Canopy Height Model SWITZERLAND

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Covering the whole variety of Switzerland (elevation, topography, species mixtures, open and close forest)

Applying models using CHM outside forest areas Large outliers in areas where matching was not

successful Time differences in comparison to reference data Temporal heterogeneity of the CHM Potential for change detection Leaf-off and leaf-on status

Challenges

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Canopy Height Model (CHM)- input image data- workflow

Accuracy assessment- reference data sets- accuracy measures

Forest application CHM- comparison tree heights NFI- habitat suitability modelling

Outline Work Christian & Martina

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ADS 80 aerial stereo-images- 0.25 and 0.5 m GSD- mosaic of year 2007-2012- leaf-on (May – September)- CIR Nadir/Backward 16bit (pushbroom)

Aerial image data

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Image matching in SocetSet- different strategies in NGATE- area- and feature-based methods- completeness of 0.95

170’000 blocks of 0.5 x 0.5 km- most nadir part of image

Reasonable calculation time - 16 min per block/strategy- 320 days (16 2-cores virtual PCs)- update ⅙ Switzerland in ~50 days

Image matching

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Topographic survey points N = 198- independent data set

Ground control points N = 2,483- used for image orientation

Stereo measurements N = 195,784- land cover types assigned- double measurements for accuracy estimation

Reference data sets – DSM accuracy

Restrictions: - matched points only - no water bodies- same image data- raster of 4 pixel for comparison

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Topographic survey points

DSM accuracies flat terrain

GSD [m] Sample Median [m] NMAD [m]0.25 164 0.07 0.290.50 34 -0.11 0.64

NMAD = Normalized Median Absolute Deviation

Terrestrial measurement of elevation [m a.s.l.]

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Topographic survey points

Ground control points

DSM accuracies flat terrain

Topographic survey pointsGround control points

GSD [m] Sample Median [m] NMAD [m]0.25 164 0.07 0.290.50 34 -0.11 0.64

GSD [m] Sample Median [m] NMAD [m]

0.25 2,033 -0.10 0.270.50 450 -0.18 0.50

NMAD = Normalized Median Absolute Deviation

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DSM accuracies land cover

Stereo measurementsdifferent land cover

Land cover class GSD [m] Sample size N Median [m] NMAD [m]

Coniferous forest 0.25 24,996 -0.08 1.760.50 7,594 -0.34 2.39

Deciduous forest0.25 13,211 0.16 2.950.50 11,076 -0.79 3.94

Herb and grass 0.25 55,689 -0.13 0.490.50 37,233 -0.25 0.95

Building 0.25 2,919 -0.12 0.830.50 359 -0.24 1.12

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DSM accuracies slope

Stereo measurementsdifferent slope categories

Slope [°] GSD [m] Sample size N Median [m] NMAD [m]

≤ 10 0.25 63,232 -0.16 0.670.50 7,944 -0.44 0.90

> 10 & ≤ 20 0.25 24,319 -0.17 1.300.50 17,337 -0.64 0.96

> 20 & ≤ 30 0.25 11,336 0.46 2.400.50 25,307 -0.86 1.29

> 30 & ≤ 40 0.25 4,999 1.17 3.260.50 24,098 -1.01 1.78

> 40 0.25 1,468 0.59 4.000.50 15,744 -1.36 2.52

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Calculated based on swissALTI3D- laser data, 0.5 points/m2

- settlements mask out with TLM- cut at 0 and 60 m

Canopy height model

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NFI 4 terrestrial tree heights N = 3,109- top canopy layer trees only- geolocated plots only- year image data < year field measurement

Buffer d=5 m around each tree- maximum value for comparison- only where > 15 points matched- not when maximum value equal zero

Double measurements NFI N = 441- estimation of measuring errors in the field

Comparison with tree heights NFI

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Correlation all trees

Tree height in canopy height model [m]

Tree

hei

ght N

FI [m

] r2 = 0.69, N= 3109

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Correlations tree type

Tree height in canopy height model [m]Tree height in canopy height model [m]

Tree

hei

ght N

FI [m

]

Tree

hei

ght N

FI [m

]

r2 = 0.7, N= 2137r2 = 0.7, N= 972

Deciduous trees Coniferous trees

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Correlations elevation

Tree height in canopy height model [m]Tree height in canopy height model [m]

Tree

hei

ght N

FI [m

]

Tree

hei

ght N

FI [m

]

r2 = 0.6, N= 1329r2 = 0.72, N= 1780

Lower elevations Higher elevations

Comparison tree height NFI

Tree type GSD [m]

Sample size

Sample no out-lier

Median [m]

NMAD [m]

Quant 68% [m]

Quant 95% [m]

RMSE [m]

RMSE no out-lier [m]

Deciduous 0.25 872 865 -0.56 3.34 0.93 7.31 4.24 3.910.50 100 97 0.50 3.08 2.38 9.54 4.47 3.75

Coniferous 0.25 1562 1541 -1.86 2.65 -0.54 4.02 4.30 3.630.50 575 560 -2.54 3.72 -0.81 4.02 6.28 5.02

Median errors < 2.6 m NMAD < 3.8 m

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Median errors < 15 cm NMAD < 2m

Double measurements NFI

Tree type Sample size

Sample size no outliers

Median [m]

NMAD [m]

Quant 68% [m]

Quant 95% [m]

RMSE [m]

RMSE no outliers [m]

Deciduous 117 116 -0.10 1.93 0.72 3.28 2.42 2.28

Coniferous 324 320 -0.15 1.26 0.50 3.27 1.72 1.55

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Capercaillie (Tetrao urogallus)- umbrella species of conservation concern- structurally rich, semi-open forests

Paired presence/absence data

Habitat suitability modelling

Capercaillie

HabitatKurt Bollmann

Michael Lanz

n=104

Explanatory variables Two models: (1) Aerial image CHM and (2) ALS CHM

*only for ALS model

Environment+ Climate+ Topography+ NDVI

StructureChm10avg Mean 10th percentile of CHM [m]Chm10sd SD 10th percentile of CHM [m]*Chm95avg Mean 95th percentile of CHM [m]Chm95sd SD 95th percentile of CHM [m]

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Aerial image data ALS dataAUC (SE) AUC (SE)

Structure 0.72 (0.04) 0.70 (0.05)

Habitat suitability model

Boosted regression trees 10-fold cross validation

Environment 0.89 (0.03) 0.88 (0.05)