A collection of Jupyter Notebooks for Google Earth Engine Python API.

Note: If you are interested in more tutorials or code snippets for Google Earth Engine Python API, feel free to write me an email to [email protected].

Classification Example for Landsat 8 including several vegetation indices and object feature extraction. Eventually you can't access the training data. In case you are interested in the training data, feel free to contact me.

Tasseled Cap Transformation for Landsat 8 TOA imagery based on the scientfic work "Derivation of a tasselled cap transformation based on Landsat 8 at-satellite reflectance" by M.Baigab, L.Zhang, T.Shuai & Q.Tong (2014).

Display Proba-V NDVI (Normalized Difference Vegetation Index) Imagery.

Display Proba-V NDVI Time-Series using Pandas and Matplotlib.

Basic Proba-V NDVI Time-Series Analysis, including auto correlation, fast fourier transformation and outlier detection.

Basic Proba-V NDVI Time-Series Prediction, using Fourier extrapolation and ARIMA model.

Linear regression on Proba-V, Landsat and Climate Hazards Group InfraRed Precipitation (CHRIPS) data. This tutorial demonstrates the comparison of one of the most common supervised machine learning methods, the linear regression. We are going to compare scikit-learn and Statsmodels. For more information about types of Machine Learning, check this link.