Spatial Data Quality Control And Evaluation Research

Along with the continuously advancing of surveying and mapping technology and growing larger of spatial database, spatial data has developed into the blood of GIS, its quality will have significant influence on the data exchange, sharing and use, but also will directly impact on the accuracy and reliability of GIS application, analysis, decision-making. Therefore the masses of users pay more and more attention to the spatial data quality, how to carry on the effective quality control, and carry on the comprehensive and scientific measurement and evaluation is becoming more and more important. This article begins with the uncertainty of spatial data which exists of itself, focus on the fuzzy uncertainty, introduces some of the theory of fuzzy mathematics and makes some discussion and research on spatial data quality control, evaluation and reliability analysis. The main contents and results are expatiated of this paper as follows:1. Introduces the significance of spatial data quality control, evaluation and reliability analysis, Describes the research trend and present situation on this topic at domestic and foreign, and summarizes some disadvantages and problems need to be solved, existed in the research achievements at present,finally summarizes the overall frame structure of this paper.2. Discusses the random uncertainties and fuzzy uncertainty existed in the spatial data and their sources, detailed introduces the quality elements effected spatial data quality, and combined with the related practical projects, summarizes the main contents and methods of spatial data quality control.3. Summarizes the traditional quality evaluation method for spatial data, according to the fuzzy uncertainty, the traditional quality evaluation method has many shortcomings and cannot make a full and reasonable evaluations on them, so this paper unified the related references, proposes the theory and model about the multi-level fuzzy comprehensive evaluation method, dealing with the random and fuzzy uncertainty existed in spatial data itself at the same time. However, the research about this method is little in spatial data field at present, combining the problems in practical applications, this paper summarizes the problems needed to solve in future research.4. according to the fuzzy uncertainty existed in spatial data, this paper also proposed the theory and model about the fuzzy fault tree method, combining the problems in practical applications, this paper summarizes the problems needed to solve in future research.