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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 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 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)
[article]
Titre : ERS-2 SAR and IRS-1C LISS III data fusion: a PCA approach to improve remote sensing based geological interpretation Type de document : Article/Communication Auteurs : T.J. Majumdar, Auteur ; S.K. Pal, Auteur ; A.K. Bhattacharya, Auteur Année de publication : 2007 Article en page(s) : pp 281 - 297 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse en composantes principales
[Termes IGN] carte géologique
[Termes IGN] détection de changement
[Termes IGN] filtrage numérique d'image
[Termes IGN] fusion d'images
[Termes IGN] géologie locale
[Termes IGN] image en couleur composée
[Termes IGN] image ERS-SAR
[Termes IGN] image IRS-LISS
[Termes IGN] image optique
[Termes IGN] image radar
[Termes IGN] Inde
[Termes IGN] interprétation automatique
[Termes IGN] système d'information géographique
[Termes IGN] transformation rapide de FourierRésumé : (Auteur) Fusion of optical and synthetic aperture radar data has been attempted in the present study for mapping of various lithologic units over a part of the Singhbhum Shear Zone (SSZ) and its surroundings. ERS-2 SAR data over the study area has been enhanced using Fast Fourier Transformation (FFT) based filtering approach, and also using Frost filtering technique. Both the enhanced SAR imagery have been then separately fused with histogram equalized IRS-1C LISS III image using Principal Component Analysis (PCA) technique. Later, Feature-oriented Principal Components Selection (FPCS) technique has been applied to generate False Color Composite (FCC) images, from which corresponding geological maps have been prepared. Finally, GIS techniques have been successfully used for change detection analysis in the lithological interpretation between the published geological map and the fusion based geological maps. In general, there is good agreement between these maps over a large portion of the study area. Based on the change detection studies, few areas could be identified which need attention for further detailed ground-based geological studies. Copyright ISPRS Numéro de notice : A2007-020 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2006.10.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2006.10.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28386
in ISPRS Journal of photogrammetry and remote sensing > vol 61 n° 5 (January 2007) . - pp 281 - 297[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-07011 SL Revue Centre de documentation Revues en salle Disponible Operation 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)
[article]
Titre : Operation analysis of a reservoir in GIS environment using remote sensing inputs Type de document : Article/Communication Auteurs : M.K. Goel, Auteur ; P. Kumar, Auteur ; Sanjay K. Jain, Auteur ; R.S. Tiwaris, Auteur Année de publication : 2007 Article en page(s) : pp 335 - 352 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] allocation
[Termes IGN] analyse des besoins
[Termes IGN] eau pluviale
[Termes IGN] gestion de l'eau
[Termes IGN] image IRS-LISS
[Termes IGN] Inde
[Termes IGN] inférence
[Termes IGN] irrigation
[Termes IGN] simulation hydrodynamique
[Termes IGN] système d'information géographique
[Termes IGN] système expertRésumé : (Auteur) Reservoir management involves allocating available water among multiple uses and users, minimizing the risks of water shortages and flooding and optimizing the beneficial use of water. Irrigation demands from a reservoir, which are generally computed by using the design cropping pattern and average rainfall conditions, may vary over the years depending on the actual cropping pattern and meteorological conditions. This study demonstrates the utility of remote sensing inputs and geographic information system (GIS) environment for determining realistic irrigation demands from a reservoir. Remote sensing data are used to map the actual cropping pattern in the command area while the GIS is used for integrating the field-level irrigation demands up to the canal system head. Ten daily irrigation demands in the command area of Samrat Ashok Sagar Reservoir in Madhya Pradesh, India, have been estimated and the reservoir operation policy has been derived. Through the simulation analysis with 29 years of inflow data, rule curves have been derived for the operation of reservoir so that water deficit (if any) can be distributed in time much in advance and severe crop failure can be avoided. Inferences drawn from the analysis can guide the system operator in using the available water in a scientific and judicious manner. Numéro de notice : A2007-036 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160600735616 En ligne : https://doi.org/10.1080/01431160600735616 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82959
in International Journal of Remote Sensing IJRS > vol 28 n° 1-2 (January 2007) . - pp 335 - 352[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 080-07011 RAB Revue Centre de documentation En réserve L003 Disponible Groundwater 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)
[article]
Titre : Groundwater assessment through an integrated approach using remote sensing, GIS and resistivity techniques: a case study from a hard rock terrain Type de document : Article/Communication Auteurs : P.K. Srivastava, Auteur ; A.K. Bhattacharya, Auteur Année de publication : 2006 Article en page(s) : pp 4599 - 4620 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] eau souterraine
[Termes IGN] ERDAS Imagine
[Termes IGN] géomorphologie locale
[Termes IGN] gradient de pente
[Termes IGN] hydrogéologie
[Termes IGN] image IRS-LISS
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-TM
[Termes IGN] Inde
[Termes IGN] MNS SRTM
[Termes IGN] modèle numérique de surface
[Termes IGN] système d'information géographiqueRésumé : (Auteur) Satellite data have been widely used in conjunction with Geographic Information System (GIS) techniques in groundwater resource management. Satellite data are useful for extracting various thematic maps required for groundwater assessment. In this study, Indian Remote Sensing (IRS) 1D LISS III and Landsat Thematic Mapper (TM)/Enhanced TM (ETM+) digital data, and digital elevation models (DEMs) from the Shuttle Radar Topography Mission (SRTM) along with other collateral data were analysed to create various thematic maps (geomorphology, landuse, lithology, lineament, soil, drainage density, river gradient and slope maps) required for groundwater modelling in a hard rock terrain of Bargarh district, Orissa, India. These thematic maps were assigned suitable weights and different rankings to the individual classes within each thematic map using Saaty's Analytical Hierarchy Process (AHP). A raster-based empirical GIS model was developed for integrating the thematic maps to locate suitable groundwater prospective zones. The integrated thematic maps were in turn used to compute the Groundwater Potential Index (GWPI). GWPI values calculated in the study area were found to vary from 0.175 to 0.940. These GWPI values have been classified into various classes: very poor (0.8). A final map showing very poor to excellent groundwater prospective zones was prepared. The results thus obtained were subsequently cross-checked with resistivity survey and pumping test data. Very poor GWPI zones show low yields of 0.5 lps from weathered granite of resistivity 20–100 ? m and thickness 0.5–6 m, while excellent GWPI zones show high yields of 5–7 lps from highly fractured granite of resistivity 100–300 ? m and thickness 14–31 m. The results obtained from integration of the various thematic maps on the GIS platform produced a good match with the resistivity and pumping test data. Copyright Taylor & Francis Numéro de notice : A2006-470 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160600554983 En ligne : https://doi.org/10.1080/01431160600554983 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28194
in International Journal of Remote Sensing IJRS > vol 27 n°18 - 19 - 20 (October 2006) . - pp 4599 - 4620[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 080-06101 RAB Revue Centre de documentation En réserve L003 Disponible Mapping 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)PermalinkRelevance of hyperspectral data for natural resources management / T.V. Ramachandra in GIS development, vol 10 n° 4 (April 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)PermalinkComparative evaluation of Indian remote sensing multi-spectral sensors data for crop classification / R.P. Singh in Geocarto international, vol 17 n° 2 (June - August 2002)PermalinkAdaptation du modèle orbitographique Spot 4 aux satellites / J.C. Clerget (2002)Permalink