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Estimating tropical forest biomass with a combination of SAR image texture and Landsat TM data: An assessment of predictions between regions / M. Cutler in ISPRS Journal of photogrammetry and remote sensing, vol 70 (June 2012)
[article]
Titre : Estimating tropical forest biomass with a combination of SAR image texture and Landsat TM data: An assessment of predictions between regions Type de document : Article/Communication Auteurs : M. Cutler, Auteur ; D. Boyd, Auteur ; Giles M. Foody, Auteur ; A. Vetrivel, Auteur Année de publication : 2012 Article en page(s) : pp 66 - 77 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] analyse comparative
[Termes IGN] analyse texturale
[Termes IGN] biomasse
[Termes IGN] biomasse (combustible)
[Termes IGN] Brésil
[Termes IGN] classification par réseau neuronal
[Termes IGN] déboisement
[Termes IGN] forêt tropicale
[Termes IGN] image JERS
[Termes IGN] image Landsat-TM
[Termes IGN] image multibande
[Termes IGN] image radar
[Termes IGN] Malaisie
[Termes IGN] matrice de co-occurrence
[Termes IGN] niveau de gris (image)
[Termes IGN] ondelette
[Termes IGN] texture d'image
[Termes IGN] ThaïlandeRésumé : (Auteur) Quantifying the above ground biomass of tropical forests is critical for understanding the dynamics of carbon fluxes between terrestrial ecosystems and the atmosphere, as well as monitoring ecosystem responses to environmental change. Remote sensing remains an attractive tool for estimating tropical forest biomass but relationships and methods used at one site have not always proved applicable to other locations. This lack of a widely applicable general relationship limits the operational use of remote sensing as a method for biomass estimation, particularly in high biomass ecosystems. Here, multispectral Landsat TM and JERS-1 SAR data were used together to estimate tropical forest biomass at three separate geographical locations: Brazil, Malaysia and Thailand. Texture measures were derived from the JERS-1 SAR data using both wavelet analysis and Grey Level Co-occurrence Matrix methods, and coupled with multispectral data to provide inputs to artificial neural networks that were trained under four different training scenarios and validated using biomass measured from 144 field plots. When trained and tested with data collected from the same location, the addition of SAR texture to multispectral data showed strong correlations with above ground biomass (r = 0.79, 0.79 and 0.84 for Thailand, Malaysia and Brazil respectively). Also, when networks were trained and tested with data from all three sites, the strength of correlation (r = 0.55) was stronger than previously reported results from the same sites that used multispectral data only. Uncertainty in estimating AGB from different allometric equations was also tested but found to have little effect on the strength of the relationships observed. The results suggest that the inclusion of SAR texture with multispectral data can go someway towards providing relationships that are transferable across time and space, but that further work is required if satellite remote sensing is to provide robust and reliable methodologies for initiatives such as Reducing Emissions from Deforestation and Degradation (REDD+). Numéro de notice : A2012-289 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.03.011 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.03.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31735
in ISPRS Journal of photogrammetry and remote sensing > vol 70 (June 2012) . - pp 66 - 77[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2012041 SL Revue Centre de documentation Revues en salle Disponible A geometry and texture coupled flexible generalization of urban building models / M. Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 70 (June 2012)
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Titre : A geometry and texture coupled flexible generalization of urban building models Type de document : Article/Communication Auteurs : M. Zhang, Auteur ; L. Zhang, Auteur ; P. Takis, Auteur ; P. Takis Mathiopoulos, Auteur ; W. Xie, Auteur ; Y. Ding, Auteur ; H. Wang, Auteur Année de publication : 2012 Article en page(s) : pp 1 - 24 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] attribut géomètrique
[Termes IGN] CityGML
[Termes IGN] données localisées 3D
[Termes IGN] façade
[Termes IGN] généralisation du bâti
[Termes IGN] instance
[Termes IGN] modèle 3D de l'espace urbain
[Termes IGN] modèle numérique du bâti
[Termes IGN] précision géométrique (imagerie)
[Termes IGN] réalité virtuelle
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] texture d'image
