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Direct analysis in real-time (DART) time-of-flight mass spectrometry (TOFMS) of wood reveals distinct chemical signatures of two species of Afzelia / Peter Kitin in Annals of Forest Science [en ligne], vol 78 n° 2 (June 2021)  

Public [article]  inAnnals of Forest Science [en ligne] > vol 78 n° 2 (June 2021) . - Article 31 Titre : Direct analysis in real-time (DART) time-of-flight mass spectrometry (TOFMS) of wood reveals distinct chemical signatures of two species of Afzelia Type de document : Article/Communication Auteurs : Peter Kitin, Auteur ; Edgard Espinoza, Auteur ; Hans Beeckman, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : Article 31 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes descripteurs IGN] abattage (sylviculture) [Termes descripteurs IGN] Afzelia (genre) [Termes descripteurs IGN] analyse discriminante [Termes descripteurs IGN] apprentissage non-dirigé [Termes descripteurs IGN] bois [Termes descripteurs IGN] espèce végétale [Termes descripteurs IGN] forêt tropicale [Termes descripteurs IGN] identification de plantes [Termes descripteurs IGN] signature spectrale [Termes descripteurs IGN] spectrométrie [Termes descripteurs IGN] taxinomie [Termes descripteurs IGN] temps réel Résumé : (Auteur) Distinct chemical fingerprints of the wood of Afzelia pachyloba and A. bipindensis demonstrated an effective method for identifying these two commercially important species. Direct analysis in real-time (DART) time-of-flight mass spectrometry (TOFMS) allowed high-throughput examination of chemotypes with vast potential in taxonomic, ecological, and forensic research of wood. Context : Afzelia is a genus of valuable tropical timber trees. Accurate identification of wood is required for the prevention of illicit timber trade as well as for certification purposes in the forest and wood products industry. For many years, particular interest has been focused on attempts to distinguish the wood of A. bipindensis Harms from A. pachyloba Harms due to substantial differences in the commercial values of these two species. Aims : We investigated if wood chemical signatures and microscopy could identify the wood of A. bipindensis and A. pachyloba. Methods : We used two approaches, namely metabolome profiling by direct analysis in real-time (DART) time-of-flight mass spectrometry (TOFMS) and wood microstructure by light microscopy and SEM. In all, we analyzed samples from 89 trees of A. bipindensis, and A. pachyloba. Results : The two species could not be separated by the IAWA standard microscopic wood features. SEM analysis showed considerable variation in the morphology of vestured pits; however, this variation was not species-specific. In contrast, DART-TOFMS followed by unsupervised statistics (Discriminant Analysis of Principal Components) showed distinct metabolome signatures of the two species. Conclusion : DART-TOFMS provides a rapid method for wood identification that can be easily applied to small heartwood samples. Time- and cost-effective classification of wood chemotypes by DART-TOFMS can have potential applications in various research questions in forestry, wood science, tree-ecophysiology, and forensics. Numéro de notice : A2021-327 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-01024-1 date de publication en ligne : 31/03/2021 En ligne : https://doi.org/10.1007/s13595-020-01024-1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97488 [article]

Tropical forest canopy height estimation from combined polarimetric SAR and LiDAR using machine-learning / Maryam Pourshamsi in ISPRS Journal of photogrammetry and remote sensing, vol 172 (February 2021)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 172 (February 2021) . - pp 79 - 94 Titre : Tropical forest canopy height estimation from combined polarimetric SAR and LiDAR using machine-learning Type de document : Article/Communication Auteurs : Maryam Pourshamsi, Auteur ; Junshi Xia, Auteur ; Naoto Yokoya, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 79 - 94 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] apprentissage automatique [Termes descripteurs IGN] bande L [Termes descripteurs IGN] canopée [Termes descripteurs IGN] classification par forêts aléatoires [Termes descripteurs IGN] classification par séparateurs à vaste marge [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données polarimétriques [Termes descripteurs IGN] forêt tropicale [Termes descripteurs IGN] Gabon [Termes descripteurs IGN] hauteur des arbres [Termes descripteurs IGN] image captée par drone [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] Rotation Forest classification [Termes descripteurs IGN] semis de points Résumé : (auteur) Forest height is an important forest biophysical parameter which is used to derive important information about forest ecosystems, such as forest above ground biomass. In this paper, the potential of combining Polarimetric Synthetic Aperture Radar (PolSAR) variables with LiDAR measurements for forest height estimation is investigated. This will be conducted using different machine learning algorithms including Random Forest (RFs), Rotation Forest (RoFs), Canonical Correlation Forest (CCFs) and Support Vector Machine (SVMs). Various PolSAR parameters are required as input variables to ensure a successful height retrieval across different forest heights ranges. The algorithms are trained with 5000 LiDAR samples (less than 1% of the full scene) and different polarimetric variables. To examine the dependency of the algorithm on input training samples, three different subsets are identified which each includes different features: subset 1 is quiet diverse and includes non-vegetated region, short/sparse vegetation (0–20 m), vegetation with mid-range height (20–40 m) to tall/dense ones (40–60 m); subset 2 covers mostly the dense vegetated area with height ranges 40–60 m; and subset 3 mostly covers the non-vegetated to short/sparse vegetation (0–20 m) .The trained algorithms were used to estimate the height for the areas outside the identified subset. The results were validated with independent samples of LiDAR-derived height showing high accuracy (with the average R2 = 0.70 and RMSE = 10 m between all the algorithms and different training samples). The results confirm that it is possible to estimate forest canopy height using PolSAR parameters together with a small coverage of LiDAR height as training data. Numéro de notice : A2021-086 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.11.008 date de publication en ligne : 19/12/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.11.008 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96846 [article]

