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Mixture effect on radial stem and shoot growth differs and varies with temperature / Maude Toïgo in Forest ecology and management, vol 488 (15 May 2021)  

Public [article]  inForest ecology and management > vol 488 (15 May 2021) . - n° 119046 Titre : Mixture effect on radial stem and shoot growth differs and varies with temperature Type de document : Article/Communication Auteurs : Maude Toïgo, Auteur ; Gaël Ledoux, Auteur ; Soline Martin-Blangy, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 119046 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Abies alba [Termes IGN] Alpes (France) [Termes IGN] climat [Termes IGN] croissance végétale [Termes IGN] diamètre des arbres [Termes IGN] échantillonnage [Termes IGN] Fagus sylvatica [Termes IGN] forêt tempérée [Termes IGN] houppier [Termes IGN] indice de stress [Termes IGN] peuplement mélangé [Termes IGN] Quercus pubescens [Termes IGN] température [Vedettes matières IGN] Sylviculture Résumé : (auteur) The effect of species diversity on forest productivity and its temporal stability is known to be species-, climate- and site- dependent and is mostly apprehended through stem diameter. Therefore, it remains largely unknown whether the mixture effect on the growth of tree crowns is similar to its effect on the growth of tree diameter. However, it is commonly accepted that changes in crown architecture are an important component of tree response to tree species diversity. Moreover, the mixture effect on species is often asymmetric, i.e. the effect of a species A on a species B is not equal to the effect of species B on A. It then appears that considering the effects of both species mixture and climate on shoot growth could contrast the results coming mainly from stem growth. We studied the effects of tree species mixture and temperature on the annual growth of shoots and basal area of stems in Fagus sylvatica-Quercus pubescens and Fagus sylvatica-Abies alba stands along a Mediterranean-Alpine gradient, for four years in five sites. The sample design was organized in 10 triplets: four triplets of mono- and bi-specific plots of Quercus pubescens and Fagus sylvatica and six triplets of mono- and bi-specific plots of Abies alba and Fagus sylvatica along an altitudinal gradient ranging from 725 m to 1431 m. We found that the mixture effect on annual shoot volume increment (SVI) and on basal area increment (BAI) was asymmetrical in seven out of 10 cases and not significant in the three remaining cases. Mixture effect on SVI ranked from −56% to 157% and on BAI it ranked from −40% to 252%. Eventually we found that mixture effect was dependent on the type of limiting factor for growth, with at the driest sites a predominance of competition effects and at the coldest site a positive mixture effect on the two species studied. Branch growth appears as a variable that can be at least as informative as radial growth regarding the tree response to species interactions. This implies that considering only stem diameter in the diversity-productivity relationship can lead to biased conclusions on the global mixture effect on tree growth, which calls for a comprehensive approach of the tree response to tree species diversity. Our results are discussed in the light of the species stress tolerances and strategies to cope with competition. Numéro de notice : A2021-357 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2021.119046 date de publication en ligne : 26/02/2021 En ligne : https://doi.org/10.1016/j.foreco.2021.119046 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97615 [article]

Non-stationary extreme value analysis of ground snow loads in the French Alps: a comparison with building standards / Erwann Le Roux in Natural Hazards and Earth System Sciences, vol 20 n° 11 (November 2020)  

