1. Deriving nationwide estimates of forest variables for Sweden using Landsat ETM+ and field data
Mats Nilsson
Department of Forest Resource Management and Geomatics,
Swedish University of Agricultural Sciences, Umeå, Sweden

2. Objectives
Create a nationwide raster database with estimated forest variables
Covers forested areas according to existing map data (1: )

3. ”kNN-Sweden”
Produces estimates of
- Total stem volume
Stem volume by species
Tree height
Stand age
New cycle with SPOT data

4. Other wooded land: 3 mil. ha Other land: 10 mil. ha
Statistics from the Swedish
National Forest Inventory (NFI)
Total land area: 41 mil. ha
Forest: 28 mil. ha
Other wooded land: 3 mil. ha
Other land: 10 mil. ha
Prop. Scots pine: 40 %
Prop. Norway spruce 42 %
Prop. Deciduous trees 18 %

5. The k Nearest Neighbour method
total stem volume stem volume per tree species
age
tree height
kNN
Satellite
images
Map data
Field data
From the NFI

6. Landsat ETM+
Ortho-rectified
Haze correction
Illumination correction

7. NFI data Plots from a 5 year period Forecasting data
>1000 plots/scene
Matching field plots and image data

8. Digital Map Data
5 km
Scale 1:

9. Dalarna

10. Users Swedish National Forest Inventory
Swedish University of Agricultural Sciences
Forest agency
Environmental Protection Agency
County Administration Boards
Swedish National Tax Board
Researchers