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Termes IGN > sciences naturelles > sciences de la vie > biologie > biométrie
biométrie
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biologie quantitative, biostatistique, statistique biologique. biologie, statistique. >> biomathématique. échantillonnage (statistique), statistique mathématique. >>Terme(s) spécifique(s) : analyse de survie (biométrie), génétique quantitative. Equiv. LCSH : Biometry. Domaine(s) : 510, 570. Voir aussi |
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A CNN-based approach for the estimation of canopy heights and wood volume from GEDI waveforms / Ibrahim Fayad in Remote sensing of environment, vol 265 (November 2021)
[article]
Titre : A CNN-based approach for the estimation of canopy heights and wood volume from GEDI waveforms Type de document : Article/Communication Auteurs : Ibrahim Fayad, Auteur ; Dino Lenco, Auteur ; Nicolas Baghdadi, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 112652 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] Brésil
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Eucalyptus (genre)
[Termes IGN] forme d'onde
[Termes IGN] Global Ecosystem Dynamics Investigation lidar
[Termes IGN] hauteur des arbres
[Termes IGN] modèle de croissance végétale
[Termes IGN] semis de points
[Termes IGN] volume en boisRésumé : (auteur) Full waveform (FW) LiDAR systems have proven their effectiveness to map forest biophysical variables in the last two decades, owing to their ability of measuring, with high accuracy, forest vertical structures. The Global Ecosystem Dynamics Investigation (GEDI) system on board the International Space Station (ISS) is the latest FW spaceborne LiDAR instrument for the continuous observation of Earth's forests. FW systems rely on very sophisticated pre-processing steps to generate a priori metrics in order to leverage their capabilities for the accurate estimation of the aforementioned forest characteristics. The ever-expanding volume of acquired GEDI data, which to date comprises more than 25 billion acquired unfiltered shots, and along with the pre-processed data, amounting to more than 90 TB of data, raises new challenges in terms of adapted preprocessing methods for the suitable exploitation of such a huge and complex amount of LiDAR data. To overcome the issues related to the generation of relevant metrics from GEDI data, we propose a new metric-free approach to estimate canopy dominant heights (Hdom) and wood volume (V) of Eucalyptus plantations over five different regions in Brazil. To avoid metric computation, we leverage deep learning techniques and, more in detail, convolutional neural networks with the aim to analyze the GEDI Level 1B geolocated waveforms. Performance comparisons were conducted between four convolutional neural network (CNN) variants using GEDI waveform data (either untouched, or subsetted) and a metric based Random Forest regressor (RF). Additionally, we tested if our framework can improve the generalization of the models to different distant regions. First, the models were trained using data from all the study regions. Cross validated results showed that the CNN based models compared well against their RF counterpart for both Hdom and V. The RMSE on the estimation of Hdom from the CNN based models varied between 1.54 and 1.94 m with a coefficient of determination (R2) between 0.86 and 0.91, while the RF model produced an accuracy on Hdom estimates of 1.45 m (R2 = 0.92). For V, CNN based estimations ranged from 27.76 to 33.33 m3.ha−1 (R2 between 0.82 and 0.88), while for RF, the RMSE was 27.61 m3.ha−1 (R2 = 0.88). Next, model generalization was assessed by means of a spatial transfer experiment. For Hdom, both the CNN and RF approaches showed similar performances to a global model, however, the CNN based approach showed higher variability on the estimation accuracy, and the variability was related to the forest structure between the trained and tested data (similar tree heights yield better accuracies). For the estimation of V, considering both approaches, the accuracy was dependent on the allometric relationship between Hdom and V in the training and testing regions while lower accuracies on V were obtained when the testing and training regions exhibited a different allometric relationship. Numéro de notice : A2021-869 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2021.112652 Date de publication en ligne : 31/08/2021 En ligne : https://doi.org/10.1016/j.rse.2021.112652 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99118
in Remote sensing of environment > vol 265 (November 2021) . - n° 112652[article]Age-dependence of stand biomass in managed boreal forests based on the Finnish National Forest Inventory data / Anna Repo in Forest ecology and management, vol 498 (October-15 2021)
[article]
Titre : Age-dependence of stand biomass in managed boreal forests based on the Finnish National Forest Inventory data Type de document : Article/Communication Auteurs : Anna Repo, Auteur ; Tuomas Rajala, Auteur ; Helena M. Henttonen, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 119507 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] âge du peuplement forestier
[Termes IGN] bilan du carbone
[Termes IGN] biomasse
[Termes IGN] changement climatique
[Termes IGN] Finlande
[Termes IGN] forêt boréale
[Termes IGN] gestion forestière
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] modélisation de la forêt
[Termes IGN] puits de carbone
[Termes IGN] tourbière
