This is the full-length screencast to the hands-on exercise provided in the MOOC 'Beyond the Visible – Imaging Spectroscopy for Agricultural Applications'! Please find more information on the MOOC registration and software installation below and refer to the course for details on data download. This screencast provides the uncut version of the tutorial (that is also available in four separate parts in the screencasts Agri-09 to Agri-12), in which the colleagues of the LMU Munich will show you step by step how to get acquainted with the data and produce a training database, how to train a machine learning algorithm, retrieve quantitative information and lastly, how to validate your results.

Note: You might find that your results differ from Tobi’s. Don’t worry, that’s normal and we can explain why: On the one hand, this is due to the fact that while the training database (the LUT file) is compiled according to the same statistical criteria, the dice are rolled anew each time you run the tool and the resulting training database can be very different, despite identical parameterization. Another deviation can happen when training the model, because the ANN does not necessarily pick the same data out of the training dataset each time. And finally, numerical uncertainties can occur when inverting the ANN (though they should be rather small in comparison).

Check out our other tutorials on Youtube and get to know the **free** EnMAP-Box software:
Basic-22: Hands-on training: EnMAP-Box Installation: [ Ссылка ]
Basic-23: Hands-on training: EnMAP-Box Intro:
[ Ссылка ]

**** FREE ONLINE COURSE ****
'Beyond the Visible – Imaging Spectroscopy for Agricultural Applications' is an advanced short course on Hyperspectral Remote Sensing particularly for agricultural applications and is presented by HYPERedu and EO-College.

OPEN FROM 12 DECEMBER 2022, 08:00 GMT

Register now: [ Ссылка ]

Building on the fundamentals covered in the Basic MOOC ‚Beyond the Visible – Introduction to Hyperspectral Remote Sensing’, this course teaches the application of imaging spectroscopy in an agricultural context. Participants are introduced to the physicochemical basics of leaf and canopy reflectance, biophysical and biochemical variables known as 'vegetation traits', various data sources, specific methods commonly used in agricultural applications and open-source software to process imaging spectroscopy data, all while comprising several hands-on training exercises.
The course was developed by GFZ Potsdam and LMU Munich as part of the HYPERedu initiative. The development was funded within the EnMAP science program under the German Space Agency at DLR with resources from the German Federal Ministry of Economic Affairs and Climate Action.

**** For FURTHER INFORMATION we recommend ****
Introduction to the EnMAP-Box
• General information on the EnMAP-Box, a free and open source python plugin for QGIS: [ Ссылка ]
• Download, documentation and tutorials of and with the EnMAP-Box: [ Ссылка ]
EnMAP-Box Agricultural Apps
• General information on the “Agricultural Apps” toolbox and guidance on how to apply the individual tool: [ Ссылка ]

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