Use R! for estimating forest parameters based on Airborne Laser - - PowerPoint PPT Presentation

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Use R! for estimating forest parameters based on Airborne Laser - - PowerPoint PPT Presentation

Oct 01, 2023 451 likes •950 views

Introduction Methods and Results Ongoing research and summary Use R! for estimating forest parameters based on Airborne Laser Scanner Data Johannes Breidenbach Forest Research Institute Baden-Wrttemberg, Department of Biometrics Forstliche

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SLIDE 1

Introduction Methods and Results Ongoing research and summary

Use R! for estimating forest parameters based

  • n Airborne Laser Scanner Data

Johannes Breidenbach

Forest Research Institute Baden-Württemberg, Department of Biometrics

Forstliche Versuchs- und Forschungsanstalt Baden-Württemberg Abteilung Biometrie und Informatik; Wonnhaldestr. 4; 79100 Freiburg Fon: +49 (0)761-4018-315; Johannes.Breidenbach@forst.bwl.de

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 2

Introduction Methods and Results Ongoing research and summary

Inhalt

1

Introduction Background Airborne Laser Scanning Analyzing laser data

2

Methods and Results A mixed model (lme) for timber volume estimation A GAMLSS for diameter distribution estimation

3

Ongoing research and summary

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 3

Introduction Methods and Results Ongoing research and summary Background Airborne Laser Scanning Analyzing laser data

1

Introduction Background Airborne Laser Scanning Analyzing laser data

2

Methods and Results A mixed model (lme) for timber volume estimation A GAMLSS for diameter distribution estimation

3

Ongoing research and summary

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 4

Introduction Methods and Results Ongoing research and summary Background Airborne Laser Scanning Analyzing laser data

Sample Plot Inventory

Forest inventory → statistical sound information on the enterprize-level (Stands are too small)

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 5

Introduction Methods and Results Ongoing research and summary Background Airborne Laser Scanning Analyzing laser data

Forest Inventory

Forest inventory → statistical sound information on the enterprize-level (Stands are too small)

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 6

Introduction Methods and Results Ongoing research and summary Background Airborne Laser Scanning Analyzing laser data

Motivation

High costs Insufficient information on stand level Staff reduction Increased economical interest in timber products ⇒ Greater information-need on the stand level

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 7

Introduction Methods and Results Ongoing research and summary Background Airborne Laser Scanning Analyzing laser data

Motivation

High costs Insufficient information on stand level Staff reduction Increased economical interest in timber products ⇒ Greater information-need on the stand level

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 8

Introduction Methods and Results Ongoing research and summary Background Airborne Laser Scanning Analyzing laser data

Motivation

High costs Insufficient information on stand level Staff reduction Increased economical interest in timber products ⇒ Greater information-need on the stand level

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 9

Introduction Methods and Results Ongoing research and summary Background Airborne Laser Scanning Analyzing laser data

Motivation

High costs Insufficient information on stand level Staff reduction Increased economical interest in timber products ⇒ Greater information-need on the stand level

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 10

Introduction Methods and Results Ongoing research and summary Background Airborne Laser Scanning Analyzing laser data

Motivation

High costs Insufficient information on stand level Staff reduction Increased economical interest in timber products ⇒ Greater information-need on the stand level

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 11

Aim ⇒ Regionalization (small area estimation): From a point-wise to a wall-to-wall information

3422500 3423000 3423500 5327000 5327500 5328000 Rechtswert [m] Hochwert [m]

Vorrat [Vfm ha−1] 454 966 FoGIS Bestandesgrenzen

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SLIDE 12

Introduction Methods and Results Ongoing research and summary Background Airborne Laser Scanning Analyzing laser data

1

Introduction Background Airborne Laser Scanning Analyzing laser data

2

Methods and Results A mixed model (lme) for timber volume estimation A GAMLSS for diameter distribution estimation

3

Ongoing research and summary

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 13

Introduction Methods and Results Ongoing research and summary Background Airborne Laser Scanning Analyzing laser data

