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Displacement monitoring of upper Atbara dam based on time series InSAR / Q.Q. Wang in Survey review, vol 52 n° 375 (November 2020)
[article]
Titre : Displacement monitoring of upper Atbara dam based on time series InSAR Type de document : Article/Communication Auteurs : Q.Q. Wang, Auteur ; Q.H. Huang, Auteur ; N. He, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 485 - 496 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] auscultation d'ouvrage
[Termes IGN] barrage
[Termes IGN] déformation d'édifice
[Termes IGN] érosion hydrique
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-SAR
[Termes IGN] série temporelle
[Termes IGN] Soudan
[Termes IGN] surveillance d'ouvrageRésumé : (auteur) Dam is an important part of engineering structure, in the process of dam construction, the dam monitoring is crucial since water erosion and time-dependent motion may cause deformation. Traditional monitoring methods are time-consuming and labour-intensive. However, Interferometric Synthetic Aperture Radar (InSAR) can provide precise and spatially dense information on slow deformations. This research investigated the longest earth-rock-fill dam in Sudan to determine the spatial and temporal deformations Sentinel-1A descending SAR images were further used to analyse the issues mentioned above. The results suggested that the dam existed the maximum displacement with a value up to 190 mm on the dam crest. Besides, the selected sections along the riverbed of the dam were analysed and the RMSE was approximately 2 mm/year. The results were in good agreement with the in situ measurements, indicating the advancement of time series InSAR in dam deformation monitoring. Numéro de notice : A2020-686 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2019.1643529 Date de publication en ligne : 17/07/2019 En ligne : https://doi.org/10.1080/00396265.2019.1643529 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96217
in Survey review > vol 52 n° 375 (November 2020) . - pp 485 - 496[article]Geostatistical analysis and mitigation of the atmospheric phase screens in Ku-band terrestrial radar interferometric observations of an alpine glacier / Simone Baffelli in IEEE Transactions on geoscience and remote sensing, vol 58 n° 11 (November 2020)
[article]
Titre : Geostatistical analysis and mitigation of the atmospheric phase screens in Ku-band terrestrial radar interferometric observations of an alpine glacier Type de document : Article/Communication Auteurs : Simone Baffelli, Auteur ; Othmar Frey, Auteur ; Irena Hajnsek, Auteur Année de publication : 2020 Article en page(s) : pp 7533 - 7556 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] Alpes
[Termes IGN] analyse spatio-temporelle
[Termes IGN] bande Ku
[Termes IGN] covariance
[Termes IGN] erreur de phase
[Termes IGN] géostatistique
[Termes IGN] glacier
[Termes IGN] image radar moirée
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] série temporelle
[Termes IGN] vapeur d'eau
[Termes IGN] variogrammeRésumé : (auteur) Terrestrial radar interferometry (TRI) can measure displacements at high temporal resolution, potentially with high accuracy. An application of this method is the observation of the surface flow velocity of steep, fast-flowing aglaciers. For these observations, the main factor limiting the accuracy of TRI observations is the spatial and temporal variabilities in the distribution of atmospheric water vapor content, causing a phase delay [atmospheric phase screen (APS)] whose magnitude is similar to the displacement phase. This contribution presents a geostatistical analysis of the spatial and temporal behaviors of the APS in Ku-Band TRI. The analysis is based on the assumption of a separable spatiotemporal covariance structure, which is tested empirically using variogram analysis. From this analysis, spatial and temporal APS statistics are estimated and used in a two-step procedure combining regression-Kriging with generalized least squares (GLS) inversion to estimate a velocity time-series. The performance of this method is evaluated by cross-validation using phase observations on stable scatterers. This analysis shows a considerable reduction in residual phase variance compared with the standard approach of combining the linear models of APS stratification and interferogram stacking. Numéro de notice : A2020-675 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2976656 Date de publication en ligne : 13/04/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2976656 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96166
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 11 (November 2020) . - pp 7533 - 7556[article]Non-stationary extreme value analysis of ground snow loads in the French Alps: a comparison with building standards / Erwann Le Roux in Natural Hazards and Earth System Sciences, vol 20 n° 11 (November 2020)
[article]
