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An intelligent approach towards automatic shape modelling and object extraction from satellite images using cellular automata based algorithm / P. V. Arun in Geocarto international, vol 29 n° 5 - 6 (August - October 2014)
[article]
Titre : An intelligent approach towards automatic shape modelling and object extraction from satellite images using cellular automata based algorithm Type de document : Article/Communication Auteurs : P. V. Arun, Auteur Année de publication : 2014 Article en page(s) : pp 628-638 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] champ aléatoire de Markov
[Termes IGN] classification par réseau neuronal
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] image IRS-LISS
[Termes IGN] image Landsat
[Termes IGN] interpolationRésumé : (auteur) Automatic feature extraction domain has witnessed the application of many intelligent methodologies over past decade; however detection accuracy of these approaches were limited as object geometry and contextual knowledge were not given enough consideration. In this paper, we propose a frame work for accurate detection of features along with automatic interpolation, and interpretation by modelling feature shape as well as contextual knowledge using advanced techniques such as SVRF, Cellular Neural Network, Core set, and MACA. Developed methodology has been compared with contemporary methods using different statistical measures. Investigations over various satellite images revealed that considerable success was achieved with the CNN approach. CNN has been effective in modelling different complex features effectively and complexity of the approach has been considerably reduced using corset optimization. The system has dynamically used spectral and spatial information for representing contextual knowledge using CNN-prologue approach. System has been also proved to be effective in providing intelligent interpolation and interpretation of random features. Numéro de notice : A2014-419 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2013.826738 En ligne : https://doi.org/10.1080/10106049.2013.826738 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73955
in Geocarto international > vol 29 n° 5 - 6 (August - October 2014) . - pp 628-638[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2014031 RAB Revue Centre de documentation En réserve L003 Disponible Coastal and marine ecological changes and fish cage culture development in Phu Quoc, Vietnam (2001 to 2011) / Diep Thi Hong Nguyen in Geocarto international, vol 29 n° 5 - 6 (August - October 2014)
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Titre : Coastal and marine ecological changes and fish cage culture development in Phu Quoc, Vietnam (2001 to 2011) Type de document : Article/Communication Auteurs : Diep Thi Hong Nguyen, Auteur ; Nitin Kumar Tripathi, Auteur ; Wenresti G. Gallardo, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 486-506 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] classification orientée objet
[Termes IGN] détection de changement
[Termes IGN] eaux côtières
[Termes IGN] herbier marin
[Termes IGN] image ALOS-AVNIR2
[Termes IGN] image Landsat-TM
[Termes IGN] image Theos
[Termes IGN] milieu marin
[Termes IGN] qualité des eaux
[Termes IGN] Viet NamRésumé : (auteur) This study employed image enhancement for LANDSAT TM and ALOS imagery to monitor the changing status of coastal resources from 2001 to 2011, object-based classification of high-resolution THEOS imagery to extract fish cage culture sites and interpolation methods to determine marine environmental quality in 2011 in the northern part of Phu Quoc Island. There were five classes in the study site: natural forest, Melaleuca forest, agriculture, peat and built-up areas. Agricultural land and Melaleuca forest changing into built-up areas constituted approximately 51.13% of the total area changing. The benthic seagrass habitat increased dramatically from 2001 to the end of 2010. Besides, marine culture has been concerned to cage culture which is one of the sources directly affecting aquatic life and water quality in coastal environment. Cage culture locations were detected using high-resolution imagery as THEOS data for image fusion and Object-based Image Analysis methods. Water quality criteria including nitrogen, phosphorus and chlorophyll-a concentrations were determined by interpolation method, and the spatial distribution of these parameters showed a concentration in the study area in the range from 0.17 to 0.49 mg/L, 0.012 to 0.073 mg/L and 0.26 to 1.046 μg/L, respectively. Numéro de notice : A2014-408 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2013.798358 En ligne : http://www.tandfonline.com/doi/full/10.1080/10106049.2013.798358 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73945
in Geocarto international > vol 29 n° 5 - 6 (August - October 2014) . - pp 486-506[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2014031 RAB Revue Centre de documentation En réserve L003 Disponible Geospatial method for computing supplemental multi-decadal US coastal land use and land cover classification products, using Landsat data and C-CAP products / Joseph P. Spruce in Geocarto international, vol 29 n° 5 - 6 (August - October 2014)
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Titre : Geospatial method for computing supplemental multi-decadal US coastal land use and land cover classification products, using Landsat data and C-CAP products Type de document : Article/Communication Auteurs : Joseph P. Spruce, Auteur ; James C. Smoot, Auteur ; Jean T. Ellis, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 470-485 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification ISODATA
[Termes IGN] classification non dirigée
[Termes IGN] détection de changement
[Termes IGN] image Landsat
[Termes IGN] image optique
[Termes IGN] occupation du sol
[Termes IGN] surveillance du littoralRésumé : (auteur) This paper discusses the development and implementation of a method that can be used with multi-decadal Landsat data for computing general coastal US land use and land cover (LULC) maps consisting of seven classes. With Mobile Bay, Alabama as the study region, the method that was applied to derive LULC products for nine dates across a 34-year time span. Classifications were computed and refined using decision rules in conjunction with unsupervised classification of Landsat data and Coastal Change and Analysis Program value-added products. Each classification’s overall accuracy was assessed by comparing stratified random locations to available high spatial resolution satellite and aerial imagery, field survey data and raw Landsat RGBs. Overall classification accuracies ranged from 83 to 91% with overall κ statistics ranging from 0.78 to 0.89. Accurate classifications were computed for all nine dates, yielding effective results regardless of season and Landsat sensor. This classification method provided useful map inputs for computing LULC change products. Numéro de notice : A2014-407 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2013.798357 Date de publication en ligne : 04/06/2013 En ligne : https://doi.org/10.1080/10106049.2013.798357 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73944
