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The recognition of road network from high-resolution satellite remotely sensed data using image morphological characteristics / C. Zhu in International Journal of Remote Sensing IJRS, vol 26 n° 24 (December 2005)
[article]
Titre : The recognition of road network from high-resolution satellite remotely sensed data using image morphological characteristics Type de document : Article/Communication Auteurs : C. Zhu, Auteur ; Wei Shi, Auteur ; et al., Auteur Année de publication : 2005 Article en page(s) : pp 5493 - 5508 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse visuelle
[Termes IGN] appariement de formes
[Termes IGN] échelle d'intensité
[Termes IGN] extraction du réseau routier
[Termes IGN] image à haute résolution
[Termes IGN] image Ikonos
[Termes IGN] morphologie mathématique
[Termes IGN] niveau de gris (image)
[Termes IGN] précision géométrique (imagerie)
[Termes IGN] reconnaissance de formes
[Termes IGN] réseau routier
[Termes IGN] segment de droiteRésumé : (Auteur) With the development of remote sensors and satellite technologies, high-resolution satellite data such as IKONOS images have been available recently. By these new high resolution satellite data, remote sensing technologies can be successfully applied to more application areas such as extracting road network from high resolution satellite images. This paper proposes a newly developed approach to extract a road network from high resolution satellite images. The approach is based on the binary and greyscale mathematical morphology and a line segment match method. First, the outline of road network is detected based on the grey morphological characteristics. Then, the basic road network is detected by the line segment match method. Next, the detected basic road network is processed based on the knowledge about the roads and binary mathematical morphological methods. Finally, visual analysis and three indicators are used to evaluate the accuracy of the extracted road networks. The results of the accuracy evaluation demonstrate that the developed road network extraction approach can provide both good visual effect and high positional accuracy. Numéro de notice : A2005-523 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160500300354 En ligne : https://doi.org/10.1080/01431160500300354 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27659
in International Journal of Remote Sensing IJRS > vol 26 n° 24 (December 2005) . - pp 5493 - 5508[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-05241 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Relating SAR image texture to the biomass of regenerating tropical forests / T.M. Kuplich in International Journal of Remote Sensing IJRS, vol 26 n° 21 (November 2005)
[article]
Titre : Relating SAR image texture to the biomass of regenerating tropical forests Type de document : Article/Communication Auteurs : T.M. Kuplich, Auteur ; P.J. Curran, Auteur ; P.M. Atkinson, Auteur Année de publication : 2005 Article en page(s) : pp 4829 - 4854 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] bande L
[Termes IGN] canopée
[Termes IGN] forêt tropicale
[Termes IGN] image JERS
[Termes IGN] image radar
[Termes IGN] Manaus
[Termes IGN] masse végétale
[Termes IGN] niveau de gris (image)
[Termes IGN] teneur en carbone
[Termes IGN] texture d'image
[Termes IGN] variogrammeRésumé : (Auteur) An accurate global carbon budget requires information on terrestrial carbon sink strength. Regenerating tropical forests are known to be important terrestrial carbon sinks but information on their location, extent and biomass (from which carbon content can be estimated) is incomplete. The use of remotely sensed data in optical wavelengths has been of limited use due to both the weak relationship between optical radiation and forest biomass and near-constant cloud cover in the tropics. L-band Synthetic Aperture Radar (SAR) backscatter, however, is related positively to biomass (but only up to an asymptote of around 40-90T ha-1) and can be obtained independently of cloud cover. Both canopy structure and biomass change over time as pioneer species are replaced by early and late regenerating species. These structural changes are related to an increase in (i) tree height, (ii) tree species richness and (iii) canopy thickness and influence the roughness of the canopy surface and consequently SAR image texture. Therefore, we investigated the degree to which textural information could be used to increase the correlation between image tone (backscatter) and biomass. Field data were used to estimate the biomass of 37 regenerating forests plots in Brazilian Amazonia. Texture measures derived from local statistics, the grey level co-occurrence matrix (GLCM) and the variogram were evaluated using simulated images on the basis of their ability to identify significant differences in image texture independently of image contrast. The selected texture measures were applied to L-band JERS-1 (Japanese Earth Resources Satellite) SAR images and the correlation between backscatter and biomass was determined for regenerating tropical forests. A strong correlation was found for the texture measures and biomass. The ra2 (adjusted coefficient of determination), measuring the correlation between backscatter and biomass, increased from 0.74 to 0.82 with the addition of GLCM-derived contrast. The addition of image texture (GLCM-derived contrast) to image tone (backscatter) potentially increases the accuracy with which JERS-1 SAR data can be used to estimate biomass in tropical forests. Numéro de notice : A2005-469 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160500239107 En ligne : https://doi.org/10.1080/01431160500239107 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27605
in International Journal of Remote Sensing IJRS > vol 26 n° 21 (November 2005) . - pp 4829 - 4854[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 080-05211 RAB Revue Centre de documentation En réserve L003 Disponible Derivation of terrain roughness indicators via granulometries / L.T. Tay in International Journal of Remote Sensing IJRS, vol 26 n° 18 (September 2005)
[article]
Titre : Derivation of terrain roughness indicators via granulometries Type de document : Article/Communication Auteurs : L.T. Tay, Auteur ; B.S. Daya Sagar, Auteur ; H.T. Chuah, Auteur Année de publication : 2005 Article en page(s) : pp 3901 - 3910 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] bassin hydrographique
