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inventaire forestier (techniques et méthodes)
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Forêts -- Inventaires, Levés forestiers. Inventaire des ressources naturelles, Topographie, Inventaire de la végétation, Sylviculture. >> >>Terme(s) spécifique(s) : Cartographie forestière. Equiv. LCSH : Forest surveys. |
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Estimation of biomass increase and CUE at a young temperate scots pine stand concerning drought occurrence by combining eddy covariance and biometric methods / Paulina Dukat in Forests, vol 12 n° 7 (July 2021)
[article]
Titre : Estimation of biomass increase and CUE at a young temperate scots pine stand concerning drought occurrence by combining eddy covariance and biometric methods Type de document : Article/Communication Auteurs : Paulina Dukat, Auteur ; Klaudia Ziemblińska, Auteur ; Janusz Olejnik, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 867 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] biomasse forestière
[Termes IGN] changement climatique
[Termes IGN] covariance
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] dioxyde de carbone
[Termes IGN] indice de végétation
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] Pinus sylvestris
[Termes IGN] Pologne
[Termes IGN] production primaire brute
[Termes IGN] puits de carbone
[Termes IGN] sécheresse
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) The accurate estimation of an increase in forest stand biomass has remained a challenge. Traditionally, in situ measurements are done by inventorying a number of trees and their biometric parameters such as diameter at the breast height (DBH) and height; sometimes these are complemented by carbon (C) content studies. Here we present the estimation of net primary productivity (NPP) over a two years period (2019–2020) at a 25-year-old Scots pine stand. Research was based on allometric equations made by direct biomass analysis (tree extraction) and carbon content estimations in individual components of sampled trees, combined with a series of stem diameter increments recorded by a network of band dendrometers. Site-specific allometric equations were obtained using two different approaches: using the whole tree biomass vs DBH (M1), and total dry biomass-derived as a sum of the results from individual tree components’ biomass vs DBH (M2). Moreover, equations for similar forest stands from the literature were used for comparison. Gross primary productivity (GPP) estimated from the eddy-covariance measurements allowed the calculation of carbon use efficiency (CUE = NPP/GPP). The two investigated years differed in terms of the sum and patterns of precipitation distribution, with a moderately dry year of 2019 that followed the extremely dry 2018, and the relatively average year of 2020. As expected, a higher increase in biomass was recorded in 2020 compared to 2019, as determined by both allometric equations based on in situ and literature data. For the former approach, annual NPP estimates reached ca. 2.0–2.1 t C ha−1 in 2019 and 2.6–2.7 t C ha−1 in 2020 depending on the “in situ equations” (M1-M2) used, while literature-derived equations for the same site resulted in NPP values ca. 20–30% lower. CUE was higher in 2020, which resulted from a higher NPP total than in 2019, with lower summer and spring GPP in 2020. However, the CUE values were lower than those reported in the literature for comparable temperate forest stands. A thorough analysis of the low CUE value would require a full interpretation of interrelated physiological responses to extreme conditions. Numéro de notice : A2021-641 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.3390/f12070867 Date de publication en ligne : 30/06/2021 En ligne : https://doi.org/10.3390/f12070867 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98313
in Forests > vol 12 n° 7 (July 2021) . - n° 867[article]Updating of forest stand data by using recent digital photogrammetry in combination with older airborne laser scanning data / Niels Lindgren in Scandinavian journal of forest research, vol 36 n° 5 ([01/07/2021])
[article]
Titre : Updating of forest stand data by using recent digital photogrammetry in combination with older airborne laser scanning data Type de document : Article/Communication Auteurs : Niels Lindgren, Auteur ; André Wästlund, Auteur ; Inka Bohlin, Auteur ; Kenneth Nyström, Auteur ; Mats Nilsson, Auteur ; Hakan Olsson, Auteur Année de publication : 2021 Article en page(s) : pp 401 - 407 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Betula (genre)
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] image aérienne
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] orthoimage
[Termes IGN] photogrammétrie numérique
[Termes IGN] Picea abies
[Termes IGN] Pinus sylvestris
[Termes IGN] Suède
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Accurate and up-to-date data about growing stock volume are essential for forest management planning. Airborne Laser Scanning (ALS) is known for producing accurate wall-to-wall predictions but the data are at present collected at long time intervals. Digital Photogrammetry (DP) is cheaper and often more frequently available but known to be less accurate. This study investigates the potential of using contemporary DP data together with older ALS data and compares this with the case when only old ALS data are trained with recent field data. Combining ALS data from 2010 to 2011 with DP data from 2015, both trained with National Forest Inventory (NFI) field plot data from 2015, improved predictions of growing stock volume. Validation using data from 100 stands inventoried in 2015 gave an RMSE of 24.3% utilizing both old ALS data and recent DP data, 26.0% for old ALS only and 24.9% for recent DP only. If information about management actions were assumed available, combining old ALS and recent DP gave RMSE of 23.0%, only ALS 23.3% and only DP 23.8%. Numéro de notice : A2021-604 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1080/02827581.2021.1936153 En ligne : https://doi.org/10.1080/02827581.2021.1936153 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98333
