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National
Forest
Inventory

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Current events/projects
        
Use of SAR (radar) data

 Imaging spectrometry

Dynamics of biodiversity

      Finnish [Finnish]
 METLA
 METLA Research
    		
    
      


      
Application of ERS-1 data to forest inventory

      The main objectives of the study are to test the applicability of
ERS-1 SAR images together with other information sources,
in estimating forest resources in large areas, for instance
at sub-national, national or larger level and, if possible, to develop an
operative forest inventory system which utilizes SAR -data.
Six test areas
have been chosen for the study. So far, only images from 
Finnish test sites have been analysed. You can view 
the proposal of the project.

      
Objectives of the study

      
    

        
  • which variables can be estimated with SAR data, e.g. 
land use, site fertility, tree species, stem volume, 
LAI, biomass, 

        
  • what kind of changes can be estimated, e.g. clear cuttings,
deforestation, afforestation, defoliation, 

        
  • what is/are the optimum season(s), should single image or 
multitemporal  images be used, 

        
  • what is the reliability of the method in an area of the size 
          
      

            
    •  0.5  - 1 million hectares

            
    •  50 000 hectares

            
    •  10 - 100 hectares

            
    •  0.5 - 5  hectares,
          
    
          (Note that the minimum area for which
the results can be estimated reliably enough with field measurements only
in NFI
is of the  size 300 000 and with field measurements and optical data about
1000 hectares.)                           

        
  • what are the optimal parameters of HUTSCAT -instrument 
           for forest inventory,

        
  • is it possible to compensate a part of field 
 measurements with HUTSCAT measurements ?
      

      A cost-benefit analysis of the method is an essential part of the project.

      
Methods

      ERS-1 SAR images are corrupted by speckle noice. During this project
we have had a look at some speckle filters.
After speckle removal the images have to be segmented
Preprocessed images can be classified with chosen 
algorithms

      
Results

      
      
Institutes and people who are connected to the project.

      
      
 











VKan, December 2000