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Variation of leaf angle distribution quantified by terrestrial LiDAR in natural European beech forest / Jing Liu in ISPRS Journal of photogrammetry and remote sensing, vol 148 (February 2019)
[article]
Titre : Variation of leaf angle distribution quantified by terrestrial LiDAR in natural European beech forest Type de document : Article/Communication Auteurs : Jing Liu, Auteur ; Andrew K. Skidmore, Auteur ; Tiejun Wang, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 208 - 220 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] angle (géométrie)
[Termes IGN] Bavière (Allemagne)
[Termes IGN] croissance végétale
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Fagus sylvatica
[Termes IGN] feuille (végétation)
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] semis de pointsMots-clés libres : inclinaison longitudinale Leaf inclination angle leaf angle distribution Résumé : (Auteur) Leaf inclination angle and leaf angle distribution (LAD) are important plant structural traits, influencing the flux of radiation, carbon and water. Although leaf angle distribution may vary spatially and temporally, its variation is often neglected in ecological models, due to difficulty in quantification. In this study, terrestrial LiDAR (TLS) was used to quantify the LAD variation in natural European beech (Fagus Sylvatica) forests. After extracting leaf points and reconstructing leaf surface, leaf inclination angle was calculated automatically. The mapping accuracy when discriminating between leaves and woody material was very high across all beech stands (overall accuracy = 87.59%). The calculation accuracy of leaf angles was evaluated using simulated point cloud and proved accurate generally (R2 = 0.88, p Numéro de notice : A2019-075 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.01.005 Date de publication en ligne : 15/01/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.01.005 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92162
in ISPRS Journal of photogrammetry and remote sensing > vol 148 (February 2019) . - pp 208 - 220[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2019021 RAB Revue Centre de documentation En réserve L003 Disponible 081-2019023 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2019022 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Estimation of winter wheat crop growth parameters using time series Sentinel-1A SAR data / P. Kumar in Geocarto international, vol 33 n° 9 (September 2018)
[article]
Titre : Estimation of winter wheat crop growth parameters using time series Sentinel-1A SAR data Type de document : Article/Communication Auteurs : P. Kumar, Auteur ; R. Prasad, Auteur ; D. K. Gupta, Auteur ; V. N. Mishra, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 942 - 956 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] bande C
[Termes IGN] blé (céréale)
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] croissance végétale
[Termes IGN] cultures
[Termes IGN] données polarimétriques
[Termes IGN] estimation statistique
[Termes IGN] hiver
[Termes IGN] image Sentinel-SAR
[Termes IGN] Leaf Area Index
[Termes IGN] régression
[Termes IGN] régression linéaire
[Termes IGN] réseau neuronal artificiel
[Termes IGN] séparateur à vaste marge
[Termes IGN] teneur en eau de la végétationRésumé : (Auteur) In the present study, Sentinel-1A Synthetic Aperture Radar analysis of time series data at C-band was carried out to estimate the winter wheat crop growth parameters. Five different date images were acquired during January 2015–April 2015 at different growth stages from tillering to ripening in Varanasi district, India. The winter wheat crop parameters, i.e. leaf area index, vegetation water content (VWC), fresh biomass (FB), dry biomass (DB) and plant height (PH) were estimated using random forest regression (RFR), support vector regression (SVR), artificial neural network regression (ANNR) and linear regression (LR) algorithms. The Ground Range Detected products of Interferometric Wide (IW) Swath were used at VV polarization. The three different subplots of 1 m2 area were taken for the measurement of crop parameters at every growth stage. In total, 73 samples were taken as the training data-sets and 39 samples were taken as testing data-sets. The highest sensitivity (adj. R2 = 0.95579) of backscattering with VWC was found using RFR algorithm, whereas the lowest sensitivity (adj. R2 = 0.66201) was found for the PH using LR algorithm. Overall results indicate more accurate estimation of winter wheat parameters by the RFR algorithm followed by SVR, ANNR and LR algorithms. Numéro de notice : A2018-337 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2017.1316781 Date de publication en ligne : 18/04/2017 En ligne : https://doi.org/10.1080/10106049.2017.1316781 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90551
in Geocarto international > vol 33 n° 9 (September 2018) . - pp 942 - 956[article]Research on the estimation model of vegetation water content in halophyte leaves based on the newly developed vegetation indices / Zhe Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 9 (September 2018)
