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Poststack seismic data denoising based on 3-D convolutional neural network / Dawei Liu in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)
[article]
Titre : Poststack seismic data denoising based on 3-D convolutional neural network Type de document : Article/Communication Auteurs : Dawei Liu, Auteur ; Dawei Liu, Auteur ; Xiaokai Wang, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1598 - 1629 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] apprentissage profond
[Termes IGN] bruit blanc
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] données localisées 3D
[Termes IGN] échantillonnage
[Termes IGN] filtrage du bruit
[Termes IGN] filtre de Gauss
[Termes IGN] post-stratification de données
[Termes IGN] séisme
[Termes IGN] sismologieRésumé : (Auteur) Deep learning has been successfully applied to image denoising. In this study, we take one step forward by using deep learning to suppress random noise in poststack seismic data from the aspects of network architecture and training samples. On the one hand, poststack seismic data denoising mainly aims at 3-D seismic data. We designed an end-to-end 3-D denoising convolutional neural network (3-D-DnCNN) that takes raw 3-D cubes as input in order to better extract the features of the 3-D spatial structure of poststack seismic data. On the other hand, denoising images with deep learning require noisy–clean sample pairs for training. In the field of seismic data processing, researchers usually try their best to suppress noise by using complex processes that combine different methods, but clean labels of seismic data are not available. In addition, building training samples in field seismic data has become an interesting but challenging problem. Therefore, we propose a training sample selection method that contains a complex workflow to produce comparatively ideal training samples. Experiments in this study demonstrate that deep learning can directly learn the ability to denoise field seismic data from selected samples. Although the building of the training samples may occur through a complex process, the experimental results of synthetic seismic data and field seismic data show that the 3-D-DnCNN has learned the ability to suppress the Gaussian noise and super-Gaussian noise from different training samples. Moreover, the 3-D-DnCNN network has better denoising performance toward arc-like imaging noise. In addition, we adopt residual learning and batch normalization in order to accelerate the training speed. After network training is satisfactorily completed, its processing efficiency can be significantly higher than that of conventional denoising methods. Numéro de notice : A2020-087 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2947149 Date de publication en ligne : 06/11/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2947149 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94661
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 3 (March 2020) . - pp 1598 - 1629[article]Recent sea level change in the black sea from satellite altimetry and tide gauge observations / Nevin Betül Avsar in ISPRS International journal of geo-information, vol 9 n° 3 (March 2020)
[article]
Titre : Recent sea level change in the black sea from satellite altimetry and tide gauge observations Type de document : Article/Communication Auteurs : Nevin Betül Avsar, Auteur ; H.S. Kutoglu, Auteur Année de publication : 2020 Article en page(s) : 18 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] altimétrie
[Termes IGN] déformation verticale de la croute terrestre
[Termes IGN] données GNSS
[Termes IGN] données marégraphiques
[Termes IGN] données satellitaires
[Termes IGN] données topographiques
[Termes IGN] érosion côtière
[Termes IGN] marégraphe
[Termes IGN] montée du niveau de la mer
[Termes IGN] Noire, mer
[Termes IGN] série temporelle
[Termes IGN] surcharge hydrologique
[Termes IGN] variation saisonnière
[Vedettes matières IGN] AltimétrieRésumé : (auteur) Global mean sea level has been rising at an increasing rate, especially since the early 19th century in response to ocean thermal expansion and ice sheet melting. The possible consequences of sea level rise pose a significant threat to coastal cities, inhabitants, infrastructure, wetlands, ecosystems, and beaches. Sea level changes are not geographically uniform. This study focuses on present-day sea level changes in the Black Sea using satellite altimetry and tide gauge data. The multi-mission gridded satellite altimetry data from January 1993 to May 2017 indicated a mean rate of sea level rise of 2.5 ± 0.5 mm/year over the entire Black Sea. However, when considering the dominant cycles of the Black Sea level time series, an apparent (significant) variation was seen until 2014, and the rise in the mean sea level has been estimated at about 3.2 ± 0.6 mm/year. Coastal sea level, which was assessed using the available data from 12 tide gauge stations, has generally risen (except for the Bourgas Station). For instance, from the western coast to the southern coast of the Black Sea, in Constantza, Sevastopol, Tuapse, Batumi, Trabzon, Amasra, Sile, and Igneada, the relative rise was 3.02, 1.56, 2.92, 3.52, 2.33, 3.43, 5.03, and 6.94 mm/year, respectively, for varying periods over 1922–2014. The highest and lowest rises in the mean level of the Black Sea were in Poti (7.01 mm/year) and in Varna (1.53 mm/year), respectively. Measurements from six Global Navigation Satellite System (GNSS) stations, which are very close to the tide gauges, also suggest that there were significant vertical land movements at some tide gauge locations. This study confirmed that according to the obtained average annual phase value of sea level observations, seasonal sea level variations in the Black Sea reach their maximum annual amplitude in May–June. Numéro de notice : A2020-254 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9030185 Date de publication en ligne : 20/03/2020 En ligne : https://doi.org/10.3390/ijgi9030185 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95008
