Regional forest maps by combination of sample surveys and satellite image interpretation

1. Regional forest maps by combination of sample surveys and satellite image interpretation Tove Vaaje Norwegian Institute of Land Inventory Norsk institutt for jord- og skogkartlegging NIJOS

2. Regional forest maps • Needed for smaller regions • Useful for: • Area management • Resource management • Area analyses • Business purposes • Etc.

3. Østfold Kommune A county southeast in Norway This area is used because of previous studies in the area

4. Data sources • DMK – digital land use maps • DEM – digital elevation model • NFI – National forest inventory • Satellite images

5. DMK • Digital land use maps(digitalt markslagskart) • Providesinformationaboutthe land capability 

6. DEM • Digital elevation model • Can correct image values for the terrain effect • Can stratify the NFI sample plots in altitude zones

7. NFI • National forest inventory • Based on sample plots laid out in a regular grid with 3 kilometers distance between plots • Each inventory cycle is five years • The permanent plots are supplied with temporary plots

8. Satellite Images • Landsat TM images covering the reference area and the inventory area

9. Method • The method used is MSFI – Multi Source Forest Inventory • Based on three components: • A defined neighbourhood for each pixel • An algorithm that finds all the training pixels meeting the neighbourhood definition • A method to calculate an estimate based on the training pixels in the neighbourhood

10. MSFI • A fundamental assumption is that spectral similarity implies similarity in forest condition  the success of the method relies on the correlation between the spectral and biotic variables

11. Previous project • The municipality of Hobøl northwest in Østfold county • Analysed the use of MSFI using more than 1000 sample plots • A program running MSFI was developed for the Norwegian forest

12. Results of previous project • 28 different forest attributes were estimated • Satisfactory results were obtained for: • Dominant tree species • Top height • Number of conifers • Total number of trees • Mean height of young forest

13. Use of data sources (1) • Satellite images • Used for the spectral analysis • A deviated cloud mask is used to remove NFI plots covered by clouds • DMK • Forest mask • Production potential of forest

14. Use of data sources (2) • All the image files need to have the same number of rows and columns, and the same pixel size • The pixels have to be adjusted to match each other. The satellite image is used as a snap grid

15. The MSFI program • The Norwegian MSFI program, developed by Arnt Kristian Gjertsen, is started with a run control file:

16. Segmentation (1) • Segmentation is performed to make more informative and usable maps • Sequences from SkoGIS++, seg.exe and zone2vec.exe,are used • A majority variable for each zone segment is selected

17. Segmentation (2) Not segmented: Segmented:

18. Distribution • To get more information about the data, a frequency commando can be used for the wanted attributes Specific distribution of a certainmaturity class can easily be presented

19. Distribution of maturity classes

20. Results (1)

21. Results (2) • Comparison with the NFI statistics for some of the attributes:

22. Results (3) • Maturity classes, as presented, do not give a satisfying result. A new classification has to be introduced:

23. Improvementof MSFI • Issues which need to be solved in a new version of the MSFI-program: • Areas covered with clouds are classfied in the inventory area. These pixels need to be marked as clouds, and not be classified • NoData areas in the rasterdata have the value 0. This makes it possible to choose a NoData area as nearest neighbour • Areas with high altitude differences is not corrected using the DEM data