http://creativecommons.org/licenses/by/4.0/

Natural Resources Institute Finland (Luke) owns the copyright, data protection, and other immaterial rights to this product. The Topographic Database from the National Land Survey has been utilized when making the product. This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA. When using the material, the owner of the rights to the material must be given as "©Natural Resources Institute Finland, 2011" and the name of the material must be given as "The Multi-source National Forest Inventory Raster Maps of 2016". For research use, the description of the method is in the references in the metadata element Lineage. A scientific citation practice shall be used in research use.

The first country level estimates correspond to years 1990-1994. The most

recent versions are from years 2005, 2007, 2009, 2011, 2013, 2015 and 2017.

The three themes presented here were made for production of

CORINE2006.

The map products are in a raster format in the ETRS-TM35FIN coordinate system

with a pixel size of 20m x 20m. These are reprojections from original themes

in the Finnish YKJ coordinate system witf pixel size 25m x 25m. The products

cover the combined land categories forest land, poorly productive forest land

and unproductive land. The other land categories as well as water bodies have

been delineated out using the elements of topographic database of the Land

Survey of Finland.

Field data from about 45 000 NFI sample plots from years 2004-2007 (NFI10)

(2003, NFI9 in northernmost Finland) were used. The satellite images used

included 57 IRS images and 41 Spot images fomr years 2005-2007.

Regeneration cuttings on the field plots were assessed using satellite images

and, in some cases, with aerial photographs. The plots were removed where the

cuts status in field data clearly did not match the image.

The map form estimates were made using the improved k-Nearest Neighbour method

(ik-NN method). The value of five for k was used most frequently. The weights

of the features in the ik-NN method are sought using an optimization method

based on genetic algorithm. Coarse scale estimates of forest variables were

used as the supplementary data. The volumes by tree species groups were

selected as the variables. The purpose is to direct the selection of the

neighbours, on the average, to forests similar to the target pixel (see the

references below). The estimation was made separately for mineral soils, mires

and open bogs and fens. The stratification of both the satellite image and the

field plots were made using the topographic map data of Land Survey Finland.

The mean height of the trees on a forest stand is the height of the basal

area median tree for the development classes young thinning stand or more

mature stands. It is about the same as the basal area weighted average

height. For seedling stands, the mean height is the average height of the

dominant and co-dominant seedlings. The mean height is assessed in the field

in the classes of 1 dm.

The canopy cover of trees is the vertical projection area on the horizontal

plane of the canopies of the individual trees on a field plot (without double

counting the overlapping canopies). In NFI10, it was assessed in the field as

a shares (0-99%) on a fixed radius plot. In North Lapland in NFI9, the

canopy cover was assessed in three categories if the plot was either on forest

land, poorly productive forest land or unproductive land. A regression model

was constructed to estimate the cover in the classes of one percent.

The canopy cover proportion of broad-leaved trees is derived from the total

cover using the basal area. However, in the seedling stands, the canopy cover

of broad-leaved trees is assessed using the shares of the stem numbers.

More information about the methods and the accuracies are given in the

publications, e.g.:

Törmä, M., Haakana, M., Hatunen, S., Härmä, P., Kallio, M., Katila, M.,

Kiiski, T., Mäkisara, K., Peräsaari, J., Piepponen, H., Repo, R., Teiniranta,

R. & Tomppo, E., 2008. Finnish Corine 2006-project: Determining Changes in

Land Cover in Finland between 2000 and 2006. Remote Sensing for Environment

Monitoring, GIS Applications and Geology VIII, Proceedings of SPIE vol. 7110.

Tomppo, E., Haakana, M., Katila, M. & Peräsaari, J. 2008. Multi-source

national forest inventory - Methods and applications. Managing Forest

Ecosystems 18. Springer. 374 p. ISBN 978-1-4020-8712-7

Tomppo, E. & Halme, M. 2004. Using coarse scale forest variables as

ancillary information and weighting of variables in k-NN estimation: a genetic

algorithm approach. Remote Sensing of Environment 92: 1-20.

Tietoaineistosarja

ISO19115

2003/Cor.1:2006