Diss. (sammanfattning) Umeå : Sveriges lantbruksuniversitet, 2005. / Härtill 5 uppsatser.

Diss. (sammanfattning) Umeå : Sveriges lantbruksuniv., 2009. / Härtill 4 uppsatser.

Les peuplements forestiers sont une unité de mesure de base pour l'inventaire forestier et la cartographie. Ils sont définis comme de grandes zones forestières (par exemple, de plus de 2 ha) et de composition homogène en terme d'essence d'arbres et d'âge. Leur délimitation précise est généralement effectuée par des opérateurs humains grâce à une analyse visuelle d'images infrarouges à très haute résolution (VHR). Cette tâche est fastidieuse, nécessite beaucoup de temps et doit être automatisée pour un suivi de l'évolution et une mise à jour efficace. Une méthode fondée sur la fusion des données lidar aéroportées et des images multispectrales VHR est proposée pour la délimitation automatique des peuplements forestiers contenant une essence dominante (pureté supérieure à 75%). C'est une principale tâche préliminaire pour la mise à jour de la base de données de la couverture forestière. Les images multispectrales donnent des informations sur les espèces d'arbres alors que les nuages de point Lidar 3D fournissent des informations géométriques sur les arbres et permettent leur extraction individuelle. Les attributs multimodaux sont calculées, à la fois au niveau des pixels et des objets (groupements de pixels ayant une taille similaire aux arbres). Une classification supervisée est ensuite effectuée au niveau de l'objet afin de discriminer grossièrement les espèces d'arbres existantes dans chaque zone d'intérêt. Les résultats de la classification sont ensuite traités pour obtenir des zones homogènes avec des bordures lisses par la minimisation d'une énergie, où des contraintes supplémentaires sont proposées pour former la fonction énergie à minimiser. Les résultats expérimentaux montrent que la méthode proposée fournit des résultats très satisfaisants en termes d'étiquetage et de délimitation, et ce pour des régions géographiquement très éloignées / Forest stands are the basic units for forest inventory and mapping. Stands are defined as large forested areas (e.g., 2 ha) of homogeneous tree species composition and age. Their accurate delineation is usually performed by human operators through visual analysis of very high resolution (VHR) infra-red images. This task is tedious, highly time consuming, and should be automated for scalability and efficient updating purposes. A method based on the fusion of airborne lidar data and VHR multispectral images is proposed for the automatic delineation of forest stands containing one dominant species (purity superior to 75%). This is the key preliminary task for forest land-cover database update. The multispectral images give information about the tree species whereas 3D lidar point clouds provide geometric information on the trees and allow their individual extraction. Multi-modal features are computed, both at pixel and object levels: the objects are groups of pixels having a size similar to trees. A supervised classification is then performed at the object level in order to coarsely discriminate the existing tree species in each area of interest. The classification results are further processed to obtain homogeneous areas with smooth borders by employing an energy minimum framework, where additional constraints are joined to form the energy function. The experimental results show that the proposed method provides very satisfactory results both in terms of stand labeling and delineation, even for spatially distant regions

Diss. (sammanfattning) Alnarp : Sveriges lantbruksuniversitet, 2005. / Härtill 4 uppsatser.

Diss. (sammanfattning). Umeå : Sveriges lantbruksuniv., 2003. / Härtill 5 uppsatser.

Diss. (sammanfattning). Uppsala : Sveriges lantbruksuniversitet, 2005. / Härtill 5 uppsatser.

Diss. (sammanfattning). Umeå : Sveriges lantbruksuniversitet, 2005. / Härtill 4 uppsatser.

Diss. (sammanfattning) Umeå : Sveriges lantbruksuniv., 2006. / Härtill 5 uppsatser.

In recent years, the tech is moving towards a more automized and smarter software. To achieve smarter software the implementation of AI is a step towards that goal. The forest industry needs to become more automized and decrease the manual labor. Decreasing manual labor will both have a positive impact on both the cost and the environment. After doing a literature study the conclusion was to use Mask R-CNN to be able to make the AI learn about the pattern of the different stands. The different stands were extracted and masked for the Mask R-CNN. First there was a comparison between the usage of a computer versus Google Colab, and the results show that Google Colab did deliver the results a little faster than on the computer. Using a smaller area with fewer stands gave a better result and decreased the risk of the algorithm crashing. Using 42 areas with about 10 stands in each gave better results than using one big area with 3248 stands. Using 42 areas gave the result of an average IoU of 42%. Comparing this to 6 areas with about 10 stands each gave the result of 28% IoU. The result of increasing the data split to 70/30 did gave the best IoU with the value of 47%.

Increasingly homogenous forest landscapes, with fewer occurrences of wildfires, deciduous trees and dying, decaying wood has led to fewer appropriate habitats and feeding opportunities for several forest dwelling species, including birds. This study sought to assess the species richness, diversity, and evenness of winterbirds in forest stands where conservation methods (planting of alder trees, free development, burning of forest stands and promotion of deciduous dominance) have been applied, as well as a managed stand of lodgepole pine (Pinus contorta), within SCA:s Tjäderbergets diversity park. These stands were compared with managed stands of Scots pine (Pinus sylvestris). Bird species composition was collected by performing regular 25-minute inventories in each stand type at 5 time periods daily over a 6-day period in late March, 2020. Significant differences in species richness was discovered between a stand of free development and the managed stands as well as a stand treated for deciduous dominance and the managed stands. There were no significant differences with regard to neither species diversity between the observed stand types, nor the presence of specialists or generalists. Evenness between the stand types showed little variation. These results may be due to the overall low number of unique species and individuals in each stand type which likely resulted from low statistical power of the statistical tests. Further research into the effects of conservation measures in forests stands on bird fauna are needed to obtain conclusive results on how conservation measures affect local bird assemblages.