Elizabeth Roslyn McDonald, Xiaoliang Wu, Peter Caccetta & Norm Campbell
Environment Australia, 2002
The NSW Forests Taskforce within Environment Australia purchased multi-temporal Landsat Thematic Mapper (TM) data ranging in dates from 1987 through to 1999 for use in the NSW Regional Forest Agreement (RFA) process. The geometrically and radiometrically corrected multi-temporal mosaics were used to assist in mapping and updating of wilderness areas, old-growth forest and disturbance history layers. The data are also used as an information layer in a Geographical Information System (GIS) to assist in the design of reserve areas.
Much of eastern NSW contains high topographic relief. The effects of the topography, coupled with a low sun angle at the time of satellite overpass, creates significant shadowing effects in the data. These effects constrain the application of image classification techniques to further 'value-add' the data for land management purposes. A collaborative project between Environment Australia and CSIRO Mathematical and Information Sciences was set up to test the effectiveness of selected illumination corrections for reducing shadowing effects.
A number of published algorithms (Teillet et al., 1982 and Meyer et al., 1993) were tested. The application of these methods required the use of a high resolution (25 metre) Digital Elevation Model (DEM). A correction method first published by Teillet et al., (1982) and referred to by Meyer et al., (1993) as the C-correction, was found to give the best results. This correction is similar to a simple cosine illumination correction but introduces an adjusted offset derived from the regression of the digital number against the calculated sun incidence angle.
A canonical variate analysis (CVA) was used to compare results before and after application of the correction. Test areas were selected over a range of incidence angles within four major land cover classes, including eucalypt forest, exotic plantations, dry-land agriculture and irrigated agriculture. As expected, the CVA for both original and corrected data showed good separation between the major land cover classes. The CVA for the original data showed that, within the major land cover classes, particularly the high relief forest and plantation sites, variation along CV1 was related to the incidence angle. A CVA applied to the corrected data showed that CV1 predominantly separated cover classes. Further analysis of the corrected data showed that location of the sites along CV2 could be related to vegetation 'greenness'.
It was concluded that the illumination correction significantly reduced the shadowing effects in the image and can be recommended for use before classification of multi-temporal image data in eastern NSW.