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A meta-analysis of changes in soil organic carbon stocks after afforestation with deciduous broadleaved, sempervirent broadleaved, and conifer tree species / Guolong Hou 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) . - 13 p. Titre : A meta-analysis of changes in soil organic carbon stocks after afforestation with deciduous broadleaved, sempervirent broadleaved, and conifer tree species Type de document : Article/Communication Auteurs : Guolong Hou, Auteur ; Claudio O. Delang, Auteur ; Xixi Lu, Auteur ; Lei Gao, Auteur Année de publication : 2020 Article en page(s) : 13 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] afforestation [Termes descripteurs IGN] arbre caducifolié [Termes descripteurs IGN] arbre sempervirent [Termes descripteurs IGN] boisement artificiel [Termes descripteurs IGN] carbone [Termes descripteurs IGN] feuillu [Termes descripteurs IGN] pinophyta [Vedettes matières IGN] Ecologie forestière Résumé : (auteur) Key message: Different tree species have dissimilar capacities to sequester soil organic carbon (SOC). Deciduous broadleaved trees show the most stable increase in SOC stock after afforestation than other tree species, while sempervirent conifer trees show the lowest rate of SOC stock change. Sempervirent broadleaved trees show the greatest increase in SOC stock 20 years after afforestation. Context: The rate at which soil organic carbon (SOC) stock changes after afforestation varies considerably with the tree species. A better understanding of the role of tree species in SOC change dynamic is needed to evaluate the SOC sequestration potential of afforestation programs. Aims: The aim of this paper is to identify the dissimilar rates at which different tree species sequester SOC, following afforestation. Methods: We complete a meta-analysis with 544 data points from 261 sites in 90 papers. We group tree species into decidious broadleved, sempervirent broadleaved and sempervirent conifer. We use standardization and/or extrapolation methods to standardize soil depths. Statistical analysis test the main effects of tree species and their interactions with previous land use and plantation age on SOC stock change after afforestation. Results: Deciduous broadleaved trees show a stable increase in SOC stock, and are especially suited for afforestation of grassland or soils with high initial SOC. Sempervirent broadleaved afforestation results in loss of SOC stock in young stands, but greater SOC stock in mature stands. Sempervirent conifer trees show the lowest rate of SOC stock change, but are suitable for nutrient-poor soil. Conclusion: The results emphasize the importance of considering tree species when estimating SOC stock change, in particular when carbon sequestration is an objective of afforestation programs. Numéro de notice : A2020-590 Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-00997-3 date de publication en ligne : 25/09/2020 En ligne : https://doi.org/10.1007/s13595-020-00997-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95921 [article]

Recent growth trends of conifers across Western Europe are controlled by thermal and water constraints and favored by forest heterogeneity / Clémentine Ols in Science of the total environment, vol 742 ([10/11/2020])  

Public [article]  inScience of the total environment > vol 742 [10/11/2020] . - n° 140453 Titre : Recent growth trends of conifers across Western Europe are controlled by thermal and water constraints and favored by forest heterogeneity Type de document : Article/Communication Auteurs : Clémentine Ols , Auteur ; Jean-Christophe Hervé , Auteur ; Jean-Daniel Bontemps , Auteur Année de publication : 2020 Article en page(s) : n° 140453 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] changement climatique [Termes descripteurs IGN] croissance végétale [Termes descripteurs IGN] inventaire forestier national (données France) [Termes descripteurs IGN] modèle de croissance [Termes descripteurs IGN] pinophyta [Termes descripteurs IGN] surveillance forestière [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Tree growing conditions are changing rapidly in the face of climate change. Capturing tree-growth response to such changes across environmental contexts and tree species calls for a continuous forest monitoring over space. Based on >10,000 tree-ring measurements sampled across the systematic grid of the continuous French national forest inventory (NFI) over the 2006–2016 period, we evaluated the radial growth trends of eight conifer tree species prevalent in European forests across their native and introduced ranges and various bioclimatic contexts (n = 16 forest systems). For each forest system, radial increments were filtered out from tree, plot, soil and climatic normal influences to isolate environment-driven growth signals and quantify residual time-series. Associated growth trends across forest systems were then confronted against environmental variables (e.g. short-term averages and trends in seasonal climate). Trends for a given species were systematically more positive in cooler contexts (higher elevations or northern distribution margins) than in warmer contexts (plains). Decreases and increases in precipitation regimes were found to be associated with negative and positive tree growth trends, respectively. Remarkably, positive growth trends were mainly observed for native forest systems (7/9) and negative trends for introduced systems (5/7). Native forests showed a more heterogeneous forest structure as compared to introduced forests that, in line with observed positive dependence of tree growth trends onto both water availability and forest heterogeneity, appears to modulate the competitive pressure on water resource with ongoing summer maximum temperature increase. Over a short annually-resolved study period, we were able to capture tree growth responses coherent with climate change across diverse forest ecosystems. With ongoing accumulation of data, the continuous French NFI hence arises as powerful support to monitoring climate change effects on forests. Numéro de notice : A2020-509 Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.scitotenv.2020.140453 date de publication en ligne : 23/06/2020 En ligne : https://doi.org/10.1016/j.scitotenv.2020.140453 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95767 [article]

