| Summary: | 碩士 === 國立臺灣大學 === 森林學系 === 84 === Forest canopy closure is an important index on ecological study
and forestmanagement . Forest canopy closure is closely related
to erosion control, water and soil conservation,watershed
runoff estimation,which is also used to assess wildlife habitat
and forest biomass. In the early years, aerial photography were
usually usedto interprete forest canopy closure. However, after
the launchofLandsat-1 in 1972, using remote sensing image to
estimate forestcanopy closure is widely studied. In general,
regression analysis is used to estimate forest canopy closure.
But this method is not appropriate for highly complex
landscapes, where forest mixtures and terrain roughness may
obscure the existence of homogeneous samples. Fuzzy classific-
ation approach solves the problem of choosing homogeneous
samples . Unlike traditional classification method which is one-
pixel-one -class, thesamples of fuzzy classification are
represented by fuzzy membership grades, hence the
classification accuracy is im- proved. The study area of this
research locates at Chi-Tou, Experimental Forest of National
Taiwan University. A Landsat Thematic Mapper scene of this area
was used in the study. In thisstudy, geometric correction and
radiometric correction were done first to improve the quality
of the TM imagery. After preprocessing,seventy-two plots with a
size of 3*3 pixels were drawn from theTM imagery. Fourteen
vegetation indices including TM1、TM2、TM3、TM4、TM5、 TM7、GVI
、NDVI、R43、R54、R32、VI43、VI45、VI42 were derived from these
plots,and stepwise discriminant analysis was used to select
more important indices. Those indices were used as input data
for the fuzzy classification approach and the minimum distance
pattern classification approach to estimate forest canopy
closure , and the results of these two approaches were compared.
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