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A CNN-based approach for the estimation of canopy heights and wood volume from GEDI waveforms / Ibrahim Fayad in Remote sensing of environment, vol 265 (November 2021)
[article]
Titre : A CNN-based approach for the estimation of canopy heights and wood volume from GEDI waveforms Type de document : Article/Communication Auteurs : Ibrahim Fayad, Auteur ; Dino Lenco, Auteur ; Nicolas Baghdadi, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 112652 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] Brésil
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Eucalyptus (genre)
[Termes IGN] forme d'onde
[Termes IGN] Global Ecosystem Dynamics Investigation lidar
[Termes IGN] hauteur des arbres
[Termes IGN] modèle de croissance végétale
[Termes IGN] semis de points
[Termes IGN] volume en boisRésumé : (auteur) Full waveform (FW) LiDAR systems have proven their effectiveness to map forest biophysical variables in the last two decades, owing to their ability of measuring, with high accuracy, forest vertical structures. The Global Ecosystem Dynamics Investigation (GEDI) system on board the International Space Station (ISS) is the latest FW spaceborne LiDAR instrument for the continuous observation of Earth's forests. FW systems rely on very sophisticated pre-processing steps to generate a priori metrics in order to leverage their capabilities for the accurate estimation of the aforementioned forest characteristics. The ever-expanding volume of acquired GEDI data, which to date comprises more than 25 billion acquired unfiltered shots, and along with the pre-processed data, amounting to more than 90 TB of data, raises new challenges in terms of adapted preprocessing methods for the suitable exploitation of such a huge and complex amount of LiDAR data. To overcome the issues related to the generation of relevant metrics from GEDI data, we propose a new metric-free approach to estimate canopy dominant heights (Hdom) and wood volume (V) of Eucalyptus plantations over five different regions in Brazil. To avoid metric computation, we leverage deep learning techniques and, more in detail, convolutional neural networks with the aim to analyze the GEDI Level 1B geolocated waveforms. Performance comparisons were conducted between four convolutional neural network (CNN) variants using GEDI waveform data (either untouched, or subsetted) and a metric based Random Forest regressor (RF). Additionally, we tested if our framework can improve the generalization of the models to different distant regions. First, the models were trained using data from all the study regions. Cross validated results showed that the CNN based models compared well against their RF counterpart for both Hdom and V. The RMSE on the estimation of Hdom from the CNN based models varied between 1.54 and 1.94 m with a coefficient of determination (R2) between 0.86 and 0.91, while the RF model produced an accuracy on Hdom estimates of 1.45 m (R2 = 0.92). For V, CNN based estimations ranged from 27.76 to 33.33 m3.ha−1 (R2 between 0.82 and 0.88), while for RF, the RMSE was 27.61 m3.ha−1 (R2 = 0.88). Next, model generalization was assessed by means of a spatial transfer experiment. For Hdom, both the CNN and RF approaches showed similar performances to a global model, however, the CNN based approach showed higher variability on the estimation accuracy, and the variability was related to the forest structure between the trained and tested data (similar tree heights yield better accuracies). For the estimation of V, considering both approaches, the accuracy was dependent on the allometric relationship between Hdom and V in the training and testing regions while lower accuracies on V were obtained when the testing and training regions exhibited a different allometric relationship. Numéro de notice : A2021-869 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2021.112652 Date de publication en ligne : 31/08/2021 En ligne : https://doi.org/10.1016/j.rse.2021.112652 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99118
in Remote sensing of environment > vol 265 (November 2021) . - n° 112652[article]Footprint size design of large-footprint full-waveform LiDAR for forest and topography applications: A theoretical study / Xuebo Yang in IEEE Transactions on geoscience and remote sensing, vol 59 n° 11 (November 2021)
[article]
Titre : Footprint size design of large-footprint full-waveform LiDAR for forest and topography applications: A theoretical study Type de document : Article/Communication Auteurs : Xuebo Yang, Auteur ; Cheng Wang, Auteur ; Xiaohuan Xi, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 9745 - 9757 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] empreinte
[Termes IGN] extraction de la végétation
[Termes IGN] forme d'onde pleine
[Termes IGN] hauteur des arbres
[Termes IGN] lidar à retour d'onde complète
[Termes IGN] onde lidar
[Termes IGN] processus gaussien
