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Two-phase forest inventory using very-high-resolution laser scanning / Henrik J. Persson in Remote sensing of environment, vol 271 (March- 2 2022)  

Public [article]  inRemote sensing of environment > vol 271 (March- 2 2022) . - n° 112909 Titre : Two-phase forest inventory using very-high-resolution laser scanning Type de document : Article/Communication Auteurs : Henrik J. Persson, Auteur ; Kenneth Olofsson, Auteur ; Johan Holmgren, Auteur Année de publication : 2022 Article en page(s) : n° 112909 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse comparative [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] échantillonnage [Termes IGN] forêt boréale [Termes IGN] hauteur des arbres [Termes IGN] inférence statistique [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] lasergrammétrie [Termes IGN] modélisation de la forêt [Termes IGN] peuplement forestier [Termes IGN] Suède [Termes IGN] télémétrie laser terrestre [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) In this study, we compared a two-phase laser-scanning-based forest inventory of stands versus a traditional field inventory using sample plots. The two approaches were used to estimate stem volume (VOL), Lorey's mean height (HL), Lorey's stem diameter (DL), and VOL per tree species in a study area in Sweden. The estimates were compared at the stand level with the harvested reference values obtained using a forest harvester. In the first phase, a helicopter acquired airborne laser scanning (ALS) data with >500 points/m2 along 50-m wide strips across the stands. These strips intersected systematic plots in phase two, where terrestrial laser scanning (TLS) was used to model DL for individual trees. In total, phase two included 99 plots across 10 boreal forest stands in Sweden (lat 62.9° N, long 16.9° E). The single trees were segmented in both the ALS and TLS data and linked to each other. The very-high-resolution ALS data enabled us to directly measure tree heights and also classify tree species using a convolutional neural network. Stem volume was predicted from the predicted DBH and the estimated height, using national models, and aggregated at the stand level. The study demonstrates a workflow to derive forest variables and stand-level statistics that has potential to replace many manual field inventories thanks to its time efficiency and improved accuracy. To evaluate the inventories, we estimated bias, RMSE, and precision, expressed as standard error. The laser-scanning-based inventory provided estimates with an accuracy considerably higher than the field inventory. The RMSE was 17 m3/ha (7.24%), 0.9 m (5.63%), and 16 mm (5.99%) for VOL, HL, and DL respectively. The tree species classification was generally successful and improved the three species-specific VOL estimates by 9% to 74%, compared to field estimates. In conclusion, the demonstrated laser-scanning-based inventory shows potential to replace some future forest inventories, thanks to the increased accuracy demonstrated empirically in the Swedish forest study area. Numéro de notice : A2022-249 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2022.112909 Date de publication en ligne : 22/01/2022 En ligne : https://doi.org/10.1016/j.rse.2022.112909 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100201 [article]

Towards low vegetation identification: A new method for tree crown segmentation from LiDAR data based on a symmetrical structure detection algorithm (SSD) / Langning Huo in Remote sensing of environment, vol 270 (March 2022)  

Public [article]  inRemote sensing of environment > vol 270 (March 2022) . - n° 112857 Titre : Towards low vegetation identification: A new method for tree crown segmentation from LiDAR data based on a symmetrical structure detection algorithm (SSD) Type de document : Article/Communication Auteurs : Langning Huo, Auteur ; Eva Lindberg, Auteur ; Johan Holmgren, Auteur Année de publication : 2022 Article en page(s) : n° 112857 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] forêt boréale [Termes IGN] hauteur à la base du houppier [Termes IGN] houppier [Termes IGN] inventaire forestier étranger (données) [Termes IGN] segmentation [Termes IGN] semis de points [Termes IGN] sous-bois [Termes IGN] sous-étage [Termes IGN] strate végétale [Termes IGN] structure d'un peuplement forestier [Termes IGN] Suède Résumé : (auteur) Obtaining low vegetation data is important in order to quantify the structural characteristics of a forest. Dense three-dimensional (3D) laser scanning data can provide information on the vertical profile of a forest. However, most studies have focused on the dominant and subdominant layers of the forest, while few studies have tried to delineate the low vegetation. To address this issue, we propose a framework for individual tree crown (ITC) segmentation from laser data that focuses on both overstory and understory trees. The framework includes 1) a new algorithm (SSD) for 3D ITC segmentation of dominant trees, by detecting the symmetrical structure of the trees, and 2) removing points of dominant trees and mean shift clustering of the low vegetation. The framework was tested on a boreal forest in Sweden and the performance was compared 1) between plots with different stem density levels, vertical complexities, and tree species composition, and 2) using airborne laser scanning (ALS) data, terrestrial laser scanning (TLS) data, and merged ALS and TLS data (ALS + TLS data). The proposed framework achieved detection rates of 0.87 (ALS + TLS), 0.86 (TLS), and 0.76 (ALS) when validated with field-inventory data (of trees with a diameter at breast height ≥ 4 cm). When validating the estimated number of understory trees by visual interpretation, the framework achieved 19%, 21%, and 39% root-mean-square error values with ALS + TLS, TLS, and ALS data, respectively. These results show that the SSD algorithm can successfully separate laser points of overstory and understory trees, ensuring the detection and segmentation of low vegetation in forest. The proposed framework can be used with both ALS and TLS data, and achieve ITC segmentation for forests with various structural attributes. The results also illustrate the potential of using ALS data to delineate low vegetation. Numéro de notice : A2022-127 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2021.112857 Date de publication en ligne : 03/01/2022 En ligne : https://doi.org/10.1016/j.rse.2021.112857 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99707 [article]

