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Termes IGN > sciences naturelles > physique > traitement d'image > analyse d'image numérique > analyse des mélanges spectraux
analyse des mélanges spectrauxSynonyme(s)SMA démélange spectral |
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Measuring the physical composition of urban morphology using multiple endmember spectral mixture models / T. Rashed in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 9 (September 2003)
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Titre : Measuring the physical composition of urban morphology using multiple endmember spectral mixture models Type de document : Article/Communication Auteurs : T. Rashed, Auteur ; J.R. Weeks, Auteur ; J. Rogan, Auteur ; R.W. Powell, Auteur ; D.A. Roberts, Auteur Année de publication : 2003 Article en page(s) : pp 1011 - 1020 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] erreur moyenne quadratique
[Termes IGN] image Landsat-TM
[Termes IGN] Los Angeles
[Termes IGN] méthode robuste
[Termes IGN] morphologie mathématique
[Termes IGN] pixelNuméro de notice : A2003-231 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.69.9.1011 En ligne : https://doi.org/10.14358/PERS.69.9.1011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22526
in Photogrammetric Engineering & Remote Sensing, PERS > vol 69 n° 9 (September 2003) . - pp 1011 - 1020[article]Fusion of spectral and shape features for identification of urban surface cover types using reflective and thermal hyperspectral data / Karl Segl in ISPRS Journal of photogrammetry and remote sensing, vol 58 n° 1-2 (June - December 2003)
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Titre : Fusion of spectral and shape features for identification of urban surface cover types using reflective and thermal hyperspectral data Type de document : Article/Communication Auteurs : Karl Segl, Auteur ; S. Roessner, Auteur ; U. Heiden, Auteur ; H. Kaufmann, Auteur Année de publication : 2003 Article en page(s) : pp 99 - 112 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse linéaire des mélanges spectraux
[Termes IGN] biotope
[Termes IGN] carte d'occupation du sol
[Termes IGN] fusion d'images
[Termes IGN] image DAIS
[Termes IGN] image hyperspectrale
[Termes IGN] image thermique
[Termes IGN] milieu urbain
[Termes IGN] morphologie mathématique
[Termes IGN] photo-interprétation assistée par ordinateur
[Termes IGN] pixel
[Termes IGN] reconnaissance de formes
[Termes IGN] réflectance
[Termes IGN] utilisation du solRésumé : (Auteur) The urban environment is characterized by an intense multifunctional use of available spaces, where the preservation of open green spaces is of special importance. For this purpose, areawide urban biotope mapping based on CIR aerial photographs has been carried out for the large cities in Germany during the last 10 years. Because of dynamic urban development and high mapping costs, the municipal authorities are interested in effective methods for mapping urban surface cover types, which can be used for evaluation of ecological conditions in urban structures and supporting updates of biotope maps. Against this background, airborne hyperspectral remote sensing data of the DAIS 7915 instrument have been analyzed for a test site in the city of Dresden (Germany) with regard to their potential for automated materialoriented identification of urban surface cover types. Previous investigations have shown that the high spectral and spatial variabilities of these data require the development of special methods, which are capable of dealing with the resulting mixedpixel problem in its specific characteristics in urban areas. Earlier, methodological developments led to an approach based on a combination of spectral classification and pixeloriented unmixing techniques to facilitate sensible endmember selection based on the reflective bands of the DAIS instrument. This approach is now extended by a shapebased classification technique including the thermal bands of the DAIS instrument to improve the detection of buildings during the process of identifying seedling pixels, which represent the starting points for linear spectral unmixing. This new approach increases the reliability of differentiation between buildings and open spaces, leading to more accurate results for the spatial distribution of surface cover types. Thus, the new approach significantly enhances the exploitation of the information potential of the hyperspectral DAIS 7915 data for an areawide identification of urban surface cover types. Copyright ISPRS Numéro de notice : A2003-088 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/S0924-2716(03)00020-0 En ligne : https://doi.org/10.1016/S0924-2716(03)00020-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22384
in ISPRS Journal of photogrammetry and remote sensing > vol 58 n° 1-2 (June - December 2003) . - pp 99 - 112[article]Exemplaires(2)
Code-barres Cote Support Localisation Section Disponibilité 081-03032 RAB Revue Centre de documentation En réserve L003 Disponible 081-03031 RAB Revue Centre de documentation En réserve L003 Disponible Linear spectral random mixture analysis for hyperspectral imagery / C.I. Chang in IEEE Transactions on geoscience and remote sensing, vol 40 n° 2 (February 2002)
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Titre : Linear spectral random mixture analysis for hyperspectral imagery Type de document : Article/Communication Auteurs : C.I. Chang, Auteur ; S.S. Chiang, Auteur ; J.A. Smith, Auteur ; I.W. Ginsberg, Auteur Année de publication : 2002 Article en page(s) : pp 375 - 392 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse en composantes indépendantes
[Termes IGN] analyse linéaire des mélanges spectraux
[Termes IGN] analyse spectrale
[Termes IGN] classification non dirigée
