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Termes IGN > sciences naturelles > sciences de la vie > biologie > botanique > formation végétale > forêt > canopée
canopée
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interface forêt-atmosphère. forêt, association végétale. >> écologie de la canopée. Source(s) : Glossaire d'écologie fondamentale / M. Duquet, 1993. Equiv. LCSH : Forest canopies. Domaine(s) : 580. Synonyme(s)Voûte forestièreVoir aussi |
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International benchmarking of the individual tree detection methods for modeling 3-D canopy structure for silviculture and forest ecology using airborne laser scanning / Yunsheng Wang in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)
[article]
Titre : International benchmarking of the individual tree detection methods for modeling 3-D canopy structure for silviculture and forest ecology using airborne laser scanning Type de document : Article/Communication Auteurs : Yunsheng Wang, Auteur ; Juha Hyyppä, Auteur ; Xinlian Liang, Auteur ; et al., Auteur ; Clément Mallet , Auteur ; António Ferraz , Auteur Année de publication : 2016 Projets : 1-Pas de projet / Article en page(s) : pp 5011 - 5027 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] arbre (flore)
[Termes IGN] canopée
[Termes IGN] densité des points
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] extraction de la végétation
[Termes IGN] lasergrammétrie
[Termes IGN] longueur d'onde
[Termes IGN] modélisation 3D
[Termes IGN] reconstruction 3D
[Termes IGN] semis de pointsRésumé : (Auteur) Canopy structure plays an essential role in biophysical activities in forest environments. However, quantitative descriptions of a 3-D canopy structure are extremely difficult because of the complexity and heterogeneity of forest systems. Airborne laser scanning (ALS) provides an opportunity to automatically measure a 3-D canopy structure in large areas. Compared with other point cloud technologies such as the image-based Structure from Motion, the power of ALS lies in its ability to penetrate canopies and depict subordinate trees. However, such capabilities have been poorly explored so far. In this paper, the potential of ALS-based approaches in depicting a 3-D canopy structure is explored in detail through an international benchmarking of five recently developed ALS-based individual tree detection (ITD) methods. For the first time, the results of the ITD methods are evaluated for each of four crown classes, i.e., dominant, codominant, intermediate, and suppressed trees, which provides insight toward understanding the current status of depicting a 3-D canopy structure using ITD methods, particularly with respect to their performances, potential, and challenges. This benchmarking study revealed that the canopy structure plays a considerable role in the detection accuracy of ITD methods, and its influence is even greater than that of the tree species as well as the species composition in a stand. The study also reveals the importance of utilizing the point cloud data for the detection of intermediate and suppressed trees. Different from what has been reported in previous studies, point density was found to be a highly influential factor in the performance of the methods that use point cloud data. Greater efforts should be invested in the point-based or hybrid ITD approaches to model the 3-D canopy structure and to further explore the potential of high-density and multiwavelengths ALS data. Numéro de notice : A2016-893 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2543225 Date de publication en ligne : 16/06/2016 En ligne : https://helda.helsinki.fi/bitstream/handle/10138/224961/080MML16.pdf;jsessionid= [...] Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83073
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 9 (September 2016) . - pp 5011 - 5027[article]Documents numériques
Tracking the seasonal dynamics of boreal forest photosynthesis using EO-1 hyperion reflectance : sensitivity to structural and illumination effects / Rocío Hernández-Clemente in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)
[article]
Titre : Tracking the seasonal dynamics of boreal forest photosynthesis using EO-1 hyperion reflectance : sensitivity to structural and illumination effects Type de document : Article/Communication Auteurs : Rocío Hernández-Clemente, Auteur ; Pasi Kolari, Auteur ; Lauri Korhonen, Auteur ; Matti Mõttus, Auteur Année de publication : 2016 Article en page(s) : pp 5105 - 5116 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] acquisition d'images
[Termes IGN] canopée
[Termes IGN] forêt boréale
[Termes IGN] image EO1-Hyperion
[Termes IGN] indice de végétation
[Termes IGN] indice foliaire
[Termes IGN] photosynthèse
[Termes IGN] réflectance végétale
[Termes IGN] teneur en chlorophylle des feuilles
