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Latent heat flux variability and response to drought stress of black poplar: A multi-platform multi-sensor remote and proximal sensing approach to relieve the data scarcity bottleneck / Flavia Tauro in Remote sensing of environment, vol 268 (January 2022)
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Titre : Latent heat flux variability and response to drought stress of black poplar: A multi-platform multi-sensor remote and proximal sensing approach to relieve the data scarcity bottleneck Type de document : Article/Communication Auteurs : Flavia Tauro, Auteur ; Antonino Maltese, Auteur ; Roberto Giannini, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 112771 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] bioénergie
[Termes IGN] évapotranspiration
[Termes IGN] gestion de l'eau
[Termes IGN] image captée par drone
[Termes IGN] image satellite
[Termes IGN] irrigation
[Termes IGN] Piémont (Italie)
[Termes IGN] Populus nigra
[Termes IGN] sécheresse
[Termes IGN] stress hydriqueRésumé : (auteur) High-throughput mapping of latent heat flux (λET) is critical to efforts to optimize water resources management and to accelerate forest tree breeding for improved drought tolerance. Ideally, investigation of the energy response at the tree level may promote tailored irrigation strategies and, thus, maximize crop biomass productivity. However, data availability is limited and planning experimental campaigns in the field can be highly operationally complex. To this end, a multi-platform multi-sensor observational approach is herein developed to dissect the λET signature of a black poplar (Populus nigra) breeding population (“POP6”) at the canopy level. POP6 comprised more than 4600 trees representing 503 replicated genotypes, whose parents were derived from contrasting environmental conditions. Trees were trialed in two adjacent plots where different irrigation treatments (moderate drought [mDr] and well-watered [WW]) were applied. Data collected from satellite and unmanned aerial vehicles (UAVs) remote sensing as well as from ground-based proximal sensors were integrated at consistent spatial aggregation and combined to compute the surface energy balance of the trees through a modified Priestley-Taylor method. Here, we demonstrated that λET response was significantly different between WW and mDr trees, whereby genotypes in mDr conditions exhibited larger standard deviations. Importantly, genotypes classified as drought tolerant based on the stress susceptibility index (SSI) presented λET values significantly higher than the rest of the population. This study confirmed that water limitation in mDr settings led to reduced soil moisture in the tree root zone and, thus, to lower λET. These results pave the way to breeding poplar and other bioenergy crops with this underexploited trait for higher λET. Most notably, the illustrated work demonstrates a multi-platform multi-sensor data fusion approach to tackle the global challenge of monitoring landscape-scale ecosystem processes at fine resolution. Numéro de notice : A2022-087 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2021.112771 Date de publication en ligne : 05/11/2021 En ligne : https://doi.org/10.1016/j.rse.2021.112771 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99496
in Remote sensing of environment > vol 268 (January 2022) . - n° 112771[article]Detection of aspen in conifer-dominated boreal forests with seasonal multispectral drone image point clouds / Alwin A. Hardenbol in Silva fennica, vol 55 n° 4 (September 2021)
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Titre : Detection of aspen in conifer-dominated boreal forests with seasonal multispectral drone image point clouds Type de document : Article/Communication Auteurs : Alwin A. Hardenbol, Auteur ; Anton Kuzmin, Auteur ; Lauri Korhonen, Auteur ; Pasi Korpelainen, Auteur ; Timo Kumpula, Auteur ; Matti Maltamo, Auteur ; Jari Kouki, Auteur Année de publication : 2021 Article en page(s) : n° 10515 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] aire protégée
[Termes IGN] analyse discriminante
[Termes IGN] Betula (genre)
[Termes IGN] détection d'arbres
[Termes IGN] forêt boréale
[Termes IGN] image captée par drone
[Termes IGN] image multibande
[Termes IGN] orthoimage couleur
[Termes IGN] peuplement mélangé
[Termes IGN] Picea abies
[Termes IGN] Pinus sylvestris
[Termes IGN] Populus tremula
[Termes IGN] semis de points
