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Estimation of the F2 generation segregation variance and relationships among growth, frost damage, and bud break in coastal Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) wide-crosses / Andy Benowicz in Annals of Forest Science [en ligne], Vol 77 n° 2 (June 2020)  

Public [article]  inAnnals of Forest Science [en ligne] > Vol 77 n° 2 (June 2020) . - 13 p. Titre : Estimation of the F2 generation segregation variance and relationships among growth, frost damage, and bud break in coastal Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) wide-crosses Type de document : Article/Communication Auteurs : Andy Benowicz, Auteur ; Michael U. Stoehr, Auteur ; Andreas Hamann, Auteur ; Alvin D. Yanchuk, Auteur Année de publication : 2020 Article en page(s) : 13 p. Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] analyse de variance [Termes descripteurs IGN] croissance végétale [Termes descripteurs IGN] gelée [Termes descripteurs IGN] pseudotsuga menziesii [Vedettes matières IGN] Inventaire forestier Résumé : (Auteur) Creation of second generation Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) hybrids based on parents from geographically distant locations did not appreciably increase variance in height, frost damage and bud break. New and favorable trait combinations between height and the two adaptive traits were found in the F2 populations. Increased genetic variance and new trait combinations can improve selection efficiency in terms of selection response and increased adaptability. This project tested a novel method for generating higher genetic variance and new trait combinations in Douglas-fir populations. Numéro de notice : A2020-170 Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-0925-9 date de publication en ligne : 23/03/2020 En ligne : https://doi.org/10.1007/s13595-020-0925-9 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94859 [article]

Accounting for spatiotemporal correlations of GNSS coordinate time series to estimate station velocities / Clément Benoist in Journal of geodynamics, vol 135 (April 2020)  

Public [article]  inJournal of geodynamics > vol 135 (April 2020) . - n° 101693 Titre : Accounting for spatiotemporal correlations of GNSS coordinate time series to estimate station velocities Type de document : Article/Communication Auteurs : Clément Benoist , Auteur ; Xavier Collilieux , Auteur ; Paul Rebischung , Auteur ; Zuheir Altamimi , Auteur ; Olivier Jamet , Auteur ; Laurent Métivier , Auteur ; Kristel Chanard , Auteur ; Liliane Bel, Auteur Année de publication : 2020 Projets : GEODESIE / Coulot, David Article en page(s) : n° 101693 Note générale : bibliographie This study contributes to the IdEx Université de Paris ANR-18-IDEX-0001. It is partly supported by the Agence Nationale de la Recherche (ANR) project « Geodesie » ANR-16-CE01-0001. This is IPGP contribution number 4120. Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes de référence et réseaux [Termes descripteurs IGN] corrélation [Termes descripteurs IGN] covariance [Termes descripteurs IGN] données spatiotemporelles [Termes descripteurs IGN] repère de référence terrestre conventionnel [Termes descripteurs IGN] série temporelle [Termes descripteurs IGN] vitesse Résumé : (auteur) It is well known that GNSS permanent station coordinate time series exhibit time-correlated noise. Spatial correlations between coordinate time series of nearby stations are also long-established and generally handled by means of spatial filtering techniques. Accounting for both the temporal and spatial correlations of the noise via a spatiotemporal covariance model is however not yet a common practice. We demonstrate in this paper the interest of using such a spatiotemporal covariance model of the stochastic variations in GNSS time series in order to estimate long-term station coordinates and especially velocities. We provide a methodology to rigorously assess the covariances between horizontal coordinate variations and use it to derive a simple exponential spatiotemporal covariance model for the stochastic variations in the IGS repro2 station coordinate time series. We then use this model to estimate station velocities for two selected datasets of 10 time series in Europe and 11 time series in the USA. We show that coordinate prediction as well as velocity determination from short time series are improved when using this spatiotemporal model, as compared with the case where spatiotemporal correlations are ignored. Numéro de notice : A2020-460 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jog.2020.101693 date de publication en ligne : 13/01/2020 En ligne : https://doi.org/10.1016/j.jog.2020.101693 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95385 [article]

Monitoring of landslide activity at the Sirobagarh landslide, Uttarakhand, India, using LiDAR, SAR interferometry and geodetic surveys / Ashutosh Tiwari in Geocarto international, vol 35 n° 5 ([01/04/2020])  

