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L’inventaire forestier national pour un suivi permanent, multi-échelles et multi-thématiques de la forêt française et des ressources bois mobilisables / Antoine Colin in Sciences, eaux & territoires, n° 33 (avril 2020)
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Titre : L’inventaire forestier national pour un suivi permanent, multi-échelles et multi-thématiques de la forêt française et des ressources bois mobilisables Type de document : Article/Communication Auteurs : Antoine Colin , Auteur ; Henri E. Cuny
, Auteur
Année de publication : 2020 Projets : 1-Pas de projet / Article en page(s) : pp 58 - 62 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Termes IGN] bois sur pied
[Termes IGN] changement climatique
[Termes IGN] coupe (sylviculture)
[Termes IGN] effet de serre
[Termes IGN] expertise
[Termes IGN] forêt
[Termes IGN] France (végétation)
[Termes IGN] politique forestière
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) Depuis 1908, la surface forestière française a augmenté de 5,1 millions d’hectares, passant de 10,3 à 15,4 millions d’hectares. Le stock de bois sur pied a quant à lui progressé de 950 millions de mètres cube au cours des trente-cinq dernières années. En parallèle, les attentes des acteurs économiques et de la société ont évolué pour répondre à de nouveaux défis : atténuation de l’effet de serre dans le contexte du changement climatique, émergence de la bioéconomie, biodiversité, etc. Pour accompagner ces évolutions sociétales, l’inventaire forestier national s’adapte en continu en s’appuyant de plus en plus sur l’expertise des partenaires de la filière. Numéro de notice : A2020-181 Affiliation des auteurs : IGN (2012-2019) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.14758/SET-REVUE.2020.3.11 Date de publication en ligne : 10/04/2020 En ligne : https://doi.org/10.14758/SET-REVUE.2020.3.11 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94952
in Sciences, eaux & territoires > n° 33 (avril 2020) . - pp 58 - 62[article]La télédétection aéroportée pour la gestion des territoires forestiers de montagne / Jean-Matthieu Monnet in Sciences, eaux & territoires, n° 33 (avril 2020)
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Titre : La télédétection aéroportée pour la gestion des territoires forestiers de montagne Type de document : Article/Communication Auteurs : Jean-Matthieu Monnet, Auteur ; Pierre Paccard, Auteur ; Catherine Riond, Auteur Année de publication : 2020 Article en page(s) : pp 64 - 69 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] abattage (sylviculture)
[Termes IGN] acquisition de données
[Termes IGN] diffusion de données
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt alpestre
[Termes IGN] France (végétation)
[Termes IGN] gestion forestière
[Termes IGN] télémétrie laser aéroportéRésumé : (Auteur) Le Programme national de la forêt et du bois 2016-2026 affiche comme objectif « d’augmenter les prélèvements de bois en France tout en assurant le renouvellement de la forêt ». Les forêts de montagne qui représentent environ un quart de la surface forestière pourraient contribuer de manière significative à cet objectif. Les contraintes d’accès et de topographie rendent cependant difficile la gestion de ces forêts. En s’appuyant sur la technologie Lidar aéroporté, il est désormais possible de cartographier à haute résolution, sur des territoires de la taille d’un parc naturel régional, les caractéristiques forestières (ressource, accessibilité) intéressant les gestionnaires. La généralisation de l’outil pose cependant des questions de coût d’acquisition des données et de droit de leur diffusion auprès des acteurs de la filière. Numéro de notice : A2020-182 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.14758/SET-REVUE.2020.3.12 Date de publication en ligne : 10/04/2020 En ligne : https://doi.org/10.14758/SET-REVUE.2020.3.12 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94956
in Sciences, eaux & territoires > n° 33 (avril 2020) . - pp 64 - 69[article]Detection of Xylella fastidiosa infection symptoms with airborne multispectral and thermal imagery: Assessing bandset reduction performance from hyperspectral analysis / T. Poblete in ISPRS Journal of photogrammetry and remote sensing, vol 162 (April 2020)