Titre : Non-stationary extreme value analysis of ground snow loads in the French Alps: a comparison with building standards Type de document : Article/Communication Auteurs : Erwann Le Roux, Auteur ; Guillaume Evin, Auteur ; Nicolas Eckert, Auteur ; Juliette Blanchet, Auteur Année de publication : 2020 Article en page(s) : pp 2961 – 2977 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Alpes (France)
[Termes IGN] changement climatique
[Termes IGN] construction
[Termes IGN] épaisseur
[Termes IGN] estimation des charges
[Termes IGN] manteau neigeux
[Termes IGN] norme
[Termes IGN] sécurité
[Termes IGN] série temporelle
[Termes IGN] toit
[Termes IGN] valeur limiteMots-clés libres : Ground snow load surcharge de neige Résumé : (auteur) In a context of climate change, trends in extreme snow loads need to be determined to minimize the risk of structure collapse. We study trends in 50-year return levels of ground snow load (GSL) using non-stationary extreme value models. These trends are assessed at a mountain massif scale from GSL data, provided for the French Alps from 1959 to 2019 by a meteorological reanalysis and a snowpack model. Our results indicate a temporal decrease in 50-year return levels from 900 to 4200 m, significant in the northwest of the French Alps up to 2100 m. We detect the most important decrease at 900 m with an average of −30 % for return levels between 1960 and 2010. Despite these decreases, in 2019 return levels still exceed return levels designed for French building standards under a stationary assumption. At worst (i.e. at 1800 m), return levels exceed standards by 15 % on average, and half of the massifs exceed standards. We believe that these exceedances are due to questionable assumptions concerning the computation of standards. For example, these were devised with GSL, estimated from snow depth maxima and constant snow density set to 150 kg m−3, which underestimate typical GSL values for the snowpack. Numéro de notice : A2020-713 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.5194/nhess-20-2961-2020 Date de publication en ligne : 06/11/2020 En ligne : https://doi.org/10.5194/nhess-20-2961-2020 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96279
in Natural Hazards and Earth System Sciences > vol 20 n° 11 (November 2020) . - pp 2961 – 2977[article]Sea surface temperature and high water temperature occurrence prediction using a long short-term memory model / Minkyu Kim in Remote sensing, vol 12 n° 21 (November 2020)
[article]
Titre : Sea surface temperature and high water temperature occurrence prediction using a long short-term memory model Type de document : Article/Communication Auteurs : Minkyu Kim, Auteur ; Hung Yang, Auteur ; Jonghwa Kim, Auteur Année de publication : 2020 Article en page(s) : n° 3654 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage profond
[Termes IGN] aquaculture
[Termes IGN] changement climatique
[Termes IGN] Corée du sud
[Termes IGN] données météorologiques
[Termes IGN] modèle de simulation
[Termes IGN] pêche
[Termes IGN] réseau neuronal récurrent
[Termes IGN] série temporelle
[Termes IGN] température de surface de la merRésumé : (auteur) Recent global warming has been accompanied by high water temperatures (HWTs) in coastal areas of Korea, resulting in huge economic losses in the marine fishery industry due to disease outbreaks in aquaculture. To mitigate these losses, it is necessary to predict such outbreaks to prevent or respond to them as early as possible. In the present study, we propose an HWT prediction method that applies sea surface temperatures (SSTs) and deep-learning technology in a long short-term memory (LSTM) model based on a recurrent neural network (RNN). The LSTM model is used to predict time series data for the target areas, including the coastal area from Goheung to Yeosu, Jeollanam-do, Korea, which has experienced frequent HWT occurrences in recent years. To evaluate the performance of the SST prediction model, we compared and analyzed the results of an existing SST prediction model for the SST data, and additional external meteorological data. The proposed model outperformed the existing model in predicting SSTs and HWTs. Although the performance of the proposed model decreased as the prediction interval increased, it consistently showed better performance than the European Center for Medium-Range Weather Forecast (ECMWF) prediction model. Therefore, the method proposed in this study may be applied to prevent future damage to the aquaculture industry. Numéro de notice : A2020-721 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs12213654 Date de publication en ligne : 07/11/2020 En ligne : https://doi.org/10.3390/rs12213654 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96311
in Remote sensing > vol 12 n° 21 (November 2020) . - n° 3654[article]Monitoring population dynamics in the Pearl River Delta from 2000 to 2010 / Sisi Yu in Geocarto international, vol 35 n° 14 ([15/10/2020])
[article]
Titre : Monitoring population dynamics in the Pearl River Delta from 2000 to 2010 Type de document : Article/Communication Auteurs : Sisi Yu, Auteur ; ZengXiang Zhang, Auteur ; Fang Liu, Auteur Année de publication : 2020 Article en page(s) : pp 1511 - 1526 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] agglomération
