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image multibandeSynonyme(s)Image xs ;Image multispectrale donnees multispectralesVoir aussi |
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Extraction of tidal channel networks from aerial photographs alone and combined with laser altimetry / Bharat Lohani in International Journal of Remote Sensing IJRS, vol 27 n°1-2 (January 2006)
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Titre : Extraction of tidal channel networks from aerial photographs alone and combined with laser altimetry Type de document : Article/Communication Auteurs : Bharat Lohani, Auteur ; D.C. Mason, Auteur ; T.R. Scott, Auteur ; B. Sreenivas, Auteur Année de publication : 2006 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] détection de contours
[Termes IGN] données lidar
[Termes IGN] fusion d'images
[Termes IGN] fusion de données
[Termes IGN] identification automatique
[Termes IGN] image multibande
[Termes IGN] marais salé
[Termes IGN] océanographie dynamique
[Termes IGN] sédimentationRésumé : (Auteur) Tidal channel networks play an important role in the intertidal zone, exerting substantial control over the hydrodynamics and sediment transport of the region and hence over the evolution of the salt marshes and tidal flats. The study of the morphodynamics of tidal channels is currently an active area of research, and a number of theories have been proposed which require for their validation measurement of channels over extensive areas. Remotely sensed data provide a suitable means for such channel mapping. The paper describes a technique that may be adapted to extract tidal channels from either aerial photographs or LiDAR data separately, or from both types of data used together in a fusion approach. Application of the technique to channel extraction from LiDAR data has been described previously. However, aerial photographs of intertidal zones are much more commonly available than LiDAR data, and most LiDAR flights now involve acquisition of multispectral images to complement the LiDAR data. In view of this, the paper investigates the use of multispectral data for semiautomatic identification of tidal channels, firstly from only aerial photographs or linescanner data, and secondly from fused linescanner and LiDAR data sets. A multi-level, knowledge-based approach is employed. The algorithm based on aerial photography can achieve a useful channel extraction, though may fail to detect some of the smaller channels, partly because the spectral response of parts of the non-channel areas may be similar to that of the channels. The algorithm for channel extraction from fused LiDAR and spectral data gives an increased accuracy, though only slightly higher than that obtained using LiDAR data alone. The results illustrate the difficulty of developing a fully automated method, and justify the semi-automatic approach adopted. Numéro de notice : A2006-058 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160500206692 En ligne : https://doi.org/10.1080/01431160500206692 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27785
in International Journal of Remote Sensing IJRS > vol 27 n°1-2 (January 2006)[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 080-06011 RAB Revue Centre de documentation En réserve L003 Disponible On the optimization and selection of wavelet texture for feature extraction from high-resolution satellite imagery with application towards urban-tree delineation / Y.O. Ouma in International Journal of Remote Sensing IJRS, vol 27 n°1-2 (January 2006)
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Titre : On the optimization and selection of wavelet texture for feature extraction from high-resolution satellite imagery with application towards urban-tree delineation Type de document : Article/Communication Auteurs : Y.O. Ouma, Auteur ; T.G. Ngigi, Auteur ; et al., Auteur Année de publication : 2006 Article en page(s) : pp 73 - 104 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse texturale
[Termes IGN] arbre urbain
[Termes IGN] données multiéchelles
[Termes IGN] extraction automatique
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] image à très haute résolution
[Termes IGN] image multibande
[Termes IGN] image Quickbird
[Termes IGN] optimisation (mathématiques)
[Termes IGN] texture d'image
