Descripteur
Termes IGN > sciences naturelles > physique > traitement d'image > analyse d'image numérique > analyse des mélanges spectraux
analyse des mélanges spectrauxSynonyme(s)SMA démélange spectral |
Documents disponibles dans cette catégorie (148)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
A global analysis urban reflectance / C. Small in International Journal of Remote Sensing IJRS, vol 26 n° 4 (February 2005)
[article]
Titre : A global analysis urban reflectance Type de document : Article/Communication Auteurs : C. Small, Auteur Année de publication : 2005 Article en page(s) : pp 661 - 681 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] albedo
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] hétérogénéité sémantique
[Termes IGN] image Landsat-ETM+
[Termes IGN] réflectance urbaineNuméro de notice : A2005-051 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160310001654950 En ligne : https://doi.org/10.1080/01431160310001654950 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27189
in International Journal of Remote Sensing IJRS > vol 26 n° 4 (February 2005) . - pp 661 - 681[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-05041 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Normalized spectral mixture analysis for monitoring urban composition using ETM+ imagery / C. Wu in Remote sensing of environment, vol 93 n° 4 (15/12/2004)
[article]
Titre : Normalized spectral mixture analysis for monitoring urban composition using ETM+ imagery Type de document : Article/Communication Auteurs : C. Wu, Auteur Année de publication : 2004 Article en page(s) : pp 480 - 492 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] Colombus (Ohio)
[Termes IGN] contrôle par télédétection
[Termes IGN] image Landsat-ETM+
[Termes IGN] impact sur l'environnement
[Termes IGN] milieu urbain
[Termes IGN] surface imperméable
[Termes IGN] utilisation du sol
[Termes IGN] variable biophysique (végétation)
[Termes IGN] végétationRésumé : (Auteur) With rapid urban growth in recent years, understanding urban biophysical composition and dynamics becomes an important research topic. Remote sensing technologies introduce a potentially scientific basis for examining urban composition and monitoring its changes over time. The vegetation-impervious surface-soil (V-I-S) model, in particular, provides a foundation for describing urban/suburban environments and a basis for further urban analyses including urban growth modeling, environmental impact analysis, and socioeconomic factor estimation. This paper develops a normalized spectral mixture analysis (NSMA) method to examine urban composition in Columbus (Ohio) using Landsat ETM+ data. In particular, a brightness normalization method is applied to reduce brightness variation. Through this normalization, brightness variability within each V-I-S component is reduced or eliminated, thus allowing a single endmember representing each component. Further, with the normalized image, three endmembers, vegetation, impervious surface, and soil, are chosen to model heterogeneous urban composition using a constrained spectral mixture analysis (SMA) model. The accuracy of impervious surface estimation is assessed and compared with two other existing models. Results indicate that the proposed model is a better alternative to existing models, with a root mean square error (RMSE) of 10.1% for impervious surface estimation in the study area. Numéro de notice : A2004-461 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2004.08.003 En ligne : https://doi.org/10.1016/j.rse.2004.08.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26981
in Remote sensing of environment > vol 93 n° 4 (15/12/2004) . - pp 480 - 492[article]A comparison of error metrics and constraints for multiple endmember spectral analysis and spectral angle mapper / P.E. Dennison in Remote sensing of environment, vol 93 n° 3 (15/11/2004)
[article]
Titre : A comparison of error metrics and constraints for multiple endmember spectral analysis and spectral angle mapper Type de document : Article/Communication Auteurs : P.E. Dennison, Auteur ; K. Halligan, Auteur ; D.A. Roberts, Auteur Année de publication : 2004 Article en page(s) : pp 359 - 367 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] albedo
[Termes IGN] analyse comparative
[Termes IGN] analyse de mélange spectral d’extrémités multiples
[Termes IGN] appariement spectral
[Termes IGN] calcul d'erreur
[Termes IGN] classe d'objets
[Termes IGN] classification Spectral angle mapper
[Termes IGN] erreur moyenne quadratique
[Termes IGN] métriqueRésumé : (Auteur) Spectral matching algorithms can be used for the identification of unknown spectra based on a measure of similarity with one or more known spectra. Two popular spectral matching algorithms use different error metrics and constraints to determine the existence of a spectral match. Multiple endmember spectral mixture analysis (MESMA) is a linear mixing model that uses a root mean square error (RMSE) error metric. Spectral angle mapper (SAM) compares two spectra using a spectral angle error metric. This paper compares two endmember MESMA and SAM using a spectral library containing six land cover classes. RMSE and spectral angle for models within each land cover class were directly compared. The dependence of RMSE on the albedo of the modeled spectrum was also explored. RMSE and spectral angle were found to be closely related, although not equivalent, due to variations in the albedo of the modeled spectra. Error constraints applied to both models resulted in large differences in the number of spectral matches. Using MESMA, the number of spectra modeled within the error constraint increased as the albedo of the modeled spectra decreased. The value of the error constraint used was shown to make a much larger difference in the number of spectra modeled than the choice of spectral matching algorithm. Numéro de notice : A2004-440 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2004.07.013 En ligne : https://doi.org/10.1016/j.rse.2004.07.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26960
in Remote sensing of environment > vol 93 n° 3 (15/11/2004) . - pp 359 - 367[article]The contribution of the sources separation method in the decomposition of mixed pixels / Mohamed Saber Naceur in IEEE Transactions on geoscience and remote sensing, vol 42 n° 11 (November 2004)
[article]
Titre : The contribution of the sources separation method in the decomposition of mixed pixels Type de document : Article/Communication Auteurs : Mohamed Saber Naceur, Auteur ; M.A. Loghmari, Auteur ; Mohamed-Rached Boussema, Auteur Année de publication : 2004 Article en page(s) : pp 2642 - 2653 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] accentuation d'image
