Mining for the Timber-Volume for a State-Wide Forest Information System. LIDAR Mapping Forum, February, 15th, 2017 Dr.-Ing.

Transcription

1 Mining for the Timber-Volume for a State-Wide Forest Information System LIDAR Mapping Forum, February, 15th, 2017 Dr.-Ing. Arno Buecken

2 Sustainable Usage of the Forest Key Idea: Do not harvest more than the timber volume that grows back. We need a precise inventory of the forest. Image: Pixabay 3

3 Images: J. Dietz Traditional forest surveying Terrestrial Survey Measuring DBH Manual Notes 4

4 Image: J. Dietz 1) Perform an angular sample count to determine the basal area of all trees of the unit 5

5 2) Determine top or mean height of the trees 6

6 Image: Pixabay 3) Determine the age of the trees 7

7 4) Estimate the timber volume by using the yield tables Yield Class The yield tables are a characteristic Yield map for forestry units. Table Age Height 8

8 Image: W. Hartmann 5) Update the map of the unit. 9

9 Image: J. Dietz 6) Take the collected data to the office. This has to be repeated every seven years for each forestry unit. 10

10 Survey Forest Surveyor Basal Area Species Distribution Height Age Yield Classes 11

11 Remote Sensing 12

12 Image: A. Böhm Forest Surveyor

13 Survey Forest Surveyor Forest Surveyor 2.0 (individual trees) Basal Area Species Distribution Basal Area Species Distribution Height Height Age Age Yield Classes Yield Classes 14

14 LIDAR point clouds Point Clouds in Testareas provide a detailed view of the forestry unit. 15

15 From Testareas to States BIG DATA State Northrhine-Westfalia Heterogenous Pointcloud 250 Billion Points 1-10 Points/m² km² Several Flight Campaigns Different Years Map: Wikipedia 16

16 Open data in Northrhine-Westfalia Since January 1st, 2017, Northrhine-Westfalia provides open-data. All geodata collected by the state are now available for free for everybody. Map: Wikipedia 17

17 Image: GEObasis.NRW Open data in Northrhine-Westfalia Classification First Pulse Last Pulse Single Return Artificial Point 18

18 Open data LIDAR point clouds Points/m² Near Espelkamp Near Winterberg Near Bad Münstereifel

19 Survey Forest Surveyor Forest Surveyor 2.0 (stand wise) Basal Area Species Distribution Basal Area Species Distribution Height Height Age Age Yield Classes Yield Classes 20

20 Species Distribution Calculate the tree species distribution from the classification map. 21

21 Survey Forest Surveyor Forest Surveyor 2.0 (stand wise) Basal Area Species Distribution Basal Area Species Distribution Height Height Age Age Yield Classes Yield Classes 22

22 Top Height For each species: Weighted average of the highest points for raster cell 23

23 Survey Forest Surveyor Forest Surveyor 2.0 (stand wise) Basal Area Species Distribution Basal Area Species Distribution Height Height Age Age Yield Classes Yield Classes 24

24 Basal Area The basal area is a measure for the density of a forestry unit. It is associated with the yield factor. There is a correlation between the yield factor and a density in the LIDAR data. Yield Factor Yield Table Desired Basal Area Basal Area 25

25 Basal Area But Density in the LIDAR data depends on the flight and scanner parameters! 26

26 Yield Factor Collection of ground truth and remote sensing data are not synchronous. Units may be fully stocked in one and empty in the other dataset. 27

27 Yield Factor 28

28 Correlation Yield Factor 1) Calculate Correlation 1,0 0,5 0,0 0% 100% Height of the Decision Plane 29

29 Correlation Mean Square Error Yield Factor 1) Calculate Correlation 2) Perform Regression Analysis 3) Calculate Mean Square Error 1,0 0,5 0,0 0% 100% Height of the Decision Plane 30

30 Yield Factor Correlation Mean Square Error Yield Factor 1,5 1,0 1,0 1) Calculate Correlation 2) Perform Regression Analysis 3) Calculate Mean Square Error 4) Calculate resulting Yield Factors for a Canopy Cover between 0% and 100% 0,5 0,5 0,0 0,0 0% 100% Height of the Decision Plane 31

31 Yield Factor Correlation Mean Square Error Yield Factor 1,5 1,0 1,0 1) Calculate Correlation 2) Perform Regression Analysis 3) Calculate Mean Square Error 4) Calculate resulting Yield Factors for a Canopy Cover between 0% and 100% 5) Decide which Decision Plane has to be used 0,5 0,5 0,0 0,0 0% 100% Height of the Decision Plane 32

32 Survey Forest Surveyor Forest Surveyor 2.0 (stand wise) Basal Area Species Distribution Basal Area Species Distribution Height Height Age Age Yield Factor Yield Classes Yield Classes Yield Table Desired Basal Area Basal Area 33

33 Conclusions From testareas towards real-world data Data collection on the same quality level than the traditional surveyor, but faster No need to post process collected data in the office Available for Forest Information Systems as well as for online Solutions 34

34 Thank you! This project is supported by: 35