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.
2020
Sammendrag
Det er ikke registrert sammendrag
Forfattere
Stefano Puliti Marius Hauglin Johannes Breidenbach Paul M. Montesano C.S.R. Neigh Johannes Rahlf Svein Solberg Torgeir Ferdinand Klingenberg Rasmus AstrupSammendrag
Det er ikke registrert sammendrag
Forfattere
Stefano Puliti Marius Hauglin Johannes Breidenbach P. Montesano C.S.R. Neigh Johannes Rahlf Svein Solberg T. F. Klingenberg Rasmus AstrupSammendrag
Boreal forests constitute a large portion of the global forest area, yet they are undersampled through field surveys, and only a few remotely sensed data sources provide structural information wall-to-wall throughout the boreal domain. ArcticDEM is a collection of high-resolution (2 m) space-borne stereogrammetric digital surface models (DSM) covering the entire land area north of 60° of latitude. The free-availability of ArcticDEM data offers new possibilities for aboveground biomass mapping (AGB) across boreal forests, and thus it is necessary to evaluate the potential for these data to map AGB over alternative open-data sources (i.e., Sentinel-2). This study was performed over the entire land area of Norway north of 60° of latitude, and the Norwegian national forest inventory (NFI) was used as a source of field data composed of accurately geolocated field plots (n=7710) systematically distributed across the study area. Separate random forest models were fitted using NFI data, and corresponding remotely sensed data consisting of either: i) a canopy height model (ArcticCHM) obtained by subtracting a high-quality digital terrain model (DTM) from the ArcticDEM DSM height values, ii) Sentinel-2 (S2), or iii) a combination of the two (ArcticCHM+S2). Furthermore, we assessed the effect of the forest- and terrain-specific factors on the models’ predictive accuracy. The best model (,i.e., ArcticCHM+S2) explained nearly 60% of the variance of the training set, which translated in the largest accuracy in terms of root mean square error (RMSE=41.4 t ha−1 ). This result highlights the synergy between 3D and multispectral data in AGB modelling. Furthermore, this study showed that despite the importance of ArcticCHM variables, the S2 model performed slightly better than ArcticCHM model. This finding highlights some of the limitations of ArcticDEM, which, despite the unprecedented spatial resolution, is highly heterogeneous due to the blending of multiple acquisitions across different years and seasons. We found that both forest- and terrain-specific characteristics affected the uncertainty of the ArcticCHM+S2 model and concluded that the combined use of ArcticCHM and Sentinel-2 represents a viable solution for AGB mapping across boreal forests. The synergy between the two data sources allowed for a reduction of the saturation effects typical of multispectral data while ensuring the spatial consistency in the output predictions due to the removal of artifacts and data voids present in ArcticCHM data. While the main contribution of this study is to provide the first evidence of the best-case-scenario (i.e., availability of accurate terrain models) that ArcticDEM data can provide for large-scale AGB modelling, it remains critically important for other studies to investigate how ArcticDEM may be used in areas where no DTMs are available as is the case for large portions of the boreal zone.
Sammendrag
Innføring av obligatorisk individmerking av tamrein i Norge ble vedtatt av Stortinget 13. juni 2019. NIBIO har i denne rapporten belyst hvilke merkemetoder for individmerking som finnes på markedet i dag og hvordan disse egner seg for bruk i reindrifta. Kunnskap om disse og individmerking generelt i næringa, forvaltningen og reindriftsmyndighetene er innhentet gjennom utstrakt kontakt med en rekke informanter. Mulighetene og utfordringene som ligger i individmerking for næring, forvaltning og myndigheter er undersøkt og kartlagt. NIBIO har belyst en del punkter som anbefales for veien videre vedrørende innføring av individmerking i reindriften. NIBIO har også foreslått pilotprosjekter som kan/bør gjennomføres for å forberede reindriften på innføring av individmerking, samt forbedrer dagens løsninger for elektronisk individmerking slik at disse blir driftssikre, kostnadslave, møter næringens behov og nytte og samtidig gir myndigheter og forvaltning ny kunnskap om Norges tamrein...
Forfattere
Stefano Puliti Johannes Breidenbach Johannes Schumacher Marius Hauglin Torgeir Ferdinand KlingenbergSammendrag
Det er ikke registrert sammendrag
Sammendrag
Det er ikke registrert sammendrag
Sammendrag
Background The age of forest stands is critical information for forest management and conservation, for example for growth modelling, timing of management activities and harvesting, or decisions about protection areas. However, area-wide information about forest stand age often does not exist. In this study, we developed regression models for large-scale area-wide prediction of age in Norwegian forests. For model development we used more than 4800 plots of the Norwegian National Forest Inventory (NFI) distributed over Norway between latitudes 58° and 65° N in an 18.2 Mha study area. Predictor variables were based on airborne laser scanning (ALS), Sentinel-2, and existing public map data. We performed model validation on an independent data set consisting of 63 spruce stands with known age. Results The best modelling strategy was to fit independent linear regression models to each observed site index (SI) level and using a SI prediction map in the application of the models. The most important predictor variable was an upper percentile of the ALS heights, and root mean squared errors (RMSEs) ranged between 3 and 31 years (6% to 26%) for SI-specific models, and 21 years (25%) on average. Mean deviance (MD) ranged between − 1 and 3 years. The models improved with increasing SI and the RMSEs were largest for low SI stands older than 100 years. Using a mapped SI, which is required for practical applications, RMSE and MD on plot level ranged from 19 to 56 years (29% to 53%), and 5 to 37 years (5% to 31%), respectively. For the validation stands, the RMSE and MD were 12 (22%) and 2 years (3%), respectively. Conclusions Tree height estimated from airborne laser scanning and predicted site index were the most important variables in the models describing age. Overall, we obtained good results, especially for stands with high SI. The models could be considered for practical applications, although we see considerable potential for improvements if better SI maps were available.
Forfattere
Gry Alfredsen Erik Larnøy Greeley Beck Johan Bjørnstad Lone Ross Callum Aidan Stephen Hill Andreas TreuSammendrag
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Sammendrag
I rapporten undersøkes og diskuteres hvilke skogtyper innen det Europeiske Natura 2000 systemet som Norge synes å ha et særlig ansvar for. Data fra Landsskogtakseringen sammenlignes med data fra EU på areal av de ulike skogtypene. Det konkluderes med at Norge har et svært høyt ansvar for oseaniske skogtyper, et høyt ansvar for Nordiske skogtyper, og et middels til lavt ansvar for sydlige skogtyper.
Sammendrag
Det er ikke registrert sammendrag