Public [article]  inGeocarto international > vol 35 n° 5 [01/04/2020] . - pp 535 - 558 Titre : Monitoring of landslide activity at the Sirobagarh landslide, Uttarakhand, India, using LiDAR, SAR interferometry and geodetic surveys Type de document : Article/Communication Auteurs : Ashutosh Tiwari, Auteur ; Avadh Bihari Narayan, Auteur ; Ramji Dwivedi, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 535 - 558 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] arpentage [Termes descripteurs IGN] corrélation croisée maximale [Termes descripteurs IGN] covariance [Termes descripteurs IGN] données GNSS [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] effondrement de terrain [Termes descripteurs IGN] escarpement [Termes descripteurs IGN] image Sentinel-SAR [Termes descripteurs IGN] Inde [Termes descripteurs IGN] interféromètrie par radar à antenne synthétique [Termes descripteurs IGN] modèle numérique de surface [Termes descripteurs IGN] précipitation [Termes descripteurs IGN] surveillance géologique [Termes descripteurs IGN] tachéomètre électronique robotisé Résumé : (auteur) A robust geodetic framework comprising Terrestrial Laser Scanner (TLS), Global Navigation Satellite Systems (GNSS), Robotic Total Station (RTS) and Multi-temporal InSAR (MT-InSAR) was employed first in India to investigate a landslide-prone Sirobagarh region, Uttarakhand, at different spatial extents, and to evaluate the relationship amongst the displacement estimates obtained from the applied surveying techniques. TLS derived digital elevation models indicated displacements >5 m on the landslide upper scarp. GNSS- and RTS-based observations showed horizontal movements towards the Alaknanda river in the landslide slope direction (maximum values: 0.1305 and 0.045 m, respectively), and downward vertical motion (largest subsidence magnitude: −2.1315 and −0.030 m, respectively). MT-InSAR processing of Sentinel-1a images identified 21071 measurement pixels, highlighting subsidence around the landslide (mean velocity range: −0.110 to 0.008 m/year). Analysis of displacement vectors using vector equality, cross-covariance, cross-correlation and principal component analysis reveals that GNSS vertical displacement estimates were partially correlated with MT-InSAR measurements (correlated for epoch difference 2–3), whereas there was good cross-correlation between MT-InSAR and LiDAR observations throughout. The displacement estimates and their analyses evident unstable movement of the landslide scarp occurring due to debris flow and rainfall, and a relatively moderate subsidence activity in the surrounding areas lying in the landslide zone. Numéro de notice : A2020-144 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1524516 date de publication en ligne : 23/10/2018 En ligne : https://doi.org/10.1080/10106049.2018.1524516 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94770 [article]

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Predictive mapping with small field sample data using semi‐supervised machine learning / Fei Du in Transactions in GIS, Vol 24 n° 2 (April 2020)  

Public [article]  inTransactions in GIS > Vol 24 n° 2 (April 2020) . - pp 315 - 331 Titre : Predictive mapping with small field sample data using semi‐supervised machine learning Type de document : Article/Communication Auteurs : Fei Du, Auteur ; A - Xing Zhu, Auteur ; Jing Liu, Auteur ; Lin Yang, Auteur Année de publication : 2020 Article en page(s) : pp 315 - 331 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] apprentissage semi-dirigé [Termes descripteurs IGN] covariance [Termes descripteurs IGN] échantillon [Termes descripteurs IGN] modèle de simulation [Termes descripteurs IGN] représentation cartographique Résumé : (Auteur) Existing predictive mapping methods usually require a large number of field samples with good representativeness as input to build reliable predictive models. In mapping practice, however, we often face situations when only small sample data are available. In this article, we present a semi‐supervised machine learning approach for predictive mapping in which the natural aggregation (clustering) patterns of environmental covariate data are used to supplement limited samples in prediction. This approach was applied to two soil mapping case studies. Compared with field sample only approaches (decision trees, logistic regression, and support vector machines), maps using the proposed approach can better capture the spatial variation of soil types and achieve higher accuracy with limited samples. A cross validation shows further that the proposed approach is less sensitive to the specific field sample set used and thus more robust when field sample data are small. Numéro de notice : A2020-174 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12598 date de publication en ligne : 04/12/2019 En ligne : https://doi.org/10.1111/tgis.12598 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94900 [article]

A single-receiver geometry-free approach to stochastic modeling of multi-frequency GNSS observables / Baocheng Zhang in Journal of geodesy, vol 94 n°4 (April 2020)  

