author =    {E. Lehmann and Z.-S. Zhou and P. Caccetta and A. Mitchell and A. Milne and K. Lowell and S. McNeill},
  title =     {Combined Analysis of Optical and SAR Remote Sensing Data for Forest Mapping and Monitoring},
  booktitle = {7th International Symposium on Digital Earth (ISDE7)},
  pages =     {},
  month =     {August},
  year =      {2011},
  address =   {Perth, Australia},
  abstract =  {Jointly processing remote sensing (RS) data acquired by sensors operating at different wavelengths offers the potential to significantly improve the operation of global forest mapping and monitoring systems. This paper presents an analysis of the forest discrimination properties of optical imagery (Landsat TM) and synthetic aperture radar (SAR) data acquired at L-band (ALOS-PALSAR) and C-band (RADARSAT-2), when considered either separately or as a combined source of information. This pilot study is carried out over a test site in north-eastern Tasmania, Australia. Canonical variate analysis, a directed discriminant technique, is used to investigate the separability of a number of training sites, which are subsequently used to define spectral classes for maximum likelihood classification. An accuracy assessment of the forest classification results is provided on the basis of independent validation data. A variable selection is also performed, producing quantitative metrics on the degree of land cover separation provided by various combinations of the SAR and optical bands. The experimental results highlight the advantages of combining multi-sensor RS data for purposes such as natural resources and land management, environmental assessment, and carbon accounting.}