C1, + 0.019 for C2, and + 0.04 for NDVI; the corresponding r2 values were 0.55, 0.80, and 0.50, respectively. The changes in ABC3V2 were not able to completely remove interannual variability for land cover types with little or no vegetation cover, which would be expected to remain stable over time, and they increased the interannual variability of mixed forest and grassland. These results are attributed to a combination of increased sensitivity to interannual dynamics on one hand, and the inability to remove all sources of noise for barren or sparsely vegetated northern land cover types on the other. Numéro de notice : A2004-025 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2002.06.007 En ligne : https://doi.org/10.1016/j.rse.2002.06.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26553
in Remote sensing of environment > vol 89 n° 2 (30/01/2004) . - pp 217 - 233[article]Unsupervised 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)
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Titre : Unsupervised classification of hyperspectral data: an ICA mixture model based approach Type de document : Article/Communication Auteurs : Chintan A. Shah, Auteur ; M.K. Arora, Auteur ; P.K. Varshney, Auteur Année de publication : 2004 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse en composantes indépendantes
[Termes IGN] classification non dirigée
[Termes IGN] image AVIRIS
[Termes IGN] image hyperspectrale
[Termes IGN] précision de la classificationRésumé : (Auteur) Conventional unsupervised classification algorithms that model the data in each class with a multivariate Gaussian distribution are often inappropriate, as this assumption is frequently not satisfied by the remote sensing data. In this Letter, a new algorithm based on independent component analysis (ICA) is presented. The ICA mixture model (ICAMM) algorithm that models class distributions as non-Gaussian densities has been employed for unsupervised classification of a test image from the AVIRIS sensor. A number of feature-extraction techniques have also been examined that serve as a preprocessing step to reduce the dimensionality of the hyperspectral data. The proposed ICAMM algorithm results in significant increase in the classification accuracy over that obtained from the conventional K-means algorithm for land cover classification. Numéro de notice : A2004-060 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160310001618040 En ligne : https://doi.org/10.1080/01431160310001618040 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26588
in International Journal of Remote Sensing IJRS > vol 25 n° 2 (January 2004)[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-04021 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Within-field wheat yield prediction from Ikonos data: a new matrix approach / E.A. Enclona in International Journal of Remote Sensing IJRS, vol 25 n° 2 (January 2004)
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Titre : Within-field wheat yield prediction from Ikonos data: a new matrix approach Type de document : Article/Communication Auteurs : E.A. Enclona, Auteur ; Prasad S. Thenkabail, Auteur ; D. Celis, Auteur ; J. Diekmann, Auteur Année de publication : 2004 Article en page(s) : pp 377 - 388 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] agriculture de précision
[Termes IGN] blé (céréale)
[Termes IGN] carte agricole
[Termes IGN] image Ikonos
[Termes IGN] pixel
[Termes IGN] rendement agricoleRésumé : (Auteur) This study demonstrates a unique matrix approach to determine within-field variability in wheat yields using fine spatial resolution 4 m IKONOS data. The matrix approach involves solving a system of simultaneous equations based on IKONOS data and post-harvest yields available at entire field scale. This approach was compared with a regression-based modelling approach involving field-sensor measured yields and the corresponding IKONOS measured indices and wavebands. The IKONOS data explained 74-78% variability in wheat yield. This is a significant result since the finer spatial resolution leads to capturing greater spatial variability and detail in landscape relative to coarser spatial resolution data. A pixel-by-pixel mapping of wheat yield variability highlights the fine spatial detail provided by IKONOS data for precision farming applications. Numéro de notice : A2004-056 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/0143116031000102485 En ligne : https://doi.org/10.1080/0143116031000102485 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26584
in International Journal of Remote Sensing IJRS > vol 25 n° 2 (January 2004) . - pp 377 - 388[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-04021 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Hyperspectral monitoring of physiological parameters of wheat during a vegetation period using AVIS data / N. Oppelt in International Journal of Remote Sensing IJRS, vol 25 n° 1 (January 2004)
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Titre : Hyperspectral monitoring of physiological parameters of wheat during a vegetation period using AVIS data Type de document : Article/Communication Auteurs : N. Oppelt, Auteur ; W. Mauser, Auteur Année de publication : 2004 Article en page(s) : pp 145 - 159 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse de données
[Termes IGN] analyse diachronique
[Termes IGN] Bavière (Allemagne)
[Termes IGN] blé (céréale)
[Termes IGN] classificateur paramétrique
[Termes IGN] hétérogénéité sémantique
[Termes IGN] image AVIRIS
[Termes IGN] image hyperspectrale
[Termes IGN] indice de végétation
