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Fast SAR image restoration, segmentation, and detection of high-reflectance regions / E. Bratsolis in IEEE Transactions on geoscience and remote sensing, vol 41 n° 12 (December 2003)
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Titre : Fast SAR image restoration, segmentation, and detection of high-reflectance regions Type de document : Article/Communication Auteurs : E. Bratsolis, Auteur ; M. Sigelle, Auteur Année de publication : 2003 Article en page(s) : pp 2890 - 2899 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] champ aléatoire de Markov
[Termes IGN] chatoiement
[Termes IGN] classification
[Termes IGN] filtre numérique
[Termes IGN] histogramme
[Termes IGN] image ERS-SAR
[Termes IGN] itération
[Termes IGN] réflectance
[Termes IGN] restauration d'image
[Termes IGN] segmentation d'imageRésumé : (Auteur) An iterative filter that can be used for speckle reduction and restoration of synthetic aperture radar (SAR) images is presented here. This method can be considered as a first step in the extraction of other important information. The second step is the detection of high-reflectance regions and continues with the segmentation of the total image. We have worked in three-look simulated and real European Remote Sensing 1 satellite amplitude images. The iterative filter is based on a membrane model Markov random field approximation optimized by a synchronous local iterative method. The final form of restoration gives a total sum-preserving regularization for the pixel values of our image. The high-reflectance regions are defined as the brightest regions of the restored image. After the separation of this extreme class, we give a fast segmentation method using the histogram of the restored image. Numéro de notice : A2003-383 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2003.817222 En ligne : https://doi.org/10.1109/TGRS.2003.817222 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26463
in IEEE Transactions on geoscience and remote sensing > vol 41 n° 12 (December 2003) . - pp 2890 - 2899[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-03121 RAB Revue Centre de documentation En réserve L003 Disponible Mapping urban areas by fusing multiple sources of coarse resolution remotely sensed data / A.M. Schneider in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 12 (December 2003)
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Titre : Mapping urban areas by fusing multiple sources of coarse resolution remotely sensed data Type de document : Article/Communication Auteurs : A.M. Schneider, Auteur ; M. Friedl, Auteur ; D.K. Mciver, Auteur Année de publication : 2003 Article en page(s) : pp 1377 - 1386 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] cartographie urbaine
[Termes IGN] classification dirigée
[Termes IGN] données multitemporelles
[Termes IGN] écosystème
[Termes IGN] image multibande
[Termes IGN] zone urbaineRésumé : (Auteur) In recent decades, rapid rates of population growth and urban expansion have led to widespread conversion of natural ecosystems and agricultural lands to urban land cover. The amount and rate of this land conversion affects local and regional ecosystems, climate, biogeochemistry, as well as food production. The main objective of the research described in this paper is to improve understanding of the methodological and validation requirements for mapping urban land cover over large areas from coarse resolution remotely sensed data. A technique called boosting is used to improve supervised classification accuracy and provides a means to integrate moDis data with the Dmsp nighttime lights data set and gridded population data. Results for North America indicate that fusion of these three data types improves urban classification results by resolving confusion between urban and other classes that occurs when any one of the data sets is used by itself. Traditional measures of accuracy assessment as well as new, mapletbased methods demonstrate the effectiveness of the methodology of creating maps of cities at continental scales. Numéro de notice : A2003-358 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.69.12.1377 En ligne : https://doi.org/10.14358/PERS.69.12.1377 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26438
in Photogrammetric Engineering & Remote Sensing, PERS > vol 69 n° 12 (December 2003) . - pp 1377 - 1386[article]Mapping 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)
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Titre : Mapping forest degradation in the Eastern Amazon SPOT 4 through spectral mixture models Type de document : Article/Communication Auteurs : Cristiano B. Souza, Auteur ; L. Firestone, Auteur ; L. Moreira Silva, Auteur ; D. Roberts, Auteur Année de publication : 2003 Article en page(s) : pp 494 - 506 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] analyse visuelle
