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Mapping red edge-based vegetation health indicators using Landsat TM data for Australian native vegetation cover
Authors:Ali Shamsoddini  Simitkumar Raval
Institution:1.Department of Remote Sensing and GIS,Tarbiat Modares University,Tehran,Iran;2.Australian Centre for Sustainable Mining Practices, School of Mining Engineering,University of New South Wales,Sydney,Australia
Abstract:The usefulness of red edge bands, and vegetation indices based on red edge bands, for vegetation health monitoring has already been demonstrated. There are some satellites such as WorldView-2 and Sentinel-2 acquiring images in red edge band data; while, the former data can be expensive and often lack consistent global coverage, the latter does not have a long term archive and consequently cannot be used for a long term time series analysis. This study tests the ability to predict red edge band and red edge-based vegetation indices through freely available Landsat Thematic Mapper data for an Australian Eucalyptus-dominated vegetation cover within and around a mine site. Two modelling strategies including multiple-linear regression as a linear approach and random forests as a non-linear approach were used. The results showed that it is possible to generate red edge derivatives using the Landsat Thematic Mapper data with less than 10% error using both linear and non-linear methods; however, the linear method resulted in higher estimation accuracies than non-linear methods.
Keywords:
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