a cumulative distribution approach to stand structure classification
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A Cumulative Distribution Approach to Stand Structure Classification. Craig Farnden and Ian S. Moss Western Mensurationists’ Meeting July 2, 2003. Why Classify?. It helps us to organize our observations of complex systems and to learn from those observations - PowerPoint PPT PresentationTRANSCRIPT
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STAND STRUCTURE CLASSIFICATION
A Cumulative Distribution Approach to Stand Structure
ClassificationCraig Farnden and Ian S. MossWestern Mensurationists’ Meeting
July 2, 2003
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STAND STRUCTURE CLASSIFICATION
Why Classify?
It helps us to organize our observations of complex systems and to learn from those observations
It facilitates communication between individuals: a given class label infers a set of attributes that are commonly understood
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STAND STRUCTURE CLASSIFICATION
Implicit Assumptions
Recognized that:
• Stand structure is a continuum
• There are few if any obvious breaks upon which to base classes
• Perceptions of what stands should look like can seriously skew a classification (“textbook” stand structures)
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STAND STRUCTURE CLASSIFICATION
Design Criteria
• Units must be internally consistent• Units must be readily recognizable• Sufficient number of units to
facilitate interpretations• Classification must be definitive
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STAND STRUCTURE CLASSIFICATION
Design Criteria• Classification attributes should be
easy to measure or assess for general applicability
• System should be open to improvement or refinement through sub-division and/or re-fitting
• Separable with respect to diameter distributions and species composition
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STAND STRUCTURE CLASSIFICATION
The Cumulative Distribution Approach to Classification
• Current classification built on 424 sample plots
• Uses mathematical algorithm to find stands with similar structures
• Pattern recognition based on two cumulative frequency distributions:– Basal area (m2/ha)– Trees/ha
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STAND STRUCTURE CLASSIFICATION
The Cumulative Distribution Approach to Classification
0
5
10
15
20
25
30
35
40
0 10 20 30 40 50 60 70 80
Tree DBH (cm)
Bas
al A
rea
(m2 /
ha)
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STAND STRUCTURE CLASSIFICATION
The Cumulative Distribution Approach to Classification
0
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3500
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0 5 10 15 20 25 30
Tree DBH (cm)
Tre
es/h
a
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STAND STRUCTURE CLASSIFICATION
0
25
50
75
100
0 5 10 15 20 25 30
Tree DBH (cm)
Tre
es/h
a P
erce
nti
le
Methodology…
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STAND STRUCTURE CLASSIFICATION
0
25
50
75
100
0 5 10 15 20 25 30
Tree DBH (cm)
Tre
es/h
a P
erce
nti
le
Methodology…
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STAND STRUCTURE CLASSIFICATION
Methodology…T= ∑distance between all pairsWGij = ∑within group pairsBGij = T - WGij
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STAND STRUCTURE CLASSIFICATION
Methodology…For each possible move, calculate:
New WGij
∆BGi
Rij = Wgij/ ∆Bgi
Find Rminij
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STAND STRUCTURE CLASSIFICATION
Results
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STAND STRUCTURE CLASSIFICATION
Results
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STAND STRUCTURE CLASSIFICATION
Results - Reference Distributions
C1
C2
C3
C4
C5
C6
C7
C8
C9
C10
C11
C12
C13
C14
C15
C16
C17
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0 5 10 15 20 25
Tree DBH (cm)
Tre
es/h
a
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STAND STRUCTURE CLASSIFICATION
Results - Reference Distributions
0
10
20
30
40
50
60
0 10 20 30 40 50 60 70 80 90 100
Tree DBH (cm)
C1
C2
C3
C4
C5
C6
C7
C8
C9
C10
C11
C12
C13
C14
C15
C16
C17
Basal A
rea (
m2/h
a)
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STAND STRUCTURE CLASSIFICATION
Classifying Stands
• Plot cumulative distributions and compare to reference distributions
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STAND STRUCTURE CLASSIFICATION
Classifying Stands
0
10
20
30
40
50
60
0 10 20 30 40 50 60 70 80 90 100
Tree DBH (cm)
12
13
14
15
16
17
Basal A
rea (
m2
/ha)
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STAND STRUCTURE CLASSIFICATION
Classifying Stands
• Use computer software (planned)
• Use keys in field guide
• Plot cumulative distributions and compare to reference distributions
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STAND STRUCTURE CLASSIFICATION
Classifying Stands
17
16
15
15
15
12
13
15
14
14
B40>19.5AND B20>27.5
B25>37OR B80>8
B60>5AND B10<35
B10<32.5
B0>30OR B15>26
B10>19OR B20>16
B35>12
B0>34
B40 >18
YY
Y
Y
Y
Y
Y
Y
Y
N
N
N
N
N
N
N
N
N
KEY "A"
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STAND STRUCTURE CLASSIFICATION
Classifying Stands
0
10
20
30
40
50
60
70
0 10 20 30 40 50 60 70 80 90
Tree DBH (cm)
Basal A
rea (
m2
/ha)
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STAND STRUCTURE CLASSIFICATION
Classifying Stands
• Use Air Photo Interpretation
• Plot cumulative distributions and compare to reference distributions
• Use computer software (planned)
• Use keys in field guide
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STAND STRUCTURE CLASSIFICATION
Classifying Stands
Class 14 Class 15 Class 17
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STAND STRUCTURE CLASSIFICATION
• Plot cumulative distributions and compare to reference distributions
• Use computer software (planned)
• Use keys in field guide
• Use Air Photo Interpretation
Classifying Stands
• Recognize through familiarity
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STAND STRUCTURE CLASSIFICATION
Classifying Stands
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STAND STRUCTURE CLASSIFICATION
Classifying Stands
4
6
2 12
16
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STAND STRUCTURE CLASSIFICATION
Classifying Stands14 16
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STAND STRUCTURE CLASSIFICATION
Unresolved Issues
• Number and distribution of classes
• Use of discrete point samples versus composite samples
• Class hierarchy– Species– Spatial distribution and complex– Small tree frequency
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STAND STRUCTURE CLASSIFICATION
Conclusions
• System has great potential– Enhanced resource interpretations– Enhanced treelist imputation– Enhanced broad scale prescriptive abilities
• Appears to be robust and defensible• Should be exportable with minimal
modifications• New and untested - guinea pigs required
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STAND STRUCTURE CLASSIFICATION
Documentation
Field guide and poster
Lignum Limited web site:
www.lignum.com
go to publications
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STAND STRUCTURE CLASSIFICATION
Acknowledgements
• This project was undertaken as part of the Lignum Ltd. IFPA
• Funding for this project was provided by Forestry Innovation Investment (FII), a forestry investment mechanism of the Gov’t of BC, and Forest Renewal BC