Wspólnotowy Serwis Informacyjny Badan i Rozwoju - CORDIS

FP5

CARBO-INVENT Streszczenie raportu

Project ID: EVK2-CT-2002-00157
Źródło dofinansowania: FP5-EESD
Kraj: Austria

Carbon stock maps derived from remote sensing imagery and national forest inventory data

For mapping the local distribution of tree carbon stocks, Landsat ETM remote sensing imagery were combined with sample based field measurements from national forest inventories (NFI's). Alternatively to the NFI reference data, airborne LIDAR data acquired in parts of project areas can be used for operational applications in case that no NFI reference data is available. For classification of tree carbon stocks, the k-Nearest Neighbours Method (k-NN-method) was applied. Specific methods for pre-processing of the remote sensing data are required to optimise the classification results.

In previous studies as well as for the applications in the test sites performed within the project CarboInvent, the reported estimation errors are high at the pixel level. However, the estimation error decreases when the size of the assessment unit increases. Therefore it is recommended to aggregate the pixel based classification results to larger assessment units, e.g. at the municipality level. Compared to field assessments it is a very cost effective method for large area mapping of the local distribution of tree carbon stocks.

Kontakt

Heinz GALLAUN, (Scientist)
Tel.: +43-3168761757
Faks: +43-31687691757
Adres e-mail
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