An advanced residual error model for tropospheric delay estimation / Szabolcs Rózsa in GPS solutions, Vol 24 n° 4 (October 2020)  

Public [article]  inGPS solutions > Vol 24 n° 4 (October 2020) . - 15 p. Titre : An advanced residual error model for tropospheric delay estimation Type de document : Article/Communication Auteurs : Szabolcs Rózsa, Auteur ; Bence Ambrus, Auteur ; Ildiko Juni, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 15 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes descripteurs IGN] erreur de positionnement [Termes descripteurs IGN] modèle d'erreur [Termes descripteurs IGN] modèle météorologique [Termes descripteurs IGN] perturbation ionosphérique [Termes descripteurs IGN] résidu [Termes descripteurs IGN] retard troposphérique [Termes descripteurs IGN] série temporelle Résumé : (auteur) Global navigation satellite systems (GNSS) are widely used for safety-of-life positioning applications. Such applications require high integrity, availability, and continuity of the positioning service. Integrity is assessed by the definition of a protection level, which is an estimation of the maximum positioning error at extremely low probability levels. The emergence of multi-frequency civilian signals and the availability of satellite-based augmentation systems improve the modeling of ionospheric disturbances considerably. As a result, in many applications the tropospheric delay tends to become one of the limiting factors of positioning—especially at low elevation angles. The currently adopted integrity concepts employ a global constant to model the variance of the residual tropospheric delay error. We introduce a new approach to derive residual tropospheric delay error models using the extreme value analysis technique. Seventeen years of global numerical weather model fields are analyzed, and new residual error models are derived for some recently developed tropospheric delay models. Our approach provides models that consider both the geographical location and the seasonal variation of meteorological parameters. Our models are validated with a 17-year-long time series of zenith tropospheric delay estimates as provided by the International GNSS Service. The results show that the developed models are still conservative, while the maximal residual error of the tropospheric delay is still improved by 39–55%. This improvement yields higher service availability and continuity in safety-of-life applications of GNSS. Numéro de notice : A2020-522 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-020-01017-7 date de publication en ligne : 07/08/2020 En ligne : https://doi.org/10.1007/s10291-020-01017-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95695 [article]

Application of convolutional and recurrent neural networks for buried threat detection using ground penetrating radar data / Mahdi Moalla in IEEE Transactions on geoscience and remote sensing, vol 58 n° 10 (October 2020)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 58 n° 10 (October 2020) . - pp 7022 - 7034 Titre : Application of convolutional and recurrent neural networks for buried threat detection using ground penetrating radar data Type de document : Article/Communication Auteurs : Mahdi Moalla, Auteur ; Hichem Frigui, Auteur ; Andrew Karem, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 7022 - 7034 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] cible souterraine [Termes descripteurs IGN] classification barycentrique [Termes descripteurs IGN] classification par réseau neuronal convolutif [Termes descripteurs IGN] détection d'objet [Termes descripteurs IGN] données radar [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] mine antipersonnel [Termes descripteurs IGN] Radar pénétrant GPR [Termes descripteurs IGN] réseau neuronal récurrent [Termes descripteurs IGN] sous-sol Résumé : (auteur) We propose discrimination algorithms for buried threat detection (BTD) that exploit deep convolutional neural networks (CNNs) and recurrent neural networks (RNN) to analyze 2-D GPR B-scans in the down-track (DT) and cross-track (CT) directions as well as 3-D GPR volumes. Instead of imposing a specific model or handcrafted features, as in most existing detectors, we use large real GPR data collections and data-driven approaches that learn: 1) features characterizing buried explosive objects (BEOs) in 2-D B-scans, both in the DT and CT directions; 2) the variation of the CNN features learned in a fixed 2-D view across the third dimension; and 3) features characterizing BEOs in the original 3-D space. The proposed algorithms were trained and evaluated using large experimental GPR data covering a surface area of 120 000 m 2 from 13 different lanes across two U.S. test sites. These data include a diverse set of BEOs consisting of varying shapes, metal content, and underground burial depths. We provide some qualitative analysis of the proposed algorithms by visually comparing their performance and consistency along different dimensions and visualizing typical features learned by some nodes of the network. We also provide quantitative analysis that compares the receiver operating characteristics (ROCs) obtained using the proposed algorithms with those obtained using existing approaches based on CNN as well as traditional learning. Numéro de notice : A2020-586 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2978763 date de publication en ligne : 25/03/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2978763 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95914 [article]

