Geothermal anomaly detection method based on evidence theory fused with multi-view remote sensing information

Abstract

The invention provides a geothermal anomaly detection method by fusing an evidence theory with multi-view remote sensing information. The geothermal anomaly detection method fusing the evidence theory with the multi-view remote sensing information comprises the following steps: firstly, performing inversion by using a single window algorithm to obtain temperature information in an area, and verifying the precision of an inversion result by combining an MOD11A1 temperature product in the same period; from three perspectives of global, local and elevation, temperature anomaly is extracted by using three methods of a global threshold, a local partitioning threshold and an elevation partitioning threshold, and then four evidence theory elements are fused by adopting a D-S evidence theory method based on a geological fracture structure buffer area, so that the range of geothermal anomaly is delineated; and the reliability of the result is verified in combination with known geothermal fields and geothermal wells in the area. According to the method, false extraction caused by local and surface fluctuation and other factors can be effectively reduced, the terrestrial heat identification precision is improved, and powerful technical support is provided for development and utilization of terrestrial heat energy.

Description

technical field [0001] The invention relates to the technical field of remote sensing, in particular to a method for detecting geothermal anomalies by integrating multi-angle remote sensing information with evidence theory. Background technique [0002] my country's geothermal resources have large reserves, low pollution, and low cost. They are cheap energy that the earth bestows on human beings. Thermal infrared remote sensing technology is usually used to detect geothermal anomalies, but the occurrence of geothermal anomalies is affected by many factors. For some geothermal areas with large research areas and low-to-medium temperature in the area, only the "average value + 1* standard" is used. "Difference" or "mean + 2*standard deviation" global threshold method or combining geological structure and other features to extract temperature anomalies may ignore some relatively high local anomalies, and will be affected by factors such as surface fluctuations, resulting in man...

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Problems solved by technology

Thermal infrared remote sensing technology is usually used to detect geothermal anomalies, but the occurrence of geothermal anomalies is affected by many factors. For some geothermal areas with large research areas and low-to-medium temperature in the area, only the "average value + 1* standard" is used. "Difference" or "mean + 2*standard deviation" global threshold method or combining geological structure and other features to extract temperature anomalies may ignore some relatively high local anomalies, and will be affected by factors such as surface fluctuations, resulting in many false anomalies , making the detection results inaccurate

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