1. Canopy Height Model SWITZERLAND

2.  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 2 Challenges

3.  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 3

4.  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 4

5.  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 5 Image matching

6.  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 6 Reference data sets – DSM accuracy Restrictions: - matched points only - no water bodies - same image data - raster of 4 pixel for comparison

7.  Topographic survey points DSM accuracies flat terrain 7 GSD [m]SampleMedian [m]NMAD [m] 0.251640.070.29 0.5034-0.110.64 NMAD = Normalized Median Absolute Deviation Terrestrial measurement of elevation [m a.s.l.]

8.  Topographic survey points  Ground control points DSM accuracies flat terrain 8 Topographic survey points Ground control points GSD [m]SampleMedian [m]NMAD [m] 0.251640.070.29 0.5034-0.110.64 GSD [m]SampleMedian [m]NMAD [m] 0.252,033-0.100.27 0.50450-0.180.50 NMAD = Normalized Median Absolute Deviation

9. DSM accuracies land cover 9  Stereo measurements different land cover Land cover classGSD [m]Sample size NMedian [m]NMAD [m] Coniferous forest 0.2524,996-0.081.76 0.507,594-0.342.39 Deciduous forest 0.2513,2110.16 2.95 0.5011,076-0.79 3.94 Herb and grass 0.2555,689-0.130.49 0.5037,233-0.250.95 Building 0.252,919-0.120.83 0.50359-0.241.12

10. DSM accuracies slope 10  Stereo measurements different slope categories Slope [°] GSD [m]Sample size NMedian [m]NMAD [m] ≤ 10 0.2563,232-0.160.67 0.507,944-0.440.90 > 10 & ≤ 20 0.2524,319-0.171.30 0.5017,337-0.640.96 > 20 & ≤ 30 0.2511,3360.462.40 0.5025,307-0.861.29 > 30 & ≤ 40 0.254,9991.173.26 0.5024,098-1.011.78 > 40 0.251,4680.594.00 0.5015,744-1.362.52

11.  Calculated based on swissALTI3D - laser data, 0.5 points/m 2 - settlements mask out with TLM - cut at 0 and 60 m 11 Canopy height model

12.  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 12 Comparison with tree heights NFI

13. 13 Correlation all trees Tree height in canopy height model [m] Tree height NFI [m] r 2 = 0.69, N= 3109

14. 14 Correlations tree type Tree height in canopy height model [m] Tree height NFI [m] r 2 = 0.7, N= 2137 r 2 = 0.7, N= 972 Deciduous treesConiferous trees

15. 15 Correlations elevation Tree height in canopy height model [m] Tree height NFI [m] r 2 = 0.6, N= 1329r 2 = 0.72, N= 1780 Lower elevationsHigher elevations

16. Comparison tree height NFI Tree typeGSD [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 0.25872865-0.563.340.937.314.243.91 0.50100970.503.082.389.544.473.75 Coniferous 0.2515621541-1.862.65-0.544.024.303.63 0.50575560-2.543.72-0.814.026.285.02  Median errors < 2.6 m  NMAD < 3.8 m

17.  Median errors < 15 cm  NMAD < 2m 17 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] Deciduous117116-0.101.930.723.282.422.28 Coniferous324320-0.151.260.503.271.721.55

18.  Capercaillie (Tetrao urogallus) - umbrella species of conservation concern - structurally rich, semi-open forests  Paired presence/absence data 18 Habitat suitability modelling Capercaillie Habitat Kurt Bollmann Michael Lanz n=104

19. Explanatory variables  Two models: (1) Aerial image CHM and (2) ALS CHM *only for ALS model Environment + Climate + Topography + NDVI Structure Chm10avgMean 10 th percentile of CHM [m] Chm10sdSD 10 th percentile of CHM [m]* Chm95avgMean 95 th percentile of CHM [m] Chm95sdSD 95 th percentile of CHM [m] 19

20. Aerial image dataALS data AUC (SE) Structure0.72 (0.04)0.70 (0.05) 20 Habitat suitability model  Boosted regression trees  10-fold cross validation Environment0.89 (0.03)0.88 (0.05)