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FP5

CARBO-INVENT Report Summary

Project ID: EVK2-CT-2002-00157
Funded under: FP5-EESD
Country: Austria

Forest type maps derived from remote sensing imagery

Within the project CarboInvent, the forest type maps were used to reduce the sampling error for the estimation of stem volume, tree biomass and carbon stocks for large areas by stratification. This method is especially relevant when estimates at the national level have to be performed e.g. for Kyoto Protocol reporting, where a high estimation accuracy is required. To derive the required strata, a supervised maximum likelihood classification and an unsupervised k-means classification was performed.

As the results have shown, both methods have a high potential for reduction of the sampling error when the classification results are used in combination with field measurements from National forest inventories for stratification. E.g., the sampling error of the tree carbon stock estimates could be reduced to one third by integration of the forest type maps. Compared to the field assessments, the application of the remote sensing methods can be achieved at very low cost. The integration of forest type maps for large area estimation of forest parameters by stratification is therefore recommended.

Reported by

Joanneum Research, DIB
Wastiangasse 6
8010 Graz
Austria
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