Research And Implementation Of Mass Geographic Data Preprocessing Technology

With the development of geographic information technology,geographic information data has become more and more complex and huge.However,due to the limitations of computer memory size and other hardware conditions,large geographic information data cannot be opened,browsed,and retrieved quickly.Therefore,it is necessary to preprocess large-scale geographic data to support rapid operation of large-scale geographic data.In order to be able to quickly process large-scale geographic data,research is mainly conducted in the following aspects and the project is implemented.(1)In order to support the rapid opening,translation,and scaling operations of large raster data(GB~TB),an image caching method using multiple threads to read and write data was designed.Use the write thread to read the image data and store it in memory as the data cache when the image is displayed;Reading data from the data cache with a read thread;Reaching the goal of displaying images quickly and improving interaction efficiency.(2)In order to support the rapid preprocessing of large-scale raster data,a super-resolution quadtree index structure based on SRCNN is designed.Based on the feature that SRCNN can restore low-resolution images into high-resolution images,when the preprocessed files are generated,the hierarchical structure of the preprocessed files is simplified,the reading and writing of data is reduced,and the preprocessing time is accelerated.(3)In order to support the real-time display and rapid scheduling operation of large-scale vector geographic data,a large-scale vector geographic data file system based on quad-tree index is studied and designed.A vector data simplification method based on point sampling and line extraction is designed to reduce the data reading time when the image is displayed and achieve real-time data display.A quadtree index structure of vector data is designed to speed up the data indexing efficiency during image display and achieve fast data scheduling.The engineering practice proves that the algorithm and implementation scheme in this paper can efficiently access geographical data and improve the efficiency of computer processing large geographical data.