Building Datacube for Maritime Applications on Discrete Global Grid System

Geospatial analysis often requires heterogeneous datasets of large volume or coverage which are not well suited to traditional data structures. Data cubes built upon Discrete Global Grid Systems (DGGS) seems to be an efficient way to manage big geospatial data. DGGS provide a uniform multiresolution spatial reference system and an efficient framework for building data cubes. The latter enables users to structure various data and provides analysis ready data for data processing, machine learning and visualization. In this study we introduce the methodology of data cube creation for marine research in Russian Arctic seas with H3 DGGS package and PostgreSQL using the R package “sf’ and Python module for H3 “h3-py”. Our experience is useful for organization and conducting large-regional geospatial analysis. Further work is identified to expand and develop methods of marine data cubes analysis.