Research on Multiple Big Data Fusion Techniques in Geographic Information System (GIS)

Abstract

Geographic Information System (GIS) has many different types of data sources, and realizing the fusion of heterogeneous data from multiple sources can enhance the application areas of GIS. This paper establishes a geographic information system based on C/S and B/S modes, and designs a database storage module and a fusion mechanism for multi-source data. Multiview image preprocessing technology is used to optimize the UAV tilt measurement image, the light component of the geographic information image is accurately and quickly extracted by fast guided filtering algorithm, and linear stretching is introduced to image enhancement of remote sensing data. Then, combining the SIFT algorithm to align the features of the geographic information image and fusing the remote sensing image and the UAV image by using the IHS transform, the fusion processing flow of multi-source heterogeneous data is designed. For the effectiveness of the fusion of multi-source big data, it is verified from the alignment of geographic information images and the fusion of multi-source heterogeneous data, respectively. It is found that the time consumption of SIFT algorithm in geographic information image alignment is only 1.241s, and the accuracy of image feature point matching is 88.44%.The CC and EN values of IHS data fusion are 0.924 and 7.652 respectively, and the modeling error of geographic information 3D model is between [0.01m,0.07m]. Through the effective fusion of multi-source big data, the three-dimensional display of geographic information by GIS system can be realized to provide support for geographic information exploration