I am working on predicting some parameters in soil using visible-near infrared reflectance data. My question is 'What is the minimum number of soil samples and their corresponding reflectance data required for generating a prediction model using ANN machine learning algorithm?'.
That's difficult to answer! How many parameters? How many wavelength channels do your data have? What is the variability? Are you using satellite or ground data? Etc.
@koen Van de Moortel
Thank you so much for answering.
I use ground-based sensor (hyperspectral data) to predict soil pH for example.
It would surprise me if you can pH from spectral data, but it sounds interesting. Could you share some data? I could try and test some models with my software, see: www.lerenisplezant.be/fitting.htm
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