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Harmonised projections of future forest resources in Europe / Jari Vauhkonen in Annals of Forest Science [en ligne], Vol 76 n° 3 (September 2019)  

Public [article]  inAnnals of Forest Science [en ligne] > Vol 76 n° 3 (September 2019) Titre : Harmonised projections of future forest resources in Europe Type de document : Article/Communication Auteurs : Jari Vauhkonen, Auteur ; Ambros Berger, Auteur ; Thomas Gschwantner, Auteur ; Klemens Schadauer, Auteur ; Philippe Lejeune, Auteur ; Jérôme Perin, Auteur ; Radim Adolt, Auteur ; Miroslav Zeman, Auteur ; Vivian Kvist Johannsen, Auteur ; Sebastian Kepfer-Rojas, Auteur ; Allan Sims, Auteur ; Claire Bastick, Auteur Année de publication : 2019 Projets : DIABOLO / Packalen, Tuula Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] biomasse [Termes descripteurs IGN] bois sur pied [Termes descripteurs IGN] carbone [Termes descripteurs IGN] Europe (géographie politique) [Termes descripteurs IGN] foresterie [Termes descripteurs IGN] gestion forestière durable [Termes descripteurs IGN] inventaire forestier étranger (données) [Termes descripteurs IGN] inventaire forestier national (données France) [Termes descripteurs IGN] politique forestière [Termes descripteurs IGN] prévision [Termes descripteurs IGN] ressources forestières [Vedettes matières IGN] Economie forestière Résumé : (auteur) Key message: A dataset of forest resource projections in 23 European countries to 2040 has been prepared for forest-related policy analysis and decision-making. Due to applying harmonised definitions, while maintaining country-specific forestry practices, the projections should be usable from national to international levels. The dataset can be accessed at https://doi.org/10.5061/dryad.4t880qh . The associated metadata are available at https://metadata-afs.nancy.inra.fr/geonetwork/srv/eng/catalog.search#/metadata/8f93e0d6-b524-43bd-bdb8-621ad5ae6fa9 Numéro de notice : A2019-322 Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-019-0863-6 date de publication en ligne : 29/07/2019 En ligne : https://doi.org/10.1007/s13595-019-0863-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93299 [article]

Sea level prediction in the Yellow Sea from satellite altimetry with a combined least squares-neural network approach / Jian Zhao in Marine geodesy, vol 42 n° 4 (July 2019)  

Public [article]  inMarine geodesy > vol 42 n° 4 (July 2019) . - pp 344 - 366 Titre : Sea level prediction in the Yellow Sea from satellite altimetry with a combined least squares-neural network approach Type de document : Article/Communication Auteurs : Jian Zhao, Auteur ; Yanguo Fan, Auteur ; Yuxiang Mu, Auteur Année de publication : 2019 Article en page(s) : pp 344 - 366 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique [Termes descripteurs IGN] changement du niveau de la mer [Termes descripteurs IGN] détection d'anomalie [Termes descripteurs IGN] données altimétriques [Termes descripteurs IGN] données Jason [Termes descripteurs IGN] données Topex-Poseidon [Termes descripteurs IGN] image ERS-SAR [Termes descripteurs IGN] méthode des moindres carrés [Termes descripteurs IGN] Pacifique nord [Termes descripteurs IGN] prévision [Termes descripteurs IGN] réseau neuronal artificiel [Termes descripteurs IGN] série temporelle Résumé : (auteur) Accessible high-quality observation datasets and proper modeling process are critically required to accurately predict sea level rise in coastal areas. This study focuses on developing and validating a combined least squares-neural network approach applicable to the short-term prediction of sea level variations in the Yellow Sea, where the periodic terms and linear trend of sea level change are fitted and extrapolated using the least squares model, while the prediction of the residual terms is performed by several different types of artificial neural networks. The input and output data used are the sea level anomalies (SLA) time series in the Yellow Sea from 1993 to 2016 derived from ERS-1/2, Topex/Poseidon, Jason-1/2, and Envisat satellite altimetry missions. Tests of different neural network architectures and learning algorithms are performed to assess their applicability for predicting the residuals of SLA time series. Different neural networks satisfactorily provide reliable results and the root mean square errors of the predictions from the proposed combined approach are less than 2 cm and correlation coefficients between the observed and predicted SLA are up to 0.87. Results prove the reliability of the combined least squares-neural network approach on the short-term prediction of sea level variability close to the coast. Numéro de notice : A2019-281 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01490419.2019.1626306 date de publication en ligne : 12/06/2019 En ligne : https://doi.org/10.1080/01490419.2019.1626306 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93115 [article]