Public [article]  inNatural Hazards and Earth System Sciences > vol 20 n° 11 (November 2020) . - pp 2961 – 2977 Titre : Non-stationary extreme value analysis of ground snow loads in the French Alps: a comparison with building standards Type de document : Article/Communication Auteurs : Erwann Le Roux, Auteur ; Guillaume Evin, Auteur ; Nicolas Eckert, Auteur ; Juliette Blanchet, Auteur Année de publication : 2020 Article en page(s) : pp 2961 – 2977 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Alpes (France) [Termes IGN] changement climatique [Termes IGN] construction [Termes IGN] épaisseur [Termes IGN] estimation des charges [Termes IGN] manteau neigeux [Termes IGN] norme [Termes IGN] sécurité [Termes IGN] série temporelle [Termes IGN] toit [Termes IGN] valeur limite Mots-clés libres : Ground snow load  surcharge de neige Résumé : (auteur) In a context of climate change, trends in extreme snow loads need to be determined to minimize the risk of structure collapse. We study trends in 50-year return levels of ground snow load (GSL) using non-stationary extreme value models. These trends are assessed at a mountain massif scale from GSL data, provided for the French Alps from 1959 to 2019 by a meteorological reanalysis and a snowpack model. Our results indicate a temporal decrease in 50-year return levels from 900 to 4200 m, significant in the northwest of the French Alps up to 2100 m. We detect the most important decrease at 900 m with an average of −30 % for return levels between 1960 and 2010. Despite these decreases, in 2019 return levels still exceed return levels designed for French building standards under a stationary assumption. At worst (i.e. at 1800 m), return levels exceed standards by 15 % on average, and half of the massifs exceed standards. We believe that these exceedances are due to questionable assumptions concerning the computation of standards. For example, these were devised with GSL, estimated from snow depth maxima and constant snow density set to 150 kg m−3, which underestimate typical GSL values for the snowpack. Numéro de notice : A2020-713 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.5194/nhess-20-2961-2020 date de publication en ligne : 06/11/2020 En ligne : https://doi.org/10.5194/nhess-20-2961-2020 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96279 [article]

La gratuité, une histoire ancienne... / Anonyme in Géomètre, n° 2182 (juillet - août 2020)

Public [article]  inGéomètre > n° 2182 (juillet - août 2020) . - pp 36 - 36 Titre : La gratuité, une histoire ancienne... Type de document : Article/Communication Auteurs : Anonyme, Auteur Année de publication : 2020 Article en page(s) : pp 36 - 36 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Histoire des sciences et techniques [Termes IGN] carte de Cassini [Termes IGN] cartographie ancienne [Termes IGN] données publiques [Termes IGN] Mont-Blanc, massif du Résumé : (Auteur) Mettre gratuitement à disposition une donnée chèrement acquise n'est pas une idée nouvelle. Deux exemples anciens nous le rappellent... Numéro de notice : A2020-432 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtSansCL DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95629 [article]

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Exploring the potential of deep learning segmentation for mountain roads generalisation / Azelle Courtial in ISPRS International journal of geo-information, vol 9 n° 5 (May 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 5 (May 2020) . - n° 338 ; 21 p. Titre : Exploring the potential of deep learning segmentation for mountain roads generalisation Type de document : Article/Communication Auteurs : Azelle Courtial , Auteur ; Achraf El Ayedi, Auteur ; Guillaume Touya , Auteur ; Xiang Zhang, Auteur Année de publication : 2020 Projets : 1-Pas de projet / Article en page(s) : n° 338 ; 21 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] 1:25.000 [Termes IGN] 1:250.000 [Termes IGN] Alpes (France) [Termes IGN] apprentissage profond [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] données routières [Termes IGN] données vectorielles [Termes IGN] généralisation automatique de données [Termes IGN] montagne [Termes IGN] route [Termes IGN] segmentation [Termes IGN] symbole graphique [Termes IGN] virage [Vedettes matières IGN] Généralisation Résumé : (auteur) Among cartographic generalisation problems, the generalisation of sinuous bends in mountain roads has always been a popular one due to its difficulty. Recent research showed the potential of deep learning techniques to overcome some remaining research problems regarding the automation of cartographic generalisation. This paper explores this potential on the popular mountain road generalisation problem, which requires smoothing the road, enlarging the bend summits, and schematising the bend series by removing some of the bends. We modelled the mountain road generalisation as a deep learning problem by generating an image from input vector road data, and tried to generate it as an output of the model a new image of the generalised roads. Similarly to previous studies on building generalisation, we used a U-Net architecture to generate the generalised image from the ungeneralised image. The deep learning model was trained and evaluated on a dataset composed of roads in the Alps extracted from IGN (the French national mapping agency) maps at 1:250,000 (output) and 1:25,000 (input) scale. The results are encouraging as the output image looks like a generalised version of the roads and the accuracy of pixel segmentation is around 65%. The model learns how to smooth the output roads, and that it needs to displace and enlarge symbols but does not always correctly achieve these operations. This article shows the ability of deep learning to understand and manage the geographic information for generalisation, but also highlights challenges to come. Numéro de notice : A2020-295 Affiliation des auteurs : UGE-LaSTIG+Ext (2020- ) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9050338 date de publication en ligne : 25/05/2020 En ligne : https://doi.org/10.3390/ijgi9050338 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95131 [article]