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Titre : Detection of Xylella fastidiosa infection symptoms with airborne multispectral and thermal imagery: Assessing bandset reduction performance from hyperspectral analysis Type de document : Article/Communication Auteurs : T. Poblete, Auteur ; C. Camino, Auteur ; P.S.A. Beck, Auteur Année de publication : 2020 Article en page(s) : pp 27 - 40 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] chlorophylle
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] espèce végétale
[Termes IGN] fluorescence
[Termes IGN] image hyperspectrale
[Termes IGN] image multibande
[Termes IGN] image satellite
[Termes IGN] image thermique
[Termes IGN] Italie
[Termes IGN] maladie bactérienne
[Termes IGN] maladie phytosanitaire
[Termes IGN] Olea europaea
[Termes IGN] stress hydrique
[Termes IGN] surveillance de la végétation
[Termes IGN] télédétection aérienne
[Termes IGN] traitement d'imageRésumé : (auteur) Xylella fastidiosa (Xf) is a harmful plant pathogenic bacterium, able to infect over 500 plant species worldwide. Successful eradication and containment strategies for harmful pathogens require large-scale monitoring techniques for the detection of infected hosts, even when they do not display visual symptoms. Although a previous study using airborne hyperspectral and thermal imagery has shown promising results for the early detection of Xf-infected olive (Olea europaea) trees, further work is needed when adopting these techniques for large scale monitoring using multispectral cameras on board airborne platforms and satellites. We used hyperspectral and thermal imagery collected during a two-year airborne campaign in a Xf-infected area in southern Italy to assess the performance of spectrally constrained machine-learning algorithms for this task. The algorithms were used to assess multispectral bandsets, selected from the original hyperspectral imagery, that were compatible with large-scale monitoring from unmanned platforms and manned aircraft. In addition, the contribution of solar–induced chlorophyll fluorescence (SIF) and the temperature-based Crop Water Stress Index (CWSI) retrieved from hyperspectral and thermal imaging, respectively, were evaluated to quantify their relative importance in the algorithms used to detect Xf infection. The detection performance using support vector machine algorithms decreased from ∼80% (kappa, κ = 0.42) when using the original full hyperspectral dataset including SIF and CWSI to ∼74% (κ = 0.36) when the optimal set of six spectral bands most sensitive to Xf infection were used in addition to the CWSI thermal indicator. When neither SIF nor CWSI were used, the detection yielded less than 70% accuracy (decreasing κ to very low performance, 0.29), revealing that tree temperature was more important than chlorophyll fluorescence for the Xf detection. This work demonstrates that large-scale Xf monitoring can be supported using airborne platforms carrying multispectral and thermal cameras with a limited number of spectral bands (e.g., six to 12 bands with 10 nm bandwidths) as long as they are carefully selected by their sensitivity to the Xf symptoms. More precisely, the blue (bands between 400 and 450 nm to derive the NPQI index) and thermal (to derive CWSI from tree temperature) were the most critical spectral regions for their sensitivity to Xf symptoms in olive. Numéro de notice : A2020-120 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.02.010 Date de publication en ligne : 18/02/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.02.010 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94745
in ISPRS Journal of photogrammetry and remote sensing > vol 162 (April 2020) . - pp 27 - 40[article]Size-class structure of the forests of Finland during 1921–2013: a recovery from centuries of exploitation, guided by forest policies / Helena M. Henttonen in European Journal of Forest Research, vol 139 n° 2 (April 2020)
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Titre : Size-class structure of the forests of Finland during 1921–2013: a recovery from centuries of exploitation, guided by forest policies Type de document : Article/Communication Auteurs : Helena M. Henttonen, Auteur ; Pekka Nöjd, Auteur ; Susanne Suvanto, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 279 – 293 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse diachronique
[Termes IGN] brûlis
[Termes IGN] densité de la végétation
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] échantillonnage de données
[Termes IGN] Finlande
[Termes IGN] forêt boréale
