Descripteur
Termes IGN > sciences naturelles > sciences de la vie > biologie > botanique > formation végétale > forêt
forêt
Commentaire :
Bois (forêts), Boisé, Espace boisé, Espace forestier, Essence forestière, Forêt et sylviculture, Groupement forestier (écologie), Massif forestier, Milieu forestier, Peuplement forestier, Région forestière Ressource forestière, Zone forestière. Campagne, Espace naturel. >> Arbre, Archéologie des forêts, Écologie des forêts, Foresterie, Paysage forestier, Politique forestière, Produit forestier, Sylviculture. Voir aussi aux noms des forêts, par ex. : Fontainebleau, Forêt de (Seine-et-Marne) ; Bayerischer Wald (Allemagne). >>Terme(s) spécifique(s) : Biomasse des forêts, Canopée, Forêt domaniale, Forêt privée, Plante des forêts, Réserve forestière, Sol forestier, Station forestière -- Typologie. Source(s) : Grand Larousse universel . - Terminologie forestière / A. Métro, 1975. Equiv. LCSH : Forests and forestry. Domaine(s) : 577, 580. Synonyme(s)paysage forestierVoir aussi |
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Comparing features of single and multi-photon lidar in boreal forests / Xiaowei Yu in ISPRS Journal of photogrammetry and remote sensing, vol 168 (October 2020)
[article]
Titre : Comparing features of single and multi-photon lidar in boreal forests Type de document : Article/Communication Auteurs : Xiaowei Yu, Auteur ; Antero Kukko, Auteur ; Harri Kaartinen, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 268 - 276 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse comparative
[Termes IGN] canopée
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] données lidar
[Termes IGN] Finlande
[Termes IGN] forêt boréale
[Termes IGN] modèle numérique de surface
[Termes IGN] photon
[Termes IGN] semis de points
[Termes IGN] télémétrie laser aéroportéRésumé : (auteur) The emerging single-photon laser scanning has made technological breakthrough in the collection of airborne laser scanning data. In principle, single-photon systems require only one detected photon for successful ranging. Further, the point density on the ground can be 10–100 times higher for single-photon lidar data than that obtained with multi-photon systems at the same flight altitude. This has great potential to reduce operation costs. Single-photon lidar technology is assumed to be the best for data acquisition when high point densities are required over very large areas, or when improvements in measurement rates can significantly reduce data acquisition costs, such as in nationwide laser scanning programmes, where the whole country is repeatedly covered with data every 5–10 years. This study investigates single-photon lidar and conventional multi-photon laser scanning data for their potential in characterizing ground and forest attributes. Performance is evaluated in a boreal forest by a comparative analysis, where single-photon lidar measurements with SPL100 (Leica/Hexagon) from two flight heights (1900 m and 3800 m) are compared with data from the Optech Titan (400 m) multi-photon airborne laser scanning (ALS) under summer conditions (i.e. leaves on). We found that SPL100 from both altitudes provides forest attribute estimates with comparable accuracy to that of Optech Titan from 400 m using an area-based method. This demonstrates that point density and flight altitude do not have significant impact on forest attribute estimation using the area-based approach. As a result, SPL100 is a cost-efficient alternative to a conventional laser scanner for forest inventories at large scale. There are systematic differences in behavior of the data sets due to differences in ranging sensitivity, beam size, and point density. We observed a higher proportion of ground returns in the SPL100 (3800 m) than in SPL100 (1900 m) data. Both SPL100 data in general produced a higher proportion of ground returns than Titan single channel did in structurally more homogeneous and one layer stands while higher proportion of ground returns from Titan than from SPL100 data in multi-layer stands. Forest structure and flight altitude has a notable impact on the distribution of points and further characteristics of the vertical structures. The pulse of Titan sensor penetrated deeper into the canopy than SPL100. Numéro de notice : A2020-637 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.08.013 Date de publication en ligne : 01/09/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.08.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96060
in ISPRS Journal of photogrammetry and remote sensing > vol 168 (October 2020) . - pp 268 - 276[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2020101 RAB Revue Centre de documentation En réserve L003 Disponible 081-2020103 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2020102 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Ground-based remote sensing of forests exploiting GNSS signals / Leila Guerriero in IEEE Transactions on geoscience and remote sensing, vol 58 n° 10 (October 2020)
[article]
Titre : Ground-based remote sensing of forests exploiting GNSS signals Type de document : Article/Communication Auteurs : Leila Guerriero, Auteur ; Francisco Martin, Auteur ; Antonio Mollfulleda, Auteur Année de publication : 2020 Article en page(s) : pp 6844 - 6860 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] atténuation du signal
[Termes IGN] bande L
[Termes IGN] bande P
[Termes IGN] biomasse aérienne
[Termes IGN] canopée
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] Leaf Area Index
[Termes IGN] polarisation
[Termes IGN] Populus (genre)
[Termes IGN] réseau neuronal artificiel
