Geothermal abnormal region extraction method based on multi-scale information fusion

Abstract

The invention discloses a geothermal abnormal region extraction method based on multi-scale information fusion, and the method comprises the steps: firstly improving the spatial resolution of a thermal infrared band in a satellite image through employing a full-constraint least square mixed pixel decomposition and sub-pixel spatial gravity model, and carrying out the inversion through employing a single-window algorithm, and obtaining high-resolution temperature information; comprehensively extracting temperature anomaly in the research area from global and local angles, delineating a geothermal anomaly range by combining geological data and known priori knowledge, and verifying the reliability of the result according to a plurality of known hot spring positions by expanding the research area; and finally, using high-resolution unmanned aerial vehicle data to further perform fine extraction in some typical terrestrial heat abnormal areas such as known hot spring positions and the like. According to the method, coarse-to-fine geothermal anomaly extraction is realized, a reference value is provided for later manual exploitation, and full utilization of resources is realized.

Description

technical field [0001] The invention relates to the field of remote sensing, in particular to a method for detecting multiple geothermal anomalies in remote sensing images, and in particular to a method for delineating multi-scale geothermal anomalies from coarse to fine based on satellite images and UAV images. Background technique [0002] Geothermal energy is a cheap energy source endowed by the earth to human beings. An effective method for regional geothermal surveys is thermal infrared remote sensing. Therefore, thermal infrared remote sensing data are often used to extract geothermal anomalies. The traditional method is to use geophysical and chemical prospecting for geothermal detection, but this method is time-consuming, laborious and inefficient. Later, due to the deepening of the research on remote sensing technology, a variety of algorithms for obtaining surface temperature using thermal infrared remote sensing data were developed. Therefore, the method of combi...

AI Technical Summary

Problems solved by technology

The most commonly used method for extracting temperature anomalies is the global threshold. Although this method is simple and fast, it may ignore some local high temperature anomalies and cause some geothermal anomalies to be missed.

After extracting temperature anomalies, geological faults and known prior knowledge are often combined to determine the final geothermal area, because geothermal heat is often distributed along the fault line, but it lacks higher-resolution thermal infrared data for verification, and for Refined extraction of some typical exceptions

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