[Termes IGN] transformation en ondelettesRésumé : (Auteur) Integration of spectral and multi-scale texture is proposed in order to improve the detection and classification of urban-trees from Quickbird imagery. Arguing that spatial -structure semantic information exits at a hierarchy of scales and that texture is a consequence of objects in the hierarchy, multi-scale wavelets decomposition is proposed for the extraction of vertical, horizontal and diagonal texture components. Pre-selection of texture sub-bands is achieved via mean, entropy, variance and second angular moment. The resulting sub-bands are analysed for separability between trees and similarly reflecting features, such as rice-paddy, grass/lawns, open ground and playground, based on KuIlbackLeibler (KL) divergence and Battacharyya distance. The results are ranked and classified with k-means. In comparison with the field data, KL gave the best results with omission and commission error of 4.4%. The proposed methodology has the ability to capture the increased natural variability in reflectance and improved the accuracy by 23.6%, in comparison with spectral-only. Numéro de notice : A2006-059 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160500295885 En ligne : https://doi.org/10.1080/01431160500295885 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27786
in International Journal of Remote Sensing IJRS > vol 27 n°1-2 (January 2006) . - pp 73 - 104[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 080-06011 RAB Revue Centre de documentation En réserve L003 Disponible
Titre : Resource management information systems : remote sensing, GIS and modelling Type de document : Monographie Auteurs : K.R. Mccloy, Auteur Mention d'édition : 2 Editeur : Londres : Taylor & Francis Année de publication : 2006 Importance : 575 p. Format : 18 x 26 cm - cont. 1 cédérom ISBN/ISSN/EAN : 978-0-415-26340-5 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Télédétection
[Termes IGN] accentuation d'image
[Termes IGN] aide à la décision
[Termes IGN] analyse de groupement
[Termes IGN] analyse visuelle
[Termes IGN] capteur actif
[Termes IGN] capteur passif
[Termes IGN] classification
[Termes IGN] correction atmosphérique
[Termes IGN] données de terrain
[Termes IGN] données localisées
[Termes IGN] estimation statistique
[Termes IGN] gestion des ressources
[Termes IGN] image hyperspectrale
[Termes IGN] indice de végétation
[Termes IGN] modèle atmosphérique
[Termes IGN] rayonnement électromagnétique
[Termes IGN] restauration d'image
[Termes IGN] SIG 3D
[Termes IGN] système d'information géographique
[Termes IGN] traitement d'imageIndex. décimale : 35.00 Télédétection - généralités Résumé : (Editeur) This new edition brings together a range of material on the geographical and spatial information systems required for the effective management of spatially distributed resources. It build a sound theoretical basis and sets out the principles of remote sensing, image interpretation and processing, GIS, and the use of field data. A new chapter on modeling provides more detail and depth, and additional or significantly enhanced topics include hyperspectral optical data, radar (and its interaction with optical data), vector data, and the conversion between data types and estimation. The book is illustrated with case studies to show the best ways to use the various techniques in practice. Note de contenu : Chapter 1 Introduction
1.1 Goals of this book
1.2 Current starus of resources
1.3 Impact of resource degradation
1.4 Nature of resource degradation
1.5 Nature of resource management
1.6 Nature of Regional resource management information systems
1.7 Geographic information in resource management
1.8 Structure of this book
Chapter 2 Physical principles of remote sensing
2.1 Introduction
2.2 Electromagnetic radiation
2.3 Interaction of radiation with matter
2.4 Passive sensing systems
2.5 Active sensing systems
2.6 Hyperspectral image data
2.7 Hypertemporal image data
2.8 Platforms
2.9 Satellite sensor systems
Chapter 3 Visual interpretation and map reading
3.1 Overview
3.2 Stereoscopy
3.3 Measuring height differences in a stereoscopic pair of photographs
3.4 Planimetric measurements on aerial photographs
3.5 Perception of colour
3.6 Principles of photographic interpretation
3.7 Visual interpretation of images
3.8 Maps and map reading
Chapter 4 Image processing
4.1 Overview
4.2 Statistical considerations
4.3 Pre-processing of image data
4.4 The enhancement of image data
4.5 Analysis of mixtures or end member analysis
4.6 Image classification
4.7 Clustering
4.8 Estimation
4.9 Analysis of hyper-spectral image data
4.10 Analysis of dynamic processes
4.11 Summary
Chapter 5 Use of field data
5.1 The purpose of field data
5.2 Collection of field spectral data
5.3 Use of field data in visual interpretation
5.4 Use of field data in the classification of digital image data
5.5 Stratified random sampling method
5.6 Accuracy assessment
5.7 Summary
