Sentinels Earth Observation ProjectLearning Image Processing in Python with Sentinels imagery
The main goal of this project is to create a set of interactive tutorials to teach people how to use data gathered from Copernicus/Sentinel’s Earth observation satellites. This data is stored in public ESA servers so everyone could access from everywhere and for free!
For the tutorials we’ll be using Jupyter Notebooks, that can serve as training material focused on the image processing techniques implemented in Python. In particular we have chosen to work on the open access data available from the Copernicus/Esa Sentinels missions, exploiting the ESA official open source toolbox, called SNAP.
- Installing SNAP Toolbox and configuring the Python module snappy 100% 100%
- ESA EO Open Science 2016 Presentation (Poster Session) 100% 100%
- Repository and SNAP basic tutorials creation 0% 0%
- Creating a set of SNAP advanced tutorials 0% 0%
For Python support or any technical problem about the Jupyter Notebooks, contact us at email@example.com
Taking part to this project for TFS is surely a great opportunity to get even more skilled about my field of study, but the main challenging point is to create something that can be shared and exploited by everyone who is interested in Earth Observation, but have not the required knowledge to go into it. Science for everyone is the goal!
Antonio is currently leading the technical development of the project because of his specialization in remote sensing engineering. He is the coauthor of the SNAP-Python proposal,together with an ESRIN Young Graduate Trainee, Laure Boudinaud, for the ESA EO Open Science Conference 2016. Twitter @tonyveco
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