[Termes IGN] échantillonnage d'image
[Termes IGN] figure géométrique
[Termes IGN] géomorphologie
[Termes IGN] granulométrie (pétrologie)
[Termes IGN] Malaisie
[Termes IGN] modèle numérique de surface
[Termes IGN] niveau de gris (image)
[Termes IGN] rugosité du solRésumé : (Auteur) Digital elevation models (DEMs) provide rich clues about various geophysical and geomorphologic processes. These clues include conspicuous protrusions and intrusions of foreground and background portions that testify the presence of channels and ridges in DEMs. We show an application of greyscale granulometries to characterize DEMs through shape-size complexity measures relative to symmetric rhombus, octagon and square templates. We first compute pattern spectra that measure the size distributions of protrusions and intrusions in a DEM. We then employ pattern spectra to compute probability size distribution functions of protrusions and intrusions relative to three templates. We finally compute shape-size complexity measures of DEM by employing these probability functions. To illustrate the implementation of granulometric approach to compute these measures of both background and foreground, we consider an interferometrically generated DEM of a part of Cameron Highlands of Malaysia. Hierarchical watersheds that could be decomposed from DEMs can be better classified via these measures. Numéro de notice : A2005-427 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160500165880 En ligne : https://doi.org/10.1080/01431160500165880 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27563
in International Journal of Remote Sensing IJRS > vol 26 n° 18 (September 2005) . - pp 3901 - 3910[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-05181 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Multivariate texture-based segmentation of remotely sensed imagery for extraction of objects and their uncertainty / Arko Lucieer in International Journal of Remote Sensing IJRS, vol 26 n° 14 (July 2005)
[article]
Titre : Multivariate texture-based segmentation of remotely sensed imagery for extraction of objects and their uncertainty Type de document : Article/Communication Auteurs : Arko Lucieer, Auteur ; Alfred Stein, Auteur ; Peter F. Fisher, Auteur Année de publication : 2005 Article en page(s) : pp 2917 - 2936 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse multivariée
[Termes IGN] extraction automatique
[Termes IGN] image CASI
[Termes IGN] image multibande
[Termes IGN] incertitude des données
[Termes IGN] niveau de gris (image)
[Termes IGN] objet géographique
[Termes IGN] segmentation d'image
[Termes IGN] texture d'imageRésumé : (Auteur) In this study, a segmentation procedure is proposed, based on grey-level and multivariate texture to extract spatial objects from an image scene. Object uncertainty was quantified to identify transitions zones of objects with indeterminate boundaries. The Local Binary Pattern (LBP) operator, modelling texture, was integrated into a hierarchical splitting segmentation to identifiy homogeneous texture regions in an image. We proposed a multivariate extension of the standard univariate LBP operator to describe colour texture. The paper is illustrated with two case studies. The first considers an image with a composite of texture regions. The two LBP operators provided good segmentation results on both grey-scale and colour textures, depicted by accuracy values of 96% and 98% respectively. The second case study involved segmentation of coastal land cover objects from a multispectral Compact Airborne Spectral Imager (CASI) image, of a coastal area in the UK. Segmentation based on the univariate LBP measure provided unsatisfactory segmentation results from a single CASI band (70% accuracy). A multivariate LBP-based segmentation of three CASI bands improved segmentation results considerably (77% accuracy). Uncertainty values for object building blocks provided valuable information for identification of object transition zones. We conclude that the multivariate LBP texture model in combinaison with a hierarchical splitting segmentation framework is suitable for identifying objects and for quantifying their uncertainty. Numéro de notice : A2005-294 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160500057723 En ligne : https://doi.org/10.1080/01431160500057723 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27430
in International Journal of Remote Sensing IJRS > vol 26 n° 14 (July 2005) . - pp 2917 - 2936[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-05141 RAB Revue Centre de documentation En réserve L003 Exclu du prêt A high-reliability, high-resolution method for land cover classification into forest and non-forest / Roger Trias-Sanz (2005)
contenu dans Image Analysis, 14th Scandinavian Conference, SCIA 2005, Joensuu, Finland, June 2005 / Heikki Kalviainen (2005)
Titre : A high-reliability, high-resolution method for land cover classification into forest and non-forest Type de document : Article/Communication Auteurs : Roger Trias-Sanz , Auteur ; Didier Boldo , Auteur Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2005 Collection : Lecture notes in Computer Science, ISSN 0302-9743 num. 3540 Conférence : SCIA 2005, 14th Scandinavian Conference on Image Analysis 19/06/2005 22/06/2005 Joensuu Finlande Proceedings Springer Importance : pp 831 - 840 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification basée sur les régions
[Termes IGN] forêt
[Termes IGN] image aérienne
[Termes IGN] occupation du sol
[Termes IGN] segmentation hiérarchique
[Termes IGN] valeur radiométriqueRésumé : (auteur) We present several methods for per-region land-cover classification based on distances on probability distributions and whole-region probabilities. We present results on using this method for locating forest areas in high-resolution aerial images with very high reliability, achieving more than 95% accuracy, using raw radiometric channels as well as derived color and texture features. Region boundaries are obtained from a multi-scale hierarchical segmentation or from a registration of cadastral maps. Numéro de notice : C2005-033 Affiliation des auteurs : MATIS (1993-2011) Thématique : FORET/IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1007/11499145_84 En ligne : https://doi.org/10.1007/11499145_84 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99876 Documents numériques
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