The Study On The Quality Evaluation Of Basic Geographic Vector Data

Data is the blood of GIS, and as a decision-making system of spatial relation, the fundamental task of GIS is to analyze and manage data, derivate and abstract spatial information. The vector data especially is an important representation of fundamental spatial data, the quality of data has decisive function in analyzing and decision-making. So accuracy analysis and quality evaluation of data in GIS is of scientific and practical importance.This paper introduces the present advances of quality evaluation in the basic geographic vector data. Meanwhile, we analyze the various factors that influence the quality of basic geographic vector data, and discuss quality model and quality evaluation methods. Finally, quality evaluation methods are yalidated.The main contents are expatiated as follows:(1) On the basis of collecting and analyzing data based on literature extensively, we have studied the quality element of basic geographic vector data quality. The quality element of data is the basic characteristics of products to satisfy user requirements and use of purpose. So, we have researched that what elements of data quality are capable of being used to describe the quality information of basic geographic vector data.(2) The various factors, affecting the quality of basic geographic vector data, are analyzed. As far as the characteristics and use of basic geographic vector data are concerned, we have discussed the source of data errors.(3) The study of quality model on the basic geographic vector data. We have analyzed the test content of quality elements in the quality model, have researched and proposed the model of quality evaluation. Meanwhile, we have established a level of quality elements, quality elements 2 and corresponding weights about DLG quality model.(4) Through reading and analyzing the massive material literature data, the present methods of data quality evaluation are discussed.(5) The verification of data quality evaluation model. The selected data quality evaluation method and model is verified in practice.