Species identification of individual trees by combining high resolution LiDAR data with multi-spectral images / Johan Holmgren in International Journal of Remote Sensing IJRS, vol 29 n° 5 (March 2008)  

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 29 n° 5 (March 2008) . - pp 1537 - 1552 Titre : Species identification of individual trees by combining high resolution LiDAR data with multi-spectral images Type de document : Article/Communication Auteurs : Johan Holmgren, Auteur ; A. Persson, Auteur ; U. Sodermans, Auteur Année de publication : 2008 Article en page(s) : pp 1537 - 1552 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] analyse discriminante [Termes IGN] données lidar [Termes IGN] flore locale [Termes IGN] houppier [Termes IGN] identification automatique [Termes IGN] image multibande [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] Picea abies [Termes IGN] Pinus sylvestris [Termes IGN] Suède [Termes IGN] sylviculture [Termes IGN] traitement du signal Résumé : (Auteur) The objectives of this study were to identify useful predictive factors for tree species identification of individual trees and to compare classifications based on a combination of LiDAR data and multi-spectral images with classification by the use of each individual data source. Crown segments derived from LiDAR data were mapped to multi-spectral images for extraction of spectral data within individual tree crowns. Several features, related to height distribution of laser returns in the canopy, canopy shape, proportion of different types of laser returns, and intensity of laser returns, were derived from LiDAR data. Data from a test site in southern Sweden were used (lat. 58°30' N, long. 13°40' E). The forest consisted of Norway spruce (Picea abies), Scots pine (Pinus sylvestris), and deciduous trees. Classification into these three tree species groups was validated for 1711 trees that had been detected in LiDAR data within 14 field plots (sizes of 20x50 m or 80x80 m). The LiDAR data were acquired by the TopEye MkII system (50 LiDAR measurements per m) and the multi-spectral images were taken by the Zeiss/Intergraph Digital Mapping Camera. The overall classification accuracy was 96% when both data sources were combined. Copyright Taylor & Francis Numéro de notice : A2008-083 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160701736471 En ligne : https://doi.org/10.1080/01431160701736471 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29078 [article]

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Detecting and measuring individual trees using an airborne laser scanner / A. Persson in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 9 (September 2002)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 68 n° 9 (September 2002) . - pp 925 - 932 Titre : Detecting and measuring individual trees using an airborne laser scanner Type de document : Article/Communication Auteurs : A. Persson, Auteur ; Johan Holmgren, Auteur Année de publication : 2002 Article en page(s) : pp 925 - 932 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] arbre (flore) [Termes IGN] contour [Termes IGN] données lidar [Termes IGN] erreur moyenne quadratique [Termes IGN] forêt [Termes IGN] houppier [Termes IGN] télémétrie laser aéroporté [Termes IGN] tronc Résumé : (Auteur) High-resolution airborne laser scanner data offer the possibility to detect and measure individual trees. In this study, an algorithm which estimated position, height, and crown diameter of individual trees was validated with field measurements. Because all the trees in this study were measured on the ground with high accuracy, their positions could be linked with laser measurements, making validation on an individual tree basis possible. In total, 71 percent of the trees were correctly detected using laser scanner data. Because a large portion of the undetected trees had a small stem diameter, 91 percent of the total stem volume was detected. Height and crown diameter of detected trees could be estimated with a root-mean-square error (RMSE) of 0,63 m and 0,61 m, respectively. Stem diameter was estimated, using laser measured tree height and crown diameter, with an RMSE of 3,8 cm. Different laser beam diameters (0,26 to 3,68 m) were also tested, the smallest beam size showing a better detection rate in dense forest. However, estimates of tree height and crown diameter were not affected much by different beam size. Copyright ASPRS Numéro de notice : A2002-323 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : sans En ligne : https://www.asprs.org/wp-content/uploads/pers/2002journal/september/2002_sep_925 [...] Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22234 [article]