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Postflood damage evaluation using landsat TM and ETM+ data integrated with DEM / M. Gianinetto in IEEE Transactions on geoscience and remote sensing, vol 44 n° 1 (January 2006)
[article]
Titre : Postflood damage evaluation using landsat TM and ETM+ data integrated with DEM Type de document : Article/Communication Auteurs : M. Gianinetto, Auteur ; P. Villa, Auteur ; G. Lechi, Auteur Année de publication : 2006 Article en page(s) : pp 236 - 243 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] aide à la décision
[Termes IGN] analyse comparative
[Termes IGN] analyse diachronique
[Termes IGN] analyse en composantes principales
[Termes IGN] dommage matériel
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-TM
[Termes IGN] impact sur l'environnement
[Termes IGN] inondation
[Termes IGN] Italie
[Termes IGN] modèle numérique de surface
[Termes IGN] risque naturel
[Termes IGN] segmentation d'imageRésumé : (Auteur) In recent decades, radar and optical satellite imagery have been used for evaluating flooding extent. In this paper, a straightforward technique based on the sequential use of the spectral-temporal principal component analysis, logical filtering, and image segmentation integrated with the digital elevation model was developed as a decisional support tool for the allocations of the resource destined for the flooded areas. The mapping technique was first applied to the catastrophic event that occurred in the Piemonte Region (Italy) in November 1994, which was the worst event of the past century for that region, with 44 casualities and over 2000 homeless. Next, it was applied to the Obion/Forked Deer inundation that occurred in Tennessee (U.S.) between November and December 2001, in which heavy damage to the infrastructure was reported. Two Landsat-5 Thematic Mapper (path 194, row 28/29) and two Landsat-7 Enhanced Thematic Mapper Plus (path 23, row 35) images were processed, two of them collected before and two after the events. The method proposed proved to be an effective approach for evaluating flood extent and for assessing the damage produced by the flooding. An overall accuracy of 85.6%, a user accuracy of 87.5 %, and a producer accuracy of 97.5 % were achieved, and an agreement of 83% between ground measures and remotely sensed data in the estimation of flood water volumes was also achieved on a regional scale. Numéro de notice : A2006-090 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2005.859952 En ligne : https://doi.org/10.1109/TGRS.2005.859952 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27817
in IEEE Transactions on geoscience and remote sensing > vol 44 n° 1 (January 2006) . - pp 236 - 243[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-06011 RAB Revue Centre de documentation En réserve L003 Disponible Resource management information systems / K.R. Mccloy (2006)
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 Application of multiple endmember spectral mixture analysis (MESMA) to AVIRIS imagery for coastal salt marsh mapping: a case study in China Camp, CA, USA / L. Li in International Journal of Remote Sensing IJRS, vol 26 n° 23 (December 2005)
[article]
Titre : Application of multiple endmember spectral mixture analysis (MESMA) to AVIRIS imagery for coastal salt marsh mapping: a case study in China Camp, CA, USA Type de document : Article/Communication Auteurs : L. Li, Auteur ; S.L. Ustin, Auteur ; M. Lay, Auteur Année de publication : 2005 Article en page(s) : pp 5193 - 5207 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse de mélange spectral d’extrémités multiples
[Termes IGN] analyse discriminante
[Termes IGN] analyse multibande
[Termes IGN] bande infrarouge
[Termes IGN] Californie (Etats-Unis)
[Termes IGN] carte de la végétation
[Termes IGN] image AVIRIS
[Termes IGN] littoral
[Termes IGN] marais salé
[Termes IGN] plante halophileRésumé : (Auteur) Multiple endmember spectral mixture analysis (MESMA) was applied to the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) imagery of a salt marsh in China Camp at San Pablo Bay, California, A nine-endmember set representing materials within the scene was used including: two Salicornia and two soils, and Grindelia, Spartina, dry grass, water and shade. The resultant abundance maps were used to investigate the spatial distribution of the marsh vegetation species, Salicornia virginica, Grindelia Stricta and Spartinafoliosa. The Spartina abundance map exhibited a well-defined zone bordering the water and the lower marsh, which is in good agreement with the field observations made in 2002. Comparison of the Salicornia map with all six field global positional system (GPS) polygons indicates Salicornia was classified with high accuracy. The proposed approach did a good job in classifying Spartina and Salicornia which cover 93.81% of the total marsh. The Grindelia fraction image underestimates in some areas, while in other areas it shows false detection. This misclassification is attributed to the spectral similarity between Grindelia and Salicornia and to the small patch size of Grindelia. Further work is required to solve this confusion. Numéro de notice : A2005-514 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160500218911 En ligne : https://doi.org/10.1080/01431160500218911 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27650
