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Changes of tree stem biomass in European forests since 1950 / Aleksandr Lebedev in Journal of forest science, vol 68 n° 3 (March 2022)
[article]
Titre : Changes of tree stem biomass in European forests since 1950 Type de document : Article/Communication Auteurs : Aleksandr Lebedev, Auteur ; Valery Kuzmichev, Auteur Année de publication : 2022 Article en page(s) : pp 107 - 115 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse diachronique
[Termes IGN] Betula pendula
[Termes IGN] biomasse forestière
[Termes IGN] densité du bois
[Termes IGN] écosystème forestier
[Termes IGN] Europe (géographie politique)
[Termes IGN] forêt tempérée
[Termes IGN] Picea abies
[Termes IGN] Pinus sylvestris
[Termes IGN] puits de carbone
[Termes IGN] tronc
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Based on the measurements of the biomass of the stems of 3 699 trees of Scots pine, Norway spruce, and silver birch in Europe since 1950, it has been shown that these tree species show a reduction in biomass and wood density. These results contradict the fact that the volume of wood is directly converted to biomass using the historical values of the conversion rates. From 1950 to 2020 the biomass of 1 m3 of the stem with bark decreased on average by 80 kg (–17%) for Scots pine, by 105 kg (–22%) for Norway spruce and by 92 kg (–15%) for silver birch. The results obtained should be taken into account when assessing the technical properties of wood and estimating carbon sequestration by forest biomass. Since decreasing trends in stem biomass have been identified for several tree species, the phenomenon may have a large degree of generality. Such studies should be continued both at the regional and national level and at the global level. Numéro de notice : A2022-366 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.17221/135/2021-JFS Date de publication en ligne : 01/03/2022 En ligne : https://doi.org/10.17221/135/2021-JFS Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100587
in Journal of forest science > vol 68 n° 3 (March 2022) . - pp 107 - 115[article]Comparison of UAV-based LiDAR and digital aerial photogrammetry for measuring crown-level canopy height in the urban environment / Longfei Zhou in Urban Forestry & Urban Greening, vol 69 (March 2022)
[article]
Titre : Comparison of UAV-based LiDAR and digital aerial photogrammetry for measuring crown-level canopy height in the urban environment Type de document : Article/Communication Auteurs : Longfei Zhou, Auteur ; Ran Meng, Auteur ; Yiyang Tan, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 127489 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse comparative
[Termes IGN] arbre urbain
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt urbaine
[Termes IGN] hauteur des arbres
[Termes IGN] houppier
[Termes IGN] image captée par drone
[Termes IGN] modèle numérique de terrain
[Termes IGN] structure-from-motionRésumé : (auteur) Spatial information on urban forest canopy height (FCH) is fundamental for urban forest monitoring and assisting urban planning and management. Traditionally, ground-based canopy height measurements are time-consuming and laborious, making it challenging for periodic inventory of urban FCH at crown level. Airborne-light detection and ranging (LiDAR) sensor can efficiently measure crown-level FCH; however, the high cost of airborne-LiDAR data collection over large scales hinders its wide applications at a high temporal resolution. Previous studies have shown that in some cases, the Unmanned Aerial Vehicle (UAV)-digital aerial photogrammetry (DAP) approach (i.e., UAV-based structure from motion algorithm) is equivalent to or even outperform airborne-LiDAR in measuring forest structure, but few studies have evaluated their performances in measuring FCH in more complex urban environment, across non-ground coverage (including both canopy and building coverage) and topographical slope gradients. Also, the contribution of multi-angle measurement technique from UAV-DAP to FCH estimation accuracy has rarely been explored in the urban environment. Here, we compared the performances of UAV-LiDAR and UAV-DAP approaches on measuring thousands of crown-level FCH at different non-ground coverage and topographical slope areas in an urban environment. Specifically, UAV-LiDAR-based spatial measurements of crown-level FCH were used as the reference after ground-based validation (R2 = 0.88, RMSE = 2.36 m). The accuracy of UAV-DAP approach with/without multi-angle measurement in different non-ground coverage and topographical slope areas were then analyzed. The results showed that although the DAP multi-angle-based approach can improve the accuracy of spatial measurement for crown-level FCH in some cases, non-ground coverage (including both canopy and building coverage) was still the main factor affecting the broad applications of DAP approach in measuring urban FCH: at areas where non-ground coverage 0.95, except for the case of flat areas (i.e., topographical slope 0.95, can significantly improve the accuracy of UAV-DAP approach in measuring crown-level FCH (R2 = 0.91, RMSE =1.61 m). Our study thus provides a complete guidance on the usage of cost-effective UAV-DAP approach for measuring crown-level FCH in the urban environment, which will be helpful for precise urban forest management and improving the efficiency of urban environmental planning. Numéro de notice : A2022-318 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.ufug.2022.127489 Date de publication en ligne : 26/01/2022 En ligne : https://doi.org/10.1016/j.ufug.2022.127489 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100424
in Urban Forestry & Urban Greening > vol 69 (March 2022) . - n° 127489[article]Estimation of uneven-aged forest stand parameters, crown closure and land use/cover using the Landsat 8 OLI satellite image / Sinan Kaptan in Geocarto international, vol 37 n° 5 ([01/03/2022])
[article]
Titre : Estimation of uneven-aged forest stand parameters, crown closure and land use/cover using the Landsat 8 OLI satellite image Type de document : Article/Communication Auteurs : Sinan Kaptan, Auteur ; Hasan Aksoy, Auteur Année de publication : 2022 Article en page(s) : pp 1408 - 1425 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification dirigée
[Termes IGN] correction géométrique
