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Regional climate moderately influences species-mixing effect on tree growth-climate relationships and drought resistance for beech and pine across Europe / Géraud de Streel in Forest ecology and management, vol 520 (15 September 2022)  

Public [article]  inForest ecology and management > vol 520 (15 September 2022) . - n° 120317 Titre : Regional climate moderately influences species-mixing effect on tree growth-climate relationships and drought resistance for beech and pine across Europe Type de document : Article/Communication Auteurs : Géraud de Streel, Auteur ; François Lebourgeois, Auteur ; Christian Ammer, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 120317 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse de groupement [Termes IGN] analyse en composantes principales [Termes IGN] Bootstrap (statistique) [Termes IGN] climat [Termes IGN] coefficient de corrélation [Termes IGN] dendrochronologie [Termes IGN] échantillonnage [Termes IGN] Europe (géographie politique) [Termes IGN] évapotranspiration [Termes IGN] Fagus sylvatica [Termes IGN] peuplement mélangé [Termes IGN] Pinus sylvestris [Termes IGN] région [Termes IGN] sécheresse [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Increasing species diversity is considered a promising strategy to mitigate the negative impacts of global change on forests. However, the interactions between regional climate conditions and species-mixing effects on climate-growth relationships and drought resistance remain poorly documented. In this study, we investigated the patterns of species-mixing effects over a large gradient of environmental conditions throughout Europe for European beech (Fagus sylvatica L.) and Scots pine (Pinus sylvestris L.), two species with contrasted ecological traits. We hypothesized that across large geographical scales, the difference of climate-growth relationships and drought resistance between pure and mixed stands would be dependent on regional climate. We used tree ring chronologies derived from 1143 beech and 1164 pine trees sampled in 30 study sites, each composed of one mixed stand of beech and pine and of the two corresponding pure stands located in similar site conditions. For each site and stand, we used Bootstrapped Correlation Coefficients (BCCs) on standardized chronologies and growth reduction during drought years on raw chronologies to analyze the difference in climate-tree growth relationships and resistance to drought between pure and mixed stands. We found consistent large-scale spatial patterns of climate-growth relationships. Those patterns were similar for both species. With the exception of the driest climates where pure and mixed beech stands tended to display differences in growth correlation with the main climatic drivers, the mixing effects on the BCCs were highly variable, resulting in the lack of a coherent response to mixing. No consistent species-mixing effect on drought resistance was found within and across climate zones. On average, mixing had no significant effect on drought resistance for neither species, yet it increased pine resistance in sites with higher climatic water balance in autumn. Also, beech and pine most often differed in the timing of their drought response within similar sites, irrespective of the regional climate, which might increase the temporal stability of growth in mixed compared to pure stands. Our results showed that the impact of species mixing on tree response to climate did not strongly differ between groups of sites with distinct climate characteristics and climate-growth relationships, indicating the interacting influences of species identity, stand characteristics, drought events characteristics as well as local site conditions. Numéro de notice : A2022-557 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2022.120317 Date de publication en ligne : 17/06/2022 En ligne : https://doi.org/10.1016/j.foreco.2022.120317 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101172 [article]

Analysis of structure from motion and airborne laser scanning features for the evaluation of forest structure / Alejandro Rodríguez-Vivancos in European Journal of Forest Research, vol 141 n° 3 (June 2022)  

Public [article]  inEuropean Journal of Forest Research > vol 141 n° 3 (June 2022) . - pp 447 - 465 Titre : Analysis of structure from motion and airborne laser scanning features for the evaluation of forest structure Type de document : Article/Communication Auteurs : Alejandro Rodríguez-Vivancos, Auteur ; José Antonio Manzanera, Auteur ; Susana Martín-Fernández, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 447 - 465 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] analyse de variance [Termes IGN] Bootstrap (statistique) [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] erreur d'échantillon [Termes IGN] Espagne [Termes IGN] forêt inéquienne [Termes IGN] inventaire forestier étranger (données) [Termes IGN] lasergrammétrie [Termes IGN] modèle de régression [Termes IGN] modèle numérique de terrain [Termes IGN] Pinus sylvestris [Termes IGN] régression linéaire [Termes IGN] semis de points [Termes IGN] structure d'un peuplement forestier [Termes IGN] structure-from-motion Résumé : (auteur) Airborne Laser Scanning (ALS) is widely extended in forest evaluation, although photogrammetry-based Structure from Motion (SfM) has recently emerged as a more affordable alternative. Return cloud metrics and their normalization using different typologies of Digital Terrain Models (DTM), either derived from SfM or from private or free access ALS, were evaluated. In addition, the influence of the return density (0.5–6.5 returns m-2) and the sampling intensity (0.3–3.4%) on the estimation of the most common stand structure variables were also analysed. The objective of this research is to gather all these questions in the same document, so that they serve as support for the planning of forest management. This study analyses the variables collected from 60 regularly distributed circular plots (r = 18 m) in a 150-ha of uneven-aged Scots pine stand. Results indicated that both ALS and SfM can be equally used to reduce the sampling error in the field inventories, but they showed differences when estimating the stand structure variables. ALS produced significantly better estimations than the SfM metrics for all the variables of interest, as well as the ALS-based normalization. However, the SfM point cloud produced better estimations when it was normalized with its own DTM, except for the dominant height. The return density did not have significant influence on the estimation of the stand structure variables in the range studied, while higher sampling intensities decreased the estimation errors. Nevertheless, these were stabilized at certain intensities depending on the variance of the stand structure variable. Numéro de notice : A2022-417 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1007/s10342-022-01447-7 Date de publication en ligne : 12/04/2022 En ligne : https://doi.org/10.1007/s10342-022-01447-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100780 [article]