[Termes IGN] signal lidarRésumé : (auteur) LiDAR footprint, defined as the illumination area of LiDAR sensor on the ground, is the fundamental unit that the sensor collects information from. The design of footprint size crucially influences the acquired LiDAR signals. For large-footprint full-waveform LiDAR, a well-designed footprint size is indispensable to acquire accurate and complete vertical profiles of scene targets. The methods that design the footprint size are increasingly needed to satisfy various application requirements. In this study, an analytical method to designing the footprint size is proposed for forest and topography applications. It is established based on a mixture Gaussian model and the designed footprint size ensures the signals of vegetation and ground can be completely extracted. Experiment results with our method show that the footprint size is preferably in the range of 10.6–25.0 m for forest application, while it is less than 32.3 m for topography application. The intersection of the two sets satisfies both applications. Furthermore, a series of sensibility studies were performed to analyze the influence of multiple key parameters to the optimal footprint size, including the scene characteristics, instrumental configurations, and application requirements. This study provides a theoretical basis for the design of future large-footprint full-waveform laser altimeters. Numéro de notice : A2021-812 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2021.3054324 Date de publication en ligne : 08/02/2021 En ligne : https://doi.org/10.1109/TGRS.2021.3054324 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98885
in IEEE Transactions on geoscience and remote sensing > vol 59 n° 11 (November 2021) . - pp 9745 - 9757[article]Inflation of wood resources in European forests: The footprints of a big-bang / Jean-Daniel Bontemps in Plos one, vol 16 n° 11 (November 2021)
[article]
Titre : Inflation of wood resources in European forests: The footprints of a big-bang Type de document : Article/Communication Auteurs : Jean-Daniel Bontemps , Auteur Année de publication : 2021 Projets : ARBRE / AgroParisTech (2007 -), LUE / Université de Lorraine Article en page(s) : n° e0259795 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] anthropisation
[Termes IGN] capital sur pied
[Termes IGN] changement climatique
[Termes IGN] dynamique de la végétation
[Termes IGN] exploitation forestière
[Termes IGN] exportation
[Termes IGN] gestion forestière
[Termes IGN] impact sur l'environnement
[Termes IGN] politique forestière
[Termes IGN] politique publique
[Termes IGN] puits de carbone
[Termes IGN] ressources forestières
[Termes IGN] Union Européenne
[Termes IGN] volume en bois
[Vedettes matières IGN] ForesterieRésumé : (auteur) The current increase in European forest resources forms a singularity across the globe. Whether this trend will persist, and how biological and economic trends feature it form crucial issues to green economy challenges and C sequestration. The present screening of Forest Europe 2015 statistics explored the features, inertia and limits of this expansion, and its relationships with countries’ development, forest management and trade, intense in this area of the world. Persisting footprint of past demographic pressure on forests was identified, with opposed traces on their area and growing stock density. Steady growing stock (GS) increases, proportional to GS, not density-limited, and sustained by forest area increases, supported the view of an inflationary forest dynamic. Economic development and liberalism fostered both forest exploitation and production, yielding no significant impact on GS changes. Wood exports exerted a tension on forest exploitation and GS changes, thus lowering GS inflation but providing a resource security margin in the face of expected climate threats. Conflicting a common view, GS inflation and moderate felling-to-increment ratios make increased use of wood resources and C sequestration reconcilable, and GS expansion timely for ongoing EU forest policy processes. Anticipated adverse impacts of ongoing climate change were not clearly identified in these statistics. Numéro de notice : A2021-871 Affiliation des auteurs : LIF (2020- ) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1371/journal.pone.0259795 Date de publication en ligne : 24/11/2021 En ligne : https://doi.org/10.1371/journal.pone.0259795 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99130
in Plos one > vol 16 n° 11 (November 2021) . - n° e0259795[article]Automatic detection of planted trees and their heights using photogrammetric rpa point clouds / Kênia Samara Mourão Santos in Boletim de Ciências Geodésicas, vol 27 n° 3 ([01/10/2021])
[article]
Titre : Automatic detection of planted trees and their heights using photogrammetric rpa point clouds Type de document : Article/Communication Auteurs : Kênia Samara Mourão Santos, Auteur ; Christel Lingnau, Auteur ; Daniel Rodrigues dos Santos, Auteur Année de publication : 2021 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] détection d'arbres
[Termes IGN] hauteur des arbres
[Termes IGN] image aérienne
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] Parana (Brésil)
[Termes IGN] Pinus taeda
[Termes IGN] plantation forestière
[Termes IGN] semis de pointsRésumé : (auteur) This work aims to analyze the potential of the Photogrammetric Point Cloud (PPC) obtained from Remote Piloted Aircraft (RPA) optical images for detecting and obtaining tree heights in a loblolly pine plantation using a global maximum filter. The enhanced algorithm used in this study is then named STD (Single Tree Detection). Field surveys were conducted to count all the trees in the field (Forest Census) and measure the trees’ height with a vertex hypsometer. The results were faced to PCC outcomes. The detection rate (r) was equal to the precision rate (p), indicating that the algorithm reaches a high tree detection performance. In summary, the STD algorithm segmented 2,192 trees, representing 89% of trees recorded in the forest census. The retrieved tree height reached, on average, a height of 17.05 m, whereas slightly higher by the traditional forest inventory (17.42 m). The root-mean-square error (RMSE) and Bias were 47 cm (2.8%) and -37 cm (-2.2%), respectively. The Dunnett test showed that the tree height did not significantly differ between the results obtained by traditional forest inventory from those generated by the STD. It confirms the potential use of PPC for forest inventory procedures. Numéro de notice : A2021-958 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.1590/s1982-21702021000300025 En ligne : https://doi.org/10.1590/s1982-21702021000300025 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100075
