RESEARCH ON NATURAL RESOURCES SPATIO-TEMPORAL BIG DATA ANALYSIS PLATFORM FOR HIGH PERFORMANCE COMPUTING
Keywords: Natural Resources, Cloud Architecture, Spatial-temporal Big Data, Platform Framework, Spatial Analysis, High Performance Computing
Abstract. In the era of earth observation big data, a new paradigm for the unified management of natural resource conservation and utilization has been established in China. The current focus of natural resources monitoring is on fully leveraging the value of big data in geospatial and temporal dimensions to support new work on natural resources management. An overall framework for a spatial-temporal big data analysis platform is proposed in this paper, which explores innovative technologies such as heterogeneous cloud collaborative services, business capabilities, data resources, and open sharing. Utilizing private cloud computing resources, the platform establishes collaborative services for storage cloud, computing cloud, and database cloud, demonstrating its ability to perform large-scale online computation of spatial-temporal data. Mainstream spatial data analysis computing methods such as vector computing, grid computing, and other grid computing methods are also established, and an open service model for interdisciplinary applications is explored. The feasibility of the proposed platform is verified using nationwide land cover data of 260 million surface area classifications, indicating its great potential for application.