Détail de l'auteur
Auteur Janis Donis |
Documents disponibles écrits par cet auteur
Ajouter le résultat dans votre panier Affiner la recherche Interroger des sources externesHarmonisation of stem volume estimates in European National Forest Inventories / Thomas Gschwantner in Annals of Forest Science [en ligne], vol 76 n° 1 (March 2019)
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 Année de publication : 2019 Projets : DIABOLO / Packalen, Tuula Article en page(s) : n° 24 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] bois sur pied
[Termes descripteurs IGN] diamètre à hauteur de poitrine
[Termes descripteurs IGN] Europe (géographie politique)
[Termes descripteurs IGN] harmonisation des données
[Termes descripteurs IGN] inventaire forestier étranger (données)
[Termes descripteurs IGN] ressources forestières
[Termes descripteurs IGN] volume en bois
[Vedettes matières IGN] Inventaire forestierRésumé : (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
in Annals of Forest Science [en ligne] > vol 76 n° 1 (March 2019) . - n° 24[article]
Titre : Tree cover mapping using hybrid fuzzy C-means method and multispectral satellite images Type de document : Article/Communication Auteurs : Linda Gulbe, Auteur ; Aleksandrs Kozlovs, Auteur ; Janis Donis, Auteur ; Agris Tradkovs, Auteur Année de publication : 2019 Article en page(s) : pp 113 - 123 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes descripteurs IGN] carte de la végétation
[Termes descripteurs IGN] classification barycentrique
[Termes descripteurs IGN] classification floue
[Termes descripteurs IGN] estimation statistique
[Termes descripteurs IGN] image Landsat-8
[Termes descripteurs IGN] image Landsat-ETM+
[Termes descripteurs IGN] image Landsat-OLI
[Termes descripteurs IGN] image Landsat-TM
[Termes descripteurs IGN] image multibande
[Termes descripteurs IGN] image Sentinel-MSI
[Termes descripteurs IGN] inventaire forestier (techniques et méthodes)
[Termes descripteurs IGN] inventaire forestier étranger (données)
[Termes descripteurs IGN] LettonieRésumé : (auteur) Countrywide up-to-date tree cover maps provide valuable information for planning and management purposes to investigate location of the resources and to identify afforestation and deforestation patterns. Landsat programme offers freely available satellite data with time span more than three decades and it can serve as bases for tree cover map calculation using satellite image classification; however, practical use of classification methods is limited due to lack of user-friendly solutions and complex interpretation of the results. The objective of this study is to evaluate user-friendly hybrid classification scheme for tree cover mapping in Latvia and to explore the nature of the spectral classes and consistency of the results when methodology is applied to images of different dates. Tree cover in this context means the area covered by crown of the tree, which may or may not be considered as forest according to local provisions. Tree cover is estimated using unsupervised fuzzy c-means methods with the stability check to ensure the presence of the same spectral classes in independent tests. Spectral classes are classified into two categories: tree cover and other by employing k-nearest neighbours. Such approach does not require high quality sample data and does not include user defined internal parameters of the algorithms (however, they can be specified if needed). The best overall accuracy achieved for year 2014 was 94.2% with producer's accuracy 98.7% (tree cover), 90.5% (other land cover), user's accuracy 90.0% (tree cover), 98.8% (other land cover) and kappa 0.89. Consistency studies showed high impact (within 10% of overall accuracy) of unique conditions during the image acquisition. Some of the spectral classes represent borderline case between relatively dense tree cover and other land cover types like sparse young stands. Those cases are the main threat to the consistency between the results of different dates and seasons. Numéro de notice : A2019-375 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : sans En ligne : https://www.balticforestry.mi.lt/bf/PDF_Articles/2019-25%5B1%5D/Baltic%20Forestr [...] Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93417
in Baltic forestry > vol 25 n° 1 (2019) . - pp 113 - 123[article]
