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Mapping forest age using National Forest Inventory, airborne laser scanning, and Sentinel-2 data / Johannes Schumacher in Forest ecosystems, vol 7 (2020)
[article]
Titre : Mapping forest age using National Forest Inventory, airborne laser scanning, and Sentinel-2 data Type de document : Article/Communication Auteurs : Johannes Schumacher, Auteur ; Marius Hauglin, Auteur ; Rasmus Astrup, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : n° 60 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte forestière
[Termes IGN] dendrochronologie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] gestion forestière
[Termes IGN] hauteur des arbres
[Termes IGN] image Sentinel-MSI
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] Norvège
[Termes IGN] peuplement forestier
[Termes IGN] Picea abies
[Termes IGN] régression linéaire
[Termes IGN] semis de pointsRésumé : (auteur) Background: The age of forest stands is critical information for forest management and conservation, for example for growth modelling, timing of management activities and harvesting, or decisions about protection areas. However, area-wide information about forest stand age often does not exist. In this study, we developed regression models for large-scale area-wide prediction of age in Norwegian forests. For model development we used more than 4800 plots of the Norwegian National Forest Inventory (NFI) distributed over Norway between latitudes 58° and 65° N in an 18.2 Mha study area. Predictor variables were based on airborne laser scanning (ALS), Sentinel-2, and existing public map data. We performed model validation on an independent data set consisting of 63 spruce stands with known age.
Results: The best modelling strategy was to fit independent linear regression models to each observed site index (SI) level and using a SI prediction map in the application of the models. The most important predictor variable was an upper percentile of the ALS heights, and root mean squared errors (RMSEs) ranged between 3 and 31 years (6% to 26%) for SI-specific models, and 21 years (25%) on average. Mean deviance (MD) ranged between − 1 and 3 years. The models improved with increasing SI and the RMSEs were largest for low SI stands older than 100 years. Using a mapped SI, which is required for practical applications, RMSE and MD on plot level ranged from 19 to 56 years (29% to 53%), and 5 to 37 years (5% to 31%), respectively. For the validation stands, the RMSE and MD were 12 (22%) and 2 years (3%), respectively.
Conclusions: Tree height estimated from airborne laser scanning and predicted site index were the most important variables in the models describing age. Overall, we obtained good results, especially for stands with high SI. The models could be considered for practical applications, although we see considerable potential for improvements if better SI maps were available.Numéro de notice : A2020-811 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1186/s40663-020-00274-9 Date de publication en ligne : 10/11/2020 En ligne : https://doi.org/10.1186/s40663-020-00274-9 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96983
in Forest ecosystems > vol 7 (2020) . - n° 60[article]Under-canopy UAV laser scanning for accurate forest field measurements / Eric Hyyppä in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)
[article]
Titre : Under-canopy UAV laser scanning for accurate forest field measurements Type de document : Article/Communication Auteurs : Eric Hyyppä, Auteur ; Juha Hyyppä, Auteur ; Teemu Hakala, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 41 - 60 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] balayage laser
[Termes IGN] canopée
[Termes IGN] cartographie et localisation simultanées
[Termes IGN] densité du bois
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] données lidar
[Termes IGN] erreur moyenne quadratique
[Termes IGN] Finlande
[Termes IGN] forêt boréale
[Termes IGN] hauteur à la base du houppier
[Termes IGN] hauteur des arbres
[Termes IGN] image captée par drone
[Termes IGN] inventaire forestier local
[Termes IGN] modèle de croissance végétale
[Termes IGN] semis de points
[Termes IGN] télédétection aérienne
[Termes IGN] télémètre laser terrestre
[Termes IGN] télémétrie laser aéroporté
