Sub-pixel area estimation of European forests using NOAA-AVHRR data

Pamela Kennedy, Sten Folving, Tuomas Häme, Kaj Andersson, Seppo Väätäinen, Pauline Stenberg, Janne Sarkeala

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientific


    A map of European forests has been produced for the pan-European area. In the database, the forest area within each NOAA-AVHRR (National Oceanic and Atmospheric Administration-Advanced Very High Resolution Radiometer) pixel has been estimated. A new approach, presented in another paper at this conference was utilized in the estimation procedure. The method takes into account both the uncertainty of a pixel to belong to a specific ground class and the mixed ground contents of a spectral class. The image interpretation was carried out using an AVHRR image mosaic compiled from the red and near infra-red channels, for the entire pan-European area. This mosaic was composited from forty-nine AVHRR images acquired in late summer 1996. Atmospheric correction of the data was performed to the individual images using the SMAC (Simplified Method for Atmospheric Corrections) procedure. An additional BRDF (Bi-directional Reflectance Distribution Function) correction was made to each image. The reflectance mosaic was computed using the weighted mean of the reflectance values of cloud-free pixels. The CORINE Land Cover database was used to represent the ground information. This study fulfils some of the key objectives of the FIRS (Forest Information from Remote Sensing) Project of the Space Applications Institute (SAI) at the Joint Research Centre, Ispra, of the European Commission. In particular, the work represents an attempt to improve upon the reliability of existing mapped information for Europe. Firstly, the method results in a continuous variable of forest probability representing an estimate of forest area for each pixel. Secondly, the likelihood of under-estimating the forest cover in areas where the forest is fragmented or over-estimating if the cover is uniform and homogeneous, is reduced. Thirdly, the resulting image database could also be utilized to estimate other forest characteristics, if relevant ground data are available. Forest area statistics derived from the probability database for Italy and France were compared with area estimates taken from EUROSTAT's (Statistical Office of the European Communities) database for 1995. The correlation coefficients were found to be 0.89 and 0.85 for Italy and France respectively.
    Original languageEnglish
    Title of host publicationConference on remote sensing and forest monitoring
    Subtitle of host publicationProceedings
    PublisherEuropean Commission EC
    Number of pages12
    Publication statusPublished - 1999
    MoE publication typeNot Eligible
    EventIUFRO Conference on Remote Sensing and Forest Monitoring - Rogow, Poland
    Duration: 1 Jun 19993 Jun 1999


    ConferenceIUFRO Conference on Remote Sensing and Forest Monitoring


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