Chapter 6 Geographic information systems
6.1 Introduction to geographic information systems
6.2 Data input
6.3 Simple raster data analysis in a GIS
6.4 Vector GIS data analysis functions (Susanne Kickner)
6.5 Data management in a GIS
6.6 Advanced analysis techniques in a Vector GIS - Network modelling (Susanne Kickner)
6.7 Advanced raster analysis techniques in a GIS
6.8 Modelling in a GIS
6.9 Uncertainty in GIS analysis
6.10 Presentation in a GIS
6.11 Three-dimensional GIS
Chapter 7 The analysis and interpretation of vegetation
7.1 Introduction
7.2 Regional vegetation mapping and monitoring
7.3 Signatures of vegetation
7.4 Modelling canopy reflectance
7.5 Estimation of vegetation parameters and status
7.6 Classification of vegetation
7.7 Analysis of vegetation phenology
7.8 Concluding remarks
Chapter 8 The management of spatial resources and decision support
8.1 Introduction
8.2 Nature of management of rural physical resources
8.3 Process of decision making in resource management
8.4 Decision support systems and their role in decision making
8.5 Other project management tools
8.6 Concluding remarksNuméro de notice : 16785 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Monographie Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=55243 Réservation
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Code-barres Cote Support Localisation Section Disponibilité 16785-01 35.00 Livre Centre de documentation Télédétection Disponible
Titre : Sampling scheme optimization from hyperspectral data Type de document : Thèse/HDR Auteurs : Pravesh Debba, Auteur Editeur : Enschede [Pays-Bas] : International Institute for Geo-Information Science and Earth Observation ITC Année de publication : 2006 Collection : ITC Publication num. 136 Importance : 164 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-90-8504-462-8 Note générale : bibliographie
thesis to fulfil the requirements for the degree of doctor on the autority of the rector magnificus of Wageningen UniversityLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] échantillonnage
[Termes IGN] image hyperspectrale
[Termes IGN] optimisation (mathématiques)Index. décimale : 35.20 Traitement d'image Numéro de notice : 17213 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère Note de thèse : thesis : Geoinformation science : Wageningen University : 2006 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81337 Réservation
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Code-barres Cote Support Localisation Section Disponibilité 17213-01 35.20 Livre Centre de documentation Télédétection Disponible Integrating LIDAR elevation data, multi-spectral imagery and neural network modelling for marsh characterization / J.T. Morris in International Journal of Remote Sensing IJRS, vol 26 n° 23 (December 2005)
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Titre : Integrating LIDAR elevation data, multi-spectral imagery and neural network modelling for marsh characterization Type de document : Article/Communication Auteurs : J.T. Morris, Auteur ; D. Porter, Auteur ; et al., Auteur Année de publication : 2005 Article en page(s) : pp 5221 - 5234 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Caroline du Sud (Etats-Unis)
[Termes IGN] classification dirigée
[Termes IGN] classification par réseau neuronal
[Termes IGN] données altimétriques
[Termes IGN] données lidar
[Termes IGN] image ADAR
[Termes IGN] image multibande
[Termes IGN] marais salant
[Termes IGN] niveau moyen des mers
[Termes IGN] North American Vertical Datum 1988
[Termes IGN] plante halophile
[Termes IGN] réseau neuronal artificiel
[Termes IGN] sédimentation
[Termes IGN] système de référence géodésiqueRésumé : (Auteur) Vertical elevation relative to mean sea level is a critical variable for the productivity and stability of salt marshes. This research classified a high spatial resolution Airborne Data Acquisition and Registration (ADAR) digital camera image of a salt marsh landscape at North Inlet, South Carolina, USA using an artificial neural network. The remote sensing-derived thematic map was cross-referenced with Light Detection and Ranging (LIDAR) elevation data to compute the frequency distribution of marsh elevation relative to tidal elevations. At North Inlet, the median elevation of the salt marsh dominated by Spartina alterniflora was 0.349m relative to the North American Vertical Datum 1988 (NAVD88), while the mean high water level was 0.618m (2001 to May, 2003) with a mean tidal range of 1.39m. The distribution of elevations of Spartina habitat within its vertical range was normal, and 80% of the salt marsh was situated between a narrow range of 0.22 m and 0.481 