in Scandinavian journal of forest research > vol 36 n° 5 [01/07/2021] . - pp 401 - 407[article]Forest cover mapping and Pinus species classification using very high-resolution satellite images and random forest / Laura Alonso-Martinez in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2021 (July 2021)
[article]
Titre : Forest cover mapping and Pinus species classification using very high-resolution satellite images and random forest Type de document : Article/Communication Auteurs : Laura Alonso-Martinez, Auteur ; J. Picos, Auteur ; Julia Armesto, Auteur Année de publication : 2021 Article en page(s) : pp 203 - 210 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] carte de la végétation
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] couvert forestier
[Termes IGN] Espagne
[Termes IGN] Eucalyptus (genre)
[Termes IGN] image multibande
[Termes IGN] image Worldview
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] Pinus pinaster
[Termes IGN] Pinus radiata
[Termes IGN] Pinus sylvestris
[Termes IGN] ressources forestières
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Advances in remote sensing technologies are generating new perspectives concerning the role of and methods used for National Forestry Inventories (NFIs). The increase in computation capabilities over the last several decades and the development of new statistical techniques have allowed for the automation of forest resource map generation through image analysis techniques and machine learning algorithms. The availability of large-scale data and the high temporal resolution that satellite platforms provide mean that it is possible to obtain updated information about forest resources at the stand level, thus increasing the quality of the spatial information. However, photointerpretation of satellite and aerial images is still the most common way that remote sensing information is used for NFIs or forest management purposes. This study describes a methodology that automatically maps the main forest covers in Galicia (Eucalyptus spp., conifers and broadleaves) using Worldview-2 and the random forest classifier. Furthermore, the method also evaluates the separate mapping of the three most abundant Pinus tree species in Galicia (Pinus pinaster, Pinus radiata and Pinus sylvestris). According to the results, Worldview-2 multispectral images allow for the efficient differentiation between the main forest classes that are present in Galicia with a very high degree of accuracy (91%) and ample spatial detail. Pinus species can also be efficiently differentiated (83%). Numéro de notice : A2021-493 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.5194/isprs-annals-V-3-2021-203-2021 Date de publication en ligne : 17/06/2021 En ligne : http://dx.doi.org/10.5194/isprs-annals-V-3-2021-203-2021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97958
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol V-2-2021 (July 2021) . - pp 203 - 210[article]Individual tree extraction from UAV lidar point clouds based on self-adaptive mean shift segmentation / Zhenyang Hui in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-1-2021 (July 2021)
[article]
Titre : Individual tree extraction from UAV lidar point clouds based on self-adaptive mean shift segmentation Type de document : Article/Communication Auteurs : Zhenyang Hui, Auteur ; N. Li, Auteur ; Y. Xia, Auteur ; Penggen Cheng, Auteur ; Y. He, Auteur Année de publication : 2021 Conférence : ISPRS 2021, Commission 1, XXIV ISPRS Congress, Imaging today foreseeing tomorrow 05/07/2021 09/07/2021 Nice on-line France OA Annals Commission 1 Article en page(s) : pp 25 - 30 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] algorithme de décalage moyen
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] extraction d'arbres
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] segmentation
[Termes IGN] semis de pointsRésumé : (auteur) Unman aerial vehicle (UAV) LiDAR has been widely used in the field of forestry. Individual tree extraction is a key step for forest inventory. Although many individual tree extraction methods have been proposed, the individual tree extraction accuracy is still low due to the complex forest environments. Moreover, many parameters in these methods generally need to be set. Thus, the degree of automation of the methods is generally low. To solve these problems, this paper proposed an automatic mean shift segmentation method, in which the kernel bandwidths can be calculated self-adaptively. Meanwhile, a hierarchy mean shift segmentation technique was proposed to extract individual tree gradually. A plot-level UAV LiDAR tree dataset was adopted for testing the performance of the proposed method. Experimental results showed that the proposed method can achieve better individual tree extraction result without any parameter setting. Compared with the traditional mean shift segmentation method, both the completeness and mean accuracy of the proposed method are higher. Numéro de notice : A2021-318 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-V-1-2021-25-2021 Date de publication en ligne : 17/06/2021 En ligne : https://doi.org/10.5194/isprs-annals-V-1-2021-25-2021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97950
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol V-1-2021 (July 2021) . - pp 25 - 30[article]Roadside tree extraction and diameter estimation with MMS lidar by using point-cloud image / Genki Takahashi in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2021 (July 2021)
