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scientifique

How geographic and climatic factors affect the adaptation of Douglas-fir provenances to the temperate continental climate zone in Europe / Marzena Niemczyk in European Journal of Forest Research, vol 140 n° 6 (December 2021)  

Public [article]  inEuropean Journal of Forest Research > vol 140 n° 6 (December 2021) . - pp 1341 - 1361 Titre : How geographic and climatic factors affect the adaptation of Douglas-fir provenances to the temperate continental climate zone in Europe Type de document : Article/Communication Auteurs : Marzena Niemczyk, Auteur ; Daniel J. Chmura, Auteur ; Jarosław Socha, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1341 - 1361 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] adaptation (biologie) [Termes IGN] Amérique du nord [Termes IGN] analyse de variance [Termes IGN] analyse diachronique [Termes IGN] climat tempéré [Termes IGN] croissance des arbres [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] gelée [Termes IGN] graine [Termes IGN] modélisation de la forêt [Termes IGN] Pologne [Termes IGN] Pseudotsuga menziesii [Termes IGN] régénération (sylviculture) [Termes IGN] sécheresse [Termes IGN] variation saisonnière [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) The contribution of Douglas-fir (Df) to European forests is likely to increase as the species is a potential adaptation option to climate change. In this study, we investigated growth and survival of Df seed sources to fill a knowledge gap regarding recommendations for the future use of Df provenances in Poland. Our experimental test site represents the most continental climate among all Df trials installed in the IUFRO 1966–67 test series in Europe. At this unique single site, we evaluated the performance of 46 Df provenances from North America, and nine local landraces of unknown origin. Repeated measurements of tree diameter, height, and volume were analysed, to age 48, representing integrated responses to geographic and climatic conditions. Significant variation in survival and productivity-related traits were found, with the interior Df provenances performing best, in contrast to previous European reports. The higher survivability and volume of the interior provenances resulted from their superior frost resistance. The low precipitation seasonality at the location of seed origin provided an additional advantage to the trees at the test site. Geographic and climatic factors of seed origin explained most of the variation in productivity (77 and 64%, respectively). The tested landraces exhibited diverse performance, implying that naturalized local seed sources in Poland need improvement and perhaps enrichment with new genetic material from North America, while considering geography and climate. Assisted migration programs should consider the limitations imposed by both frost and drought events in guiding future Df selections for continental climates. Further field testing, early greenhouse screening and DNA testing are also recommended. Numéro de notice : A2021-837 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s10342-021-01398-5 Date de publication en ligne : 22/07/2021 En ligne : https://doi.org/10.1007/s10342-021-01398-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99017 [article]

Geoid determination through the combined least-squares adjustment of GNSS/levelling/gravity networks – a case study in Linyi, China / Dongmei Guo in Survey review, Vol 53 n° 381 (November 2021)  

Public [article]  inSurvey review > Vol 53 n° 381 (November 2021) . - pp 504 - 512 Titre : Geoid determination through the combined least-squares adjustment of GNSS/levelling/gravity networks – a case study in Linyi, China Type de document : Article/Communication Auteurs : Dongmei Guo, Auteur ; Zhixin Xue, Auteur Année de publication : 2021 Article en page(s) : pp 504 - 512 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique [Termes IGN] analyse de variance [Termes IGN] Chine [Termes IGN] compensation par moindres carrés [Termes IGN] données GNSS [Termes IGN] géoïde altimétrique [Termes IGN] géoïde local [Termes IGN] levé gravimétrique [Termes IGN] méthode des moindres carrés [Termes IGN] modèle stochastique [Termes IGN] pondération [Termes IGN] réseau de nivellement [Termes IGN] réseau gravimétrique Résumé : (Auteur) A detailed discussion of the adjustment problems used to combine GNSS/levelling/gravity network data is provided in this paper. The two primary problems inherent to heterogeneous data networks, namely, parametric models that describe the datums and systematic distortions among the available data sets and stochastic models that describe the observational residuals, are described. For parametric models, a relationship between the transformation parameters and the effects of datums and systematic distortions inherent among different height data types is established based on a least squares criterion. For stochastic models, the stochastic errors in GNSS/levelling/gravity data are evaluated, and a Helmert variance component estimation approach is introduced to refine weighting models. Finally, the proposed model is applied to determine the hybrid geoid in Linyi, China. The numerical results validate the capability and effectiveness of the proposed combined adjustment technique for hybrid geoid computations, revealing an achievable external accuracy of ±1.22 cm compared with GNSS/levelling measurements, which can be increased by 0.44 cm compared with classic adjustments of GNSS/levelling/geoid height data. Numéro de notice : A2021-913 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2020.1842642 Date de publication en ligne : 16/11/2020 En ligne : https://doi.org/10.1080/00396265.2020.1842642 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99316 [article]

