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Mapping aboveground biomass and its prediction uncertainty using LiDAR and field data, accounting for tree-level allometric and LiDAR model errors / Svetlana Saarela in Forest ecosystems, vol 7 (2020)
[article]
Titre : Mapping aboveground biomass and its prediction uncertainty using LiDAR and field data, accounting for tree-level allometric and LiDAR model errors Type de document : Article/Communication Auteurs : Svetlana Saarela, Auteur ; André Wästlund, Auteur ; Emma Hölmstrom, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : n° 43 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] biomasse aérienne
[Termes IGN] carte thématique
[Termes IGN] données allométriques
[Termes IGN] données de terrain
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] erreur de modèle
[Termes IGN] inférence statistique
[Termes IGN] modèle d'incertitude
[Termes IGN] modèle de croissance végétale
[Termes IGN] modèle non linéaire
[Termes IGN] semis de points
[Termes IGN] SuèdeRésumé : (auteur) Background: The increasing availability of remotely sensed data has recently challenged the traditional way of performing forest inventories, and induced an interest in model-based inference. Like traditional design-based inference, model-based inference allows for regional estimates of totals and means, but in addition for wall-to-wall mapping of forest characteristics. Recently Light Detection and Ranging (LiDAR)-based maps of forest attributes have been developed in many countries and been well received by users due to their accurate spatial representation of forest resources. However, the correspondence between such mapping and model-based inference is seldom appreciated. In this study, we applied hierarchical model-based inference to produce aboveground biomass maps as well as maps of the corresponding prediction uncertainties with the same spatial resolution. Further, an estimator of mean biomass at regional level, and its uncertainty, was developed to demonstrate how mapping and regional level assessment can be combined within the framework of model-based inference.
Results: Through a new version of hierarchical model-based estimation, allowing models to be nonlinear, we accounted for uncertainties in both the individual tree-level biomass models and the models linking plot level biomass predictions with LiDAR metrics. In a 5005 km2 large study area in south-central Sweden the predicted aboveground biomass at the level of 18 m ×18 m map units was found to range between 9 and 447 Mg ·ha−1. The corresponding root mean square errors ranged between 10 and 162 Mg ·ha−1. For the entire study region, the mean aboveground biomass was 55 Mg ·ha−1 and the corresponding relative root mean square error 8%. At this level 75% of the mean square error was due to the uncertainty associated with tree-level models.
Conclusions: Through the proposed method it is possible to link mapping and estimation within the framework of model-based inference. Uncertainties in both tree-level biomass models and models linking plot level biomass with LiDAR data are accounted for, both for the uncertainty maps and the overall estimates. The development of hierarchical model-based inference to handle nonlinear models was an important prerequisite for the study.Numéro de notice : A2020-814 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1186/s40663-020-00245-0 Date de publication en ligne : 03/07/2020 En ligne : https://doi.org/10.1186/s40663-020-00245-0 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96987
in Forest ecosystems > vol 7 (2020) . - n° 43[article]Modélisation d'une maquette sur la base de données LiDAR et intégration d'un projet 3D / Julien Brunner in Géomatique suisse, vol 118 n° 6 (juin 2020)
[article]
Titre : Modélisation d'une maquette sur la base de données LiDAR et intégration d'un projet 3D Titre original : Gestaltung eines Modells auf der Grundlage von LiDAR-Daten und Integration eines 3D-Projekts = Modellizzazione di una maquette in base ai dati LiDAR e all'integrazione di un progetto 3D Type de document : Article/Communication Auteurs : Julien Brunner, Auteur Année de publication : 2020 Article en page(s) : pp 180 - 187 Langues : Français (fre) Allemand (ger) Italien (ita) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] arbre (flore)
[Termes IGN] ArcGIS
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt alpestre
[Termes IGN] modèle numérique de terrain
[Termes IGN] restitution lasergrammétrique
[Termes IGN] segmentationRésumé : (auteur) Le centre d'équilibre du Valais est connu. Il a été calculé dans les années 2000 par un technicien de la région, avec l'appui de Swisstopo. Situé en pleine forêt, proche de St-Luc, ce point est représenté par un totem, orné du drapeau valaisan. L'AVECEV® a pour projet la valorisation de ce lieu en construisant une passerelle gravitant autour du centre. [...] Le travail présenté ici va donc se concentrer sur la restitution des arbres, avec pour seule base un relevé LiDAR® et créer toutes les analyses qui permettront de définir si les objectifs sont atteints ou non. Numéro de notice : A2020-866 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99262
in Géomatique suisse > vol 118 n° 6 (juin 2020) . - pp 180 - 187[article]Documents numériques
en open access
Modélisation d'une maquette ... - pdf éditeurAdobe Acrobat PDF 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]Réservation
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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 Delineating minor landslide displacements using GPS and terrestrial laser scanning-derived terrain surfaces and trees: a case study of the Slumgullion landslide, Lake City, Colorado / Jin Wang in Survey review, vol 52 n° 372 (May 2020)
[article]
Titre : Delineating minor landslide displacements using GPS and terrestrial laser scanning-derived terrain surfaces and trees: a case study of the Slumgullion landslide, Lake City, Colorado Type de document : Article/Communication Auteurs : Jin Wang, Auteur ; Duo Wang, Auteur ; Shengqi Liu, Auteur ; Boyu Jia, Auteur Année de publication : 2020 Article en page(s) : pp 215 - 223 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] algorithme ICP
