Spectral Analysis of Geophysical Data - Advances in Data, Methods, Models and Their Applications in Geoscience - page 51

4 o

1.00E+007

(a)

1.00E+006

1.00E+005

(b)

1.00E+004

1.00E+003

1.00E+002

1.00E+001

1.00E+006

4 o

1.00E+005

12 o

(c)

1.00E+004

157 o

149 o

1.00E+003

1.00E+002

1.00E+001

0 40 80 120 160 200

Angle (deg)

(B)
Fig. 6. Angular spectrum of the total field magnetic anomaly over (A) the upper sub-area
and (B) the lower sub-area of the Middle Benue Trough, Nigeria. In each of the curves, the
labels represent as follows: (a) the low frequency band (1-20), (b) the mid-frequency band
(20-40) and (c) the high frequency band (40-60).

7. Conclusion
Spectrum analysis is a basic tool in signal processing and shows how the signal power is
distributed as a function of spatial frequencies. These Fourier-based methods have found
usefulness in the analysis of geophysical data and what has been presented in this chapter is
just tip of the iceberg. It is important as a rule to have a good understanding of the signal
and the corrupting noise. This will lead to a successful extraction of the desired signal from
the observed map data. Parameter estimation from such processes have to be carefully done
as some operations involved in the processes bear on the resultant data. For example, the
effect of the window function bears to some extent on the final outcomes of the
computations of angular spectra of both the synthetic and real aeromagnetic field data used
in the last section. The window effects must be recognized and pointed out.