An automatic classification method of thermal anomalies before earthquakes for mutual enhancement of air-ground data

Abstract

The invention relates to an automatic classification method of thermal anomalies before earthquakes for mutual enhancement of air-ground data, which comprises the following steps: preprocessing remotesensing data to obtain brightness temperature images of infrared anomalies to be heated of regions of interest and background field images; the surface temperature data of corresponding date are obtained and processed by Kriging interpolation. Retrieval of surface temperature; the retrieved surface temperature is weighted with the actual surface temperature to obtain the equilibrium surface temperature, and each pixel value corresponding to the brightness temperature image to be extracted and the background field image is calculated to obtain the thermal infrared anomaly extraction image; theunit probability statistical information of the fault zone and the earthquake source is used as the weight constraint, and the radiation field around the fault zone is also considered as the weight constraint. The thermal infrared anomaly extraction images are processed to generate the optimized thermal infrared anomaly images before the earthquake, and the interference of other thermal infraredanomalies on the thermal infrared anomaly extraction results is eliminated. The optimized results of thermal infrared anomalies before earthquakes are divided into several grades by normal distribution.

Description

technical field [0001] The invention belongs to the technical field of geographic space information systems, and mainly relates to a method for grading pre-earthquake thermal infrared anomalies. Background technique [0002] With the rapid development of satellite thermal infrared remote sensing technology, the accuracy and reliability of thermal infrared radiation data acquisition have been improved, providing effective and reliable data support for pre-earthquake thermal infrared anomaly extraction and earthquake monitoring. Satellite thermal infrared anomaly extraction technology has become an important An important means of monitoring and forecasting. The actual satellite thermal infrared radiation data are often affected by ionospheric disturbances and instantaneous climate changes. However, the existing satellite thermal infrared anomaly extraction methods (power spectrum relative change method, offset index method, improved RST method, etc.) The average value is used...

AI Technical Summary

Problems solved by technology

[0011] In the process of extracting pre-earthquake thermal anomalies from satellite thermal infrared images, due to the constraints of surface temperature, daily temperature field, airflow real-time changes, and lack of ground data, the pre-earthquake thermal infrared anomaly extraction results often have large-scale non-earthquake anomalies , even if the effective anomaly is prone to serious problems such as deviation, the present invention introduces the balanced surface temperature into the pre-earthquake thermal infrared anomaly extraction process, and uses the difference result of the corresponding balanced surface temperature between the brightness temperature image to be extracted and the background field brightness temperature image as the weight Constraints, extract abnormal results; introduce fault zone and earthquake source information, calculate unitized earthquake probability and weight it, and weight the radiation domain at the same time, on the basis of double weight constraints, weaken the influence of atmospheric disturbance and overcome large-area irrelevance Thermal infrared radiation interference, and automatically optimize the classification of the anomaly extraction results in the previous step, and establish a scientific and reasonable automatic classification implementation plan for pre-earthquake thermal infrared anomalies

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