Research On Key Technology Of Spatial-temporal Data Cloud Storage In Heihe River Basin Based On MongoDB Database

With the rapid growth of population and economic development in semi-arid and arid regions of northwest China, regional water shortage is getting worse. Water crisis has become an important factor that restricts the social and economic sustainable development and we must face this challenge. In order to address a variety of water environment and water ecological problems, acquiring and using the information of hydrology is essential to reveal the physical mechanism of hydrological processes and rational planning of water resources. Nowadays, with the development of hydrological observation technologies, hydrology has changed from a traditional sense of scarcity data science into a readable data-rich science. Facing multi-source, a large amount of spatial-temporal observation data, how to manage, classify extract, analyze and visualize a diverse range of these data has become an urgent need for the development of hydrology problems.Nowadays,with the widely used of Web 2.0 technology and mobile internet technology, a large number of non-relational, distributed storage types of No SQL databases have been generated that provide us a new way to solve above problems of hydrological information science. No SQL database not only meets the needs of the high read and write, but also has high availability and scalability. It is more emphasis on efficiently storage of big data compared with traditional relational database. This master thesis builds a cloud storage experiment environment based on Mongo DB database. Besides, an open source software framework called MEAN is introduced to develop a web application. All of our works are to resolve a series of problems about storing and accessing of spatial-temporal data. The main work of this master thesis as follows:(1) This master thesis built a cloud storage experiment environment by combing the replication sets of Mongo DB approach with sharding of Mongo DB approach..(2) This master thesis explored to use the ODM database model(made by the Consortium of University for the Advancement of Hydrologic Science. Inc.) to store hydrological observation data of Heihe river basin in cloud storage environment.(3) Compared to traditional relational database, a new approach was to try by using Geo JSON encoding format file to store spatial data of Heihe river basin in cloud storage environment.(4) In this master thesis, I conducted an intensive research and analysis on a full stack development framework MEAN which includes four major components: Mongo DB、Express、Angular JS and Node.js, and summarized its superiority and innovation of MEAN in front-end Web development. And then, a spatial-temporal storage web application was designed and developed. This web application is very useful that provide a data basis for researching and analyzing social and economic sustainable development. It also can provide helps to local government in decision-making for alleviating the risk of the shortage of water resource.