Recently, the monograph titled "Generation and Application of Ocean Remote Sensing Big Data Information" authored by Research Fellow Hao Zengzhou and colleagues from our institute has been officially published and released by Science Press, and included in the series "Ocean Remote Sensing and Ocean Big Data".
This specialized work thoroughly synthesizes the research achievements of the author team in recent years related to the generation and analysis of ocean remote sensing big data information. The book consists of 8 chapters, delving into the essence and characteristics of ocean remote sensing big data, providing detailed explanations of the technology for generating ocean remote sensing big data information, systematically elucidating the understanding of spatial-temporal characteristics of marine environmental elements, information mining of element correlations, cognitive understanding of marine phenomena, applications in marine disasters and marine forecasting using ocean remote sensing big data. Additionally, the book analyzes the development prospects of ocean remote sensing big data management and application technologies, with implications for promoting and referencing China's work on ocean big data and marine environmental security.
Against the backdrop of rapid development in ocean information, the ocean sector has entered the era of big data, where ocean remote sensing, as a "vast information machine" within ocean big data, has become a crucial pillar. Facing remote sensing detection from multiple platforms such as aerial, near-space, polar orbit, and geostationary orbit, the information generation of ocean remote sensing big data based on satellite remote sensing is critically important for understanding various marine environments obtained through high spatial, temporal, and spectral remote sensing detections.
This book for the first time bridges diverse and heterogeneous ocean remote sensing products into the information generation of ocean remote sensing big data, illustrating the information generation technologies of four typical marine environmental elements: surface chlorophyll concentration, significant wave height, sea surface wind field, and sea surface temperature. Through ocean remote sensing big data, it aims to understand spatial-temporal characteristics of marine environmental elements in different sea areas, analyze element correlations, perform information mining, comprehend marine phenomena, and apply them in marine disaster and marine forecasting, thereby providing technical support for the marine environmental security system in terms of remote sensing data generation, information mining, and analysis applications.
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