[Vedettes matières IGN] GénéralisationRésumé : (Auteur) In the past, numerous research efforts have focused on generalization of city building models. However, a generic procedure for creating flexible generalization results supporting the fast and efficient update of original building models with various complexities is still an open problem. Moreover, building clusters created in previously published generalization methods are not flexible enough to meet the various requirements for both legible and realistic visualization. Motivated by these observations, this paper proposes a new method for generating a flexible generalization outcome which enables convenient updating of original building models. It also proposes a flexible preprocessing of this generalized information to render a legible and realistic urban scene. This is accomplished by introducing a novel component structure, termed as FEdge, particularly designed for efficiently managing the geometry and texture information in building cluster instances (both original building models and building clusters) during the generalization, visualization and updating processes. Furthermore, a multiple representation structure, referred to as Evolved Buffer-Tree (EBT), is also introduced. The purpose of the EBT is to organize building cluster instances and to employ more flexible LODs for both legible and realistic visualization of urban scenes. FEdge has an intuitive planar shape which can be effectively used in representing rough 3D facade composed by detailed continuous meshes. Each FEdge is given a unique identifier, referred to as FEdge Index. In the proposed generalization scheme, firstly each original building model treated as a building cluster instance is abstracted and presented as FEdge Indices. These FEdge Indices are then used for producing generalized building cluster instances in the EBT portably, and to support convenient model updating and flexible preprocessing of the generalization results for renderable building cluster instances. Secondly, to achieve a legible and realistic visualization of urban scene, the EBT is flexibly assigned diverse LODs maintaining more important legible information than LODs defined in CityGML for 3D building models. To make the generalization more accurate by considering the city roads and districts, an algorithm for automatic road analysis is applied in our clustering and combination. Numerous experiments considering the geometrical and textural complexity of common urban building models, as well as a typical case study of complex city scene with a large number of building models, verify the effectiveness of our generalization method and the dynamic visualization of the generalized urban models. Numéro de notice : A2012-285 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.03.008 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.03.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31731
in ISPRS Journal of photogrammetry and remote sensing > vol 70 (June 2012) . - pp 1 - 24[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2012041 SL Revue Centre de documentation Revues en salle Disponible Evaluation of bayesian despeckling and texture extraction methods based on Gauss–Markov and auto-binomial gibbs random fields: Application to TerraSAR-X data / D. Espinoza Molina in IEEE Transactions on geoscience and remote sensing, vol 50 n° 5 Tome 2 (May 2012)
[article]
Titre : Evaluation of bayesian despeckling and texture extraction methods based on Gauss–Markov and auto-binomial gibbs random fields: Application to TerraSAR-X data Type de document : Article/Communication Auteurs : D. Espinoza Molina, Auteur ; D. Gleich, Auteur ; M. Dactu, Auteur Année de publication : 2012 Article en page(s) : pp 2001 - 2025 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] analyse comparative
[Termes IGN] analyse texturale
[Termes IGN] champ aléatoire de Markov
[Termes IGN] échantillonnage de Gibbs
[Termes IGN] évaluation
[Termes IGN] filtre de déchatoiement
[Termes IGN] image radar moirée
[Termes IGN] image TerraSAR-X
[Termes IGN] inférence statistique
[Termes IGN] texture d'imageRésumé : (Auteur) Speckle hinders information in synthetic aperture radar (SAR) images and makes automatic information extraction very difficult. The Bayesian approach allows us to perform the despeckling of an image while preserving its texture and structures. This model-based approach relies on a prior model of the scene. This paper presents an evaluation of two despeckling and texture extraction model-based methods using the two levels of Bayesian inference. The first method uses a Gauss-Markov random field as prior, and the second is based on an auto-binomial model (ABM). Both methods calculate a maximum a posteriori and determine the best model using an evidence maximization algorithm. Our