Abstract:
The vegetation of a 420 square mile area of the
Oregon Coastal Mountain Range was mapped using data from
the multispectral scanner system aboard Landsat.
Advantages of this mapping system include rapid synoptic
coverage of the same geographic area at different
periods in time at a reduced cost compared to
photogrammetric mapping. The main disadvantages are the
relatively poor resolution (1.1 acres) and
classification accuracy for forest vegetation types.
This project was designed to investigate the use of
Principal Components Analysis (PCA) to combine data from
two different dates (May and late July) in an attempt to
improve classification accuracy. There were two
significant results of this study.
First, the overall classification accuracy was 7.7
percent (67.4 to 75.1 percent) higher for the July as
compared to the May overpass when only single dates were
used. This may be attributed to the stable phenological
condition of July vegetation as compared to more
variable condition in May. Spectral reflectance
constantly changes over the spring growth period and
varies greatly with changes in elevation.
Second, it was found that combining data from the
May and July overpasses using PCA resulted in an
additional increase in overall classification accuracy
by another 7.5 percent (75.1 to 82.6 percent) over the
July single date classification.