[article]
Titre : Roadside tree extraction and diameter estimation with MMS lidar by using point-cloud image Type de document : Article/Communication Auteurs : Genki Takahashi, Auteur ; H. Masuda, Auteur Année de publication : 2021 Article en page(s) : pp 67 - 74 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] alignement d'arbres
[Termes IGN] apprentissage automatique
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] extraction d'arbres
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] route
[Termes IGN] semis de points
[Termes IGN] Tokyo (Japon)
[Termes IGN] zone urbaineRésumé : (auteur) Efficient management of roadside trees for local governments is important. Mobile Mapping System (MMS) equipped with a high-density LiDAR scanner has the possibility to be applied to estimate DBH of roadside trees using point clouds. In this study, we propose a method for detecting roadside trees and estimating their DBHs automatically from MMS point clouds. In our method, point clouds captured using the MMS are mapped on a 2D image plane, and they are converted into a wireframe model by connecting adjacent points. Then, geometric features are calculated for each point in the wireframe model. Tree points are detected using a machine learning technique. The DBH of each tree is calculated using vertically aligned circles extracted from the wireframe model. Our method allows robustly calculating the DBH even if there is a hump at breast height. We evaluated our method using actual MMS data measured in an urban area in Tokyo. Our method achieved a high extraction performance of 100 percent of precision and 95.1 percent of recall for 102 roadside trees. The average accuracy of the DBH was 2.0 cm. These results indicate that our method is useful for the efficient management of roadside trees. Numéro de notice : A2021-491 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-V-2-2021-67-2021 Date de publication en ligne : 17/06/2021 En ligne : http://dx.doi.org/10.5194/isprs-annals-V-2-2021-67-2021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97956
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol V-2-2021 (July 2021) . - pp 67 - 74[article]Forest height estimation from a robust TomoSAR method in the case of small tomographic aperture with airborne dataset at L-band / Xing Peng in Remote sensing, vol 13 n° 11 (June-1 2021)PermalinkHorvitz-Thompson–like estimation with distance-based detection probabilities for circular plot sampling of forests / Kasper Kansanen in Biometrics, vol 77 n° 2 (June 2021)PermalinkIndividual tree identification using a new cluster-based approach with discrete-return airborne LiDAR data / Haijian Liu in Remote sensing of environment, vol 258 (June 2021)PermalinkModel-based estimation of forest canopy height and biomass in the Canadian boreal forest using radar, LiDAR, and optical remote sensing / Michael L. Benson in IEEE Transactions on geoscience and remote sensing, vol 59 n° 6 (June 2021)PermalinkPredicting tree species based on the geometry and density of aerial laser scanning point cloud of treetops / Nina Kranjec in Geodetski vestnik, vol 65 n° 2 (June - August 2021)PermalinkAutomated street tree inventory using mobile LiDAR point clouds based on Hough transform and active contours / Amir Hossein Safaie in ISPRS Journal of photogrammetry and remote sensing, vol 174 (April 2021)PermalinkVariations in temperate forest biomass ratio along three environmental gradients are dominated by interspecific differences in wood density / Baptiste Kerfriden in Plant ecology, vol 222 n° 3 (March 2021)PermalinkForest height estimation using a single-pass airborne L-band polarimetric and interferometric SAR system and tomographic techniques / Yue Huang in Remote sensing, Vol 13 n° 3 (February 2021)PermalinkA density-based algorithm for the detection of individual trees from LiDAR data / Melissa Latella in Remote sensing, Vol 13 n° 2 (January-2 2021)PermalinkEvaluation de la qualité des mesures de croissance pluriannuelles des données d’inventaire forestier national en vue de leur utilisation en monitoring à haute fréquence de la production forestière / Félix Altenhoven (2021)PermalinkFOSTER - An R package for forest structure extrapolation / Martin Queinnec in Plos one, vol 16 n° 1 (January 2021)PermalinkUne généralisation de la méthode de partage des poids dans le cas où la base de sondage est continue / Philippe Brion (2021)PermalinkHigh resolution mapping of forest resources and prediction reliability using multisource inventory approach / Ankit Sagar (2021)PermalinkLes inventaires forestiers nationaux : des méthodes dynamiques pour un sujet dynamique / Olivier Bouriaud (2021)PermalinkThe role of net ecosystem productivity and of inventories in climate change research: the need for “net ecosystem productivity with harvest”, NEPH / E.D. Schulze in Forest ecosystems, vol 8 (2021)PermalinkUnit-level small area estimation of forest inventory with GEDI auxiliary information in France / Shaohui Zhang (2021)PermalinkCNN-based tree species classification using high resolution RGB image data from automated UAV observations / Sebastian Egli in Remote sensing, vol 12 n° 23 (December-2 2020)PermalinkMapping forest tree species in high resolution UAV-based RGB-imagery by means of convolutional neural networks / Felix Schiefer in ISPRS Journal of photogrammetry and remote sensing, vol 170 (December 2020)PermalinkEffects of radiometric correction on cover type and spatial resolution for modeling plot level forest attributes using multispectral airborne LiDAR data / Wai Yeung Yan in ISPRS Journal of photogrammetry and remote sensing, vol 169 (November 2020)PermalinkTowards an optimization of sample plot size and scanner position layout for terrestrial laser scanning in multi-scan mode / Tim Ritter in Forests, vol 11 n° 10 (October 2020)Permalink