Earth Observation Using Python - (Special Publications) 2nd Edition by Rebekah B Esmaili (Hardcover)

Book Synopsis

Python is a popular programming language among geoscientists because it is open source, easy to learn, and capable of analyzing publicly accessible datasets. Knowing how to overcome coding and data visualization obstacles in remote sensing can increase research productivity, shareability, and reproducibility.

Earth Observation Using Python: A Practical Programming Guide, Second Edition is a hands-on workbook for all career levels that applies Python programming techniques to satellite datasets. Step-by-step exercises for various Earth science domains are presented in each section.

Volume highlights include:

• Practical tutorials using recent real-world NASA, NOAA, JAXA, and EUMETSAT remote sensing datasets
• Curated list of go-to libraries useful for scientific computing, analytics, data visualization, mapping, and machine learning
• Data conventions, methods, and problem-solving skills for reading and writing scientific data formats
• Visualization and analysis skills to create publication-ready plots, from simple scatter to complex geolocated imagery
• How machine learning and cloud computing can support programming with Python
• Effective practices for organizing and sharing code with the scientific community

From the Back Cover

Python is a popular programming language among geoscientists because it is open source, easy to learn, and capable of analyzing publicly accessible datasets. Knowing how to overcome coding and data visualization obstacles in remote sensing can increase research productivity, shareability, and reproducibility.

Earth Observation Using Python: A Practical Programming Guide, Second Edition is a hands-on workbook for all career levels that applies Python programming techniques to satellite datasets. Step-by-step exercises for various Earth science domains are presented in each section.

Volume highlights include:

• Practical tutorials using recent real-world NASA, NOAA, JAXA, and EUMETSAT remote sensing datasets
• Curated list of go-to libraries useful for scientific computing, analytics, data visualization, mapping, and machine learning
• Data conventions, methods, and problem-solving skills for reading and writing scientific data formats
• Visualization and analysis skills to create publication-ready plots, from simple scatter to complex geolocated imagery
• How machine learning and cloud computing can support programming with Python
• Effective practices for organizing and sharing code with the scientific community

About the Author

Rebekah B. Esmaili, PhD, Physical Scientist, Maryland, USA