Digitalni repozitorij raziskovalnih organizacij Slovenije

Iskanje po repozitoriju
A+ | A- | Pomoč | SLO | ENG

Iskalni niz: išči po
išči po
išči po
išči po

Možnosti:
  Ponastavi


Iskalni niz: "ključne besede" (National Forest Inventory) .

1 - 5 / 5
Na začetekNa prejšnjo stran1Na naslednjo stranNa konec
1.
National Forest Inventory in Slovenia (history and current design)
Mitja Skudnik, Gal Kušar, 2024, druge monografije in druga zaključena dela

Ključne besede: national forest inventory, history, statistical design
Objavljeno v DiRROS: 20.05.2024; Ogledov: 226; Prenosov: 306
.pdf Celotno besedilo (7,52 MB)

2.
3.
National Forest Inventory (NFI) in Slovenia : purpose, role and use of results
Mitja Skudnik, Primož Simončič, 2023, prispevek na konferenci brez natisa

Ključne besede: national forest inventory, monitoring, developement of forests, national level, Slovenia
Objavljeno v DiRROS: 24.07.2023; Ogledov: 548; Prenosov: 205
.pdf Celotno besedilo (4,91 MB)

4.
5.
Artificial neural networks as an alternative method to nonlinear mixed-effects models for tree height predictions
Mitja Skudnik, Jernej Jevšenak, 2022, izvirni znanstveni članek

Povzetek: Tree heights are one of the most important aspects of forest mensuration, but data are often unavailable due to costly and time-consuming field measurements. Therefore, various types of models have been developed for the imputation of tree heights for unmeasured trees, with mixed-effects models being one of the most commonly applied approaches. The disadvantage here is the need of sufficient sample size per tree species for each plot, which is often not met, especially in mixed forests. To avoid this limitation, we used principal component analysis (PCA) for the grouping of similar plots based on the most relevant site descriptors. Next, we compared mixed-effects models with height-diameter models based on artificial neural networks (ANN). In terms of root mean square error (RMSE), mixed-effects models provided the most accurate tree height predictions at the plot level, especially for tree species with a smaller number of tree height measurements. When plots were grouped using the PCA and the number of observations per category increased, ANN predictions improved and became more accurate than those provided by mixed-effects models. The performance of ANN also increased when the competition index was included as an additional explanatory variable. Our results show that in the pursuit of the most accurate modelling approach for tree height predictions, ANN should be seriously considered, especially when the number of tree measurements and their distribution is sufficient.
Ključne besede: height-diameter models, national forest inventory, permanent sample plot, mixed forests, model comparison, principal component analysis
Objavljeno v DiRROS: 08.06.2022; Ogledov: 651; Prenosov: 295
URL Povezava na datoteko

Iskanje izvedeno v 1 sek.
Na vrh