Multi-resolution time series imagery for forest disturbance and regrowth monitoring in Queensland, Australia

Awduron Sefydliadau
  • Michael Schmidt(Awdur)
    Queensland Department of Science, Information Technology, Innovation and the Arts
    The University of Queensland
  • Richard Lucas(Awdur)
    University of New South Wales
  • Pete Bunting(Awdur)
  • Jan Verbesselt(Awdur)
    Wageningen University and Research Centre
  • John Armston(Awdur)
    The University of Queensland
Math Erthygl
Iaith wreiddiolSaesneg
Tudalennau (o-i)156-168
Nifer y tudalennau13
CyfnodolynRemote Sensing of Environment
Dyddiad ar-lein cynnar04 Rhag 2014
Dangosyddion eitem ddigidol (DOIs)
StatwsCyhoeddwyd - 01 Maw 2015
Cysylltiad parhaol
Arddangos ystadegau lawrlwytho
Gweld graff cysylltiadau
Fformatau enwi


High spatio-temporal resolution optical remote sensing data provide unprecedented opportunities to monitor and detect forest disturbance and loss. To demonstrate this potential, a 12-year time series (2000 to 2011) with an 8-day interval of a 30 m spatial resolution data was generated by the use of the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) with Landsat sensor observations and Moderate Resolution Imaging Spectroradiometer (MODIS) data as input. The time series showed a close relationship over homogeneous forested and grassland sites, with r2 values of 0.99 between Landsat and the closest STARFM simulated data; and values of 0.84 and 0.94 between MODIS and STARFM. The time and magnitude of clearing and re-clearing events were estimated through a phenological breakpoint analysis, with 96.2% of the estimated breakpoints of the clearing event and 83.6% of the re-clearing event being within 40 days of the true clearing. The study highlights the benefits of using these moderate resolution data for quantifying and understanding land cover change in open forest environments.