Slides for the Open Knowledge Finland Biodiversity Map Hack Weekend 28.11.2015

1. Biodiversity Map data status
Konsta Happonen
18.11.2015

2. Introduction
The Biodiversity Map project is generating forest structure raster
data sets from open LiDAR data.
Forest structure data is then combined with spatial data on
old-growth conservation areas to build a predictive model for
old-growth forests with conservation value.
Pilot phase concentrates on Central Finland and Keuruu forest
conflict.

3. The data: LiDAR intensity, 2 m resolution

4. The data: Canopy cover index, 6 m resolution

5. The data: Maximum height from ground surface, 6 m
resolution

6. The data: Old growth nature reserves
Old growth conservation
areas belonging to old
growth conservation
programmes on both
public and private lands
More specific information
not available

7. The data: Nature reserves on private lands
Shape file of all privately owned conservation areas in Central
Finland
A separate table for METSO-areas with heterogeneous data on
tree species composition, deadwood, METSO classification etc.

8. The data: Area in forestry use
A vector layer
showing the area in
forestry use.
Contains
information on land
ownership - public
or private.

9. The predictive model
Divide the area to 18 m x 18 m tiles
→ calculate mean, minimum, maximum and variance for from all
raster variables for the 18 m tiles
→ sample conservation areas and areas in forestry use
→ build logistic regression model
Model output: a predictive map of ”probability of being a
conservation area” for the 18 m x 18 m tiles.
Hudak, Andrew T.; Crookston, Nicholas L.; Evans, Jeffrey S.; Falkowski,
Michael J.; Smith, Alistair M.S.; Gessler, Paul E.; and Morgan, Penelope,
”Regression modeling and mapping of coniferous forest basal area and
tree density from discrete-return lidar and multispectral satellite data”
Can. J. Remote Sensing, Vol. 32, No.2, pp. 126-138 2006

10. To Do:
The best resolution: 18 m, 20 m, 30 m?
Other data we should in
Scanning procedure changed in 2013 - does this affect our
analysis?
Focus of the model: general ”old-growthness” or many
models for specific types of old growth forest (eg. mixed
deciduous-coniferous, METSO-class II etc.)
Choise of a representative sample from areas under forestry
use: include clearcuttings, young forests?
How to account for roads, buildings etc.
Sampling design: how many tiles from conservation areas?
How about outside?
Threshold for being a conservation area: does a tile have to
be wholly inside a nature reserve to be considered old-growth?
Just a little? at least 50%?
Model selection criteria, goodness-of-fit methods, multimodel
inference?