ISPRS Journal of photogrammetry and remote sensing / International society for photogrammetry and remote sensing (1980 -) . vol 64 n° 4Paru le : 01/07/2009 ISBN/ISSN/EAN : 0924-2716 |
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Ajouter le résultat dans votre panierUse Markov random fields for automatic cloud-shadow detection on high resolution / Sylvie Le Hégarat-Mascle in ISPRS Journal of photogrammetry and remote sensing, vol 64 n° 4 (July - August 2009)
[article]
Titre : Use Markov random fields for automatic cloud-shadow detection on high resolution Type de document : Article/Communication Auteurs : Sylvie Le Hégarat-Mascle, Auteur ; Cyrille André, Auteur Année de publication : 2009 Article en page(s) : pp 351 - 366 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] champ aléatoire de Markov
[Termes IGN] connexité (graphes)
[Termes IGN] détection automatique
[Termes IGN] graphe
[Termes IGN] image optique
[Termes IGN] nuage
[Termes IGN] ombre
[Termes IGN] pixel
[Termes IGN] processus ponctuel marquéRésumé : (Auteur) In this study, we propose an automatic detection algorithm for cloud/shadow on remote sensing optical images. It is based on physical properties of clouds and shadows, namely for a cloud and its associated shadow: both are connex objects of similar shape and area, and they are related by their relative locations. We show that these properties can be formalized using Markov Random Field (MRF) framework at two levels: one MRF over the pixel graph for connexity modelling, and one MRF over the graph of objects (clouds and shadows) for their relationship modelling. Then, we show that, practically, having performed an image pre-processing step (channel inter-calibration) specific to cloud detection, the local optimization of the proposed MRF models leads to a rather simple image processing algorithm involving only six parameters. Using a 39 image database, performance is shown and discussed, in particular in comparison with the Marked Point Process approach. Numéro de notice : A2009-294 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2008.12.007 En ligne : https://doi.org/10.1016/j.isprsjprs.2008.12.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29924
in ISPRS Journal of photogrammetry and remote sensing > vol 64 n° 4 (July - August 2009) . - pp 351 - 366[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-09041 SL Revue Centre de documentation Revues en salle Disponible Observations of urban and suburban environments with global satellite scatterometer data / Son V. Nghiem in ISPRS Journal of photogrammetry and remote sensing, vol 64 n° 4 (July - August 2009)
[article]
Titre : Observations of urban and suburban environments with global satellite scatterometer data Type de document : Article/Communication Auteurs : Son V. Nghiem, Auteur ; D. Balk, Auteur Année de publication : 2009 Article en page(s) : pp 367 - 380 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] banlieue
[Termes IGN] Bogota (Colombie)
[Termes IGN] Canton (Kouangtoung)
[Termes IGN] Dallas (Texas)
[Termes IGN] densité de population
[Termes IGN] densité du bâti
[Termes IGN] détection de contours
[Termes IGN] Dhaka (Bangladesh)
[Termes IGN] diffusomètre
[Termes IGN] échantillonnage d'image
[Termes IGN] éclairage public
[Termes IGN] image Landsat-ETM+
[Termes IGN] milieu urbain
[Termes IGN] Phoenix
[Termes IGN] Quito (Equateur)
[Termes IGN] télédétection en hyperfréquenceRésumé : (Auteur) A global and consistent characterization of land use and land change in urban and suburban environments is crucial for many fundamental social and natural science studies and applications. Presented here is a dense sampling method (DSM) that uses satellite scatterometer data to delineate urban and intraurban areas at a posting scale of about 1 km. DSM results are analyzed together with information on population and housing censuses, with Landsat Enhanced Thematic Mapper Plus (ETM+) imagery, and with Defense Meteorological Satellite Program (DMSP) night-light data. The analyses include Dallas-Fort Worth and Phoenix in the United States, Bogotá in Colombia, Dhaka in Bangladesh, Guangzhou in China, and Quito in Ecuador. Results show that scatterometer signatures correspond to buildings and infrastructures in urban and suburban environments. City extents detected by scatterometer data are significantly smaller than city light extents, but not all urban areas are detectable by the current SeaWinds scatterometer on the QuikSCAT satellite. Core commercial and industrial areas with high buildings and large factories are identified as high-backscatter centers. Data from DSM backscatter and DMSP nighttime lights have a good correlation with population density. However, the correlation relations from the two satellite datasets are different for different cities indicating that they contain complementary information. Together with night-light and census data, DSM and satellite scatterometer data provide new observations to study global urban and suburban environments and their changes. Furthermore, the capability of DSM to identify hydrological channels on the Greenland ice sheet and ecological biomes in central Africa demonstrates that DSM can be used to observe persistent structures in natural environments at a km scale, providing contemporaneous data to study human impacts beyond urban and suburban areas. Copyright ISPRS Numéro de notice : A2009-295 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2009.01.004 En ligne : https://doi.org/10.1016/j.isprsjprs.2009.01.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29925
