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Recent increase in European forest harvests as based on area estimates (Ceccherini et al. 2020a) not confirmed in the French case / Nicolas Picard in Annals of Forest Science [en ligne], vol 78 n° 1 (March 2021)  

Public [article]  inAnnals of Forest Science [en ligne] > vol 78 n° 1 (March 2021) . - n° 9 Titre : Recent increase in European forest harvests as based on area estimates (Ceccherini et al. 2020a) not confirmed in the French case Type de document : Article/Communication Auteurs : Nicolas Picard, Auteur ; Jean-Michel Leban , Auteur ; Jean-Marc Guehl, Auteur ; Erwin Dreyer, Auteur ; Olivier Bouriaud , Auteur ; Jean-Daniel Bontemps , Auteur ; Guy Landmann, Auteur ; Antoine Colin , Auteur ; Jean-Luc Peyron, Auteur ; Pascal Marty, Auteur Année de publication : 2021 Projets : 1-Pas de projet / Article en page(s) : n° 9 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse diachronique [Termes IGN] base de données forestières [Termes IGN] exploitation forestière [Termes IGN] France (administrative) [Termes IGN] inventaire forestier national (données France) [Termes IGN] récolte de bois [Termes IGN] série temporelle [Termes IGN] superficie [Termes IGN] tempête Klaus de 2009 [Termes IGN] volume en bois [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) A recent paper by Ceccherini et al.( 2020a ) reported an abrupt increase of 30% in the French harvested forest area in 2016–2018 compared to 2004–2015. A re-analysis of their data rather led us to conclude that, when accounting for the singular effect of storm Klaus, the rate of change in harvested area depended on the change year used to separate the two periods to compare. Moreover, the comparison with data on harvested volumes from different sources brought contrasted results depending on the source. Therefore, it cannot be concluded that wood harvest increased in France in 2016–2018 compared to 2004–2015. The discrepancy between Ceccherini et al.’s data and other data on harvested volumes points out the difficulty of reconciling different approaches to estimate wood harvest at a country level. Numéro de notice : A2021-130 Affiliation des auteurs : LIF+Ext (2020- ) Autre URL associée : vers HAL Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-021-01030-x date de publication en ligne : 25/01/2021 En ligne : https://doi.org/10.1007/s13595-021-01030-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96964 [article]

From local to global: A transfer learning-based approach for mapping poplar plantations at national scale using Sentinel-2 / Yousra Hamrouni in ISPRS Journal of photogrammetry and remote sensing, vol 171 (January 2021)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 171 (January 2021) . - pp 76 - 100 Titre : From local to global: A transfer learning-based approach for mapping poplar plantations at national scale using Sentinel-2 Type de document : Article/Communication Auteurs : Yousra Hamrouni, Auteur ; Eric Paillassa, Auteur ; Véronique Chéret, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 76 - 100 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] apprentissage automatique [Termes IGN] base de données forestières [Termes IGN] carte de la végétation [Termes IGN] classification par forêts aléatoires [Termes IGN] couvert forestier [Termes IGN] échantillonnage [Termes IGN] France (administrative) [Termes IGN] image Sentinel-MSI [Termes IGN] mise à jour de base de données [Termes IGN] Populus (genre) [Termes IGN] série temporelle Résumé : (auteur) Reliable estimates of poplar plantations area are not available at the French national scale due to the unsuitability and low update rate of existing forest databases for this short-rotation species. While supervised classification methods have been shown to be highly accurate in mapping forest cover from remotely sensed images, their performance depends to a great extent on the labelled samples used to build the models. In addition to their high acquisition cost, such samples are often scarce and not fully representative of the variability in class distributions. Consequently, when classification models are applied to large areas with high intra-class variance, they generally yield poor accuracies because of data shift issues. In this paper, we propose the use of active learning to efficiently adapt a classifier trained on a source image to spatially distinct target images with minimal labelling effort and without sacrificing the classification performance. The adaptation consists in actively adding to the initial local model new relevant training samples from other areas in a cascade that iteratively improves the generalisation capabilities of the classifier leading to a global model tailored to these different areas. This active selection relies on uncertainty sampling to directly focus on the most informative pixels for which the algorithm is the least certain of their class labels. Experiments conducted on Sentinel-2 time series revealed their high capacity to identify poplar plantations at a local scale with an average F-score ranging from 89.5% to 99.3%. For large area adaptation, the results showed that when the same number of training samples was used, active learning outperformed random sampling by up to 5% of the overall accuracy and up to 12% of the class F-score. Additionally, and depending on the class considered, the random sampling model required up to 50% more samples to achieve the same performance of an active learning-based model. Moreover, the results demonstrate the suitability of the derived global model to accurately map poplar plantations among other tree species with overall accuracy values up to 14% higher than those obtained with local models. The proposed approach paves the way for a national scale mapping in an operational context. Numéro de notice : A2021-013 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.10.018 date de publication en ligne : 20/11/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.10.018 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96417 [article]

