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Visualizing topography by openness: a new application of image processing to digital elevation models / R. Yokoyama in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 3 (March 2002)
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Titre : Visualizing topography by openness: a new application of image processing to digital elevation models Type de document : Article/Communication Auteurs : R. Yokoyama, Auteur ; M. Shirasawa, Auteur ; R. Pike, Auteur Année de publication : 2002 Article en page(s) : pp 257 - 265 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] ligne de visée
[Termes IGN] modèle numérique de surface
[Termes IGN] niveau de gris (image)
[Termes IGN] paysage
[Termes IGN] visualisation 3DRésumé : (Auteur) A new parameter, here termed openness, expressing the degree of dominance or enclosure of a location on an irregular surface, is developed to visualise topographic character. Openness is an angular measure of the relation between surface relief and horizontal distance. For angles less than 90', it is equivalent to the internal angle of a cone, its APEX at a DEM location, constrained by neighbouring elevations within a specified radial distance. Openness incorporates the terrain line-of-sight, or viewshed, concept and is calculated from multiple zenith and nadir angles-here along eight azimuths. Openness has two viewer perspectives. Positive values, expressing openness above the surface, are high for convex forms, whereas negative values describe this attribute below the surface and are high for concave forms. Openness values are mapped by gray-scale tones. The emphasis of terrain convexity and concavity in openness maps facilitates the interpretation of landforms on the Earth's surface and its seafloor, and on the planets, as well as features on any irregular surface-such as those generated by industrial procedures. Numéro de notice : A2002-029 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans En ligne : https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=c3d9a561fdb9e8c34 [...] Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=21946
in Photogrammetric Engineering & Remote Sensing, PERS > vol 68 n° 3 (March 2002) . - pp 257 - 265[article]Application of remote sensing to enhance the control of wildlife associated mycobacterium bovis infection / J.S. Mckenzie in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 2 (February 2002)
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Titre : Application of remote sensing to enhance the control of wildlife associated mycobacterium bovis infection Type de document : Article/Communication Auteurs : J.S. Mckenzie, Auteur ; R.S. Morris, Auteur ; D.U. Pfeiffer, Auteur ; J.R. Dymond, Auteur Année de publication : 2002 Article en page(s) : pp 153 - 159 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] biotope
[Termes IGN] cartographie thématique
[Termes IGN] classification
[Termes IGN] image multibande
[Termes IGN] image SPOT
[Termes IGN] prévention des risques
[Termes IGN] risque sanitaireRésumé : (Auteur) The brushtail possum (Trichosurus vulpecula) is a wildlife vector for tuberculosis (TB) caused by Mycobacterium bovis in New Zealand. Supervised automatic classification of a SPOT3 multi spectral image was used to generate a vegetation map, which was used together with slope data to model the risk of TB-infected possums being present in habitat patches. The vegetation data were also used to identify habitat patterns which, together with other geographic variables, were incorporated into logistic regression models to identify predictors of possum TB risk of farms. The impact of the predicted possum TB risk data on the cost-effectiveness of vector control programs at both individual farm and larger regional control areas is discussed, plus issues associated with the uptake of the models by operational managers. Numéro de notice : A2002-013 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans En ligne : https://www.asprs.org/wp-content/uploads/pers/2002journal/february/2002_feb_153- [...] Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=21930
in Photogrammetric Engineering & Remote Sensing, PERS > vol 68 n° 2 (February 2002) . - pp 153 - 159[article]Comparison of GENIE and conventional supervised classifiers for multispectral image feature extraction / N.R. Harvey in IEEE Transactions on geoscience and remote sensing, vol 40 n° 2 (February 2002)
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Titre : Comparison of GENIE and conventional supervised classifiers for multispectral image feature extraction Type de document : Article/Communication Auteurs : N.R. Harvey, Auteur ; et al., Auteur Année de publication : 2002 Article en page(s) : pp 393 - 404 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] classification dirigée
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] extraction semi-automatique
[Termes IGN] image multibandeRésumé : (Auteur) We have developed an automated feature detection/classification system, called GENetic Imagery Exploitation (GENIE), which has been designed to generate image processing pipelines for a variety of feature detection/classification tasks. GENIE is a hybrid evolutionary algorithm that addresses the general problem of finding features of interest in multispectral remotely-sensed images. We describe our system in detail together with experiments involving comparisons of GENIE with several conventional supervised classification techniques, for a number of classification tasks using multispectral remotely sensed imagery. Numéro de notice : A2002-098 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/36.992801 En ligne : https://doi.org/10.1109/36.992801 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22013