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] analyse en composantes indépendantes
[Termes IGN] bande spectrale
[Termes IGN] classification pixellaire
[Termes IGN] décomposition d'image
[Termes IGN] fusion de données multisource
[Termes IGN] occupation du sol
[Termes IGN] signature spectrale
[Termes IGN] Tunisie
[Termes IGN] valeur radiométriqueRésumé : (Auteur) In this paper, we propose to prove the importance of the application of blind sources separation methods on remote sensing data. Indeed, satellite images are represented by radiometric values where each one is considered as a mixture of different sources. The primary goal of our research is to hand back the different sources covering the scanned zone. The main constraint to restore these sources is to take our observation images as a mixture of physically independent components. In our work, the independence between the different sources is obtained through two statistical methods. The first method is based on the reduction of the spatial source correlations, and the second one is based on the joint maximization of the fourth-order cumulants. On the opposite of the original multispectral images that are represented according to correlated axes, the source images extracted from the proposed algorithms are represented according to mutually independent axes that allow each source to represent specifically a certain type of land cover. This increases the reliability of the analysis and the interpretation of the scanned zone. The source images obtained from the application of the sources separation method give a more effective representation of the information contained on the observation images. The performance of these source images is investigated through an application for the decomposition of mixed pixels. The originality of our application comes from the determination of the mixing matrix modeling the spectral endmembers based on source filters. These filters model the sensibility of each source channel according to the different spectral bands, which give an interesting information about the spectral theme represented by the corresponding source image. This application shows that the proportions of the different land cover types existing into the pixel are better estimated through the source images than through the original multispectral images. This method could offer an interesting solution to mixed-pixel classification. Numéro de notice : A2004-463 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2004.834764 En ligne : https://doi.org/10.1109/TGRS.2004.834764 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26983
in IEEE Transactions on geoscience and remote sensing > vol 42 n° 11 (November 2004) . - pp 2642 - 2653[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-04111 RAB Revue Centre de documentation En réserve L003 Disponible Spectral 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)
[article]
Titre : Spectral mixture analysis of the urban landscape in Indianapolis with Landsat ETM+ imagery Type de document : Article/Communication Auteurs : Dong Lu, Auteur ; Q. Weng, Auteur Année de publication : 2004 Article en page(s) : pp 1053 - 1062 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] analyse en composantes principales
[Termes IGN] arbre (mathématique)
[Termes IGN] classification hybride
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] image Landsat-ETM+
[Termes IGN] Indianapolis
[Termes IGN] paysage urbainRésumé : (Auteur) This paper examines characteristics of urban land-use and land-cover (LULC) classes using spectral mixture analysis (SMA), and develops a conceptual model for characterizing urban LULC patterns. A Landsat Enhanced Thematic Mapper Plus (ETM+) image of Indianapolis City was used in this research and a minimum noise fraction (MNF) transform was employed to convert the ETM+ image into principal components. Five image endmembers (shade, green vegetation, impervious surface, dry soil, and dark soil) were selected, and an unconstrained least-squares solution was used to unmix the MNF components into fraction images. Different combinations of three or four endmembers were evaluated. The best fraction images were chosen to classify LULC classes based on a hybrid procedure that combined maximum-likelihood and decision-tree algorithms. The results indicate that the SMA-based approach significantly improved classification accuracy as compared to the maximum-likelihood classifier. The fraction images were found to be effective for characterizing the urban landscape patterns. Numéro de notice : A2004-347 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.70.9.1053 En ligne : https://doi.org/10.14358/PERS.70.9.1053 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26874
in Photogrammetric Engineering & Remote Sensing, PERS > vol 70 n° 9 (September 2004) . - pp 1053 - 1062[article]Urban land-cover change analysis in central Puget Sound / M. Alberti in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 9 (September 2004)PermalinkChange detection techniques / Dong Lu in International Journal of Remote Sensing IJRS, vol 25 n° 12 (June 2004)PermalinkReducing signature variability in unmixing coastal marsh Thematic Mapper scenes using spectral indices / A.S. Rogers in International Journal of Remote Sensing IJRS, vol 25 n° 12 (June 2004)PermalinkEstimation of subpixel target size for remotely sensed imagery / C.I. Chang in IEEE Transactions on geoscience and remote sensing, vol 42 n° 6 (June 2004)PermalinkUsing Lidar and effective LAI data to evaluate Ikonos and Landsat 7 ETM+ vegetation cover estimates in a ponderosa pine forest / X. Chen in Remote sensing of environment, vol 91 n° 1 (15/05/2004)PermalinkLinear mixture analysis-based compression for hyperspectral image analysis / Q. Du in IEEE Transactions on geoscience and remote sensing, vol 42 n° 4 (April 2004)PermalinkEstimation of land surface temperature-vegetation abundance relationship for urban heat island studies / Q. Wenger in Remote sensing of environment, vol 89 n° 4 (29/02/2004)PermalinkSnow-cover mapping in forest by constrained linear spectral unimixing of MODIS data / D. Vikhamar in Remote sensing of environment, vol 88 n° 3 (15/12/2003)PermalinkHigh spatial resolution spectral mixture analysis of urban reflectance / C. Small in Remote sensing of environment, vol 88 n° 1 (30/11/2003)PermalinkMapping forest degradation in the Eastern Amazon SPOT 4 through spectral mixture models / Cristiano B. Souza in Remote sensing of environment, vol 87 n° 4 (15/11/2003)Permalink