stand structure classification a cumulative distribution approach to stand structure classification...

STAND STRUCTURE CLASSIFICATION

A Cumulative Distribution Approach to Stand Structure

ClassificationCraig Farnden and Ian S. MossWestern Mensurationists’ Meeting

July 2, 2003


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


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)


Design Criteria

• Units must be internally consistent• Units must be readily recognizable• Sufficient number of units to

facilitate interpretations• Classification must be definitive


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


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



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)



0

500

1000

1500

2000

2500

3000

3500

4000

0 5 10 15 20 25 30

Tree DBH (cm)

Tre

es/h

a


0

25

50

75

100

0 5 10 15 20 25 30

Tree DBH (cm)

Tre

es/h

a P

erce

nti

le

Methodology…


Methodology…T= ∑distance between all pairsWGij = ∑within group pairsBGij = T - WGij


Methodology…For each possible move, calculate:

New WGij

∆BGi

Rij = Wgij/ ∆Bgi

Find Rminij


Results


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


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)


Classifying Stands

• Plot cumulative distributions and compare to reference distributions


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)


Classifying Stands

• Use computer software (planned)

• Use keys in field guide



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"


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)


Classifying Stands

• Use Air Photo Interpretation





Classifying Stands

Class 14 Class 15 Class 17





• Use Air Photo Interpretation

Classifying Stands

• Recognize through familiarity


Classifying Stands


Classifying Stands

4

6

2 12

16


Classifying Stands14 16


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


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


Documentation

Field guide and poster

Lignum Limited web site:

www.lignum.com

go to publications


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

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