Articles containing the keyword 'species proportion'

Tree species composition is an essential attribute in stand-level forest management inventories and remotely sensed data might be useful for its estimation. Previous studies on this topic have had several operational drawbacks, e.g., performance studied at a small scale and at a single tree-level with large fieldwork costs. The current study presents the results from a large-area inventory providing species composition following an operational area-based approach. The study utilizes a combination of airborne laser scanning and hyperspectral data and 97 field sample plots of 250 m² collected over 350 km² of productive forest in Norway. The results show that, with the availability of hyperspectral data, species-specific volume proportions can be provided in operational forest management inventories with acceptable results in 90% of the cases at the plot level. Dominant species were classified with an overall accuracy of 91% and a kappa-value of 0.73. Species-specific volumes were estimated with relative root mean square differences of 34%, 87%, and 102% for Norway spruce (Picea abies (L.) Karst.), Scots pine (Pinus sylvestris L.), and deciduous species, respectively. A novel tree-based approach for selecting pixels improved the results compared to a traditional approach based on the normalized difference vegetation index.

• Ørka, Norwegian University of Life Sciences, Faculty of Environmental Sciences and Natural Resource Management, P.O. Box 5003, NO-1432 Ås, Norway https://orcid.org/0000-0002-7492-8608 E-mail: hans-ole.orka@nmbu.no
• Hansen, Norwegian University of Life Sciences, Faculty of Environmental Sciences and Natural Resource Management, P.O. Box 5003, NO-1432 Ås, Norway; Norwegian Forest Extension Institute, Honnevegen 60, NO-2836 Biri, Norway https://orcid.org/0000-0001-5174-4497 E-mail: eh@skogkurs.no
• Dalponte, Department of Sustainable Agro-ecosystems and Bioresources, Research and Innovation Centre, Fondazione E. Mach, Via E. Mach 1, 38010 San Michele all’Adige, TN, Italy https://orcid.org/0000-0001-9850-8985 E-mail: michele.dalponte@fmach.it
• Gobakken, Norwegian University of Life Sciences, Faculty of Environmental Sciences and Natural Resource Management, P.O. Box 5003, NO-1432 Ås, Norway https://orcid.org/0000-0001-5534-049X E-mail: terje.gobakken@nmbu.no
• Næsset, Norwegian University of Life Sciences, Faculty of Environmental Sciences and Natural Resource Management, P.O. Box 5003, NO-1432 Ås, Norway E-mail: erik.naesset@nmbu.no

Crown dimensions are correlated to growth of other parts of a tree and often used as predictors in growth models. The crown-to-bole diameter ratio (CDBDR), which is a ratio of maximum crown width to diameter at breast height (DBH), was modelled using data from permanent sample plots located on Norway spruce (Picea abies (L.) Karst.) and European beech (Fagus sylvatica L.) stands in different parts of the Czech Republic. Among various tree and stand-level measures evaluated, DBH, height to crown base (HCB), dominant height (HDOM), basal area of trees larger in diameter than a subject tree (BAL), basal area proportion of the species of interest (BAPOR), and Hegyi’s competition index (CI) were found to be significant predictors in the CDBDR model. Random effects were included using the mixed-effects modelling to describe sample plot-level variation. For each species, the mixed-effects model described a larger part of the variation of the CDBDR than nonlinear ordinary least squares model with no trend in the residuals. The spatially explicit mixed-effects model showed more attractive fit statistics [conditional R² ≈ 0.73 (spruce), 0.78 (beech)] than its spatially inexplicit counterpart [conditional R² ≈ 0.71 (spruce), 0.76 (beech)]. The model showed that CDBDR increased with increasing HDOM – a measure that combines the stand development stage and site quality – but decreased with increasing HCB and competition (increasing BAL and CI), and decreasing proportions of the species of interest (increasing BAPOR). For both species, the spatially explicit mixed-effects model should be a preferred choice for a precise prediction of the CDBDR. The CDBDR model will have various management implications such as determination of spacing, stand basal area, stocking, and planning of appropriate species mixture.

• Sharma, Faculty of Forestry and Wood Sciences, Czech University of Life Sciences Prague, Kamýcká 129, 16521, Praha 6 – Suchdol, Czech Republic E-mail: sharmar@fld.czu.cz
• Vacek, Faculty of Forestry and Wood Sciences, Czech University of Life Sciences Prague, Kamýcká 129, 16521, Praha 6 – Suchdol, Czech Republic E-mail: vacekz@fld.czu.cz
• Vacek, Faculty of Forestry and Wood Sciences, Czech University of Life Sciences Prague, Kamýcká 129, 16521, Praha 6 – Suchdol, Czech Republic E-mail: vacekstanislav@fld.czu.cz