[Termes IGN] variation saisonnièreRésumé : (Auteur) During the growing season, the photosynthesis and growth of boreal forests are regulated by physiological responses to environmental factors. Physiological variations affect the spectral properties of leaves. Linking canopy-level spectral reflectance to leaf-level processes for monitoring forest seasonal physiology using satellite images is hindered by view and illumination effects and variations in canopy structure. To better understand the connection between the two structural levels, we used nine narrow-band vegetation indices (VIs) derived from Hyperion imagery to track the seasonal dynamics of boreal forest stands: the photochemical reflectance indices (PRI and PRI515) related to the xanthophyll cycle, the red edge (RE) index, the Maccioni (Macc) and the green normalized difference vegetation index related to chlorophyll concentration (Ca + b), the carotenoid simple ratio and Gitelson carotenoid concentration index related to carotenoid concentration (Cx + c), the normalized difference vegetation index related to fractional cover, and the plant senescence reflectance index related to the Cx + c/Ca + b ratio. As ground truth, we used measurements of exposed pine shoot light use efficiency (LUE) and photosynthesis. Over the study period (May to August), LUE and photosynthesis were best correlated with the chlorophyll VIs Macc and RE. Both indices also exhibited the lowest coefficient of variation in association with forest structure. PRI, on the other hand, was affected by canopy structure and observation geometry and was uncoupled from LUE during the growing season. Our findings demonstrate that the photosynthesis and productivity of boreal forests in the growing season are best tracked using VIs related to total pigment concentration (i.e., chlorophyll). Numéro de notice : A2016--064 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2554466 En ligne : https://doi.org/10.1109/TGRS.2016.2554466 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83075
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 9 (September 2016) . - pp 5105 - 5116[article]Radiometric correction of airborne radar images over forested terrain with topography / Marc Simard in IEEE Transactions on geoscience and remote sensing, vol 54 n° 8 (August 2016)
[article]
Titre : Radiometric correction of airborne radar images over forested terrain with topography Type de document : Article/Communication Auteurs : Marc Simard, Auteur ; Bryan V. Riel, Auteur ; Michael Denbina, Auteur ; Scott Hensley, Auteur Année de publication : 2016 Article en page(s) : pp 4488 - 4500 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] canopée
[Termes IGN] correction radiométrique
[Termes IGN] évaluation des données
[Termes IGN] forêt
[Termes IGN] homomorphisme
[Termes IGN] image aérienne
[Termes IGN] image radar
[Termes IGN] réflectivité
[Termes IGN] reliefRésumé : (Auteur) Radiometric correction of radar images is essential to produce accurate estimates of biophysical parameters related to forest structure and biomass. We present a new algorithm to correct radiometry for 1) terrain topography and 2) variations of canopy reflectivity with viewing and tree-terrain geometry. This algorithm is applicable to radar images spanning a wide range of incidence angles over terrain with significant topography and can also take into account aircraft attitude, antenna steering angle, and target geometry. The approach includes elements of both homomorphic and heteromorphic terrain corrections to correct for topographic effects and is followed by an additional radiometric correction to compensate for variations of canopy reflectivity with viewing and tree-terrain geometry. The latter correction is based on lookup tables and enables derivation of biophysical parameters irrespective of viewing geometry and terrain topography. We evaluate the performance of the new algorithm with airborne radar data and show that it performs better than classical homomorphic methods followed by cosine-based corrections. Numéro de notice : A2016-885 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2543142 En ligne : http://dx.doi.org/10.1109/TGRS.2016.2543142 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83049
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 8 (August 2016) . - pp 4488 - 4500[article]A hierarchical approach to three-dimensional segmentation of LiDAR data at single-tree level in a multilayered forest / Claudia Paris in IEEE Transactions on geoscience and remote sensing, vol 54 n° 7 (July 2016)
[article]
Titre : A hierarchical approach to three-dimensional segmentation of LiDAR data at single-tree level in a multilayered forest Type de document : Article/Communication Auteurs : Claudia Paris, Auteur ; Davide Valduga, Auteur ; Lorenzo Bruzzone, Auteur Année de publication : 2016 Article en page(s) : pp 4190 - 4203 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] arbre remarquable
[Termes IGN] canopée
[Termes IGN] données lidar
[Termes IGN] exploration de données
[Termes IGN] forêt
[Termes IGN] hauteur de la végétation
[Termes IGN] regroupement de données
[Termes IGN] semis de pointsRésumé : (Auteur) Small-footprint high-density LiDAR data provide information on both the dominant and the subdominant layers of the forest. However, tree detection is usually carried out in the Canopy Height Model (CHM) image domain, where not all the dominant trees are distinguishable and the understory vegetation is not visible. To address these issues, we propose a novel method that integrates the analysis of the CHM with that of the point cloud space (PCS) to 1) improve the accuracy in the detection and delineation of the dominant trees and 2) identify and delineate the subdominant trees. By means of a derivative analysis of the horizontal profile of the forest, the method detects the missed crowns and delineates the crown boundaries directly in the PCS. Then, for each segmented crown, the vertical profile is analyzed to identify the presence of subcanopies and extract them. The proposed method does not require any prior knowledge on the stand properties (e.g., crown size and forest density). Experimental results obtained on two LiDAR data sets characterized by different laser point density show that the proposed method always improved the detection rate compared to other state-of-the-art techniques. It correctly detected 97% and 92% of the dominant trees measured in situ in high- and low-density LiDAR data, respectively. Moreover, it automatically identified 77% of the subdominant trees manually extracted by an expert operator in the high-density LiDAR data. Numéro de notice : A2016-881 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2538203 En ligne : https://doi.org/10.1109/TGRS.2016.2538203 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83044
