| The brightness temperature of an object is the temperature of a black body which radiate equal energy with the object. Satellite infrared brightness temperature is calculated according to the black body radiation law using the object thermal radiation intensity data collected and recorded by on-board sensors. Since B.И.ΓΟΡΗЫЙfound the phenomena of infrared anomalies before earthquakes for the first time in 1988, many scholars have worked a lot in this field. Currently many researchers extract infrared anomalies before earthquakes by increased brightness temperature. But infrared brightness temperature is the comprehensive reflection of thermal radiation of surface factors. It is uneven in normal situations because it is influenced by non-structural factors such as seasons, elevation, latitude, vegetation, and so on. So it is unable to determine whether anomalies exist or not only according to the level of the brightness temperature on remote sensing images, let alone distinguish between structural anomalies and non-structural anomalies. Anomalies judgment must be on the base of understanding of the normal background.Therefore it is necessary and urgent to study the brightness temperature variation rules in normal situations, that is the variation law of the brightness temperature background field At present, scholars research the satellite infrared brightness temperature background field mostly on the base of individual earthquake cases, in order to extract infrared anomalies before earthquakes. To extract and highlight thermal anomalies, different authors may use very different infrared brightness temperature background fields in different earthquake cases and they don't understand its physical meaning, changes with time and space and influence factors thoroughly. It leads to confusion of analysis results and difficulties in evaluation. People have researched infrared anomalies before earthquakes for more than 10 years. Some earthquake cases and data are accumulated and a lot of problems are found. Now it's time to study the brightness temperature background field in depth. For the above-mentioned problems, this thesis makes a systematical study on the satellite infrared brightness temperature background field and its influence factors in the mainland of China. It concludes the following three main aspects.1. Distribution features of the satellite brightness temperature background field in the mainland of ChinaThis thesis chooses GMS-5 satellite images every latter half of night from July 1,2000 to June 30,2001 as data, calculates the maximal and mean values every month as the infrared brightness temperature background field in the mainland of China and takes a comparative analysis of the two kinds of the background field. The result shows that the distribution of the infrared brightness temperature background field in the mainland of China is mainly controlled by elevation and latitude. The higher latitude and the elevation are, the lower the brightness temperature is. But features of brightness temperature variation are different in different months. In January, the brightness temperature is mainly controlled by latitude. The contour line trends from east to west on the whole and the brightness temperature is higher in the south than in the north. From January to July, the brightness temperature contour line changes gradually from EW-trending to NS-trending, that is to say, the brightness temperature changes from controlled mainly by latitude to elevation. From June to August, the brightness temperature is mainly controlled by elevation and is influenced by latitude at the same time. The brightness temperature in the Tibetan plateau is the lowest. From July to January next year, the brightness temperature contour line changes from NS-trending to EW-trending, that is to say, the controlling factor of brightness temperature changes elevation to latitude. The result above shows that when extracting thermal infrared anomalies prior to earthquakes, we should avoid the illusion of brightness temperature anomalies resulted from the elevation factor as much as possible in summer and take much account of the latitude influence on brightness temperature distribution in winter.Analyzing the different value between the maximum and mean values, it can be found that in contrast with in January, the different value in July is increased noticeably in most regions especially in Xinjiang, South China and Sichuan-Yunnan. It shows that cloudy and rainy weather in summer influences a lot on brightness temperature. So the mean value should be used as the background field cautiously when analyzing satellite thermal infrared anomalies prior to earthquakes in summer.2. Relationship between the satellite infrared brightness temperature and ground elevation in the mainland of ChinaAccording to active blocks and features of brightness temperature distribution, the mainland of China is divided into 6 regions for separate research: the Northwest, the Qinghai-Tibet, the Sichuan-Yunnan, the Northeast, the Northern China and the Southern China. On the base of maximum background field analysis above, this work studies on the relationship between infrared brightness temperature and ground elevation in the 6 regions, compares