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An automated approach for updating land cover maps based on integrated change detection and classification methods / X. Chen in ISPRS Journal of photogrammetry and remote sensing, vol 71 (July 2012)
[article]
Titre : An automated approach for updating land cover maps based on integrated change detection and classification methods Type de document : Article/Communication Auteurs : X. Chen, Auteur ; J. Chen, Auteur ; Y. Shi, Auteur ; Yasushi Yamaguchi, Auteur Année de publication : 2012 Article en page(s) : pp 86 - 95 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] carte d'occupation du sol
[Termes IGN] champ aléatoire de Markov
[Termes IGN] Chensi (Chine)
[Termes IGN] détection de changement
[Termes IGN] image Landsat-ETM+
[Termes IGN] mise à jour de base de donnéesRésumé : (Auteur) Updating land cover maps from remotely sensed data in a timely manner is important for many areas of scientific research. Unfortunately, traditional classification procedures are very labor intensive and subjective because of the required human interaction. Based on the strategy of updating land cover data only for the changed area, we proposed an integrated, automated approach to update land cover maps without human interaction. The proposed method consists primarily of the following three parts: a change detection technique, a Markov Random Fields (MRFs) model, and an iterated training sample selecting procedure. In the proposed approach, remotely sensed data acquired in different seasons or from different remote sensors can be used. Meanwhile, the approach is completely unsupervised. Therefore, the methodology has a wide scope of application. A case study of Landsat data was conducted to test the performance of this method. The experimental results show that several sub-modules in this method work effectively and that reasonable classification accuracy can be achieved. Numéro de notice : A2012-350 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.05.006 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.05.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31796
in ISPRS Journal of photogrammetry and remote sensing > vol 71 (July 2012) . - pp 86 - 95[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2012051 SL Revue Centre de documentation Revues en salle Disponible The potential of spectral mixture analysis to improve the estimation accuracy of tropical forest biomass / T.M. Basuki in Geocarto international, vol 27 n° 4 (July 2012)
[article]
Titre : The potential of spectral mixture analysis to improve the estimation accuracy of tropical forest biomass Type de document : Article/Communication Auteurs : T.M. Basuki, Auteur ; Andrew K. Skidmore, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 329 - 345 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] biomasse
[Termes IGN] estimation statistique
[Termes IGN] forêt tropicale
[Termes IGN] image Landsat-ETM+
[Termes IGN] Indonésie
[Termes IGN] régressionRésumé : (Auteur) A main limitation of pixel-based vegetation indices or reflectance values for estimating above-ground biomass is that they do not consider the mixed spectral components on the earth's surface covered by a pixel. In this research, we decomposed mixed reflectance in each pixel before developing models to achieve higher accuracy in above-ground biomass estimation. Spectral mixture analysis was applied to decompose the mixed spectral components of Landsat-7 ETM+ imagery into fractional images. Afterwards, regression models were developed by integrating training data and fraction images. The results showed that the spectral mixture analysis improved the accuracy of biomass estimation of Dipterocarp forests. When applied to the independent validation data set, the model based on the vegetation fraction reduced 5–16% the root mean square error compared to the models using a single band 4 or 5, multiple bands 4, 5, 7 and all non-thermal bands of Landsat ETM+. Numéro de notice : A2012-334 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2011.634928 Date de publication en ligne : 05/12/2011 En ligne : https://doi.org/10.1080/10106049.2011.634928 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31780
in Geocarto international > vol 27 n° 4 (July 2012) . - pp 329 - 345[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2012041 RAB Revue Centre de documentation En réserve L003 Disponible Verification of 2D building outlines using oblique airborne images / A. Nyaruhuma in ISPRS Journal of photogrammetry and remote sensing, vol 71 (July 2012)
[article]
Titre : Verification of 2D building outlines using oblique airborne images Type de document : Article/Communication Auteurs : A. Nyaruhuma, Auteur ; Markus Gerke, Auteur ; M. George Vosselman, Auteur ; E.G. Mtalo, Auteur Année de publication : 2012 Article en page(s) : pp 62 - 75 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] arbre aléatoire
[Termes IGN] base de données foncières
[Termes IGN] bâtiment
[Termes IGN] boosting adapté
[Termes IGN] classification de Dempster-Shafer
[Termes IGN] contour
[Termes IGN] image aérienne oblique
