Refining Pre-Seismic Thermal Anomaly Detection from MODIS Data with Standard Deviation Thresholds and RETIRA Model

Author:

Wongpornchai Pisanu1,Suwanprasit Chanida1

Affiliation:

1. Chiang Mai University

Abstract

Abstract

Earthquakes arise from tectonic plate movements and seismic waves, profoundly affecting populations and infrastructure. Remote sensing technologies are invaluable for investigating these phenomena by monitoring the earth surface processes. This study examines pre-seismic thermal anomalies preceding a 4.9 Mw earthquake on February 20, 2019, in Wang Nuea district, Lampang province, Thailand. The Moderate Resolution Imaging Spectroradiometer (MODIS) and applied standard deviation thresholds along with the Robust Estimator of Thermal Infrared Anomalies (RETIRA) index were integrated. Anomalies were categorized based on standard deviation thresholds: normal (≤ 1.0 S.D.), moderate (1.5 S.D.), significant (2.0 S.D.), high (2.5 S.D.), and extreme (≥ 3.0 S.D.). Our findings revealed significant temperature increases near fault lines and lineament structures over the eight days before the earthquake, normalizing post-event. The average temperature elevation was 2.968°C above the pixel-wise mean temperature. A targeted survey of 13 locations identified that 23.08% were along faults or lineaments, 69.23% were devoid of such features, and 7.69% yielded indeterminate results. Non-fault areas, typically dynamic farmlands, were also associated with thermal anomalies. These insights underscore the utility of remote sensing in earthquake studies and its potential to enhance disaster readiness and mitigation efforts.

Publisher

Research Square Platform LLC

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