[Termes IGN] signal GNSSRésumé : (auteur) The estimation of aboveground biomass is commonly recognized for global relevance because of the vegetation role in the carbon cycle. Both active and passive microwave sensors can significantly contribute to this goal because of their high sensitivity to water content and high penetration at lower frequencies (L-/P-bands). In particular, Global Navigation Satellite Systems (GNSSs) are recently receiving increasing interest as source of opportunity to be employed as illuminator for L-band remote sensing, since they could provide low-cost sensors for nondestructive forest biomass estimation over large areas. In this article, we suggest a method to extract forest information using the GNSS direct signals collected in clear sky and below the vegetation canopy at both circular polarizations. An experimental campaign, carried out in the framework of an European Space Agency (ESA) project, was conducted over three poplar forests with different biomass to verify the feasibility of this technique. The relationships between the GNSS measurements and the tree parameters were first assessed and then interpreted and supported by statistical analysis and a theoretical model. The signal collected under the canopy is affected by attenuation and depolarization with respect to the one collected in open air, and this article demonstrated that both direct line-of-sight propagation and volume scattering play a role in the signal magnitude and its fluctuation in time. Although the experimental data set is limited in size and environmental conditions, two inversion algorithms were also tested with the encouraging retrieval results. Numéro de notice : A2020-585 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2976899 Date de publication en ligne : 23/03/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2976899 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95913
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 10 (October 2020) . - pp 6844 - 6860[article]The effect of leaf-on and leaf-off forest canopy conditions on LiDAR derived estimations of forest structural diversity / Sophie Davison in International journal of applied Earth observation and geoinformation, vol 92 (October 2020)
[article]
Titre : The effect of leaf-on and leaf-off forest canopy conditions on LiDAR derived estimations of forest structural diversity Type de document : Article/Communication Auteurs : Sophie Davison, Auteur ; Daniel N.M. Donoghue, Auteur ; Nikolaos Galiatsatos, Auteur Année de publication : 2020 Article en page(s) : n° 102160 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] canopée
[Termes IGN] couvert forestier
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] données lidar
[Termes IGN] hauteur des arbres
[Termes IGN] indicateur de biodiversité
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] peuplement forestier
[Termes IGN] semis de points
[Termes IGN] structure de la végétationRésumé : (auteur) Forest structural diversity metrics describing diversity in tree size and crown shape within forest stands can be used as indicators of biodiversity. These diversity metrics can be generated using airborne laser scanning (LiDAR) data to provide a rapid and cost effective alternative to ground-based inspection. Measures of tree height derived from LiDAR can be significantly affected by the canopy conditions at the time of data collection, in particular whether the canopy is under leaf-on or leaf-off conditions, but there have been no studies of the effects on structural diversity metrics. The aim of this research is to assess whether leaf-on/leaf-off changes in canopy conditions during LiDAR data collection affect the accuracy of calculated forest structural diversity metrics. We undertook a quantitative analysis of LiDAR ground detection and return height, and return height diversity from two airborne laser scanning surveys collected under leaf-on and leaf-off conditions to assess initial dataset differences. LiDAR data were then regressed against field-derived tree size diversity measurements using diversity metrics from each LiDAR dataset in isolation and, where appropriate, a mixture of the two. Models utilising leaf-off LiDAR diversity variables described DBH diversity, crown length diversity and crown width diversity more successfully than leaf-on (leaf-on models resulted in R² values of 0.66, 0.38 and 0.16, respectively, and leaf-off models 0.67, 0.37 and 0.23, respectively). When LiDAR datasets were combined into one model to describe tree height diversity and DBH diversity the models described 75% and 69% of the variance (R² of 0.75 for tree height diversity and 0.69 for DBH diversity). The results suggest that tree height diversity models derived from airborne LiDAR, collected (and where appropriate combined) under any seasonal conditions, can be used to differentiate between simple single and diverse multiple storey forest structure with confidence. Numéro de notice : A2020-749 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.jag.2020.102160 Date de publication en ligne : 09/06/2020 En ligne : https://doi.org/10.1016/j.jag.2020.102160 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96399
in International journal of applied Earth observation and geoinformation > vol 92 (October 2020) . - n° 102160[article]Tree species classification using structural features derived from terrestrial laser scanning / Louise Terryn in ISPRS Journal of photogrammetry and remote sensing, vol 168 (October 2020)
[article]
Titre : Tree species classification using structural features derived from terrestrial laser scanning Type de document : Article/Communication Auteurs : Louise Terryn, Auteur ; Kim Calders, Auteur ; Mathias I. Disney, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 170 - 181 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse comparative