Airborne Laser Scanning

http://www.geokosmos.com/technologies/airbornscan.jpg

Active remote sensing system Laser for distance measurement Pointcloud with XYZ-raw data

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 14

Introduction Methods and Results Ongoing research and summary Background Airborne Laser Scanning Analyzing laser data

Airborne Laser Scanning

http://www.geokosmos.com/technologies/airbornscan.jpg

Active remote sensing system Laser for distance measurement Pointcloud with XYZ-raw data

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 15

Introduction Methods and Results Ongoing research and summary Background Airborne Laser Scanning Analyzing laser data

Airborne Laser Scanning

http://www.geokosmos.com/technologies/airbornscan.jpg

Active remote sensing system Laser for distance measurement Pointcloud with XYZ-raw data

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 16

Introduction Methods and Results Ongoing research and summary Background Airborne Laser Scanning Analyzing laser data

Digital Terrain Model

Software: TreesVis, FELIS Uni Freiburg

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 17

Introduction Methods and Results Ongoing research and summary Background Airborne Laser Scanning Analyzing laser data

Digital Surface Model

Software: TreesVis, FELIS Uni Freiburg

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 18

Introduction Methods and Results Ongoing research and summary Background Airborne Laser Scanning Analyzing laser data

1

Introduction Background Airborne Laser Scanning Analyzing laser data

2

Methods and Results A mixed model (lme) for timber volume estimation A GAMLSS for diameter distribution estimation

3

Ongoing research and summary

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 19

Introduction Methods and Results Ongoing research and summary Background Airborne Laser Scanning Analyzing laser data

Area-based method

Aggregation of laser data on sample plot level → metrics Statical relation between

Metrics Sample plot attributes (volume, diameter distribution, tree height)

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 20

Introduction Methods and Results Ongoing research and summary Background Airborne Laser Scanning Analyzing laser data

Area-based method

Aggregation of laser data on sample plot level → metrics Statical relation between

Metrics Sample plot attributes (volume, diameter distribution, tree height)

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 21

Introduction Methods and Results Ongoing research and summary Background Airborne Laser Scanning Analyzing laser data

Area-based method

Aggregation of laser data on sample plot level → metrics Statical relation between

Metrics Sample plot attributes (volume, diameter distribution, tree height)

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 22

Introduction Methods and Results Ongoing research and summary Background Airborne Laser Scanning Analyzing laser data

Area-based method

Aggregation of laser data on sample plot level → metrics Statical relation between

Metrics Sample plot attributes (volume, diameter distribution, tree height)

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 23

Introduction Methods and Results Ongoing research and summary Background Airborne Laser Scanning Analyzing laser data

Computation of metrics

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 24

Introduction Methods and Results Ongoing research and summary Background Airborne Laser Scanning Analyzing laser data

Computation of metrics - basic R

Vegetationshöhe [m] Häufigkeit 10 15 20 25 30 10 20 30 40 50

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 25

Introduction Methods and Results Ongoing research and summary Background Airborne Laser Scanning Analyzing laser data

Computation of metrics - basic R

Vegetationshöhe [m] Häufigkeit 10 15 20 25 30 10 20 30 40 50 0% Perzentil 25% Perzentil 50% Perzentil 75% Perzentil 100% Perzentil

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 26

Introduction Methods and Results Ongoing research and summary Background Airborne Laser Scanning Analyzing laser data

Computation of metrics - basic R

Vegetationshöhe [m] Häufigkeit 10 15 20 25 30 10 20 30 40 50 0% Perzentil 25% Perzentil 50% Perzentil 75% Perzentil 100% Perzentil Mittelwert

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 27

Introduction Methods and Results Ongoing research and summary Background Airborne Laser Scanning Analyzing laser data

Other predictor variables - ArcGIS

Crown cover Coniferous proportion

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 28

Introduction Methods and Results Ongoing research and summary A mixed model (lme) for timber volume estimation A GAMLSS for diameter distribution estimation

1

Introduction Background Airborne Laser Scanning Analyzing laser data

2

Methods and Results A mixed model (lme) for timber volume estimation A GAMLSS for diameter distribution estimation

