Research And Application Of Two-dimensional Map Simplification And Layout Optimization Algorithm

Visualization technology,as a new data analysis technology under the background of contemporary big data,provides an intuitive and clear way to display the process and results of data analysis.Spatial data visualization is an important part of information visualization,and map is one of the most commonly used carriers for spatial data visualization.As one of the most frequently used and indispensable tools in daily life,maps have many functions such as information transmission function,information load function,simulation function and cognitive function.Because of the powerful functions of the map itself,it plays an important role in planning management,military command,transportation,science education and other fields.Traditional maps have various forms,and the information contained in the maps is also complex.Ordinary people need to spend a lot of time to get the information they want.We can generate simplified maps similar to traditional maps,thereby improving the efficiency and accuracy of spatial data analysis and visual viewing by researchers and ordinary people.However,the production of traditional reconstructed maps requires manual drawing by professional cartographers in combination with their own experience and actual geographic information data.This traditional cartographic process of obtaining reconstructed maps is cumbersome.The reconstructed map generated by the automatic map reconstruction method is slightly insufficient in terms of simplification,deformation,and layout,and cannot well retain the structural information and domain relationships of the actual map.These factors will affect the final visualization of the reconstructed map.Through practical analysis and investigation,we proposed a two-dimensional map simplification and layout optimization algorithm.The main steps of the research process in this article are as follows:(1)In order to reduce the amount of data and achieve the purpose of data simplification,we extract the geographic boundary data that is most relevant to geographic boundary simplification from the original geographic information data with a large amount of data according to actual needs.Then we use the Visvalingam-Whyatt algorithm to simplify the data of the geographic boundary data to reduce the amount of data describing the points of the geographic boundary.(2)In order to standardize the shape of the boundary of the geographic boundary,after simplifying the geographic boundary data,we need to normalize the data.By straightening the lines of the geographic boundary;straightening the corners of the geographic boundary;and then denoising the geographic boundary data,we can standardize the graphic boundaries of the simplified map and eliminate boundary redundancy.(3)In order to obtain the optimal layout effect,we can transform the layout optimization problem into a quadratic optimization problem based on the simplification and normalization of geographic boundary data,and by setting up an objective function and finding corresponding constraints.After synchronizing the objective function and constraints,we can get a quadratic optimization equations.Finally,we use the Mosek mathematical solver to solve the quadratic optimization equations to obtain the optimal layout results.(4)In order to demonstrate the algorithm,we use the Vue.js framework and related component libraries to build an algorithm front-end visualization system to display the map before and after reconstruction.We use Echarts.js to visualize the data comparison between the reconstructed map and the actual map in terms of area size and area similarity.In this paper,we have carried out experimental tests on multiple samples and compared them with existing algorithms in terms of domain relationship similarity and regional topology consistency.In addition,we conducted user surveys in the form of questionnaires.Through comprehensive analysis of objective experimental results and subjective user experience,the effectiveness of the proposed algorithm is verified.