Seismic Microwave Brightness Temperature Anomaly Detection Using Multitemporal Passive Microwave Satellite Images: Ideas and Limits

• Main Authors: Yuan Qi, Zelang Miao, Lixin Wu, Yifan Ding
• Format: Article
• Language: English
• Published: IEEE 2021-01-01
• Series: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
• Subjects: Microwave brightness temperature (MBT); multitemporal image; seismic anomaly; time-series analysis; uncertainty
• Online Access: https://ieeexplore.ieee.org/document/9468917/

Thermal anomalies related to large earthquakes are frequently reported, but focus on the inconsistencies and uncertainties in the uncovered results caused by the diverse method used, data used, and case studies is lacking. Taking seismic anomaly detection using passive microwave remote sensing as an example, this study revealed and illustrated the time series of microwave brightness temperature (MBT) anomaly associated with the May 2008 Wenchuan earthquake, the April 2010 Yushu earthquake, the April 2013 Lushan earthquake, and the April and May 2015 Nepal earthquake sequence. Cross comparison showed that the spatial distribution of MBT anomalies behaves differently with different background-removal methods. More regional and detailed MBT anomalies (but with weaker intensities) were obtained with higher frequency data, whereas more pronounced MBT anomalies (but with fewer details) were acquired with lower frequency data. The amplitude and spatial scales of MBT anomalies at H polarization were larger than that at V polarization. And 10.7 GHz at H polarization was recommended as the optimal band. The spatiotemporal evolutions of MBT anomalies associated with the four selected earthquake cases were compared and found to be closely related to respective earthquake preparation mechanisms. The aforementioned characteristics and uncertainties of MBT anomalies under different conditions were then discriminated and discussed based on microwave remote-sensing physics, and the applications and limitations of the present study were illustrated and analyzed. The findings of this study are of great significance for remote sensing data selection, reliability assessment, and result interpretation in seismic-anomaly research.