Constraint based evaluation of generalized images generated by deep learning / Azelle Courtial (2020)  

Public Titre : Constraint based evaluation of generalized images generated by deep learning Type de document : Article/Communication Auteurs : Azelle Courtial , Auteur ; Guillaume Touya , Auteur ; Xiang Zhang, Auteur Editeur : ICA Commission on Generalisation and Multiple Representation Année de publication : 2020 Projets : 1-Pas de projet / Conférence : ICA 2020, 23rd Workshop on Map Generalisation and Multiple Representation 05/11/2020 06/11/2020 Delft Pays-Bas Open Access Proceedings Importance : 3 p. Format : 21 x 30 cm Note générale : Bibliographie Langues : Français (fre) Descripteur : [Termes IGN] 1:25.000 [Termes IGN] 1:250.000 [Termes IGN] Alpes (France) [Termes IGN] apprentissage profond [Termes IGN] carte routière [Termes IGN] classification pixellaire [Termes IGN] données maillées [Termes IGN] généralisation automatique de données [Termes IGN] généralisation cartographique automatisée [Termes IGN] montagne [Termes IGN] précision cartographique [Termes IGN] programmation par contraintes [Termes IGN] réseau routier [Vedettes matières IGN] Généralisation Résumé : (Auteur) The use of deep learning techniques for map generalisation raises new problems regarding the evaluation of the results: (1) images are used as input/output instead of vector data; (2) the deep learning processes do not guarantee results that follow cartographic principles; (3) the deep learning models are black boxes that hide the causal mechanisms. Also, deep learning intern evaluation is mostly based on the realism of the images and the pixel classification accuracy, and none of these criteria is sufficient to evaluate a generalisation process. In this article, we propose an adaptation of the constraint-based evaluation to the images generated by deep learning. Six raster-based constraints are proposed for a mountain road generalisation use case. Numéro de notice : C2020-018 Affiliation des auteurs : UGE-LaSTIG+Ext (2020- ) Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : sans date de publication en ligne : 17/11/2020 En ligne : https://varioscale.bk.tudelft.nl/events/icagen2020/ICAgen2020/ICAgen2020_paper_2 [...] Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96380

Réflexions d’une paysagiste sur la progression des boisements spontanés dans les Alpes et les Pyrénées / Françoise Copin in Revue forestière française [en ligne], vol 71 n° 4-5 (2019)  

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Apport des mesures du radar à synthèse d'ouverture de Sentinel-1 pour l'étude des propriétés du manteau neigeux / Gaëlle Veyssière (2019)  

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Les peintures murales des lieux de culte du Sud de l’arc alpin du XIVe au XVIe siècle / Océane Acquier in Géomatique expert, n° 124 (septembre - octobre 2018)

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Potential and limits of Sentinel-1 data for small alpine glaciers monitoring / Matthias Jauvin (2018)  

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Restaurer les milieux et prévenir les inondations grâce au génie végétal / Freddy Rey (2018)    

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Determination of a high spatial resolution geopotential model using atomic clock comparisons / Guillaume Lion in Journal of geodesy, vol 91 n° 6 (June 2017)    

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The protective effect of forests against rockfalls across the French Alps: Influence of forest diversity / S. Dupire in Forest ecology and management, vol 382 (15 December 2016)  

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Paul Helbronner, le métronome de l'inutile / Daniel Léon in Pour la science, n° 463 (mai 2016)

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La mesure du Mont-Blanc / Bernard Flacelière in XYZ, n° 145 (décembre 2015 - février 2016)

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Interrogations au sommet / Michel Ravelet in Géomètre, n° 2129 (octobre 2015)

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