Storage and Analysis of Remote Sensing Data

The optimal method of storing remote sensing data for use in training artificial intelligence is considered. Various data storage systems—including relational and nonrelational databases—are analyzed in terms of their applicability to the analysis of the large quantities of remote sensing data in the Kurkinsky district of Tula region. Attention focuses on the normalization and productivity of relational systems and the benefits of nonrelational systems, especially MongoDB, for Big Data analysis. The importance of selecting the appropriate data storage system for effective training of artificial intelligence is emphasized.