[Termes IGN] croissance urbaine
[Termes IGN] delta de la rivière des perles
[Termes IGN] données démographiques
[Termes IGN] image DMSP-OLS
[Termes IGN] Kouangtoung (Chine)
[Termes IGN] prise de vue nocturne
[Termes IGN] recensement démographique
[Termes IGN] répartition géographique
[Termes IGN] série temporelle
[Termes IGN] surveillance de l'urbanisationRésumé : (auteur) Although numerous literatures have documented the monitoring of population distributions and dynamics for socio-economic development, environmental protection, and urban planning on different scales, little attention has been paid to long-term and multi-frequency population evolution on urban agglomeration scale, especially in non-census years. Furthermore, although multi models have been applied to population spatialization based on night-time light imagery (NLT) and census data, their accuracy needs to be further improved. Selected the Pearl River Delta (PRD), China as the study area, this work aimed to solve the aforementioned problems by constructing the residential extent extraction index (REEI) and employing the population growth theory and ‘DN density–population density’ model. Results indicated that the proposed approaches were feasible to optimize NTL products and simulate populations in both census (2000, 2010) and non-census (2005) years. Population evolution in the PRD presented distinct differences from space and over time, and mainly driven by socioeconomic development. Numéro de notice : A2020-617 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1576778 Date de publication en ligne : 28/05/2019 En ligne : https://doi.org/10.1080/10106049.2019.1576778 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95993
in Geocarto international > vol 35 n° 14 [15/10/2020] . - pp 1511 - 1526[article]Time series potential assessment for biophysical characterization of orchards and crops in a mixed scenario with Sentinel-1A SAR data / Hemant Sahu in Geocarto international, vol 35 n° 14 ([15/10/2020])PermalinkAn advanced residual error model for tropospheric delay estimation / Szabolcs Rózsa in GPS solutions, Vol 24 n° 4 (October 2020)PermalinkAnalysis of shoreline changes in Vishakhapatnam coastal tract of Andhra Pradesh, India: an application of digital shoreline analysis system (DSAS) / Mirza Razi Imam Baig in Annals of GIS, vol 26 n° 4 (October 2020)PermalinkMapping wetland using the object-based stacked generalization method based on multi-temporal optical and SAR data / Yaotong Cai in International journal of applied Earth observation and geoinformation, vol 92 (October 2020)PermalinkWide-area near-real-time monitoring of tropical forest degradation and deforestation using Sentinel-1 / Dirk Hoekman in Remote sensing, vol 12 n° 19 (October-1 2020)PermalinkAn overview of clustering methods for geo-referenced time series: from one-way clustering to co- and tri-clustering / Xiaojing Wu in International journal of geographical information science IJGIS, vol 34 n° 9 (September 2020)PermalinkApplying multi-temporal Landsat satellite data and Markov-cellular automata to predict forest cover change and forest degradation of sundarban reserve forest, Bangladesh / Mohammad Emran Hasan in Forests, vol 11 n° 9 (September 2020)PermalinkAssessing local trends in indicators of ecosystem services with a time series of forest resource maps / Matti Katila in Silva fennica, vol 54 n° 4 (September 2020)PermalinkBenefits of non-tidal loading applied at distinct levels in VLBI analysis / Matthias Glomsda in Journal of geodesy, vol 94 n° 9 (September 2020)PermalinkCombining optical and radar satellite image time series to map natural vegetation: savannas as an example / Maylis Lopes in Remote sensing in ecology and conservation, vol 6 n° 3 (September 2020)PermalinkDeriving a frozen area fraction from Metop ASCAT backscatter based on Sentinel-1 / Helena Bergstedt in IEEE Transactions on geoscience and remote sensing, vol 58 n° 9 (September 2020)PermalinkIlluminating the spatio-temporal evolution of the 2008–2009 Qaidam earthquake sequence with the joint use of Insar time series and teleseismic data / Simon Daout in Remote sensing, vol 12 n° 17 (September-1 2020)PermalinkA novel algorithm to estimate phytoplankton carbon concentration in inland lakes using Sentinel-3 OLCI images / Heng Lyu in IEEE Transactions on geoscience and remote sensing, vol 58 n° 9 (September 2020)PermalinkGipsyX/RTGx, a new tool set for space geodetic operations and research / Willy I. Bertiger in Advances in space research, vol 66 n° 3 (1 August 2020)PermalinkPredicting biomass dynamics at the national extent from digital aerial photogrammetry / Bronwyn Price in International journal of applied Earth observation and geoinformation, vol 90 (August 2020)PermalinkAutomated 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)PermalinkEvaluating 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)PermalinkImproved 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)PermalinkLong 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)PermalinkPredicting 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)Permalink