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Copula-based modeling of dependence structure in geodesy and GNSS applications: case study for zenith tropospheric delay in complex terrain / Roya Mousavian in GPS solutions, vol 25 n° 1 (January 2021)  

Public [article]  inGPS solutions > vol 25 n° 1 (January 2021) . - n° 12 Titre : Copula-based modeling of dependence structure in geodesy and GNSS applications: case study for zenith tropospheric delay in complex terrain Type de document : Article/Communication Auteurs : Roya Mousavian, Auteur ; Christof Lorenz, Auteur ; Masoud Mashhadi Hossainali, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 12 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes descripteurs IGN] corrélation croisée normalisée [Termes descripteurs IGN] dissymétrie [Termes descripteurs IGN] données GNSS [Termes descripteurs IGN] Europe centrale [Termes descripteurs IGN] modèle atmosphérique [Termes descripteurs IGN] prévision météorologique [Termes descripteurs IGN] retard troposphérique zénithal [Termes descripteurs IGN] série temporelle Résumé : (auteur) Modeling and understanding the statistical relationships between geophysical quantities is a crucial prerequisite for many geodetic applications. While these relationships can depend on multiple variables and their interactions, commonly used scalar methods like the (cross) correlation are only able to describe linear dependencies. However, particularly in regions with complex terrain, the statistical relationships between variables can be highly nonlinear and spatially heterogeneous. Therefore, we introduce Copula-based approaches for modeling and analyzing the full dependence structure. We give an introduction to Copula theory, including five of the most widely used models, namely the Frank, Clayton, Ali-Mikhail-Haq, Gumbel and Gaussian Copula, and use this approach for analyzing zenith tropospheric delays (ZTDs). We apply modeled ZTDs from the Weather and Research Forecasting (WRF) model and estimated ZTDs through the processing of Global Navigation Satellite System (GNSS) data and evaluate the pixel-wise dependence structures of ZTDs over a study area with complex terrain in Central Europe. The results show asymmetry and nonlinearity in the statistical relationships, which justifies the application of Copula-based approaches compared to, e.g., scalar measures. We apply a Copula-based correction for generating GNSS-like ZTDs from purely WRF-derived estimates. Particularly the corrected time series in the alpine regions show improved Nash–Sutcliffe efficiency values when compared against GNSS-based ZTDs. The proposed approach is therefore highly suitable for analyzing statistical relationships and correcting model-based quantities, especially in complex terrain, and when the statistical relationships of the analyzed variables are unknown. Numéro de notice : A2021-007 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-020-01044-4 date de publication en ligne : 02/11/2020 En ligne : https://doi.org/10.1007/s10291-020-01044-4 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96297 [article]

Determination of precise Galileo orbits using combined GNSS and SLR observations / Grzegorz Bury in GPS solutions, vol 25 n° 1 (January 2021)  

Public [article]  inGPS solutions > vol 25 n° 1 (January 2021) . - n° 11 Titre : Determination of precise Galileo orbits using combined GNSS and SLR observations Type de document : Article/Communication Auteurs : Grzegorz Bury, Auteur ; Krzysztof Sosnica, Auteur ; Radoslaw Zajdel, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 11 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Techniques orbitales [Termes descripteurs IGN] données TLS (télémétrie) [Termes descripteurs IGN] Galileo [Termes descripteurs IGN] International Terrestrial Reference Frame [Termes descripteurs IGN] orbite précise [Termes descripteurs IGN] orbitographie [Termes descripteurs IGN] pondération [Termes descripteurs IGN] positionnement par GNSS Résumé : (auteur) Galileo satellites are equipped with laser retroreflector arrays for satellite laser ranging (SLR). In this study, we develop a methodology for the GNSS-SLR combination at the normal equation level with three different weighting strategies and evaluate the impact of laser observations on the determined Galileo orbits. We provide the optimum weighting scheme for precise orbit determination employing the co-location onboard Galileo. The combined GNSS-SLR solution diminishes the semimajor axis formal error by up to 62%, as well as reduces the dependency between values of formal errors and the elevation of the Sun above the orbital plane—the β angle. In the combined solution, the standard deviation of the SLR residuals decreases from 36.1 to 29.6 mm for Galileo-IOV satellites and |β|> 60°, when compared to GNSS-only solutions. Moreover, the bias of the Length-of-Day parameter is 20% lower for the combined solution when compared to the microwave one. As a result, the combination of GNSS and SLR observations provides promising results for future co-locations onboard the Galileo satellites for the orbit determination, realization of the terrestrial reference frames, and deriving geodetic parameters. Numéro de notice : A2021-008 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-020-01045-3 date de publication en ligne : 31/10/2020 En ligne : https://doi.org/10.1007/s10291-020-01045-3 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96298 [article]

Inferencing hourly traffic volume using data-driven machine learning and graph theory / Zhiyan Yi in Computers, Environment and Urban Systems, vol 85 (January 2021)  