Public [article]  inJournal of geodesy > vol 94 n°4 (April 2020) Titre : A single-receiver geometry-free approach to stochastic modeling of multi-frequency GNSS observables Type de document : Article/Communication Auteurs : Baocheng Zhang, Auteur ; Pengyu Hou, Auteur ; Teng Liu, Auteur ; Yunbin Yuan, Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes descripteurs IGN] analyse de variance [Termes descripteurs IGN] corrélation croisée normalisée [Termes descripteurs IGN] corrélation temporelle [Termes descripteurs IGN] fréquence multiple [Termes descripteurs IGN] méthode des moindres carrés [Termes descripteurs IGN] méthode robuste [Termes descripteurs IGN] modèle stochastique [Termes descripteurs IGN] positionnement ponctuel précis [Termes descripteurs IGN] récepteur [Termes descripteurs IGN] traitement de données GNSS [Termes descripteurs IGN] trajet multiple Résumé : (auteur) The proper choice of stochastic model is of great importance to global navigation satellite system (GNSS) data processing. Whereas extensive investigations into stochastic modeling are mainly based on the relative (or differential) method employing zero and/or short baselines, this work proposes an absolute method that relies upon a stand-alone receiver and works by applying the least-squares variance component estimation to the geometry-free functional model, thus facilitating the characterization of stochastic properties of multi-frequency GNSS observables at the undifferenced level. In developing the absolute method, special care has been taken of the code multipath effects by introducing ambiguity-like parameters to the code observation equations. By means of both the relative and absolute methods, we characterize the precision, cross and time correlation of the code and phase observables of two newly emerging constellations, namely the Chinese BDS and the European Galileo, collected by a variety of receivers of different types at multiple frequencies. Our first finding is that so far as the precision is concerned, the absolute method yields nearly the same numerical values as those derived by the zero-baseline-based relative method. However, the two methods give contradictory results with regard to the cross correlation, which is found (not) to occur between BDS phase observables when use has been made of the relative (absolute) method. Our explanation to this discrepancy is that the cross correlation found in the relative method originates from the parts (antenna, cable, low noise amplifier) shared by two receivers creating a zero baseline. The time correlation is only of significance when the multipath effects are present, as is the case with the short-baseline-based relative method; this correlation turns out to be largely weaker (or ideally absent) in the absolute (or zero-baseline-based relative) method. Moreover, with the absolute method, the stochastic properties determined for two receivers of the same type but subject to different multipath effects are virtually the same. We take this as a convincing evidence that the absolute method is robust against multipath effects. Hence, the absolute method proposed in the present work represents a promising complement to the relative method and appears to be particularly beneficial to GNSS positioning, navigation and timing technologies based on the undifferenced observables, typically the precise point positioning. Numéro de notice : A2020-160 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-020-01366-8 date de publication en ligne : 09/03/2020 En ligne : https://doi.org/10.1007/s00190-020-01366-8 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94817 [article]

Estimation of variance and spatial correlation width for fine-scale measurement error in digital elevation model / Mikhail L. Uss in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)  

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A breakpoint detection in the mean model with heterogeneous variance on fixed time-intervals / Olivier Bock in Statistics and Computing, vol 29 n° 1 (February 2020)  

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Flowering acceleration in native Brazilian tree species for genetic conservation and breeding / Gleidson Guilherme Caldas Mende in Annals of forest research, Vol 63 n° 1 (January - June 2020)  

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A new segmentation method for the homogenisation of GNSS-derived IWV time-series / Annarosa Quarello (2020)  

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Combination of GRACE monthly gravity fields on the normal equation level / Ulrich Meyer in Journal of geodesy, vol 93 n° 9 (September 2019)  

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The Iranian height datum offset from the GBVP solution and spirit-leveling/gravimetry data / Amir Ebadi in Journal of geodesy, vol 93 n° 8 (August 2019)  

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Genetic diversity and structure of Silver fir (Abies alba Mill.) at the south-eastern limit of its distribution range / Maria Teodosiu in Annals of forest research, vol 62 n° 2 (June - December 2019)  

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Helmert-VCE-aided fast-WTLS approach for global ionospheric VTEC modelling using data from GNSS, satellite altimetry and radio occultation / Andong Hu in Journal of geodesy, vol 93 n°6 (June 2019)  

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Seasonal pattern in time series of variances of GPS residual errors Anova estimates / Darko Anđić in Geodetski vestnik, vol 63 n° 2 (June - August 2019)  

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Coastline extraction from SAR images using robust ridge tracing / Dailiang Wang in Marine geodesy, vol 42 n° 3 (May 2019)  

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