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MapMosaic : dynamic layer compositing for interactive geovisualization / María-Jesús Lobo in International journal of geographical information science IJGIS, vol 31 n° 9-10 (September - October 2017)
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Titre : MapMosaic : dynamic layer compositing for interactive geovisualization Type de document : Article/Communication Auteurs : María-Jesús Lobo , Auteur ; Caroline Appert, Auteur ; Emmanuel Pietriga, Auteur
Année de publication : 2017 Article en page(s) : pp 1818 - 1845 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes d'information géographique
[Termes IGN] analyse comparative
[Termes IGN] cartographie dynamique
[Termes IGN] couche thématique
[Termes IGN] données maillées
[Termes IGN] données matricielles
[Termes IGN] données vectorielles
[Termes IGN] géovisualisation
[Termes IGN] interactivité
[Termes IGN] interface utilisateur
[Termes IGN] logiciel SIG
[Termes IGN] MAPublisher
[Termes IGN] multiplexage
[Termes IGN] QGIS
[Termes IGN] visualisation dynamiqueMots-clés libres : MapMuxing Résumé : (Auteur) GIS software applications and other mapping tools enable users to correlate data from multiple layers and gain insight from the resulting visualizations. However, most of these applications only feature basic, monolithic layer compositing techniques. These techniques do not always support users effectively in their tasks, as we observed during interviews with GIS experts. We introduce MapMosaic, a novel approach based on dynamic visual compositing that enables users to interactively create and manipulate local composites of multiple vector and raster map layers, taking into account the semantics and attribute values of objects and fields in the compositing process. We evaluate MapMosaic ’s interaction model against that of QGIS (a widely used desktop GIS) and MAPublisher (a professional cartography tool) using the ‘Cognitive Dimensions’ framework and through an analytical comparison, showing that MapMosaic ’s model is more flexible and can support users more effectively in their tasks. We also report on feedback obtained from experts, which further confirms the potential of this highly dynamic approach to map layer compositing. Numéro de notice : A2017-505 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2017.1325488 En ligne : https://doi.org/10.1080/13658816.2017.1325488 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86451
in International journal of geographical information science IJGIS > vol 31 n° 9-10 (September - October 2017) . - pp 1818 - 1845[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2017051 RAB Revue Centre de documentation En réserve L003 Disponible Sentinel-1A SAR and sentinel-2A MSI data fusion for urban ecosystem service mapping / Jan Haas in Remote Sensing Applications: Society and Environment, RSASE, vol 8 (November 2017)
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Titre : Sentinel-1A SAR and sentinel-2A MSI data fusion for urban ecosystem service mapping Type de document : Article/Communication Auteurs : Jan Haas, Auteur ; Yifang Ban, Auteur Année de publication : 2017 Article en page(s) : pp 41 - 53 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] fusion d'images
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] occupation du sol
[Termes IGN] segmentation d'image
[Termes IGN] service écosystémique
[Termes IGN] Zurich (Suisse)Résumé : (auteur) The two main objectives of this study are to evaluate the potential use and synergetic effects of ESA Sentinel-1A C-band SAR and Sentinel-2A MSI data for classification and mapping of ecologically important urban and peri-urban space and to introduce spatial characteristics into ecosystem service analyses based on remotely sensed data. Image resolutions between 5 m and 20 m provided by the Sentinel satellites introduce a new relevant spatial scale in-between high and medium resolution data at which not only urban areas but also their important hinterlands can be effectively and efficiently mapped. Sentinel-1/2 data fusion facilitates both the capture of ecologically relevant details while at the same time also enabling large-scale urban analyses that draw surrounding regions into consideration. The combined use of Sentinel-1A SAR in Interferometric Wide Swath mode and simulated Sentinel-2A MSI (APEX) data is being evaluated in a classification of the Zürich metropolitan area, Switzerland. The SAR image was terrain-corrected, speckle-filtered and co-registered to the simulated Sentinel-2 image. After radiometric and spatial resampling, the fused image stack was segmented and classified by SVM. After post-classification, landscape elements were investigated in terms of spatial characteristics and topological relations that are believed to influence ecosystem service supply and demand, i.e. area, contiguity, perimeter-to-area ratio and distance. Based on the classification results, ecosystem service supplies and demands accounting for spatial and topological patch characteristics were attributed to 14 land cover classes. The quantification of supply and demand values resulted in a positive ecosystem service budget for Zürich. The spatially adjusted service budgets and the original budgets are similar from a landscape perspective but deviate up to 50% on the patch level. The introduction of spatial and topological patch characteristics gives a more accurate impression of ecosystem service supply and demands and their distributions, thus enabling more detailed analyses in complex urban surroundings. The method and underlying data are considered suitable for urban land cover and ecosystem service mapping and the introduction of spatial aspects into relative ecosystem service valuation concepts is believed to add another important aspect in currently existing approaches. Numéro de notice : A2017-414 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.rsase.2017.07.006 En ligne : https://doi.org/10.1016/j.rsase.2017.07.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86305
