whigg/automation-of-bulk-preprocessing-of-sentinel-images-using-snap-graph-processing-tool

Automation-of-Bulk-Preprocessing-of-Sentinel-Images-using-SNAP-Graph-Processing-Tool

This Jupyter Notebook automates the preprocessing of Sentinel-2 images through Graph Processing Tool (GPT) using the XML file saved from the Sentinel Application Platform's (SNAP's) Graph Builder tool. This allows to take advantage of the batch proessing option available in SNAP GPT. Here, the specific processing chain was defined (Figure 1) and the defined chain was applied can be applied to several images in an automatic way (In this Notebook, two Sentinel-2 images are used. However, this approach can be applied to several Sentinel-2 and/or Sentinel-1 images). This method allows reducing processin time and storage requirement since no intermediate steps outputs are created and stored. Only the final product is physically saved. The Notebook uses the resources from Mac's Terminal and Python library. This Notebook is prepared based on the NASA ARSET's training "Agricultural Crop Classification with Synthetic Aperture Radar and Optical Remote Sensing".

Remember: To run this Notebook, first the SNAP software should be downloaded and installed (http://step.esa.int/main/download/snap-download/).