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 7 (July 2016) . - pp 4190 - 4203[article]Mapping tree species diversity of a tropical montane forest by unsupervised clustering of airborne imaging spectroscopy data / Elisa Schäfer in Ecological indicators, vol 64 (May 2016)
[article]
Titre : Mapping tree species diversity of a tropical montane forest by unsupervised clustering of airborne imaging spectroscopy data Type de document : Article/Communication Auteurs : Elisa Schäfer, Auteur ; Janne Heiskanen, Auteur ; Vuokko Heikinheimo, Auteur ; Petri Pellikka, Auteur Année de publication : 2016 Article en page(s) : pp 49 - 58 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse d'image orientée objet
[Termes IGN] arbre (flore)
[Termes IGN] biodiversité
[Termes IGN] canopée
[Termes IGN] forêt tropicale
[Termes IGN] image aérienne
[Termes IGN] Kenya
[Termes IGN] placette d'échantillonnage
[Termes IGN] segmentation d'imageRésumé : (auteur) With the ongoing global biodiversity loss, approaches to measuring and monitoring biodiversity are necessary for effective conservation planning, especially in tropical forests. Remote sensing has much potential for biodiversity mapping, and high spatial resolution imaging spectroscopy (IS) allows for direct prediction of tree species diversity based on spectral reflectance. The objective of this study was to test an approach for mapping tree species alpha diversity that takes advantage of an unsupervised object-based clustering. Tree species diversity of a tropical montane forest in the Taita Hills, Kenya, was mapped based on spectral variation of high spatial resolution IS data.
Airborne IS data and species data from 31 field plots were collected in the study area. Species diversity measures were obtained from the IS data by clustering spectrally similar image segments representing tree crowns. In order to do this, the image was segmented to objects that represented tree crowns. Three measures of species diversity were calculated based on the field data and on the clustering results, and the relationships were statistically analyzed.
According to the results, the approach succeeded well in revealing tree species diversity patterns. Especially, tree species richness was well predicted (RMSE = 3 species; r2 = 0.50) directly based on the clustering results. The optimal number of clusters was found to be close to the estimated number of tree species in the forest. Minimum tree size was an important determinant of the relationships, because only part of the trees are visible to the airborne sensor in the multi-layered closed canopy forest.
In general, the object-based approach proved to be a viable alternative to a pixel-based clustering. The approach takes advantage of the capability of IS to detect spectral differences among tree crowns, but without the need for spectral training data, which is expensive to collect. With further development, the approach could be applied also for estimating beta diversity.Numéro de notice : A2016-346 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.ecolind.2015.12.026 En ligne : http://dx.doi.org/10.1016/j.ecolind.2015.12.026 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81035
in Ecological indicators > vol 64 (May 2016) . - pp 49 - 58[article]Multisensor and multispectral Lidar characterization and classification of a forest environment / Christopher Hopkinson in Canadian journal of remote sensing, vol 42 n° 5 ([01/05/2016])PermalinkComparison of three Landsat TM compositing methods: A case study using modeled tree canopy cover / Bonnie Ruefenacht in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 3 (March 2016)PermalinkImproved salient feature-based approach for automatically separating photosynthetic and nonphotosynthetic components within terrestrial Lidar point cloud data of forest canopies / Lixia Ma in IEEE Transactions on geoscience and remote sensing, vol 54 n° 2 (February 2016)PermalinkIs waveform worth it? A comparison of LiDAR approaches for vegetation and landscape characterization / Karen Anderson in Remote sensing in ecology and conservation, vol 2 n° 1 (February 2016)PermalinkAssessment of forest canopy vertical structure with multi - scale remote sensing : from the plot to the large area / Phil Wilkes (2016)PermalinkEstimating over- and understorey canopy density of temperate mixed stands by airborne LiDAR data / Hooman Latifi in Forestry, an international journal of forest research, vol 89 n° 1 (January 2016)PermalinkCanopy density model: A new ALS-derived product to generate multilayer crown cover maps / António Ferraz in IEEE Transactions on geoscience and remote sensing, vol 53 n° 12 (December 2015)PermalinkTropical forest canopy cover estimation using satellite imagery and airborne lidar reference data / Lauri Korhonen in Silva fennica, vol 49 n° 5 ([01/10/2015])PermalinkAboveground-biomass estimation of a complex tropical forest in India using Lidar / Cédric Vega in Remote sensing, vol 7 n° 8 (August 2015)PermalinkSavannah woody structure modelling and mapping using multi-frequency (X-, C- and L-band) Synthetic Aperture Radar data / Laven Naidoo in ISPRS Journal of photogrammetry and remote sensing, vol 105 (July 2015)Permalink