Design And Implementation Of GIS Visual Analysis Platform Based On Hadoop

With the advent of the Internet era,data has become an indispensable part of more and more fields,and its role has become more and more important.Spatio-temporal data has begun to infiltrate our production and living areas,and plays an important role.This article analyzes and visualizes business spatio-temporal data according to actual needs.It adopts GIS,spatio-temporal data management and data visualization techniques,and details the process of data storage,management and GIS visual analysis in the visual analysis platform.In this paper,by comparing the development status of visual analysis platforms at home and abroad,this visual analysis platform is designed according to the actual application scenario requirements combined with spatio-temporal data management,big data analysis and GIS and other cutting-edge technologies.This article details the relevant theories and technical solutions used by the platform.Subsequently,this article analyzes the needs of the entire visualization platform and divides the platform into different functional modules.This article selects five important modules: the board management module,the base map design module,the business data module,the spatial analysis module,and the spatiotemporal analysis module,and introduces the non-functional requirements of the platform.Secondly,this article divides the platform into different functional modules and describes the functional structure,architectural design and data storage design of the platform.Integrate the distributed framework of Hadoop in Web GIS,use Hbase to manage and store spatio-temporal data,perform statistical analysis on the data through Map Reduce mode,and use the Mapbox framework for data rendering to achieve a visual analysis platform.At the same time,this article details the use of Mapbox for map rendering and drawing,and describes the Geo Hash algorithm in detail,and establishes a spatial data indexing mechanism and a spatiotemporal indexing mechanism to achieve rapid positioning and improve system computing efficiency.In addition,the spatial query and spatial-temporal query algorithms used on this platform are introduced to improve and increase the data query speed.Finally,this article summarizes the project,expounds the deficiencies in the project,and also makes a prospect for the future development of the platform.