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Rational function model for sensor orientation of IRS-P6 LISS-4 imagery / V. Nagasubramanian in Photogrammetric record, vol 22 n° 120 (December 2007 - February 2008)
[article]
Titre : Rational function model for sensor orientation of IRS-P6 LISS-4 imagery Type de document : Article/Communication Auteurs : V. Nagasubramanian, Auteur ; P. Radhadevi, Auteur ; R. Ramachandran, Auteur ; R. Krishnan, Auteur Année de publication : 2007 Article en page(s) : pp 309 - 320 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] géométrie de l'image
[Termes IGN] géoréférencement direct
[Termes IGN] image IRS-LISS
[Termes IGN] modèle par fonctions rationnelles
[Termes IGN] orientation du capteur
[Termes IGN] point d'appuiRésumé : (Auteur) This paper explores the application of a rational function model (RFM) as a replacement sensor model for IRS-P6 LISS-4 imagery. The rational polynomial coefficients (RPCs), initially generated using a rigorous sensor model (RSM) through direct georeferencing, are bias-compensated with a minimum number of ground control points and are used for various photogrammetric applications such as digital elevation model and ortho-image generation. The performance of RFM and RSM is compared in the sensor modelling of LISS-4 imagery over long strips. Results show that accuracies achieved using RFM are within 1 pixel (worst case) of the accuracies derived using RSM. Error variation as a function of the number of quasi-control points (anchor points) used for RFM fitting as well as model errors with respect to the length of the image strip are analysed. System-level accuracy does not deteriorate when the RFM is fitted up to a length of 1200 km. Absolute positioning accuracy of 1·5 pixels (~9 m) is achieved from bias-compensated RPCs. The results demonstrate the potential of RFM as a replacement sensor model. This allows standardisation of product generation packages to handle multiple sensors. Copyright RS&PS + Blackwell Publishing Numéro de notice : A2007-567 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/j.1477-9730.2007.00447.x En ligne : https://doi.org/10.1111/j.1477-9730.2007.00447.x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28930
in Photogrammetric record > vol 22 n° 120 (December 2007 - February 2008) . - pp 309 - 320[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 106-07041 Revue Centre de documentation Revues en salle Disponible Spatially integrated approach for terrain modelling and analysis for mobile communication applications / S. Muralikrishnan in Geocarto international, vol 22 n° 4 (December 2007 - January 2008)
[article]
Titre : Spatially integrated approach for terrain modelling and analysis for mobile communication applications Type de document : Article/Communication Auteurs : S. Muralikrishnan, Auteur ; I.V. Muralikrishnan, Auteur ; A.S. Manjunath, Auteur ; K.M.M. Rao, Auteur Année de publication : 2007 Article en page(s) : pp 297 - 307 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] fibre optique
[Termes IGN] image à résolution subdecamétrique
[Termes IGN] image IRS-PAN
[Termes IGN] Inde
[Termes IGN] modèle numérique de terrain
[Termes IGN] réseau de télécommunication
[Termes IGN] système d'information géographique
[Termes IGN] télécommunication spatiale
[Termes IGN] téléphonie mobileRésumé : (Auteur) In recent years in India, deregulation has opened the telecommunications market up to new arenas putting pressure on existing organizations to become more efficient. New technologies such as fibre optic cables, efficient terrestrial broadcasting and satellites are offering greatly increased bandwidth. However, the ever-increasing demand to provide low-cost and large area coverage with high reception quality has forced these industries to explore advanced optimization strategies for their network planning. The telecommunications companies have begun to recognize that many of their work practices have spatial elements and data can be used more efficiently. In the present study, a planning strategy for establishing a network of towers for the purpose of mobile communications using remote sensing and raster GIS is demonstrated. In particular, this study addresses how to develop a surface model using IRS-1C PAN stereo pair. This information derived from the satellite data was integrated with raster GIS GRID modelling. The study clearly demonstrates that the IRS data could be utilized for planning a suitable network of towers for telecom applications. Copyright Taylor & Francis Numéro de notice : A2007-540 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106040701204578 Date de publication en ligne : 19/11/2007 En ligne : https://doi.org/10.1080/10106040701204578 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28903
in Geocarto international > vol 22 n° 4 (December 2007 - January 2008) . - pp 297 - 307[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-07041 RAB Revue Centre de documentation En réserve L003 Disponible Usage of ERS SAR data over the Singhbhum shear zone, India for structural mapping and tectonic studies / S.K. Pal in Geocarto international, vol 22 n° 4 (December 2007 - January 2008)