How do tree mortality models from combined tree-ring and inventory data affect projections of forest succession? / Marco Vanoni in Forest ecology and management, vol 433 (15 February 2019)  

Public [article]  inForest ecology and management > vol 433 (15 February 2019) . - pp 606 - 617 Titre : How do tree mortality models from combined tree-ring and inventory data affect projections of forest succession? Type de document : Article/Communication Auteurs : Marco Vanoni, Auteur ; Maxime Cailleret, Auteur ; Lisa Hülsmann, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 606 - 617 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Végétation [Termes descripteurs IGN] Abies alba [Termes descripteurs IGN] arbre (flore) [Termes descripteurs IGN] arbre mort [Termes descripteurs IGN] croissance végétale [Termes descripteurs IGN] diamètre des arbres [Termes descripteurs IGN] données dendrométriques [Termes descripteurs IGN] dynamique de la végétation [Termes descripteurs IGN] Europe centrale [Termes descripteurs IGN] Fagus sylvatica [Termes descripteurs IGN] forêt [Termes descripteurs IGN] inventaire forestier étranger (données) [Termes descripteurs IGN] larix decidua [Termes descripteurs IGN] modèle de croissance [Termes descripteurs IGN] modèle de simulation [Termes descripteurs IGN] mortalité [Termes descripteurs IGN] Picea abies [Termes descripteurs IGN] Pinus cembra [Termes descripteurs IGN] prévision [Termes descripteurs IGN] quercus (genre) [Termes descripteurs IGN] Suisse Résumé : (auteur) Tree mortality is caused by complex interactions between multiple biotic and abiotic factors. Processes of tree mortality that are not induced by natural disturbances are often reflected in distinct radial growth patterns of trees, which typically serve as reliable indicators of impending tree mortality. However, it remains unclear whether empirical mortality models that are based on tree size and growth result in more realistic projections of forest succession in dynamic vegetation models (DVMs). We used a combination of tree-ring and inventory data from unmanaged Swiss natural forest reserves to derive species-specific survival models for six Central European tree species (Abies alba, Fagus sylvatica, Larix decidua, Picea abies, Pinus cembra and Quercus spp.). We jointly used 528 tree-ring samples and inventory data from eight forest reserves. We implemented the estimated parameters of the survival models into the DVM ForClim and performed simulations of forest succession that were validated using the inventory data of the forest reserves. Size- and growth-dependent variables (i.e., diameter at breast height and mean ring width) over the last few years prior to tree death were reliable predictors to distinguish between dying and living trees. Very low mean ring widths over several preceding years as well as small and large trees, respectively, reflected low survival probabilities. However, the small sample sizes of small and large trees resulted in considerable uncertainty of the survival probabilities. The implementation of these survival models in ForClim yielded plausible projections in short-term simulations and for some sites improved the predictions compared to the current ForClim version. Stand basal area, however, tended to be overestimated. Long-term simulations of ForClim based on the empirical survival models resulted in realistic predictions only if the uncertainty of the predicted survival probabilities was considered. We conclude that the combination of different data sources in combination with the consideration of intra-specific trait variability yields robust predictions of tree survival probabilities, thus paving the way towards better tree mortality models and more reliable projections of future forest dynamics. Numéro de notice : A2019-009 Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2018.11.042 date de publication en ligne : 29/11/2018 En ligne : https://doi.org/10.1016/j.foreco.2018.11.042 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91603 [article]

