Python is a modern programming language, useful for reading Earth-observing satellite datasets, which can be challenging to use due to the volume of information that results from the multitude of sensors, platforms, and spatio-temporal spacing. This study is an attempt with making satellite data and analysis accessible to the Earth science community through practical examples using real-world datasets. Python for Remote Sensing Applications in Earth Science: A Practical Programming Guide introduces the basics of Python to interpret satellite datasets. This interdisciplinary and applied volume provides an in-depth analysis on specific topics aiming to identify routines for cleaning datasets prior to analysis.
Volume highlights include:
- Description of data conventions, common methods, and problem-solving skills required to work with satellite datasets
- Utilization of satellite data in research and professional work by sharing tools to address community needs
- Reviewing a variety of self-describing binary datasets that these observations are often encoded in
- Documentation and distribution of the code which can improve efficiency and transparency within the community
- A working knowledge of the field, with enough detail to make informed decisions about the usefulness and meaning of analytical results