Web Cameras In Automatic Autumn Colour Monitoring

Heikki Astola, Matthieu Molinier, Tapani Mikkola, Eero Kubin

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    6 Citations (Scopus)


    The objective of ForSe - Season Monitoring study was to develop an automatic method to analyze web-camera images of nature. As the outcome the image analysis produces indices that indicate the seasonal development stage of the forest (e.g. degree of autumn colour of deciduous trees). IP web-cameras of a pilot camera network were programmed to take one image in 15 minute interval on daylight hours during autumn period. One camera was used as a source of the training data (Enontekiö), and one for testing data (Oulanka). The image data was preprocessed to reduce noise and to and spectral angle feature was calculated to compensate the illumination variations between consequential images and within a single image. Selected areas of the training site camera images of autumn season were classified into six classes describing the seasonal status of the leaves (green, light green, yellow, red, brown, fallen). The spectral angle features were calculated for these areas and clustered by K-means into 30 clusters. Class labels were assigned to the cluster centres using k-NN method (k=5). To see the progress of a certain colour class in the time series of images of a test site camera, the classified pixels within selected regions of interest (ROI) were used to produce a continuous season colour index (SCI). The behaviour of the index was compared with a reference classification supplied by phenology experts from Finnish Forest Research Institute (Metla). The results were well in line with the reference classification, and show that the implemented processing chain can be used to obtain a numerical index describing the seasonal status of deciduous leaves' colour.
    Original languageEnglish
    Title of host publicationProceedings of 2008 IEEE International Conference on Geoscience and Remote Sensing Symposium, IGARSS 2008
    PublisherIEEE Institute of Electrical and Electronic Engineers
    ISBN (Print)978-1-4244-2807-6, 978-1-4244-2808-3
    Publication statusPublished - 2008
    MoE publication typeA4 Article in a conference publication
    Event2008 IEEE International Geoscience and Remote Sensing Symposium - Boston, United States
    Duration: 6 Jul 200811 Jul 2008


    Conference2008 IEEE International Geoscience and Remote Sensing Symposium
    Abbreviated titleIGARSS 2008
    Country/TerritoryUnited States


    • change detection
    • SAR
    • dual-polarisation
    • TerraSAR-X
    • clearcuts


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