Welcome to the Use Data for Earth and Environmental Science in Open Source Python Textbook!
About the Use Data for Earth and Environmental Science in Open Source Python Textbook
Use Data for Earth and Environmental Science in Open Source Python is an intermediate and multidisciplinary online textbook that addresses major questions in Earth science and teaches students to use the analytical tools necessary to undertake exploration of heterogeneous “big” scientific data.
This textbook assumes that readers have reviewed the Introduction to Earth Data Science textbook or are familiar with the Python programming language, Jupyter Notebook, and git/GitHub.
This textbook is designed for the Earth Analytics Python course for the Earth Data Analytics Professional Certificate taught by instructors at CU Boulder.
In this textbook, you will learn computationally intensive techniques to address scientific questions using a suite of different types of publicly available data including:
- Satellite and airborne lidar and spectral remote sensing data,
- Data collected using distributed in situ (on the ground) sensor networks
- Social media data, and
- Basic demographic data.
This textbook is highly technical, and each chapter covers some aspect of scientific programming with Python and open reproducible science workflows.
|Section 1. Time Series Data in Python|
|Chapter 1 : Time Series Data in Pandas|
|Chapter 1.5 : Flood Returns Period Analysis in Python|
|Section 2. Intro to Spatial Vector Data in Python|
|Chapter 2 : Spatial Data in Python|
|Chapter 3 : Processing Spatial Vector Data in Python|
|Section 3. Introduction to Raster Data in Python|
|Chapter 4 : Intro to Raster Data in Python|
|Chapter 5 : Processing Raster Data in Python|
|Section 5. Multispectral Remote Sensing Data in Python|
|Chapter 7 : Intro to Multispectral Remote Sensing Data|
|Chapter 8 : NAIP|
|Chapter 9 : Landsat Data|
|Chapter 10 : MODIS Data|
|Chapter 11 : Calculate Vegetation Indices in Python|
|Section 7. Introduction to API Data Access in Open Source Python|
|Chapter 15 : APIs|
|Chapter 16 : Twitter Data|