Eucalyptus growth and yield system: Linking individual-tree and stand-level growth models in clonal Eucalypt plantations in Brazil / Henrique Ferraco Scolforo in Forest ecology and management, vol 432 (15 January 2019)  

Public [article]  inForest ecology and management > vol 432 (15 January 2019) . - pp 1 - 16 Titre : Eucalyptus growth and yield system: Linking individual-tree and stand-level growth models in clonal Eucalypt plantations in Brazil Type de document : Article/Communication Auteurs : Henrique Ferraco Scolforo, Auteur ; John Paul McTague, Auteur ; Harold Burkhart, Auteur ; John Roise, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 1 - 16 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] analyse comparative [Termes descripteurs IGN] Brésil [Termes descripteurs IGN] clonage [Termes descripteurs IGN] croissance végétale [Termes descripteurs IGN] Eucalyptus (genre) [Termes descripteurs IGN] gestion forestière [Termes descripteurs IGN] hauteur de la végétation [Termes descripteurs IGN] inventaire forestier (techniques et méthodes) [Termes descripteurs IGN] modèle de croissance [Termes descripteurs IGN] peuplement forestier [Termes descripteurs IGN] prévision [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Linking individual-tree and stand-level growth models is required for estimating future forest stand structure, while maintaining the desired accuracy for forest management decision making. There is a scarcity of studies addressing this issue for clonal Eucalypt stands in Brazil. Thus, this paper aims to develop a compatible individual-tree and stand-level growth and yield system for clonal Eucalypt stands in Brazil. The dataset used in this study is derived from remeasurement information of sixteen TECHS sites. At every site, eleven Eucalypt clones were planted in single block plots, while extra plots under a rainfall exclusion regime were also installed in fourteen sites. Prediction and projection diameter percentile equations were developed, as well as an individual-tree mortality equation and a generalized height-diameter equation. In addition, a detailed explanation of the structural architecture of the developed compatible growth and yield system is provided. Differences when forecasting forest afforestation and updating forest inventories were highlighted in order to provide the proper use of the developed growth and yield system. Finally, the individual-tree equations were validated through the use of the rainfall exclusion regime plots as was the growth and yield system when applied for prediction and projection purposes. The individual-tree level equations provided accurate estimates. The newly developed compatible growth and yield system also displayed unbiased and accurate estimates. The system achieved full compatibility between individual-tree and stand-level estimates and produced accurate stand table estimates. The growth and yield system presented is a powerful analytical tool that can serve to update inventory data in tropical Brazil and also to provide estimates for expected forest afforestation. The system has the capability of providing detailed outputs, which allows forest managers to consider merchandizing the clonal Eucalypt stands into multiple products. Numéro de notice : A2019-002 Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.foreco.2018.08.045 date de publication en ligne : 12/09/2018 En ligne : https://doi.org/10.1016/j.foreco.2018.08.045 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91595 [article]

Assessing spatiotemporal predictability of LBSN : a case study of three Foursquare datasets / Ming Li in Geoinformatica [en ligne], vol 22 n° 3 (July 2018)  

