Change detection from satellite data time series using pixel value distributions

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


    The paper proposes a novel approach for change detection from image time series. In this approach changes are detected from evaluated distances between the (possibly multivariate) distributions of pixel values. Basing change detection on these distributions facilitates, e.g., joint analysis of images having different resolutions and comparisons of smaller areas against larger images. Furthermore, clouded areas can be excluded from each image separately, allowing the data in the remaining pixels to be utilized independent on the whether the corresponding pixels have been covered by clouds in the other images in the time series. In the paper the proposed method is applied to forest cover change detection using Landsat data covering Mexico.
    Original languageEnglish
    Title of host publicationProceedings of ESA Living Planet Symposium
    Subtitle of host publicationSeaSAR 2013
    EditorsLeny Ouwehand
    PublisherEuropean Space Agency (ESA)
    Number of pages1
    ISBN (Print)978-9-2922-1286-5
    Publication statusPublished - 2013
    MoE publication typeA4 Article in a conference publication
    EventESA Living Planet Symposium 2013 - Edinburgh, United Kingdom
    Duration: 9 Sept 201313 Sept 2013
    Conference number: ESA SP-722


    ConferenceESA Living Planet Symposium 2013
    Country/TerritoryUnited Kingdom


    • time series
    • change detection


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