1. Forest data acquisition in Nordic countries - roadmap for the future
Annika Kangas, Rasmus Astrup, Johannes Breidenbach, Jonas Fridman, Terje Gobakken, Kari T. Korhonen, Matti Maltamo, Mats Nilsson, Thomas Nord-Larsen, Erik Næsset & Håkan Olsson

2. Forest resources assessments are needed to ensure sustainability
The sustainability of utilizing forest resources was discussed already at 18th and 19th centuries
Visual assessments of forest resources were carried out to address fears concerning sustainability
The debate resulted in starting national sampling-based forest inventory
Norway 1919, Finland 1921, Sweden 1923
In Denmark the forest resources assessments were carried out with questionnaires until 2002

3. Current NFI designs Method used Number of strata Cycle
Method used
Number of strata
Cycle
N of plots per year
Use of dGNSS
Proportion of permanent clusters
Denmark
Cluster sampling -
5 years
8600
33%
Finland
Stratified cluster sampling 6
Panel system of 5 years
15000
Since %
60%
Norway
Stratified systematic sampling 4
4400
Currently 50%
100%
Sweden 5
10000
From 2017 onwards
65%

4. Use of remote sensing in NFI is limited
Currently remote sensing information is not used either in design nor estimation of the official regional results
Exception small-area results (e.g. municipality level results in Finland)
Instead, remote sensing is utilized in forest resources map production
Satellite images
Airborne laser scanning (ALS) Denmark, Sweden
Digital aerial photogrammetry (DAP) Norway
Maps publicly available for service providers

5. Remote sensing material used Publishing times Coverage Resolution
Name of the product
Remote sensing material used
Publishing times
Coverage
Resolution
Field data
Availability for public
Denmark
Land use/land cover map
Landsat
1990, 2000, 2011
100%
30m × 30 m
None No
Forest resource map
ALS
25m × 25 m
NFI plots
No (Yes for research purposes)
Yes
Finland
MS-NFI map
Landsat (Spot, Sentinel)
2015, 2013, 2011
16 m × 16 m
Yes (older maps exist but not published)
FMI forest resources map
Parts of country yearly
Full coverage 2020
Special set of plots
No (legislation to open it under work)
Norway
SR16 Forest resources map
DAP / ALS
2017
Trøndelag region available
SATSKOG
2007
Sweden
SLU forest map
2000, 2005, 2010
100 %
Skogliga grunddata
2016
100% (Except alpine areas)
12.5m × 12.5m
National Corine
10m × 10 m-25m × 25 m

6. Remote sensing will be used more in future
Local pivotal method (LPM) uses auxiliary information for obtaining a balanced sample
design taken into use in Sweden
tested in Finland
New estimation methods are being tested and introduced to operational NFI
model-assisted estimation
post-stratification
small area estimation

7. Forest management inventory FMI
Method used
Who pays
Subsidies available
Coordination
Denmark
Visual assessment of aerial photos in combination with field measurements
Forest owner no
Finland
Area-based laser scanning  (Government)
Visual assessment in the field (Planning organization)
Government (computationally recommended treatments)
Forest owner (plan)
yes (data collection)
no (plan)
Norway
Visual assessment of aerial photos
Area-based laser scanning
yes
(currently about 57%)
(by the region forester)
Sweden

8. Users of the FMI data
FMI data traditionally collected for the decision making of forest owner
Harvest scheduling
Silvicultural decisions
Forest industry and forest service providers have increasing needs for the FMI data
Timber trade
Wood procurement
Planning for end-use of timber for different products
Forest administration as well
Monitoring cuttings, regeneration, natural hazards
Inspections of forest operations

9. Each decision problem has unique requirements for the contents and accuracy of the data
Monitoring cuttings
Timeliness critical → automatic detection from satellite images needed
Timber trade
Species-level timber assortments estimates and quality assessments critical → field information so far most accurate
Planning end-use of timber and optimal bucking
Accurate diameter distribution estimates critical → field information so far most accurate
No single data acquisition method can fulfill all requirements

10. Synergies between NFI and FMI possible
NFI and FMI are designed for different purposes
NFI for national / regional statistics and decision making
FMI for local (stand-level / estate level) decision making
In the future the scopes are getting closer due to utilization of remote sensing
Remote sensing and NFI data can be combined to produce accurate information also at stand level
Remote sensing used for collecting FMI data for larger regions and with shorter intervals

11. Synergies require research on optimal approach
Are locally selected plots needed for FMI in addition to NFI plots?
Does the accuracy of ALS and DAP campaigns reduce due to sensor / weather condition / forest characteristics variation when data is collected from larger areas?
What is the accuracy required for the produced data to be useful for the original and new purposes?
CARISMA network is working on answering these questions