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An iterative-mode scan design of terrestrial laser scanning in forests for minimizing occlusion effects / Linyuan Li in IEEE Transactions on geoscience and remote sensing, vol 59 n° 4 (April 2021)
[article]
Titre : An iterative-mode scan design of terrestrial laser scanning in forests for minimizing occlusion effects Type de document : Article/Communication Auteurs : Linyuan Li, Auteur ; Xihan Mu, Auteur ; Maxime Soma, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 3547 - 3566 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] détection de partie cachée
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] données de terrain
[Termes IGN] données lidar
[Termes IGN] hauteur des arbres
[Termes IGN] houppier
[Termes IGN] itération
[Termes IGN] semis de pointsRésumé : (auteur) Occlusion effect, an inherent problem of terrestrial laser scanning (TLS) measurements, limits the potential of TLS data in tree attribute estimation. Multiple scans seek to mitigate this effect to provide enhanced scan completeness. However, the numbers and locations of the scans (i.e., the scan design) are usually determined via a subjective assessment of the tree density, spatial patterns of trees, and attributes to be derived. These could cause suboptimal scan completeness and limit tree attribute estimation. This study proposed an iterative-mode scan design to minimize the occlusion effect. First, we introduced a PoTo index based on visibility analysis to evaluate how many trees can be scanned from a location and to select effective candidates for the optimal TLS location. Second, we introduced a cumulative degree of ring closure (CDRC) to quantify the scan completeness for each candidate and determine the optimal TLS location. The TLS data sets of virtual forests with field-measured and synthetic plot parameter settings were simulated according to iterative- and regular-mode designs by using a Heidelberg light detection and ranging (LiDAR) Operations Simulator (HELIOS). The results demonstrated that an iterative-mode design can improve the scan completeness of trees compared to the regular-mode design. The tree attribute (diameter at breast height (DBH), tree height, stem curve, and crown volume) estimates of the iterative-mode design were less erroneous than those of the regular-mode design (e.g., the root-mean-square error (RMSE) could decrease the stem curve estimation by 38% and the crown volume estimation by 15%). This study suggests that the iterative-mode design can obtain an improved quality of the TLS data, especially for dense stands. Numéro de notice : A2021-288 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3018643 Date de publication en ligne : 10/09/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3018643 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97397
in IEEE Transactions on geoscience and remote sensing > vol 59 n° 4 (April 2021) . - pp 3547 - 3566[article]The impact of drought stress on the height growth of young norway spruce full-sib and half-sib clonal trials in Sweden and Finland / Haleh Hayatgheibi in Forests, vol 12 n° 4 (April 2021)
[article]
Titre : The impact of drought stress on the height growth of young norway spruce full-sib and half-sib clonal trials in Sweden and Finland Type de document : Article/Communication Auteurs : Haleh Hayatgheibi, Auteur ; Matti Haapanen, Auteur ; Jenny Lundströmer, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 498 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] clonage
[Termes IGN] croissance des arbres
[Termes IGN] Finlande
[Termes IGN] génétique forestière
[Termes IGN] hauteur des arbres
[Termes IGN] Indice de précipitations antérieures
[Termes IGN] Picea abies
[Termes IGN] stress hydrique
[Termes IGN] Suède
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) The summer drought of 2018 was one of the most climatically severe events in Europe that led to record-breaking temperatures and wildfires in many parts of Europe. The main objective of this study was to assess the impact of the 2018 drought on the phenotypic and genetic response of Norway spruce height growth using the Standardized Precipitation-Evapotranspiration Index (SPEI). To achieve this, the total cumulative height growth of about 6000 clones from 2016 to 2019 in four full-sib trials in Sweden, aged 6–7 years, and from 2017 to 2019 in two half-sib trials in Finland, aged 8–9 years, were measured. The results indicate that the 2018 drought caused reductions in the increment of trees. Although heritability estimates were similar to other reports for Norway spruce, the additive genetic variance was highly inflated in one of the visibly drought-damaged trials in Southern Sweden. Similarly, the genotype by environment (G × E) interaction was highly significant in the drought-damaged Southern Swedish trials. Both additive genetic and phenotypic correlations obtained between height increments in 2019 and final heights were the weakest in all studied trials, implying that the drought legacies might have influenced the recovery of trees in 2019. We may conclude that the severe drought can be an underlying factor for a strong G × E interaction and changes in the ranking of genotypes. Therefore, a selection of drought-resistant genotypes with a good growth capacity tested in variables sites should be considered as an important criterion for future breeding of Norway spruce. Numéro de notice : A2021-348 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.3390/f12040498 Date de publication en ligne : 16/04/2021 En ligne : https://doi.org/10.3390/f12040498 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97595
