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National Forest Inventories : pathways for common reporting
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The article was published on 2010-01-01. It has received 596 citations till now.read more
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Journal ArticleDOI
Construction of tree species composition map of Estonia using multispectral satellite images, soil map and a random forest algorithm
Abstract: Abstract Landsat-8 OLI and Sentinel-2 MSI images from years 2015 and 2016, a 1:10,000 digital soil map and a large number of reference samples were used with a random forest machine learning implementation in GRASS GIS to construct a tree species map for the entire territory of Estonia (42,755 km2). Class probabilities for seven main tree species, an extra class for other species and probability of the forest cover not conforming to the forest definition were assigned for each pixel. Validation of dominant species distribution by area showed very strong correlation at county level both in state forests (R2 = 0.98) and in private forests (R2 = 0.93). Validation of tree species composition using harvester measurement data from 2,045 regeneration felling areas showed also very strong correlation (R2 = 0.75) with the measured values of the proportion of coniferous trees. There was some tendency to underestimate the proportion of more common species and overestimation was found for the species with smaller proportion in the mixture. The accuracy for the proportion of deciduous species that were present in a smaller number of reference observations was substantially smaller. Validation of the results by using data from 659 large sample plots from the database of the Estonian Network of Forest Research Plots and 3,002 small sample plots from the National Forest Inventory (NFI) data base confirmed the findings based on harvester data. The NFI data revealed also a decrease of estimation error with the increase of forest age. Cohen’s kappa index of agreement for main species for NFI sample plots with main species proportion equal to or greater than 75% decreased from 0.69 to 0.66 when observations with forests younger than 20 years were included in the comparison. Overall, the constructed map provides valuable data about tree species composition for the forests where no up to date inventory data are available or for the projects that require continuous cover of tree species data of known quality over the entire Estonia.
Journal ArticleDOI
Comparison of calculation methods for estimating annual carbon stock change in German forests under forest management in the German greenhouse gas inventory.
Steffi Röhling,Karsten Dunger,Gerald Kändler,Susann Klatt,Thomas Riedel,Wolfgang Stümer,Johannes Brötz +6 more
TL;DR: The possibility of introducing an annual rather than periodical approach to calculating emission factors with the given data and thus smoothing the trajectory of time series for emissions from forest biomass is explored.
Journal ArticleDOI
A probability model for root and butt rot in Picea abies derived from Norwegian National Forest Inventory data.
Gro Hylen,Aksel Granhus +1 more
TL;DR: A probability model for decay at breast height utilizing 18,141 increment cores sampled on temporary plots of the Norwegian National Forest Inventory showed a good fit to the data and retained significant relationships between decay and a suite of tree, stand and site variables, including diameter at Breast height, stand age, altitude, growing season temperature sum, and vegetation type.
Journal ArticleDOI
Recent growth trends of conifers across Western Europe are controlled by thermal and water constraints and favored by forest heterogeneity.
TL;DR: Over a short annually-resolved study period, a continuous French NFI arises as powerful support to monitoring climate change effects on forests to capture tree growth responses coherent with climate change across diverse forest ecosystems.
Journal ArticleDOI
The Inventory of Carbon Stocks in New Zealand's Post-1989 Natural Forest for Reporting under the Kyoto Protocol
Peter N. Beets,Mark O. Kimberley,Thomas S. H. Paul,Graeme R. Oliver,Stephen H. Pearce,Joanna M. Buswell +5 more
TL;DR: New Zealand undertook a national inventory of this natural stratum of post-1989 forest to provide estimates of carbon stocks and stock change in woody species over the first commitment period of the Kyoto Protocol, and developed a yield table for predicting carbon (t/ha) as a function of vegetation mean age.
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