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Individual tree diameter growth modeling system for Dalat pine (Pinus dalatensis Ferré) of the upland mixed tropical forests / Bao Huy in Forest ecology and management, vol 480 (15 January 2021)  

Public [article]  inForest ecology and management > vol 480 (15 January 2021) . - n° 118612 Titre : Individual tree diameter growth modeling system for Dalat pine (Pinus dalatensis Ferré) of the upland mixed tropical forests Type de document : Article/Communication Auteurs : Bao Huy, Auteur ; Le Canh nam, Auteur ; Krishna P. Poudel, Auteur ; Hailemariam Temesgen, Auteur Année de publication : 2021 Article en page(s) : n° 118612 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Végétation [Termes descripteurs IGN] cerne [Termes descripteurs IGN] conservation de la flore [Termes descripteurs IGN] croissance végétale [Termes descripteurs IGN] diamètre à hauteur de poitrine [Termes descripteurs IGN] facteur édaphique [Termes descripteurs IGN] flore endémique [Termes descripteurs IGN] forêt tropicale [Termes descripteurs IGN] modèle de croissance [Termes descripteurs IGN] Pinus (genre) [Termes descripteurs IGN] Viet Nam Résumé : (auteur) Pinus dalatensis Ferré (Dalat pine, or five-needle pine, locally) is an endemic large tree species of Vietnam that has both high timber and non-timber values. It is also a rare tree species listed in the Red List of the International Union for Conservation of Nature (IUCN). The objective of this study was to develop an individual tree diameter growth modeling system to facilitate the sustainable management and conservation of this species. We used Haglöf Sweden ® increment borers to collect tree ring samples from a total of 56 trees resulting in a dataset of 4566 diameter at breast height (dbh, cm) measurements at age (t, year) and obtained the associated ecological environmental factors in three different sites in the Central Highlands, Vietnam. A subset of this dataset (n = 1264) also had the climate data collected over the period of past 32–38 years (from 1980 to 2011 and from 1979 to 2016). Weighted mixed-effects models were used to model Dalat pine trees growth and account for autocorrelation and heteroscedasticity of the dbh measurements. Cross validation over 200 realizations were used to select the best equation form of dbh growth and incorporate the environmental effects and climatic factors that help improve reliability of the models. Under the mixed-effects modeling paradigm, the Mitscherlich equation fitted with random effects of ecological environmental factors (eco-subregions and altitude) and climatic factors (temperature, humidity, and temperature in dry and in rainy seasons) produced the best results. Whereas, under the fixed-effect modeling paradigm, the models that used the exponential function of environmental or climatic factors as the modifiers of an average diameter growth performed the best (Bias = −5.9% and RMSE = 10.0 cm). The models developed in this study will be useful for forecasting growth and for silvicultural planning under shifting environment and climate and are expected to contribute to the sustainable management of this endemic species. Numéro de notice : A2021-063 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.foreco.2020.118612 date de publication en ligne : 08/10/2020 En ligne : https://doi.org/10.1016/j.foreco.2020.118612 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96743 [article]

Near-real-time identification of the drivers of deforestation in French Guiana / Marie Ballère (2021)  

Public Titre : Near-real-time identification of the drivers of deforestation in French Guiana Type de document : Article/Communication Auteurs : Marie Ballère , Auteur ; Stéphane Mermoz, Auteur ; Alexandre Bouvet, Auteur ; Thierry Koleck, Auteur Editeur : Munich [Allemagne] : European Geosciences Union EGU Année de publication : 2021 Conférence : EGU 2021, General Assembly 19/04/2021 30/04/2021 en ligne OA Abstracts only Format : 21 x 30 cm Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] déboisement [Termes descripteurs IGN] exploitation forestière [Termes descripteurs IGN] forêt tropicale [Termes descripteurs IGN] Guyane (département français) [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] image Sentinel-SAR [Termes descripteurs IGN] mine d'or [Termes descripteurs IGN] surveillance forestière [Termes descripteurs IGN] urbanisation Numéro de notice : C2021-004 Affiliation des auteurs : UGE-LaSTIG+Ext (2020- ) Thématique : BIODIVERSITE/FORET/IMAGERIE Nature : Communication nature-HAL : ComSansActesPubliés-Unpublished DOI : sans En ligne : https://doi.org/10.5194/egusphere-egu21-16015 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97598

