Auburn University

Biosystems Engineering , Auburn UniversityChristian Brodbeck

John Fulton, Joey Shaw, Tim McDonald, Donn Rodekohr

Timber Mapping for Site-Specific Forest Management

Value Map

The Goal

• Develop site-specific data on a tract of timber that allows for future tree-to-tree based management decisions

Measure Individual

Tree Volume

Calculate Value / Tree

Analyze and Pattern

Variation

Adjust Management Decisions

Achieving the Goal• Ground Measurements

– Tree Location (X,Y,Z)– Tree Diameter (DBH) and Height– Soil Properties– Elevation

• LIDAR / GIS Analysis – Individual tree height determination– Bare Earth model– Volume / Value calculations

• Feasibility / Future Research

Ground Measurements• Order 1 soil survey

conducted• Tree location (x, y, and z)

using RTK GPS and a Total Station

• Tree diameter at breast height using calipers

• 20% of total tree heights using a laser range finder and clinometers

Traditional Volume Estimations• Conduct a timber cruise

– Statistical sample of plots distributed on a grid

– Measure all merchantable timber within plot

• Volume of trees on the plot are calculated using timber volume equations

• Volume is then extrapolated to entire tract– Tract is harvested and yield

data is not collected

Individual Tree Parameters

• To develop value maps, tree volume must first be determined.– Volume (cu. ft.) = A * DBH2 * Height

• For Pulpwood, A = 0.002323

• For Sawtimber, A = 0.002052

• Determination of individual tree height– Linear Regression Height Model

– LiDAR

Regression Height Model• Linear Regression Height

Model– Plotted known Heights vs.

DBH– Linear regression utilized to

correlate height and DBH– Heights, y, calculated based

on DBH, x, utilizing regression equation, y = 0.253x + 12.689

• Model reliability checked by plotting known heights vs. predicted heights and calculating individual R2

• Calculated individual stem volume

Class > 12y = 0.253x + 12.689

R2 = 0.3971

5

10

15

20

25

10 15 20 25 30 35 40 45

DBH (cm)

Mea

sure

d H

eigh

t (m

)

Class > 12

Class > 12

y = 0.3971x + 11.164R2 = 0.3971

10

15

20

25

5 10 15 20 25 30

Actual Height (m)

Reg

ress

ion

Pred

icte

d H

eigh

t (m

)

LIDAR• Light Detection and Ranging

(LIDAR) used to remotely measure– Distance, Speed, Rotation, and

Chemical composition and concentration

• Commercially purchased LIDAR typically contains two large datasets– Bare Earth

• Surfaces and Digital Elevation Models

– First Return• Vegetative Cover / Canopy• Buildings in urban areas

How do you filter out the useful data?

LIDARHow do you filter out the data?

• Two methods utilized

– LiDAR assigned height based on proximity

– LiDAR assigned height based on Canopy Surface

Models (CSM)

LIDAR Analysis by Proximity

220.17210.09200.39190.25

21210.26266

Ave Hgt

(LDR) (m)

LDR Hgt (m)

LDRDist (m)

Tree Num

1.5m

True Tree Position with

known heights

LIDAR Analysis by CSM• DEM created from Bare Earth data • It was assumed all trees were taller than 9m,

so all LiDAR First Return points less than 9m above the DEM were deleted– Remaining First Return dataset utilized to create

the three CSM.• Three Canopy Surface Models compared

– Kriging– Inverse Distance Weighted– Natural Neighbor

Results• The three proximity

approaches and three CSM were compared

• Predicted Height vs. Known height was plotted and R2

calculated to determine and compare reliability

y = 0.5892x + 8.955R2 = 0.5729

10

15

20

25

30

5 10 15 20 25 30

Actual Height (m)

LiD

AR

Hei

ght (

m)

y = 0.5621x + 9.3306R2 = 0.5349

10.00

15.00

20.00

25.00

30.00

5.00 10.00 15.00 20.00 25.00 30.00

Acutal Height (m)

Lida

r Hei

ght (

m)

Proximity Average

CSM Natural

Neighbor

GIS Analysis

Individual tree and total value calculated based on timber volume and current market price

Measure Individual

Tree Volume

Calculate Value / Tree

Analyze and Pattern

Variation

Adjust Management Decisions

GIS Analysis

Too much hardwood

competition (increase herbicide)

Too much within-pine competition (conduct more

aggressive thinning)

Poor productivity (plant lower

value seedlings)

Optimal growth

Feasibility / Future Research• Is this feasible?

– Commercially purchase the LIDAR data

• Input Bare Earth and First Return data into onboard computer

– Utilize Feller Buncher outfitted with GPS and diameter sensor to acquire an X, Y, and DBH

Onboard computer has bare earth surface and tract boundary loaded

Future Research

Onboard computer also has CSM

Future Research

Tree Height

Calculate Volume

Calculate Value

Future Research

Value Map

Thank You

Christian Brodbeckbrodbcj@auburn.edu

Biosystems EngineeringAuburn University

http://www.auprecisionforestry.org/