A new semi-automatic seamless cloud-free Landsat mosaicing approach tracks forest change over large extents

Samuel Hislop, Simon Jones, Mariela Soto-Berelov, Andrew Skidmore, Andrew Haywood, Trung H. Nguyen

    Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

    1 Citation (Scopus)

    Abstract

    The extensive and freely available archive of Landsat satellite data is used throughout the world to assess forest changes over large areas and long time periods (30-40 years). But analyzing Landsat data in time-series is not free of challenges (e.g. data processing and storage capabilities, dealing with cloud cover and other data gaps, and accounting for changes in illumination conditions due to atmospheric effects, sun angle and vegetation phenology). In this research, we present a method used to create annual seamless cloud-free mosaics for the entire state of Victoria, Australia (19 Landsat tiles), for a 30 year period. These mosaics were created by first constructing yearly Best Available Pixel (BAP) composites from over 3000 individual scenes. Then, forested areas were analyzed in time-series to determine breakpoints (e.g. a disturbance event such as fire). Following this, the breakpoints were used to fit a piece-wise linear regression model through each pixel's temporal trajectory. In this way, data gaps and other radiometric anomalies were removed. These gap-free composites can be used by a variety of stakeholders for land management, statutory reporting and decision making activities. This ensures state-wide consistency, and offers significant savings in processing and storage requirements.

    Original languageEnglish
    Title of host publication2018 IEEE International Geoscience and Remote Sensing Symposium
    Subtitle of host publicationproceedings
    Place of PublicationPiscataway, New Jersey
    PublisherInstitute of Electrical and Electronics Engineers (IEEE)
    Pages4954-4957
    Number of pages4
    ISBN (Electronic)9781538671504, 9781538671498
    ISBN (Print)9781538671511
    DOIs
    Publication statusPublished - 2018
    Event38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Valencia, Spain
    Duration: 22 Jul 201827 Jul 2018

    Conference

    Conference38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018
    CountrySpain
    CityValencia
    Period22/07/1827/07/18

    Keywords

    • Compositing
    • Landsat
    • Time Series

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  • Cite this

    Hislop, S., Jones, S., Soto-Berelov, M., Skidmore, A., Haywood, A., & Nguyen, T. H. (2018). A new semi-automatic seamless cloud-free Landsat mosaicing approach tracks forest change over large extents. In 2018 IEEE International Geoscience and Remote Sensing Symposium: proceedings (pp. 4954-4957). [8518009] Piscataway, New Jersey: Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/IGARSS.2018.8518009