[article]
Titre : Usage of ERS SAR data over the Singhbhum shear zone, India for structural mapping and tectonic studies Type de document : Article/Communication Auteurs : S.K. Pal, Auteur ; T.J. Majumdar, Auteur ; A.K. Bhattacharya, Auteur Année de publication : 2007 Article en page(s) : pp 285 - 295 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse comparative
[Termes IGN] carte géologique
[Termes IGN] géologie structurale
[Termes IGN] image ERS-SAR
[Termes IGN] image IRS
[Termes IGN] image Landsat-TM
[Termes IGN] Inde
[Termes IGN] linéament
[Termes IGN] lithologieRésumé : (Auteur) The extraction of lineaments and anomalous patterns in the Singhbhum Shear Zone, Jharkhand, India, has multifaceted applications for mineral exploration as well as for geological interpretation of neotectonic movements. ERS-1 SAR data are very useful for such applications because of their structural information content. A comparative study has been attempted with ERS, Landsat and IRS images for the interpretation of various geological structures over the Singhbhum Shear Zone. The Rose diagram generated from this study has shown major trends that matched well with the geological map of the area and the associated tectonic boundary as well as with the results obtained from ground based studies. Copyright Taylor & Francis Numéro de notice : A2007-539 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106040701337642 Date de publication en ligne : 19/11/2007 En ligne : https://doi.org/10.1080/10106040701337642 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28902
in Geocarto international > vol 22 n° 4 (December 2007 - January 2008) . - pp 285 - 295[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-07041 RAB Revue Centre de documentation En réserve L003 Disponible Multispectral image classification: a supervised neural computation approach based on rough-fuzzy membership function and weak fuzzy similarity relation / A. Agrawal in International Journal of Remote Sensing IJRS, vol 28 n°19-20 (October 2007)
[article]
Titre : Multispectral image classification: a supervised neural computation approach based on rough-fuzzy membership function and weak fuzzy similarity relation Type de document : Article/Communication Auteurs : A. Agrawal, Auteur ; N. Kumar, Auteur ; M. Radhakrishna, Auteur Année de publication : 2007 Article en page(s) : pp 4597 - 4608 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification dirigée
[Termes IGN] classification par réseau neuronal
[Termes IGN] ERDAS Imagine
[Termes IGN] image IRS-LISS
[Termes IGN] image multibande
[Termes IGN] incertitude des données
[Termes IGN] Inde
[Termes IGN] Kappa de Cohen
[Termes IGN] Perceptron multicouche
[Termes IGN] sous ensemble flouRésumé : (Auteur) A supervised neural network classification model based on rough-fuzzy membership function, weak fuzzy similarity relation, multilayer perceptron, and back-propagation algorithm is proposed. The described model is capable of dealing with rough uncertainty as well as fuzzy uncertainty associated with the classification of multispectral images. The concept of weak fuzzy similarity relation is used for generation of fuzzy equivalence classes during the calculation of rough-fuzzy membership function. The model allows efficient modelling of indiscernibility and fuzziness between patterns by appropriate weights being assigned using the back-propagated errors depending upon the rough-fuzzy membership values at the corresponding outputs. The effectiveness of the proposed model is demonstrated on classification problem of IRS-P6 LISS IV image of Allahabad area. The results are compared with statistical (minimum distance to means), conventional Multi-Layer Perceptron (MLP) and Fuzzy Multi-Layer Perceptron (FMLP) models. The better overall accuracy, user's and producer's accuracies and kappa coefficient of the proposed classifier in comparison to other considered models demonstrate the effectiveness of this model in multispectral image classification. Copyright Taylor & Francis Numéro de notice : A2007-449 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160701244898 En ligne : https://doi.org/10.1080/01431160701244898 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28812
in International Journal of Remote Sensing IJRS > vol 28 n°19-20 (October 2007) . - pp 4597 - 4608[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 080-07111 RAB Revue Centre de documentation En réserve L003 Disponible Cloud-top pressure retrieval using the oxygen a-band in the IRS-3 MOS instrument / R. Preusker in International Journal of Remote Sensing IJRS, vol 28 n° 9 (May 2007)
[article]
Titre : Cloud-top pressure retrieval using the oxygen a-band in the IRS-3 MOS instrument Type de document : Article/Communication Auteurs : R. Preusker, Auteur ; J. Fischer, Auteur ; et al., Auteur Année de publication : 2007 Article en page(s) : pp 1957 - 1967 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] image IRS-MOS