in Boletim de Ciências Geodésicas > vol 27 n° 3 [01/10/2021][article]Impact of beam diameter and scanning approach on point cloud quality of terrestrial laser scanning in forests / Meinrad Abegg in IEEE Transactions on geoscience and remote sensing, vol 59 n° 10 (October 2021)
[article]
Titre : Impact of beam diameter and scanning approach on point cloud quality of terrestrial laser scanning in forests Type de document : Article/Communication Auteurs : Meinrad Abegg, Auteur ; Ruedi Boesch, Auteur ; Michael E. Schaepman, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 8153 - 8167 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] densité du peuplement
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] faisceau laser
[Termes IGN] forêt
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] modélisation de la forêt
[Termes IGN] qualité des données
[Termes IGN] semis de points
[Termes IGN] signal lidar
[Termes IGN] Suisse
[Termes IGN] télémétrie laser terrestreRésumé : (auteur) In recent years, portable laser scanning devices and their applications in the context of forest mensuration have undergone rapid methodological and technological developments. Devices have become smaller, lighter, and more affordable, whereas new data-driven methods and software packages have facilitated the derivation of information from point clouds. Thus, terrestrial laser scanning (TLS) is now well established, and laser–object interactions have been studied using theoretical, modeling, and experimental approaches. The representation of scanned objects in terms of accuracy and completeness is a key factor for successful feature extraction. Still, little is known about the influence of TLS and survey properties on point clouds in complex scattering environments, such as forests. In this study, we investigate the influence of laser beam diameter and signal triggering on the quality of point clouds in forested environments. Based on the Swiss National Forest Inventory data, we simulate the TLS measurements in 684 virtual forest stands using a 3-D content creation suite. We show that small objects lack sufficient representation in the point cloud and they are further negatively influenced by large laser beam diameters, dense stands, and large distances from the scanning device. We provide simulations that make it possible to derive a rationale for decisions regarding the appropriate choice of TLS device and survey configuration for forest inventories. Numéro de notice : A2021-709 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1109/TGRS.2020.3037763 Date de publication en ligne : 08/12/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3037763 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98608
in IEEE Transactions on geoscience and remote sensing > vol 59 n° 10 (October 2021) . - pp 8153 - 8167[article]Stand delineation based on laser scanning data and simulated annealing / Yusen Sun in European Journal of Forest Research, vol 140 n° 5 (October 2021)PermalinkThe effects of combining the variables in allometric biomass models on biomass estimates over large forest areas: A european beech case study / Erick O. Osewe in Forests, vol 12 n° 10 (October 2021)PermalinkThe impact of air pollution on the growth of scots pine stands in poland on the basis of dendrochronological analyses / Longina Chojnacka-Ożga in Forests, vol 12 n° 10 (October 2021)PermalinkMapping canopy heights in dense tropical forests using low-cost UAV-derived photogrammetric point clouds and machine learning approaches / He Zhang in Remote sensing, vol 13 n° 18 (September-2 2021)PermalinkModeling in forestry using mixture models fitted to grouped and ungrouped data / Eric K. Zenner in Forests, vol 12 n° 9 (September 2021)PermalinkPicea abies and Pseudotsuga menziesii radial growth in relation to climate: case study from South Bohemia / Jan Mondek in Austrian journal of forest science, vol 2021 n° 3 (2021)PermalinkTarget-based automated matching of multiple terrestrial laser scans for complex forest scenes / Xuming Ge in ISPRS Journal of photogrammetry and remote sensing, vol 179 (September 2021)PermalinkAutomated tree-crown and height detection in a young forest plantation using mask region-based convolutional neural network (Mask R-CNN) / Zhenbang Hao in ISPRS Journal of photogrammetry and remote sensing, vol 178 (August 2021)PermalinkMathematically optimized trajectory for terrestrial close-range photogrammetric 3D reconstruction of forest stands / Karel Kuželka in ISPRS Journal of photogrammetry and remote sensing, vol 178 (August 2021)PermalinkVariation in morphological and wood cell traits in coppice stems of Populus nigra L. and Salix alba L. / Seray Özden in Journal of forest science, vol 67 n° 8 (August 2021)Permalink