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Revitalisierung
TetraoVit-project
von Mooren und Habitatmanagment für das Birkhuhn
im Osterzgebirge („TetraoVit“)
| 04.09.2019 | H. Metzler, M. Homann, Referat 53 Naturschutz im Wald

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| 04.09.2019 | H. Metzler, M. Homann, Referat 53 Naturschutz im Wald
milestone 1. develop a habitat-key system
open
r 50 bis 80 m
low single trees/
gappy treegroups arround
display area
breeding-/
raising- habitat
regular
winter habitat
forest
potential
habitat
gappy treegroups
conifers to be < 6 m
thinned
decidous-dominated
mixed woodland
or bog-woodland
essential habitats of Tetrao tetrix
important physical parameters:
1. tree-species, 2. tree-height, 3. tree coverage,
(habitat-key system)
4. ground-vegetation, 5. topographical exponation
2

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| 04.09.2019 | H. Metzler, M. Homann, Referat 53 Naturschutz im Wald
Actionplan „Black grouse“
Bog revitalisation
cell (10 x 10 m) -based
Black grouse habitat evaluation
by remote sensing data
Our intention:
milestone 3. method for (semi-) automatic analysis and
prognosis of Black grouse habitat structure
3

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| 04.09.2019 | H. Metzler, M. Homann, Referat 53 Naturschutz im Wald
Tree species (at least treegroups)
Tree height
Tree coverage
Ground vegetation
Landforms
-> Picea abies, Picea pungens, Pinus silvestris, Pinus mugo,
Larix, soft decidous (= Betula, Sorbus, Salix), Fagus, other decidous trees
-> 0,5m classes
-> 10 % steps
->
mostly... pure soil, Vaccinium/Calluna, moss, high grass
(Molinia, Calamagrostis), low grass (Carex, Deschampsia)
goals: providing 5 remote sensing parameters for each cell
4
->

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| 04.09.2019 | H. Metzler, M. Homann, Referat 53 Naturschutz im Wald
remote sensing data used for detecting
tree-species and type of ground vegetation:
5
aerial- / satellite data
resolution [m]
bands
shooting date(s)
DOP Sachsen
0,2
4 RGBI
24.06.2016
DOP Tschechien
0,2
4 RGBI
11.06.2017
WorldView2 (WV2)
0,52
8 MS
03.07.2015
0,46
1 PAN
03.07.2015
WorldView3 (WV3)
1,24
8 MS
13.08.2018
0,31
1 PAN
13.08.2018
Pleiades
2
4 RGBI
21.05.2018
0,5
1 PAN
21.05.2018
PlanetScope
3
4 RGBI
08.05., 07.06.,07.08.2018
Sentinel2B
[esa copernicus]
10-60
10 MS
09.04., 04.05., 03.07., 07.08., 11.10.2018
[Planet Labs Inc]
[Airbus DS Geo SA]
[Digital Globe]
[Digital Globe]
[cuzk]
+ sampling reference data by terrestrial proof

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| 04.09.2019 | H. Metzler, M. Homann, Referat 53 Naturschutz im Wald
LUP – LUFTBILD UMWELT PLANUNG GmbH
Große Weinmeisterstraße 3a
D-14469 Potsdam
Deutschland
info@lup-umwelt.de
data processing & report done by:
6

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| 04.09.2019 | H. Metzler, M. Homann, Referat 53 Naturschutz im Wald
DOP 0,2m
WorldView3 0,3m
PlanetScope 3m
Sentinel2B 10m
Resolution:
7

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| 04.09.2019 | H. Metzler, M. Homann, Referat 53 Naturschutz im Wald
class
short
form
tree-species / -group
tree-species
1
RBU
Fagus sylvatica
Fagus sylvatica
2
ELA
Larix
Larix decidua
3
FI
Picea (all without P. pungens)
Picea abies, Picea omorika, Picea sitchensis
4
PFI
Picea pungens
Picea pungens
5
KI
Pinus (all without P. mugo)
Pinus sylvestris, Pinus contorta
6
BKI
Pinus mugo
Pinus mugo
7
SWL
Soft decidous trees
Betula pendula, Betula pubescens, Sorbus aucuparia, Salix sp.
8
uLW
other decidous trees
Acer pseudoplatanus, Alnus glutinosa, Populus tremula
9
uNW
other conifers
Pseudotsuga menziesii, Abis alba, Abies normaniana
10
kA
-
Classification for detecting tree-species / -groups [BA]:
8

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| 04.09.2019 | H. Metzler, M. Homann, Referat 53 Naturschutz im Wald
class
type
1
pure soil
2
Vaccinium/Calluna (> 50 %)
3
Vaccinium/Calluna (> 20 %)
4
peat vetetation (mosses, low Carex sp.)
5
low grass (f.e. Eriophorum vaginatum, Eriophorum angustifolium, Deschampsia flexuosa, Carex sp.)
6
high grass (f.e. Molinia caerulea, Calamagrostis villosa, Calamagrostis arundinacea)
7
rocks /stones
8
other groundvetegation
99
-
Classification for detecting groundvegetation [BVT_BIRKH]:
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| 04.09.2019 | H. Metzler, M. Homann, Referat 53 Naturschutz im Wald
class
short form
Tree coverage
1
0,0
-
2
0,1
10 %
3
0,2
20 %
4
0,3
30 %
5
0,4
40 %
6
0,5
50 %
7
0,6
60 %
8
0,7
70 %
9
0,8
80 %
10
0,9
90 %
11
1,0
100 %
Classification for detecting tree coverage [KSG]
based on normalized surfacemodel (nDOM):
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| 04.09.2019 | H. Metzler, M. Homann, Referat 53 Naturschutz im Wald
short form
tree height
0,0
-
0,5
0,5 m
1,0
1,0 m
1,5
1,5 m
2,0
2,0 m
2,5
2,5 m
3,0
3,0 m
3,5
3,5 m
4,0
4,0 m
4,5
4,5 m
Classification for detecting tree height [BHOE_DFE]
based on normalized surfacemodel (nDOM):
11

