Publikasjoner
NIBIOs ansatte publiserer flere hundre vitenskapelige artikler og forskningsrapporter hvert år. Her finner du referanser og lenker til publikasjoner og andre forsknings- og formidlingsaktiviteter. Samlingen oppdateres løpende med både nytt og historisk materiale. For mer informasjon om NIBIOs publikasjoner, besøk NIBIOs bibliotek.
2013
Sammendrag
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Sammendrag
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Sammendrag
An 11-year remotely sensed surface albedo dataset coupled with historical meteorological and stand-level forest management data for a variety of stands in Norway’s most productive logging region is used to develop regression models describing temporal changes in forest albedo following clear-cut harvest disturbance events. Datasets are grouped by dominant tree species, and two alternate multiple regression models are developed and tested following a potential-modifier approach. This result in models with statistically significant parameters (p < 0.05) that explain a large proportion of the observed variation, requiring a single canopy modifier predictor coupled with either monthly or annual mean air temperature as a predictor of a stand’s potential albedo. Models based on annual mean temperature predict annual albedo with errors (RMSE) in the range of 0.025–0.027, while models based on monthly mean temperature predict monthly albedo with errors ranging between of 0.057–0.065 depending on the dominant tree species. While both models have the potential to be transferable to other boreal regions with similar forest management regimes, further validation efforts are required. As active management of boreal forests is increasingly seen as a means to mitigate climate change, the presented models can be used with routine forest inventory and meteorological data to predict albedo evolution in managed forests throughout the region, which, together with carbon cycle modeling, can lead to more holistic climate impact assessments of alternative forest harvest scenarios and forest product systems.
Sammendrag
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Sammendrag
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Sammendrag
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Sammendrag
The aim of this study was to determine whether forest clear-cuts during 2000–2011 could be detected as a decrease in surface height by combining Digital Surface Models (DSMs) from the Shuttle Radar Topography Mission (SRTM) and Tandem-X, and to evaluate the performance of this method using SRTM X- and C-band data as references representing the heights before logging. The study area was located in a Norway spruce-dominated forest estate in southeastern Norway. We interpolated 11-year DSM changes into a 10 m × 10 m raster, and averaged these changes per forest stand. Based on threshold values for DSM decreases we classified the pixels and stands into the categories “clear-cut” and “not clear-cut”, and compared this to a complete record of logged stands during 2000–2011. The classification accuracy was moderate or fairly good. A correct detection was achieved for 59%–67% of the clear-cut stands. Omission errors were most common, occurring in 33%–42% of the stands. Commission errors were found in 13%–21% of the clear-cut stands. The results obtained for X-band SRTM were only marginally better than for C-band. In conclusion, the combination of SRTM and Tandem-X has the potential of providing near global data sets for the recent 12 years’ logging, which should be particularly valuable for deforestation mapping.
Sammendrag
Samlet sett for Norge vil klimaendringene i hovedsak virke positivt på gran ved å øke utbredelsen og produksjonsevnen. Men risikoen for klimarelaterte skader ventes å øke, særlig i lavlandet på Østlandet
Forfattere
Jan BjerketvedtSammendrag
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Sammendrag
The ground-based harvesting system consisting of a harvester and a forwarder is the dominant harvesting system in parts of the world, due to its high productivity. Both machines usually operate along extraction trails, and are equipped with cranes that can reach some distance from the extraction trail. In this work we optimize the layout of an extraction trail network by considering how terrain topography influences the cost of forwarding. Given the complexity of finding optimal machine trails for terrain transportation, traditional optimization methods might be limited due to the problem size. In this study, the optimization is done with a greedy constructive heuristic and a Greedy Randomized Adaptive Search Procedure (GRASP) metaheuristic, and the results of the two solution techniques are compared. Both the greedy heuristic and the GRASP metaheuristic were examined for a semi-random terrain and a smooth cone-shaped terrain, and provided useable extraction trail layouts in terms of how a forest machine operates on slopes. The objective value of the solution found by the GRASP metaheuristic was 5.6% better than the greedy heuristic in the semi-random terrain, and 2.3% better in the cone-shaped terrain. The result of this study showed that the GRASP metaheuristic is useful for finding feasible routes in the terrain, increasing efficiency. The method could be useful for planning feasible routes in the terrain, thereby increasing efficiency, or for acquiring a better estimate of the cost of terrain transport in price setting.