Abstract

The aim of this study is to evaluate the capability of Land- sat TM and SPOT HRV image data to update the forest cover maps of Forillon National Park, in the Gasp6 Peninsula, eastern Canada. Our results show that Landsat TM data could provide good information on forest cover-type (evergreen, deciduous, and mixed) and defoliation caused by the spruce budworm. In contrast, SPOT HRV could not give useful information on defoliation levels. This is due mostly to the lack of spectral information (SPOT HRV having no spectral band in the middle infrared region; i.e., between 1500 and 2400 nm). The spectral content of SPOT is also limited because of the Low dynamic range of the HRVl and HRV2 digital numbers. Forillon National Park is situated at the eastern extremity of GaspCsie in the Province of QuCbec, Canada. It covers an area of 240 sq. km and forms part of the Appalachian physiographic zone and the boreal forest vegetational zone. Here the dominant species are balsam fir, white and black spruce, and white birch. This forest cover has been considerably modified since the creation of the park in 1970. In particular, an infestation by the spruce budworm during 1978 to 1982 has been responsible for the mortality of varying de- grees of severity in the balsam fir stands. Such changes require updating of the original forest inventory map, which was based on data by Grandtner et al. (l). The aim of this research is to evaluate the relative merits of Landsat TM and SPOT HRV image data for identifying and map- ping such changes in the forest cover of the park. Computer-com- patible tapes (CCT) of two satellite images were available for the analysis. Landsat 5 TM image 50873-142907 was acquired for July 22, 1986. This image was corrected geometrically by the Canada Centre for Remote Sensing (CCRS), with the conversion of the pixel resolution from 30 to 25 m, by resampling in the Mosaics format. SPOT HRV image 10502-152546 was acquired in the na- dir-viewing mode for July 8, 1987. The SPOT image was corrected geometrically in our remote sensing laboratory by using a number of easily recognized ground-control points and an appropriate quadratic function. The pixel resolution is 20 m. Both images were obtained under ideal, cloud, and haze-free atmospheric conditions.

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