[Termes IGN] image hyperspectraleRésumé : (Auteur) Independent component analysis (ICA) has shown success in blind source separation and channel equalization. Its applications to remotely sensed images have been investigated in recent years. Linear spectral mixture analysis (LSMA) has been widely used for subpixel detection and mixed pixel classification. It models an image pixel as a linear mixture of materials present in an image where the material abundance fractions are assumed to be unknown and nonrandom parameters. This paper considers an application of ICA to the LSMA, referred to as ICA-based linear spectral random mixture analysis (LSRMA), which describes an image pixel as a random source resulting from a random composition of multiple spectral signatures of distinct materials in the image. It differs from the LSMA in that the abundance fractions of the material spectral signatures in the LSRMA are now considered to be unknown but random independent signal sources. Two major advantages result from the LSRMA. First, it does not require prior knowledge of the materials to be used in the linear mixture model, as required for the LSMA. Second, and most importantly, the LSRMA models the abundance fraction of each material spectral signature as an independent random signal source so that the spectral variability of materials can be described by their corresponding abundance fractions and captured more effectively in a stochastic manner. The experimental results demonstrate that the proposed LSRMA provides an effective unsupervised technique for target detection and image classification in hyperspectral imagery. Numéro de notice : A2002-097 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/36.992799 En ligne : https://doi.org/10.1109/36.992799 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22012
in IEEE Transactions on geoscience and remote sensing > vol 40 n° 2 (February 2002) . - pp 375 - 392[article]Exemplaires(2)
Code-barres Cote Support Localisation Section Disponibilité 065-02021 RAB Revue Centre de documentation En réserve L003 Disponible 065-02022 RAB Revue Centre de documentation En réserve L003 Disponible Revealing the anatomy of cities through spectral mixture analysis of multispectral satellite imagery: a case study of the greater Cairo region, Egypt / T. Rashed in Geocarto international, vol 16 n° 4 (December 2001 - February 2002)
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Titre : Revealing the anatomy of cities through spectral mixture analysis of multispectral satellite imagery: a case study of the greater Cairo region, Egypt Type de document : Article/Communication Auteurs : T. Rashed, Auteur ; J.R. Weeks, Auteur ; M.S. Gadalla, Auteur ; A. Hill, Auteur Année de publication : 2001 Article en page(s) : pp 5 - 15 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] analyse spectrale
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification dirigée
[Termes IGN] Egypte
[Termes IGN] image multibande
[Termes IGN] milieu urbain
[Termes IGN] occupation du solRésumé : (Auteur) This paper examines the feasibility of spectral mixture analysis (SMA) in deriving comparable physical measures of urban land cover that describe the morphological characteristics of cities. SMA offers a way of analyzing satellite imagery of urban areas that may be superior to more standard methods of classification. Mixing models are based on the assumption that the remotely measured spectrum of a given pixel can be modeled as a combination of pure spectra, called endmembers. SMA, using four image endmembers (vegetation, impervious surface, soil, and shade), was applied to an IRS-1C multispectral image in order to extract measures that describe the anatomy of the Greater Cairo region, Egypt, in terms of endmember fractions. The resulting fractions were then used to classify the urban scene into eight classes of natural and human-built features through a decision tree (DT) classifier. The accuracy of the DT classification was compared to the accuracies of two per-pixel supervised classifications of the IRS-1C image employing maximum likelihood (ML) and minimum distance-to-means (MDM) classifiers. Overall KAPPA accuracies were 0. 88 for the DT classification based on SMA fractions, and 0.60 and 0.45 for the classifications conducted through ML and MDM respectively. Numéro de notice : A2002-038 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106040108542210 En ligne : https://doi.org/10.1080/10106040108542210 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=21955
in Geocarto international > vol 16 n° 4 (December 2001 - February 2002) . - pp 5 - 15[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 059-01041 RAB Revue Centre de documentation En réserve L003 Disponible Detection of interannual vegetation responses to climatic variability using AVIRIS data in a coastal savanna in California / M. Garcia in IEEE Transactions on geoscience and remote sensing, vol 39 n° 7 (July 2001)
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Titre : Detection of interannual vegetation responses to climatic variability using AVIRIS data in a coastal savanna in California Type de document : Article/Communication Auteurs : M. Garcia, Auteur ; S.L. Ustin, Auteur Année de publication : 2001 Article en page(s) : pp 1480 - 1490 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse linéaire des mélanges spectraux
[Termes IGN] analyse spectrale
[Termes IGN] Californie (Etats-Unis)
[Termes IGN] image AVIRIS
[Termes IGN] image hyperspectrale
[Termes IGN] littoral
[Termes IGN] pluie
[Termes IGN] savaneRésumé : (Auteur)Ecosystem responses to interannual weather variability are large and superimposed over any long-term directional climatic responses making it difficult to assign causal relationships to vegetation change. Better understanding of ecosystem responses to interannual climatic variability is crucial to predicting long-term functioning and stability. Hyperspectral data have the potential to detect ecosystem responses that are undetected by broadband sensors and can be used to scale to coarser resolution global mapping sensors, e.g., advanced very high resolution radiometer (AVHRR) and MODIS. This research focused on detecting vegetation responses to interannual climate using the airborne visible-infrared imaging spectrometer (AVIRIS) data over a natural savanna in the Central Coast Range in California. Results of linear spectral mixture analysis and assessment of the model errors were compared for two AVIRIS images acquired in spring of a dry and a wet year. The results show that mean unmixed fractions for these vegetation types were not significantly different between years due to the high spatial variability within the landscape. However, significant community differences were found between years on a pixel basis, underlying the importance of site-specific analysis. Multitemporal hyperspectral coverage is necessary to understand vegetation dynamics. Numéro de notice : A2001-206 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/36.934079 En ligne : https://doi.org/10.1109/36.934079 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=21900
in IEEE Transactions on geoscience and remote sensing > vol 39 n° 7 (July 2001) . - pp 1480 - 1490[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-01071 RAB Revue Centre de documentation En réserve L003 Disponible Hyperspectral subpixel target detection using the linear mixing model / D. Manolakis in IEEE Transactions on geoscience and remote sensing, vol 39 n° 7 (July 2001)
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