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Information on carbon stocks and the rate of carbon accumulation is needed to harness the climate change mitigation potential of boreal forests. While previous studies have revealed general patterns and mechanisms for age-dependence of stand biomass, simple stand-level models that address the age-biomass relationship on average in managed boreal forests in different environmental conditions are largely missing. We developed models for the relationship between stand age and biomass by forest types on peatlands and mineral soils across climate zones in managed forests in Finland based on National Forest Inventory measurements from 1996 to 2018. In addition, we analyzed at which rate biomass accumulates when managed forest ages in different growth conditions. In northern Finland the maximum biomass change rate was one third, and the maximum biomass stock less than half of the corresponding values in sub-xeric heath forests on minerals soils in southern Finland. On drained peatlands the maximum biomass growth rate was approximately half, and on undrained peatlands one third of the maximum growth rate on mineral soils. On most fertile sites on mineral soils the maximum biomasses were three times larger than on the poorest sites. Correspondingly, the maximum biomass stock change rates were almost eight times faster on most fertile sites. In the example cases presented, the highest annual biomass change rates were achieved in young forests on average at the stand ages of 7–32 years, whereas the 95% of the maximum stock were reached on average in stands of 63–147 years. At the age of highest biomass growth rate stands contained 27–59% of the maximum biomass stocks. The developed models can be used in practical applications such as accounting of biogenic carbon in life-cycle assessments, mapping carbon, or creating simple predictions of biomass stock development in regions, or estimating the mitigation potential of afforestation and reforestation or estimating the magnitude of carbon offsets projects. Numéro de notice : A2021-659 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2021.119507 Date de publication en ligne : 30/07/2021 En ligne : https://doi.org/10.1016/j.foreco.2021.119507 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98398
in Forest ecology and management > vol 498 (October-15 2021) . - n° 119507[article]Impact of beam diameter and scanning approach on point cloud quality of terrestrial laser scanning in forests / Meinrad Abegg in IEEE Transactions on geoscience and remote sensing, vol 59 n° 10 (October 2021)
[article]
Titre : Impact of beam diameter and scanning approach on point cloud quality of terrestrial laser scanning in forests Type de document : Article/Communication Auteurs : Meinrad Abegg, Auteur ; Ruedi Boesch, Auteur ; Michael E. Schaepman, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 8153 - 8167 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] densité du peuplement
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] faisceau laser
[Termes IGN] forêt
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] modélisation de la forêt
[Termes IGN] qualité des données
[Termes IGN] semis de points
[Termes IGN] signal lidar
[Termes IGN] Suisse
[Termes IGN] télémétrie laser terrestreRésumé : (auteur) In recent years, portable laser scanning devices and their applications in the context of forest mensuration have undergone rapid methodological and technological developments. Devices have become smaller, lighter, and more affordable, whereas new data-driven methods and software packages have facilitated the derivation of information from point clouds. Thus, terrestrial laser scanning (TLS) is now well established, and laser–object interactions have been studied using theoretical, modeling, and experimental approaches. The representation of scanned objects in terms of accuracy and completeness is a key factor for successful feature extraction. Still, little is known about the influence of TLS and survey properties on point clouds in complex scattering environments, such as forests. In this study, we investigate the influence of laser beam diameter and signal triggering on the quality of point clouds in forested environments. Based on the Swiss National Forest Inventory data, we simulate the TLS measurements in 684 virtual forest stands using a 3-D content creation suite. We show that small objects lack sufficient representation in the point cloud and they are further negatively influenced by large laser beam diameters, dense stands, and large distances from the scanning device. We provide simulations that make it possible to derive a rationale for decisions regarding the appropriate choice of TLS device and survey configuration for forest inventories. Numéro de notice : A2021-709 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1109/TGRS.2020.3037763 Date de publication en ligne : 08/12/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3037763 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98608
in IEEE Transactions on geoscience and remote sensing > vol 59 n° 10 (October 2021) . - pp 8153 - 8167[article]The effects of combining the variables in allometric biomass models on biomass estimates over large forest areas: A european beech case study / Erick O. Osewe in Forests, vol 12 n° 10 (October 2021)
[article]
Titre : The effects of combining the variables in allometric biomass models on biomass estimates over large forest areas: A european beech case study Type de document : Article/Communication Auteurs : Erick O. Osewe, Auteur ; Ioan Dutca, Auteur Année de publication : 2021 Article en page(s) : n° 1428 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] biomasse aérienne
[Termes IGN] biomasse forestière
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] données allométriques
[Termes IGN] Fagus sylvatica
[Termes IGN] hauteur des arbres
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] modèle de croissance végétale
[Termes IGN] modélisation de la forêt
[Termes IGN] Roumanie
