Abstract
With the rapid development of big data, numerous industries have turned their focus from information research and construction to big data technologies. Earth science and geographic information systems industries are highly information-intensive, and thus there is an urgent need to study and integrate big data technologies to improve their level of information. However, there is a large gap between existing big data and traditional geographic information technologies. Owing to certain characteristics, it is difficult to quickly and easily apply big data to geographic information technologies. Through the research, development, and application practices achieved in recent years, we have gradually developed a common geospatial big data solution. Based on the formation of a set of geospatial big data frameworks, a complete geospatial big data platform system called BiGeo was developed. Through the management and analysis of massive amounts of spatial data from Sichuan Province, China, the basic framework of this platform can be better utilized to meet our needs. This paper summarizes the design, implementation, and experimental experience of BiGeo, which provides a new type of solution to the research and construction of geospatial big data.
Highlights
Sichuan Province, China has a total area of 486,000 square kilometers with 18 prefecture-level cities and three autonomous prefectures, including 54 municipal districts, 17 county-level cities, 108 counties, and four autonomous counties
After many years of development, geographic information science has accumulated a large number of storage organization models [15,16,17], visualization schemes [18,19], spatial analysis and statistical algorithms [10,20,21], service publishing technologies [22,23,24], and data integration and migration standards [25,26,27] for spatial data
ArcGIS: ArcGIS GeoAnalytics Server applies distributed computing based on vector-based feature data [31,32]
Summary
Sichuan Province, China has a total area of 486,000 square kilometers with 18 prefecture-level cities and three autonomous prefectures, including 54 municipal districts, 17 county-level cities, 108 counties, and four autonomous counties. After many years of development, geographic information science has accumulated a large number of storage organization models [15,16,17], visualization schemes [18,19], spatial analysis and statistical algorithms [10,20,21], service publishing technologies [22,23,24], and data integration and migration standards [25,26,27] for spatial data These technologies all face the problem of a distributed transformation in a big data environment. It is possible to provide a geospatial big data custom application system for the SaaS layer through the basic frameworks and components
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