Spatial Distribution Characteristics And Activity Prediction Of Ground Fissures In Changzhi Mining Area

With the continuous development of society and economy,human has an increasing demand for natural resources.As one of the non-renewable natural resources,mineral resources have suffered from excessive exploitation.It has caused serious damage to the geological environment and affected the normal life of human beings.Because of the mining of mineral resources,the regional stratigraphic stress balance have changed on the gob area.These behavior has caused the surface subsidence,the formation of geological hazards,such as collapse and ground fissures.The ground fissures caused by underground resources exploit,which has the characteristic of wide distribution,large quantity and harmfulness.It is important that the study of the cause of formation,development and mobility prediction of ground fissures.In this paper,Geographic Information System(GIS)and artificial neural network models are used to study the spatial distribution and activity prediction of ground fractures in Huoerxinhe coal mine.First of all,we used the geological map,remote sensing images and field investigation data and related statistical data to carry out analysis of the geology environment background.And then,we obtained the terrain,physiognomy,surface water,groundwater,land use and spatial distribution of geological structure information by using Remote sensing and GIS technology.And constructed of ground fissure thematic spatial data sets.Secondly,we have analyzed and summarized the spatial distribution characteristics and rules of ground fractures in the study area.Finally,we take a research of the neotectonic movement,land use,groundwater,surface water,mining condition and the influence of formation geomorphic conditions on the ground fissures.Then we using BP(Back Propagation,a neural network model)combined with GIS technology to carried on the forecast analysis of activity of the ground fissure.Through the study,we have known the ground fissures in the study area are mainly distributed in the village and nearby areas.We have found that geological hazards,such as the area crack and subsidence have been repaired by landfill.Then,we have verified the area that there is a ground fissure before repaired by visiting the nearby villages and look up to relevant information.Meanwhile,BP neural network model and GIS technology are used to predict the activity of ground fractures.It is concluded that the ground fractures in this area mainly occur within the goaf range.It is of great practical significance to predict the activity intensity of ground fractures and provide data support for the development of mining areas and the construction of surrounding cities.