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Expansion tendancielle du stock de bois dans les forêts françaises (1976–2015) [diaporama] / Jean-Daniel Bontemps (2018)
Titre : Expansion tendancielle du stock de bois dans les forêts françaises (1976–2015) [diaporama] Type de document : Article/Communication Auteurs : Jean-Daniel Bontemps , Auteur ; Anaïs Denardou-Tisserand , Auteur ; Jean-Luc Dupouey, Auteur Editeur : Saint-Mandé : Institut national de l'information géographique et forestière - IGN (2012-) Année de publication : 2018 Conférence : IGN - EcoFor 2018, Colloque 60 ans d’inventaire forestier pour éclairer l’avenir 15/10/2018 16/10/2018 Paris France open access proceedings Importance : 33 p. Format : 21 x 30 cm Langues : Français (fre) Descripteur : [Termes IGN] bois sur pied
[Termes IGN] forêt alpestre
[Termes IGN] forêt de feuillus
[Termes IGN] forêt domaniale
[Termes IGN] forêt privée
[Termes IGN] grande région écologique
[Termes IGN] politique forestière
[Termes IGN] puits de carbone
[Termes IGN] résineux
[Termes IGN] ressources forestières
[Vedettes matières IGN] Inventaire forestierNuméro de notice : C2018-105 Affiliation des auteurs : LIF+Ext (2012-2019) Thématique : FORET Nature : Communication nature-HAL : ComSansActesPubliés-Unpublished DOI : sans En ligne : https://inventaire-forestier.ign.fr/IMG/pdf/02_expansion_foret_metropole_jdbonte [...] Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97509 Geometric multi-wavelet total variation for SAR image time series analysis / Abdourrahmane M. Atto (2018)
Titre : Geometric multi-wavelet total variation for SAR image time series analysis Type de document : Article/Communication Auteurs : Abdourrahmane M. Atto, Auteur ; Anoumou Kemavo, Auteur ; Jean-Paul Rudant , Auteur ; Grégoire Mercier, Auteur Editeur : Chambéry : Université de Savoie Année de publication : 2018 Conférence : FUSION 2018, 21th International Conference on Information Fusion 10/07/2018 13/07/2018 Cambridge Royaume-Uni Proceedings IEEE Projets : PHOENIX / Atto, Abdourrahmane M. Importance : pp Note générale : bibliographie
Projet PHOENIX ANR-15-CE23-00Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] Amazonie
[Termes IGN] forêt tropicale
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-SAR
[Termes IGN] Oyapoc (fleuve)
[Termes IGN] série temporelleRésumé : (auteur) A time series issued from modern synthetic aperture radar satellite imaging sensors is a huge dataset composed by many hundreds of million pixels when observing large-scale earth structures such as big forests or glaciers. A concise monitoring of these large scale structures for anomaly spotting thus requires loading and analyzing huge spatio/polarimetric multi-temporal image series. The contributions of the present paper for the sake of parsimonious analysis of such huge datasets are associated with a framework having two main processing stages. The first stage is the derivation of an index called geometric multi-wavelet total variation for fast and robust anomaly spotting. This index is useful for identifying significant abnormal patterns appearing as geo-spatial non-stationarities in multi-wavelet total variation map. The second stage consists in the proposal of a concise asymmetric multi-date change information matrix on regions associated with significant multi-wavelet total variations. This stage is necessary for a fine characterization of change impacts on existing geo-spatial structures. Experimental tests based on Sentinel-1 data show relevant results on a wide Amazonian forest surrounding the Franco-Brazilian Oyapock Bridge. Numéro de notice : C2018-125 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.23919/ICIF.2018.8455223 Date de publication en ligne : 06/09/2018 En ligne : https://doi.org/10.23919/ICIF.2018.8455223 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100016 Realizing mitigation efficiency of European commercial forests by climate smart forestry / Rasoul Yousefpour in Scientific reports, vol 8 (2018)
[article]
Titre : Realizing mitigation efficiency of European commercial forests by climate smart forestry Type de document : Article/Communication Auteurs : Rasoul Yousefpour, Auteur ; Andrey Lessa Derci Augustynczik, Auteur ; Christopher P.O. Reyer, Auteur ; Petra Lasch-Born, Auteur ; Felicitas Suckow, Auteur ; Marc Hanewinkel, Auteur Année de publication : 2018 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] changement climatique
[Termes IGN] croissance des arbres
[Termes IGN] Europe (géographie politique)
[Termes IGN] foresterie
[Termes IGN] forêt boréale
[Termes IGN] forêt tempérée
[Termes IGN] Picea abies
[Termes IGN] Pinus sylvestris
[Termes IGN] puits de carbone
[Termes IGN] ressources forestières