Exploring the spatial disparity of home-dwelling time patterns in the USA during the COVID-19 pandemic via Bayesian inference / Xiao Huang in Transactions in GIS, vol 26 n° 4 (June 2022)  

Public [article]  inTransactions in GIS > vol 26 n° 4 (June 2022) . - pp 1939 - 1961 Titre : Exploring the spatial disparity of home-dwelling time patterns in the USA during the COVID-19 pandemic via Bayesian inference Type de document : Article/Communication Auteurs : Xiao Huang, Auteur ; Yang Xu, Auteur ; Rui Liu, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 1939 - 1961 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse multiéchelle [Termes IGN] disparité [Termes IGN] distribution spatiale [Termes IGN] données socio-économiques [Termes IGN] épidémie [Termes IGN] estimation bayesienne [Termes IGN] hétérogénéité spatiale [Termes IGN] inférence statistique [Termes IGN] logement [Termes IGN] maladie virale [Termes IGN] méthode de Monte-Carlo par chaînes de Markov [Termes IGN] méthode robuste Résumé : (auteur) In this study, we aim to reveal hidden patterns and confounders associated with policy implementation and adherence by investigating the home-dwelling stages from a data-driven perspective via Bayesian inference with weakly informative priors and by examining how home-dwelling stages in the USA varied geographically, using fine-grained, spatial-explicit home-dwelling time records from a multi-scale perspective. At the U.S. national level, two changepoints are identified, with the former corresponding to March 22, 2020 (9 days after the White House declared the National Emergency on March 13) and the latter corresponding to May 17, 2020. Inspections at U.S. state and county level reveal notable spatial disparity in home-dwelling stage-related variables. A pilot study in the Atlanta Metropolitan area at the Census Tract level reveals that the self-quarantine duration and increase in home-dwelling time are strongly correlated with the median household income, echoing existing efforts that document the economic inequity exposed by the U.S. stay-at-home orders. To our best knowledge, our work marks a pioneering effort to explore multi-scale home-dwelling patterns in the USA from a purely data-driven perspective and in a statistically robust manner. Numéro de notice : A2022-533 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/MATHEMATIQUE Nature : Article DOI : 10.1111/tgis.12918 Date de publication en ligne : 17/03/2022 En ligne : https://doi.org/10.1111/tgis.12918 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101081 [article]

Two-phase forest inventory using very-high-resolution laser scanning / Henrik J. Persson in Remote sensing of environment, vol 271 (March- 2 2022)  

Public [article]  inRemote sensing of environment > vol 271 (March- 2 2022) . - n° 112909 Titre : Two-phase forest inventory using very-high-resolution laser scanning Type de document : Article/Communication Auteurs : Henrik J. Persson, Auteur ; Kenneth Olofsson, Auteur ; Johan Holmgren, Auteur Année de publication : 2022 Article en page(s) : n° 112909 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse comparative [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] échantillonnage [Termes IGN] forêt boréale [Termes IGN] hauteur des arbres [Termes IGN] inférence statistique [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] lasergrammétrie [Termes IGN] modélisation de la forêt [Termes IGN] peuplement forestier [Termes IGN] Suède [Termes IGN] télémétrie laser terrestre [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) In this study, we compared a two-phase laser-scanning-based forest inventory of stands versus a traditional field inventory using sample plots. The two approaches were used to estimate stem volume (VOL), Lorey's mean height (HL), Lorey's stem diameter (DL), and VOL per tree species in a study area in Sweden. The estimates were compared at the stand level with the harvested reference values obtained using a forest harvester. In the first phase, a helicopter acquired airborne laser scanning (ALS) data with >500 points/m2 along 50-m wide strips across the stands. These strips intersected systematic plots in phase two, where terrestrial laser scanning (TLS) was used to model DL for individual trees. In total, phase two included 99 plots across 10 boreal forest stands in Sweden (lat 62.9° N, long 16.9° E). The single trees were segmented in both the ALS and TLS data and linked to each other. The very-high-resolution ALS data enabled us to directly measure tree heights and also classify tree species using a convolutional neural network. Stem volume was predicted from the predicted DBH and the estimated height, using national models, and aggregated at the stand level. The study demonstrates a workflow to derive forest variables and stand-level statistics that has potential to replace many manual field inventories thanks to its time efficiency and improved accuracy. To evaluate the inventories, we estimated bias, RMSE, and precision, expressed as standard error. The laser-scanning-based inventory provided estimates with an accuracy considerably higher than the field inventory. The RMSE was 17 m3/ha (7.24%), 0.9 m (5.63%), and 16 mm (5.99%) for VOL, HL, and DL respectively. The tree species classification was generally successful and improved the three species-specific VOL estimates by 9% to 74%, compared to field estimates. In conclusion, the demonstrated laser-scanning-based inventory shows potential to replace some future forest inventories, thanks to the increased accuracy demonstrated empirically in the Swedish forest study area. Numéro de notice : A2022-249 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2022.112909 Date de publication en ligne : 22/01/2022 En ligne : https://doi.org/10.1016/j.rse.2022.112909 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100201 [article]