in International Journal of Remote Sensing IJRS > vol 26 n° 23 (December 2005) . - pp 5193 - 5207[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-05231 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Reconstructing spatiotemporal trajectories from sparse data / P. Partsinevelos in ISPRS Journal of photogrammetry and remote sensing, vol 60 n° 1 (December 2005 - March 2006)
[article]
Titre : Reconstructing spatiotemporal trajectories from sparse data Type de document : Article/Communication Auteurs : P. Partsinevelos, Auteur ; Peggy Agouris, Auteur ; A. Stefanidis, Auteur Année de publication : 2005 Article en page(s) : pp 3 - 16 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse de groupement
[Termes IGN] carte de Kohonen
[Termes IGN] classification dirigée
[Termes IGN] classification par réseau neuronal
[Termes IGN] données spatiotemporelles
[Termes IGN] modélisation spatio-temporelle
[Termes IGN] objet mobile
[Termes IGN] reconstruction d'itinéraire ou de trajectoire
[Termes IGN] segmentation
[Termes IGN] seuillageRésumé : (Auteur) In motion imagery-based tracking applications, it is common to extract locations of moving objects without any knowledge about the identity of the objects they correspond to. The identification of individual spatiotemporal trajectories from such data sets is far from trivial when these trajectories intersect in space, time, or attributes. In this paper, we present a novel approach for the reconstruction of entangled spatiotemporal trajectories of moving objects captured in motion imagery data sets. We have developed AGENT (Attribute-aided Classification of Entangled Trajectories), a novel framework that comprises classification, clustering, and neural net processes to progressively reconstruct elongated trajectories using as input spatiotemporal coordinates of image patches and corresponding attribute values. AGENT proceeds by first forming brief fragments and then linking them and adding points to them. An initial classification allows us to form brief segments corresponding to distinct objects. These segments are then linked together through clustering to form longer trajectories. Back-propagation neural network classification and geometric/self-organizing map (SOM) analysis refine these trajectories by removing misclassified and redistributing unassigned points. Thus, AGENT integrates some established classification and clustering tools to devise a novel approach that can address the tracking challenges of busy environments. Furthermore, AGENT allows us use spatiotemporal (ST) thresholds to cluster trajectories according to their spatial and temporal extent. In the paper, we present in detail our framework and experimental results that support the application potential of our approach. Numéro de notice : A2006-218 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2005.10.004 En ligne : https://doi.org/10.1016/j.isprsjprs.2005.10.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27945
in ISPRS Journal of photogrammetry and remote sensing > vol 60 n° 1 (December 2005 - March 2006) . - pp 3 - 16[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-06011 SL Revue Centre de documentation Revues en salle Disponible Utilisation des signatures de texture d'ordre elevé pour une meilleure discrimination des classes d'occupation du sol sur une image radar à synthese d'ouverture / E. Tonye in Revue Française de Photogrammétrie et de Télédétection, n° 179 (Décembre 2005)
[article]
Titre : Utilisation des signatures de texture d'ordre elevé pour une meilleure discrimination des classes d'occupation du sol sur une image radar à synthese d'ouverture Type de document : Article/Communication Auteurs : E. Tonye, Auteur ; A. Akono, Auteur ; Jean-Paul Rudant , Auteur ; et al., Auteur Année de publication : 2005 Article en page(s) : pp 3 - 17 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse discriminante
[Termes IGN] analyse texturale
[Termes IGN] bande C
[Termes IGN] Cameroun
[Termes IGN] flore locale
[Termes IGN] forêt
[Termes IGN] image ERS-SAR
