Research And Application Of GIS Data Cloud Storage Based On MongoDB

GIS is a special spatial information system that combines geography,cartography,remote sensing and computer science.Because it can process geographical data which containing spatial information attributes,it has been widely used in many application domains such as environmental protection,resource management,and agricultural production.With the improvement of computer performance and the popularity of the Internet,GIS as a purely research type,has gradually transformed into the geographic service type.It gradually integrates into practical applications such as navigation,positioning,and route planning,and plays an important role in global issues such as land desertification,nuclear proliferation,and haze.In recent years,due to the development of information acquisition technology,geographic data has grown at PB levels,and traditional GIS storage methods have become gradually difficult to satisfy GIS requirements for data reading or writing rates,response speeds,and scalability.Cloud storage as a large-capacity,scalable,highperformance,low-cost technology can well solve these problems encountered in the current GIS,therefore the exploration and research of GIS cloud storage system will have great significance.In this paper,we conducted the investigation on the current research and development status of GIS technology both at home and abroad at first,and discussed the background and significance of GIS research.Based on systematical analysis of the bottlenecks encountered in current GIS technologies,the necessity of integrating GIS with cloud storage was pointed out.Then,combined with the current GIS storage features,we design and implement a five-server distributed cloud storage architecture by using the NoSQL type database--MongoDB.Several existing improved MongoDB data equalization algorithms are studied and their advantages and disadvantages are analyzed in detail.Furthermore,we use the thermal data recognition algorithm in Flash storage to improve the MongoDB data equalization strategy.And then,we testing the new distributed cloud storage architecture and the improved algorithm,the test results demonstrate that the feasibility and effectiveness of the framework.Finally,we adopt the full-stack development framework of Node.js and introduce leading-edge open source technologies such as Leaflet,EChart,JQuery,and Bootstrap to design and implement a GIS data storage platform.