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] réflectance végétale
[Termes IGN] saison
[Termes IGN] surveillance agricole
[Termes IGN] zone humideRésumé : (Auteur) Information on the quantity and spatial distribution of canopy physiological and biochemical components is of importance for the study of nutrient cycles, productivity, vegetation stress and, more recently, in driving ecosystem models. In this context, remote sensing can play a unique and essential role because of its ability to acquire synoptic information at different time and space scales. This paper presents parts of a two-year field and laboratory study with the new airborne hyperspectral sensor, the Airborne Visible near Infrared Imaging Spectrometer (AVIS), over a test site in the Bavarian Alpine foothills, Germany (48' 8'N, 11°17' E ). The 80-band AVIS was developed at the Department for Earth and Environmental Sciences of the LudwigMaximiliansUniversity Munich and records the 550-1000 mn spectral range. Using this system, 18 hyperspectral datasets were collected between April and September of 1999 and 2000. Weekly measurements of several plant parameters (height, biomass, leaf chlorophyll content, leaf nitrogen content) were carried out during these time periods on three (1999) and six (2000) fields of winter wheat, whereby two different cultivars were investigated in 2000. After system correction and calibration, the hyperspectral data were atmospherically corrected and calibrated to reflectance. The resulting spectra were analysed for their chemical compounds. The statistical analysis was carried out using the Chlorophyll Absorption Integral (CAI) in comparison to established indices: Optimized Soil-Adjusted Vegetation Index (OSAVI) and hyperspectral Normalized Difference Vegetation Index (hNDVI). Both the chlorophyll and nitrogen content of the leaves showed good correlations with CAI on a field mean basis. These results as well as two-dimensional information on these parameters are presented to provide information about the spatial heterogeneity within a field. Numéro de notice : A2004-036 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/0143116031000115300 En ligne : https://doi.org/10.1080/0143116031000115300 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26564
in International Journal of Remote Sensing IJRS > vol 25 n° 1 (January 2004) . - pp 145 - 159[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-04011 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Spectral characteristics and feature selection of hyperspectral remote sensing data / X. Jiang in International Journal of Remote Sensing IJRS, vol 25 n° 1 (January 2004)
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Titre : Spectral characteristics and feature selection of hyperspectral remote sensing data Type de document : Article/Communication Auteurs : X. Jiang, Auteur ; L. Tanguy, Auteur Année de publication : 2004 Article en page(s) : pp 51 - 59 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification
[Termes IGN] image hyperspectrale
[Termes IGN] index spatial
[Termes IGN] Pékin (Chine)
[Termes IGN] signature spectrale
[Termes IGN] spectromètre imageurRésumé : (Auteur) Hyperspectral remote sensing data with bandwidth of nanometre (nm) level have tens or even several hundreds of channels and contain abundant spectral information. Different channels have their own properties and show the spectral characteristics of various objects in image. Rational feature selection from the varieties of channels is very important for effective analysis and information extraction of hyperspectral data. This paper, taking Shunyi region of Beijing as a study area, comprehensively analysed the spectral characteristics of hyperspectral data. On the basis of analysing the information quantity of bands, correlation between different bands, spectral absorption characteristics of objects and object separability in bands, a fundamental method of optimum band selection and feature extraction from hyperspectral remote sensing data was proposed. Numéro de notice : A2004-035 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/0143116031000115292 En ligne : https://doi.org/10.1080/0143116031000115292 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26563
in International Journal of Remote Sensing IJRS > vol 25 n° 1 (January 2004) . - pp 51 - 59[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-04011 RAB Revue Centre de documentation En réserve L003 Exclu du prêt PermalinkAutomated subpixel photobathymetry and water quality mapping / R.L. Huguenin in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 1 (January 2004)
PermalinkBayesian-based subpixel brightness temperature estimation from multichannel infrared GOES radiometer data / S. Cain in IEEE Transactions on geoscience and remote sensing, vol 42 n° 1 (January 2004)
PermalinkCartographie des rizières d'une zone des hautes terres centrales de Madagascar pour la détermination des zones à risque du paludisme / F. Thomas (2004)
PermalinkComparing cooccurrence probabilities and Markov random fields for texture analysis of SAR sea ice imagery / D.A. Clausi in IEEE Transactions on geoscience and remote sensing, vol 42 n° 1 (January 2004)
PermalinkDetecting building changes from multitemporal aerial stereopairs / Franck Jung in ISPRS Journal of photogrammetry and remote sensing, vol 58 n° 3-4 (January - June 2004)
PermalinkPermalinkPermalinkImage Analysis and Recognition, International Conference, ICIAR 2004, Porto, Portugal, September-October 2004, Part 1. Proceedings / Aurélio Campilho (2004)