evaluation approach assesses the quality of the image by means of the despeckling and texture extraction qualities. The proposed objective measures are used to quantify the despeckling performances of these methods. The accuracy of modeling and characterization of texture were determined using both supervised and unsupervised classifications, and confusion matrices. Real and simulated SAR data were used during the validation procedure. The results show that both methods enhance the image during the despeckling process. The ABM is superior regarding texture extraction and despeckling for real SAR images. Numéro de notice : A2012-190 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2169679 En ligne : https://doi.org/10.1109/TGRS.2011.2169679 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31637
in IEEE Transactions on geoscience and remote sensing > vol 50 n° 5 Tome 2 (May 2012) . - pp 2001 - 2025[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2012051B RAB Revue Centre de documentation En réserve L003 Disponible Potential of texture measurements of two-date dual polarization PALSAR data for the improvement of forest biomass estimation / M. Sarker in ISPRS Journal of photogrammetry and remote sensing, vol 69 (April 2012)
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Titre : Potential of texture measurements of two-date dual polarization PALSAR data for the improvement of forest biomass estimation Type de document : Article/Communication Auteurs : M. Sarker, Auteur ; J. Nichol, Auteur ; B. Ahmad, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 146 - 166 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] biomasse
[Termes IGN] Hong-Kong
[Termes IGN] image ALOS-PALSAR
[Termes IGN] image radar moirée
[Termes IGN] polarimétrie radar
[Termes IGN] polarisation
[Termes IGN] texture d'imageRésumé : (Auteur) The recently available space-borne SAR sensor, PALSAR, is more promising than its predecessor JERS-1 for biomass estimation because of its long wavelength (L-band), and its ability to provide data with different polarizations, varying incidence angles and higher spatial resolutions. This research investigates the potential of two-date dual polarization (HH and HV) SAR imagery for biomass estimation using different kinds of texture processing and different combinations of single and dual polarization ratios. The investigation is conducted in a mountainous, sub-tropical study area where biomass levels are far beyond the previously recognized saturation levels for L-band SAR images, and forest is a mixture of native and non-native species and plantations. We analyzed two-date SAR data with four steps of image processing, including raw data processing in various combinations, texture measurement parameters of HH and HV polarizations, texture measurement parameters of HH and HV together (both jointly and as a ratio), and a ratio of two-date texture parameters along with a single and two-date ratio. When the processed images were compared with ground data from 50 plots, the performance from raw data processing was low, with adjusted r2 = 0.22, but after all four processing steps, promising model accuracy (adjusted r2 = 0.90 and RMSE = 28.58 t/ha) and validation accuracy (using the Leave-One-Out-Cross-Validation) with adjusted r2 = 0.88 and RMSE = 35.69 t/ha, were achieved from the combination of single- and two-date polarization ratios of texture parameters. The strong performance achieved indicates that L-band dual-polarization (HH and HV) SAR data from PALSAR has great potential for biomass estimation, far beyond the previously reported L-band saturation point for biomass. This result is attributed to the synergy among texture processing and dual polarization on the one hand, which were able to average out random speckle noise, and the use of ratio instead of absolute quantities, due to its well known ability to reduce forest structural and terrain effects. The additional use of two-date SAR data with these processing techniques was able to add complementary information derived from biomass response in both wet and dry seasons. Thus overall, undesirable image noise and terrain effects were reduced. Numéro de notice : A2012-198 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.03.002 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.03.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31645
in ISPRS Journal of photogrammetry and remote sensing > vol 69 (April 2012) . - pp 146 - 166[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2012031 SL Revue Centre de documentation Revues en salle Disponible Détection et identification de zones de végétation arborée: utilisation conjointe d'images satellite RapidEye et de données BDOrtho / François Tassin (2012)