[Termes IGN] logique floueRésumé : (Auteur) Oblique airborne images are interesting not only for visualization but also for the acquisition and updating of geo-spatial vector data. This is because side views of vertical structures, such as buildings, are present in those images. In recent years, techniques for automatic verification of building outlines have been proposed. These techniques utilized color, texture and height from vertical images or range data while oblique images contain façade information that can also be used to identify buildings. This paper presents a methodology to verify 2D building outlines in a cadastral dataset by using oblique airborne images. The method searches for clues such as building edges, wall façade edges and texture. The 2D clues in images taken from different perspectives but expected to contain the same wall are transformed to 3D, combined and used for a verification of the particular wall. Unlike methods that use vertical images or LIDAR, walls are verified individually and then the results are combined for the building. We compare three methods for combining wall-based evidence. Experiments using almost 700 buildings show that best results are obtained using Adaptive Boosting where – with a bias for better identification of demolished buildings – 100% of demolished buildings are identified and 91% of existing buildings are confirmed. The other two methods are Random Trees and a variant of the Dempster–Shafer approach combined with fuzzy reasoning and they only show some minor differences to the Adaptive Boosting result. The research as presented in this paper demonstrates the potential of oblique images, but some further work has to be done, including the identification of modified buildings and the extension towards verification of 3D building models. Numéro de notice : A2012-348 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.04.007 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.04.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31794
in ISPRS Journal of photogrammetry and remote sensing > vol 71 (July 2012) . - pp 62 - 75[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2012051 SL Revue Centre de documentation Revues en salle Disponible Approximation theory applied to DEM vertical accuracy assessment / X. Liu in Transactions in GIS, vol 16 n° 3 (June 2012)
[article]
Titre : Approximation theory applied to DEM vertical accuracy assessment Type de document : Article/Communication Auteurs : X. Liu, Auteur ; P. Hu, Auteur ; H. Hu, Auteur ; J. Sherda, Auteur Année de publication : 2012 Article en page(s) : pp 397 - 410 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] approximation
[Termes IGN] estimation statistique
[Termes IGN] interpolation linéaire
[Termes IGN] modèle numérique de surface
[Termes IGN] précision altimétrique
[Termes IGN] précision du positionnementRésumé : (Auteur) Existing research on DEM vertical accuracy assessment uses mainly statistical methods, in particular variance and RMSE which are both based on the error propagation theory in statistics. This article demonstrates that error propagation theory is not applicable because the critical assumption behind it cannot be satisfied. In fact, the non-random, non-normal, and non-stationary nature of DEM error makes it very challenging to apply statistical methods. This article presents approximation theory as a new methodology and illustrates its application to DEMs created by linear interpolation using contour lines as the source data. Applying approximation theory, a DEM's accuracy is determined by the largest error of any point (not samples) in the entire study area. The error at a point is bounded by max(|?mode|+M2h2/8) where |?node| is the error in the source data used to interpolate the point, M2 is the maximum norm of the second-order derivative which can be interpreted as curvature, and h is the length of the line on which linear interpolation is conducted. The article explains how to compute each term and illustrates how this new methodology based on approximation theory effectively facilitates DEM accuracy assessment and quality control. Numéro de notice : A2012-283 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/j.1467-9671.2012.01343.x Date de publication en ligne : 28/05/2012 En ligne : https://doi.org/10.1111/j.1467-9671.2012.01343.x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31729
in Transactions in GIS > vol 16 n° 3 (June 2012) . - pp 397 - 410[article]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 Extraction of building roof contours from LiDAR data using a Markov-random-field-based approach / E. Dos Santos Galvanin in IEEE Transactions on geoscience and remote sensing, vol 50 n° 3 (March 2012)PermalinkMarkov Chain CFAR detection for polarimetric data using data fusion / C. Fei in IEEE Transactions on geoscience and remote sensing, vol 50 n° 2 (February 2012)PermalinkPermalinkPermalinkPermalinkMathématiques programme 2012 Term. [terminale] STI2D, Term. STL / Jean-Denis Astier (2012)PermalinkMathématiques Tle [terminale] ES-L / Eric Sigward (2012)PermalinkMathématiques Tle [terminale] S / Eric Sigward (2012)PermalinkModèle d'estimation de l'imprécision des mesures géométriques de données géographiques / Jean-François Girres (2012)PermalinkStrategies to mitigate aliasing of loading signals while estimating GPS frame parameters / Xavier Collilieux in Journal of geodesy, vol 86 n° 1 (January 2012)Permalink