Geothermal Anomaly Detection Based on Evidence Theory Integrating Multi-View Remote Sensing Information
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摘要: 针对传统遥感地热探测方法存在虚假异常多、效率低等问题，提出一种证据理论融合多视角遥感信息的地热异常探测方法.基于遥感数据反演的温度信息，分别从全局、局部分块和高程分区等多视角提取温度异常.采用Dempster/Shafer证据理论方法融合上述热异常证据，实现多视角温度异常探测.最后，根据断裂构造建立缓冲区，通过分析缓冲区内及附近的热异常圈定地热范围.以山东省青岛市为例，基于Landsat-8卫星影像利用提出方法探测地热，72.7%的温度异常分布在断裂构造的1 km缓冲区内；圈定的11处地热异常，其中3处为青岛市已全部探明的地热田或地热井，验证了方法的可靠性.与传统遥感地热异常探测方法相比，提出的方法通过融合全局、局部和高程信息，消除了大量虚假异常，提高结果的精度和可靠性.Abstract: Because traditional remote sensing geothermal anomaly detection methods usually yield many false anomalies and show low detection efficiency, a method based on evidence theory integrating multi-view remote sensing information is proposed. Based on the temperature information retrieved from remote sensing data, temperature anomalies are extracted from global, local block and elevation perspectives respectively. Then, the Dempster/Shafer evidence theory method is used to fuse the above three kinds of information to realize geothermal anomaly detection from multiple perspectives. Finally, buffer zones are established according to the fault structure, and the geothermal ranges are delineated by analyzing the anomalies in the buffer zone. Taking Qingdao City of Shandong Province as the research area, the proposed method was used to detect geothermal anomalies based on Landsat-8 satellite images, and 72.7% of the anomalies were distributed within the 1 km buffer zone. Eleven geothermal anomalies are delineated, of which three are proven geothermal fields or geothermal wells in Qingdao, which verifies the reliability of the method. Compared with traditional remote sensing geothermal anomaly detection methods, the proposed method can eliminate a lot of false anomalies by fusing global, local and elevation information, and improve the accuracy and reliability of results.
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Key words:
- geothermal anomaly /
- local block /
- elevation partition /
- fault structure /
- D-S evidence theory fusion /
- geomatics
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图 2 研究区域位置和Landsat-8遥感影像
Fig. 2. Location of study area and Landsat-8 remote sensing image
图 3 Landsat-8热红外影像温度反演结果
Fig. 3. Landsat-8 thermal infrared image temperature inversion result
图 4 反演温度与MOD11A1温度产品相关性分析
Fig. 4. Correlation analysis between inversion temperature and MOD11A1 temperature product
图 5 不同方法提取的温度异常
a.全局阈值法；b.局部分块法；c.高程分区法；d.D-S融合
Fig. 5. Temperature anomalies extracted by different methods
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