[Termes IGN] image radar moirée
[Termes IGN] littoral
[Termes IGN] mangrove
[Termes IGN] marais
[Termes IGN] matrice de co-occurrence
[Termes IGN] milieu urbain
[Termes IGN] occupation du sol
[Termes IGN] polarisation
[Termes IGN] signature texturale
[Termes IGN] texture d'imageRésumé : (Auteur) Dans ce travail, on montre l'avantage des paramètres de texture d'ordre supérieur à 2 pour la discrimination des classes d'occupation du sol sur une image radar à synthèse d'ouverture (RSO). En effet, plusieurs études de classification texturales d'images RSO ont été effectuées jusqu'à maintenant, mais la plupart de ces études utilisent la technique des matrices de co-occurrence de niveaux de gris, qui est elle-même basée sur les paramètres de texture d'ordre 2. Dans cette étude, on mesure les signatures texturales aux ordres 2, 3 et 4 en quatre points distincts représentant quatre classes d'occupation du sol sur une image RSO ERS-1 de la côte Atlantique du Cameroun. Les signatures texturales mesurées sont établies à base de 17 paramètres de texture suffisamment discriminants. Une comparaison des signatures est ensuite effectuée et on constate que les signatures d'ordre supérieur produisent le meilleur taux de discrimination des classes d'occupation du sol. Numéro de notice : A2005-554 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27690
in Revue Française de Photogrammétrie et de Télédétection > n° 179 (Décembre 2005) . - pp 3 - 17[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 018-05031 RAB Revue Centre de documentation En réserve L003 Disponible Classifying and mapping wildfire severity: a comparison of methods / C.K. Brewer in Photogrammetric Engineering & Remote Sensing, PERS, vol 71 n° 11 (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)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)PermalinkStructural damage assessments from Ikonos data using change detection, object-oriented segmentation, and classification techniques / D.H.A. Khudhairy in Photogrammetric Engineering & Remote Sensing, PERS, vol 71 n° 7 (July 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)PermalinkLand covers update by supervised classification of segmented ASTER images / A.R.S. Marcal in International Journal of Remote Sensing IJRS, vol 26 n° 7 (April 2005)PermalinkSPOT-4 Vegetation multi-temporal compositing for land cover change studies over tropical regions / João M.B. Carreiras in International Journal of Remote Sensing IJRS, vol 26 n° 7 (April 2005)PermalinkIntegration of spatial and spectral information by means of unsupervised extraction and classification for homogenous objects applied to multispectral and hyperspectral data / L.O. Jimenez in IEEE Transactions on geoscience and remote sensing, vol 43 n° 4 (April 2005)PermalinkMultivariate analysis and geovisualization with an integrated geographic knowledge discovery approach / D. Guo in Cartography and Geographic Information Science, vol 32 n° 2 (April 2005)PermalinkRemote sensing image thresholding methods for determining landslide activity / P.L. Rosin in International Journal of Remote Sensing IJRS, vol 26 n° 6 (March 2005)PermalinkMapping tropical forest structure in south-eastern Madagascar using remote sensing and artificial neural networks / J.C. Ingram in Remote sensing of environment, vol 94 n° 4 (28/02/2005)PermalinkSatellite image classification using genetically guided fuzzy clustering with spatial information / S. Bandyopadhyay in International Journal of Remote Sensing IJRS, vol 26 n° 3 (February 2005)PermalinkAgriculture classification using PolSAR data / H. Skriver (2005)PermalinkNon rigid registration of shapes via diffeomorphic point matching and clustering / Laurent Garcin (2005)PermalinkTélédétection et paludisme urbain / Laurence Jolivet (2005)PermalinkA texture orientation estimator for discriminating between forests, orchards, vineyards, and tilled fields / Roger Trias-Sanz (2005)PermalinkDiscrimination potential of X-band polarimetric SAR data / Nicolas Baghdadi in International Journal of Remote Sensing IJRS, vol 25 n° 22 (November 2004)PermalinkFiltering airborne Laser scanner data: a wavelet-based clustering method / T. Thuy in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 11 (November 2004)PermalinkSpectral mixture analysis of the urban landscape in Indianapolis with Landsat ETM+ imagery / Dong Lu in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 9 (September 2004)PermalinkDerivation of a threshold function for the advanced very high resolution radiometer 3, 75um channel and its application in automatic cloud discrimination over snow/ice surfaces / X. Xiong in International Journal of Remote Sensing IJRS, vol 25 n° 15 (August 2004)Permalink