in Remote Sensing Applications: Society and Environment, RSASE > vol 8 (November 2017) . - pp 41 - 53[article]A higher order conditional random field model for simultaneous classification of land cover and land use / Lena Albert in ISPRS Journal of photogrammetry and remote sensing, vol 130 (August 2017)
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Titre : A higher order conditional random field model for simultaneous classification of land cover and land use Type de document : Article/Communication Auteurs : Lena Albert, Auteur ; Franz Rottensteiner, Auteur ; Christian Heipke, Auteur Année de publication : 2017 Article en page(s) : pp 63 - 80 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] champ aléatoire conditionnel
[Termes IGN] classification à base de connaissances
[Termes IGN] classification automatique
[Termes IGN] classification pixellaire
[Termes IGN] image aérienne
[Termes IGN] inférence
[Termes IGN] occupation du sol
[Termes IGN] prise en compte du contexte
[Termes IGN] relation sémantique
[Termes IGN] utilisation du solRésumé : (Auteur) We propose a new approach for the simultaneous classification of land cover and land use considering spatial as well as semantic context. We apply a Conditional Random Fields (CRF) consisting of a land cover and a land use layer. In the land cover layer of the CRF, the nodes represent superpixels; in the land use layer, the nodes correspond to objects from a geospatial database. Intralayer edges of the CRF model spatial dependencies between neighbouring image sites. All spatially overlapping sites in both layers are connected by interlayer edges, which leads to higher order cliques modelling the semantic relation between all land cover and land use sites in the clique. A generic formulation of the higher order potential is proposed. In order to enable efficient inference in the two-layer higher order CRF, we propose an iterative inference procedure in which the two classification tasks mutually influence each other. We integrate contextual relations between land cover and land use in the classification process by using contextual features describing the complex dependencies of all nodes in a higher order clique. These features are incorporated in a discriminative classifier, which approximates the higher order potentials during the inference procedure. The approach is designed for input data based on aerial images. Experiments are carried out on two test sites to evaluate the performance of the proposed method. The experiments show that the classification results are improved compared to the results of a non-contextual classifier. For land cover classification, the result is much more homogeneous and the delineation of land cover segments is improved. For the land use classification, an improvement is mainly achieved for land use objects showing non-typical characteristics or similarities to other land use classes. Furthermore, we have shown that the size of the superpixels has an influence on the level of detail of the classification result, but also on the degree of smoothing induced by the segmentation method, which is especially beneficial for land cover classes covering large, homogeneous areas. Numéro de notice : A2017-510 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.04.006 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.04.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86456
in ISPRS Journal of photogrammetry and remote sensing > vol 130 (August 2017) . - pp 63 - 80[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2017081 RAB Revue Centre de documentation En réserve L003 Disponible 081-2017083 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2017082 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt Local and global evaluation for remote sensing image segmentation / Tengfei Su in ISPRS Journal of photogrammetry and remote sensing, vol 130 (August 2017)
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Titre : Local and global evaluation for remote sensing image segmentation Type de document : Article/Communication Auteurs : Tengfei Su, Auteur ; Shengwei Zhang, Auteur Année de publication : 2017 Article en page(s) : pp 256 - 276 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse d'image orientée objet
[Termes IGN] discrétisation
[Termes IGN] erreur
[Termes IGN] objet géographique
[Termes IGN] segmentation d'imageRésumé : (Auteur) In object-based image analysis, how to produce accurate segmentation is usually a very important issue that needs to be solved before image classification or target recognition. The study for segmentation evaluation method is key to solving this issue. Almost all of the existent evaluation strategies only focus on the global performance assessment. However, these methods are ineffective for the situation that two segmentation results with very similar overall performance have very different local error distributions. To overcome this problem, this paper presents an approach that can both locally and globally quantify segmentation incorrectness. In doing so, region-overlapping metrics are utilized to quantify each reference geo-object's over and under-segmentation error. These quantified error values are used to produce segmentation error maps which have effective illustrative power to delineate local segmentation error patterns. The error values for all of the reference geo-objects are aggregated through using area-weighted summation, so that global indicators can be derived. An experiment using two scenes of very different high resolution images showed that the global evaluation part of the proposed approach was almost as effective as other two global evaluation methods, and the local part was a useful complement to comparing different segmentation results. Numéro de notice : A2017-516 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.06.003 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.06.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86478
