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Auteur A. Boucher |
Documents disponibles écrits par cet auteur (4)
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Geostatistical solutions for super-resolution land cover mapping / A. Boucher in IEEE Transactions on geoscience and remote sensing, vol 46 n° 1 (January 2008)
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Titre : Geostatistical solutions for super-resolution land cover mapping Type de document : Article/Communication Auteurs : A. Boucher, Auteur ; P. Kyriakidis, Auteur ; C. Cronkite-Ratcliff, Auteur Année de publication : 2008 Article en page(s) : pp 272 - 283 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] carte d'occupation du sol
[Termes IGN] géostatistique
[Termes IGN] spatiocarte
[Termes IGN] variogrammeRésumé : (Auteur) Super-resolution land cover mapping aims at producing fine spatial resolution maps of land cover classes from a set of coarse-resolution class fractions derived from satellite information via, for example, spectral unmixing procedures. Based on a prior model of spatial structure or texture that encodes the expected patterns of classes at the fine (target) resolution, this paper presents a sequential simulation framework for generating alternative super-resolution maps of class labels that are consistent with the coarse class fractions. Two modes of encapsulating the prior structural information are investigated-one uses a set of indicator variogram models, and the other uses training images. A case study illustrates that both approaches lead to super-resolution class maps that exhibit a variety of spatial patterns ranging from simple to complex. Using four different examples, it is demonstrated that the structural model controls the patterns seen on the super-resolution maps, even for cases where the coarse fraction data are highly constraining. Copyright IEEE Numéro de notice : A2008-046 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2007.907102 En ligne : https://doi.org/10.1109/TGRS.2007.907102 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29041
in IEEE Transactions on geoscience and remote sensing > vol 46 n° 1 (January 2008) . - pp 272 - 283[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-08011 RAB Revue Centre de documentation En réserve L003 Disponible Integrating fine scale information in super-resolution land-cover mapping / A. Boucher in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 8 (August 2007)
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Titre : Integrating fine scale information in super-resolution land-cover mapping Type de document : Article/Communication Auteurs : A. Boucher, Auteur ; P.C. Kyriakidis, Auteur Année de publication : 2007 Article en page(s) : pp 913 - 921 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] analyse infrapixellaire
[Termes IGN] carte d'occupation du sol
[Termes IGN] krigeage
[Termes IGN] limite de résolution géométrique
[Termes IGN] variogrammeRésumé : (Auteur) Super-resolution or sub-pixel class mapping is the task of providing fine spatial resolution maps of, for example, landcover classes, from satellite sensor measurements obtained at a coarser spatial resolution. Often, the only information available consists of coarse class fraction data, typically obtained through spectral unmixing. This paper shows how to integrate, in addition to such coarse fractions, class labels at a set of fine pixels obtained independent of the satellite sensor measurements. The integration of such fine spatial resolution information is achieved within the Indicator Kriging formalism in either a prediction or simulation mode. The spatial dissimilarity or texture of class labels at the fine (target) resolution is quantified in a non-parametric way from an analog scene using a set of experimental indicator semivariogram maps. The output of the proposed procedure consists of maps of probabilities of class occurrence, or of a series of simulated class maps characterizing the inherent spatial uncertainty in the super-resolution mapping process. Numéro de notice : A2007-370 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.73.8.913 En ligne : http://dx.doi.org/10.14358/PERS.73.8.913 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28733
in Photogrammetric Engineering & Remote Sensing, PERS > vol 73 n° 8 (August 2007) . - pp 913 - 921[article]A novel method for mapping land cover changes: Incorporating time and space with geostatistics / A. Boucher in IEEE Transactions on geoscience and remote sensing, vol 44 n° 11 Tome 2 (November 2006)
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Titre : A novel method for mapping land cover changes: Incorporating time and space with geostatistics Type de document : Article/Communication Auteurs : A. Boucher, Auteur ; K.C. Seto, Auteur ; A.G. Journel, Auteur Année de publication : 2006 Article en page(s) : pp 3427 - 3435 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] classification pixellaire
[Termes IGN] détection de changement
[Termes IGN] données de terrain
