For mapping multiple vegetation types at large scale, determining appropria
te plot size and spatial resolution is very important. However, this can be
difficult because of spectral mixtures, low correlation of remote sensing
and field data, and high cost to collect field data at a high density. This
paper presents a method to determine appropriate plot size and spatial res
olution for mapping multiple vegetation types using remote sensing data for
a large area. This method is based on field data and gee-statistics theory
. The method accounts simultaneously for within-support and regional spatia
l variability by modeling both within-support and regional semi-variograms.
The range parameters of the within-support semi-variograms implied the max
imum range of the appropriate plot sizes. Using tile regional semi-variogra
ms, the support size was considered appropriate when the ratio of the nugge
t variance to sill variance stabilized. The method is assessed using field
data and satellite TM data by developing the semi-variograms by vegetation
type and TM band; and by cross validation of vegetation classification. A p
ossible improvement for remote sensing to aid mapping is suggested.