in ISPRS International journal of geo-information > vol 9 n° 3 (March 2020) . - 18 p.[article]Spectral–spatial–temporal MAP-based sub-pixel mapping for land-cover change detection / Da He in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)
[article]
Titre : Spectral–spatial–temporal MAP-based sub-pixel mapping for land-cover change detection Type de document : Article/Communication Auteurs : Da He, Auteur ; Yanfei Zhong, Auteur ; Liangpei Zhang, Auteur Année de publication : 2020 Article en page(s) : pp 1696 - 1717 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] changement d'occupation du sol
[Termes IGN] classification du maximum a posteriori
[Termes IGN] détection de changement
[Termes IGN] distribution spatiale
[Termes IGN] données spatiotemporelles
[Termes IGN] image Aqua-MODIS
[Termes IGN] image Landsat-8
[Termes IGN] image Landsat-TM
[Termes IGN] image multibande
[Termes IGN] image Quickbird
[Termes IGN] image Terra-MODIS
[Termes IGN] modèle dynamique
[Termes IGN] optimisation spatiale
[Termes IGN] précision infrapixellaire
[Termes IGN] série temporelle
[Termes IGN] urbanisation
[Termes IGN] Wuhan (Chine)
[Termes IGN] zone urbaineRésumé : (Auteur) The maximum a posteriori (MAP) estimation model-based sub-pixel mapping (SPM) method is an alternative way to solve the ill-posed SPM problem. The MAP estimation model has been proven to be an effective SPM approach and has been extensively developed over the past few years, as a result of its effective regularization capability that comes from the spatial regularization model. However, various spatial regularization models do not always truly reflect the detailed spatial distribution in a real situation, and the over-smoothing effect of the spatial regularization model always tends to efface the detailed structural information. In this article, under the scenario of time-series observation by remote sensing imagery, the joint spectral–spatial–temporal MAP-based (SST_MAP) model for SPM is proposed. In SST_MAP, a newly developed temporal regularization model is added to the MAP model, based on the prerequisite for a temporally close fine image covering the same study region. This available fine image can provide the specific spatial structures most closely conforming to the ground truth for a more precise constraint, thereby reducing the over-smoothing effect. Furthermore, the three dimensions are mutually balanced and mutually constrained, to reach an equilibrium point and achieve restoration of both smooth areas for the homogeneous land-cover classes and a detailed structure for the heterogeneous land-cover classes. Four experiments were designed to validate the proposed SST_MAP: three synthetic-image experiments and one real-image experiment. The restoration results confirm the superiority of the proposed SST_MAP model. Notably, under the background of time-series observation, SST_MAP provides an alternative way of land-cover change detection (LCCD), achieving both detailed spatial-scale and high-frequency temporal LCCD observation for the study case of urbanization analysis within the city of Wuhan in China. Numéro de notice : A2020-088 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2947708 Date de publication en ligne : 18/12/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2947708 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94662
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 3 (March 2020) . - pp 1696 - 1717[article]Thermal unmixing based downscaling for fine resolution diurnal land surface temperature analysis / Jiong Wang in ISPRS Journal of photogrammetry and remote sensing, vol 161 (March 2020)
[article]
Titre : Thermal unmixing based downscaling for fine resolution diurnal land surface temperature analysis Type de document : Article/Communication Auteurs : Jiong Wang, Auteur ; Olivier Schmitz, Auteur ; Meng Lu, Auteur ; Derek Karssenberg, Auteur Année de publication : 2020 Article en page(s) : pp 76 - 89 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] données spatiotemporelles
[Termes IGN] factorisation de matrice non-négative
[Termes IGN] image Aqua-MODIS
[Termes IGN] image Landsat
[Termes IGN] image Terra-MODIS
[Termes IGN] image thermique
[Termes IGN] mise à l'échelle
[Termes IGN] Pays-Bas
[Termes IGN] radiance
[Termes IGN] réduction
[Termes IGN] température de surface
[Termes IGN] variation diurneRésumé : (Auteur) Due to the limitation in the availability of airborne imagery data that are high in both spatial and temporal resolution, land surface temperature (LST) dense in both space and time can only be obtained through downscaling of frequently acquired LST with coarse resolution. Many conventional downscaling techniques are only feasible in an ideal situation, where land surface factors as LST predictors are continuously available for downscaling the LST. These techniques are also applied only at large scales ignoring sub-regional variations. Based upon unmixing based approaches, this study presents an LST downscaling workflow, where only the coarse resolution of 1 km LST image at the prediction time is required. The conceptual backbone of the study is assuming that the LST patterns are governed by thermal behaviors of a fixed set of temperature sensitive land surface components. In operation, the study focuses on central Netherlands covering an area of 90 × 90 km. The MODIS and Landsat imagery acquired simultaneously are used as a coarse-fine resolution pair to derive downscaling mechanism which is then applied to coarse imagery at a time with missing fine resolution imagery. First, an optimal number of thermal components are extracted at fine resolution through the application of the non-negative matrix factorization (NMF). These components