【摘要】 以 2 0 0 1年 11月 14日昆仑山 8 1级地震为例 ,运用月均亮温点对点差值分析法和断裂带内外亮温差值分析法 ,研究了活动断裂与震前红外异常的空间关系及发震断裂上震前卫星红外异常的时间演化过程。研究发现 :震前月平均亮温相对于 2 0 0 0年同期平均亮温的增温区沿发震断裂呈条带状分布 ;从震前 1个半月的 2 0 0 1年 10月开始 ,断裂带内外的相对温差发生明显变化 ,断裂带内的平均亮温与其外围的平均亮温差从 - 2℃增加到 1℃ ,相对增温幅度达 2～ 3℃左右 ,地震之后相对温差又回到正常状态。由此可见 ,震前卫星红外增温与东昆仑断裂带存在着明显的对应关系 ;地震前沿断裂带的红外增温大于其它地区。断裂带内外亮温差值分析法是定量研究红外增温与活动断裂的时空关系、挖掘震前增温异常的有效方法。更多还原

【Abstract】 The Kunlun M S8.1 earthquake took place on Nov. 14, 2001 in eastern Kunlun Mountains, Northwest China. Two methods are developed to extract the information of the satellite infrared anomalies prior to the earthquake. One is pixel-by-pixel analysis by subtracting the average brightness temperature 1 month before the event from the average brightness temperature in the same period in 2 000 pixel by pixel. The obtained image can be divided into two different regions: temperature increase and non-increase regions. The image shows that most regions in north Tibetan Plateau are temperature non-increase, but some temperature increase belts occur along active faults, and especially along the eastern Kunlun Fault. This temperature increase is considered to be earthquake precursor. The second method is based on the analysis of temperature difference inside and outside the fault zone. The inside region is defined as the buffer region created by GIS within 15km radius to the Hoh Sai Hu segment of the Eastern Kunlun Fault. The outside region is the buffer region in 15～30km radius to the inside region. This method is used to calculate the difference of the average brightness temperature for inside region and outside region in each night(0～8am) in 2001. The result shows that the temperature of the inside region is normally about 2℃ lower than that of the outside region. However, one and half months before the earthquake (beginning from Oct.2001),the brightness temperature of the inside region became 1℃ higher than that of the outside region. It returned to normal value after the event. The results indicate that the satellite infrared anomalies correspond spatially to the seismogenic fault. The temperature increase in the seismogenic fault belt is higher than that in the other regions. The analysis of temperature difference inside and outside the fault zone is an effective method for extracting the precursor information from satellite infrared images.更多还原