3

Ongoing research and summary

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 29

Introduction Methods and Results Ongoing research and summary A mixed model (lme) for timber volume estimation A GAMLSS for diameter distribution estimation

Hierarchical data structure

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 30

Introduction Methods and Results Ongoing research and summary A mixed model (lme) for timber volume estimation A GAMLSS for diameter distribution estimation

Hierarchical data structure

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 31

Introduction Methods and Results Ongoing research and summary A mixed model (lme) for timber volume estimation A GAMLSS for diameter distribution estimation

Linear mixed model - lme yij = X ijβ + Ui,jγi + Uijγij + εij with γi ∼ N(0, D(1)), γij ∼ N(0, D(2)), εij ∼ N(0, Σij) where Σij =    σ2ˆ y2δ

ij1

· · · Kov(εij1, εijnij) . . . ... . . . Kov(εijnij, εij1) · · · σ2ˆ y2δ

ijnij

   and Kov(εijk, εijk′) = exp(−s/ρ) σˆ yδ

ijk σˆ

yδ

ijk′

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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Regionalization - Maptools

3422500 3423000 3423500 5327000 5327500 5328000 Rechtswert [m] Hochwert [m]

Laubwald Mischwald Nadelwald Lichter Bereich Starke vertikale Strukur FoGIS Bestandesgrenzen

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SLIDE 33

Regionalization - Maptools

3422500 3423000 3423500 5327000 5327500 5328000 Rechtswert [m] Hochwert [m]

Vorrat [Vfm ha−1] 454 966 FoGIS Bestandesgrenzen

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SLIDE 34

Regionalization - Maptools

3422500 3423000 3423500 5327000 5327500 5328000

457.13 278.87 199.27 346.96 588.60 412.67 397.51 537.47 431.40 515.96 323.84 521.79 556.95 482.69 428.28 143.29 563.85 261.38 337.48 138.01 391.16 518.55 281.84 590.42 134.58 521.74 356.49 608.37 176.22 686.29 (67.8) (0.1) (3.6) (3.7) (1.0) (0.1) (0.3) (0.3) (0.2) (0.8) (0.7) (0.4) (0.2) (0.1) (1.4) (0.7) (12.2) (0.1) (0.3) (0.1) (11.1) (12.9) (0.5) (0.6) (0.1) (9.4) (0.2) (4.5) (0.2) (3.5) (0.1) 506.52 NA 289.10 388.83 282.85 420.70 599.50 582.90 534.70 413.80 542.25 395.82 NA NA NA 710.20 183.47 407.66 NA NA 256.50 200.05 514.00 NA 510.70 485.60 805.40 NA 473.55 (NA) (8.7) (NA) (NA) (8.9) (21.9) (28.3) (20.8) (NA) (NA) (5.1) (10.2) (13.4) (NA) (NA) (NA) (15.4) (30.3) (13.0) (NA) (NA) (NA) (9.2) (17.4) (NA) (36.9) (NA) (29.6) (NA) (29.4)

Rechtswert [m] Hochwert [m]

Vorrat [Vfm ha−1] 98.36 − 293.22 293.22 − 406.69 406.69 − 521.75 521.75 − 686.29 Stichprobenpunkte

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Introduction Methods and Results Ongoing research and summary A mixed model (lme) for timber volume estimation A GAMLSS for diameter distribution estimation

1

Introduction Background Airborne Laser Scanning Analyzing laser data

2

Methods and Results A mixed model (lme) for timber volume estimation A GAMLSS for diameter distribution estimation

3

Ongoing research and summary

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 36

Introduction Methods and Results Ongoing research and summary A mixed model (lme) for timber volume estimation A GAMLSS for diameter distribution estimation

Modeling I

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 37

Introduction Methods and Results Ongoing research and summary A mixed model (lme) for timber volume estimation A GAMLSS for diameter distribution estimation

Modeling II

Generalized additive model for location, scale and shape - GAMLSS Be y ∼ Weibull(a, b, c), a = 7, b, c > 0 with density f(y|b, c) = c b y b c−1 exp

  • −

y b c , then b = h−1(η) und c = h−1(η). Where a = Location-, b = Scale- and c = Shape parameter, ηi = x′

i β as well as h = link function.