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] paturage
[Termes IGN] peuplement forestier
[Termes IGN] Picea abies
[Termes IGN] Pinus sylvestris
[Termes IGN] politique forestière
[Termes IGN] sylviculture
[Termes IGN] utilisation du sol
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Frequency distributions of tree diameters are a powerful tool for analyzing changes of tree populations in large areas. We analyzed the densities and mean volume estimates of trees in different size classes for the Finnish forests over the time-span of the National Forest Inventories (1921–2013). The results display a general increase in trees in all size classes, species group and geographical area, mainly after the 1970s. The densities of medium- and large-sized conifers showed large increases in the southern boreal subzone, spruces even more than pines. Small- to medium-sized pines have increased in the middle and northern boreal subzones. The shifts in growing stock are related to changing land use, resulting from the development of the society. The low quantities of both growing stock and large trees during the 1920s reflect a poor initial state of forests. Several land use forms of the former agriculture-based society were detrimental to forests, including slash and burn agriculture, cattle grazing and tar production. The pressure from alternative land use forms was stronger in southern Finland, where the population density (people per km2) is much higher. Between 1971 and 2013, the changes in size-class structure can be attributed mainly to intensified silviculture boosted by actions of the Finnish governments, including both legislation and financial support for management activities. Not only the development of growing stock has exceeded expectations, but the increase has also concentrated in the economically valuable trees in the large size classes. Numéro de notice : A2020-344 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s10342-019-01241-y Date de publication en ligne : 27/11/2019 En ligne : https://doi.org/10.1007/s10342-019-01241-y Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95224
in European Journal of Forest Research > vol 139 n° 2 (April 2020) . - pp 279 – 293[article]How far can we trust forestry estimates from low-density LiDAR acquisitions? The Cutfoot Sioux experimental forest (MN, USA) case study / Enrico Borgogno Mondino in International Journal of Remote Sensing IJRS, vol 41 n° 12 (20 - 30 March 2020)
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Titre : How far can we trust forestry estimates from low-density LiDAR acquisitions? The Cutfoot Sioux experimental forest (MN, USA) case study Type de document : Article/Communication Auteurs : Enrico Borgogno Mondino, Auteur ; Vanina Fissore, Auteur ; Michael J. Falkowski, Auteur ; Brian Palik, Auteur Année de publication : 2020 Article en page(s) : pp 4551 - 4569 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] auscultation topographique
[Termes IGN] diamètre des arbres
[Termes IGN] données dendrométriques
[Termes IGN] données lidar
[Termes IGN] feuillu
[Termes IGN] hauteur des arbres
[Termes IGN] image Landsat-OLI
[Termes IGN] inventaire forestier local
[Termes IGN] Minnesota (Etats-Unis)
[Termes IGN] modèle d'erreur
[Termes IGN] Pinophyta
[Termes IGN] semis de points
[Termes IGN] structure d'un peuplement forestier
[Termes IGN] surface forestière
[Termes IGN] télémètre laser aéroportéRésumé : (auteur) Aerial discrete return LiDAR (Light Detection And Ranging) technology (ALS – Aerial Laser Scanner) is now widely used for forest characterization due to its high accuracy in measuring vertical and horizontal forest structure. Random and systematic errors can still occur and these affect the native point cloud, ultimately degrading ALS data accuracy, especially when adopting datasets that were not natively designed for forest applications. A detailed understanding of how uncertainty of ALS data could affect the accuracy of derivable forest metrics (e.g. tree height, stem diameter, basal area) is required, looking for eventual error biases that can be possibly modelled to improve final accuracy. In this work a low-density ALS dataset, originally acquired by the State of Minnesota (USA) for non-forestry related purposes (i.e. topographic mapping), was processed attempting to characterize forest inventory parameters for the Cutfoot Sioux Experimental Forest (north-central Minnesota, USA). Since accuracy of estimates strictly depends on