Lars Waser Kai Jütte Theresia Stampfer

Evaluating the potential of satellite data to classify tree species and multiple stages of tree damages

RU-Science Day 4 June 2013

Evaluating the potential of satellite data to classify tree species and multiple stages of

tree damages

Lars Waser Kai JütteTheresia Stampfer

Landesforst Mecklenburg-VorpommernAnstalt des öffentlichen Rechts

Betriebsteil Forstplanung, Versuchswesen, Forstliche Informationssysteme



Tornado „Doris“

1/13



Situation / goals

Tornado „Doris“ – severe storm & hail; 11 June 2010

> 2000 ha of forest affected / destroyed

=> Focus on detecting multiple stages of tree damages (ash / Scots pine)

=> Which tree species are affected most? (tree species classification)

Which satellite system is most appropriate? (costs, Pros / Cons)

2/13



Study areasGerman State Mecklenburg-Vorpommern

3/13



Satellite data

- Passive optical system, 2 m- 8 bands RGBI, costal, yellow, NIR2, Rededge

WorldView-2 images - Active system, X-band (3 cm)- 1.25 m

TerraSAR-X images

4/13



Training / reference data 7 Tree species: Delineated tree crown polygons (756)

4 stages of tree damages (ash / Scots pine): 4 x 120 polygons

=> Ash, beech, Douglas fir, larch, Norway spruce, oak, poplar

Terr

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1 (0-25%) 2 (25-50%) 3 (50-75%) 4 (75-100%)destroyed foliage

5/13



In-situ spectral measurements

6/13

e.g. damage stage 3

a mobile crane Aerial images

Terrestrial survey

Crown view from:

WorldView-2 images



Training / reference data

- Delineated tree crown polygons (756)Different stages of damaged Scots pine (2011)

7/13



Classification Pre-processing - De-Hazing+Atmospheric Correction

- Original bands & 22 Vegetation indices

- 20 indices (filters, textural & structural)

Signatures (variables)

Validation of prediction: external, independent reference data (polygons)

- Noise reduction

Multinomial log. regression

- Cross-Validation (10-fold)

- Variable selection

- Image segmentations

8/13



Results

TerraSAR-X

Waser et al. in prep. for Remote Sensing of Environment

WorldView-2

7 tree species

ash

Scots pine

Overallacc.

Overallacc.kappa kappa

0.90 0.83 0.310.56

=> ash and poplar > 0.7

ash, beech, Douglas fir, larch, Norway spruce, oak, poplar

Stage of damage

1 32 4 1 32 4

0.83 0.730.65 0.78 0.62 0.520.44 0.56

0.78 0.710.62 0.72 0.62 0.530.39 0.59

10-fold cross-validated

9/13



Results

TerraSAR-X

Waser et al. in prep. for Remote Sensing of Environment

WorldView-2

7 tree species

ash

Scots pine

Overallacc.

Overallacc.kappa kappa

0.90 0.83 0.310.56

=> ash and poplar > 0.7

ash, beech, Douglas fir, larch, Norway spruce, oak, poplar

Stage of damage

1 32 4 1 32 4

0.83 0.730.65 0.78 0.62 0.520.44 0.56

0.79 0.710.62 0.76 0.62 0.530.39 0.59

10-fold cross-validated

9/13



Overall accuracies of prediction (independent reference data) 81% 50%

WorldView-2 versus TerraSAR-X: tree species

WorldView-2 TerraSAR-X

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WorldView-2 versus TerraSAR-X: damaged ash


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WorldView-2 versus TerraSAR-X: damaged Scots pine


Overall accuracies of prediction (independent reference data) 72% 35%

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Conclusions & outlook

Multispectral WorldView-2 have a high potential for classifying: - tree species (7)

- 4 different stages of damaged ash and Scots pine

TerraSAR-X data less (not) appropriate (exceptions)

Calculation of indices significantly (p = 0.01) improved classification accuracies

Reasonable amount of effort regarding data acquisition and pre-processing

Testing aerial images (lower costs, more flexible)

13/13



13/13

Thank you!

Lars Waser Kai Jütte Theresia Stampfer

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