Public [article]  inComputers, Environment and Urban Systems > vol 85 (January 2021) . - n° 101548 Titre : Inferencing hourly traffic volume using data-driven machine learning and graph theory Type de document : Article/Communication Auteurs : Zhiyan Yi, Auteur ; Xiaoyue Cathy Liu, Auteur ; Nikola Markovic, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 101548 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] apprentissage automatique [Termes descripteurs IGN] classification barycentrique [Termes descripteurs IGN] corrélation automatique de points homologues [Termes descripteurs IGN] échantillonnage de données [Termes descripteurs IGN] Extreme Gradient Machine [Termes descripteurs IGN] modèle de simulation [Termes descripteurs IGN] planification [Termes descripteurs IGN] théorie des graphes [Termes descripteurs IGN] trafic routier [Termes descripteurs IGN] Utah (Etas-Unis) Résumé : (auteur) Traffic volume is a critical piece of information in many applications, such as transportation long-range planning and traffic operation analysis. Effectively capturing traffic volumes on a network scale is beneficial to Transportation Systems Management & Operations (TSM&O). Yet it is impractical to install sensors to cover a large road network. To address this issue, spatial prediction techniques are widely performed to estimate traffic volumes at sites without sensors. In retrospect, most relevant studies resort to machine learning methods and treat each prediction location independently during the training process, ignoring the potential spatial dependency among them. This paper presents an innovative spatial prediction method of hourly traffic volume on a network scale. To achieve this, we applied a state-of-the-art tree ensemble model - extreme gradient boosting tree (XGBoost) - to handle the large-scale features and hourly traffic volume samples, due to the model's powerful scalability. Moreover, spatial dependency among road segments is taken into account in the proposed model using graph theory. Specifically, we created a traffic network graph leveraging probe trajectory data, and implemented a graph-based approach - breadth first search (BFS) - to search neighboring sites in this graph for computing spatial dependency. The proposed spatial dependency feature is subsequently incorporated as a new feature fed into XGBoost. The proposed model is tested on the road network in the state of Utah. Numerical results not only indicate high computational efficiency of the proposed model, but also demonstrate significant improvement in prediction accuracy of hourly traffic volume comparing with the benchmarked models. Numéro de notice : A2021-004 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2020.101548 date de publication en ligne : 24/09/2020 En ligne : https://doi.org/10.1016/j.compenvurbsys.2020.101548 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96271 [article]

Monitoring tree-crown scale autumn leaf phenology in a temperate forest with an integration of PlanetScope and drone remote sensing observations / Shengbiao Wu in ISPRS Journal of photogrammetry and remote sensing, vol 171 (January 2021)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 171 (January 2021) . - pp 36 - 48 Titre : Monitoring tree-crown scale autumn leaf phenology in a temperate forest with an integration of PlanetScope and drone remote sensing observations Type de document : Article/Communication Auteurs : Shengbiao Wu, Auteur ; Jing Wang, Auteur ; Zhengbing Yan, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 36 - 48 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] Chine [Termes descripteurs IGN] forêt tempérée [Termes descripteurs IGN] houppier [Termes descripteurs IGN] image captée par drone [Termes descripteurs IGN] image MODIS [Termes descripteurs IGN] image PlanetScope [Termes descripteurs IGN] phénologie [Termes descripteurs IGN] photosynthèse [Termes descripteurs IGN] série temporelle [Termes descripteurs IGN] surveillance forestière Résumé : (auteur) In temperate forests, autumn leaf phenology signals the end of leaf growing season and shows large variability across tree-crowns, which importantly mediates photosynthetic seasonality, hydrological regulation, and nutrient cycling of forest ecosystems. However, critical challenges remain with the monitoring of autumn leaf phenology at the tree-crown scale due to the lack of spatially explicit information for individual tree-crowns and high (spatial and temporal) resolution observations with nadir view. Recent availability of the PlanetScope constellation with a 3 m spatial resolution and near-daily nadir view coverage might help address these observational challenges, but remains underexplored. Here we developed an integration of PlanetScope with drone observations for improved monitoring of crown-scale autumn leaf phenology in a temperate forest in Northeast China. This integration includes: 1) visual identification of individual tree-crowns (and species) from drone observations; 2) extraction of time series of PlanetScope vegetation indices (VIs) for each identified tree-crown; 3) derivation of three metrics of autumn leaf phenology from the extracted VI time series, including the start of fall (SOF), middle of fall (MOF), and end of fall (EOF); and 4) accuracy assessments of the PlanetScope-derived phenology metrics with reference from local phenocams. Our results show that (1) the PlanetScope-drone integration captures large inter-crown phenological variations, with a range of 28 days, 25 days, and 30 days for SOF, MOF, and EOF, respectively, (2) the extracted crown-level phenology metrics strongly agree with those derived from local phenocams, with a root-mean-square-error (RMSE) of 4.1 days, 3.0 days and 5.4 days for SOF, MOF, and EOF, respectively, and (3) PlanetScope maps large variations in autumn leaf phenology over the entire forest landscape with spatially explicit information. These results demonstrate the ability of our proposed method in monitoring the large spatial heterogeneity of crown-scale autumn leaf phenology in the temperate forest, suggesting the potential of using high-resolution satellites to advance crown-scale phenology studies over large geographical areas. Numéro de notice : A2021-011 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.10.017 date de publication en ligne : 13/11/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.10.017 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96305 [article]

