Thousands of satellite datasets are freely available online, but scientists need the right tools to efficiently analyze data and share results. Python has easy-to-learn syntax and thousands of libraries to perform common Earth science programming tasks.

Earth Observation Using Python: A Practical Programming Guide presents an example-driven collection of basic methods, applications, and visualizations to process satellite data sets for Earth science research.

Gain Python fluency using real data and case studies
Read and write common scientific data formats, like netCDF, HDF, and GRIB2
Create 3-dimensional maps of dust, fire, vegetation indices and more
Learn to adjust satellite imagery resolution, apply quality control, and handle big files
Develop useful workflows and learn to share code using version control
Acquire skills using online interactive code available for all examples in the book

The American Geophysical Union promotes discovery in Earth and space science for the benefit of humanity. Its publications disseminate scientific knowledge and provide resources for researchers, students, and professionals.

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About the Author

Rebekah Bradley Esmaili, Atmospheric Scientist, Science and Technology Corp. (STC) and NOAA/JPSS, University of Maryland, USA.

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