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Semantic‐based urban growth prediction / Marvin Mc Cutchan in Transactions in GIS, Vol 24 n° 6 (December 2020)  

Public [article]  inTransactions in GIS > Vol 24 n° 6 (December 2020) . - 1482 - 1503 Titre : Semantic‐based urban growth prediction Type de document : Article/Communication Auteurs : Marvin Mc Cutchan, Auteur ; Simge Özdal‐Oktay, Auteur ; Ioannis Giannopoulos, Auteur Année de publication : 2020 Article en page(s) : 1482 - 1503 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] apprentissage profond [Termes IGN] croissance urbaine [Termes IGN] dynamique spatiale [Termes IGN] Europe (géographie politique) [Termes IGN] information sémantique [Termes IGN] modèle de simulation [Termes IGN] modélisation spatiale [Termes IGN] occupation du sol [Termes IGN] OpenStreetMap [Termes IGN] organisation spatiale [Termes IGN] OWL [Termes IGN] prévision [Termes IGN] réseau neuronal artificiel [Termes IGN] urbanisation [Termes IGN] ville durable Résumé : (Auteur) Urban growth is a spatial process which has a significant impact on the earth’s environment. Research on predicting this complex process makes it therefore especially fruitful for decision‐making on a global scale, as it enables the introduction of more sustainable urban development. This article presents a novel method of urban growth prediction. The method utilizes geospatial semantics in order to predict urban growth for a set of random areas in Europe. For this purpose, a feature space representing geospatial configurations was introduced which embeds semantic information. Data in this feature space was then used to perform deep learning, which ultimately enables the prediction of urban growth with high accuracy. The final results reveal that geospatial semantics hold great potential for spatial prediction tasks. Numéro de notice : A2020-766 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12655 Date de publication en ligne : 14/07/2020 En ligne : https://doi.org/10.1111/tgis.12655 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96657 [article]

Improved wavelet neural network based on change rate to predict satellite clock bias / Xu Wang in Survey review, vol 52 n° 372 (May 2020)  

Public [article]  inSurvey review > vol 52 n° 372 (May 2020) Titre : Improved wavelet neural network based on change rate to predict satellite clock bias Type de document : Article/Communication Auteurs : Xu Wang, Auteur ; Hongzhou Chai, Auteur ; Chang Wang, Auteur ; et al., Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] courbe de Gauss [Termes IGN] erreur systématique interfréquence d'horloge [Termes IGN] estimation de précision [Termes IGN] ondelette [Termes IGN] ondelette de Shannon [Termes IGN] prévision [Termes IGN] réseau neuronal artificiel Résumé : (auteur) To develop a high-accuracy method for predicting SCB based on the analysis of the shortcomings of the wavelet neural network (WNN) model, an improved WNN model to predict SCB is proposed herein. The activation function of the WNN is constructed by combining the advantages of Shannon and Gauss ‘window’ functions to improve the WNN. Finally, the improved WNN model is used to predict SCB. The results show that the proposed model has the highest prediction accuracy, stability, and robustness. Moreover, it effectively predicts long-time SCB data. Therefore, the proposed model can predict SCB with high accuracy. Numéro de notice : A2020-289 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2020.1758999 Date de publication en ligne : 24/05/2020 En ligne : https://doi.org/10.1080/00396265.2020.1758999 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95117 [article]

Clinal variation along precipitation gradients in Patagonian temperate forests: unravelling demographic and selection signatures in three Nothofagus spp. / Carolina Soliani in Annals of Forest Science [en ligne], Vol 77 n° 1 (March 2020)  

Public [article]  inAnnals of Forest Science [en ligne] > Vol 77 n° 1 (March 2020) . - 17 p. Titre : Clinal variation along precipitation gradients in Patagonian temperate forests: unravelling demographic and selection signatures in three Nothofagus spp. Type de document : Article/Communication Auteurs : Carolina Soliani, Auteur ; Maria Marta Azpilicueta, Auteur ; Maria Veronica Arana, Auteur ; Paula Marchelli, Auteur Année de publication : 2020 Article en page(s) : 17 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse diachronique [Termes IGN] forêt tempérée [Termes IGN] génétique forestière [Termes IGN] Nothofagus (genre) [Termes IGN] nothofagus pumilio [Termes IGN] Patagonie [Termes IGN] Pléistocène [Termes IGN] précipitation [Termes IGN] prévision [Termes IGN] sécheresse [Termes IGN] stress hydrique [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Key message: Past demographic changes and current selection pressures determine the genetic variation displayed by Nothofagus species along rainfall gradients. Based on the diversity trends observed at candidate genes associated to drought stress, we inferred a differential species’ adaptive potential. Context: Clinal genetic variation in natural populations could reflect either recent demographic history or the evolution of adapted genotypes along heterogeneous environments. Aims: We describe genetic variation patterns in three Nothofagus species of South American temperate forests, growing along steep rainfall gradients. Our hypothesis is that the selection pressure along this gradient reinforces the genetic structure previously shaped by Pleistocene climate oscillations. Methods: We screened variation along gradients at putative adaptive markers: candidate genes involved in response to drought, and EST-SSRs linked to drought stress genes. Genomic SSRs (gSSRs) were used to decouple the incidence of demographic events in the genetic structure. Results: Genetic diversity at SSRs agreed with the putative location of cryptic Pleistocene refugia in Nothofagus. In addition, each species showed different trends for nucleotide diversity at candidate genes. Unbiased heterozygosity significantly correlated with precipitation at EST-SSRs in Nothofagus nervosa. We found evidences of balancing selection and several SNPs departed from neutral expectations. Conclusions: Nothofagus genetic variability shows a strong imprint of demographic changes that reveals refugia location for the species during Pleistocene. This variability is modelled by environmental conditions across natural gradients, which impose selection pressure at genome regions related to stress response, providing clues about inter-specific differences in adaptive potential to water deficit. Numéro de notice : A2020-032 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-019-0908-x Date de publication en ligne : 10/01/2020 En ligne : https://doi.org/10.1007/s13595-019-0908-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94489 [article]

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) . - n° 79 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 ; François Morneau , Auteur ; Antoine Colin , Auteur ; et al., Auteur Année de publication : 2019 Projets : DIABOLO / Packalen, Tuula Article en page(s) : n° 79 Note générale : bibliographie Correction de cet article https://link.springer.com/article/10.1007%2Fs13595-019-0872-5 Langues : Anglais (eng) Descripteur : [Termes IGN] biomasse [Termes IGN] bois sur pied [Termes IGN] Europe (géographie politique) [Termes IGN] foresterie [Termes IGN] gestion forestière durable [Termes IGN] inventaire forestier étranger (données) [Termes IGN] inventaire forestier national (données France) [Termes IGN] politique forestière [Termes IGN] prévision [Termes IGN] puits de carbone [Termes IGN] ressources forestières [Vedettes matières IGN] Economie forestière Résumé : (auteur) 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 Affiliation des auteurs : IGN+Ext (2012-2019) Autre URL associée : correction de l'article 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 IGN] détection d'anomalie [Termes IGN] données altimétriques [Termes IGN] données Jason [Termes IGN] données Topex-Poseidon [Termes IGN] image ERS-SAR [Termes IGN] méthode des moindres carrés [Termes IGN] montée du niveau de la mer [Termes IGN] Pacifique nord [Termes IGN] prévision [Termes IGN] réseau neuronal artificiel [Termes 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 Affiliation des auteurs : non IGN 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)  

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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)  

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

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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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