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Automated estimation and tools to extract positions, velocities, breaks, and seasonal terms from daily GNSS measurements: illuminating nonlinear Salton Trough deformation / Michael B. Heflin in Earth and space science, vol 7 n° 7 (July 2020)
[article]
Titre : Automated estimation and tools to extract positions, velocities, breaks, and seasonal terms from daily GNSS measurements: illuminating nonlinear Salton Trough deformation Type de document : Article/Communication Auteurs : Michael B. Heflin, Auteur ; Andrea Donnellan, Auteur ; Jay Parker, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 10 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] Californie (Etats-Unis)
[Termes IGN] chaîne de traitement
[Termes IGN] champ de vitesse
[Termes IGN] déformation horizontale de la croute terrestre
[Termes IGN] données GNSS
[Termes IGN] dorsale
[Termes IGN] faille géologique
[Termes IGN] modèle géologique
[Termes IGN] positionnement par GNSS
[Termes IGN] série temporelle
[Termes IGN] sismologie
[Termes IGN] station GPS
[Termes IGN] valeur aberrante
[Termes IGN] variation saisonnièreRésumé : (auteur) This paper describes the methods used to estimate positions, velocities, breaks, and seasonalterms from daily Global Navigation Satellite System (GNSS) measurements. Break detection and outlierremoval have been automated so that decades of daily measurements from thousands of stations can beprocessed in a few hours. New measurements are added, and parameters are updated every week. Modelparameters allow separation of interseismic, annual, coseismic, and postseismic signals. Tools availablethrough GeoGateway (http://geo-gateway.org) allow rapid visualization and analysis of these terms forresults that can be subsetted in time or space. Results show highly variable and nonlinear motion for GPSstations in southern California. The variable motion is related to seasonal motions, distributed tectonicmotion, earthquakes, and postseismic motions that can continue for years. In some areas results suggest thatadditional processes are responsible for the observed motions. In general, following earthquakes, stationsreturn to their longterm motions after 2–3 years, though some exceptions occur. The use of the tools showsnonlinear motion in the Salton Trough of southern California related to the 2010 M7.2 El MayorCucapahearthquake, 2012 Brawley earthquake swarm, and a creep event on the Superstition Hills fault in 2017. Numéro de notice : A2020-446 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1029/2019EA000644 Date de publication en ligne : 18/05/2020 En ligne : https://doi.org/10.1029/2019EA000644 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95516
in Earth and space science > vol 7 n° 7 (July 2020) . - 10 p.[article]Evaluating techniques for mapping island vegetation from unmanned aerial vehicle (UAV) images: Pixel classification, visual interpretation and machine learning approaches / S.M. Hamylton in International journal of applied Earth observation and geoinformation, vol 89 (July 2020)
[article]
Titre : Evaluating techniques for mapping island vegetation from unmanned aerial vehicle (UAV) images: Pixel classification, visual interpretation and machine learning approaches Type de document : Article/Communication Auteurs : S.M. Hamylton, Auteur ; R.H. Morris, Auteur ; R.C. Carvalho, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : n° 102085 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage automatique
[Termes IGN] carte de la végétation
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] classification pixellaire
[Termes IGN] détection de changement
[Termes IGN] données de terrain
[Termes IGN] image captée par drone
[Termes IGN] Nouvelle-Galles du Sud
[Termes IGN] pesticide
[Termes IGN] réserve naturelle
[Termes IGN] série temporelle
[Termes IGN] surveillance de la végétationRésumé : (auteur) We evaluate three approaches to mapping vegetation using images collected by an unmanned aerial vehicle (UAV) to monitor rehabilitation activities in the Five Islands Nature Reserve, Wollongong (Australia). Between April 2017 and July 2018, four aerial surveys of Big Island were undertaken to map changes to island vegetation following helicopter herbicide sprays to eradicate weeds, including the creeper Coastal Morning Glory (Ipomoea cairica) and Kikuyu Grass (Cenchrus clandestinus). The spraying was followed by a large scale planting campaign to introduce native plants, such as tussocks of Spiny-headed Mat-rush (Lomandra longifolia). Three approaches to mapping vegetation were evaluated, including: (i) a pixel-based image classification algorithm applied to the composite spectral wavebands of the images collected, (ii) manual digitisation of vegetation directly from images based on visual interpretation, and (iii) the application of a machine learning algorithm, LeNet, based on a deep learning convolutional neural network (CNN) for detecting planted Lomandra tussocks. The uncertainty of each approach was assessed via comparison against an independently collected field dataset. Each of the vegetation mapping approaches had a comparable accuracy; for a selected weed management and planting area, the overall accuracies were 82 %, 91 % and 85 % respectively for the pixel based image classification, the visual interpretation / digitisation and the CNN machine learning algorithm. At the scale of the whole island, statistically significant differences in the performance of the three approaches to mapping Lomandra plants were detected via ANOVA. The manual digitisation took a longer time to perform than others. The three approaches resulted in markedly different vegetation maps characterised by different digital data formats, which offered fundamentally different types of information on vegetation character. We draw attention to the need to consider how different digital map products will be used for vegetation management (e.g. monitoring the health individual species or a broader profile of the community). Where individual plants are to be monitored over time, a feature-based approach that represents plants as vector points is appropriate. The CNN approach emerged as a promising technique in this regard as it leveraged spatial information from the UAV images within the architecture of the learning framework by enforcing a local connectivity pattern between neurons of adjacent layers to incorporate the spatial relationships between features that comprised the shape of the Lomandra tussocks detected. Numéro de notice : A2020-716 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.jag.2020.102085 Date de publication en ligne : 03/03/2020 En ligne : https://doi.org/10.1016/j.jag.2020.102085 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96287
