About this book:

"Eyes in the Sky, Eyes on the Sea: Satellite Remote Sensing for Oceanography" by Richard J. Greatbatch serves as an applied introduction to leveraging satellite data for marine science and resource management. The book comprehensively covers the fundamentals of satellite remote sensing, starting with the basic physics of orbits, sensors, and radiative transfer that underpin how satellites observe the ocean. It details practical aspects such as accessing and processing various satellite data formats (NetCDF/HDF), managing metadata, and performing crucial preprocessing steps like reprojection, gridding, and atmospheric correction over water. The author emphasizes moving from theoretical understanding to practical application, providing code examples in Python and R, and exploring cloud-based platforms for scalable analysis.

The core of the book delves into specific applications of satellite remote sensing across diverse oceanographic variables. Chapters are dedicated to ocean color (chlorophyll, turbidity, CDOM, and water quality indicators), sea surface temperature (thermal and microwave methods), sea surface height and altimetry (geodesy, tides, and mean sea level), and the derivation of waves and currents. Specialized applications further illustrate the utility of these techniques, including monitoring sea ice, detecting coastal change, identifying harmful algal blooms, informing fisheries and ecosystem management, tracking oil spills and marine pollution, mapping marine debris and Sargassum, and charting bathymetry and benthic habitats. Each application highlights the unique strengths and limitations of different satellite sensors and the necessity of validation against in situ observations.

A significant portion of the text addresses advanced analytical techniques crucial for drawing meaningful conclusions from satellite data. This includes building and analyzing time series, identifying anomalies, and constructing climatologies to understand long-term trends and seasonal variability. The book also explores sensor fusion and data assimilation, explaining how combining data from multiple sources and integrating them with numerical models can create a more comprehensive and predictive understanding of ocean dynamics. Finally, it examines the growing role of machine learning in processing and interpreting satellite data, and discusses the critical transition from scientific analysis to actionable decision support, stressing ethical considerations, data transparency, and the future outlook for satellite oceanography.