The effects of photo-interpreted variables in the estimation of stand-level merchantable volumes in the Province of Quebec

2010

Date Source: 

François Labbé of the Quebec Ministry of Natural Resources and Wildlife

Organizer: 

Gaetan Daigle or Louis-Paul Rivest at the Department of Mathematics and Statistics at Laval University

Context

The Quebec forest inventory is currently carried out using a stratified sampling design.  Aerial photos of a target Forest Management Unit (FMU) are first taken.  The areas of such FMU’s vary between 160 km2 and 27,000 km2. Photo-interpreters divide the territory into homogeneous polygons and, for each of those polygons, estimate the value of specific biological and physical variables. Once the photo-interpretation is completed, polygons with similar photo-interpreted characteristics are grouped into strata.  There can be more than 1000 strata in a FMU.  The stratification is used to direct the field inventory in which 400 m2 plots are established in stratum and in which forest properties such as basal area and merchantable volume per species are measured.  The target sample size is of 15 per stratum, but only a fraction of the plots required can be established within the target FMU. Several plots are therefore recruited from other FMU’s or from previous inventories through heuristic rules. Plots are assigned to strata, and strata-level forest properties are imputed from plot averages.  Field measurements are taken in the sampled plots such as the basal area and wood volume by species. 
 

As can be seen from the synthetic description of the current forest inventory practice in Québec, the photo-interpreted variables are used only for constructing the strata.  Can they be used to estimate the stand-level merchantable total and by species volume?
 

Objectives
 

Primary objective
 

The primary objective is to predict the total stand-level merchantable volume using the information from photo-interpreted, climatic, geographical and ecological classification variables.
 

Secondary objectives
 

It is also of interest to learn the following:

  1. How the explicative variables can be used to predict the hardwood and softwood total volume?
  2. How the explicative variables can be used to predict each of the species’ volume?

 

Research Question: 

To what extent do photo-interpreted variables explain the stand-level merchantable total volume and the wood volume by species?
 

Variables: 

Potential explanatory variables:

Group

Num

Name

Units

Description

 

1

ID _ PET _ MES

 

Temporary sample plot identifier

2

Tenure

0/1

0=Public land, 1=Private land

Photo-interpreted

3

Pert

0/1

0 = Undisturbed plot, 1 = Disturbed plot

4

h _ moy

m

Stand height

5

pct _ couv

%

Stand density expressed as the proportion of the plot area occupied by the projection of tree crown on the ground

6

pct _ RES

%

Forest type expressed as the proportion of basal area occupied by softwoods

7

Pct _ EB

%

Proportion of basal area occupied by White Spruce

8

Pct _ EN

%

Proportion of basal area occupied by Black Spruce

9

Pct _ EP

%

Proportion of basal area occupied by Red and Black Spruces

10

Pct _ ML

%

Proportion of basal area occupied by Tamarack

11

Pct _ PG

%

Proportion of basal area occupied by Jack Pine

12

Pct _ RX

%

Proportion of basal area occupied by undetermined softwoods

13

Pct _ SB

%

Proportion of basal area occupied by Balsam Fir

14

Pct _ SE

%

Proportion of basal area occupied by Balsam Fir and White Spruce

15

Pct _ TO

%

Proportion of basal area occupied by Eastern White Cedar

16

Pct _ BJ

%

Proportion of basal area occupied by Yellow Birch

17

Pct _ BP

%

Proportion of basal area occupied by White Birch

18

Pct _ EO

%

Proportion of basal area occupied by Red Maple

19

Pct _ ER

%

Proportion of basal area occupied by Maples

20

Pct _ ES

%

Proportion of basal area occupied by Sugar Maple

21

Pct _ FI

%

Proportion of basal area occupied by shade intolerant hardwoods

22

Pct _ FH

%

Proportion of basal area occupied by hardwoods on humid stations

23

Pct _ FN

%

Proportion of basal area occupied by non-commercial tree species

24

Pct _ FO

%

Proportion of basal area occupied by Black Ash

25

Pct _ FT

%

Proportion of basal area occupied by shade tolerant hardwoods

26

Pct _ FX

%

Proportion of basal area occupied by undetermined hardwoods

27

Pct _ PE

%

Proportion of basal area occupied by Poplars

28

Age _ moy

Year

Mid value of stand age class

29

Age _ structure

0/1

0=Even-aged forest stand, 1=Uneven-aged forest stand

30

Dep _ epais

cm

Modal deposit thickness

31

Drainage

 

Drainage index

Climatic

32

Deg _ jr

°C

Degree-day temperature

33

Ptot

mm

Mean annual total precipitation

34

Aridite

cm

Aridity index

Geographic

35

latitude

° decimal

Latitude

36

longitude

° decimal

Longitude

37

ALTITUDE

m

Altitude

38

PENTE

%

Slope

39

EXPOSITION

°

Aspect

40

potentiel

 

Site potential productivity index

41

topex

 

Wind exposure index

Ecological Land Classification Hierarchy

42

sous _ dom

 

Bioclimatic subdomain

43

reg _ ecol

 

Land region

44

sous _ reg

 

Land subregion

45

unit _ pays

 

Regional landscape

46

dist _ eco

 

Land distinct

 

Dependent variables:

Num

Name

Units

Description

1

ID _ PET _ MES

 

Temporary sample plot identifier

2

V _ BJ

m3/ha

Yellow Birch volume

3

V _ BP

m3/ha

White Birch volume

4

V _ EB

m3/ha

White Spruce volume

5

V _ SB

m3/ha

Balsam Fir volume

6

V _ TO

m3/ha

Eastern White-Cedar volume

7

V _ PE

m3/ha

Poplars volume

8

V _ EP

m3/ha

Black Spruce and Red Spruce volume

9

V _ FEU

m3/ha

Hardwood volume

10

V _ RES

m3/ha

Softwood volume

11

V _ TOT

m3/ha

Total volume

 

 

 

Data Access: 

A training data set of 5479 plots is available to construct the different models. This data set includes all the photo-interpreted variables along with some climatic and geophysical variables. Total volume in each plot is also available. Prediction of volumes has to be made for plots included in the test data set (UAF=012-54 with 1214 plots)
 

Data Files: 

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