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Improving aboveground biomass estimates by taking into account density variations between tree components / Antoine Billard 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) . - n° 103 Titre : Improving aboveground biomass estimates by taking into account density variations between tree components Type de document : Article/Communication Auteurs : Antoine Billard, Auteur ; Rodolphe Bauer, Auteur ; Frédéric Mothe, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : n° 103 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] allométrie [Termes IGN] base de données forestières [Termes IGN] biomasse aérienne [Termes IGN] bois de chauffage [Termes IGN] branche (arbre) [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] écorce [Termes IGN] hauteur des arbres [Termes IGN] résineux [Termes IGN] tomographie radar [Termes IGN] volume en bois [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Key message: Strong density differences were observed between stem wood at 1.30 m and other tree components (stem wood, stem bark, knots, branch stumps and branches). The difference, up to 40% depending on the component, should be taken into account when estimating the biomass available for industrial uses, mainly fuelwood and wood for chemistry. Context: Basic density is a major variable in the calculation of tree biomass. However, it is usually measured on stem wood only and at breast height. Aims: The objectives of this study were to compare basic density of stem wood at 1.30 m with other tree components and assess the impact of differences on biomass. Methods: Three softwood species were studied: Abies alba Mill., Picea abies (L.) H. Karst., Pseudotsuga menziesii (Mirb.) Franco. X-Ray computed tomography was used to measure density. Results: Large differences were observed between components. Basic density of components was little influenced by tree size and stand density. Overall, bark, knot and branch biomasses were highly underestimated by using basic density measured at 1.30 m. Conclusion: Using available wood density databases mainly based on breast height measurements would lead to important biases (up to more than 40%) on biomass estimates for some tree components. Further work is necessary to complete available databases. Numéro de notice : A2020-714 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s13595-020-00999-1 date de publication en ligne : 26/10/2020 En ligne : https://doi.org/10.1007/s13595-020-00999-1 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96282 [article]

Classifying physiographic regimes on terrain and hydrologic factors for adaptive generalization of stream networks / Lauwrence V. Stanislawski in International journal of cartography, Vol 6 n° 1 (March 2020)  

