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Multi-platform comparisons of MODIS and AVHRR normalized difference vegetation index data / K. Gallo in Remote sensing of environment, vol 99 n° 3 (30/11/2005)
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Titre : Multi-platform comparisons of MODIS and AVHRR normalized difference vegetation index data Type de document : Article/Communication Auteurs : K. Gallo, Auteur ; L. Ji, Auteur ; et al., Auteur Année de publication : 2005 Article en page(s) : pp 221 - 231 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse comparative
[Termes IGN] capteur (télédétection)
[Termes IGN] image NOAA-AVHRR
[Termes IGN] image Terra-MODIS
[Termes IGN] Normalized Difference Vegetation IndexRésumé : (Auteur) The relationship between AVHRR-derived normalized difference vegetation index (NDVI) values and those of future sensors is critical to continued long-term monitoring of land surface properties. The follow-on operational sensor to the AVHRR, the Visible/Infrared Imager/ Radiometer Suite (VIIRS), will be very similar to the NASA Earth Observing System's Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. NDVI data derived from visible and near-infrared data acquired by the MODIS (Terra and Aqua platforms) and AVHRR (NOAA-16 andNOAA-17) sensors were compared over the same time periods and a variety of land cover classes within the conterminous United States. The results indicate that the 16-day composite NDVI values are quite similar over the composite intervals of 2002 and 2003, and linear relationships exist between the NDVI values from the various sensors. The composite AVHRR NDVI data included water and cloud masks and adjustments for water vapor as did the MODIS NDVI data. When analyzed over a variety of land cover types and composite intervals, the AVHRR derived NDVI data were associated with 89% or more of the variation in the MODIS NDVI values. The results suggest that it may be possible to successfully reprocess historical AVHRR data sets to provide continuity of NDVI products through future sensor systems. Numéro de notice : A2005-458 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2005.08.014 En ligne : https://doi.org/10.1016/j.rse.2005.08.014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27594
in Remote sensing of environment > vol 99 n° 3 (30/11/2005) . - pp 221 - 231[article]Supervised image classification by contextual adaboost based on posteriors in neighborhoods / Ryuei Nishii in IEEE Transactions on geoscience and remote sensing, vol 43 n° 11 (November 2005)
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Titre : Supervised image classification by contextual adaboost based on posteriors in neighborhoods Type de document : Article/Communication Auteurs : Ryuei Nishii, Auteur ; Shinto Eguchi, Auteur Année de publication : 2005 Conférence : IGARSS 2004, International Geoscience And Remote Sensing Symposium, Science for society: exploring and manging a changing planet 20/09/2004 24/09/2004 Anchorage Alaska - Etats-Unis Proceedings IEEE Article en page(s) : pp 2547 - 2554 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] apprentissage automatique
[Termes IGN] axiome de Bayes
[Termes IGN] classification contextuelle
[Termes IGN] classification dirigée
[Termes IGN] géostatistique
[Termes IGN] probabilités
[Termes IGN] segmentation d'imageRésumé : (Auteur) AdaBoost, a machine learning technique, is employed for supervised classification of land-cover categories of geostatistical data. We introduce contextual classifiers based on neighboring pixels. First, posterior probabilities are calculated at all pixels. Then averages of the log posteriors are calculated in different neighborhoods and are then used as contextual classification functions. Weights for the classification functions can be determined by minimizing the empirical risk with multiclass. Finally, a convex combination of classification functions is obtained. The classification is performed by a noniterative maximization procedure. The proposed method is applied to artificial multispectral images and benchmark datasets. The performance of the proposed method is excellent and similar to Markov-random-field-based classifier, which requires an iterative maximization procedure. Numéro de notice : A2005-495 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2005.848693 En ligne : https://doi.org/10.1109/TGRS.2005.848693 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27631
in IEEE Transactions on geoscience and remote sensing > vol 43 n° 11 (November 2005) . - pp 2547 - 2554[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-05111 RAB Revue Centre de documentation En réserve L003 Disponible Use of HRSC-A for sampling bidirectional reflectance / Antero Kukko in ISPRS Journal of photogrammetry and remote sensing, vol 59 n° 6 (November 2005)