Competition overrides climate as trigger of growth decline in a mixed Fagaceae Mediterranean rear-edge forest / Alvaro Rubio-Cuadrado in Annals of Forest Science [en ligne], vol 77 n° 4 (December 2020)  

Public [article]  inAnnals of Forest Science [en ligne] > vol 77 n° 4 (December 2020) . - 18 p. Titre : Competition overrides climate as trigger of growth decline in a mixed Fagaceae Mediterranean rear-edge forest Type de document : Article/Communication Auteurs : Alvaro Rubio-Cuadrado, Auteur ; J. Julio Camarero, Auteur ; Guillermo G. Gordaliza, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 18 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] analyse diachronique [Termes descripteurs IGN] croissance végétale [Termes descripteurs IGN] dendrochronologie [Termes descripteurs IGN] densité de la végétation [Termes descripteurs IGN] dynamique de la végétation [Termes descripteurs IGN] exploitation forestière [Termes descripteurs IGN] fagaceae [Termes descripteurs IGN] Fagus sylvatica [Termes descripteurs IGN] forêt méditerranéenne [Termes descripteurs IGN] gestion forestière [Termes descripteurs IGN] modèle de croissance [Termes descripteurs IGN] peuplement mélangé [Termes descripteurs IGN] quercus pyrenaica [Termes descripteurs IGN] quercus sessiliflora [Termes descripteurs IGN] structure d'un peuplement forestier [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Key message: In recent decades, there has been a decline in growth in a rear-edge broadleaf forest of Fagus sylvatica , Quercus petraea , and Quercus pyrenaica . Although temperatures have been rising due to climate change, the observed decline in growth was mainly attributed to increased density and competition between trees since the cessation of traditional uses such as logging in the 1960s. Context: In recent decades, two major factors have influenced tree growth in many forests: climate warming, which is associated with aridification and negative growth trends in many Mediterranean forests, and abandonment of forest management, resulting from forest policy in conjunction with rural depopulation in Europe, often leading to an increase in competition and a decrease in growth. Aims: Here, we study the growth trends in a mixed forest of Fagus sylvatica, Quercus petraea, and Quercus pyrenaica, where the abandonment of traditional uses in the 1960s has been followed by an increase in tree density. In this forest, both F. sylvatica and Q. petraea reach their south-westernmost limits of distribution. Methods: Using dendrochronological methods and growth modeling, we assess the importance of climate warming on the shifts in competitive growth advantage of these three coexisting tree species and the relative importance of climate and competition on growth trends. Results: Q. petraea and especially F. sylvatica showed a favorable evolution of their competitive capacity, despite the increase in temperatures that has occurred in the area in recent decades. F. sylvatica presented the lowest sensitivity to climate. Conclusion: Under the current climate and forest structure conditions, competition is the most limiting factor on tree growth for the two oak species. Numéro de notice : A2020-661 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-01004-5 date de publication en ligne : 01/10/2020 En ligne : https://doi.org/10.1007/s13595-020-01004-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96135 [article]

Improving aboveground biomass estimates by taking into account density variations between tree components / Antoine Billard in Annals of Forest Science [en ligne], vol 77 n° 4 (December 2020)  

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Inclusion of GPS clock estimates for satellites Sentinel-3A/3B in DORIS geodetic solutions / Petr Štěpánek in Journal of geodesy, vol 94 n° 12 (December 2020)  

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Large-scale stochastic flood hazard analysis applied to the Po River / A. Curran in Natural Hazards, vol 104 n° 3 (December 2020)  

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Mapping forest tree species in high resolution UAV-based RGB-imagery by means of convolutional neural networks / Felix Schiefer in ISPRS Journal of photogrammetry and remote sensing, vol 170 (December 2020)  

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MS-RRFSegNetMultiscale regional relation feature segmentation network for semantic segmentation of urban scene point clouds / Haifeng Luo in IEEE Transactions on geoscience and remote sensing, Vol 58 n° 12 (December 2020)  

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Nonlocal graph convolutional networks for hyperspectral image classification / Lichao Mou in IEEE Transactions on geoscience and remote sensing, Vol 58 n° 12 (December 2020)  

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Quantification of cotton water consumption by remote sensing / Jefferson Vieira José in Geocarto international, vol 35 n° 16 ([01/12/2020])  

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Reference system origin and scale realization within the future GNSS constellation “Kepler” / Susanne Glaser in Journal of geodesy, vol 94 n° 12 (December 2020)  

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Remote sensing in urban planning: Contributions towards ecologically sound policies? / Thilo Wellmann in Landscape and Urban Planning, vol 204 (December 2020)  

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Semantic trajectory segmentation based on change-point detection and ontology / Yuan Gao in International journal of geographical information science IJGIS, vol 34 n° 12 (December 2020)  

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