Canopy Height Model SWITZERLAND

 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

 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

 ADS 80 aerial stereo-images and 0.5 m GSD - mosaic of year leaf-on (May – September) - CIR Nadir/Backward 16bit (pushbroom) Aerial image data 4

 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 days (16 2-cores virtual PCs) - update ⅙ Switzerland in ~50 days 5 Image matching

 Topographic survey points N = 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

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

 Topographic survey points  Ground control points DSM accuracies flat terrain 8 Topographic survey points Ground control points GSD [m]SampleMedian [m]NMAD [m] GSD [m]SampleMedian [m]NMAD [m] 0.252, NMAD = Normalized Median Absolute Deviation

DSM accuracies land cover 9  Stereo measurements different land cover Land cover classGSD [m]Sample size NMedian [m]NMAD [m] Coniferous forest , , Deciduous forest , , Herb and grass , , Building 0.252,

DSM accuracies slope 10  Stereo measurements different slope categories Slope [°] GSD [m]Sample size NMedian [m]NMAD [m] ≤ , , > 10 & ≤ , , > 20 & ≤ , , > 30 & ≤ , , > , ,

 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

 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 = estimation of measuring errors in the field 12 Comparison with tree heights NFI

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

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 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

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 Coniferous  Median errors < 2.6 m  NMAD < 3.8 m

 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] Deciduous Coniferous

 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

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

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)