[Termes IGN] arbre (flore)
[Termes IGN] classification barycentrique
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] composition d'un peuplement forestier
[Termes IGN] couvert forestier
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] espèce végétale
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] ombre
[Termes IGN] régression logistique
[Termes IGN] semis de pointsRésumé : (auteur) Fast and automated collection of forest data, such as species composition information, is required to support climate mitigation actions. Recently, there have been significant advances in the use of terrestrial laser scanning (TLS) instruments, which facilitate the capture of detailed forest structure. However, for tree species recognition the structural information from TLS has mainly been used to complement spectral information. TLS-only classification studies have been limited in size and diversity of plot forest types. In this paper, we investigate the potential of TLS for tree species classification. We used quantitative structure models to determine 17 structural tree features. These features were computed for 758 trees of five tree species, including two understory species, of a 1.4 hectare mixed deciduous forest plot. Three classification methods were compared: k-nearest neighbours, multinomial logistic regression and support vector machine. We assessed the potential underlying causes for structural differences with principal component analysis. We obtained classification success rates of approximately 80%, however, with producer accuracies for three of the five species ranging from 0 to 60%. Low producer accuracies were the result of a high intra- and low inter-species variability. These effects were, respectively, caused by a high size-dependency of the structural features and a convergence of structural traits across species as a result of the individual tree position in the forest canopy and shade tolerance. Nevertheless, the producer accuracies could be improved through sensitivity vs. specificity trade-offs, with over 50% for all species being obtainable. The high intra -and low inter-species variability complicate the classification. Furthermore, the classification performance and best classification method greatly depend on its targeted application. In conclusion, this study proves the added value of TLS for tree species classification but also shows that TLS opens up potential for testing and further development of ecological theory. Numéro de notice : A2020-636 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.08.009 Date de publication en ligne : 21/08/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.08.009 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96059
in ISPRS Journal of photogrammetry and remote sensing > vol 168 (October 2020) . - pp 170 - 181[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2020101 RAB Revue Centre de documentation En réserve L003 Disponible 081-2020103 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2020102 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Weighted spherical sampling of point clouds for forested scenes / Alex Fafard in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 10 (October 2020)
[article]
Titre : Weighted spherical sampling of point clouds for forested scenes Type de document : Article/Communication Auteurs : Alex Fafard, Auteur ; Ali Rouzbeh Kargar, Auteur ; Jan Van Aardt, Auteur Année de publication : 2020 Article en page(s) : pp 619 - 625 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] coordonnées sphériques
[Termes IGN] densité de la végétation
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] données lidar
[Termes IGN] échantillonnage
[Termes IGN] mangrove
[Termes IGN] Micronésie
[Termes IGN] scène forestière
[Termes IGN] semis de points
[Termes IGN] volume en boisRésumé : (Auteur) Terrestrial laser scanning systems are characterized by a sampling pattern which varies in point density across the hemisphere. Additionally, close objects are over-sampled relative to objects that are farther away. These two effects compound to potentially bias the three-dimensional statistics of measured scenes. Previous methods of sampling have resulted in a loss of structural coherence. In this article, a method of sampling is proposed to optimally sample points while preserving the structure of a scene. Points are sampled along a spherical coordinate system, with probabilities modulated by elevation angle and squared distance from the origin. The proposed approach is validated through visual comparison and stem-volume assessment in a challenging mangrove forest in Micronesia. Compared to several well-known sampling techniques, the proposed approach reduces sampling bias and shows strong performance in stem-reconstruction measurement. The proposed sampling method matched or exceeded the stem-volume measurement accuracy across a variety of tested decimation levels. On average it achieved 3.0% higher accuracy at estimating stem volume than the closest competitor. This approach shows promise for improving the evaluation of terrestrial laser-scanning data in complex scenes. Numéro de notice : A2020-493 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.86.10.619 Date de publication en ligne : 01/10/2020 En ligne : https://doi.org/10.14358/PERS.86.10.619 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96093
in Photogrammetric Engineering & Remote Sensing, PERS > vol 86 n° 10 (October 2020) . - pp 619 - 625[article]Exemplaires(1)
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