• DocumentCode
    576723
  • Title

    Forest mapping and monitoring in Tasmania using multi-temporal Landsat and ALOS-PALSAR data

  • Author

    Lehmann, E.A. ; Zhou, Z. -S ; Caccetta, P. ; Milne, A. ; Mitchell, A. ; Lowell, K. ; Held, A.

  • Author_Institution
    Div. of Math., Inf. & Stat., Commonwealth Sci. & Ind. Res. Organ. (CSIRO), Perth, WA, Australia
  • fYear
    2012
  • fDate
    22-27 July 2012
  • Firstpage
    6431
  • Lastpage
    6434
  • Abstract
    Developing a large-scale forest monitoring system able to take advantage of the complementary nature of optical and radar remote sensing data presents a number of technical and conceptual challenges. This paper investigates the issue of sensor interoperability in a time series of Landsat and ALOS-PALSAR data for purposes related to forest mapping and monitoring. The proposed approach relies on the processing methods developed in the frame of an existing and operational Landsat-based forest monitoring system. These methods are here applied to a PALSAR dataset within a bioregion of north-eastern Tasmania, Australia. Particular attention is given to the selection of training data in an attempt to generate results comparable to those obtained with the original Landsat-only time series, thereby allowing for a relevant assessment of interoperability. Results are presented in the form of forest maps and areal forest estimates. Despite similar gross amounts of forest extents, these results highlight differences in the forest (and change) classifications produced using different sensors. Combinations of sensors should therefore be carefully considered in light of what is required of the monitoring system.
  • Keywords
    forestry; geophysical image processing; image classification; radar imaging; remote sensing by radar; synthetic aperture radar; vegetation mapping; ALOS-PALSAR data; Australia; Landsat time series; Landsat-based forest monitoring system; PALSAR dataset; areal forest estimation; forest mapping; interoperability assessment method; large-scale forest monitoring system; multitemporal Landsat data; north-eastern Tasmania bioregion; optical remote sensing data; radar remote sensing data; Biomedical optical imaging; Earth; Noise measurement; Optical sensors; Remote sensing; Satellites; Time series analysis; Forest mapping; interoperability; multi-sensor; multi-temporal; remote sensing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
  • Conference_Location
    Munich
  • ISSN
    2153-6996
  • Print_ISBN
    978-1-4673-1160-1
  • Electronic_ISBN
    2153-6996
  • Type

    conf

  • DOI
    10.1109/IGARSS.2012.6352731
  • Filename
    6352731