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) European temperate and boreal forests sequester up to 12% of Europe’s annual carbon emissions. Forest carbon density can be manipulated through management to maximize its climate mitigation potential, and fast-growing tree species may contribute the most to Climate Smart Forestry (CSF) compared to slow-growing hardwoods. This type of CSF takes into account not only forest resource potentials in sequestering carbon, but also the economic impact of regional forest products and discounts both variables over time. We used the process-based forest model 4 C to simulate European commercial forests’ growth conditions and coupled it with an optimization algorithm to simulate the implementation of CSF for 18 European countries encompassing 68.3 million ha of forest (42.4% of total EU-28 forest area). We found a European CSF policy that could sequester 7.3–11.1 billion tons of carbon, projected to be worth 103 to 141 billion euros in the 21st century. An efficient CSF policy would allocate carbon sequestration to European countries with a lower wood price, lower labor costs, high harvest costs, or a mixture thereof to increase its economic efficiency. This policy prioritized the allocation of mitigation efforts to northern, eastern and central European countries and favored fast growing conifers Picea abies and Pinus sylvestris to broadleaves Fagus sylvatica and Quercus species. Numéro de notice : A2018-010 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89003
in Scientific reports > vol 8 (2018)[article]Tree species classification using within crown localization of waveform LiDAR attributes / Rosmarie Blomley in ISPRS Journal of photogrammetry and remote sensing, vol 133 (November 2017)
[article]
Titre : Tree species classification using within crown localization of waveform LiDAR attributes Type de document : Article/Communication Auteurs : Rosmarie Blomley, Auteur ; Aarne Hovi, Auteur ; Martin Weinmann, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 142 - 156 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse multiéchelle
[Termes IGN] Betula pendula
[Termes IGN] betula pubescens
[Termes IGN] croissance des arbres
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] espèce végétale
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] forêt boréale
[Termes IGN] Norvège
[Termes IGN] Picea abies
[Termes IGN] Pinus sylvestris
[Termes IGN] rotation d'objetRésumé : (Auteur) Since forest planning is increasingly taking an ecological, diversity-oriented perspective into account, remote sensing technologies are becoming ever more important in assessing existing resources with reduced manual effort. While the light detection and ranging (LiDAR) technology provides a good basis for predictions of tree height and biomass, tree species identification based on this type of data is particularly challenging in structurally heterogeneous forests. In this paper, we analyse existing approaches with respect to the geometrical scale of feature extraction (whole tree, within crown partitions or within laser footprint) and conclude that currently features are always extracted separately from the different scales. Since multi-scale approaches however have proven successful in other applications, we aim to utilize the within-tree-crown distribution of within-footprint signal characteristics as additional features. To do so, a spin image algorithm, originally devised for the extraction of 3D surface features in object recognition, is adapted. This algorithm relies on spinning an image plane around a defined axis, e.g. the tree stem, collecting the number of LiDAR returns or mean values of returns attributes per pixel as respective values. Based on this representation, spin image features are extracted that comprise only those components of highest variability among a given set of library trees. The relative performance and the combined improvement of these spin image features with respect to non-spatial statistical metrics of the waveform (WF) attributes are evaluated for the tree species classification of Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) Karst.) and Silver/Downy birch (Betula pendula Roth/Betula pubescens Ehrh.) in a boreal forest environment. This evaluation is performed for two WF LiDAR datasets that differ in footprint size, pulse density at ground, laser wavelength and pulse width. Furthermore, we evaluate the robustness of the proposed method with respect to internal parameters and tree size. The results reveal, that the consideration of the crown-internal distribution of within-footprint signal characteristics captured in spin image features improves the classification results in nearly all test cases Numéro de notice : A2017-724 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.08.013 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.08.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88409
in ISPRS Journal of photogrammetry and remote sensing > vol 133 (November 2017) . - pp 142 - 156[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2017111 RAB Revue Centre de documentation En réserve L003 Disponible 081-2017112 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt 081-2017113 DEP-EXM Revue Saint-Mandé Dépôt en unité Exclu du prêt Significant effect of topographic normalization of airborne LiDAR data on the retrieval of plant area index profile in mountainous forests / Jing Liu in ISPRS Journal of photogrammetry and remote sensing, vol 132 (October 2017)
