Highlights• Image based forest attribute map generated using NFI plots show similar accuracy as currently used LiDAR based forest attribute map.• Also similar accuracies were found for different forest types.• Aerial images from leaf-off season is not recommended.
AbstractExploring the possibility to produce nation-wide forest attribute maps using stereophotogrammetry of aerial images, the national terrain model and data from the National Forest Inventory (NFI). The study areas are four image acquisition blocks in mid-and south Sweden. Regression models were developed and applied to 12.5 m × 12.5 m raster cells for each block and validation was done with an independent dataset of forest stands. Model performance was compared for eight different forest types separately and the accuracies between forest types clearly differs for both image-and LiDAR methods, but between methods the difference in accuracy is small at plot level. At stand level, the root mean square error in percent of the mean (RMSE%) were ranging: from 7.7% to 10.5% for mean height; from 12.0% to 17.8% for mean diameter; from 21.8% to 22.8% for stem volume; and from 17.7% to 21.1% for basal area. This study clearly shows that aerial images from the national image program together with field sample plots from the NFI can be used for large area forest attribute mapping.
Tree retention practices promoting biodiversity may reshape future boreal forest production landscapes. Using the Heureka system, scenarios of 0%, 5%, and 20% retained patches at the stand level were projected over 200 years in a 533 ha boreal landscape. Visualizations of future forest states at a landscape scale and a more detailed scale were made based on the projections. The no retention results in no forest >120 years old, and no large trees (diameter at breast height >40 cm for conifers and >35 cm for broadleaved trees) 100 years from now. With retention levels of 5% and 20%, the area of old forest will comprise 7% and 19% of the total area, respectively. The average number of large trees per ha will be 4 and 13, respectively. Deadwood volumes will be 2.5 times higher at 5% retention and 4 times higher at 20% retention compared to no retention. Landscape visualizations indicate that retention patches covering 5% will marginally modify the visual impression, compared to clear-cuts, while 20% cover will create a much more varied landscape. We conclude that the retention approach is essential for restoring natural conditions. Landscape transformation will be slow and depend on starting conditions and retention levels.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.