in ISPRS Journal of photogrammetry and remote sensing > vol 130 (August 2017) . - pp 256 - 276[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2017081 RAB Revue Centre de documentation En réserve L003 Disponible 081-2017083 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2017082 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt A relative evaluation of random forests for land cover mapping in an urban area / Di Shi in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 8 (August 2017)
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Titre : A relative evaluation of random forests for land cover mapping in an urban area Type de document : Article/Communication Auteurs : Di Shi, Auteur ; Xiaojun Yang, Auteur Année de publication : 2017 Article en page(s) : pp 541 - 552 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse comparative
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] objet géographique complexe
[Termes IGN] occupation du sol
[Termes IGN] Perceptron multicouche
[Termes IGN] zone urbaineRésumé : (auteur) Random forests as a novel ensemble learning algorithm have significant potential for land cover mapping in complex areas but have not been sufficiently tested by the remote sensing community relative to some more popular pattern classifiers. In this research, we implemented random forests as a pattern classifier for land cover mapping from a satellite image covering a complex urban area, and evaluated the performance relative to several popular classifiers including Gaussian maximum likelihood (GML), multi-layer-perceptron networks (MLP), and support vector machines (SVM). Each classifier was carefully configured with the parameter settings recommended by recent literature, and identical training data were used in each classification. The accuracy of each classified map was further evaluated using identical reference data. Random forests were slightly more accurate than SVM and MLP but significantly better than GML in the overall map accuracy. Random forests and support vector machines generated almost identical overall map accuracy, but the former produced a smaller standard deviation of categorical accuracies, suggesting its better overall capability in classifying both homogeneous and heterogeneous land cover classes. Random forests have shown its robustness due to the most accurate classification on the whole, relatively balanced performance across all land cover categories, and relatively easier to implement. These findings should help promote the use of random forests for land cover classification in complex areas. Numéro de notice : A2017-435 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article DOI : 10.14358/PERS.83.8.541 En ligne : https://doi.org/10.14358/PERS.83.8.541 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86339
in Photogrammetric Engineering & Remote Sensing, PERS > vol 83 n° 8 (August 2017) . - pp 541 - 552[article]Fusion of Landsat 8 OLI and sentinel-2 MSI data / Qunming Wang in IEEE Transactions on geoscience and remote sensing, vol 55 n° 7 (July 2017)
PermalinkFusion of RADARSAT-2 and multispectral optical remote sensing data for LULC extraction in a tropical agricultural area / Mohamed Barakat A. Gibril in Geocarto international, vol 32 n° 7 (July 2017)
PermalinkGlobal multi-layer network of human mobility / Alexander Belyi in International journal of geographical information science IJGIS, vol 31 n° 7-8 (July - August 2017)
PermalinkShape-adaptive geometric simplification of heterogeneous line datasets / Timofey Samsonov in International journal of geographical information science IJGIS, vol 31 n° 7-8 (July - August 2017)
PermalinkChange detection of linear features in temporally spaced remotely sensed images using edge-based grid analysis / Arati Paul in Geocarto international, vol 32 n° 6 (June 2017)
PermalinkObject-based analysis of multispectral airborne laser scanner data for land cover classification and map updating / Leena Matikainen in ISPRS Journal of photogrammetry and remote sensing, vol 128 (June 2017)
PermalinkA time-series approach to estimating soil moisture from vegetated surfaces using L-band radar backscatter / Jeffrey D. Ouellette in IEEE Transactions on geoscience and remote sensing, vol 55 n° 6 (June 2017)
PermalinkTotal canopy transmittance estimated from small-footprint, full-waveform airborne LiDAR / Milutin Milenković in ISPRS Journal of photogrammetry and remote sensing, vol 128 (June 2017)
PermalinkVerification and updating of the database of topographic objects with geometric information about buildings by means of airborne laser scanning dataeans of Airborne Laser Scanning Data / Małgorzata Mendela-Anzlik in Reports on geodesy and geoinformatics, vol 103 n° 1 (June 2017)
PermalinkCartographic continuum rendering based on color and texture interpolation to enhance photo-realism perception / Charlotte Hoarau in ISPRS Journal of photogrammetry and remote sensing, vol 127 (May 2017)
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