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Harmonisation of stem volume estimates in European National Forest Inventories / Thomas Gschwantner in Annals of Forest Science [en ligne], vol 76 n° 1 (March 2019)  

Public [article]  inAnnals of Forest Science [en ligne] > vol 76 n° 1 (March 2019) . - n° 24 Titre : Harmonisation of stem volume estimates in European National Forest Inventories Type de document : Article/Communication Auteurs : Thomas Gschwantner, Auteur ; Iciar A. Alberdi, Auteur ; Andras Balazs, Auteur ; Sébastien Bauwens, Auteur ; Susann Bender, Auteur ; Dragan Borotra, Auteur ; Michal Bosela, Auteur ; Olivier Bouriaud , Auteur ; Isabel Canelas, Auteur ; Janis Donis, Auteur ; Alexandra Freudenschuss, Auteur ; Jean-Christophe Hervé (1961-2017) , Auteur ; et al., Auteur ; François Morneau , Auteur ; et al., Auteur Année de publication : 2019 Projets : DIABOLO / Packalen, Tuula Article en page(s) : n° 24 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] bois sur pied [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] Europe (géographie politique) [Termes IGN] harmonisation des données [Termes IGN] inventaire forestier étranger (données) [Termes IGN] ressources forestières [Termes IGN] volume en bois [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Key message: Volume predictions of sample trees are basic inputs for essential National Forest Inventory (NFI) estimates. The predicted volumes are rarely comparable among European NFIs because of country-specific dbh-thresholds and differences regarding the inclusion of the tree parts stump, stem top, and branches. Twenty-one European NFIs implemented harmonisation measures to provide consistent stem volume predictions for comparable forest resource estimates. Context: The harmonisation of forest information has become increasingly important. International programs and interest groups from the wood industry, energy, and environmental sectors require comparable information. European NFIs as primary source of forest information are well-placed to support policies and decision-making processes with harmonised estimates. Aims: The main objectives were to present the implementation of stem volume harmonisation by European NFIs, to obtain comparable growing stocks according to five reference definitions, and to compare the different results. Methods: The applied harmonisation approach identifies the deviations between country-level and common reference definitions. The deviations are minimised through country-specific bridging functions. Growing stocks were calculated from the un-harmonised, and harmonised stem volume estimates and comparisons were made. Results: The country-level growing stock results differ from the Cost Action E43 reference definition between − 8 and + 32%. Stumps and stem tops together account for 4 to 13% of stem volume, and large branches constitute 3 to 21% of broadleaved growing stock. Up to 6% of stem volume is allocated below the dbh-threshold. Conclusion: Comparable volume figures are available for the first time on a large-scale in Europe. The results indicate the importance of harmonisation for international forest statistics. The presented work contributes to the NFI harmonisation process in Europe in several ways regarding comparable NFI reporting and scenario modelling. Numéro de notice : A2019-619 Affiliation des auteurs : LIF+Ext (2012-2019) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-019-0800-8 date de publication en ligne : 28/02/2019 En ligne : https://doi.org/10.1007/s13595-019-0800-8 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95351 [article]

Hyperspectral UAV-imagery and photogrammetric canopy height model in estimating forest stand variables / Sakari Tuominen in Silva fennica, vol 51 n° 5 (2017)  