[Termes IGN] forêt inéquienne
[Termes IGN] houppier
[Termes IGN] image Landsat-OLI
[Termes IGN] occupation du sol
[Termes IGN] peuplement forestier
[Termes IGN] Turquie
[Termes IGN] utilisation du solRésumé : (Auteur) This study used the Landsat 8 OLI satellite image and the supervised classification method to estimate uneven-aged forest stand parameters and land use/cover. The spatial success of classification was also investigated. The overall success rates and Kappa values of the classification were, respectively, 74.7% and 0.75 for actual structural type, 84.6% and 0.80 for crown closure, and 88.35% and 0.81 for land use class, whereas the spatial success of classification on the forest cover type map was 36.91% for actual structural type, 64.74% for crown closure, and 41.78% for land use/cover class. The results revealed that the Landsat 8 OLI image can be used to identify stand parameters and land use/cover class. However, because the spatial success rates were below 50% for the actual structural type and land use/cover class of the stand types, it is not suitable for use in spatial classification determination for these classes. Numéro de notice : A2022-277 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1765888 Date de publication en ligne : 20/05/2020 En ligne : https://doi.org/10.1080/10106049.2020.1765888 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100795
in Geocarto international > vol 37 n° 5 [01/03/2022] . - pp 1408 - 1425[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 059-2022051 RAB Revue Centre de documentation En réserve L003 Disponible 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)
[article]
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] SuèdeRésumé : (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
in Remote sensing of environment > vol 270 (March 2022) . - n° 112857[article]Multi-species individual tree segmentation and identification based on improved mask R-CNN and UAV imagery in mixed forests / Chong Zhang in Remote sensing, vol 14 n° 4 (February-2 2022)
[article]
Titre : Multi-species individual tree segmentation and identification based on improved mask R-CNN and UAV imagery in mixed forests Type de document : Article/Communication Auteurs : Chong Zhang, Auteur ; Jiawei Zhou, Auteur ; Huiwen Wang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 874 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] Chine
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] détection de contours
[Termes IGN] échantillonnage de données
[Termes IGN] entropie
[Termes IGN] estimation quantitative
[Termes IGN] feuillu
[Termes IGN] hauteur des arbres
[Termes IGN] image captée par drone
[Termes IGN] peuplement mélangé
[Termes IGN] Pinophyta
[Termes IGN] segmentation d'imageRésumé : (auteur) High-resolution UAV imagery paired with a convolutional neural network approach offers significant advantages in accurately measuring forestry ecosystems. Despite numerous studies existing for individual tree crown delineation, species classification, and quantity detection, the comprehensive situation in performing the above tasks simultaneously has rarely been explored, especially in mixed forests. In this study, we propose a new method for individual tree segmentation and identification based on the improved Mask R-CNN. For the optimized network, the fusion type in the feature pyramid network is modified from down-top to top-down to shorten the feature acquisition path among the different levels. Meanwhile, a boundary-weighted loss module is introduced to the cross-entropy loss function Lmask to refine the target loss. All geometric parameters (contour, the center of gravity and area) associated with canopies ultimately are extracted from the mask by a boundary segmentation algorithm. The results showed that F1-score and mAP for coniferous species were higher than 90%, and that of broadleaf species were located between 75%–85.44%. The producer’s accuracy of coniferous forests was distributed between 0.8–0.95 and that of broadleaf ranged in 0.87–0.93; user’s accuracy of coniferous was distributed between 0.81–0.84 and that of broadleaf ranged in 0.71–0.76. The total number of trees predicted was 50,041 for the entire study area, with an overall error of 5.11%. The method under study is compared with other networks including U-net and YOLOv3. Results in this study show that the improved Mask R-CNN has more advantages in broadleaf canopy segmentation and number detection. Numéro de notice : A2022-168 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/rs14040874 Date de publication en ligne : 11/02/2022 En ligne : https://doi.org/10.3390/rs14040874 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99793
in Remote sensing > vol 14 n° 4 (February-2 2022) . - n° 874[article]A stand-level growth and yield model for thinned and unthinned even-aged Scots pine forests in Norway / Christian Kuehne in Silva fennica, vol 56 n° 1 (January 2022)PermalinkGenerating 2m fine-scale urban tree cover product over 34 metropolises in China based on deep context-aware sub-pixel mapping network / Da He in International journal of applied Earth observation and geoinformation, vol 106 (February 2022)PermalinkQuantifying the shape of urban street trees and evaluating its influence on their aesthetic functions based on mobile lidar data / Tianyu Hu in ISPRS Journal of photogrammetry and remote sensing, vol 184 (February 2022)PermalinkSurvival time and mortality rate of regeneration in the deep shade of a primeval beech forest / R. Petrovska in European Journal of Forest Research, vol 141 n° 1 (February 2022)PermalinkTree mortality caused by Diplodia shoot blight on Pinus sylvestris and other mediterranean pines / Maria Caballol in Forest ecology and management, vol 505 (February-1 2022)PermalinkUse of remotely sensed data to estimate tree species diversity as an indicator of biodiversity in Blouberg Nature Reserve, South Africa / Mangana Rampheri in Geocarto international, vol 37 n° 2 ([15/01/2022])PermalinkDetection of windthrown tree stems on UAV-orthomosaics using U-Net convolutional networks / Stefan Reder in Remote sensing, vol 14 n° 1 (January-1 2022)PermalinkPermalinkGeospatial assessment of urban ecosystem disservices: An example of poisonous urban trees in Berlin, Germany / Peer von Döhren in Urban Forestry & Urban Greening, vol 67 (January 2022)PermalinkPermalink