Title :
Equation-Based InSAR Data Quadtree Downsampling for Earthquake Slip Distribution Inversion
Author :
Chisheng Wang ; Xiaoli Ding ; Qingquan Li ; Mi Jiang
Author_Institution :
Shenzhen Key Lab. of Spatial Inf. Smart Sensing & Services & Key Lab. for Geo-Environ. Monitoring of Coastal Zone of the Nat. Adm. of Surveying, Shenzhen Univ., Shenzhen, China
Abstract :
Downsampling is a routine step before applying interferometric synthetic aperture radar (InSAR) data to earthquake inversion because of the high computational burden. In this letter, we make use of the matrix perturbation theory to describe the downsampling process, which is considered as matrix perturbation on inversion equation. First, we derive a formula to quantitatively assess the perturbation on the inversion solution caused by data downsampling. Next, we propose an equation-based InSAR data downsampling algorithm to better reduce the perturbation. The experiment with simulated data demonstrates that our new algorithm preserves the most details from full data inversion comparing with previous algorithms. Finally, we use our method to study the slip distribution of the 2008 Mw 6.3 Dangxiong earthquake.
Keywords :
earthquakes; geophysical signal processing; geophysical techniques; inverse problems; matrix algebra; perturbation theory; quadtrees; radar interferometry; radar signal processing; signal sampling; synthetic aperture radar; AD 2008; China; Dangxiong earthquake; downsampling process; earthquake inversion; earthquake slip distribution inversion; equation-based InSAR data downsampling algorithm; equation-based InSAR data quadtree downsampling; interferometric synthetic aperture radar data; inversion equation; inversion solution; matrix perturbation theory; perturbation reduction; Earthquakes; Equations; Global Positioning System; Green´s function methods; Noise; Noise level; Sampling methods; Earthquake inversion; interferometric synthetic aperture radar (InSAR); quadtree downsampling; slip distribution;
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
DOI :
10.1109/LGRS.2014.2318775