Quality Evaluation And Optimization Of Water Level Data For Typical Lakes In China Based On Big Spatial Data

With the rapid development of "3S" technology,data haves gradually become a major component of national basic strategic construction.The application of spatial big data in various fields is also becoming more and more extensive and deeper.Spatial big data haves the characteristics of huge data scale,complex data associations,diverse types,and high timeliness.However,the quality of spatial data is unsatisfactory due to the various uncertain factors in the process of collecting,processing and disseminating the spatial data.How to effectively control the quality of spatial big data and improve the availability of existing spatial data as much as possible are currently important research topics.Lake water level is an important feature of lakes,and long-term water level sequences are of great significance for studying regional environmental climate and other changes.Satellite radar altimeters can provide altimetry data for water areas lacking hydrological stations,fill in the data gaps in existing measurement records,and eventually form lake water level data products.For a specific lake or reservoir,different water level data products are generated by using different altimeters,data processing methods and correction methods.Consequently,the altimeter water level products provided to end users are also different.In this paper,four open-share water level products(Hydroweb database,GRLM database,DAHITI database,and multi-source radar altimeter global lake water level change datasets)were used for comparative analysis in Poyang Lake and Qinghai Lake.The altimeter water level data product,the Poyang Lake water level / hydrological station measured water level from 2005 to 2015 and the Qinghai Lake water level / hydrological station measured water level from 2001 to 2019 were also used to perform mean value correction,root mean square error(RMSE),and consistency check,The validation results show that DAHITI water level data products have better reliability than the other three types of water level data.Finally,through data cleaning,optimization and fusion,the time series of water level with wider time span and higher precision in the research area of Poyang Lake and Qinghai Lake were derived,which provides a more powerful basis for the end-users to analyze the water level changes for a longer time.The main research contents of this paper include as the follows:(1)This paper discusses the development and current situation of spatial data quality evaluation,analyzes the definition and basic characteristics of spatial data quality,discusses the uncertainties affecting the quality of spatial data and the quality control of spatial data.(2)Develop a method for evaluating the quality of spatial data for lake water level data.According to the spatial data quality evaluation method and the spatial data quality measurement model,the spatial data quality evaluation system is summarized,and the water level data product quality evaluation system model is summarized by the example.(3)The principle of satellite altimeter height measurement is discussed,and the water level products of the four global water hydrological databases used in the paper are introduced.(4)Using the proposed spatial data quality evaluation methods,the four water level data products of typical lakes in China,Poyang Lake and Qinghai Lake,were verified for accuracy and data cleaning.Finally,the water level time series of the same lake is optimized through data filter and data fusion,which widens the time range of the original water level time series,improves the availability of the original water level products,and makes it more convenient for end-users' s choice and application.