Dynamic simulation for the process of mining subsidence based on cellular automata model

Open Geosciences

Li Jiye¹  Chen Qiuji¹  Hou Enke² 

[1] Department of Geography, College of Geomatics, Xi’an University of Science and Technology, Xi’an, 710054, People’s Republic of China;Department of Geology, College of Geology and Environment, Xi’an University of Science and Technology, Xi’an, 710054, People’s Republic of China;

关键词: mining subsidence;    cellular automata;    dynamic reclamation;    geographic information system;   

DOI  :  10.1515/geo-2020-0172

来源: DOAJ

【 摘 要 】

Under the background of the ecological civilization era, rapidly obtaining coal mining information, timely assessing the ecological environmental impacts, and drafting different management and protection measures in advance to enhance the capacity of green mine construction have become the urgent technical problems to be solved at present. Simulating and analyzing mining subsidence is the foundation for a land reclamation plan. The Cellular Automata (CA) model provides a new tool for simulating the evolution of mining subsidence. This paper takes a mine in East China as a research area, analyses the methods and measures for developing a model of mining subsidence based on the theories of CA and mining technology, then discusses the results of simulation from different aspects. Through comparative analysis, it can be found that the predicted result is well consonant with the observation data. The CA model can simulate complex systems. The system of mining subsidence evolution CA is developed with the support of ArcGIS and Python, which can help to realize data management, visualization, and spatial analysis. The dynamic evolution of subsidence provides a basis for constructing a reclamation program. The research results show that the research methods and techniques adopted in this paper are feasible for the dynamic mining subsidence, and the work will continue to do in the future to help the construction of ecological civilization in mining areas.

【 授权许可】

Unknown