[Termes IGN] troncRésumé : (auteur) Surveying and robotic technologies are converging, offering great potential for robotic-assisted data collection and support for labour intensive surveying activities. From a forest monitoring perspective, there are several technological and operational aspects to address concerning under-canopy flying unmanned airborne vehicles (UAV). To demonstrate this emerging technology, we investigated tree detection and stem curve estimation using laser scanning data obtained with an under-canopy flying UAV. To this end, we mounted a Kaarta Stencil-1 laser scanner with an integrated simultaneous localization and mapping (SLAM) system on board an UAV that was manually piloted with the help of video goggles receiving a live video feed from the onboard camera of the UAV. Using the under-canopy flying UAV, we collected SLAM-corrected point cloud data in a boreal forest on two 32 m 32 m test sites that were characterized as sparse ( = 42 trees) and obstructed ( = 43 trees), respectively. Novel data processing algorithms were applied for the point clouds in order to detect the stems of individual trees and to extract their stem curves and diameters at breast height (DBH). The estimated tree attributes were compared against highly accurate field reference data that was acquired semi-manually with a multi-scan terrestrial laser scanner (TLS). The proposed method succeeded in detecting 93% of the stems in the sparse plot and 84% of the stems in the obstructed plot. In the sparse plot, the DBH and stem curve estimates had a root-mean-squared error (RMSE) of 0.60 cm (2.2%) and 1.2 cm (5.0%), respectively, whereas the corresponding values for the obstructed plot were 0.92 cm (3.1%) and 1.4 cm (5.2%). By combining the stem curves extracted from the under-canopy UAV laser scanning data with tree heights derived from above-canopy UAV laser scanning data, we computed stem volumes for the detected trees with a relative RMSE of 10.1% in both plots. Thus, the combination of under-canopy and above-canopy UAV laser scanning allowed us to extract the stem volumes with an accuracy comparable to the past best studies based on TLS in boreal forest conditions. Since the stems of several spruces located on the test sites suffered from severe occlusion and could not be detected with the stem-based method, we developed a separate work flow capable of detecting trees with occluded stems. The proposed work flow enabled us to detect 98% of trees in the sparse plot and 93% of the trees in the obstructed plot with a 100% correction level in both plots. A key benefit provided by the under-canopy UAV laser scanner is the short period of time required for data collection, currently demonstrated to be much faster than the time required for field measurements and TLS. The quality of the measurements acquired with the under-canopy flying UAV combined with the demonstrated efficiency indicates operational potential for supporting fast and accurate forest resource inventories. Numéro de notice : A2020-240 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.03.021 Date de publication en ligne : 11/04/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.03.021 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94994
in ISPRS Journal of photogrammetry and remote sensing > vol 164 (June 2020) . - pp 41 - 60[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2020061 RAB Revue Centre de documentation En réserve L003 Disponible 081-2020063 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2020062 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt How far can we trust forestry estimates from low-density LiDAR acquisitions? The Cutfoot Sioux experimental forest (MN, USA) case study / Enrico Borgogno Mondino in International Journal of Remote Sensing IJRS, vol 41 n° 12 (20 - 30 March 2020)
[article]
Titre : How far can we trust forestry estimates from low-density LiDAR acquisitions? The Cutfoot Sioux experimental forest (MN, USA) case study Type de document : Article/Communication Auteurs : Enrico Borgogno Mondino, Auteur ; Vanina Fissore, Auteur ; Michael J. Falkowski, Auteur ; Brian Palik, Auteur Année de publication : 2020 Article en page(s) : pp 4551 - 4569 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] auscultation topographique
[Termes IGN] diamètre des arbres
[Termes IGN] données dendrométriques
[Termes IGN] données lidar
[Termes IGN] feuillu
[Termes IGN] hauteur des arbres
[Termes IGN] image Landsat-OLI
[Termes IGN] inventaire forestier local
[Termes IGN] Minnesota (Etats-Unis)
[Termes IGN] modèle d'erreur
[Termes IGN] Pinophyta
[Termes IGN] semis de points
[Termes IGN] structure d'un peuplement forestier
[Termes IGN] surface forestière
[Termes IGN] télémètre laser aéroportéRésumé : (auteur) Aerial discrete return LiDAR (Light Detection And Ranging) technology (ALS – Aerial Laser Scanner) is now widely used for forest characterization due to its high accuracy in measuring vertical and horizontal forest structure. Random and systematic errors can still occur and these affect the native point cloud, ultimately degrading ALS data accuracy, especially when adopting datasets that were not natively designed for forest applications. A detailed understanding of how uncertainty of ALS data could affect the accuracy of derivable forest metrics (e.g. tree height, stem diameter, basal area) is required, looking for eventual error biases that can be possibly modelled to