in International journal of applied Earth observation and geoinformation > vol 89 (July 2020) . - n° 102085[article]Improved crop classification with rotation knowledge using Sentinel-1 and -2 time series / Sébastien Giordano in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 7 (July 2020)
[article]
Titre : Improved crop classification with rotation knowledge using Sentinel-1 and -2 time series Type de document : Article/Communication Auteurs : Sébastien Giordano , Auteur ; Simon Bailly , Auteur ; Loïc Landrieu , Auteur ; Nesrine Chehata , Auteur Année de publication : 2020 Projets : MAESTRIA / Mallet, Clément Article en page(s) : pp 431 - 441 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] Alpes-de-haute-provence (04)
[Termes IGN] chaîne de traitement
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] parcelle agricole
[Termes IGN] photo-identification
[Termes IGN] Seine-et-Marne (77)
[Termes IGN] série temporelle
[Termes IGN] surface cultivéeRésumé : (Auteur) Leveraging the recent availability of accurate, frequent, and multimodal (radar and optical) Sentinel-1 and -2 acquisitions, this paper investigates the automation of land parcel identification system (LPIS) crop type classification. Our approach allows for the automatic integration of temporal knowledge, i.e., crop rotations using existing parcel-based land cover databases and multi-modal Sentinel-1 and -2 time series. The temporal evolution of crop types was modeled with a linear-chain conditional random field, trained with time series of multimodal (radar and optical) satellite acquisitions and associated LPIS. Our model was tested on two study areas in France (≥ 1250 km2) which show different crop types, various parcel sizes, and agricultural practices: . the Seine et Marne and the Alpes de Haute-Provence classified accordingly to a fine national 25-class nomenclature. We first trained a Random Forest classifier without temporal structure to achieve 89.0% overall accuracy in Seine et Marne (10 classes) and 73% in Alpes de Haute-Provence (14 classes). We then demonstrated experimentally that taking into account the temporal structure of crop rotation with our model resulted in an increase of 3% to +5% in accuracy. This increase was especially important (+12%) for classes which were poorly classified without using the temporal structure. A stark positive impact was also demonstrated on permanent crops, while it was fairly limited or even detrimental for annual crops. Numéro de notice : A2020-382 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.86.7.431 Date de publication en ligne : 01/07/2020 En ligne : https://doi.org/10.14358/PERS.86.7.431 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95428
in Photogrammetric Engineering & Remote Sensing, PERS > vol 86 n° 7 (July 2020) . - pp 431 - 441[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 105-2020071 SL Revue Centre de documentation Revues en salle Disponible Long time-series remote sensing analysis of the periodic cycle evolution of the inlets and ebb-tidal delta of Xincun Lagoon, Hainan Island, China / Huaguo Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 165 (July 2020)
[article]
Titre : Long time-series remote sensing analysis of the periodic cycle evolution of the inlets and ebb-tidal delta of Xincun Lagoon, Hainan Island, China Type de document : Article/Communication Auteurs : Huaguo Zhang, Auteur ; Dongling Li, Auteur ; Juan Wang, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 67 - 85 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] cyclone
[Termes IGN] delta
[Termes IGN] fond marin
[Termes IGN] Hainan (Chine)
[Termes IGN] lagune
[Termes IGN] marée océanique
[Termes IGN] marégraphie
[Termes IGN] message d'alerte
[Termes IGN] modèle conceptuel de données spatio-temporelles
[Termes IGN] précipitation
[Termes IGN] sable
[Termes IGN] série temporelle
[Termes IGN] surveillance du littoral
[Termes IGN] variation temporelleRésumé : (auteur) Coastal lagoon–tidal inlet systems occur worldwide, and each has its own unique evolution characteristics in relation to its geographical location, sediment characteristics, and tidal current and ocean wave conditions. However, insufficient observation data means that it is often difficult to fully understand the long-term and short-term evolution of ebb-tidal deltas, and it is even more difficult to monitor and warn against their evolution. This study uses long time-series remote sensing data for the period 1962–2018 to investigate the evolution of an ebb-tidal delta in Xincun Lagoon, Hainan Island, China. Four shoal-sandbar breaching and tidal-inlet migration events were observed, and the corresponding periodic variation characteristics of the ebb-tidal delta were documented. A conceptual model for the periodic evolution of ebb-tidal deltas was also proposed. The results showed that the long-period (15–20 years) evolution was controlled by the effects of seabed friction and tidal-scale lagoon resonance, while the changes in the length of the east sand-spit could be used as a significant