Public [article]  inInternational journal of cartography > Vol 6 n° 1 (March 2020) . - pp 4 - 21 Titre : Classifying physiographic regimes on terrain and hydrologic factors for adaptive generalization of stream networks Type de document : Article/Communication Auteurs : Lauwrence V. Stanislawski, Auteur ; Michael P. Finn, Auteur ; Barbara P. Buttenfield, Auteur Année de publication : 2020 Article en page(s) : pp 4 - 21 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] algorithme de généralisation [Termes IGN] altitude [Termes IGN] base de données hydrographiques [Termes IGN] cartographie des flux [Termes IGN] classification dirigée [Termes IGN] classification par maximum de vraisemblance [Termes IGN] cours d'eau [Termes IGN] drainage [Termes IGN] Etats-Unis [Termes IGN] pente [Termes IGN] perméabilité du sol [Termes IGN] représentation multiple [Termes IGN] réseau hydrographique [Termes IGN] ruissellement [Termes IGN] segmentation [Termes IGN] traitement automatique de données [Vedettes matières IGN] Généralisation Résumé : (auteur) Automated generalization software must accommodate multi-scale representations of hydrographic networks across a variety of geographic landscapes, because scale-related hydrography differences are known to vary in different physical conditions. While generalization algorithms have been tailored to specific regions and landscape conditions by several researchers in recent years, the selection and characterization of regional conditions have not been formally defined nor statistically validated. This paper undertakes a systematic classification of landscape types in the conterminous United States to spatially subset the country into workable units, in preparation for systematic tailoring of generalization workflows that preserve hydrographic characteristics. The classification is based upon elevation, standard deviation of elevation, slope, runoff, drainage and bedrock density, soil and bedrock permeability, area of inland surface water, infiltration-excess of overland flow, and a base flow index. A seven class solution shows low misclassification rates except in areas of high landscape diversity such as the Appalachians, Rocky Mountains, and Western coastal regions. Numéro de notice : A2020-070 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/23729333.2018.1443759 date de publication en ligne : 20/03/2018 En ligne : https://doi.org/10.1080/23729333.2018.1443759 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94632 [article]

Fusion entre bases de données hétérogènes concernant la pollution des sols [diaporama] / Chuanming Dong (2020)  

Public Titre : Fusion entre bases de données hétérogènes concernant la pollution des sols [diaporama] Type de document : Article/Communication Auteurs : Chuanming Dong, Auteur Editeur : GdR MaDICS Année de publication : 2020 Conférence : Atelier 2020 AGEE du second symposium GdR CNRS MaDICS 06/07/2020 06/07/2020 en ligne France programme Langues : Français (fre) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] acteur [Termes IGN] appariement de données localisées [Termes IGN] base de données localisées [Termes IGN] base de données thématiques [Termes IGN] données spatiotemporelles [Termes IGN] intégration de données [Termes IGN] polluant [Termes IGN] pollution des sols Numéro de notice : C2020-026 Affiliation des auteurs : UGE-LaSTIG (2020- ) Autre URL associée : vers HAL Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComSansActesPubliés-Unpublished DOI : sans En ligne : https://hal.archives-ouvertes.fr/hal-03198895/file/AGEE - Fusion entre bases de  [...] Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97635

Mapping dead forest cover using a deep convolutional neural network and digital aerial photography / Jean-Daniel Sylvain in ISPRS Journal of photogrammetry and remote sensing, vol 156 (October 2019)  

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Cognitive aspects of human-computer interaction for GIS / Dieter Fritsch (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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GIS Coop: networks of silvicultural trials for supporting forest management under changing environment / Ingrid Seynave in Annals of Forest Science [en ligne], vol 75 n° 2 (June 2018)  

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Within- and between-tree variation of wood density components in Pinus nigra at six sites in Portugal / Alexandra Dias in Annals of Forest Science [en ligne], vol 75 n° 2 (June 2018)  

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Contribuer à l'observation des écosystèmes forestiers [diaporama] / Fabienne Benest (2018)  

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Enjeux pour le monitoring forestier à l'échelle européenne [diaporama] / Annemarie Bastrup-Birk (2018)  

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How to enrich forest information by the analysis of the hardwood selling prices from public forests? : Case study, hardwood in Bourgogne Franche-Comte, France [diaporama] / Jean-Michel Leban (2018)  

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Interaction avec les inventaires européens : ENFIN/DIABOLO [diaporama] / Claude Vidal (2018)  

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Outil d'aide à la décision pour les territoires forestiers (exemple du Plan d’Approvisionnement Territorial du PNR des Boucles de la Seine Normande) [diaporama] / Silvère Gabet (2018)  

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