improve final accuracy. In this work a low-density ALS dataset, originally acquired by the State of Minnesota (USA) for non-forestry related purposes (i.e. topographic mapping), was processed attempting to characterize forest inventory parameters for the Cutfoot Sioux Experimental Forest (north-central Minnesota, USA). Since accuracy of estimates strictly depends on the applied species-specific dendrometric models a first required step was to map tree species over the forest. A rough classification, aiming at separating conifers from broadleaf, was achieved by processing a Landsat 8 OLI (Operational Land Imager) scene. ALS-derived forest metrics initially greatly overestimated those measured at the ground in 230 plots. Conversely, ALS-derived tree density was greatly underestimated. To reduce ALS uncertainty, trees belonging to the dominated plane were removed from the ground dataset, assuming that they could not properly be detected by low-density ALS measures. Consequently, MAE (Mean Absolute Error) values significantly decreased to 4.0 m for tree height and to 0.19 cm for diameter estimates. Remaining discrepancies were related to a bias affecting the native ALS point cloud, which was modelled and removed. Final MAE values were 1.32 m for tree height, 0.08 m for diameter, 8.5 m2 ha−1 for basal area, and 0.06 m for quadratic mean diameter. Specifically focusing on tree height and diameter estimates, the significance of differences between ground and ALS estimates was tested relative to the expected ‘best accuracy’. Results showed that after correction: 94.35% of tree height differences were lower than the corresponding reference value (2.86 m); 70% of tree diameter differences were lower than the corresponding reference value (4.5 cm for conifers and 6.8 cm for broadleaf). Finally, forest parameters were computed for the whole Cutfoot Sioux Experimental Forest. Main findings include: 1) all forest estimates based on a low-density ALS point cloud can be derived at plot level and not at a tree level; 2) tree height estimates obtained by low-density ALS point clouds at the plot level are highly reasonably accurate only after testing and modelling eventual error bias; 3) diameter, basal area, and quadratic mean diameter estimates have large uncertainties, suggesting the need for a higher point density and, probably, a better mapping of tree species (if possible) than achieved with a remote sensing-based approach. Numéro de notice : A2020-450 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431161.2020.1723173 Date de publication en ligne : 20/02/2020 En ligne : https://doi.org/10.1080/01431161.2020.1723173 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95535
in International Journal of Remote Sensing IJRS > vol 41 n° 12 (20 - 30 March 2020) . - pp 4551 - 4569[article]Warming effects on morphological and physiological performances of four subtropical montane tree species / Yiyong Li in Annals of Forest Science, Vol 77 n° 1 (March 2020)
[article]
Titre : Warming effects on morphological and physiological performances of four subtropical montane tree species Type de document : Article/Communication Auteurs : Yiyong Li, Auteur ; Yue Xu, Auteur ; Ting Wu, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 11 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] changement climatique
[Termes IGN] croissance des arbres
[Termes IGN] diagnostic foliaire
[Termes IGN] effet thermique
[Termes IGN] forêt tropicale
[Termes IGN] hauteur des arbres
[Termes IGN] montagne
[Termes IGN] photosynthèse
[Termes IGN] phytobiologie
[Termes IGN] stress hydrique
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Key message: In a downward transplantation experiment, warming stimulated growth and photosynthesis of Schima superba Gardn. et Champ., Syzygium rehderianum Merr. et Perry and Itea chinensis Hook. et Arn. via increased stomatal conductance. Warming had no effect on growth of Machilus breviflora (Benth.) Hemsl., indicating species-specific differences in response to warming. Context: Climate change has been shown to shift species composition and community structure in subtropical forests. Thus, understanding the species-specific responses of growth and physiological processes to warming is essential. Aims:
To investigate how climate warming affects growth, morphological and physiological performance of co-occurring tree species when they are growing at different altitudes. Methods: Soils and 1-year-old seedlings of four subtropical co-occurring tree species (Schima superba Gardn. et Champ., Syzygium rehderianum Merr. et Perry, Itea chinensis Hook. et Arn. and Machilus breviflora (Benth.) Hemsl.) were transplanted to three altitudes (600 m, 300 m and 30 m a.s.l.), inducing an effective warming of 1.0 °C and 1.5 °C. Growth, morphological, and physiological performances of these seedlings were monitored. Results: When exposed to warmer conditions, aboveground growth of the four species except M. breviflora was strongly promoted, accompanied by increased light-saturated photosynthetic rate and stomatal conductance. Warming also significantly increased concentrations of non-structural carbohydrates in leaves of S. rehderianum and M. breviflora, stems of S. superba and S. rehderianum, and roots of I. chinensis. However, we did not detect any effect of warming on stomatal length and stomatal density. Conclusion:
