Fractal Based Analysis Of And Distinction Between Remote Sensing Images Of Field Mapping Units

Fractal is a term which indicates all the figures and frames having the property ofself-similarity but not necessarily a definite length. Fractal theory has been frequentlyused in the field of geology since its very beginnings. It is widely used in thefollowing studies: the distribu tion of sand granularity, the aeromagneticsabnormity analysis, the rule of geochemical elements distribution, and the fractaldimension of a certain river system pattern, et al.Field mapping plays a basic role in the field of geology. Aerial remote sensingtechnique is getting developed rapidly and it has provided plentiful of remote sensingimages for field mapping. The river system of each type of rock or the assemblage ofrocks possess the character of fractal. This paper will analyses the fractal character ofimages of several mapping units and calculates their fractional dimensions and finallyacquires a new method in identifying the mapping units in field mapping of variousscales.Seven sedimental, two vocanical and one intrusive rock units have been selectedbased on their exposure conditions. When the units are decided, their topograpicdetails of river system on a 1:250000 scale remote sensing image are detected andplotted in computer. Because of the differences in rocks or rock assemblages, eachmapping unit shows diagnostic river system patterns. For this reason, it is closelyrelated between the mapping unit and its water system patterns based on the remotesensing image.Remote sensing images are loaded into CoreDraw before river systems aredetected and at the same time plotted to form a new file. ArcView GIS is used toperform the Box counting analysis to the new file. Least squares fitting of a straightline to the acquired data points are carried out in Matlab. The slop of the line iscalculated to be the Fractal dimension.The calculated fractal dimensions of nine mapping units by the box countingmethod range from 1 to 1.1. The correlation coefficients of the nine lines (R2) are allabove 0.9998, indicating a well statistical self-similarity and fractal property for thenine mapping units. Each mapping unit has its particular fractal dimension and thelater can therefore be used as a label for the former. This is particularly the case whenthe mapping unit is composed of only one rock type. Among the nine mapping units,Pleistocene Junjianshan basalt holds the lowest fractal dimension while the stratumfrom Permian has the highest. The difference in rock type or assemblage of rocks isused to explain the distinction in their fractal dimensions.This paper has established the way of extracting the lines of river system out fromthe remote sensing image for a mapping unit and the procedure of forming aacceptable file by ArcView. Fractal dimensions for the nine units are calculated usingbox counting method. The result is discussed.More reliable fractal dimensions will be obtained if more detailed and larger scaleremote sensing images are used and the conclusion will certainly be well used in thepractical field mapping of various scales.