m. Areas classified as Juncus marsh, dominated by Juneus roemerianus, had a broader, skewed distribution, with 80% of the distribution between 0.296 m and 0.981 m and a median elevation of 0.519 m. The Juneus marsh occurs within the intertidal region of brackish marshes and along the upper fringe of salt marshes. The relative elevation of the Spartina marsh at North Inlet is consistent with recent work that predicts a decrease in equilibrium elevation with an increasing rate of sea-level rise and suggests that the marshes here have not kept up with an increase in the rate of sea-level rise during the last two decades. Numéro de notice : A2005-515 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160500219018 En ligne : https://doi.org/10.1080/01431160500219018 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27651
in International Journal of Remote Sensing IJRS > vol 26 n° 23 (December 2005) . - pp 5221 - 5234[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-05231 RAB Revue Centre de documentation En réserve L003 Exclu du prêt ASTER geometric performance / A. Iwasaki in IEEE Transactions on geoscience and remote sensing, vol 43 n° 12 (December 2005)
PermalinkMapping impervious surface type and sub-pixel abundance using Hyperion hyperspectral imagery / J. Falcone in Geocarto international, vol 20 n° 4 (December 2005 - February 2006)
PermalinkA method for the surface reflectance retrieval from PROBA/CHRIS data over land: application to ESA SPARC campaigns / L. Guanter in IEEE Transactions on geoscience and remote sensing, vol 43 n° 12 (December 2005)
PermalinkA change detection model based on neighborhood correlation image analysis and decision tree classification / J. Im in Remote sensing of environment, vol 99 n° 3 (30/11/2005)
PermalinkMesures et caractérisation des changements d'occupation des sols à partir de l'analyse diachronique de données satellitales : application à la zone humide d'Akgöl (Turquie) / D. Gramond in Photo interprétation, vol 41 n° 4 (Novembre 2005)
PermalinkWavelet filter analysis of local atmospheric pressure effects on gravity variations / X.G. Hu in Journal of geodesy, vol 79 n° 8 (November 2005)
PermalinkFusion of hyperspectral data using segmented PCT for color representation and classification / V. Tsagaris in IEEE Transactions on geoscience and remote sensing, vol 43 n° 10 (October 2005)
PermalinkQuality criteria benchmark for hyperspectral imagery / E. Christophe in IEEE Transactions on geoscience and remote sensing, vol 43 n° 9 (September 2005)
PermalinkRemote sensing of water quality for Burullus lake, Egypt / Kh. M. Dewidar in Geocarto international, vol 20 n° 3 (September - November 2005)
PermalinkSpectral filtering and classification of terrestrial laser scanner point clouds / Derek D. Lichti in Photogrammetric record, vol 20 n° 111 (September - November 2005)
PermalinkUtilisation des images satellitaires Spot pour la cartographie des types de peuplements de la forêt de la Mamora (Maroc) / Abderrahman Aafi in Revue Française de Photogrammétrie et de Télédétection, n° 178 (Septembre 2005)
PermalinkDe-shadowing of satellite/airborne imagery / R. Richter in International Journal of Remote Sensing IJRS, vol 26 n° 15 (August 2005)
PermalinkPermalinkA statistical self-organizing learning system for remote sensing classification / H.M. Chi in IEEE Transactions on geoscience and remote sensing, vol 43 n° 8 (August 2005)
PermalinkMultivariate texture-based segmentation of remotely sensed imagery for extraction of objects and their uncertainty / Arko Lucieer in International Journal of Remote Sensing IJRS, vol 26 n° 14 (July 2005)
PermalinkA comparative analysis of image fusion methods / Z. Wang in IEEE Transactions on geoscience and remote sensing, vol 43 n° 6 (June 2005)
PermalinkDesigning fuzzy rule based classifier using self-organizing feature map for analysis of multispectral satellite images / Nikhil R. Pal in International Journal of Remote Sensing IJRS, vol 26 n° 10 (May 2005)
PermalinkNeural network model for standard PCA and its variants applied to remote sensing / S. Chitroub in International Journal of Remote Sensing IJRS, vol 26 n° 10 (May 2005)
PermalinkA comparison of local variance, fractal dimension, and Moran's index as aids to multispectral image classification / C.W. Emerson in International Journal of Remote Sensing IJRS, vol 26 n° 8 (April 2005)
PermalinkA whole image approach using field measurements for transforming EO1 Hyperion hyperspectral data into canopy reflectance spectra / E.W. Ramsey in International Journal of Remote Sensing IJRS, vol 26 n° 8 (April 2005)
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