[article]
Titre : Research on the estimation model of vegetation water content in halophyte leaves based on the newly developed vegetation indices Type de document : Article/Communication Auteurs : Zhe Li, Auteur ; Fei Zhang, Auteur ; Lihua Chen, Auteur ; Haiwei Zhang, Auteur ; Hsiang-Te Kung, Auteur Année de publication : 2018 Article en page(s) : pp 538 - 548 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] croissance végétale
[Termes IGN] feuille (végétation)
[Termes IGN] indice de végétation
[Termes IGN] plante halophile
[Termes IGN] Populus euphratica
[Termes IGN] signature spectrale
[Termes IGN] Sinkiang (Chine)
[Termes IGN] Tamarix (genre)
[Termes IGN] teneur en eau de la végétationRésumé : (Auteur) The vegetation water content (VWC) quantitative is useful for monitoring vegetation physiological growth. The relationship between VWC and vegetation water indices was analyzed. The optimal estimation model was established. The results show that: (1) Absorption bands primarily fell within 380 to 400 nm, 680 to 720 nm, 1420 to 1450 nm, 1900 to 1940 nm, and 2450 to 2500 nm; (2) comparing published vegetation water indices and developed vegetation indices, it showed that DVI(1712,1382), NDSI(2201,1870) and RSI(2259,1870) had a better correlation with VWC than the published vegetation water; and (3) NDSI(2201,1870) and RSI(2259,1870) performed well in estimating vegetation water content, DVI(1712,1382) had a rough estimate of its water content. Moreover, the linear combination of DVI(1712,1382), NDSI(2201,1870) and RSI(2259,1870) improved the estimation of VWC. The best vegetation indices for estimating VWC were found to be the linear combination of DVI(1712,1382), NDSI(2201,1870) and RSI(2259,1870) in arid area of northwestern China. Numéro de notice : A2018-361 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.84.9.537 Date de publication en ligne : 01/09/2018 En ligne : https://doi.org/10.14358/PERS.84.9.537 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90672
in Photogrammetric Engineering & Remote Sensing, PERS > vol 84 n° 9 (September 2018) . - pp 538 - 548[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 105-2018091 RAB Revue Centre de documentation En réserve L003 Disponible Seed dispersal, microsites or competition : what drives gap regeneration in an old-growth forest? An application of spatial point process modelling / Georg Gratzer in Forests, vol 9 n° 5 (May 2018)
[article]
Titre : Seed dispersal, microsites or competition : what drives gap regeneration in an old-growth forest? An application of spatial point process modelling Type de document : Article/Communication Auteurs : Georg Gratzer, Auteur ; Rasmus Plenge Waagepetersen, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Végétation
[Termes IGN] croissance végétale
[Termes IGN] dynamique de la végétation
[Termes IGN] forêt ancienne
[Termes IGN] modèle de croissance végétale
[Termes IGN] modèle de simulation
[Termes IGN] processus ponctuel
[Termes IGN] régénération (sylviculture)Résumé : (Auteur) The spatial structure of trees is a template for forest dynamics and the outcome of a variety of processes in ecosystems. Identifying the contribution and magnitude of the different drivers is an age-old task in plant ecology. Recently, the modelling of a spatial point process was used to identify factors driving the spatial distribution of trees at stand scales. Processes driving the coexistence of trees, however, frequently unfold within gaps and questions on the role of resource heterogeneity within-gaps have become central issues in community ecology. We tested the applicability of a spatial point process modelling approach for quantifying the effects of seed dispersal, within gap light environment, microsite heterogeneity, and competition on the generation of within gap spatial structure of small tree seedlings in a temperate, old growth, mixed-species forest. By fitting a non-homogeneous Neyman–Scott point process model, we could disentangle the role of seed dispersal from niche partitioning for within gap tree establishment and did not detect seed densities as a factor explaining the clustering of small trees. We found only a very weak indication for partitioning of within gap light among the three species and detected a clear niche segregation of Picea abies (L.) Karst. on nurse logs. The other two dominating species, Abies alba Mill. and Fagus sylvatica L., did not show signs of within gap segregation. Numéro de notice : A2018-486 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/f9050230 Date de publication en ligne : 27/04/2018 En ligne : https://doi.org/10.3390/f9050230 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91222
in Forests > vol 9 n° 5 (May 2018)[article]Above-bottom biomass retrieval of aquatic plants with regression models and SfM data acquired by a UAV platform – A case study in Wild Duck Lake Wetland, Beijing, China / Ran Jing in ISPRS Journal of photogrammetry and remote sensing, vol 134 (December 2017)
[article]