Our results provide evidence that climate warming could have species-specific impacts on co-occurring tree species, which might subsequently shift species composition and forest structure.Numéro de notice : A2020-037 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-019-0910-3 Date de publication en ligne : 10/01/2020 En ligne : https://doi.org/10.1007/s13595-019-0910-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94491
in Annals of Forest Science > Vol 77 n° 1 (March 2020) . - 11 p.[article]
Titre : Applications of photogrammetry for environmental research Type de document : Monographie Auteurs : Francesco Mancini, Éditeur scientifique ; Riccardo Salvini, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2020 Importance : 154 p. ISBN/ISSN/EAN : 978-3-03928-181-7 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] hauteur des arbres
[Termes IGN] image satellite
[Termes IGN] photographie aérienne
[Termes IGN] Populus (genre)
[Termes IGN] risque environnementalRésumé : (Editeur) The book presents a collection of papers focused on recent progress in key areas of photogrammetry for environmental research. Applications oriented to the understanding of natural phenomena and quantitative processes using dataset from photogrammetry (from satellite to unmanned aerial vehicle images) and terrestrial laser scanning, also by a diachronic approach, are reported. The book covers topics of interest of many disciplines from geography, geomorphology, engineering geology, geotechnology, including landscape description and coastal studies. Mains issues faced by the book are related to applications on coastal monitoring, using multitemporal aerial images, and investigations on geomorphological hazard by the joint use of proximal photogrammetry, terrestrial and aerial laser scanning aimed to the reconstruction of detailed surface topography and successive 2D/3D numerical simulations for rock slope stability analyses. Results reported in the book bring into evidence the fundamental role of multitemporal surveys and reliable reconstruction of morphologies from photogrammetry and laser scanning as support to environmental researches. Numéro de notice : 26302 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Monographie DOI : 10.3390/books978-3-03928-181-7 Date de publication en ligne : 30/01/2020 En ligne : https://doi.org/10.3390/books978-3-03928-181-7 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95035 Potential of UAV photogrammetry for characterization of forest canopy structure in uneven-aged mixed conifer–broadleaf forests / Sadeepa Jayathunga in International Journal of Remote Sensing IJRS, vol 41 n° 1 (01 - 08 janvier 2020)PermalinkSpatiotemporal variation in the relationship between boreal forest productivity proxies and climate data / Clémentine Ols in Dendrochronologia, vol 58 (December 2019)PermalinkEstimating pasture biomass and canopy height in brazilian savanna using UAV photogrammetry / Juliana Batistoti in Remote sensing, Vol 11 n° 20 (October-2 2019)PermalinkThe utility of terrestrial photogrammetry for assessment of tree volume and taper in boreal mixedwood forests / Christopher Mulverhill in Annals of Forest Science, Vol 76 n° 3 (September 2019)PermalinkA general method for the classification of forest stands using species composition and vertical and horizontal structure / Miquel De Cáceres in Annals of Forest Science, vol 76 n° 2 (June 2019)PermalinkRegisTree: a registration algorithm to enhance forest inventory plot georeferencing / Maryem Fadili in Annals of Forest Science, vol 76 n° 2 (June 2019)PermalinkBayesian calibration of a carbon balance model PREBAS using data from permanent growth experiments and national forest inventory / Francesco Minunno in Forest ecology and management, vol 440 (15 May 2019)PermalinkEstimation of the forest stand mean height and aboveground biomass in Northeast China using SAR Sentinel-1B, multispectral Sentinel-2A, and DEM imagery / Yanan Liu in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)PermalinkEstimation of aboveground biomass and carbon in a tropical rain forest in Gabon using remote sensing and GPS data / Kalifa Goïta in Geocarto international, vol 34 n° 3 ([01/03/2019])PermalinkEvidence of climate effects on the height-diameter relationships of tree species / Mathieu Fortin in Annals of Forest Science, vol 76 n° 1 (March 2019)Permalink