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An operational MISR pixel classifier using support vector machines / D. Mazzoni in Remote sensing of environment, vol 107 n° 1-2 (15 March 2007)  

Public [article]  inRemote sensing of environment > vol 107 n° 1-2 (15 March 2007) . - pp 149 - 158 Titre : An operational MISR pixel classifier using support vector machines Type de document : Article/Communication Auteurs : D. Mazzoni, Auteur ; M.J. Garay, Auteur ; R. Davies, Auteur ; et al., Auteur Année de publication : 2007 Article en page(s) : pp 149 - 158 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] apprentissage automatique [Termes IGN] classification dirigée [Termes IGN] classification par réseau neuronal [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] image Terra-MISR Résumé : (Auteur) The Multi-angle Imaging SpectroRadiometer (MISR) data products now include a scene classification for each 1.1-km pixel that was developed using Support Vector Machines (SVMs), a cutting-edge machine learning technique for supervised classification. Using a combination of spectral, angular, and texture features, each pixel is classified as land, water, cloud, aerosol, or snow/ice, with the aerosol class further divided into smoke, dust, and other aerosols. The classifier was trained by MISR scientists who labeled hundreds of scenes using a custom interactive tool that showed them the results of the training in real time, making the process significantly faster. Preliminary validation shows that the accuracy of the classifier is approximately 81% globally at the 1.1-km pixel level. Applications of this classifier include global studies of cloud and aerosol distribution, as well as data mining applications such as searching for smoke plumes. This is one of the largest and most ambitious operational uses of machine learning techniques for a remote-sensing instrument, and the success of this system will hopefully lead to further use of this approach. Copyright Elsevier Numéro de notice : A2007-054 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2006.06.021 En ligne : https://doi.org/10.1016/j.rse.2006.06.021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28419 [article]

Reconstruction of cloud geometry from multi-view satellite images / G. Seiz in Remote sensing of environment, vol 100 n° 2 (30 January 2006)  

Public [article]  inRemote sensing of environment > vol 100 n° 2 (30 January 2006) . - pp 143 - 149 Titre : Reconstruction of cloud geometry from multi-view satellite images Type de document : Article/Communication Auteurs : G. Seiz, Auteur ; R. Davies, Auteur Année de publication : 2006 Article en page(s) : pp 143 - 149 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] hydrologie [Termes IGN] image Terra-MISR [Termes IGN] modèle de transfert radiatif [Termes IGN] nuage [Termes IGN] radiance [Termes IGN] reconstruction 3D Résumé : (Auteur) Reflected solar radiances measured by the pushbroom cameras of the Multiangle Imaging SpectroRadiometer (MISR) on the Terra satellite at nine viewing angles are combined to give eight stereo pairs. These are analyzed with stereo-photogrammetric methods to measure the geometry of a convective cloud system. Both cloud-top heights and cloud sides are retrieved with a precision of about 200-300 m. Two case studies of deep, convective clouds over ocean are considered. The accuracy of the MISR retrieval is tested in the first case study by reference to coincident, higher resolution stereo data from ASTER, showing how the accuracy of the cloud-top height retrieval is improved using the oblique MISR views. In the second case study, the entire cross-section of the cloud aligned with the viewing azimuthal direction is measured, using all nine cameras. The methodology presented is an important step towards more routine retrievals of the 3D geometrical reconstruction of isolated, deep-convective clouds. Such reconstructions are a necessary prerequisite to the subsequent 3D radiative transfer modeling used to aid the remote sensing of the elusive microphysical properties of such clouds. Numéro de notice : A2006-033 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2005.09.016 En ligne : https://doi.org/10.1016/j.rse.2005.09.016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27760 [article]

Total station survey system (TSSS) software / R. Munjy in Surveying and Mapping, vol 49 n° 4 (Winter 1989)

Public [article]  inSurveying and Mapping > vol 49 n° 4 (Winter 1989) . - pp 173 - 178 Titre : Total station survey system (TSSS) software Type de document : Article/Communication Auteurs : R. Munjy, Auteur ; L. Fenske, Auteur ; R. Davies, Auteur ; M. Hartwig, Auteur Année de publication : 1989 Article en page(s) : pp 173 - 178 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie [Termes IGN] compensation [Termes IGN] instrumentation Wild [Termes IGN] interface logicielle [Termes IGN] tachéomètre électronique Numéro de notice : A1989-424 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83648 [article]

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