A constrained extended Kalman filter based on LS-VCE formulated by condition equations with prediction of cross-covariances / Vahid Mahboub in Survey review, Vol 53 n° 380 (September 2021)  

Public [article]  inSurvey review > Vol 53 n° 380 (September 2021) . - pp 422 - 435 Titre : A constrained extended Kalman filter based on LS-VCE formulated by condition equations with prediction of cross-covariances Type de document : Article/Communication Auteurs : Vahid Mahboub, Auteur ; Narges Fatholahi, Auteur Année de publication : 2021 Article en page(s) : pp 422 - 435 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] algorithme de filtrage [Termes IGN] analyse de variance [Termes IGN] filtre adaptatif [Termes IGN] filtre de Kalman [Termes IGN] matrice de covariance [Termes IGN] méthode des moindres carrés [Termes IGN] modèle non linéaire [Termes IGN] modèle stochastique Résumé : (auteur) A constrained extended Kalman filter (CEKF) based on least-squares variance component estimation (LS-VCE) is generally developed by condition equations since the proper prediction of dispersion matrices is one of the main bottlenecks in the KF algorithms. Here we investigate four problems which have not been simultaneously considered yet. These problems are examination of non-linearty of dynamic model, VCE, general non-linear state constraints and fairly general stochastic model. Although a few contributions proposed some adaptive KF in particular based on Helmert’s VCE method, they developed their filters for special problems with some restrictive conditions such as independence of all variables and/or linearity of the dynamic model. Also some of these filters did not apply VCE methods to all parts of the dynamic model. In this contribution, we try to overcome all of these restrictions. Moreover, LS-VCE method gives some added advantages over other VCE methods. First the new formulation of CEKF is developed by condition equations with prediction of all possible cross-covariances as algorithm 1. Then the LS-VCE method is applied to it after some modifications which results in an adaptive constrained extended Kalman filter (ACEKF) as the second algorithm. Numéro de notice : A2021-636 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2020.1814030 Date de publication en ligne : 07/09/2020 En ligne : https://doi.org/10.1080/00396265.2020.1814030 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98300 [article]

Estimation of biomass increase and CUE at a young temperate scots pine stand concerning drought occurrence by combining eddy covariance and biometric methods / Paulina Dukat in Forests, vol 12 n° 7 (July 2021)  

Public [article]  inForests > vol 12 n° 7 (July 2021) . - n° 867 Titre : Estimation of biomass increase and CUE at a young temperate scots pine stand concerning drought occurrence by combining eddy covariance and biometric methods Type de document : Article/Communication Auteurs : Paulina Dukat, Auteur ; Klaudia Ziemblińska, Auteur ; Janusz Olejnik, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 867 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] biomasse forestière [Termes IGN] changement climatique [Termes IGN] covariance [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] dioxyde de carbone [Termes IGN] indice de végétation [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] Pinus sylvestris [Termes IGN] Pologne [Termes IGN] production primaire brute [Termes IGN] puits de carbone [Termes IGN] sécheresse [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) The accurate estimation of an increase in forest stand biomass has remained a challenge. Traditionally, in situ measurements are done by inventorying a number of trees and their biometric parameters such as diameter at the breast height (DBH) and height; sometimes these are complemented by carbon (C) content studies. Here we present the estimation of net primary productivity (NPP) over a two years period (2019–2020) at a 25-year-old Scots pine stand. Research was based on allometric equations made by direct biomass analysis (tree extraction) and carbon content estimations in individual components of sampled trees, combined with a series of stem diameter increments recorded by a network of band dendrometers. Site-specific allometric equations were obtained using two different approaches: using the whole tree biomass vs DBH (M1), and total dry biomass-derived as a sum of the results from individual tree components’ biomass vs DBH (M2). Moreover, equations for similar forest stands from the literature were used for comparison. Gross primary productivity (GPP) estimated from the eddy-covariance measurements allowed the calculation of carbon use efficiency (CUE = NPP/GPP). The two investigated years differed in terms of the sum and patterns of precipitation distribution, with a moderately dry year of 2019 that followed the extremely dry 2018, and the relatively average year of 2020. As expected, a higher increase in biomass was recorded in 2020 compared to 2019, as determined by both allometric equations based on in situ and literature data. For the former approach, annual NPP estimates reached ca. 2.0–2.1 t C ha−1 in 2019 and 2.6–2.7 t C ha−1 in 2020 depending on the “in situ equations” (M1-M2) used, while literature-derived equations for the same site resulted in NPP values ca. 20–30% lower. CUE was higher in 2020, which resulted from a higher NPP total than in 2019, with lower summer and spring GPP in 2020. However, the CUE values were lower than those reported in the literature for comparable temperate forest stands. A thorough analysis of the low CUE value would require a full interpretation of interrelated physiological responses to extreme conditions. Numéro de notice : A2021-641 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.3390/f12070867 Date de publication en ligne : 30/06/2021 En ligne : https://doi.org/10.3390/f12070867 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98313 [article]