Titre : Above-bottom biomass retrieval of aquatic plants with regression models and SfM data acquired by a UAV platform – A case study in Wild Duck Lake Wetland, Beijing, China Type de document : Article/Communication Auteurs : Ran Jing, Auteur ; Zhaoning Gong, Auteur ; Wenji Zhao, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 122 - 134 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] arbre de décision
[Termes IGN] biomasse
[Termes IGN] croissance végétale
[Termes IGN] drone
[Termes IGN] image aérienne
[Termes IGN] indice de végétation
[Termes IGN] lac
[Termes IGN] macrophyte
[Termes IGN] modèle de régression
[Termes IGN] orthoimage
[Termes IGN] Pékin (Chine)
[Termes IGN] régression linéaire
[Termes IGN] semis de points
[Termes IGN] structure-from-motion
[Termes IGN] zone humideRésumé : (Auteur) Above-bottom biomass (ABB) is considered as an important parameter for measuring the growth status of aquatic plants, and is of great significance for assessing health status of wetland ecosystems. In this study, Structure from Motion (SfM) technique was used to rebuild the study area with high overlapped images acquired by an unmanned aerial vehicle (UAV). We generated orthoimages and SfM dense point cloud data, from which vegetation indices (VIs) and SfM point cloud variables including average height (HAVG), standard deviation of height (HSD) and coefficient of variation of height (HCV) were extracted. These VIs and SfM point cloud variables could effectively characterize the growth status of aquatic plants, and thus they could be used to develop a simple linear regression model (SLR) and a stepwise linear regression model (SWL) with field measured ABB samples of aquatic plants. We also utilized a decision tree method to discriminate different types of aquatic plants. The experimental results indicated that (1) the SfM technique could effectively process high overlapped UAV images and thus be suitable for the reconstruction of fine texture feature of aquatic plant canopy structure; and (2) an SWL model based on point cloud variables: HAVG, HSD, HCV and two VIs: NGRDI, ExGR as independent variables has produced the best predictive result of ABB of aquatic plants in the study area, with a coefficient of determination of 0.84 and a relative root mean square error of 7.13%. In this analysis, a novel method for the quantitative inversion of a growth parameter (i.e., ABB) of aquatic plants in wetlands was demonstrated. Numéro de notice : A2017-732 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.11.002 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.11.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88431
in ISPRS Journal of photogrammetry and remote sensing > vol 134 (December 2017) . - pp 122 - 134[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2017121 RAB Revue Centre de documentation En réserve L003 Disponible 081-2017122 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt 081-2017123 DEP-EXM Revue Saint-Mandé Dépôt en unité Exclu du prêt Vertical stratification of forest canopy for segmentation of understory trees within small-footprint airborne LiDAR point clouds / Hamid Hamraz in ISPRS Journal of photogrammetry and remote sensing, vol 130 (August 2017)PermalinkSurface soil moisture retrieval using the L-band synthetic aperture radar onboard the Soil Moisture Active–Passive Satellite and evaluation at core validation sites / Seung-Bum Kim in IEEE Transactions on geoscience and remote sensing, vol 55 n° 4 (April 2017)PermalinkLaser scanning based growth analysis of plants as a new challenge for deformation monitoring / Jan Dupuis in Journal of applied geodesy, vol 10 n° 1 (March 2016)PermalinkTemporal MODIS data for identification of wheat crop using noise clustering soft classification approach / Priyadarshi Upadhyay in Geocarto international, vol 31 n° 3 - 4 (March - April 2016)PermalinkUn modèle de prévision de rendement de la canne à sucre basé sur des images satellitaires SPOT : l'exemple de la Réunion / N. Boyer in Revue Française de Photogrammétrie et de Télédétection, n° 197 (Juin 2012)PermalinkUtilisation de l'imagerie radar TerraSar-X THRS pour le suivi de la coupe de canne à sucre à l'île de la Réunion / Nicolas Baghdadi in Revue Française de Photogrammétrie et de Télédétection, n° 197 (Juin 2012)PermalinkThe establishment of an in vitro gene bank in Dianthus spiculifolius Schur and D. glacialis ssp. gelidus (Schott Nym. et Kotschy) Tutin: I. The initiation of a tissue collection and the characterization of the cultures in minimal growth conditions / Mihaela Holobiuc in Annals of forest research, vol 52 n° 1 (January 2009)PermalinkPrévoir la croissance et la production du Pin sylvestre : le module Sylvestris sous Capsis 4 / Thomas Pérot in Revue forestière française, vol 59 n° 1 (janvier - février 2007)PermalinkAssessment of regional forest and scrub productivity using a coupled vegetation process model with remote sensing / Nicholas C. Coops in Geocarto international, vol 17 n° 4 (December 2002 - February 2003)PermalinkAdvances in environmental and ecological modelling / François Blasco (1999)Permalink