Data Quality and the Detection of Woody Vegetation
Elizabeth Farmer*, Karin J. Reinke, Alex M. Lechner and Simon D. Jones
School of Mathematical and Geospatial Sciences RMIT University Melbourne, Australia
Abstract: This paper presents preliminary work into the data quality of a series of woody vegetation presence maps of differing spatial resolutions. The correspondence between two differing map products is compared. The non-woody/woody map products considered were derived from medium resolution satellite imagery, including the SPOT and Landsat satellites, and produced by government agencies at a national and regional scale. These 'off-the-shelf products are routinely utilised in environmental, conservation and landscape management. Whilst metadata and data quality statements exist for these map products, localised error in terms of the detection of small patches of woody vegetation remains largely unquantified and poorly understood by users. This work describes and quantifies differences in mapped woody vegetation extent as a consequence of remote sensing data product. Localised errors are compared to landscape scale error estimates, and the implications for the delineation of small woody vegetation patches are discussed. Small patches of remnant woody vegetation have recognised ecological and conservational importance in terms of the ecosystem services they offer. Consequently, there is a distinct need to map and monitor these critical ecological structures. It is in this context that remote sensing technologies, due to their spatial coverage and synoptic view of landscape structure, are increasingly being utilised to provide assessments of woody vegetation extent. The ability of remote sensing technologies coupled with standard processing methods to accurately map and characterise small patches of woody vegetation needs to be understood in order for users of this information to achieve best practice in environmental and conservation management. Previous research (Farmer et al., in review) has indicated that the minimum mapping unit of remote sensing derived map products is significantly greater than a single pixel when considering small, discrete patches of woody vegetation. As a result small patches of woody vegetation are under-represented by up to 40% in current methods of vegetation mapping. The magnitude of these localised errors and their implications for landscape scale estimates of woody vegetation cover are demonstrated to be a consequence of map product and landscape structure, in particular landscape fragmentation and the associated patch size distribution.
Keywords: Fitness for purpose, Landscape structure, Scale, Spatial resolution, Woody vegetation, Extent