Analyzing Method Of Thermal Information Associated With Faults Based On Thermal Infrared Remote Sensing

Faults provide the path for geothermal natural convection and partially influence the ground surface thermal environment. Recently, the distance relationship between geothermal areas and faults has been considered of great importance. Remote-sensed thermal infrared (TIR) images have been used to detect and characterise the presence and potential of geothermal anomaly areas for many years. However, geothermal anomalies are difficult to detect in TIR images because they are only slightly warmer than the ambient background temperature. Furthermore, the success of efforts has always been limited by the difficulty of differentiating between several heating effects within different surface land covers. The primary purpose of this work was to determine the applicability of a combined technique of satellite image analysis and statistics in establishing the relationship between thermal anomalies and faults. In addition, spatial pattern analysis should be improved by land cover simplification and supported by geophysical prospecting tectonic models. In this study, we devote several of the below sections to bring out an analyzing method of thermal information associated with faults based on thermal infrared remote sensing. First, we derived LSTs from the Landsat TM/ETM+ thermal bands of varying periods. Second, we attempted to employ land use/land cover classification of the LST images to eliminate noise in the form of the abnormal high temperatures caused by human-driven land cover in built-up and bare land and the abnormal low temperatures caused by water and hill shade. Then the enhanced and noise-reduced images that manifested as fragments were implemented by kriging interpolation. Third, we compared the spatial pattern of the enhanced images with geophysical prospecting tectonic profiles and with regional geological tectonic maps, and analysed the spatial correspondence between the thermal anomalies and the faults. Finally, we used the approximate width of the ranges calculated as the scales to enhance and extract the thermal anomaly associated with faults.The main progresses and results list as follows:(1) LSTs were retrieved from Landsat thermal infrared images and computed from the algorithm which defined by meteorological information, as using single-channel algorithm where contained the meteorological information or using Artis'algorithm when there was no meteorological information. Analysed the thermal infrared anomalies caused by non-structure factor, and put forward a method to eliminate them.(2) Enhance the images using improved-scale-analysing-interpolation method. Improve the sample method as mean sample to get steady surface thermal enhanced map.(3) Compared the spatial pattern of the enhanced images with geophysical prospecting tectonic profiles and with regional geological tectonic maps. Summarized the distributing rule that the thermal anomalies occurring as wave crests appeared near the faults and were located in the dip planes of the faults.(4) Analysed the spatial statistical correspondence between the thermal anomalies and the faults. Estimated the temperature anomaly-affected ranges of both sides of the faults and calculated the approximate width of the ranges, and tested by regression models to display the relationships of the temperatures and locating distances in these affected ranges. (5) Using different scale of fault thermal anomalies described as the approximate width of the fault ranges to enhance and extract the different scale fault thermal anomalies.