Research On Remote Sensing Survey Of Mining Area And Estimation Of Soil Erosion In Liaoning Province

Liaoning province has a complex geological structure and rich mineral resources.It is a famous heavy industry base in China.The long history of mining and the increasing number of engineering construction projects have also caused many ecological and environmental problems such as soil erosion as well as economic development,and even seriously threaten the lives and property of the people.In the past decade,the state has vigorously strengthened the supervision and management of soil and water conservation in production and construction projects such as mining development,and at the same time,it has also paid more and more attention to the planning,management,and ecological restoration of mining areas,and has vigorously promoted the research and application of spatial information technology in this field.The acquisition of mining area information is the prerequisite for the estimation of soil erosion and the supervision of production and construction projects,while the estimation of soil erosion in the mining area is the basic work of strengthening the supervision of soil and water conservation in the mining area,the planning management and ecological restoration of mining area.Therefore,it is necessary to gradually solve the scientific problems existing in the mining area information extraction,the estimation of the soil erosion in the mining area and the supervision of production construction projects,so as to lay the foundation for rational planning and ecological management in mining area,while promoting the scientific development of the supervision mode of the production construction project.First of all,in order to solve the problems such as heavy workload,low efficiency,and lack of accuracy in the remote sensing survey of mining areas under the current technical conditions,this paper conducts a technical and theoretical research based on remote sensing data.Based on the multi-spectral images and DEM data,the characteristic indicators that have significant differences between the mine construction land and other land features were selected to participate in the mining area identification.This method has been applied in Nanfen District to obtain more satisfactory extraction results from the mining area,which effectively improves the recognition accuracy and the computational efficiency of the classifier.It has reliability and good practicality,and can meet the needs of mine land area information extraction.At the same time,the image features of mine features are analyzed and the logical relationship of remote sensing image recognition is established.The spatial structure elements of mining targets and the multi-objective combination relationship feature identification mark are constructed,which further enhances the accuracy of mine development land occupation information extraction.And efficiency.The above studies provide technical support for the acquisition of mine land occupation information in planning and supervision of mining areas.Based on this research,the information of mining area mining in Liaoning Province was extracted,and then the soil erosion estimates for the mining areas of Liaoning Province were calculated using the grading standard and the general soil loss equation respectively.The differences in erosion intensity under different methods and their accuracy were explored,in order to provide prospective and necessary basic data for the future planning of the water and soil conservation,ecological restoration,and scientific supervision of the mining area.Through comparison of different estimation results,it can be seen that the grade of erosion intensity obtained by using the classification standard is generally lower than the grade estimated by the general soil loss equation,and the general soil loss equation is more suitable for the estimation of soil erosion in the mining area.The paper applies the extraction results of the mining area to the supervision of the "Sky-Earth Integration" in the emerging production and construction project,and uses Qianshan District as a pilot point for the exploratory application of the regulatory model.Accurately acquired the disturbance status,quantity,distribution and dynamic changes of production and construction projects.Effectively verified the reliability and practicality of the regulatory technology,and discussed the key technologies and scientific issues involved in the regulatory approach,laying the foundation for better promotion to the provincial production and construction project supervision in the future.The innovation of the thesis is to propose a comprehensive multi-feature indicator mining area identification method based on multi-spectral images and DEM data,extracting indicators with specific significance in vegetation,geology,and topography,and screening out indicators with significant differences in mining areas and non-mining areas,and select the indicators with significant differences between the mining area and the non-mining area as the optimal band combination for identifying the mining area,in order to solve the problem of redundancy of data information and resulting in excessive computation,the practice has proved that this method can improve the efficiency and accuracy of mining area identification,and provides new ideas for the development of mining area information extraction technology.