Public [article]  inSilva fennica > vol 51 n° 5 (2017) Titre : Hyperspectral UAV-imagery and photogrammetric canopy height model in estimating forest stand variables Type de document : Article/Communication Auteurs : Sakari Tuominen, Auteur ; Andras Balazs, Auteur ; Eija Honkavaara, Auteur ; et al., Auteur Année de publication : 2017 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] classification barycentrique [Termes IGN] drone [Termes IGN] estimation de quantité [Termes IGN] étalonnage radiométrique [Termes IGN] image aérienne [Termes IGN] image hyperspectrale [Termes IGN] image RVB [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] modèle numérique de surface de la canopée [Termes IGN] peuplement forestier [Termes IGN] photogrammétrie numérique [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Remote sensing using unmanned aerial vehicle (UAV) -borne sensors is currently a highly interesting approach for the estimation of forest characteristics. 3D remote sensing data from airborne laser scanning or digital stereo photogrammetry enable highly accurate estimation of forest variables related to the volume of growing stock and dimension of the trees, whereas recognition of tree species dominance and proportion of different tree species has been a major complication in remote sensing-based estimation of stand variables. In this study, the use of UAV-borne hyperspectral imagery was examined in combination with a high-resolution photogrammetric canopy height model in estimating forest variables of 298 sample plots. Data were captured from eleven separate test sites under weather conditions varying from sunny to cloudy and partially cloudy. Both calibrated hyperspectral reflectance images and uncalibrated imagery were tested in combination with a canopy height model based on RGB camera imagery using the k-nearest neighbour estimation method. The results indicate that this data combination allows accurate estimation of stand volume, mean height and diameter: the best relative RMSE values for those variables were 22.7%, 7.4% and 14.7%, respectively. In estimating volume and dimension-related variables, the use of a calibrated image mosaic did not bring significant improvement in the results. In estimating the volumes of individual tree species, the use of calibrated hyperspectral imagery generally brought marked improvement in the estimation accuracy; the best relative RMSE values for the volumes for pine, spruce, larch and broadleaved trees were 34.5%, 57.2%, 45.7% and 42.0%, respectively. Numéro de notice : A2017-645 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14214/sf.7721 En ligne : https://doi.org/10.14214/sf.7721 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=87000 [article]

Improving Finnish multi-source national forest inventory by 3D aerial imaging / Sakari Tuominen in Silva fennica, vol 51 n° 4 (2017)

Public [article]  inSilva fennica > vol 51 n° 4 (2017) Titre : Improving Finnish multi-source national forest inventory by 3D aerial imaging Type de document : Article/Communication Auteurs : Sakari Tuominen, Auteur ; Timo P Pitkänen, Auteur ; Andras Balazs, Auteur ; et al., Auteur Année de publication : 2017 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] classification barycentrique [Termes IGN] corrélation automatique de points homologues [Termes IGN] distribution spatiale [Termes IGN] Finlande [Termes IGN] image aérienne [Termes IGN] image satellite [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] inventaire forestier étranger (données) [Termes IGN] modèle numérique de surface de la canopée [Termes IGN] photogrammétrie numérique [Termes IGN] placette d'échantillonnage [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Optical 2D remote sensing techniques such as aerial photographing and satellite imaging have been used in forest inventory for a long time. During the last 15 years, airborne laser scanning (ALS) has been adopted in many countries for the estimation of forest attributes at stand and sub-stand levels. Compared to optical remote sensing data sources, ALS data are particularly well-suited for the estimation of forest attributes related to the physical dimensions of trees due to its 3D information. Similar to ALS, it is possible to derive a 3D forest canopy model based on aerial imagery using digital aerial photogrammetry. In this study, we compared the accuracy and spatial characteristics of 2D satellite and aerial imagery as well as 3D ALS and photogrammetric remote sensing data in the estimation of forest inventory variables using k-NN imputation and 2469 National Forest Inventory (NFI) sample plots in a study area covering approximately 5800 km2. Both 2D data were very close to each other in terms of accuracy, as were both the 3D materials. On the other hand, the difference between the 2D and 3D materials was very clear. The 3D data produce a map where the hotspots of volume, for instance, are much clearer than with 2D remote sensing imagery. The spatial correlation in the map produced with 2D data shows a lower short-range correlation, but the correlations approach the same level after 200 meters. The difference may be of importance, for instance, when analyzing the efficiency of different sampling designs and when estimating harvesting potential. Numéro de notice : A2017-646 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=87003 [article]