in ISPRS Journal of photogrammetry and remote sensing > vol 64 n° 4 (July - August 2009) . - pp 367 - 380[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-09041 SL Revue Centre de documentation Revues en salle Disponible Calibration facility for airborne imaging spectrometers / P. Gege in ISPRS Journal of photogrammetry and remote sensing, vol 64 n° 4 (July - August 2009)
[article]
Titre : Calibration facility for airborne imaging spectrometers Type de document : Article/Communication Auteurs : P. Gege, Auteur ; J. Fries, Auteur ; et al., Auteur Année de publication : 2009 Article en page(s) : pp 387 - 397 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] Airborne Prism Experiment
[Termes IGN] capteur aérien
[Termes IGN] étalonnage de capteur (imagerie)
[Termes IGN] spectromètre imageurRésumé : (Auteur) A new facility designed to perform calibration measurements of airborne imaging spectrometers was established at the German Aerospace Center (DLR) in Oberpfaffenhofen. This Calibration Home Base (CHB) is optimized to characterize radiometrically, spectrally, and geometrically the APEX (Airborne Prism Experiment) imaging spectrometer, which is currently being developed under the authority of the European Space Agency (ESA). It however can be used for other optical sensors as well. Computer control of major laboratory equipment allows automation of time consuming measurements. In APEX configuration (wavelength range: 380 to 2500 nm, instantaneous field of view: 0.48 mrad, field of view: +14ring operator) spectral measurements can be performed to a wavelength uncertainty of +0.15 nm, geometric measurements at increments of 0.0017 mrad across track and 0.0076 mrad along track, and radiometric measurements to an uncertainty of +3% relative to national standard. The CHB can be adapted to similar sensors (including those with thermal infrared detectors) by exchanging the monochromator’s lamp, the gratings and the filters, and by adjusting the distance between the sensor and folding mirror. Copyright ISPRS Numéro de notice : A2009-296 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2009.01.006 En ligne : https://doi.org/10.1016/j.isprsjprs.2009.01.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29926
in ISPRS Journal of photogrammetry and remote sensing > vol 64 n° 4 (July - August 2009) . - pp 387 - 397[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-09041 SL Revue Centre de documentation Revues en salle Disponible Optimizing Support Vector Machine learning for semi-arid vegetation mapping by using clustering analysis / L. Su in ISPRS Journal of photogrammetry and remote sensing, vol 64 n° 4 (July - August 2009)
[article]
Titre : Optimizing Support Vector Machine learning for semi-arid vegetation mapping by using clustering analysis Type de document : Article/Communication Auteurs : L. Su, Auteur Année de publication : 2009 Article en page(s) : pp 407 - 413 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse de groupement
[Termes IGN] apprentissage automatique
[Termes IGN] carte de la végétation
[Termes IGN] classification ascendante hiérarchique
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] occupation du sol
[Termes IGN] précision de la classification
[Termes IGN] séparateur à vaste marge
[Termes IGN] zone semi-arideRésumé : (Auteur) In remote sensing communities, support vector machine (SVM) learning has recently received increasing attention. SVM learning usually requires large memory and enormous amounts of computation time on large training sets. According to SVM algorithms, the SVM classification decision function is fully determined by support vectors, which compose a subset of the training sets. In this regard, a solution to optimize SVM learning is to efficiently reduce training sets. In this paper, a data reduction method based on agglomerative hierarchical clustering is proposed to obtain smaller training sets for SVM learning. Using a multiple angle remote sensing dataset of a semi-arid region, the effectiveness of the proposed method is evaluated by classification experiments with a series of reduced training sets. The experiments show that there is no loss of SVM accuracy when the original training set is reduced to 34% using the proposed approach. Maximum likelihood classification (MLC) also is applied on the reduced training sets. The results show that MLC can also maintain the classification accuracy. This implies that the most informative data instances can be retained by this approach. Copyright ISPRS Numéro de notice : A2009-297 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2009.02.002 En ligne : https://doi.org/10.1016/j.isprsjprs.2009.02.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29927
in ISPRS Journal of photogrammetry and remote sensing > vol 64 n° 4 (July - August 2009) . - pp 407 - 413[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-09041 SL Revue Centre de documentation Revues en salle Disponible