Inside the notebook environment (notebooks.vgt.vito.be), these samples can be found under ~/Private/notebook-samples. You may want to run 'git pull' inside this directory to get the latest versions.
Quick start sample
Finds PROBA-V products and computes a histogram using the processing cluster.
Keywords: catalog query, Spark, Python, histogram, matplotlib
R quick start
Users of the R programming language can use this sample to get started quickly with finding and reading PROBA-V data from inside their notebook or VM.
Keywords: catalog query, raster, R
Time series analysis (cal/val)
Uses MEP web services to retrieve time series from various products for a given point coordinate.
Keywords: Time series, REST, WCS, calibration, validation
Create time lapses using our data client library!
Keywords: Time series, Time lapse, Sentinel 2, Proba-V
Trains a machine learning classifier to classify snow pixels based on PROBA-V radiometry.
Keywords: Spark, Machine learning, Python, Seaborn, graphs, plotting
Takes all timeseries from the time series viewer application, and runs a naïve trend detection algorithm on them using Spark. This simple approach gives some nice results.
Keywords: SparkSQL, time series, Python, plotting, maps, pandas
BioPhysical parameters with Sentinel Toolbox Python bindings
Computes BioPhysical parameters using Sentinel 2 reflectance data.
Nice demonstration on how snappy can be used and configured inside a notebook, and how it integrates with Python libraries.
Keywords: Python, Snappy, BioPhysical parameters, Sentinel-2, plotting, numpy