SAR data for tropical forest disturbance alerts in French Guiana: Benefit over optical imagery / Marie Ballère in Remote sensing of environment, Vol 252 (January 2021)  

Public [article]  inRemote sensing of environment > Vol 252 (January 2021) . - n° 112159 Titre : SAR data for tropical forest disturbance alerts in French Guiana: Benefit over optical imagery Type de document : Article/Communication Auteurs : Marie Ballère , Auteur ; Alexandre Bouvet, Auteur ; Stéphane Mermoz, Auteur ; Thuy Le Toan, Auteur ; Thierry Koleck, Auteur ; Caroline Bedeau, Auteur ; Mathilde André, Auteur ; Elodie Forestier, Auteur ; Pierre-Louis Frison , Auteur ; Cédric Lardeux, Auteur Année de publication : 2021 Projets : 1-Pas de projet / Article en page(s) : n° 112159 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] forêt tropicale [Termes descripteurs IGN] Guyane (département français) [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] image Sentinel-SAR [Termes descripteurs IGN] surveillance forestière [Termes descripteurs IGN] temps réel Résumé : (auteur) French Guiana forests cover 8 million hectares. With 98% of emerged land covered by forests, French Guiana is the area with the highest proportion of forest cover in the world. These forests are home to an exceptionally rich and diverse wealth of biodiversity that is both vulnerable and under threat due to high levels of pressure from human activity. As part of the French territory, French Guiana benefits from determined and continuous national efforts in the preservation of biodiversity and the environmental functionalities of ecosystems. The loss and fragmentation of forest cover caused by gold mining (legal and illegal), smallholder agriculture and forest exploitation, are considered as small-scale disturbances, although representing strong effects to vulnerable natural habitats, landscapes, and local populations. To monitor forest management programs and combat illegal deforestation and forest opening near-real time alerts system based on remote sensing data are required. For this large territory under frequent cloud cover, Synthetic-Aperture Radar (SAR) data appear to be the best adapted. In this paper, a method for forest alerts in a near-real time context based on Sentinel-1 data over the whole of French Guiana (83,534 km2) was developed and evaluated. The assessment was conducted for 2 years between 2016 and 2018 and includes comparisons with reference data provided by French Guiana forest organizations and comparisons with the existing University of Maryland Global Land Analysis and Discovery Forest Alerts datasets based on Landsat data. The reference datasets include 1,867 plots covering 2,124.5 ha of gold mining, smallholder agriculture and forest exploitation. The validation results showed high user accuracies (96.2%) and producer accuracies (81.5%) for forest loss detection, with the latter much higher than for optical forest alerts (36.4%). The forest alerts maps were also compared in terms of detection timing, showing systematic temporal delays of up to one year in the optical method compared to the SAR method. These results highlight the benefits of SAR over optical imagery for forest alerts detection in French Guiana. Finally, the potential of the SAR method applied to tropical forests is discussed. The SAR-based map of this study is available on http://cesbiomass.net/. Numéro de notice : A2021-066 Affiliation des auteurs : UGE-LaSTIG+Ext (2020- ) Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2020.112159 date de publication en ligne : 05/11/2020 En ligne : https://doi.org/10.1016/j.rse.2020.112159 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96937 [article]

Mapping tree species deciduousness of tropical dry forests combining reflectance, spectral unmixing, and texture data from high-resolution imagery / Astrid Helena Huechacona-Ruiz in Forests, vol 11 n°11 (November 2020)  

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Wide-area near-real-time monitoring of tropical forest degradation and deforestation using Sentinel-1 / Dirk Hoekman in Remote sensing, vol 12 n° 19 (October 2020)  

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Evaluating the impact of declining tsetse fly (Glossina pallidipes) habitat in the Zambezi valley of Zimbabwe / Farai Matawa in Geocarto international, vol 35 n° 12 ([01/09/2020])  

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Improved supervised learning-based approach for leaf and wood classification from LiDAR point clouds of forests / Sruthi M. Krishna Moorthy in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)  

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Warming effects on morphological and physiological performances of four subtropical montane tree species Authors Authors and affiliations / Yiyong Li in Annals of Forest Science [en ligne], Vol 77 n° 1 (March 2020)  

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Can 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])  

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Individual tree crown segmentation in tropical peat swamp forest using airborne hyperspectral data / Sitinor Atikah Nordin in Geocarto international, vol 34 n° 11 ([15/08/2019])  

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Monitoring the structure of forest restoration plantations with a drone-lidar system / D.R.A. Almeida in International journal of applied Earth observation and geoinformation, vol 79 (July 2019)  

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Object-based random forest modelling of aboveground forest biomass outperforms a pixel-based approach in a heterogeneous and mountain tropical environment / Eduarda M.O. Silveira in International journal of applied Earth observation and geoinformation, vol 78 (June 2019)  

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Estimating architecture-based metabolic scaling exponents of tropical trees using terrestrial LiDAR and 3D modelling / Alvaro Lau in Forest ecology and management, vol 439 (1 May 2019)  

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