it with air temperature lapse rate and discusses other influence factors of brightness temperature background field and problems that should be paid attention to in anomaly recognition.In this thesis, the decreasing infrared brightness temperature per 100m increase of the ground elevation is defined as the brightness temperature gradient. The systemic study result shows that: 1) the brightness temperature gradient of the 6 regions are all less than the air temperature lapse rate(0.64oC/100m) which was calculated based on the air temperature data and they are also less than 0.4oC/100m, from 0.15oC/100m to 0.35oC/100m in most situations. It may be the result of atmospheric absorption to ground radiation. The under-part radiation passes through thicker atmosphere than the top, so it is absorbed more. This results in the brightness temperature gradient less than the air temperature lapse rate. This result shows that satellite infrared brightness temperature sometimes differs from ground temperature. Atmosphere has a great influence on satellite infrared brightness temperature and the atmospheric impacts cannot be ignored in analysis of satellite thermal infrared anomalies before earthquakes. 2) the brightness temperature gradient in most regions is generally greater in summer than in winter. It is the result of the effect of the cold air in winter in most regions of China. 3)the general trends of brightness temperature gradient are similar between different areas except for some differences in details. 3. Relationship between the satellite infrared brightness temperature and terrestrial heat flow in the mainland of ChinaTerrestrial heat flow is a phenomenon that the heat energy in earth interior transfers to the surface. It is the most direct terrain display of the thermal effect processes in earth interior. The terrestrial heat flow value is the heat passing through per unit surface from earth interior in per unit time. This study tries to discuss the possibility and problems of observing thermal anomalies of earthquakes with satellite remote sensing technology by analyzing the relationship between thermal infrared brightness temperature and heat flow.In order to eliminate the influence of complicated geographical factors such as elevation, latitude, vegetation and so on, this work takes the different values between adjacent months in a year as the analysis object on the base of the maximum of brightness temperature every month, calculates the mean values of monthly different values in each heat flow value region(40-50,50-60,60-70,70-80,80-90 mW/m2) in each structural division (the Northwest, the Qinghai-Tibet, the Sichuan-Yunnan, the Northeast, the North China and the South China) and researches the relationship between monthly different values of brightness temperature and heat flow values. The result shows that:1) Monthly different values of brightness temperature are different in different regions. It is the highest in the Northeast and decreases in turn in the Northwest, the North China, the Qinghai-Tibet, the South China and the Sichuan-Yunnan. It reflects that seasonal temperature difference is different in different regions: it is higher in the north than south and is lowest in the wet and warm Sichuan-Yunnan.2) On the whole, monthly different values decrease with the increasing heat flow value in most regions. In regions where the heat flow value is high, brightness temperature is influenced little by air temperature and the temperature difference is low. In regions where the heat flow value is low, brightness temperature is influenced much by air temperature and the temperature difference is comparatively high. 3)As long as the thermal anomalies of earthquakes are high enough, the range is wide enough and the sky is clear, it is possible to observe the thermal anomalies by satellite infrared sensors. If the increased value of terrestrial heat flow anomalies of earthquake exceeds 100 mW?m-2,it may generate satellite infrared anomalies more than 3oC.Conclusions:(1)This thesis has studied the space-time change law of satellite infrared brightness temperature background field in the mainland of China and found that elevation and latitude affect brightness temperature differently in different seasons.(2)The concept of brightness temperature gradient has been put forward for the first time. It quantitatively describes the relationship between brightness temperature and elevation. This thesis has studied the brightness temperature gradient in different regions in the mainland of China and found that the brightness temperature gradients of the 6 regions are all less than the air temperature lapse rate and generally greater in summer than in winter.(3)This thesis has studied the relationship between brightness temperature and terrestrial heat flow for the first time, preliminarily demonstrated that it is possible to observe the earthquake thermal anomalies of wide range and high heat flow by satellite thermal infrared sensors and given a semi-quantitative result that increased brightness temperature of more than 3oC may be generated when the terrestrial heat flow increases 100 mW?m-2.Furthermore, several problems about the study are discussed.
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