Titre : Détection et identification de zones de végétation arborée: utilisation conjointe d'images satellite RapidEye et de données BDOrtho Type de document : Mémoire Auteurs : François Tassin, Auteur ; Arnaud Le Bris , Encadrant ; Clément Mallet , Encadrant Editeur : Lyon : Ecole Centrale de Lyon Année de publication : 2012 Importance : 48 p. Format : 21 x 30 cm Note générale : bibliographie
Rapport de Stage, Ecole Centrale LyonLangues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse discriminante
[Termes IGN] bande rouge
[Termes IGN] BD ortho
[Termes IGN] classificateur paramétrique
[Termes IGN] classification dirigée
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] détection d'arbres
[Termes IGN] extraction de la végétation
[Termes IGN] filtre de Gabor
[Termes IGN] forêt
[Termes IGN] image aérienne
[Termes IGN] image infrarouge couleur
[Termes IGN] image RapidEye
[Termes IGN] orthoimage couleur
[Termes IGN] peuplement végétal
[Termes IGN] texture d'imageRésumé : (auteur) La production des bases de données géographiques nationales par l'IGN repose en grande partie sur le travail de photo-interprètes. Le laboratoire MATIS poursuit des recherches pour automatiser partiellement certaines étapes de la chaine de production, notamment la saisie initiale des zones de végétation arborée. L'objet de cette étude est d'étudier l'apport du satellite RapidEye, utilisé conjointement avec les images aériennes produites par l'IGN, pour deux problématiques : la détection de la végétation arborée d'une part et la discrimination des types de peuplements d'autre part. L'étude repose sur l'utilisation des images satellite RapidEye (résolution 5m) et des images aériennes de l'IGN (résolution 50cm). Deux classifieurs sont comparés, un classifieur probabiliste (modélisation statistique de la radiométrie des différentes classes) développé en interne et les "Support Vector Machines". Plusieurs combinaisons de canaux radiométriques, d'indices de végétation et d'attributs texturaux sont étudiés et l'apport de la bande spectrale red edge est discuté. Il apparait que la détection de la végétation arborée est plus efficace quand les images RapidEye sont associées à des informations texturales obtenues grâce aux images aériennes, tandis que la discrimination des espèces est plus efficace avec les images satellite. Enfin des pistes de réflexion sur la possibilité de mise à jour automatique de la base de données sont aussi abordées. Note de contenu : Introduction
1 - Organisation de l'entreprise
2 - Présentation du stage
3 - Méthodologie
4 - Détection de la végétation arborée : séparation forêt/non-forêt
5 - Discrimination des Espèces
ConclusionNuméro de notice : 21687 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Rapport de stage Organisme de stage : MATIS (IGN) Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90925 Documents numériques
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Diaporama présentation - pdf auteurAdobe Acrobat PDF Recovering quasi-real occlusion-free textures for facade models by exploiting fusion of image and laser street data and image inpainting / Karim Hammoudi (2012)PermalinkUne approche parallèle d'évaluation des paramètres de texture pour l'analyse d'images de grande taille / N. Talla Tankam in Revue Française de Photogrammétrie et de Télédétection, n° 195 (Novembre 2011)PermalinkClassification orientée-objet supervisée d'une forêt avec une sélection guidée d'attributs personnalisés / Olivier de Joinville in Revue Française de Photogrammétrie et de Télédétection, n° 195 (Novembre 2011)PermalinkSurveying buildings: Point clouds and multi-image panoramas / Luigi Colombo in Geoinformatics, vol 14 n° 7 (01/10/2011)PermalinkOndelettes et théorie des évidences pour la classification orientée-objet : Caractérisation et suivi des changements d’occupation des sols de la métropole de Rennes / A. Lefebvre in Revue internationale de géomatique, vol 21 n° 3 (septembre - novembre 2011)PermalinkMulti close-range image matching based on a self-adaptive triangle constraint / Q. Zhu in Photogrammetric record, vol 25 n° 132 (December 2010 - February 2011)PermalinkEvaluation of the influence of local fuel homogeneity on fire hazard through Landsat-5 TM texture measures / Cristina Vega-Garcia in Photogrammetric Engineering & Remote Sensing, PERS, vol 76 n° 7 (July 2010)PermalinkColor correction of texture images for true photorealistic visualization / Y. Song in ISPRS Journal of photogrammetry and remote sensing, vol 65 n° 3 (May - June 2010)Permalinkvol 65 n° 3 - May - June 2010 - Visualisation and exploration of geospatial data (Bulletin de ISPRS Journal of photogrammetry and remote sensing) / Jochen SchiewePermalinkInfluence of image characteristics on image quality / T. Royer (2010)Permalink