Robust GNSS phase tracking using variational bayesian inference / Fabio Fabozzi (2022)  

Public Titre : Robust GNSS phase tracking using variational bayesian inference Titre original : Méthodes de poursuite robuste de phase pour signaux GNSS basées sur l’inférence bayésienne variationnelle Type de document : Thèse/HDR Auteurs : Fabio Fabozzi, Auteur ; Stéphanie Bidon, Auteur Editeur : Toulouse : Université de Toulouse Année de publication : 2022 Importance : 173 p. Format : 21 x 30 cm Note générale : bibliographie Thèse en vue de l'obtention du Doctorat de l'Université de Toulouse, délivré par l'Institut Supérieur de l’Aéronautique et de l’Espace, Spécialité Signal, Image, acoustique et optimisation Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal [Termes IGN] données GNSS [Termes IGN] filtrage bayésien [Termes IGN] filtre de Kalman [Termes IGN] glissement de cycle [Termes IGN] inférence statistique [Termes IGN] méthode robuste [Termes IGN] phase [Termes IGN] rapport signal sur bruit [Termes IGN] récepteur GNSS [Termes IGN] signal GNSS Index. décimale : THESE Thèses et HDR Résumé : (auteur) In this Ph.D. thesis, we are interested in robust carrier-phase estimation by using Variational Bayesian filtering. Carrier-phase measurement has become a fundamental task in many various engineering applications such as precise point positioning in GNSS (Global Navigation Satellite System). Unfortunately, phase measurements obtained by traditional phase tracking techniques may be strongly affected by the presence of ambiguous phase jumps, known as cycle slips. The latter may strongly impact the performance of the considered phase tracking algorithm leading to, in the worst case, a permanent loss of lock (drop-lock) of the signal. A re-acquistion process is then necessary which afflicts the tracking performance. Therefore, to address this problem, we propose a robust nonlinear filter for carrier-phase tracking based on Restricted Variational Bayes inference. This methodology gives us a closed-form and easy-to-implement expression of the estimator. First, the algorithm is developed only for slow phase dynamics (i.e., first-order loop), then, its order is augmented by estimating a state vector formed by the carrier-phase and its derivatives. The performance of the proposed algorithm is compared with that of conventional techniques such as DPLL (Digital Phase Lock Loop) and KF (Kalman Filter)-based DPLL in terms of precision of estimation (root-mean-square error) and cycle slipping occurrence (mean-time-to-first-slip and cycle slip rate). The comparison is firstly conducted using synthetic data, and then, real GNSS data into a GNSS software-defined-radio receiver. Results show that the proposed method outperforms the conventional linear filters, when the signal-to-noise ratio is low. Note de contenu : Introduction 1- Introduction to GNSS 2- DPLL and robust phase tracking techniques 3- RVB algorithm in case of slow dynamics 4- RVB algorithm in case of high-order dynamics 5- RVB algorithm using real GNSS data Conclusion Numéro de notice : 15268 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Thèse française Note de thèse : thèse de Doctorat : Signal, Image, acoustique et optimisation : Toulouse : 2022 Organisme de stage : ISAE-ONERA SCANR DOI : sans En ligne : https://depozit.isae.fr/theses/2022/2022_Fabozzi_Fabio.pdf Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100684

Performance investigation of LAMBDA and bootstrapping methods for PPP narrow-lane ambiguity resolution / Omer Faruk Atiz in Geo-spatial Information Science, vol 24 n° 4 (October 2021)  

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3D map creation using crowdsourced GNSS data / Terence Lines in Computers, Environment and Urban Systems, vol 89 (September 2021)  

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Regularized regression: A new tool for investigating and predicting tree growth / Stuart I. Graham in Forests, vol 12 n° 9 (September 2021)  

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Variational bayesian compressive multipolarization indoor radar imaging / Van Ha Tang in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 9 (September 2021)  

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Vectorial integer bootstrapping: flexible integer estimation with application to GNSS / Peter J.G. Teunissen in Journal of geodesy, vol 95 n° 9 (September 2021)  

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Data science: Measuring uncertainties / Carlos Alberto De Bragança Pereira (2021)  

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

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Model based signal processing techniques for nonconventional optical imaging systems / Daniele Picone (2021)  

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Quantification probabiliste des taux de déformation crustale par inversion bayésienne de données GPS / Colin Pagani (2021)  

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Integrated Kalman filter of accurate ranging and tracking with wideband radar / Shaopeng Wei in IEEE Transactions on geoscience and remote sensing, Vol 58 n° 12 (December 2020)  

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