Public [article]  inGeoinformatica [en ligne] > vol 22 n° 3 (July 2018) . - pp 541 - 561 Titre : Assessing spatiotemporal predictability of LBSN : a case study of three Foursquare datasets Type de document : Article/Communication Auteurs : Ming Li, Auteur ; Rene Westerholt, Auteur ; Hongchao Fan, Auteur ; Alexander Zipf, Auteur Année de publication : 2018 Article en page(s) : pp 541 - 561 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] comportement [Termes descripteurs IGN] jeu de données localisées [Termes descripteurs IGN] modèle de simulation [Termes descripteurs IGN] prévision [Termes descripteurs IGN] réseau social géodépendant [Termes descripteurs IGN] ville Résumé : (Auteur) Location-based social networks (LBSN) have provided new possibilities for researchers to gain knowledge about human spatiotemporal behavior, and to make predictions about how people might behave through space and time in the future. An important requirement of successfully utilizing LBSN in these regards is a thorough understanding of the respective datasets, including their inherent potential as well as their limitations. Specifically, when it comes to predictions, we must know what we can actually expect from the data, and how we could maximize their usefulness. Yet, this knowledge is still largely lacking from the literature. Hence, this work explores one particular aspect which is the theoretical predictability of LBSN datasets. The uncovered predictability is represented with an interval. The lower bound of the interval corresponds to the amount of regular behaviors that can easily be anticipated, and represents the correct predication rate that any algorithm should be able to achieve. The upper bound corresponds to the amount of information that is contained in the dataset, and represents the maximum correct prediction rate that cannot be exceeded by any algorithms. Three Foursquare datasets from three American cities are studied as an example. It is found that, within our investigated datasets, the lower bound of predictability of the human spatiotemporal behavior is 27%, and the upper bound is 92%. Hence, the inherent potentials of the dataset for predicting human spatiotemporal behavior are clarified, and the revealed interval allows a realistic assessment of the quality of predictions and thus of associated algorithms. Additionally, in order to provide further insight into the practical use of the dataset, the relationship between the predictability and the check-in frequencies are investigated from three different perspectives. It was found that the individual perspective provides no significant correlations between the predictability and the check-in frequency. In contrast, the same two quantities are found to be negatively correlated from temporal and spatial perspectives. Our study further indicates that the heavily frequented contexts and some extraordinary geographic features such as airports could be good starting points for effective improvements of prediction algorithms. In general, this research provides novel knowledge regarding the nature of the LBSN dataset and practical insights for a more reasonable utilization of the dataset. Numéro de notice : A2018-349 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10707-016-0279-5 date de publication en ligne : 25/11/2016 En ligne : https://doi.org/10.1007/s10707-016-0279-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90758 [article]

Predicting suitability of forest dynamics to future climatic conditions: the likely dominance of Holm oak [Quercus ilex subsp. ballota (Desf.) Samp.] and Aleppo pine (Pinus halepensis Mill.) / Javier López-Tirado in Annals of Forest Science [en ligne], vol 75 n° 1 (March 2018)  

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Maintaining real-time precise point positioning during outages of orbit and clock corrections / Ahmed El-Mowafy in GPS solutions, vol 21 n° 3 (July 2017)  

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Motion priors based on goals hierarchies in pedestrian tracking applications / Francisco Madrigal in Machine Vision and Applications, vol 28 n° 3-4 (May 2017)  

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Efficient obstruction analysis for GNSS relative positioning of terrestrial mobile mapping system / J.Y. Han in Survey review, vol 47 n° 342 (May 2015)  

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Maîtriser l'espace, le temps et les identités grâce aux cartes pendant la première guerre mondiale / Isabelle Avila in Cartes & Géomatique, n° 223 (mars 2015) 

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Traffic prediction and analysis using a big data and visualisation approach / Declan McHugh (2015) 

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La forêt française, l'agroforesterie et la filière bois : quel potentiel d'atténuation climatique à moyen et long terme ? / Michel de Galbert in Revue forestière française, vol 66 n° 5 (septembre - octobre 2014)  

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Usage et lecture des cartes / Ferjan Ormeling in Cartes & Géomatique, n° 221 (septembre 2014)

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Proactive flood monitoring / Sergey Markov in GEO: Geoconnexion international, vol 13 n° 4 (april 2014)

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Temporal accuracy in urban growth forecasting: a study using the SLEUTH model / Gargi Chaudhuri in Transactions in GIS, vol 18 n° 2 (April 2014)

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