Détail de l'auteur
Auteur Simo Poso |
Documents disponibles écrits par cet auteur (1)
Ajouter le résultat dans votre panier Affiner la recherche Interroger des sources externes
Estimation of local forest attributes, utilizing two-phase sampling and auxiliary data / Sakari Tuominen (2007)
Titre : Estimation of local forest attributes, utilizing two-phase sampling and auxiliary data Type de document : Thèse/HDR Auteurs : Sakari Tuominen, Auteur ; Simo Poso, Directeur de thèse Editeur : Helsinki [Finlande] : Faculty of Agriculture and Forestry of the University of Helsinki Année de publication : 2007 Autre Editeur : Helsinki [Finland] : The Finnish Society of Forest Science Importance : 46 p. Format : 21 x 30 cm ISBN/ISSN/EAN : 978-951-651-170-5 Note générale : bibliographie
Academic dissertation to be presented, with the permission of the Faculty of Agriculture and Forestry of University of Helsinki, for public criticism in Auditorium 2, Forest Sciences' Building, Latokartanonkaari 9, HelsinkiLangues : Anglais (eng) Descripteur : [Termes IGN] analyse comparative
[Termes IGN] base de données forestières
[Termes IGN] échantillonnage
[Termes IGN] extraction de données
[Termes IGN] Finlande
[Termes IGN] forêt
[Termes IGN] fusion de données multisource
[Termes IGN] gestion forestière
[Termes IGN] image à très haute résolution
[Termes IGN] image aérienne
[Termes IGN] image spectrale
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] placette d'échantillonnage
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) This thesis examines the feasibility of a forest inventory method based on two-phase sampling in estimating forest attributes at the stand or substand levels for forest management purposes. The method is based on multi-source forest inventory combining auxiliary data consisting of remote sensing imagery or other geographic information and field measurements. Auxiliary data are utilized as first-phase data for covering all inventory units. Various methods were examined for improving the accuracy of the forest estimates. Pre-processing of auxiliary data in the form of correcting the spectral properties of aerial imagery was examined (I), as was the selection of aerial image features for estimating forest attributes (II). Various spatial units were compared for extracting image features in a remote sensing aided forest inventory utilizing very high resolution imagery (III). A number of data sources were combined and different weighting procedures were tested in estimating forest attributes (IV, V). Correction of the spectral properties of aerial images proved to be a straightforward and advantageous method for improving the correlation between the image features and the measured forest attributes. Testing different image features that can be extracted from aerial photographs (and other very high resolution images) showed that the images contain a wealth of relevant information that can be extracted only by utilizing the spatial organization of the image pixel values. Furthermore, careful selection of image features for the inventory task generally gives better results than inputting all extractable features to the estimation procedure. When the spatial units for extracting very high resolution image features were examined, an approach based on image segmentation generally showed advantages compared with a traditional sample plot-based approach. Combining several data sources resulted in more accurate estimates than any of the individual data sources alone. The best combined estimate can be derived by weighting the estimates produced by the individual data sources by the inverse values of their mean square errors. Despite the fact that the plot-level estimation accuracy in two-phase sampling inventory can be improved in many ways, the accuracy of forest estimates based mainly on single-view satellite and aerial imagery is a relatively poor basis for making stand-level management decisions. Note de contenu : Introduction
1 - Two-phase sampling in forest inventory
2 - Remote sensing in forest inventory
3 - Objectives of the thesis and substudies
4 - Materials
5 - Results
6 - DiscussionNuméro de notice : 21697 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Thèse étrangère Note de thèse : Thesis : Forestry : Helsinki : 2007 En ligne : https://helda.helsinki.fi/handle/10138/20667 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90940