are assumed to possess unique temperature change patterns caused by combined effects of land cover change, radiance change, or both. Given the LST change and thermal components at coarse resolution, the LST change load of each component can then be obtained at the coarse resolution by solving a system of linear equations encoding thermal component-LST relationship. Such LST change load of thermal components is further unmixed to fine resolution and linearly weighted by the component distribution at fine resolution to obtain the fine resolution LST change. During the process, the coarse LST data is used directly without any resampling practice as shown in previous studies. Thus the technique is less time consuming even with a large downscaling factor of 30. The downscaled fine resolution LST represents an R-squared of over 0.7 outperforming classic downscaling techniques. The downscaled LST differentiates temperature over major land types and captures both seasonal and diurnal LST dynamics. Numéro de notice : A2020-063 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.01.014 Date de publication en ligne : 16/01/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.01.014 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94580
in ISPRS Journal of photogrammetry and remote sensing > vol 161 (March 2020) . - pp 76 - 89[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2020031 RAB Revue Centre de documentation En réserve L003 Disponible 081-2020033 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2020032 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Unsupervised extraction of urban features from airborne lidar data by using self-organizing maps / Alper Sen in Survey review, vol 52 n° 371 (March 2020)
[article]
Titre : Unsupervised extraction of urban features from airborne lidar data by using self-organizing maps Type de document : Article/Communication Auteurs : Alper Sen, Auteur ; Baris Suleymanoglu, Auteur ; Metin Soycan, Auteur Année de publication : 2020 Article en page(s) : pp 150 - 158 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] algorithme de filtrage
[Termes IGN] carte de Kohonen
[Termes IGN] classification non dirigée
[Termes IGN] classification par réseau neuronal
[Termes IGN] données lidar
[Termes IGN] extraction de la végétation
[Termes IGN] extraction de points
[Termes IGN] filtre adaptatif
[Termes IGN] khi carré
[Termes IGN] pondération
[Termes IGN] réseau neuronal artificiel
[Termes IGN] semis de points
[Termes IGN] zone urbaineRésumé : (auteur) The extraction of artificial and natural features using light detection and ranging (Lidar) data is a fundamental task in many fields of research for environmental science. In this study, the possibility of using self-organising maps (SOM), which is an unsupervised artificial neural network classification method to extract the bare earth surface and features from airborne Lidar data, was investigated for two different urban areas. The effect of the enlargement of the study area was analysed using the proposed approach. The appropriate weights of SOM inputs, which are 3D coordinates and intensity, obtained from a Lidar point cloud were determined by using Pearson's chi-squared independence test. The weighted SOM feature extraction performance was better than that of the unweighted SOM. The filtering results of SOM to separate ground and non-ground data were also compared with those obtained by the adaptive TIN filtering algorithm. Most of the non-ground features could be removed by the weighted SOM. Numéro de notice : A2020-079 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2018.1532704 Date de publication en ligne : 12/10/2018 En ligne : https://doi.org/10.1080/00396265.2018.1532704 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94642
in Survey review > vol 52 n° 371 (March 2020) . - pp 150 - 158[article]An OD flow clustering method based on vector constraints: a case study for Beijing taxi origin-destination data / Xiaogang Guo in ISPRS International journal of geo-information, vol 9 n° 2 (February 2020)PermalinkAutomated extraction of lane markings from mobile LiDAR point clouds based on fuzzy inference / Heidar Rastiveis in ISPRS Journal of photogrammetry and remote sensing, vol 160 (February 2020)PermalinkComplex deformation at shallow depth during the 30 October 2016 Mw6.5 Norcia earthquake: interferencebetween tectonic and gravity processes? / Arthur Delorme in Tectonics, vol 39 n° 2 (February 2020)PermalinkExtending Processing Toolbox for assessing the logical consistency of OpenStreetMap data / Sukhjit Singh Sehra in Transactions in GIS, Vol 24 n° 1 (February 2020)PermalinkLandslide displacement mapping based on ALOS-2/PALSAR-2 data using image correlation techniques and SAR interferometry: application to the Hell-Bourg landslide (Salazie Circle, La Réunion Island) / Daniel Raucoules in Geocarto international, vol 35 n° 2 ([01/02/2020])PermalinkA LiDAR–optical data fusion approach for identifying and measuring small stream impoundments and dams / Benjamin Swan in Transactions in GIS, Vol 24 n° 1 (February 2020)PermalinkMicro-tasking as a method for human assessment and quality control in a geospatial data import / Atle Frenvik Sveen in Cartography and Geographic Information Science, vol 47 n° 2 (February 2020)PermalinkPromoting environmental justice through Integrated mapping approaches: the map of water conflicts in Andalusia (Spain) / Belen Pedregal in ISPRS International journal of geo-information, vol 9 n° 2 (February 2020)PermalinkRadial interpolation of GPS and leveling data of ground deformation in a resurgent caldera: application to Campi Flegrei (Italy) / Andrea Bevilacqua in Journal of geodesy, vol 94 n°2 (February 2020)PermalinkReal-time mapping of natural disasters using citizen update streams / Iranga Subasinghe in International journal of geographical information science IJGIS, vol 34 n° 2 (February 2020)Permalink