摘要:
利用遥感热红外和多光谱数据,分析与温泉相关的遥感解译构造,温泉出露在“*”“入”字形构造交汇部位。“*”字形构造条件更优。深入剖析与温泉相关的遥感特征,提出地表温度、羟基异常、土壤湿度、水系和高程等遥感因子。采用基于GIS的数学地质统计预测方法——证据权法、找矿信息量法和特征因子法,分析与温泉相关的地质、遥感和物探因子进行数学地质统计及预测,综合分析圈定57处地热有利区,其中A类8处、B类18处、C类31处,8个A类地热有利区中均含包已知地热点,B类有利区内打出一处51.6℃温泉,预测结果可信度较高。该方法体系可为地热预测提供新思路。
Abstract:
Based on thermal infrared and multispectral remote sensing data, this study analyzed the thermal spring-related structures interpreted from remote sensing images. Thermal springs crop out at the intersections of asterisk- and lambda-shaped structures, with asterisk-shaped structures exhibiting more favorable conditions. By delving into remote sensing characteristics related to thermal springs, this study presented remote sensing factors like surface temperature, hydroxyl anomaly, soil moisture, hydrographic net, and elevation. Using mathematical geostatistics and prediction methods based on geographical information system (GIS), including the weight of evidence, prospecting information content method, and feature factor method, this study analyzed the geological, remote sensing, and geophysical factors related to thermal springs for mathematical geostatistics and prediction. The comprehensive analysis reveals 57 favorable geothermal areas, including 8 in category A, 18 in category B, and 31 in category C. All the category-A favorable geothermal areas include known geothermal sites, and one category-B favorable area reveals a 51.6 ℃ thermal spring, suggesting reliable prediction results. The methodology of this study provides a new approach for geothermal resource prediction.
下载: