Fusion of AIRSAR and MEIS data for estimating forest parameters

During the SEIDAM Project remotely sensed data from a variety of sensors were acquired over test sites in British Columbia in 1993 and 1994. Included in these data sets are multi-frequency, multi-polarization AIRSAR data, and optical data from the MEIS sensor. Ground plots were used to provide initial calibration data for forest parameters such as the estimation of timber volume from AIRSAR data. The AIRSAR data were fused with geocoded one-meter MEIS data from the Greater Victoria Watershed District test site in order to identify forest cover types and individual trees automatically. The purpose of this data fusion was to create additional calibration sites for volume estimation. This paper reports on progress on using AIRSAR and MEIS data to estimate forest parameters for largely unmanaged forest stands of Douglas fir in the Greater Victoria Watershed District (GVWD) test site on Vancouver Island, Canada, an area of high relief.