A Multispectral-Oriented Semantic Computing System applied to Agriculture and Ocean Analysis

This research presents a multispectral-oriented semantic computing system for environmental changes and detection with a new method to integrate two different semantic spaces for realizing deep semantic interpretation. Three significant approaches are introduced for realizing (1) a multispectral image space for semantic computing analysis, (2) dictionary creation for deep environment interpretation (coral reef analysis), and (3) space integration between multispectral image (colour) space and physical parameters (sea-water and land quality) space applied to agriculture and ocean analysis. We clarify the feasibility and effectiveness of our method and system by showing several experimental results on agriculture and ocean condition interpretation.