Combined InSAR and terrestrial structural monitoring of bridges / Sivasakthy Selvakumaran in IEEE Transactions on geoscience and remote sensing, vol 58 n° 10 (October 2020)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 58 n° 10 (October 2020) . - pp 7141 - 7153 Titre : Combined InSAR and terrestrial structural monitoring of bridges Type de document : Article/Communication Auteurs : Sivasakthy Selvakumaran, Auteur ; Cristian Rossi, Auteur ; Andrea Marinoni, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 7141 - 7153 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] coin réflecteur [Termes descripteurs IGN] données multisources [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] incertitude des données [Termes descripteurs IGN] interféromètrie par radar à antenne synthétique [Termes descripteurs IGN] Londres [Termes descripteurs IGN] pont [Termes descripteurs IGN] surveillance d'ouvrage [Termes descripteurs IGN] tachéomètre électronique Résumé : (auteur) This article examines advances in interferometric synthetic aperture radar (InSAR) satellite measurement technologies to understand their relevance, utilization, and limitations for bridge monitoring. Waterloo Bridge is presented as a case study to explore how InSAR data sets can be combined with traditional measurement techniques including sensors installed on the bridge and automated total stations. A novel approach to InSAR bridge monitoring was adopted by the installation of physical reflectors at key points of structural interest on the bridge, in order to supplement the bridge’s own reflection characteristics and ensure that the InSAR measurements could be directly compared and combined with in situ measurements. The interpretation and integration of InSAR data sets with civil infrastructure data are more than a trivial task, and a discussion of uncertainty of measurement data is presented. Finally, a strategy for combining and interpreting varied data from multiple sources to provide useful insights into each of these methods is presented, outlining the practical applications of this data analysis to support wider monitoring strategies. Numéro de notice : A2020-588 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2979961 date de publication en ligne : 01/04/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2979961 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95916 [article]

Evolution of orbit and clock quality for real-time multi-GNSS solutions / Kamil Kazmierski in GPS solutions, Vol 24 n° 4 (October 2020)  

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From small sets of GPS trajectories to detailed movement profiles: quantifying personalized trip-dependent movement diversity / Elham Naghizade in International journal of geographical information science IJGIS, vol 34 n° 10 (October 2020)  

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Ground-based remote sensing of forests exploiting GNSS signals / Leila Guerriero in IEEE Transactions on geoscience and remote sensing, vol 58 n° 10 (October 2020)  

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Impact of INSAT-3D/3DR radiance data assimilation in predicting tropical cyclone Titli over the bay of Bengal / Raghu Nadimpalli in IEEE Transactions on geoscience and remote sensing, vol 58 n° 10 (October 2020)  

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Integer-estimable GLONASS FDMA model as applied to Kalman-filter-based short- to long-baseline RTK positioning / Pengyu Hou in GPS solutions, Vol 24 n° 4 (October 2020)  

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A low-cost integrated MEMS-based INS/GPS vehicle navigation system with challenging conditions based on an optimized IT2FNN in occluded environments / Elahe S. Abdolkarimi in GPS solutions, Vol 24 n° 4 (October 2020)  

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A machine learning framework for estimating leaf biochemical parameters from its spectral reflectance and transmission measurements / Bikram Koirala in IEEE Transactions on geoscience and remote sensing, vol 58 n° 10 (October 2020)  

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Multiview automatic target recognition for infrared imagery using collaborative sparse priors / Xuelu Li in IEEE Transactions on geoscience and remote sensing, vol 58 n° 10 (October 2020)  

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Network-constrained bivariate clustering method for detecting urban black holes and volcanoes / Qiliang Liu in International journal of geographical information science IJGIS, vol 34 n° 10 (October 2020)  

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Python software tools for GNSS interferometric reflectometry (GNSS-IR) / Angel Martín in GPS solutions, Vol 24 n° 4 (October 2020)  

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