Application of Multi-Source Data Fusion Based on GIS Platform
Dapeng Zhang, G.S. Cai, Jiqiang Chen · 2024
This paper proposes a multi-source data fusion algorithm based on the Dempster-Shafer (D-S) evidence theory, which aims to realize the fusion and processing of uncertain data through the geographic information system (GIS) platform. This algorithm aims at the uncertainty problem of different data sources in the collection and processing process, and combines spatial analysis methods to improve the interpretation accuracy of geographic information. This paper uses this theory to design a fusion model specifically for solving the uncertainty problem between multi-source heterogeneous data. By combining and reasoning evidence of geographic data from different sources, the algorithm can analyze the relationship between data sources from multiple dimensions and perform more accurate spatial reasoning. This paper introduces a processing mechanism for uncertain data, so that the algorithm can adapt to various complex geographical environments and data conditions. The experimental results show that the algorithm significantly improves the accuracy of data fusion in practical applications, reduces the misjudgment rate by about 12%, and significantly improves the reliability of spatial analysis.