in Geocarto international > vol 29 n° 5 - 6 (August - October 2014) . - pp 470-485[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2014031 RAB Revue Centre de documentation En réserve L003 Disponible Mapping fuels at the wildland-urban interface using colour ortho-images and Lidar data / Melissa F. Rosa in Geocarto international, vol 29 n° 5 - 6 (August - October 2014)
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Titre : Mapping fuels at the wildland-urban interface using colour ortho-images and Lidar data Type de document : Article/Communication Auteurs : Melissa F. Rosa, Auteur ; Douglas A. Stow, Auteur Année de publication : 2014 Article en page(s) : pp 570-588 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] biomasse (combustible)
[Termes IGN] carte thématique
[Termes IGN] classification orientée objet
[Termes IGN] combustible
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] fusion de données
[Termes IGN] incendie
[Termes IGN] orthoimage
[Termes IGN] orthoimage couleur
[Termes IGN] San Diego
[Termes IGN] simulationRésumé : (auteur) Fuel type mapping of the wildland-urban interface (WUI) in support of fire spread simulation modelling should include both natural and urban features. The objective of this study was to evaluate the utility of (1) Light Detection and Ranging (LiDAR) structural data, (2) ortho-image data and (3) a combination of both as input to an object-based classification approach for mapping fuels within two WUI areas in San Diego, California. A separability analysis was utilized to determine the surface topographical and spectral layers most influential for discriminating WUI fuels. An accuracy assessment revealed that the combination of LiDAR and ortho-image data inputs substantially increased classification accuracy by 20–30% and achieved overall accuracies > 80%. Results from the study provide knowledge on how reliable fuel types within the WUI can be mapped using high-resolution LiDAR and ortho-image data while presenting new insights into fuel type mapping. Numéro de notice : A2014-417 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2013.819040 En ligne : https://doi.org/10.1080/10106049.2013.819040 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73951
in Geocarto international > vol 29 n° 5 - 6 (August - October 2014) . - pp 570-588[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2014031 RAB Revue Centre de documentation En réserve L003 Disponible A rule-based parameter aided with object-based classification approach for extraction of building and roads from WorldView-2 images / Zahra Ziaei in Geocarto international, vol 29 n° 5 - 6 (August - October 2014)
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Titre : A rule-based parameter aided with object-based classification approach for extraction of building and roads from WorldView-2 images Type de document : Article/Communication Auteurs : Zahra Ziaei, Auteur ; Biswajeet Pradhan, Auteur ; Shattri Bin Mansor, Auteur Année de publication : 2014 Article en page(s) : pp 554-569 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification à base de connaissances
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] détection du bâti
[Termes IGN] eCognition
[Termes IGN] image Worldview
[Termes IGN] plus proche voisin, algorithme duRésumé : (auteur) Roads and buildings constitute a significant proportion of urban areas. Considerable amount of research has been done on the road and building extraction from remotely sensed imagery. However, a few of them have been concentrating on using only spectral information. This study presents a comparison between three object-based models for urban features’ classification, specifically roads and buildings, from WorldView-2 satellite imagery. The three applied algorithms are support vector machines (SVMs), nearest neighbour (NN) and proposed rule-based system. The results indicated that the proposed rules in this study, despite the spectral complexity of land cover types, performed a satisfactory output with an overall accuracy of 92.92%. The advantages offered by the proposed rules were not provided by other two applied algorithms and it revealed the highest accuracy compared to SVM and NN. The overall accuracy for SVM was 76.76%, which is almost similar to the result achieved by NN (77.3%). Numéro de notice : A2014-412 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2013.819039 En ligne : https://doi.org/10.1080/10106049.2013.819039 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73949
in Geocarto international > vol 29 n° 5 - 6 (August - October 2014) . - pp 554-569[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2014031 RAB Revue Centre de documentation En réserve L003 Disponible Detection, segmentation and classification of 3D urban objects using mathematical morphology and supervised learning / Andrès Serna in ISPRS Journal of photogrammetry and remote sensing, vol 93 (July 2014)PermalinkGround and building extraction from LiDAR data based on differential morphological profiles and locally fitted surfaces / Domen Mongus in ISPRS Journal of photogrammetry and remote sensing, vol 93 (July 2014)PermalinkSAR change detection based on intensity and texture changes / Maoguo Gong in ISPRS Journal of photogrammetry and remote sensing, vol 93 (July 2014)PermalinkPermalinkAn effective morphological index in automatic recognition of built-up area suitable for high spatial resolution images as ALOS and SPOT data / Bo Yu in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 6 (June 2014)PermalinkUne approche basée objet combinée avec les classifieurs avancés (SVM, RF, Extra Trees) pour la détection des changements du bâti / Loubna Elmansouri in Revue internationale de géomatique, vol 24 n° 2 (juin - août 2014)PermalinkAutomatic reconstruction of regular buildings using a shape-based balloon snake model / Diaro Yari in Photogrammetric record, vol 29 n° 146 (June - August 2014)PermalinkDevelopment of fuzzy rule-based parameters for urban object-oriented classification using very high resolution imagery / Alireza Hamedianfar in Geocarto international, vol 29 n° 3 - 4 (June - July 2014)PermalinkFeature extraction of hyperspectral images with image fusion and recursive filtering / Xudong Kang in IEEE Transactions on geoscience and remote sensing, vol 52 n° 6 Tome 2 (June 2014)PermalinkMonitoring coastal morphological changes using remote sensing and GIS in the Red river delta area, Vietnam / Si Son Tong in Photo interprétation, European journal of applied remote sensing, vol 50 n° 2 (juin 2014)Permalink