The concepts of fractals and multifractals have been increasingly applied i
n various fields of science for describing complexity and self-similarity i
n nature. Fractals and multifractals are a natural consequence of self-simi
larity resulting from scale-independent processes. In the present paper, a
theoretical investigation is developed to illustrate: (1) the characteristi
cs of multifractality as measured by the parameter tau "(q); (2) relationsh
ips between multifractality and spatial statistics including semivariogram
and autocorrelation in geostatistics, indexes used in lacunarity analysis a
nd correlation coefficients. It can be shown that these statistics primaril
y are related to multifractality as determined by tau "(1). This is an impo
rtant result because not only does it provide the link between multifractal
s and spatial statistics but it also shows that statistics based on second-
order moments are restrictive in that they only characterize a multifractal
measure around the mean value. In applications where extreme values need t
o be taken into account, the entire multifractal spectrum should be used ra
ther than local properties of the spectrum around the mean only; alternativ
ely, statistics defined on the basis of higher-order moments can be employe
d for analysis of extreme values. These theoretical results are illustrated
by means of application to Landsat TM imagery (bands 1 to 7) from the Mitc
hell-Sulphurets mineral district, northwestern British Columbia, Canada. It
is shown that variations of the TM data bands 1 to 3 in this area can be a
pproximated by fractals but for those of bands 4, 5 and 7, multifractal mod
els with different fractal spectra must be used.:The multifractality of the
se images is evaluated and several methods of spatial analysis are applied
to the dataset including a new version of principal component analysis in c
onjunction with the newly defined statistical parameters based on multifrac
tality. (C) 1999 Elsevier Science Ltd. All rights reserved.