[Termes IGN] cartographie écologique
[Termes IGN] classification ascendante hiérarchique
[Termes IGN] déboisement
[Termes IGN] image Ikonos
[Termes IGN] image multibande
[Termes IGN] image SPOT
[Termes IGN] statistique mathématiqueRésumé : (Auteur) In this paper, we present a methodology to map classes of degraded forest in the Eastern Amazon. Forest degradation field data, available in the literature, and 1-m resolution IKONOS image were linked with fraction images (vegetation, nonphotosynthetic vegetation (NPV), soil and shade) derived from spectral mixture models applied to a Satellite Pour l'Observation de la Terre (SPOT) 4 multispectral image. The forest degradation map was produced in two steps. First, we investigated the relationship between ground (i.e., field and IKONOS data) and satellite scales by analyzing statistics and performing visual analyses of the field classes in terms of fraction values. This procedure allowed us to define four classes of forest at the SPOT 4 image scale, which included: intact forest; logged forest (recent and older logged forests in the field); degraded forest (heavily burned, heavily logged and burned forests in the field) ; and regeneration (old heavily logged and old heavily burned forest in the field). Next, we used a decision tree classifier (DTQ to define a set of rules to separate the forest classes using the fraction images. We classified 35% of the forest area (2097.3 km2 ) as intact forest. Logged forest accounted for 56% of the forest area and 9% of the forest area was classified as degraded forest. The resultant forest degradation map showed good agreement (86% overall accuracy) with areas of degraded forest visually interpreted from two IKONOS images. In addition, high correlation (R2 = 0.97) was observed between the total live aboveground biomass of degraded forest classes (defined at the field scale) and the NPV fraction image. The NPV fraction also improved our ability to mapping of old selectively logged forests. Numéro de notice : A2003-338 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2002.08.002 En ligne : https://doi.org/10.1016/j.rse.2002.08.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22633
in Remote sensing of environment > vol 87 n° 4 (15/11/2003) . - pp 494 - 506[article]Improvements in land use mapping for irrigated agriculture from satellite sensor data using a multi-stage maximum likelihood classification / I.A. El-Magd in International Journal of Remote Sensing IJRS, vol 24 n° 21 (November 2003)
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Titre : Improvements in land use mapping for irrigated agriculture from satellite sensor data using a multi-stage maximum likelihood classification Type de document : Article/Communication Auteurs : I.A. El-Magd, Auteur ; T.W. Tanton, Auteur Année de publication : 2003 Article en page(s) : pp 4197 - 4206 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte agricole
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] cultures
[Termes IGN] cultures irriguées
[Termes IGN] image Landsat-ETM+
[Termes IGN] rizière
[Termes IGN] utilisation du solRésumé : (Auteur) The accuracy of conventional land use classification of irrigated agriculture from optical satellite images using maximum likelihood supervised classification was compared with a classification based on multistage maxinium likelihood supervised classification. In the multistage maximum likelihood classification series of sub-classifications were carried out which included masking and/or omitting certain crops from the classifications. These series of classifications improved the identification of individual crops/land use types. The output from the optimum sub-classifications were stacked to give an overall crop types/land use map. When the multistage classification was tested against a single stage classification on a large irrigation scheme in Central Asia the final accuracy of crop/land use classification increased from 85% to 94%. Field verification confirmed the accuracy at 93.5%. These results were achieved with a single Landsat 7 Enhanced Thematic Mapper (ETM+) sensor dataset as of 2 August 1999 over an area of 38.5 km. Numéro de notice : A2003-305 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/0143116031000139791 En ligne : https://doi.org/10.1080/0143116031000139791 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22601
in International Journal of Remote Sensing IJRS > vol 24 n° 21 (November 2003) . - pp 4197 - 4206[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-03211 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Mangrove research and coastal ecosystem studies with SPOT-4 HRVIR and TERRA ASTER in the Arabian Gulf / Hideo Saito in International Journal of Remote Sensing IJRS, vol 24 n° 21 (November 2003)