[Termes IGN] nuage
[Termes IGN] pression atmosphérique
[Termes IGN] radiance
[Termes IGN] radiosondageRésumé : (Auteur) Backscattered solar radiation as measured by MOS (Modular Optoelectronical Scanner) on the IRS3 (Indian Remote sensing Satellite 3) has been used in an algorithm to retrieve cloud top pressure. The algorithm uses a radiance ratio between absorbing channels in the Oxygen-A absorption band at 761 nm and a window channel at 750 nm. The ratios are directly related to the average photon path length, which is mainly determined by the cloud top pressure. This paper presents the principles of the retrieval scheme, results of a sensitivity study and a first validation using radiosondes. Copyright Taylor & Francis Numéro de notice : A2007-278 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160600641632 En ligne : https://doi.org/10.1080/01431160600641632 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28641
in International Journal of Remote Sensing IJRS > vol 28 n° 9 (May 2007) . - pp 1957 - 1967[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-07051 RAB Revue Centre de documentation En réserve L003 Exclu du prêt ERS-2 SAR and IRS-1C LISS III data fusion: a PCA approach to improve remote sensing based geological interpretation / T.J. Majumdar in ISPRS Journal of photogrammetry and remote sensing, vol 61 n° 5 (January 2007)PermalinkOperation analysis of a reservoir in GIS environment using remote sensing inputs / M.K. Goel in International Journal of Remote Sensing IJRS, vol 28 n° 1-2 (January 2007)PermalinkCensus of natural resources with earth observation and GIS : a proto-type from India / R.K. Jaiswail in Geocarto international, vol 21 n° 4 (December 2006 - February 2007)PermalinkLineament analysis through remote sensing as a contribution to the identification of caves in western Lebanon / A. Shaban in Photo interprétation, vol 42 n° 4 (Décembre 2006)PermalinkEvaluation of the Oceansat-1 Multi-frequency Scanning Microwave Radiometer and its potential for soil moisture retrieval / J. Wen in International Journal of Remote Sensing IJRS, vol 27 n°18 - 19 - 20 (October 2006)PermalinkExtraction of ground control points (GCPs) from synthetic aperture radar images and SRTM DEM / S.H. Hong in International Journal of Remote Sensing IJRS, vol 27 n°18 - 19 - 20 (October 2006)PermalinkGroundwater assessment through an integrated approach using remote sensing, GIS and resistivity techniques: a case study from a hard rock terrain / P.K. Srivastava in International Journal of Remote Sensing IJRS, vol 27 n°18 - 19 - 20 (October 2006)PermalinkMapping damage in the Jammu and Kashmir caused by 8 October 2005 mw 7.3 earthquakes from the Cartosat-1 and Resourcesat-1 imagery / K. Vinod Kumar in International Journal of Remote Sensing IJRS, vol 27 n°18 - 19 - 20 (October 2006)PermalinkSatellite image classification using granular neural networks / D. Stathakis in International Journal of Remote Sensing IJRS, vol 27 n°18 - 19 - 20 (October 2006)PermalinkCoastal geomorphological and land-use and land-cover study of Sagar island, Bay of Bengal (India) using remotely sensed data / K.S. Jayappa in International Journal of Remote Sensing IJRS, vol 27 n° 17 (September 2006)PermalinkInter-comparison of NOAA-AVHRR and IRS-P4 (MSMR) derived sea surface temperatures / B. Jena in International Journal of Remote Sensing IJRS, vol 27 n°15-16 (August 2006)PermalinkStudy of tectonics in relation to the seismic activity of the Davalt area, Nasik district, Maharashtra, India using remote sensing and GIS techniques / J. Sarup in International Journal of Remote Sensing IJRS, vol 27 n°12-13-14 (July 2006)PermalinkAbsolute position estimation using IRS satellite images / Y.S. Oh in ISPRS Journal of photogrammetry and remote sensing, vol 60 n° 4 (June - July 2006)PermalinkRelevance of hyperspectral data for natural resources management / T.V. Ramachandra in GIS development, vol 10 n° 4 (April 2006)PermalinkInterprétation visuelle des images satellitaires (Landsat TM, SPOT 4, IRS et Ikonos) et mouvements de masse : cas d'étude au Liban / C. Abdallah in Photo interprétation, vol 42 n° 1 (Mars 2006)PermalinkMangrove mapping and monitoring: RS and GIS in conservation and management planning / S.K. Singh in GIM international, vol 20 n° 3 (March 2006)PermalinkRegional study for mapping the natural resources prospect and problem zones using remote sensing and GIS / R.K. Jaiswal in Geocarto international, vol 20 n° 3 (September - November 2005)PermalinkA quantitative comparison of methods for classifying burned areas with LISS-3 imagery / R.M. Roman-Cuesta in International Journal of Remote Sensing IJRS, vol 26 n° 9 (May 2005)PermalinkLandslide susceptibility mapping using GIS and the weight-of-evidence model / S. Lee in International journal of geographical information science IJGIS, vol 18 n° 8 (december 2004)PermalinkProbabilistic landslide hazard mapping using GIS and remote sensing data at Boun, Korea / S. Lee in International Journal of Remote Sensing IJRS, vol 25 n° 11 (June 2004)Permalink