<p><b>Learn basic Python programming to create functional and effective visualizations from earth observation satellite data sets</b></p> <p>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.</p> <p><i>Earth Observation Using Python: A Practical Programming Guide </i>presents an example-driven collection of basic methods, applications, and visualizations to process satellite data sets for Earth science research.</p> <ul> <li>Gain Python fluency using real data and case studies</li> <li>Read and write common scientific data formats, like netCDF, HDF, and GRIB2</li> <li>Create 3-dimensional maps of dust, fire, vegetation indices and more</li> <li>Learn to adjust satellite imagery resolution, apply quality control, and handle big files</li> <li>Develop useful workflows and learn to share code using version control</li> <li>Acquire skills using online interactive code available for all examples in the book</li> </ul> <p>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.<br /><br />Find out more about this book from this <a href=”https://eos.org/editors-vox/a-new-practical-guide-to-using-python-for-earth-observation”>Q&A with the Author</a> </p>