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Titre : Use of HRSC-A for sampling bidirectional reflectance Type de document : Article/Communication Auteurs : Antero Kukko, Auteur ; Risto Kuittinen, Auteur ; Juha Hyyppä, Auteur Année de publication : 2005 Article en page(s) : pp 323 - 341 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] anisotropie
[Termes IGN] distribution du coefficient de réflexion bidirectionnelle BRDF
[Termes IGN] échantillon
[Termes IGN] GPS-INS
[Termes IGN] image aérienne
[Termes IGN] modèle numérique de surface
[Termes IGN] qualité des donnéesRésumé : (Auteur) This paper describes a method for sampling bidirectional reflectance information from multiangular airborne images. The method uses high resolution surface models to determinate the location of the imaged point on the ground and the orientation of the measured surface fragment. Since natural surfaces scatter incident radiation anisotropically, viewing and illumination conditions play a critical role in the interpretation of remotely sensed images. Thus, directionally defined reflectance data are needed for the modelling and correction of bidirectional effects on airborne optical images. Two test sites were imaged with a wide range of viewing azimuth angles at two different times. A high resolution HRSC-A stereo camera was used for image acquisition. Algorithms were implemented to reconstruct the image acquisition and retrieve the image samples from the HRSC-A image data. Combined with GPS and INS data, automatically derived high resolution digital surface models, including vegetation canopies, houses, etc., were used to determine the viewing and illumination geometry on the target surface. The brightness of a sample point was recorded as a measure for reflectance. A large number of directionally defined samples and a wide angular range of sample geometry were obtained. The images were first classified. Sampled reflectance data were verified by investigating the bidirectional reflectance of five agricultural and forest targets. Errors affecting the data quality, such as angular uncertainty, were studied. The multiangular image data, the developed sampling methods and the obtained bidirectional dataset proved to be applicable in investigations of bidirectional reflectance effects of natural targets. Airborne imagery combined with high resolution digital surface models permit extensive investigation of the bidirectional reflectance of a wide range of natural objects and large habitats. Copyright ISPRS Numéro de notice : A2005-489 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2005.06.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2005.06.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27625
in ISPRS Journal of photogrammetry and remote sensing > vol 59 n° 6 (November 2005) . - pp 323 - 341[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-05041 SL Revue Centre de documentation Revues en salle Disponible LAI retrieval from multiangular image classification and inversion of a ray tracing model / R. Casa in Remote sensing of environment, vol 98 n° 4 (30/10/2005)
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Titre : LAI retrieval from multiangular image classification and inversion of a ray tracing model Type de document : Article/Communication Auteurs : R. Casa, Auteur ; H.G. Jones, Auteur Année de publication : 2005 Article en page(s) : pp 414 - 428 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] classification dirigée
[Termes IGN] couvert végétal
[Termes IGN] cultures
[Termes IGN] image multiangulaire
[Termes IGN] Italie
[Termes IGN] lancer de rayons
[Termes IGN] Leaf Area Index
[Termes IGN] modèle d'inversion
[Termes IGN] modèle de diffusion du rayonnement
[Termes IGN] pomme de terre
[Termes IGN] rayonnement infrarouge
[Termes IGN] réflectance végétaleRésumé : (Auteur) A non-conventional approach for the estimation of leaf area index (LAI) and leaf angle distribution (LAD), based on the use of information contained in multiangular images and the inversion of a canopy ray tracing model, is proposed in this work. As an alternative to the use of overall image reflectance data, the image fraction components, i.e. sunlit and shaded leaves and soil, are obtained by supervised classification of groundbased multiangular images acquired using an inexpensive colour infrared camera, the Dycam ADC. These data are used for the inversion of a numerical model of a vegetation canopy in which the latter is described as composed of randomly distributed disks (leaves). The model was developed using the POV-ray ray tracer. Model inversion is carried out using the look-up-table approach. The proposed methodology was tested using an extensive data set gathered on the potato crop during experimental trials carried out at Viterbo (Italy) for 3 years. The results show that LAI was successfully estimated with a RMSE varying from 0.29 to 0.75 in the different years. The potential sources of error in both estimated and measured LAI values are extensively discussed. Numéro de notice : A2005-433 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2005.08.005 En ligne : https://doi.org/10.1016/j.rse.2005.08.005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27569