[Termes IGN] filtre de déchatoiement
[Termes IGN] géostatistique
[Termes IGN] krigeage
[Termes IGN] série temporelle
[Termes IGN] utilisation du sol
[Termes IGN] variogrammeRésumé : (Auteur) Landsat data are now available for more than 30 years, providing the longest high-resolution record of Earth monitoring. This unprecedented time series of satellite imagery allows for extensive temporal observation of terrestrial processes such as land cover and land use change. However, despite this unique opportunity, most existing change detection techniques do not fully capitalize on this long time series. In this paper, a method that exploits both the temporal and spatial domains of time series satellite data to map land cover changes is presented. The time series of each pixel in the image is modeled with a combination of: 1) pixel-specific remotely sensed data; 2) neighboring pixels derived from ground observation data; and 3) time series transition probabilities. The spatial information is modeled with variograms and integrated using indicator kriging; time series transition probabilities are combined using an information-based cascade approach. This results in a map that is significantly more accurate in identifying when, where, and what land cover changes occurred. For the six images used in this paper, the prediction accuracy of the time series improves significantly, increasing from 31% to 61%, when both space and time are considered with the maximum likelihood. The consideration of spatial continuity also reduced unwanted speckles in the classified images, removing the need for any postprocessing. These results indicate that combining space and time domains significantly improves the accuracy of temporal change detection analyses and can produce high-quality time series land cover maps. Copyright IEEE Numéro de notice : A2006-529 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2006.879113 En ligne : https://doi.org/10.1109/TGRS.2006.879113 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28252
in IEEE Transactions on geoscience and remote sensing > vol 44 n° 11 Tome 2 (November 2006) . - pp 3427 - 3435[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-06111B RAB Revue Centre de documentation En réserve L003 Disponible Super-resolution land cover mapping with indicator geostatistics / A. Boucher in Remote sensing of environment, vol 104 n° 3 (15/10/2006)
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Titre : Super-resolution land cover mapping with indicator geostatistics Type de document : Article/Communication Auteurs : A. Boucher, Auteur ; P.C. Kyriakidis, Auteur Année de publication : 2006 Article en page(s) : pp 264 - 282 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte d'occupation du sol
[Termes IGN] Chine
[Termes IGN] delta
[Termes IGN] fleuve
[Termes IGN] géostatistique
[Termes IGN] image Landsat-TM
[Termes IGN] incertitude de position
[Termes IGN] krigeage
[Termes IGN] problème inverse
[Termes IGN] variogrammeRésumé : (Auteur) Many satellite images have a coarser spatial resolution than the extent of land cover patterns on the ground, leading to mixed pixels whose composite spectral response consists of responses from multiple land cover classes. Spectral unmixing procedures only determine the fractions of such classes within a coarse pixel without locating them in space. Super-resolution or sub-pixel mapping aims at providing a fine resolution map of class labels, one that displays realistic spatial structure (without artifact discontinuities) and reproduces the coarse resolution fractions. In this paper, existing approaches for super-resolution mapping are placed within an inverse problem framework, and a geostatistical method is proposed for generating alternative synthetic land cover maps at the fine (target) spatial resolution; these super-resolution realizations are consistent with all the information available. More precisely, indicator coKriging is used to approximate the probability that a pixel at the fine spatial resolution belongs to a particular class, given the coarse resolution fractions and (if available) a sparse set of class labels at some informed fine pixels. Such Kriging-derived probabilities are used in sequential indicator simulation to generate synthetic maps of class labels at the fine resolution pixels. This non-iterative and fast simulation procedure yields alternative super-resolution land cover maps that reproduce: (i) the observed coarse fractions, (ii) the fine resolution class labels that might be available, and (iii) the prior structural information encapsulated in a set of indicator variogram models at the fine resolution. A case study is provided to illustrate the proposed methodology using Landsat TM data from SE China. Numéro de notice : A2006-415 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2006.04.020 En ligne : https://doi.org/10.1016/j.rse.2006.04.020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28139
in Remote sensing of environment > vol 104 n° 3 (15/10/2006) . - pp 264 - 282[article]