This document provides summary stats (area) for the forest
conservation value projections. We show the statistics for all four
models tested in our analysis.
Content:
- Forest area in Denmark according to Bjerreskov et al. 2021.
- Training data area: High conservation value and low conservation
value forests.
- Disturbance detected in forests overall.
- Gradient Boosting model summary stats (BIOWIDE).
- Random Forest model summary stats (BIOWIDE).
- Gradient Boosting model summary stats (Derek’s stratification).
- Random Forest model summarz stats (Derek’s stratification).
Forests area in Denmark according to Bjerreskov et al. 2021
Below you can find the total area of forest in the forest mask from
Bjerreskov et al. 2021. This is the reference for the total area of
forest used in our project. The mask is based on the tree type layer
from the same publication (see predictor description). We generated the
forest mask by refining the treetype layer into a forest mask by
applying a minimum mapping filter removing all continuous forest patches
smaller than 500 m2 (see also Bjerreskov et al. 2021).
Layer
|
Area [km²]
|
forest mask
|
6345.3
|
Training data area: High conservation value and low conservation
value forests
Here you can see the area covered by our training data. Including
both the high conservation value forests with designations (p15, p25 and
private old growth), as well as the low conservation value training
polygons. The proportions are given relative to the total area of forest
according to the forest mask generated from Bjerreskov et al. 2021 (see
above).
category
|
Area [km²]
|
Proportion of all forest [%]
|
p25
|
111.71
|
2e-06
|
private_old_growth
|
31.98
|
1e-06
|
p15
|
17.79
|
0e+00
|
total_high_quality
|
161.13
|
3e-06
|
ikke_p25
|
46.70
|
1e-06
|
NST_plantations
|
59.33
|
1e-06
|
total_low_quality
|
106.03
|
2e-06
|
Disturbance overall
We used a disturbance layer generated by Cornelius (Senf and Seidl 2021) to
estimate the disturbance in Denmark’s forests since the lidar data for
EcoDes-DK15 was collected.
Please note that this disturbance mask was projected and down-sampled
from a 30 m Landsat grid to the 10 m EcoDes-DK15 grid (nearest neighbour
algorithm), potentially adding small uncertainties to the area
estimates. Currently, we also only account for disturbances from 2016
till 2020.
Name
|
Area [km²]
|
Proportion [%]
|
disturbed forest
|
84.49
|
1.30
|
total forest
|
6345.30
|
100.00
|
Gradient Boosting projections summary stats (BIOWIDE)
This gradient boosting model was trained based on the “BIOWIDE”
stratification.
Type
|
Area [km²]
|
Proportion [%]
|
high conservation value forest
|
1979.92
|
31.20
|
low conservation value forest
|
4307.60
|
67.90
|
total forest
|
6345.30
|
100.00
|
Disturbance statistics:
Type
|
Area [km²]
|
Proportion [%]
|
disturbed high conservation value forest
|
18.20
|
0.90
|
total high conservation value forest
|
1979.92
|
100.00
|
Type
|
Area [km²]
|
Proportion [%]
|
disturbed low conservation value forest
|
66.29
|
1.50
|
total low conservation value forest
|
4307.60
|
100.00
|
Type
|
Area [km²]
|
Proportion [%]
|
disturbed high conservation value forest
|
18.20
|
21.50
|
disturbed low conservation value forest
|
66.29
|
78.50
|
total disturbed forest
|
84.49
|
100.00
|
Random Forest projections summary stats (BIOWIDE)
This random forest model was trained based on the “BIOWIDE”
stratification.
Type
|
Area [km²]
|
Proportion [%]
|
high conservation value forest
|
1999.61
|
31.50
|
low conservation value forest
|
4287.91
|
67.60
|
total forest
|
6345.30
|
100.00
|
Disturbance statistics:
Type
|
Area [km²]
|
Proportion [%]
|
disturbed high conservation value forest
|
17.81
|
0.90
|
total high conservation value forest
|
1999.61
|
100.00
|
Type
|
Area [km²]
|
Proportion [%]
|
disturbed low conservation value forest
|
66.69
|
1.60
|
total low conservation value forest
|
4287.91
|
100.00
|
Type
|
Area [km²]
|
Proportion [%]
|
disturbed high conservation value forest
|
17.81
|
21.10
|
disturbed low conservation value forest
|
66.69
|
78.90
|
total disturbed forest
|
84.49
|
100.00
|
Gradient Boosting projections summary stats (Derek’s
stratification)
This gradient boosting model was trained based on the “Derek’s”
stratification.
Type
|
Area [km²]
|
Proportion [%]
|
high conservation value forest
|
1986.18
|
31.30
|
low conservation value forest
|
4301.33
|
67.80
|
total forest
|
6345.30
|
100.00
|
Disturbance statistics:
Type
|
Area [km²]
|
Proportion [%]
|
disturbed high conservation value forest
|
18.19
|
0.90
|
total high conservation value forest
|
1986.18
|
100.00
|
Type
|
Area [km²]
|
Proportion [%]
|
disturbed low conservation value forest
|
66.30
|
1.50
|
total low conservation value forest
|
4301.33
|
100.00
|
Type
|
Area [km²]
|
Proportion [%]
|
disturbed high conservation value forest
|
18.19
|
21.50
|
disturbed low conservation value forest
|
66.30
|
78.50
|
total disturbed forest
|
84.49
|
100.00
|
Random Forest projections summary stats (Derek’s
stratification)
This random forest model was trained based on the “Derek’s”
stratification.
Type
|
Area [km²]
|
Proportion [%]
|
high conservation value forest
|
2007.38
|
31.60
|
low conservation value forest
|
4280.13
|
67.50
|
total forest
|
6345.30
|
100.00
|
Disturbance statistics:
Type
|
Area [km²]
|
Proportion [%]
|
disturbed high conservation value forest
|
17.97
|
0.90
|
total high conservation value forest
|
2007.38
|
100.00
|
Type
|
Area [km²]
|
Proportion [%]
|
disturbed low conservation value forest
|
66.52
|
1.60
|
total low conservation value forest
|
4280.13
|
100.00
|
Type
|
Area [km²]
|
Proportion [%]
|
disturbed high conservation value forest
|
17.97
|
21.30
|
disturbed low conservation value forest
|
66.52
|
78.70
|
total disturbed forest
|
84.49
|
100.00
|