[Termes IGN] variation saisonnièreRésumé : (auteur) Current remote sensing methods can provide detailed tree species classification in boreal forests. However, classification studies have so far focused on the dominant tree species, with few studies on less frequent but ecologically important species. We aimed to separate European aspen (Populus tremula L.), a biodiversity-supporting tree species, from the more common species in European boreal forests (Pinus sylvestris L., Picea abies [L.] Karst., Betula spp.). Using multispectral drone images collected on five dates throughout one thermal growing season (May–September), we tested the optimal season for the acquisition of mono-temporal data. These images were collected from a mature, unmanaged forest. After conversion into photogrammetric point clouds, we segmented crowns manually and automatically and classified the species by linear discriminant analysis. The highest overall classification accuracy (95%) for the four species as well as the highest classification accuracy for aspen specifically (user’s accuracy of 97% and a producer’s accuracy of 96%) were obtained at the beginning of the thermal growing season (13 May) by manual segmentation. On 13 May, aspen had no leaves yet, unlike birches. In contrast, the lowest classification accuracy was achieved on 27 September during the autumn senescence period. This is potentially caused by high intraspecific variation in aspen autumn coloration but may also be related to our date of acquisition. Our findings indicate that multispectral drone images collected in spring can be used to locate and classify less frequent tree species highly accurately. The temporal variation in leaf and canopy appearance can alter the detection accuracy considerably. Numéro de notice : A2021-735 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14214/sf.10515 Date de publication en ligne : 14/07/2021 En ligne : https://doi.org/10.14214/sf.10515 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98691
in Silva fennica > vol 55 n° 4 (September 2021) . - n° 10515[article]Variation in morphological and wood cell traits in coppice stems of Populus nigra L. and Salix alba L. / Seray Özden in Journal of forest science, vol 67 n° 8 (August 2021)
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Titre : Variation in morphological and wood cell traits in coppice stems of Populus nigra L. and Salix alba L. Type de document : Article/Communication Auteurs : Seray Özden, Auteur Année de publication : 2021 Article en page(s) : pp 396 - 407 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] anatomie du bois
[Termes IGN] cerne
[Termes IGN] croissance végétale
[Termes IGN] densité du bois
[Termes IGN] Populus nigra
[Termes IGN] qualité du bois
[Termes IGN] Salix alba
[Termes IGN] taillis
[Termes IGN] Turquie
[Vedettes matières IGN] SylvicultureRésumé : (auteur) Coppice management is an ecologically important silvicultural practice to provide the quicker and higher potential of wood biomass production for industrial demands. Understanding morphological and anatomical responses of coppiced trees could help to determine the quantity and quality of wood and thus provide better management of coppiced tree plantations for short-time biomass production. However, there is a little investigation in morphological and anatomical adaptation in different fast-growing tree species. The present study, therefore, studied how morphology and anatomy vary between two fast-growing coppices of Populus nigra L. (black poplar) and Salix alba L. (white willow). Each coppiced tree was grown in a similar habitat and was at a similar age. However, each coppiced tree showed different morphological and anatomical plasticity in their stems in response to environmental factors. Poplar coppices showed better anatomical properties due to greater vessel diameter, fibre length, fibre width, fibre wall thickness, and ray height; however willow coppices had better morphological plasticity which had higher average stem height and ring width. The results suggest that willow coppices had the greater height growth potential even at 2 years of age than poplar coppices. Numéro de notice : A2021-699 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.17221/208/2020-JFS Date de publication en ligne : 22/06/2021 En ligne : https://doi.org/10.17221/208/2020-JFS Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98561
in Journal of forest science > vol 67 n° 8 (August 2021) . - pp 396 - 407[article]Secondary metabolites in leaves of hybrid aspen are affected by the competitive status and early thinning in dense coppices / Linda Rusalepp in Annals of Forest Science [en ligne], vol 78 n° 1 (March 2021)
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Titre : Secondary metabolites in leaves of hybrid aspen are affected by the competitive status and early thinning in dense coppices Type de document : Article/Communication Auteurs : Linda Rusalepp, Auteur ; Reimo Lutter, Auteur ; Heiki Hepner, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 1 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] arbre dominant
[Termes IGN] diagnostic foliaire
[Termes IGN] éclaircie (sylviculture)
[Termes IGN] gestion forestière
[Termes IGN] peuplement mélangé
[Termes IGN] Populus tremula
[Termes IGN] taillis
[Vedettes matières IGN] SylvicultureRésumé : (auteur) Key message: Non-selective thinning of a hybrid aspen coppice stands via corridor or cross-corridor cutting impacts residual trees differently depending on their competitive status. Suppressed residual trees’ metabolic profile indicates increased stress level, especially after cross-corridor thinning.