Detecting ground deformation in the built environment using sparse satellite InSAR data with a convolutional neural network / Nantheera Anantrasirichai in IEEE Transactions on geoscience and remote sensing, vol 59 n° 4 (April 2021)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 59 n° 4 (April 2021) . - pp 2940 - 2950 Titre : Detecting ground deformation in the built environment using sparse satellite InSAR data with a convolutional neural network Type de document : Article/Communication Auteurs : Nantheera Anantrasirichai, Auteur ; Juliet Biggs, Auteur ; Krisztina Kelevitz, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 2940 - 2950 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] apprentissage automatique [Termes IGN] bati [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] complétion [Termes IGN] covariance [Termes IGN] déformation de la croute terrestre [Termes IGN] données d'apprentissage [Termes IGN] effet atmosphérique [Termes IGN] image radar moirée [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] interpolation spatiale [Termes IGN] matrice [Termes IGN] optimisation (mathématiques) [Termes IGN] représentation parcimonieuse [Termes IGN] Royaume-Uni [Termes IGN] zone urbaine Résumé : (auteur) The large volumes of Sentinel-1 data produced over Europe are being used to develop pan-national ground motion services. However, simple analysis techniques like thresholding cannot detect and classify complex deformation signals reliably making providing usable information to a broad range of nonexpert stakeholders a challenge. Here, we explore the applicability of deep learning approaches by adapting a pretrained convolutional neural network (CNN) to detect deformation in a national-scale velocity field. For our proof-of-concept, we focus on the U.K. where previously identified deformation is associated with coal-mining, ground water withdrawal, landslides, and tunneling. The sparsity of measurement points and the presence of spike noise make this a challenging application for deep learning networks, which involve calculations of the spatial convolution between images. Moreover, insufficient ground truth data exist to construct a balanced training data set, and the deformation signals are slower and more localized than in previous applications. We propose three enhancement methods to tackle these problems: 1) spatial interpolation with modified matrix completion; 2) a synthetic training data set based on the characteristics of the real U.K. velocity map; and 3) enhanced overwrapping techniques. Using velocity maps spanning 2015–2019, our framework detects several areas of coal mining subsidence, uplift due to dewatering, slate quarries, landslides, and tunnel engineering works. The results demonstrate the potential applicability of the proposed framework to the development of automated ground motion analysis systems. Numéro de notice : A2021-283 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s12518-020-00323-6 Date de publication en ligne : 31/08/2020 En ligne : https://doi.org/10.1007/s12518-020-00323-6 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97391 [article]

Forest fragmentation assessment using field-based sampling data from forest inventories / Habib Ramezani in Scandinavian journal of forest research, vol 36 n° 4 ([01/04/2021])  

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The influence of urban form on the spatiotemporal variations in land surface temperature in an arid coastal city / Irshad Mir Parvez in Geocarto international, vol 36 n° 6 ([30/03/2021])  

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A practical method for calculating reliable integer float estimator in GNSS precise positioning / Xianwen Yu in Survey review, Vol 53 n° 377 (February 2021)  

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Adaptive filtering / Wenping Cao (2021)  

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Initialization methods of convolutional neural networks for detection of image manipulations / Ivan Castillo Camacho (2021)  

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A new segmentation method for the homogenisation of GNSS-derived IWV time-series / Annarosa Quarello (2021)  

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A review of image fusion techniques for pan-sharpening of high-resolution satellite imagery / Farzaneh Dadrass Javan in ISPRS Journal of photogrammetry and remote sensing, vol 171 (January 2021)  

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Stochastic models for geodesy and geoinformation science / Frank Neitzel (2021)    

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Une généralisation de la méthode de partage des poids dans le cas où la base de sondage est continue / Philippe Brion (2021)

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Error propagation in regional geoid computation using spherical splines, least-squares collocation, and Stokes’s formula / Vegard Ophaug in Journal of geodesy, vol 94 n° 12 (December 2020)  

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