[article]
Titre : Significant effect of topographic normalization of airborne LiDAR data on the retrieval of plant area index profile in mountainous forests Type de document : Article/Communication Auteurs : Jing Liu, Auteur ; Andrew K. Skidmore, Auteur ; Marco Heurich, Auteur ; Tiejun Wang, Auteur Année de publication : 2017 Article en page(s) : pp 77 - 87 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] Allemagne
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt alpestre
[Termes IGN] hauteur des arbres
[Termes IGN] lever topographique
[Termes IGN] normalisation
[Termes IGN] reliefRésumé : (Auteur) As an important metric for describing vertical forest structure, the plant area index (PAI) profile is used for many applications including biomass estimation and wildlife habitat assessment. PAI profiles can be estimated with the vertically resolved gap fraction from airborne LiDAR data. Most research utilizes a height normalization algorithm to retrieve local or relative height by assuming the terrain to be flat. However, for many forests this assumption is not valid. In this research, the effect of topographic normalization of airborne LiDAR data on the retrieval of PAI profile was studied in a mountainous forest area in Germany. Results show that, although individual tree height may be retained after topographic normalization, the spatial arrangement of trees is changed. Specifically, topographic normalization vertically condenses and distorts the PAI profile, which consequently alters the distribution pattern of plant area density in space. This effect becomes more evident as the slope increases. Furthermore, topographic normalization may also undermine the complexity (i.e., canopy layer number and entropy) of the PAI profile. The decrease in PAI profile complexity is not solely determined by local topography, but is determined by the interaction between local topography and the spatial distribution of each tree. This research demonstrates that when calculating the PAI profile from airborne LiDAR data, local topography needs to be taken into account. We therefore suggest that for ecological applications, such as vertical forest structure analysis and modeling of biodiversity, topographic normalization should not be applied in non-flat areas when using LiDAR data. Numéro de notice : A2017-639 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.08.005 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.08.005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86992
in ISPRS Journal of photogrammetry and remote sensing > vol 132 (October 2017) . - pp 77 - 87[article]Réservation
Réserver ce documentExemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2017101 RAB Revue Centre de documentation En réserve L003 Disponible 081-2017102 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt 081-2017103 DEP-EXM Revue Saint-Mandé Dépôt en unité Exclu du prêt Strong gradients in forest sensitivity to climate change revealed by dynamics of forest fire cycles in the post Little Ice Age Era / Igor Drobyshev in Journal of geophysical research : Biogeosciences, vol 122 n° 10 (October 2017)PermalinkTree size thresholds produce biased estimates of forest biomass dynamics / Eric B. Searle in Forest ecology and management, vol 400 (15 September 2017)PermalinkForest canopy height estimation using satellite laser altimetry : a case study in the Western Ghats, India / S.M. Ghosh in Applied geomatics, vol 9 n° 3 (September 2017)PermalinkImage matching as a data source for forest inventory – Comparison of semi-global matching and next-generation automatic terrain extraction algorithms in a typical managed boreal forest environment / Mari Kukkonen in International journal of applied Earth observation and geoinformation, vol 60 (August 2017)PermalinkChange detection in forests and savannas using statistical analysis based on geographical objects / Lucilia Rezende Leite in Boletim de Ciências Geodésicas, vol 23 n° 2 (abr - jun 2017)PermalinkFeasibility of Terrestrial laser scanning for collecting stem volume information from single trees / Ninni Saarinen in ISPRS Journal of photogrammetry and remote sensing, vol 123 (January 2017)PermalinkModéliser et quantifier les services écosystémiques forestiers à l’échelle des petits territoires / Thomas Cordonnier in Sciences, eaux & territoires, n° 21 (décembre 2016)PermalinkThe 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)PermalinkAboveground biomass mapping in French Guiana by combining remote sensing, forest inventories and environmental data / Ibrahim Fayad in International journal of applied Earth observation and geoinformation, vol 52 (October 2016)PermalinkAutomatic segment-level tree species recognition using high resolution aerial winter imagery / Anton Kuzmin in European journal of remote sensing, vol 49 n° 1 (2016)Permalink