in Remote sensing of environment > vol 98 n° 4 (30/10/2005) . - pp 414 - 428[article]Derivation of terrain roughness indicators via granulometries / L.T. Tay in International Journal of Remote Sensing IJRS, vol 26 n° 18 (September 2005)
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Titre : Derivation of terrain roughness indicators via granulometries Type de document : Article/Communication Auteurs : L.T. Tay, Auteur ; B.S. Daya Sagar, Auteur ; H.T. Chuah, Auteur Année de publication : 2005 Article en page(s) : pp 3901 - 3910 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] bassin hydrographique
[Termes IGN] échantillonnage d'image
[Termes IGN] figure géométrique
[Termes IGN] géomorphologie
[Termes IGN] granulométrie (pétrologie)
[Termes IGN] Malaisie
[Termes IGN] modèle numérique de surface
[Termes IGN] niveau de gris (image)
[Termes IGN] rugosité du solRésumé : (Auteur) Digital elevation models (DEMs) provide rich clues about various geophysical and geomorphologic processes. These clues include conspicuous protrusions and intrusions of foreground and background portions that testify the presence of channels and ridges in DEMs. We show an application of greyscale granulometries to characterize DEMs through shape-size complexity measures relative to symmetric rhombus, octagon and square templates. We first compute pattern spectra that measure the size distributions of protrusions and intrusions in a DEM. We then employ pattern spectra to compute probability size distribution functions of protrusions and intrusions relative to three templates. We finally compute shape-size complexity measures of DEM by employing these probability functions. To illustrate the implementation of granulometric approach to compute these measures of both background and foreground, we consider an interferometrically generated DEM of a part of Cameron Highlands of Malaysia. Hierarchical watersheds that could be decomposed from DEMs can be better classified via these measures. Numéro de notice : A2005-427 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160500165880 En ligne : https://doi.org/10.1080/01431160500165880 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27563
in International Journal of Remote Sensing IJRS > vol 26 n° 18 (September 2005) . - pp 3901 - 3910[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-05181 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Integrated shadow removal based on photogrammetry and image analysis / Y. Li in International Journal of Remote Sensing IJRS, vol 26 n° 18 (September 2005)
PermalinkChange detection with heterogeneous data using ecoregional stratification, statistical summaries and a land allocation algorithm / K.M. Bergen in Remote sensing of environment, vol 97 n° 4 (15/09/2005)
Permalinkn° 178 - Septembre 2005 (Bulletin de Revue Française de Photogrammétrie et de Télédétection) / Société française de photogrammétrie et de télédétection
PermalinkCloud-free satellite image mosaics with regression trees and histogram matching / E.H. Helmert in Photogrammetric Engineering & Remote Sensing, PERS, vol 71 n° 9 (September 2005)
PermalinkUne approche pour la description et l'interrogation d'images satellitaires à très haute résolution spatiale / E. Lopez-Ornelas in Ingénierie des systèmes d'information, ISI : Revue des sciences et technologies de l'information, RSTI, vol 10 n° 4 (juillet -août 2005)
PermalinkFish-eye calibration and epipolar rectification / Saji Abraham in ISPRS Journal of photogrammetry and remote sensing, vol 59 n° 5 (August - October 2005)
PermalinkPrototyping a global algorithm for systematic fire-affected area mapping using MODIS time series data / D.P. Roy in Remote sensing of environment, vol 97 n° 2 (30/07/2005)
PermalinkEstimating and accommodating uncertainty through the soft classification of remote sensing data / M.A. Ibrahim in International Journal of Remote Sensing IJRS, vol 26 n° 14 (July 2005)
PermalinkKernel based re-classification of Earth observation data for fine scale habitat mapping / Iphigenia Keramitsoglou in Journal for nature conservation, vol 13 n° 2-3 (July 2005)
Permalinkn° 177 - Juin 2005 (Bulletin de Revue Française de Photogrammétrie et de Télédétection) / Société française de photogrammétrie et de télédétection
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