[Termes IGN] analyse comparative
[Termes IGN] arbre (flore)
[Termes IGN] Colorado (Etats-Unis)
[Termes IGN] effondrement de terrain
[Termes IGN] Ransac (algorithme)
[Termes IGN] semis de points
[Termes IGN] télémétrie laser terrestreRésumé : (Auteur) Multi-temporal high-density terrestrial laser scanning (TLS) datasets are processed to delineating possible movements from terrain surfaces and trees. Terrain surface movements are estimated with the help of segmentation and random sample consensus (RANSAC) algorithm. Tree movements are interpreted by iterative closest point (ICP) solved translations and rotations of tree point clouds. The capabilities of the proposed methodology were tested using a case study of the Slumgullion landslide, where the trees without clear trunks cover the terrain surfaces. The displacements from the terrain surfaces and trees are similar with the results observed using our global positioning system (GPS) and historic results. Numéro de notice : A2020-177 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2018.1558580 Date de publication en ligne : 25/12/2018 En ligne : https://doi.org/10.1080/00396265.2018.1558580 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94835
in Survey review > vol 52 n° 372 (May 2020) . - pp 215 - 223[article]Filtering of airborne LiDAR bathymetry based on bidirectional cloth simulation / Anxiu Yang in ISPRS Journal of photogrammetry and remote sensing, vol 163 (May 2020)
[article]
Titre : Filtering of airborne LiDAR bathymetry based on bidirectional cloth simulation Type de document : Article/Communication Auteurs : Anxiu Yang, Auteur ; Fanlin Yang, Auteur ; Dianpeng Su, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 49 - 61 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] ajustement de paramètres
[Termes IGN] Chine
[Termes IGN] courbe de Gauss
[Termes IGN] données lidar
[Termes IGN] filtrage de points
[Termes IGN] itération
[Termes IGN] lidar bathymétrique
[Termes IGN] relief sous-marin
[Termes IGN] semis de points
[Termes IGN] télémétrie laser aéroportéRésumé : (auteur) Current filtering methods of airborne LiDAR bathymetry (ALB) point clouds cannot identify negative anomalies or avoid over-filtering of the data. To overcome these problems, we propose a bidirectional cloth simulation filtering (BCSF) method and verify it using captured data. First, a transfer iterative trend surface is established to eliminate the negative anomalies and realize the continuous expression of the seafloor topography. The terrain complexities of the seafloor points are calculated using four extracted feature factors: slope, standard deviation of depth, Gaussian curvature, and roughness. We then calculate the sub-regional terrain complexity and the adaptive distance threshold and obtain user-defined parameters. Finally, sub-regional filtering is carried out, and a filtered surface is established to solve the over-filtering problem of convex and concave seafloor topographies based on the BCSF correction model. To evaluate the performance of the proposed method, the BCSF method was applied to ALB data captured around Yuanzhi Island in the South China Sea. The experimental results show that the BCSF method effectively filters out non-seafloor points and fully preserves the seafloor microtopography to realize the integrity of the seafloor topography. The proposed BCSF method outperforms the cloth simulation filtering method in terms of the elimination rate, which decreases from 38.78% to 2.52% and from 29.52% to 0.70% in the whole study area and local study area, respectively. Consequently, the BCSF method that combines forward filtering with inverse filtering exhibits complementary advantages, avoids over-filtering, and demonstrates strong adaptability and robustness for ALB data. Numéro de notice : A2020-137 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.03.004 Date de publication en ligne : 09/03/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.03.004 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94755
in ISPRS Journal of photogrammetry and remote sensing > vol 163 (May 2020) . - pp 49 - 61[article]Réservation
Réserver ce documentExemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2020051 RAB Revue Centre de documentation En réserve L003 Disponible 081-2020053 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2020052 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Improved supervised learning-based approach for leaf and wood classification from LiDAR point clouds of forests / Sruthi M. Krishna Moorthy in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)PermalinkMethod for extraction of airborne LiDAR point cloud buildings based on segmentation / Maohua Liu in Plos one, vol 15 n° 5 (May 2020)PermalinkOutlier detection and robust plane fitting for building roof extraction from LiDAR data / Emon Kumar Dey in International Journal of Remote Sensing IJRS, vol 41 n° 16 (01-10 May 2020)PermalinkA point cloud feature regularization method by fusing judge criterion of field force / Xijiang Chen in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)PermalinkLa télédétection aéroportée pour la gestion des territoires forestiers de montagne / Jean-Matthieu Monnet in Sciences, eaux & territoires, n° 33 (avril 2020)PermalinkDirectionally constrained fully convolutional neural network for airborne LiDAR point cloud classification / Congcong Wen in ISPRS Journal of photogrammetry and remote sensing, vol 162 (April 2020)PermalinkUsing multi-scale and hierarchical deep convolutional features for 3D semantic classification of TLS point clouds / Zhou Guo in International journal of geographical information science IJGIS, vol 34 n° 4 (April 2020)PermalinkHow 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)PermalinkClassification and segmentation of mining area objects in large-scale spares Lidar point cloud using a novel rotated density network / Yueguan Yan in ISPRS International journal of geo-information, vol 9 n° 3 (March 2020)PermalinkComparison and analysis of results of 3D modelling of complex cultural and historical objects using different types of terrestrial laser scanner / Admir Mulahusic in Survey review, vol 52 n° 371 (March 2020)Permalink