PermalinkPermalinkPermalinkPermalinkPermalinkRecalage vectoriel 3D de contours de bâtiments à partir d'un couple d'images aériennes stéréoscopiques / D. Rambourg (2004)
PermalinkSimultane Schätzung von Topographie und Dynamik polarer Gletscher aus multi-temporalen SAR Interferogrammen / F.J. Meyer (2004)
PermalinkPermalinkUsing textural and geometric information for an automatic bridge detection system / Roger Trias-Sanz (2004)
PermalinkUtilisation de simulations d'images hyperspectrales à partir de base de données 3D pour la spécification de futurs capteurs spatiaux / Audrey Malherbe (2004)
PermalinkClassification of wheat crop with multi-temporal images: performance of maximum likelihood and artificial neural networks / C.S. Murthy in International Journal of Remote Sensing IJRS, vol 24 n° 23 (December 2003)
PermalinkGeometric processing of hyperspectral image data acquired by VIFIS on board light aircraft / Y. Gu in International Journal of Remote Sensing IJRS, vol 24 n° 23 (December 2003)
PermalinkSpatial resolution improvement of remote sensing images by fusion of subpixel-shifted multi-observation images / Y. Lu in International Journal of Remote Sensing IJRS, vol 24 n° 23 (December 2003)
PermalinkAutomatic satellite image georeferencing using a contour-matching approach / Francisco Eugenio in IEEE Transactions on geoscience and remote sensing, vol 41 n° 12 (December 2003)
PermalinkA cognitive pyramid for contextual classification of remote sensing images / E. Binaghi in IEEE Transactions on geoscience and remote sensing, vol 41 n° 12 (December 2003)
PermalinkCombining metric aerial photography and near-infrared videography to define within-field soil sampling frameworks / G.G. Wright in Geocarto international, vol 18 n° 4 (December 2003 - February 2004)
PermalinkMapping urban areas by fusing multiple sources of coarse resolution remotely sensed data / A.M. Schneider in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 12 (December 2003)
PermalinkIkonos satellite, imagery, and products / G. Dial in Remote sensing of environment, vol 88 n° 1 (30/11/2003)
PermalinkIkonos spatial resolution and image interpretability characterization / R. Ryan in Remote sensing of environment, vol 88 n° 1 (30/11/2003)
PermalinkRadiometric characterization of Ikonos multispectral imagery / M. Pagnutti in Remote sensing of environment, vol 88 n° 1 (30/11/2003)
PermalinkPlanimetric accuracy of Ikonos 1m panchromatic orthoimage products and their utility for local government GIS basemap applications / C.H. Davis in International Journal of Remote Sensing IJRS, vol 24 n° 22 (November 2003)
PermalinkMapping forest degradation in the Eastern Amazon SPOT 4 through spectral mixture models / Cristiano B. Souza in Remote sensing of environment, vol 87 n° 4 (15/11/2003)
PermalinkSpectral reflectance characterization of shallow lakes from the Brazilian pantanal wetlands with field and airborne hyperspectral data / L.S. Galvao in International Journal of Remote Sensing IJRS, vol 24 n° 21 (November 2003)
PermalinkStudy of urban spatial patterns from SPOT panchromatic imagery using textural analysis / Qian Zhang in International Journal of Remote Sensing IJRS, vol 24 n° 21 (November 2003)
PermalinkAutomated change detection for updates of digital map databases / T. Knudsen in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 11 (November 2003)
PermalinkA credit assignment approach to fusing classifiers of multiseason hyperspectral imagery / C. Bachmann in IEEE Transactions on geoscience and remote sensing, vol 41 n° 11 (November 2003)
PermalinkA new maximum-likelihood joint segmentation technique for multitemporal SAR and multiband optical images / P. Lombardo in IEEE Transactions on geoscience and remote sensing, vol 41 n° 11 (November 2003)
PermalinkStatistical and operational performance assessment of multitemporal SAR image filtering / Emmanuel Trouvé in IEEE Transactions on geoscience and remote sensing, vol 41 n° 11 (November 2003)
PermalinkIncreasing the spatial resolution of agricultural land cover maps using a Hopfield neural network / A.J. Tatem in International journal of geographical information science IJGIS, vol 17 n° 7 (october 2003)
PermalinkPermalinkLes surfaces inondées dans le delta intérieur du Niger au Mali par NOAA/AVHRR / A. Mariko in Bulletin [Société Française de Photogrammétrie et Télédétection], n° 172 (Octobre 2003)
PermalinkAirborne forest fire mapping with an adaptive infrared sensor / D. Oertel in International Journal of Remote Sensing IJRS, vol 24 n° 18 (September 2003)
PermalinkDetection of a landslide movement as geometric misregistration in image matching of SPOT HRV data of two different dates / Yasushi Yamaguchi in International Journal of Remote Sensing IJRS, vol 24 n° 18 (September 2003)
PermalinkGeometric information from Ikonos: strict and highly accurate solution based on VirtuoZo / Z. Hu in GIM international, vol 17 n° 9 (September 2003)
PermalinkA hierarchical fuzzy classification approach for high-resolution multispectral data over urban areas / A.K. Shackelford in IEEE Transactions on geoscience and remote sensing, vol 41 n° 9 (September 2003)
PermalinkImprovements to urban area characterization using multitemporal and multiangle SAR images / F. Dell'acqua in IEEE Transactions on geoscience and remote sensing, vol 41 n° 9 (September 2003)
PermalinkImproving the performance of classifiers in high-dimensional remote sensing applications: an adaptive resampling strategy for error-prone exemplars / C. Bachmann in IEEE Transactions on geoscience and remote sensing, vol 41 n° 9 (September 2003)
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