Context: Early thinning with regular corridor harvests is proposed for the management of post-harvest re-sprouted hybrid aspen (Populus tremula L. × P. tremuloides Michx.) coppice stands. The selection of remaining trees is not size-based and their physiological acclimation to the post-thinning conditions is unknown.
Aims: To analyse differences in secondary metabolite profile between thinning treatments and trees competitive status.
Methods: We used an HPLC-qTOF mass spectrometer to analyse the leaf extracts of dominant and suppressed trees from stands with different thinning intensities: un-thinned control with basal area of 15.4 ± 1.52 m2 ha−1, corridor thinning with basal area of 8.5 ± 0.46 m2 ha−1 and cross-corridor thinning with basal area of 3.9 ± 0.34 m2 ha−1.
Results: Competitive status and thinning treatment both had significant effects on the contents of compounds. Higher exposure to irradiance increased the contents of flavonoids and hydroxycinnamates. Corridor thinning treatments doubled the foliar contents of secondary metabolites and lowered macronutrient contents in competitively suppressed residual trees. Dominant residual trees were not affected in this respect.
Conclusion: Forest management practice and competitive status can significantly modify the metabolite profile in tree leaves. After corridor thinning of a young aspen coppice stand, the small-sized residual trees may initially respond with increased allocation to leaf chemical defence rather than to productivity.Numéro de notice : A2021-030 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-01014-3 Date de publication en ligne : 05/01/2021 En ligne : https://doi.org/10.1007/s13595-020-01014-3 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96722
in Annals of Forest Science [en ligne] > vol 78 n° 1 (March 2021) . - n° 1[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)
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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 d'arbres décisionnels
[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 temporelleRésumé : (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
in ISPRS Journal of photogrammetry and remote sensing > vol 171 (January 2021) . - pp 76 - 100[article]Réservation
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PermalinkGround-based remote sensing of forests exploiting GNSS signals / Leila Guerriero in IEEE Transactions on geoscience and remote sensing, vol 58 n° 10 (October 2020)
PermalinkGrowth parameters and resistance to Sphaerulina musiva-induced canker are more important than wood density for increasing genetic gain from selection of Populus spp. hybrids for northern climates / Marzena Niemczyk in Annals of Forest Science [en ligne], Vol 77 n° 2 (June 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)
PermalinkThe effects of different combinations of simulated climate change-related stressors on juveniles of seven forest tree species grown as mono-species and mixed cultures / Alfas Pliüra in Baltic forestry, vol 26 n° 1 (2020)
PermalinkPermalinkClassification of poplar trees with object-based ensemble learning algorithms using Sentinel-2A imagery / H. Tombul in Journal of geodetic science, vol 10 n° 1 (January 2020)
PermalinkPermalinkTélédétection des habitats insulaires ligériens par drone : Retour d’expérience sur les îles de Mareau-aux-Prés (Loiret) / Hilaire Martin in Revue forestière française [en ligne], vol 71 n° 6 (2019)
PermalinkThe utility of terrestrial photogrammetry for assessment of tree volume and taper in boreal mixedwood forests / Christopher Mulverhill in Annals of Forest Science [en ligne], Vol 76 n° 3 (September 2019)
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