Abstract for presentation at The 13th Australasian Remote Sensing and Photogrammetry Conference

Impact of spatial resolution on the recovery of vegetation cover estimations from remotely sensed data

  • Kathryn Sheffield, School of Mathematical and Geospatial Sciences, RMIT University, Melbourne, Australia
  • Dr Simon Jones, School of Mathematical and Geospatial Sciences, RMIT University, Melbourne, Australia
  • Dr Andre Zerger, CSIRO Sustainable Ecosystems, Canberra, Australia
  • Dr Phil Gibbons, Department of Environment and Conservation, New South Wales, Australia

    • This paper compares canopy cover estimations derived from four different sensors at six different spatial scales. A case study was undertaken in southern New South Wales in the Albury-Holbrook area, targeting woodland vegetation communities. Standard methodologies, employed in Victoria and New South Wales to create woody vegetation canopy cover maps, were used. These methods were compared using data derived from commercially available satellite sensing systems including Landsat-5 TM, SPOT-5 and Ikonos, and, an aircraft mounted digital camera (DuncanTech 4100) flown at three operating heights. This yielded six datasets at the following spatial resolutions: 25cm, 50cm, 1m, 4m, 10m and 25m. Spectral wavelengths utilised include red, green and near infrared bands. Consideration was given to the different radiometric and spectral resolutions of the datasets, in addition to registration errors implicit in using imagery acquired from several platforms.
    Ground data was also collected across the study area. The field protocol used to collect ground data was designed with respect to the spatial variation of vegetation and the spatial resolution of remotely sensed data. The size of each site and the location of measurements recorded within each site were determined by the spatial resolution of remote sensing imagery utilised. The use of remotely sensed data with a range of spatial resolutions resulted in a hierarchical sampling design, enabling target attributes to be characterised across different spatial areas.
    A key objective of the project is to optimize the integration of a suite of data sets including ground data, aerial photography, and high- and medium-resolution satellite remote sensing data. An important outcome of this work is an analysis of optimal spatial scale for mapping canopy cover estimations in this landscape.

    Conference Organiser - ICMS Pty Ltd