in Forests > vol 12 n° 4 (April 2021) . - n° 498[article]Developing a site index model for P. Pinaster stands in NW Spain by combining bi-temporal ALS data and environmental data / Juan Guerra-Hernández in Forest ecology and management, vol 481 (February 2021)
[article]
Titre : Developing a site index model for P. Pinaster stands in NW Spain by combining bi-temporal ALS data and environmental data Type de document : Article/Communication Auteurs : Juan Guerra-Hernández, Auteur ; Stefano Arellano-Pérez, Auteur ; Eduardo González-Ferreiro, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 118690 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] anomalie de croissance des arbres
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] échantillonnage
[Termes IGN] Galice (Espagne)
[Termes IGN] gestion forestière
[Termes IGN] hauteur des arbres
[Termes IGN] indice de végétation
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] lasergrammétrie
[Termes IGN] Pinus pinaster
[Termes IGN] régression multivariée par spline adaptative
[Termes IGN] série temporelleRésumé : (auteur) Site index (SI) is a common measure of forest site productivity, serving as a valuable baseline for forest management. The main objective of this study was to develop a SI model for Pinus pinaster Ait. in north-west Spain by combining bi–temporal, low–density airborne laser scanning (ALS) data (acquired in the periods 2009–2011 and 2015–2017) with climatic, edaphic and physiographical data. Site productivity, assessed by site quality curves, was modelled using an age-independent difference equation method based on ALS metrics and environmental variables. For the model development process, we used data from 156 sample plots in pure and even-aged P. pinaster stands distributed throughout Galicia (NW Spain) and measured in the Spanish National Forest Inventory (SNFI). The generalized algebraic difference approach (GADA) formulation was tested by using two different base equations for modelling the dominant height growth (ΔH) from ALS variables. The GADA formulation derived from the Bertalanffy’s base model produced the best estimates of dominant height (H) for P. pinaster stands in Galicia. Use of the proposed model to estimate ΔH for a new pine stand requires two ALS data sets for estimating site-specific (local) parameters. To enable use of the model when such information is not available, the relationship between the values of the site-specific parameter and environmental variables was described using Multivariate Adaptive Regression Splines (MARS). Use of the MARS equation enabled us to develop spatially-explicit predictive maps of the site-specific parameter values, which can be used together with the GADA model to derive ΔH curves and SI estimates for P. pinaster stands in the whole study region. Numéro de notice : A2021-225 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.foreco.2020.118690 Date de publication en ligne : 01/11/2021 En ligne : https://doi.org/10.1016/j.foreco.2020.118690 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97200
in Forest ecology and management > vol 481 (February 2021) . - n° 118690[article]Forest height estimation using a single-pass airborne L-band polarimetric and interferometric SAR system and tomographic techniques / Yue Huang in Remote sensing, Vol 13 n° 3 (February 2021)
[article]
Titre : Forest height estimation using a single-pass airborne L-band polarimetric and interferometric SAR system and tomographic techniques Type de document : Article/Communication Auteurs : Yue Huang, Auteur ; Qiaoping Zhang, Auteur ; Laurent Ferro-Famil, Auteur Année de publication : 2021 Article en page(s) : n° 487 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] Alberta (Canada)
[Termes IGN] bande L
[Termes IGN] forêt boréale
[Termes IGN] hauteur des arbres
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] modèle numérique de surface
[Termes IGN] modèle numérique de terrain
[Termes IGN] polarimétrie radar
[Termes IGN] surveillance forestière
[Termes IGN] tomographie radarRésumé : (auteur) This paper addresses forest height estimation for boreal forests at the test site of Edson in Alberta, Canada, using dual-baseline PolInSAR dataset measured by Intermap’s single-pass system. This particular dataset is acquired by using both ping-pong and non-ping-pong modes, which permit forming a dual-baseline TomoSAR configuration, i.e., an extreme configuration for tomographic processing. A tomographic approach, based on polarimetric Capon and MUSIC estimators, is proposed to estimate the elevation of tree top and of underlying ground, and hence forest height is estimated. The resulting forest DTM and DSM over the test site are validated against LiDAR-derived estimates, demonstrating the undeniable capability of the single-pass L-band PolInSAR system for forest monitoring. Numéro de notice : A2021-200 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/rs13030487 Date de publication en ligne : 30/01/2021 En ligne : https://doi.org/10.3390/rs13030487 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97153
in Remote sensing > Vol 13 n° 3 (February 2021) . - n° 487[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)
[article]
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 IGN] apprentissage automatique
[Termes IGN] bande L
[Termes IGN] canopée
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] données lidar
[Termes IGN] données polarimétriques
[Termes IGN] forêt tropicale
[Termes IGN] Gabon
[Termes IGN] hauteur des arbres
[Termes IGN] image captée par drone
[Termes IGN] image radar moirée
[Termes IGN] Rotation Forest classification
[Termes IGN] semis de pointsRésumé : (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
in ISPRS Journal of photogrammetry and remote sensing > vol 172 (February 2021) . - pp 79 - 94[article]Réservation
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