in IEEE Transactions on geoscience and remote sensing > vol 40 n° 2 (February 2002) . - pp 393 - 404[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-02021 RAB Revue Centre de documentation En réserve L003 Disponible 065-02022 RAB Revue Centre de documentation En réserve L003 Disponible A derivative-aided hyperspectral image analysis system for land-cover classification / F. Tsai in IEEE Transactions on geoscience and remote sensing, vol 40 n° 2 (February 2002)
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Titre : A derivative-aided hyperspectral image analysis system for land-cover classification Type de document : Article/Communication Auteurs : F. Tsai, Auteur ; W.D. Philpot, Auteur Année de publication : 2002 Article en page(s) : pp 416 - 425 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse de données
[Termes IGN] classification dirigée
[Termes IGN] image hyperspectrale
[Termes IGN] occupation du solRésumé : (Auteur) The large number of spectral bands in hyperspectral data seriously complicates their use for classification. Selection of a useful subset of bands or derived features (spectral ratios, differences, derivatives) is always desirable, strongly affects the accuracy of the classification, and is often a practical necessity to keep the processing speed and memory requirements under control. This paper examines one possible procedure for selecting spectral derivatives to improve supervised classification of hyperspectral images. The procedure is designed to identify derivative features that are more effective at separating target classes and then add them to a base subset of features for classification. The goal is to create the smallest set of features that will result in the best classification result. A key issue in this process is the interplay of the number of features and the size of the training data sets since classification accuracy declines if the dimensionality of the feature space is too large relative to the number of training samples. Numéro de notice : A2002-100 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/36.992805 En ligne : https://doi.org/10.1109/36.992805 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22015
in IEEE Transactions on geoscience and remote sensing > vol 40 n° 2 (February 2002) . - pp 416 - 425[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-02021 RAB Revue Centre de documentation En réserve L003 Disponible 065-02022 RAB Revue Centre de documentation En réserve L003 Disponible Linear spectral random mixture analysis for hyperspectral imagery / C.I. Chang in IEEE Transactions on geoscience and remote sensing, vol 40 n° 2 (February 2002)
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Titre : Linear spectral random mixture analysis for hyperspectral imagery Type de document : Article/Communication Auteurs : C.I. Chang, Auteur ; S.S. Chiang, Auteur ; J.A. Smith, Auteur ; I.W. Ginsberg, Auteur Année de publication : 2002 Article en page(s) : pp 375 - 392 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse en composantes indépendantes
[Termes IGN] analyse linéaire des mélanges spectraux
[Termes IGN] analyse spectrale
[Termes IGN] classification non dirigée
[Termes IGN] image hyperspectraleRésumé : (Auteur) Independent component analysis (ICA) has shown success in blind source separation and channel equalization. Its applications to remotely sensed images have been investigated in recent years. Linear spectral mixture analysis (LSMA) has been widely used for subpixel detection and mixed pixel classification. It models an image pixel as a linear mixture of materials present in an image where the material abundance fractions are assumed to be unknown and nonrandom parameters. This paper considers an application of ICA to the LSMA, referred to as ICA-based linear spectral random mixture analysis (LSRMA), which describes an image pixel as a random source resulting from a random composition of multiple spectral signatures of distinct materials in the image. It differs from the LSMA in that the abundance fractions of the material spectral signatures in the LSRMA are now considered to be unknown but random independent signal sources. Two major advantages result from the LSRMA. First, it does not require prior knowledge of the materials to be used in the linear mixture model, as required for the LSMA. Second, and most importantly, the LSRMA models the abundance fraction of each material spectral signature as an independent random signal source so that the spectral variability of materials can be described by their corresponding abundance fractions and captured more effectively in a stochastic manner. The experimental results demonstrate that the proposed LSRMA provides an effective unsupervised technique for target detection and image classification in hyperspectral imagery. Numéro de notice : A2002-097 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/36.992799 En ligne : https://doi.org/10.1109/36.992799 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22012
in IEEE Transactions on geoscience and remote sensing > vol 40 n° 2 (February 2002) . - pp 375 - 392[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-02021 RAB Revue Centre de documentation En réserve L003 Disponible 065-02022 RAB Revue Centre de documentation En réserve L003 Disponible Look beneath the surface with augmented reality / G. Roberts in GPS world, vol 13 n° 2 (February 2002)
PermalinkAnalyse d'images aériennes haute résolution pour la reconstruction de scènes urbaines / Matthieu Cord in Bulletin [Société Française de Photogrammétrie et Télédétection], n° 166 (Janvier 2002)
PermalinkAnalyse et segmentation de séquences d'images en vue d'une reconnaissance de formes efficace / Santiago Venegas Martinez (2002)
PermalinkApport des SIG et de la télédétection à la détermination d'unités dynamiques des paysages / S. Bancarel (2002)
PermalinkApprofondissement des techniques de diagnostique des propriétés spectrales d'une culture / Laure Chandelier (2002)
PermalinkPermalinkPermalinkPermalinkPermalinkFabrication conjointe de modèles numériques de surface et d'ortho-images pour la visualisation perspective de scènes urbaines / Didier Boldo (2002)
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