the applied species-specific dendrometric models a first required step was to map tree species over the forest. A rough classification, aiming at separating conifers from broadleaf, was achieved by processing a Landsat 8 OLI (Operational Land Imager) scene. ALS-derived forest metrics initially greatly overestimated those measured at the ground in 230 plots. Conversely, ALS-derived tree density was greatly underestimated. To reduce ALS uncertainty, trees belonging to the dominated plane were removed from the ground dataset, assuming that they could not properly be detected by low-density ALS measures. Consequently, MAE (Mean Absolute Error) values significantly decreased to 4.0 m for tree height and to 0.19 cm for diameter estimates. Remaining discrepancies were related to a bias affecting the native ALS point cloud, which was modelled and removed. Final MAE values were 1.32 m for tree height, 0.08 m for diameter, 8.5 m2 ha−1 for basal area, and 0.06 m for quadratic mean diameter. Specifically focusing on tree height and diameter estimates, the significance of differences between ground and ALS estimates was tested relative to the expected ‘best accuracy’. Results showed that after correction: 94.35% of tree height differences were lower than the corresponding reference value (2.86 m); 70% of tree diameter differences were lower than the corresponding reference value (4.5 cm for conifers and 6.8 cm for broadleaf). Finally, forest parameters were computed for the whole Cutfoot Sioux Experimental Forest. Main findings include: 1) all forest estimates based on a low-density ALS point cloud can be derived at plot level and not at a tree level; 2) tree height estimates obtained by low-density ALS point clouds at the plot level are highly reasonably accurate only after testing and modelling eventual error bias; 3) diameter, basal area, and quadratic mean diameter estimates have large uncertainties, suggesting the need for a higher point density and, probably, a better mapping of tree species (if possible) than achieved with a remote sensing-based approach. Numéro de notice : A2020-450 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431161.2020.1723173 Date de publication en ligne : 20/02/2020 En ligne : https://doi.org/10.1080/01431161.2020.1723173 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95535
in International Journal of Remote Sensing IJRS > vol 41 n° 12 (20 - 30 March 2020) . - pp 4551 - 4569[article]Can mixed pine forests conserve understory richness by improving the establishment of understory species typical of native oak forests? / Daphne Lopez-Marcos in Annals of Forest Science, Vol 77 n° 1 (March 2020)
PermalinkEffects of Quercus rubra L. on soil properties and humus forms in 50-year-old and 80-year-old forest stands of Lombardy plain / Chiara Ferré in Annals of Forest Science, Vol 77 n° 1 (March 2020)
PermalinkLarge-scale two-phase estimation of wood production by poplar plantations exploiting Sentinel-2 data as auxiliary information / Agnese Marcelli in Silva fennica, vol 54 n° 2 (March 2020)
PermalinkMulti-century reconstruction suggests complex interactions of climate and human controls of forest fire activity in a Karelian boreal landscape, North-West Russia / N. Ryzhkova in Forest ecology and management, vol 459 (1 March 2020)
PermalinkSpecies richness influences the spatial distribution of trees in European forests / Cristina Bastias in Oikos, vol 129 n° 3 (March 2020)
PermalinkWarming effects on morphological and physiological performances of four subtropical montane tree species / Yiyong Li in Annals of Forest Science, Vol 77 n° 1 (March 2020)
PermalinkAssessing forest availability for wood supply in Europe / Iciar A. Alberdi in Forest policy and economics, vol 111 (February 2020)
PermalinkCan Carbon Sequestration in Tasmanian “Wet” Eucalypt Forests Be Used to Mitigate Climate Change? Forest Succession, the Buffering Effects of Soils, and Landscape Processes Must Be Taken into Account / Peter D. McIntosh in International journal of forestry research, vol 2020 ([01/02/2020])
PermalinkForest gaps retard carbon and nutrient release from twig litter in alpine forest ecosystems / Bo Tan in European Journal of Forest Research, vol 139 n° 1 (February 2020)
PermalinkA novel fire index-based burned area change detection approach using Landsat-8 OLI data / Sicong Liu in European journal of remote sensing, vol 53 n° 1 (2020)
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