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| 04.09.2019 | H. Metzler, M. Homann, Referat 53 Naturschutz im Wald
Accuracy detecting treespecies/ -groups:
Results
best results
12

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| 04.09.2019 | H. Metzler, M. Homann, Referat 53 Naturschutz im Wald
Sentinel with WV3
Sentinel with DOP
Results detecting treespecies/ -groups
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| 04.09.2019 | H. Metzler, M. Homann, Referat 53 Naturschutz im Wald
Sentinel with WV3
Sentinel with DOP
Results detecting groundvegetation
14
- ‚other‘ ground vegetation
- ‚no result‘
43 %
nonspecific classes
quite high

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| 04.09.2019 | H. Metzler, M. Homann, Referat 53 Naturschutz im Wald
Results nDOM
(used for tree-height and tree-coverage
determination)
15

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| 04.09.2019 | H. Metzler, M. Homann, Referat 53 Naturschutz im Wald
Results landforms
16
Landforms TPI 40 100
Using DEM and the Topographic Position
Index Tool, applied with Land Facet Corridor
Designer (Jeff Jenness, 2013), categories of
landforms (such as crests, plains, valleys
etc.) were determined.

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| 04.09.2019 | H. Metzler, M. Homann, Referat 53 Naturschutz im Wald
Application:
query for selected conditions: -> tree-height, tree-coverage, tree-species, groundvegetation
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| 04.09.2019 | H. Metzler, M. Homann, Referat 53 Naturschutz im Wald
Application within GIS:
query for selected conditions: -> tree-height, tree-coverage, tree-species, groundvegetation
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1 square = 10 x 10 m = 0,01 ha

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| 04.09.2019 | H. Metzler, M. Homann, Referat 53 Naturschutz im Wald
I.
The high temporal resolution of more spatially resolved data such as PlanetScope
or Sentinel 2 offers a high information value.
Classification based solely on this data, however, is sub-optimal, and the best
results can be achieved by including textures from high-resolution spatial data
such as Digital Orthophotos or WorldView satellite data.
Conclusions
:
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| 04.09.2019 | H. Metzler, M. Homann, Referat 53 Naturschutz im Wald
Conclusions
:
II.
The introduction of an operationally efficient (semi-)automated process for the
structural analysis of potential black grouse habitats seems possible after the
evaluation of all classification approaches.
As a favorite both for cost reasons and due to the classification accuracy, the variant
"Sentinel 2 plus textures from DOP" emerges. Another important data basis is the
surface model. This should be as up-to-date and accurate as possible to be able to
locate the tree-covered areas exactly. If no suitable laser scan data is available,
stereo aerial images from the orthophotographic observation can alternatively be
used to generate surface models (stereomatching).
For a large-scale application on the entire ridge of the Ore Mountains (about 5,000
km ²), the collection of good reference (training) data is very important.
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| 04.09.2019 | H. Metzler, M. Homann, Referat 53 Naturschutz im Wald
Habitat Evaluation - first steps
:
1. display area
2. breeding-/
raising habitat
3. winter habitat
4. potential
habitat
- trying to evaluate the project area regarding to four different habitat types
- evaluation steps are done separately for each habitat type
- starting with displaying area (highest requirements), then habitat types 2, 3, 4
- criteria: tree species, coverage of trees, tree height, ground vegetation, topography
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| 04.09.2019 | H. Metzler, M. Homann, Referat 53 Naturschutz im Wald
First attempt to find and evaluate (potential) display areas
Classification and class borders (topography not integrated yet):
Evaluation
Tree species
Tree coverage
Tree Height
Ground vegetation
very suitable
(3 points)
Picea pungens,
Betula, Salix, Sorbus
0 - 10 %
0 - 0,5 m
raw soil, low grass,
dwarf shrubs > 50%
suitable
(2 points)
Pinus spec., Larix,
decidous trees
20 - 30 %
1 - 1,5 m
dwarf shrubs
< 50%
less suitable
(1 point)
Picea abies, Fagus
sylv., no detection
40 - 50 %
2 - 5 m
no detection, high
grass, bog, stones
not suitable
(false)
> 50 %
> 5 m
Points for tree coverage and tree height are doubled -> maximum sum of points: 18
cells with less than 10 points or not suitable criterea are eliminated as display area
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| 04.09.2019 | H. Metzler, M. Homann, Referat 53 Naturschutz im Wald
First results:
Generally, the detection of potential display areas seems to work, results are plausible,
but several corrections are necessary, some of them cannot be automized.
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| 04.09.2019 | H. Metzler, M. Homann, Referat 53 Naturschutz im Wald
nearly a fourth (24,7%) of the evaluated cells
were detected as potential display areas
further reductions will result from manual
corrections and eliminating isolated cells
-> trying to use clustering techniques
perhaps more strict class borders and/or
minimum sums of evalution points are
necessary
habitat evaluation by remote sensing
has to be compared and perhaps calibrated
with results of terrestrial mapping (O. Volf)
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| 04.09.2019 | H. Metzler, M. Homann, Referat 53 Naturschutz im Wald
TetraoVit-project
25
| 04.09.2019 | H. Metzler, M. Homann Referat 53 Naturschutz im Wald
Revitalisierung von Mooren und Habitatmanagment für das Birkhuhn
im Osterzgebirge („TetraoVit“)