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Effective initiatives for forest-based mitigation of climate change rely on continuous efforts to improve the estimation of forest biomass. Allometric biomass models, which are nonlinear models that predict aboveground biomass (AGB) as a function of diameter at breast height (D) and tree height (H), are typically used in forest biomass estimations. A combined variable D2H may be used instead of two separate predictors. The Q-ratio (i.e., the ratio between the parameter estimates of D and parameter estimates of H, in a separate variable model) was proposed recently as a measure to guide the decision on whether D and H can be safely combined into D2H, being shown that the two model forms are similar when Q = 2.0. Here, using five European beech (Fagus sylvatica L.) biomass datasets (of different Q-ratios ranging from 1.50 to 5.05) and an inventory dataset for the same species, we investigated the effects of combining the variables in allometric models on biomass estimation over large forest areas. The results showed that using a combined variable model instead of a separate variable model to predict biomass of European beech trees resulted in overestimation of mean AGB per hectare for Q > 2.0 (i.e., by 6.3% for Q = 5.05), underestimation for Q Numéro de notice : A2021-864 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.3390/f12101428 Date de publication en ligne : 19/10/2021 En ligne : https://doi.org/10.3390/f12101428 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99080
in Forests > vol 12 n° 10 (October 2021) . - n° 1428[article]Modeling in forestry using mixture models fitted to grouped and ungrouped data / Eric K. Zenner in Forests, vol 12 n° 9 (September 2021)
[article]
Titre : Modeling in forestry using mixture models fitted to grouped and ungrouped data Type de document : Article/Communication Auteurs : Eric K. Zenner, Auteur ; Mahdi Teimouri, Auteur Année de publication : 2021 Article en page(s) : n° 1196 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Statistiques
[Termes IGN] algorithme espérance-maximisation
[Termes IGN] complexité
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] distribution de Weibull
[Termes IGN] distribution, loi de
[Termes IGN] dynamique de la végétation
[Termes IGN] estimation par noyau
[Termes IGN] méthode du maximum de vraisemblance (estimation)
[Termes IGN] modélisation de la forêt
[Termes IGN] structure d'un peuplement forestierRésumé : (auteur) The creation and maintenance of complex forest structures has become an important forestry objective. Complex forest structures, often expressed in multimodal shapes of tree size/diameter (DBH) distributions, are challenging to model. Mixture probability density functions of two- or three-component gamma, log-normal, and Weibull mixture models offer a solution and can additionally provide insights into forest dynamics. Model parameters can be efficiently estimated with the maximum likelihood (ML) approach using iterative methods such as the Newton-Raphson (NR) algorithm. However, the NR algorithm is sensitive to the choice of initial values and does not always converge. As an alternative, we explored the use of the iterative expectation-maximization (EM) algorithm for estimating parameters of the aforementioned mixture models because it always converges to ML estimators. Since forestry data frequently occur both in grouped (classified) and ungrouped (raw) forms, the EM algorithm was applied to explore the goodness-of-fit of the gamma, log-normal, and Weibull mixture distributions in three sample plots that exhibited irregular, multimodal, highly skewed, and heavy-tailed DBH distributions where some size classes were empty. The EM-based goodness-of-fit was further compared against a nonparametric kernel-based density estimation (NK) model and the recently popularized gamma-shaped mixture (GSM) models using the ungrouped data. In this example application, the EM algorithm provided well-fitting two- or three-component mixture models for all three model families. The number of components of the best-fitting models differed among the three sample plots (but not among model families) and the mixture models of the log-normal and gamma families provided a better fit than the Weibull distribution for grouped and ungrouped data. For ungrouped data, both log-normal and gamma mixture distributions outperformed the GSM model and, with the exception of the multimodal diameter distribution, also the NK model. The EM algorithm appears to be a promising tool for modeling complex forest structures. Numéro de notice : A2021-721 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.3390/f12091196 En ligne : https://doi.org/10.3390/f12091196 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98639
in Forests > vol 12 n° 9 (September 2021) . - n° 1196[article]Regularized regression: A new tool for investigating and predicting tree growth / Stuart I. Graham in Forests, vol 12 n° 9 (September 2021)PermalinkCalibration of the process-based model 3-PG for major central European tree species / David I. Forrester in European Journal of Forest Research, vol 140 n° 4 (August 2021)PermalinkImproving tree biomass models through crown ratio patterns and incomplete data sources / Maria Menéndez-Miguélez in European Journal of Forest Research, vol 140 n° 3 (June 2021)PermalinkThe social drift of trees. Consequence for growth trend detection, stand dynamics, and silviculture / Hans Pretzsch in European Journal of Forest Research, vol 140 n° 3 (June 2021)PermalinkTree height growth modelling using LiDAR-derived topography information / Milan Kobal in ISPRS International journal of geo-information, vol 10 n° 6 (June 2021)PermalinkWalking through the forests of the future: using data-driven virtual reality to visualize forests under climate change / Jiawei Huang in International journal of geographical information science IJGIS, vol 35 n° 6 (June 2021)PermalinkWeak relationships of continuous forest management intensity and remotely sensed stand structural complexity in temperate mountain forests / Thomas Asbeck in European Journal of Forest Research, vol 140 n° 3 (June 2021)PermalinkSelf-thinning tree mortality models that account for vertical stand structure, species mixing and climate / David I. Forrester in Forest ecology and management, Vol 487 ([01/05/2021])PermalinkModels for integrating and identifying the effect of senescence on individual tree survival probability for Norway spruce / Jouni Siipilehto in Silva fennica, vol 55 n° 2 (April 2021)PermalinkAnalysis of plot-level volume increment models developed from machine learning methods applied to an uneven-aged mixed forest / Seyedeh Kosar Hamidi in Annals of Forest Science, vol 78 n° 1 (March 2021)Permalink