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Titre : Mangrove research and coastal ecosystem studies with SPOT-4 HRVIR and TERRA ASTER in the Arabian Gulf Type de document : Article/Communication Auteurs : Hideo Saito, Auteur ; M.F. Bellan, Auteur ; A. Al-Habshi, Auteur ; et al., Auteur Année de publication : 2003 Article en page(s) : pp 4073 - 4092 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Abou Dabi
[Termes IGN] cartographie thématique
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] détection de changement
[Termes IGN] Doubaï
[Termes IGN] écosystème
[Termes IGN] Emirats Arabes Unis
[Termes IGN] image SPOT-HRVIR
[Termes IGN] image Terra-ASTER
[Termes IGN] littoral
[Termes IGN] mangrove
[Termes IGN] Persique, golfe
[Termes IGN] surveillance écologique
[Termes IGN] zone tropicale humideRésumé : (Auteur) Mangroves reach their optimal development in the wet tropics although some little known mangrove stands are reported in subtropical arid coastlines especially from the Red Sea to Pakistan where they form one of the driest mangrove habitats in the world. Because they constitute the only available evergreen forest in hyperarid warm coastal areas, the main wetlands for migratory birds and essential nursery ground for many species of fish, it Is imperative to produce a sufficiently accurate map for monitoring their changes and for their protection. The main objective of the present work is to test and to select the best methodological approach to discriminate and map the mangroves and related coastal ecosystems in the United Arab Emirates (UAE). between Abu Dhabi and Dubai, a coastal stretch about 750km long. It was found that the best practical results were produced by the Maximum Likelihood and Mahalanobis classifications although some limitations remain unsolved, especially in open ecosystems, which are common in arid areas. Moreover, SPOT4 HighResolution Visible InfraRed (HRVIR) data proves at least as efficient as TERRA ASTER data, in spite of a slightly finer ground resolution and the great number of channels for ASTER. Ultimately, the most appropriate working scale for mapping coastal habitats, compatible with pixel size, is in the order of 1/25 000. Numéro de notice : A2003-302 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/0143116021000035030 En ligne : https://doi.org/10.1080/0143116021000035030 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22598
in International Journal of Remote Sensing IJRS > vol 24 n° 21 (November 2003) . - pp 4073 - 4092[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-03211 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Study of urban spatial patterns from SPOT panchromatic imagery using textural analysis / Qian Zhang in International Journal of Remote Sensing IJRS, vol 24 n° 21 (November 2003)
PermalinkAutomated change detection for updates of digital map databases / T. Knudsen in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 11 (November 2003)
PermalinkA credit assignment approach to fusing classifiers of multiseason hyperspectral imagery / C. Bachmann in IEEE Transactions on geoscience and remote sensing, vol 41 n° 11 (November 2003)
PermalinkLinear features extraction in rain forest context from interferometric SAR images by fusion of coherence and amplitude information / V.P. Onana in IEEE Transactions on geoscience and remote sensing, vol 41 n° 11 (November 2003)
PermalinkA Markov random field approach to spatio-temporal contextual image classification / F. Melgani in IEEE Transactions on geoscience and remote sensing, vol 41 n° 11 (November 2003)
PermalinkA new maximum-likelihood joint segmentation technique for multitemporal SAR and multiband optical images / P. Lombardo in IEEE Transactions on geoscience and remote sensing, vol 41 n° 11 (November 2003)
PermalinkStrategies for integrating information from multiple resolutions into land-use/land-cover classification routines / D.M. Chen in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 11 (November 2003)
PermalinkBayesian classification by data augmentation / B. Regguzoni in International Journal of Remote Sensing IJRS, vol 24 n° 20 (October 2003)
PermalinkData fusion and feature extraction in the wavelet domain / Magnus Orn Ulfarsson in International Journal of Remote Sensing IJRS, vol 24 n° 20 (October 2003)
PermalinkA neural adaptive model for feature extraction and recognition in high resolution remote sensing imagery / E. Binaghi in International Journal of Remote Sensing IJRS, vol 24 n° 20 (October 2003)
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