Compilation of a European forest map from Portugal to the Ural mountains based on earth observation data and forest statistics

A. Schuck (Corresponding Author), R. Päivinen, Tuomas Häme, J. Van Brusselen, P. Kennedy, S. Folving

    Research output: Contribution to journalArticleScientificpeer-review

    33 Citations (Scopus)

    Abstract

    This article focuses on the approach of combining the information from both remote sensing and forest inventory statistics in order to produce a European forest proportion map covering the area from Portugal to the Ural mountains. For this purpose, a calibration method was developed, tested and applied to the pan-European area. The resulting forest map was analysed on a pixel-by-pixel basis and given to inventory and remote sensing experts for consultation. When comparing both the result of the calibrated forest map with that of the original AVHRR mosaic of the area it was found that the satellite-derived estimates of forest area closely matched the ground inventory statistics indicating the high accuracy obtained from the AVHRR mosaic alone. Most visible discrepancies were found in northern Europe where the inventory data showed less forest than the image data. In southern Europe, the inventory data displayed more forest than the AVHRR image. This project was carried out for the European Commission, Joint Research Centre in 1999/2000 (contract no. 17223-2000-12 F1SC ISP FI) mainly by the European Forest Institute and VTT Information Technology.
    Original languageEnglish
    Pages (from-to)187-202
    Number of pages6
    JournalForest Policy and Economics
    Volume5
    Issue number2
    DOIs
    Publication statusPublished - 2003
    MoE publication typeA1 Journal article-refereed
    Event10th Annual Conference of the EFI - Joensuu, Finland
    Duration: 28 Aug 200328 Aug 2003

    Keywords

    • European forest map
    • earth observation
    • forest inventory
    • forests
    • forest inventory statistics
    • calibration method
    • calibration
    • timberline masking
    • remote sensing

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