early warning indicator for shoal-sandbar breaching and tidal-inlet migration events. In addition, both types of event were jointly triggered by typhoon storm-surges and the accompanying heavy rainfall, strong winds, and strong waves. Thus, the periodic evolution process of the ebb-tidal delta in Xincun Lagoon was determined to be a systematic process that is either controlled or influenced by a series of interconnecting factors. Moreover, we concluded that it is both feasible and valuable to establish a monitoring and early warning framework of ebb-tidal deltas through the use of time-series remote sensing images. The results of this study can improve the existing understanding of the processes and driving factors of periodic shoal-sandbar breaching and tidal-inlet migration, and can also increase safety nourishment for coastal lagoon–tidal inlet systems. Numéro de notice : A2020-348 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.05.006 Date de publication en ligne : 26/05/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.05.006 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95230
in ISPRS Journal of photogrammetry and remote sensing > vol 165 (July 2020) . - pp 67 - 85[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2020071 RAB Revue Centre de documentation En réserve L003 Disponible 081-2020073 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2020072 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Predicting displacement of bridge based on CEEMDAN-KELM model using GNSS monitoring data / Qian Fan in Journal of applied geodesy, vol 14 n° 3 (July 2020)
[article]
Titre : Predicting displacement of bridge based on CEEMDAN-KELM model using GNSS monitoring data Type de document : Article/Communication Auteurs : Qian Fan, Auteur ; Xiaolin Meng, Auteur ; Dinh Tung Nguyen, Auteur ; Yilin Xie, Auteur ; Jiayong Yu, Auteur Année de publication : 2020 Article en page(s) : pp 253 – 261 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Topographie moderne
[Termes IGN] apprentissage automatique
[Termes IGN] combinaison linéaire
[Termes IGN] données GNSS
[Termes IGN] méthode fondée sur le noyau
[Termes IGN] pont
[Termes IGN] prévention des risques
[Termes IGN] série temporelle
[Termes IGN] surveillance d'ouvrageRésumé : (auteur) Bridges are critical to economic and social development of a country. In order to ensure the safe operation of bridges, it is of great significance to accurately predict displacement of monitoring points from bridge Structural Health System (SHM). In the paper, a CEEMDAN-KELM model is proposed to improve the accuracy of displacement prediction of bridge. Firstly, the original displacement monitoring time series of bridge is accurately and effectively decomposed into multiple components called intrinsic mode functions (IMFs) and one residual component using a method named complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN). Then, these components are forecasted by establishing appropriate kernel extreme learning machine (KELM) prediction models, respectively. At last, the prediction results of all components including residual component are summed as the final prediction results. A case study using global navigation satellite system (GNSS) monitoring data is used to illustrate the feasibility and validity of the proposed model. Practical results show that prediction accuracy using CEEMDAN-KELM model is superior to BP neural network model, EMD-ELM model and EMD-KELM model in terms of the same monitoring data. Numéro de notice : A2020-396 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1515/jag-2019-0057 Date de publication en ligne : 27/03/2020 En ligne : https://doi.org/10.1515/jag-2019-0057 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95431
in Journal of applied geodesy > vol 14 n° 3 (July 2020) . - pp 253 – 261[article]A simple distributed water balance model for an urbanized river basin using remote sensing and GIS techniques / Olutoyin Adeola Fashae in Geocarto international, vol 35 n° 9 ([01/07/2020])PermalinkSpatiotemporally Varying Coefficients (STVC) model: a Bayesian local regression to detect spatial and temporal nonstationarity in variables relationships / Chao Song in Annals of GIS, vol 26 n° 3 (July 2020)PermalinkTemporal and spatial variations of monsoonal upwelling along the South West and East coasts of India / Shailee Patel in Marine geodesy, Vol 43 n° 4 (July 2020)PermalinkAn empirical study on the intra-urban goods movement patterns using logistics big data / Pengxiang Zhao in International journal of geographical information science IJGIS, vol 34 n° 6 (June 2020)PermalinkAn integrated approach for detection and prediction of greening situation in a typical desert area in China and its human and climatic factors analysis / Lei Zhou in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)PermalinkCoastline change modelling induced by climate change using geospatial techniques in Togo (West Africa) / Yawo Konko in Advances in Remote Sensing, vol 9 n° 2 (June 2020)PermalinkImproved optical image matching time series inversion approach for monitoring dune migration in North Sinai Sand Sea: Algorithm procedure, application, and validation / Eslam Ali in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)PermalinkMonitoring clearcutting and subsequent rapid recovery in Mediterranean coppice forests with Landsat time series / Gherardo Chirici in Annals of Forest Science, Vol 77 n° 2 (June 2020)PermalinkValidation of Sentinel-3A SRAL coastal sea level data at high posting rate: 80 Hz / Ana Aldarias in IEEE Transactions on geoscience and remote sensing, vol 58 n° 6 (June 2020)PermalinkFusing adjacent-track InSAR datasets to densify the temporal resolution of time-series 3-D displacement estimation over mining areas with a prior deformation model and a generalized weighting least-squares method / Yuedong Wang in Journal of geodesy, vol 94 n° 5 (May 2020)Permalink