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 38

Qu1: (24,26.8] Qu3: (28.9,32.7] Plots: 20 Trees: 242

Density 20 40 60 80 0.00 0.04 0.08

Qu1: (18.2,21.1] Qu3: (25.2,28.9] Plots: 45 Trees: 472

Density 20 40 60 80 0.00 0.04 0.08

Qu1: (21.1,24] Qu3: (25.2,28.9] Plots: 33 Trees: 436

DBH (cm) Density 20 40 60 80 0.00 0.04 0.08

Qu1: (15.4,18.2] Qu3: (21.5,25.2] Plots: 58 Trees: 725

20 40 60 80 0.00 0.04 0.08

Qu1: (18.2,21.1] Qu3: (21.5,25.2] Plots: 38 Trees: 561

20 40 60 80 0.00 0.04 0.08

Qu1: (12.5,15.4] Qu3: (17.7,21.5] Plots: 51 Trees: 676

DBH (cm) 20 40 60 80 0.00 0.04 0.08

Qu1: (15.4,18.2] Qu3: (17.7,21.5] Plots: 29 Trees: 430

20 40 60 80 0.00 0.04 0.08

Qu1: (9.67,12.5] Qu3: (14,17.7] Plots: 40 Trees: 449

20 40 60 80 0.00 0.04 0.08

Qu1: (6.81,9.67] Qu3: (10.3,14] Plots: 22 Trees: 228

DBH (cm) 20 40 60 80 0.00 0.04 0.08

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SLIDE 39

Introduction Methods and Results Ongoing research and summary

1

Introduction Background Airborne Laser Scanning Analyzing laser data

2

Methods and Results A mixed model (lme) for timber volume estimation A GAMLSS for diameter distribution estimation

3

Ongoing research and summary

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 40

Introduction Methods and Results Ongoing research and summary

Ongoing research

20 40 60 80 10 20 30 40 DBH (cm) Height (m)

Bivariate height- and diameter distribution Random forests to estimate tree-species specific timber volume (multivariate)

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 41

Introduction Methods and Results Ongoing research and summary

Ongoing research

Fi Bu Ta Dgl BAh Vorrat (m3ha−1) 50 100 150 200

Bivariate height- and diameter distribution Random forests to estimate tree-species specific timber volume (multivariate)

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 42

Introduction Methods and Results Ongoing research and summary

Summary

R is well suited for analyzing laser data due to its...

functionality to call other programs - shell() flexibility (writing own functions) state-of-the-art statistical methods

Still learning R after 5 years of use...

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

slide-43
SLIDE 43

Introduction Methods and Results Ongoing research and summary

Summary

R is well suited for analyzing laser data due to its...

functionality to call other programs - shell() flexibility (writing own functions) state-of-the-art statistical methods

Still learning R after 5 years of use...

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

slide-44
SLIDE 44

Introduction Methods and Results Ongoing research and summary

Summary

R is well suited for analyzing laser data due to its...

functionality to call other programs - shell() flexibility (writing own functions) state-of-the-art statistical methods

Still learning R after 5 years of use...

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 45

Introduction Methods and Results Ongoing research and summary

Summary

R is well suited for analyzing laser data due to its...

functionality to call other programs - shell() flexibility (writing own functions) state-of-the-art statistical methods

Still learning R after 5 years of use...

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

slide-46
SLIDE 46

Introduction Methods and Results Ongoing research and summary

Summary

R is well suited for analyzing laser data due to its...

functionality to call other programs - shell() flexibility (writing own functions) state-of-the-art statistical methods

Still learning R after 5 years of use...

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS

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SLIDE 47

Introduction Methods and Results Ongoing research and summary

Thanks go to... Christian Gläser, Drs. Edgar Kublin, Matthias Schmidt, Arne Nothdurft, Gerald Kändler You for your attention!

  • J. Breidenbach

Use R! for estimating forest parameters based on ALS