Forestry applications using LiDAR

Transcription

1 Forestry applications using LiDAR Ariadna Just (1), Mariló Cabré (1), Antonio Magariños (1), Jordi Vayreda (2) (1) ICGC (2) CREAF

2 2 Soil orders in Catalonia Forest presence 15% 30% 41% 8% 6% 56% Forest

3 3 Source: BIOLULIA

4 4 Existing forestry maps Forest land cover SPANISH FOREST MAP: MFE50 LAND COVER MAP OF CATALONIA: MCSC Resolution: 1:50000 Coverage: Spain Epoch represented: Distributor: MAGRAMA. Ministry of Agriculture, food and environment. OTHER LAND COVER MAPS: Resolution: 2m Coverage: Catalonia Epoch represented: 2009 Distributor: CREAF, Ecological and Forestry Applications Research Centre - CTFC: Map of Pure and mixed forest formations of Catalonia

5 5 Existing forestry maps Forest structure National forest inventory: IFN3 ( ) Other forest inventories Applications: Total aerial carbon % Trees in Catalonia Bark volume growth 0 (t/ha) 1-10 (t/ha) (t/ha) (t/ha) (t/ha) (t/ha) (t/ha) (t/ha) >=70 (t/ha) Source: SIBosC Source: Vangdata Source: SIBosC INSPIRE Conference 2016 Barcelona, 26 th 27 th September, 2016

6 6 ICGC. Cartography of Catalonia Existing cartography Topographic maps: From 1:5000 to 1:50000 over Catalonia 1:1000 in urban areas Geological cartography Digital Terrain Models Ortophotos: 25cm, 50cm, 2.5m over Catalonia 10cm on the coast

7 7 High resolution forestry maps: mvba20m Total Aerial Carbon Total Aerial Biomass Forest Canopy Cover Bark volume Basal Area Breast Height Foliage Biomass Medium Height

8 8 High resolution forestry maps: mvba20m LiDAR data Cartography of Catalonia forest biophysical variables (mvba20m) Total aerial carbon (t C/ha) Total aerial biomass (t/ha) Land Cover Map Bark volume (m3/ha) Basal area (m2/ha) Foliage biomass (t/ha) Diameter at breast height (cm) Forest canopy cover (%) Medium height (m) Plots of forest inventory

9 9 High resolution forestry maps: mvba20m Main characteristics: Resolution: 20m Coverage: Catalonia woodland Epoch represented: 2005 Distribution: WMS OGC service Download as GeoTIFF format: or More info:

10 10 High resolution forestry maps: mvba20m Comparison of different variables in La Garrotxa Volcanic Zone Natural Park

11 11 High resolution forestry maps: mvba20m Resolution 2500 larger than the traditional forest inventories Total Aerial Carbon (t C/ha) Before 2016 Nowadays Resolution: 1000x1000m Resolution: 20x20m Source: CREAF

12 12 Workflow Initial data LiDAR metrics Model adjustment Product Generation LiDAR data Forest inventory Land cover map Land cover map LiDAR point statistics LiDAR point Forest inventory cloud statistics Statistic models Cover maps

13 13 LiDARCAT Workflow Initial data LiDAR data capture LiDAR data processing LiDAR data distribution Flight dates: Sensor: ALS50 II Leica Point density: 0.5pt/m 2 Trajectory calculation Sensor calibration Point cloud generation Point cloud QC Strip adjustment Adjustment QC Automatic classification Editing (Manual classification) Format: LAS & LAZ 1.2 Classes: Ground, vegetation, building, towers, wires, noise, low points, air points Download: Administration-and- Enterprises/Downloads/Eleva tion/dades-lidar2

14 14 Workflow Initial data Land Cover Map of Catalonia Plots of forest inventory Resolution: 2m Epoch represented: 2009 Coverage: Catalonia Distributor: CREAF, Ecological and Forestry Applications Research Centre IFN3, 3rd National Forest Inventory ( ) CREAF forest inventories (2004, 2007, 2008, 2010, 2011)

15 15 Workflow Initial data LiDAR metrics Model adjustment Product Generation LiDAR data Forest inventory Land cover map Land cover map LiDAR point statistics LiDAR point Forest inventory cloud statistics Statistic models Cover maps

16 16 LiDAR Forestry Applications Workflow LiDAR metrics Orthometric Height Height above ground OH all point cloud OH TIN terrain = H above ground From 3m

17 17 Workflow Initial data LiDAR metrics Model adjustment Product Generation LiDAR data Forest inventory Land cover map Land cover map LiDAR point statistics LiDAR point Forest inventory cloud statistics Statistic models Cover maps

18 18 LiDAR Forestry Applications Workflow Model adjustment LiDAR explanatory variables Hmean, Hmax, percentiles, Num Points, Elev Skewness, FCC, Diff years, etc. Model adjustment Stepwise regression Statistical model for each specie and a general model Model validation Plots of forest inventories List of main species CAT = _ _

19 19 Workflow Initial data LiDAR metrics Model adjustment Product Generation LiDAR data Forest inventory Land cover map Land cover map LiDAR point statistics LiDAR point Forest inventory cloud statistics Statistic models Cover maps

20 20 Workflow Product generation The model is applied to each 20x20m pixel CAT = Statistical model Land cover map LiDAR data Total Aerial Carbon

21 21 LiDAR Forestry Applications Mbva20 - Applications Forest resources management planning Management/planning of estates or protected areas (Natura 2000, ENPEs ) Location and characterisation of mature forests Forest inventories (with or without field support)

22 22 LiDAR Forestry Challenges Challenges Challenges: Update mvba20 for the next decade ( ) LIDARCAT2. Flight dates: 2016 IFN4. Publication: by the end of 2016 Maps of biophysical variables for the scrubland cover Applications: Fire danger maps Increase the amount of forestry products INSPIRE directives

23 23 Institut Cartogràfic i Geològic de Catalunya Parc de Montjuïc, E Barcelona 41º22 12 N, 2º09 20 E (ETRS89) icgc@icgc.cat twitter.com/icgcat facebook.com/icgcat Tel. (+34) Fax (+34)