%0 Journal Article
%T Fault Strike Detection Using Satellite Gravity Data Decomposition by Discrete Wavelets: A Case Study from Iran
%J Journal of Sciences, Islamic Republic of Iran
%I University of Tehran
%Z 1016-1104
%A eshaghzadeh, ata
%A Dehghanpour, A.
%A kalantari, Roghayeh Alsadat
%D 2019
%\ 01/26/2019
%V 30
%N 1
%P 41-50
%! Fault Strike Detection Using Satellite Gravity Data Decomposition by Discrete Wavelets: A Case Study from Iran
%K Discrete wavelet transform (DWT)
%K Makran
%K Saravan fault
%K Satellite gravity
%R 10.22059/jsciences.2019.69631
%X Estimating the gravity anomaly causative bodies boundary can facilitate the gravity field interpretation. In this paper, 2D discrete wavelet transform (DWT) is employed as a method to delineate the boundary of the gravity anomaly sources. Hence, the GRACEâ€™ satellite gravity data is decomposed using DWT. DWT decomposites a single approximation coefficients into four distinct components: the approximation, horizontal, vertical and diagonal. For evaluating the efficiency of wavelets, both the noisy and free-noise synthetic gravity data, have been decomposed at level 1 with six discrete two-dimensional wavelets. In this manuscript, the satellite gravity data of a part of the Makran region (in the south-east of Iran) is decomposed by DWT in order to detect the Saravan Fault trend. The outcome indicates the acceptable performance of the Haar and Biorthogonal mother wavelets in detecting the edges of the real and synthetic gravity anomaly sources. Also, the results demonstrate that the satellite gravity data can be appropriate to study the regional geological structures, particular in revealing the hidden faults where have great importance in earthquake risk analysis.
%U https://jsciences.ut.ac.ir/article_69631_0201cd22fc676d52170a29e57c575c5a.pdf