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A spatial dataset of forest mensuration collected in black pine plantations in central Italy / Paolo Cantiani in Annals of Forest Science, vol 74 n° 3 (September 2017)
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Titre : A spatial dataset of forest mensuration collected in black pine plantations in central Italy Type de document : Article/Communication Auteurs : Paolo Cantiani, Auteur ; Maurizio Marchi, Auteur Année de publication : 2017 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] arbre (flore)
[Termes IGN] base de données localisées
[Termes IGN] bois mort
[Termes IGN] données de terrain
[Termes IGN] données dendrométriques
[Termes IGN] éclaircie (sylviculture)
[Termes IGN] géoréférencement
[Termes IGN] houppier
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] peuplement forestier
[Termes IGN] Pinus nigra
[Termes IGN] placette d'échantillonnage
[Termes IGN] sol
[Termes IGN] Toscane (Italie)
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) Key message : The dataset provides an exhaustive tree inventory with forest mensuration and spatial location carried out in 54 plots sampled in 45- to 55-year-old black pine plantations, located in two areas of Tuscany (central Italy). Forest mensuration includes horizontal and vertical structure measurements and a total of 4171 trees were geo-referenced. The most abundant species was the black pine, Pinus nigra spp. laricio, for which a total of 3631 trees were observed. The dataset was collected as part of the SelPiBio LIFE project (LIFE13 BIO/IT/000282). Dataset access athttp://doi.org/10.5281/zenodo.438681. Associated metadata available athttps://metadata-afs.nancy.inra.fr/geonetwork/apps/georchestra/?uuid=73591027-0f1e-40a3-95d0-b614517c1290&hl=eng.
Context : The main aim of the SelPiBio LIFE project (www.selpibio.eu) is to demonstrate the effects of two thinning regimes, selective and from below, on soil biodiversity in young black pine stands. The spatial structure of forests and the relationships between trees are a good proxy of overall biodiversity level. Spatial datasets with geo referenced trees and related mensurational data represent the highest level of information for forest inventories and research activities.
Aims : This dataset has been developed during the A2 Action (Assessment of structural and mensurational parameters of the forest stands and the dead wood) of the project, to record the main mensurational parameters of the studied black pine stands. A tree-level database was compiled to describe the vertical and horizontal structure of 54 monitoring plots before the application of the silvicultural treatment.
Methods : In addition to classical in-field measurements (e.g. diameters at breast height, total height of the tree, crown depth etc.), all trees were georeferenced by means of polar coordinates collected from the centre of each monitoring plot, including crown projection on the ground, described with eight points. Then, a polynomial spline function was fitted across the recorded data to obtain a convex polygon and to calculate crown area and crown perimeter of each measured tree in GIS environment.
Results : A polygonal ESRI shapefile in ETRS89/UTM32N reference system (EPSG: 25832) with 4171 records representing the crown projections on the ground of each measured tree with all the mensurational parameters included into the attribute table. The database is freely available under the Creative Commons Attribution-NonCommercial 4. 182 0 License.
Conclusion : With this database, a wide range of forestry-related indices could be easily calculated, including geostatistical analysis and autocorrelation functions, to compare Italian artificial black pine stands with other studied forests.Numéro de notice : A2017-355 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article DOI : 10.1007/s13595-017-0648-8 Date de publication en ligne : 26/06/2017 En ligne : https://doi.org/10.1007/s13595-017-0648-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85722
in Annals of Forest Science > vol 74 n° 3 (September 2017)[article]